{"type":"status","state":"running"} {"type":"user_prompt","text":"peux tu corriger les bug dans le engine de geocode , pcq regarde ici regarde cette annonce https://www.immo-ka.com/propriete/duproprio%3A1126225/4671-rue-des-perdrix-jonquiere-lac-kenogami est localise a saint augustin alors querl est au saguenay nom de rue proche maios pas pentoute la meme chose opeux tu faire geocode plus rigoureux","ts":1787663437505} {"type":"claude","event":{"type":"system","subtype":"init","cwd":"/Users/simon-pierreboucher/apps/immo-ka","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","tools":["Task","AskUserQuestion","Bash","CronCreate","CronDelete","CronList","Edit","EnterPlanMode","EnterWorktree","ExitPlanMode","ExitWorktree","Glob","Grep","Monitor","NotebookEdit","PushNotification","Read","RemoteTrigger","ScheduleWakeup","Skill","TaskOutput","TaskStop","TodoWrite","ToolSearch","WebFetch","WebSearch","Write"],"mcp_servers":[],"model":"claude-fable-5","permissionMode":"bypassPermissions","slash_commands":["update-config","debug","simplify","batch","fewer-permission-prompts","loop","schedule","claude-api","clear","compact","context","cost","heapdump","init","review","security-review","insights","team-onboarding"],"apiKeySource":"ANTHROPIC_API_KEY","claude_code_version":"2.1.117","output_style":"default","agents":["Explore","general-purpose","Plan","statusline-setup"],"skills":["update-config","debug","simplify","batch","fewer-permission-prompts","loop","schedule","claude-api"],"plugins":[],"uuid":"9cd2929a-295f-4e07-beaf-e1b91aa122f8","memory_paths":{"auto":"/Users/simon-pierreboucher/.claude/projects/-Users-simon-pierreboucher-apps-immo-ka/memory/"},"fast_mode_state":"off"}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"33b5b61b-fcca-4713-8f3d-0636f3da184f","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXF7JPLDUPgzwnv4LB4","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":33940,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":33940,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"13eb26a5-8fe0-4d80-bf2d-ae98e6e8f69b"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXF7JPLDUPgzwnv4LB4","type":"message","role":"assistant","content":[{"type":"text","text":"Je vais examiner le moteur de géocodage et la fiche en question pour comprendre pourquoi elle atterrit à Saint-Augustin."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":33940,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":33940,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"f91084a2-a240-43bd-a9f3-2b37c8d9dfec"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXF7JPLDUPgzwnv4LB4","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","name":"Agent","input":{"description":"Trouver le moteur de géocodage","subagent_type":"Explore","prompt":"Dans le repo /Users/simon-pierreboucher/apps/immo-ka (app immobilière Node/JS), trouve le moteur de géocodage : le code qui transforme une adresse d'annonce en coordonnées lat/lng (probablement via Nominatim, Google, Mapbox, Photon ou autre). Thoroughness: medium.\n\nJe cherche à corriger un bug : l'annonce \"4671, rue des Perdrix, Jonquière (Lac-Kénogami)\" (source duproprio, uid duproprio:1126225) est géocodée à Saint-Augustin au lieu de Saguenay — le géocodeur a probablement matché une rue des Perdrix ailleurs sans valider la ville.\n\nRapporte :\n1. Le(s) fichier(s) + numéros de ligne du code de géocodage (construction de la requête, appel API, sélection du résultat, validation éventuelle).\n2. Comment l'adresse est construite (quels champs : rue, ville, région, code postal).\n3. Où les coordonnées sont stockées (colonne BD, table).\n4. S'il existe déjà une validation du résultat (bounding box, comparaison de ville, etc.).\n5. Comment le géocodage est déclenché (au sync ? script batch ? à la volée ?).\n\nRecherche aussi rapidement s'il y a un script/CLI pour re-géocoder des fiches existantes. Rapport concis avec chemins et lignes précises."},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":33940,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":33940,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"90e9186d-94d6-4514-ba1c-4d66955a4861"}} {"type":"claude","event":{"type":"system","subtype":"task_started","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Trouver le moteur de géocodage","task_type":"local_agent","prompt":"Dans le repo /Users/simon-pierreboucher/apps/immo-ka (app immobilière Node/JS), trouve le moteur de géocodage : le code qui transforme une adresse d'annonce en coordonnées lat/lng (probablement via Nominatim, Google, Mapbox, Photon ou autre). Thoroughness: medium.\n\nJe cherche à corriger un bug : l'annonce \"4671, rue des Perdrix, Jonquière (Lac-Kénogami)\" (source duproprio, uid duproprio:1126225) est géocodée à Saint-Augustin au lieu de Saguenay — le géocodeur a probablement matché une rue des Perdrix ailleurs sans valider la ville.\n\nRapporte :\n1. Le(s) fichier(s) + numéros de ligne du code de géocodage (construction de la requête, appel API, sélection du résultat, validation éventuelle).\n2. Comment l'adresse est construite (quels champs : rue, ville, région, code postal).\n3. Où les coordonnées sont stockées (colonne BD, table).\n4. S'il existe déjà une validation du résultat (bounding box, comparaison de ville, etc.).\n5. Comment le géocodage est déclenché (au sync ? script batch ? à la volée ?).\n\nRecherche aussi rapidement s'il y a un script/CLI pour re-géocoder des fiches existantes. Rapport concis avec chemins et lignes précises.","uuid":"75a084ae-aea9-433c-8f88-e41cecdde30c","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"type":"text","text":"Dans le repo /Users/simon-pierreboucher/apps/immo-ka (app immobilière Node/JS), trouve le moteur de géocodage : le code qui transforme une adresse d'annonce en coordonnées lat/lng (probablement via Nominatim, Google, Mapbox, Photon ou autre). Thoroughness: medium.\n\nJe cherche à corriger un bug : l'annonce \"4671, rue des Perdrix, Jonquière (Lac-Kénogami)\" (source duproprio, uid duproprio:1126225) est géocodée à Saint-Augustin au lieu de Saguenay — le géocodeur a probablement matché une rue des Perdrix ailleurs sans valider la ville.\n\nRapporte :\n1. Le(s) fichier(s) + numéros de ligne du code de géocodage (construction de la requête, appel API, sélection du résultat, validation éventuelle).\n2. Comment l'adresse est construite (quels champs : rue, ville, région, code postal).\n3. Où les coordonnées sont stockées (colonne BD, table).\n4. S'il existe déjà une validation du résultat (bounding box, comparaison de ville, etc.).\n5. Comment le géocodage est déclenché (au sync ? script batch ? à la volée ?).\n\nRecherche aussi rapidement s'il y a un script/CLI pour re-géocoder des fiches existantes. Rapport concis avec chemins et lignes précises."}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"9873fb58-fb74-4889-814d-5a30775b0ec0","timestamp":"2026-08-25T13:10:52.051Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Running find /Users/simon-pierreboucher/apps/immo-ka -typ…","usage":{"total_tokens":8495,"tool_uses":1,"duration_ms":1158},"last_tool_name":"Bash","uuid":"b41b5915-24b1-4764-b2f2-68792a86adcf","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXGAKV5D1Vw42TDKoSc","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01RB3eLUvnVJmzzu8xV5AJ6R","name":"Bash","input":{"command":"find /Users/simon-pierreboucher/apps/immo-ka -type f -name \"*.js\" -o -name \"*.ts\" -o -name \"*.json\" | head -30"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":8484,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":8484,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"108d60ef-84f8-46e6-9ac0-fbef78176166"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01RB3eLUvnVJmzzu8xV5AJ6R","type":"tool_result","content":"/Users/simon-pierreboucher/apps/immo-ka/frontend/dist/ka-agent.js\n/Users/simon-pierreboucher/apps/immo-ka/frontend/dist/assets/config-vx_oE7vA.js\n/Users/simon-pierreboucher/apps/immo-ka/frontend/dist/assets/index-CkwfzGSn.js\n/Users/simon-pierreboucher/apps/immo-ka/frontend/dist/assets/PropertyMap-441nQqpP.js\n/Users/simon-pierreboucher/apps/immo-ka/frontend/dist/assets/MapView-DQhnmJfg.js\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/jsesc/jsesc.js\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/jsesc/package.json\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/babel__template/package.json\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/babel__template/index.d.ts\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/react-dom/test-utils/index.d.ts\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/react-dom/server.d.ts\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/react-dom/canary.d.ts\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/react-dom/experimental.d.ts\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/react-dom/package.json\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/react-dom/index.d.ts\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/react-dom/client.d.ts\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/babel__generator/package.json\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/babel__generator/index.d.ts\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/babel__traverse/package.json\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/babel__traverse/index.d.ts\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/prop-types/package.json\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/prop-types/index.d.ts\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/estree/flow.d.ts\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/estree/package.json\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/estree/index.d.ts\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/babel__core/package.json\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/babel__core/index.d.ts\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/react/jsx-dev-runtime.d.ts\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/react/jsx-runtime.d.ts\n/Users/simon-pierreboucher/apps/immo-ka/frontend/node_modules/@types/react/canary.d.ts","is_error":false}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"10c4f2c8-9c0a-4d46-9bb7-52754ed59c49","timestamp":"2026-08-25T13:10:53.301Z"}} 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/Users/simon-pierreboucher/apps/immo-ka"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":5,"cache_creation_input_tokens":2066,"cache_read_input_tokens":8484,"cache_creation":{"ephemeral_5m_input_tokens":2066,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"9d1ba226-106d-457b-b2fa-fd0e7d41b678"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01AwuCqYSY42DobTCramhmLv","type":"tool_result","content":"total 168\ndrwxr-xr-x 21 simon-pierreboucher staff 672 Aug 24 19:10 .\ndrwxr-xr-x 6 simon-pierreboucher staff 192 Aug 18 18:39 ..\n-rw-r--r-- 1 simon-pierreboucher staff 14340 Aug 12 13:44 .DS_Store\ndrwxr-xr-x 3 simon-pierreboucher staff 96 Aug 12 11:10 .claude\n-rw------- 1 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{"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01VoFWxMQX3f7cisYY6jhtQY","type":"tool_result","content":"Found 16 files\nimmoka/connectors/agences_web.py\nscripts/build_inspecteurs.py\nscripts/build_demenageurs.py\nrun.py\nimmoka/ingest.py\nimmoka/hydro.py\nimmoka/commerces.py\nimmoka/db.py\nimmoka/connectors/_detailutil.py\nimmoka/connectors/agenceimage.py\nimmoka/connectors/bhhs_quebec.py\nimmoka/connectors/publimaison.py\nimmoka/connectors/charisma.py\nimmoka/auth.py\nimmoka/geocode.py\ngeocode.py"}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"7bf38e8c-9bf5-4bde-b8d8-85e530c4e06a","timestamp":"2026-08-25T13:10:57.164Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Finding 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{"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_012MukGhtbV1Acr8Zyw6gmhz","type":"tool_result","content":"1\t# -----------------------------------------------------------------------------\n2\t# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n3\t# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n4\t# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)\n5\t# - cache persistant (table geocode_cache) : une adresse n'est géocodée\n6\t# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce\n7\t# - politesse : 1 requête/seconde max, User-Agent identifiable\n8\t# - validation : les coordonnées doivent tomber dans la région attendue\n9\t# (bounding box par ville), sinon flag geocode_failed — jamais de\n10\t# coordonnées bidon\n11\t# -----------------------------------------------------------------------------\n12\tfrom __future__ import annotations\n13\t\n14\timport sqlite3\n15\t\n16\timport re\n17\timport time\n18\t\n19\timport requests\n20\t\n21\tfrom . import db\n22\tfrom .normalize import strip_accents\n23\t\n24\tNOMINATIM_URL = \"https://nominatim.openstreetmap.org/search\"\n25\t# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre\n26\t# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)\n27\tAQ_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n28\t \"Adresse_Geocodage/GeocodeServer/findAddressCandidates\")\n29\tAQ_MIN_SCORE = 75\n30\t# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête\n31\t# User-Agent contient des accents (latin-1)\n32\tUSER_AGENT = \"ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)\"\n33\tREQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s\n34\tREQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte\n35\tRETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours\n36\t\n37\t# Bounding boxes (lat_min, lat_max, lng_min, lng_max)\n38\t_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n39\t# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord\n40\t# et la Gaspésie (expansion provinciale) — même boîte que schema.finalize()\n41\t_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n42\t\n43\t_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n44\t \"l'ancienne-lorette\", \"ancienne-lorette\"}\n45\t\n46\t\n47\tdef _bbox_for(city: str) -> tuple[float, float, float, float]:\n48\t key = strip_accents((city or \"\").strip().lower())\n49\t return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n50\t\n51\t\n52\tdef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n53\t return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n54\t\n55\t\n56\tdef norm_key(address: str) -> str:\n57\t \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\"\n58\t s = strip_accents((address or \"\").lower())\n59\t s = re.sub(r\"\\b(?:app?t?|appartement|unite|suite|#)\\.?\\s*[\\w-]+\\b\", \" \", s)\n60\t s = re.sub(r\"[^a-z0-9]+\", \" \", s)\n61\t return re.sub(r\"\\s+\", \" \", s).strip()\n62\t\n63\t\n64\tclass Geocoder:\n65\t def __init__(self, con) -> None:\n66\t self.con = con\n67\t self.session = requests.Session()\n68\t self.session.headers[\"User-Agent\"] = USER_AGENT\n69\t self._last = 0.0\n70\t\n71\t @staticmethod\n72\t def _clean(address: str) -> str:\n73\t \"\"\"Nettoyages qui aident Nominatim sur les adresses québécoises.\"\"\"\n74\t s = address.strip()\n75\t # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique\n76\t s = re.sub(r\"^(\\d+)-(\\d+)\\s\", r\"\\2 \", s)\n77\t # « 6275 et 6375 boulevard X » -> premier civique\n78\t s = re.sub(r\"^(\\d+)\\s+et\\s+\\d+\\s\", r\"\\1 \", s)\n79\t # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu\n80\t s = re.sub(r\"montr[ée]al\\s*-\\s*\", \"\", s, flags=re.I)\n81\t # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau\n82\t s = re.sub(r\",?\\s*(?:bureau|suite|local|app\\.?|apt\\.?)\\s*[\\w-]+\\b\", \"\", s, flags=re.I)\n83\t # « Vanier (Québec) » -> « Vanier, Québec »\n84\t s = re.sub(r\"\\s*\\((qu[ée]bec)\\)\", r\", \\1\", s, flags=re.I)\n85\t # abréviations cardinales : « Rue Salaberry O » -> « Ouest »\n86\t s = re.sub(r\"\\bO\\.?(?=,|\\s*$)\", \"Ouest\", s)\n87\t s = re.sub(r\"\\bE\\.?(?=,|\\s*$)\", \"Est\", s)\n88\t return s\n89\t\n90\t def _build_query(self, address: str, city: str) -> str:\n91\t q = self._clean(address)\n92\t key = strip_accents(q.lower())\n93\t if city and strip_accents(city.lower()) not in key:\n94\t q += f\", {city}\"\n95\t if \"quebec\" not in strip_accents(q.lower()) and \"qc\" not in q.lower():\n96\t q += \", Québec\"\n97\t return q + \", Canada\"\n98\t\n99\t def _query_nominatim(self, params: dict) -> tuple[float, float] | None:\n100\t \"\"\"Une requête Nominatim, throttlée.\"\"\"\n101\t wait = REQUEST_DELAY - (time.time() - self._last)\n102\t if wait > 0:\n103\t time.sleep(wait)\n104\t try:\n105\t resp = self.session.get(NOMINATIM_URL, params={\n106\t \"format\": \"jsonv2\", \"limit\": 1, \"countrycodes\": \"ca\", **params,\n107\t }, timeout=20)\n108\t self._last = time.time()\n109\t resp.raise_for_status()\n110\t hits = resp.json()\n111\t except Exception:\n112\t self._last = time.time()\n113\t return None\n114\t if not hits:\n115\t return None\n116\t try:\n117\t return float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n118\t except (KeyError, ValueError):\n119\t return None\n120\t\n121\t def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] | None:\n122\t \"\"\"Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).\n123\t\n124\t Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE\n125\t pour éviter les correspondances approximatives sur une autre rue.\n126\t \"\"\"\n127\t premier = self._clean(address).split(\",\")[0].strip()\n128\t ville = (city or \"Québec\").strip()\n129\t wait = REQUEST_DELAY_AQ - (time.time() - self._last)\n130\t if wait > 0:\n131\t time.sleep(wait)\n132\t try:\n133\t resp = self.session.get(AQ_URL, params={\n134\t \"SingleLine\": f\"{premier}, {ville}\",\n135\t \"f\": \"json\", \"outSR\": 4326, \"maxLocations\": 1,\n136\t }, timeout=20)\n137\t self._last = time.time()\n138\t resp.raise_for_status()\n139\t cands = resp.json().get(\"candidates\") or []\n140\t except Exception:\n141\t self._last = time.time()\n142\t return None\n143\t if not cands or cands[0].get(\"score\", 0) < AQ_MIN_SCORE:\n144\t return None\n145\t loc = cands[0].get(\"location\") or {}\n146\t try:\n147\t return float(loc[\"y\"]), float(loc[\"x\"])\n148\t except (KeyError, ValueError):\n149\t return None\n150\t\n151\t def _attempts(self, address: str, city: str) -> list[dict]:\n152\t \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n153\t\n154\t 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n155\t 2) recherche libre complète\n156\t 3) structurée rue seule -> centroïde de rue (repli acceptable pour la\n157\t carte quand le numéro civique est absent d'OpenStreetMap)\n158\t \"\"\"\n159\t premier = self._clean(address).split(\",\")[0].strip()\n160\t ville = (city or \"\").strip()\n161\t if not ville:\n162\t k = strip_accents(address.lower())\n163\t ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n164\t commun = {\"city\": ville, \"state\": \"Québec\", \"country\": \"Canada\"}\n165\t\n166\t tries: list[dict] = []\n167\t m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n168\t if m:\n169\t tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n170\t tries.append({\"q\": self._build_query(address, city)})\n171\t if m:\n172\t tries.append({\"street\": m.group(2), **commun})\n173\t return tries\n174\t\n175\t def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n176\t \"\"\"Adresse -> (lat, lng), via cache puis Nominatim. None si introuvable.\"\"\"\n177\t key = norm_key(address)\n178\t if not key or len(key) < 6:\n179\t return None\n180\t row = self.con.execute(\n181\t \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n182\t (key,)).fetchone()\n183\t if row is not None:\n184\t if not row[\"failed\"]:\n185\t return (row[\"lat\"], row[\"lng\"])\n186\t if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n187\t return None # échec récent : ne pas marteler l'API\n188\t\n189\t bbox = _bbox_for(city)\n190\t coords = None\n191\t # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n192\t # limite stricte. Nominatim (1 req/s) seulement en repli.\n193\t provider = \"adresses_quebec\"\n194\t c = self._query_adresses_quebec(address, city)\n195\t if c is not None and _in_bbox(*c, bbox):\n196\t coords = c\n197\t if coords is None:\n198\t provider = \"nominatim\"\n199\t for params in self._attempts(address, city):\n200\t c = self._query_nominatim(params)\n201\t if c is not None and _in_bbox(*c, bbox):\n202\t coords = c\n203\t break\n204\t ok = coords is not None\n205\t self.con.execute(\n206\t \"INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)\"\n207\t \" VALUES (?,?,?,?,?,?)\"\n208\t \" ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,\"\n209\t \" lng=excluded.lng, provider=excluded.provider,\"\n210\t \" failed=excluded.failed, ts=excluded.ts\",\n211\t (key, coords[0] if ok else None, coords[1] if ok else None,\n212\t provider, 0 if ok else 1, time.time()))\n213\t self.con.commit()\n214\t return coords if ok else None\n215\t\n216\t\n217\tdef run(limit: int | None = None) -> dict:\n218\t \"\"\"Géocode les annonces actives sans coordonnées, par adresse unique.\n219\t\n220\t `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de\n221\t cache sont gratuits et toujours appliqués).\n222\t \"\"\"\n223\t con = db.connect()\n224\t geo = Geocoder(con)\n225\t rows = con.execute(\n226\t \"\"\"SELECT uid, address, city FROM listings\n227\t WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n228\t AND dup_hidden=0\n229\t ORDER BY address\"\"\").fetchall()\n230\t\n231\t # regrouper par immeuble (adresse normalisée)\n232\t groupes: dict[str, list] = {}\n233\t for r in rows:\n234\t groupes.setdefault(norm_key(r[\"address\"]), []).append(r)\n235\t\n236\t done = failed = requests_made = 0\n237\t for key, members in groupes.items():\n238\t if not key:\n239\t continue\n240\t cached = con.execute(\n241\t \"SELECT failed FROM geocode_cache WHERE address=?\", (key,)).fetchone()\n242\t if cached is None:\n243\t if limit is not None and requests_made >= limit:\n244\t continue\n245\t requests_made += 1\n246\t try:\n247\t coords = geo.resolve(members[0][\"address\"], members[0][\"city\"])\n248\t if coords:\n249\t for r in members:\n250\t con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n251\t (coords[0], coords[1], r[\"uid\"]))\n252\t done += len(members)\n253\t else:\n254\t # introuvable/hors zone : flag ; jamais de coordonnées bidon\n255\t for r in members:\n256\t con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\",\n257\t (r[\"uid\"],))\n258\t failed += len(members)\n259\t con.commit()\n260\t except sqlite3.OperationalError:\n261\t # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,\n262\t # elle sera reprise au prochain passage — jamais crasher tout le run.\n263\t try:\n264\t con.rollback()\n265\t except sqlite3.Error:\n266\t pass\n267\t time.sleep(1.0)\n268\t continue\n269\t\n270\t con.close()\n271\t stats = {\"geocoded\": done, \"failed\": failed,\n272\t \"unique_addresses\": len(groupes), \"api_requests\": requests_made}\n273\t print(f\"[immo-ka] geocode {stats}\")\n274\t return stats\n275\t\n276\t\n277\tAQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n278\t \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\n279\tBATCH_SIZE = 200\n280\t\n281\t\n282\tdef run_batch(limit: int | None = None) -> dict:\n283\t \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n284\t adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de\n285\t milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim).\"\"\"\n286\t con = db.connect()\n287\t geo = Geocoder(con) # pour réutiliser _clean / bbox\n288\t rows = con.execute(\n289\t \"\"\"SELECT uid, address, city FROM listings\n290\t WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n291\t AND dup_hidden=0 ORDER BY address\"\"\").fetchall()\n292\t # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache\n293\t uniq: dict[str, dict] = {}\n294\t for r in rows:\n295\t k = norm_key(r[\"address\"])\n296\t if not k or len(k) < 6:\n297\t continue\n298\t u = uniq.setdefault(k, {\"address\": r[\"address\"], \"city\": r[\"city\"],\n299\t \"members\": []})\n300\t u[\"members\"].append(r[\"uid\"])\n301\t pending = []\n302\t for k, u in uniq.items():\n303\t c = con.execute(\"SELECT lat,lng,failed FROM geocode_cache WHERE address=?\",\n304\t (k,)).fetchone()\n305\t if c is not None and not c[\"failed\"]: # déjà résolu : appliquer direct\n306\t for uid in u[\"members\"]:\n307\t con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n308\t (c[\"lat\"], c[\"lng\"], uid))\n309\t continue\n310\t if c is not None and c[\"failed\"]:\n311\t continue\n312\t pending.append((k, u))\n313\t con.commit()\n314\t if limit is not None:\n315\t pending = pending[:limit]\n316\t\n317\t session = requests.Session()\n318\t session.headers[\"User-Agent\"] = USER_AGENT\n319\t done = failed = 0\n320\t for i in range(0, len(pending), BATCH_SIZE):\n321\t chunk = pending[i:i + BATCH_SIZE]\n322\t records = {\"records\": [\n323\t {\"attributes\": {\"OBJECTID\": j,\n324\t \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n325\t f\"{(u['city'] or 'Québec').strip()}\"}}\n326\t for j, (_k, u) in enumerate(chunk)]}\n327\t try:\n328\t resp = session.get(AQ_BATCH_URL, params={\n329\t \"addresses\": json.dumps(records, ensure_ascii=False),\n330\t \"f\": \"json\", \"outSR\": 4326}, timeout=60)\n331\t locs = resp.json().get(\"locations\", [])\n332\t except Exception:\n333\t time.sleep(1.0)\n334\t continue\n335\t by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n336\t for j, (k, u) in enumerate(chunk):\n337\t loc = by_id.get(j)\n338\t coords = None\n339\t if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n340\t lc = loc.get(\"location\") or {}\n341\t try:\n342\t cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n343\t if _in_bbox(*cand, _bbox_for(u[\"city\"])):\n344\t coords = cand\n345\t except (KeyError, ValueError, TypeError):\n346\t coords = None\n347\t try:\n348\t if coords:\n349\t for uid in u[\"members\"]:\n350\t con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n351\t (coords[0], coords[1], uid))\n352\t con.execute(\n353\t \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n354\t \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n355\t \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n356\t \" failed=0, ts=excluded.ts\",\n357\t (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n358\t done += len(u[\"members\"])\n359\t else:\n360\t for uid in u[\"members\"]:\n361\t con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n362\t con.execute(\n363\t \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n364\t \" VALUES (?,?,?,?,1,?) ON CONFLICT(address) DO UPDATE SET\"\n365\t \" failed=1, ts=excluded.ts\",\n366\t (k, None, None, \"adresses_quebec_batch\", time.time()))\n367\t failed += len(u[\"members\"])\n368\t con.commit()\n369\t except sqlite3.OperationalError:\n370\t try: con.rollback()\n371\t except sqlite3.Error: pass\n372\t time.sleep(1.0)\n373\t print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n374\t f\"(résolues {done}, échecs {failed})\")\n375\t con.close()\n376\t stats = {\"geocoded\": done, \"failed\": failed, \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n377\t print(f\"[immo-ka] geocode-batch {stats}\")\n378\t return stats\n379\t\n\n\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n\n"}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"9fe8e83d-f4f6-45ba-a84d-373773e8cbb2","timestamp":"2026-08-25T13:10:59.192Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Reading immoka/geocode.py","usage":{"total_tokens":12578,"tool_uses":7,"duration_ms":7447},"last_tool_name":"Read","uuid":"58567ab2-2cd5-4a21-a5d0-2939012e70e0","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXGaF9We5WpTwGvBC7V","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01EszwJq9rbZoFgszfrX9Rkr","name":"Read","input":{"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":7,"cache_creation_input_tokens":1165,"cache_read_input_tokens":11380,"cache_creation":{"ephemeral_5m_input_tokens":1165,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"78eee022-b9f8-415a-9f33-0b10ab6a18ed"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01EszwJq9rbZoFgszfrX9Rkr","type":"tool_result","content":"1\t# -----------------------------------------------------------------------------\n2\t# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n3\t# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n4\t# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)\n5\t# - cache persistant (table geocode_cache) : une adresse n'est géocodée\n6\t# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce\n7\t# - politesse : 1 requête/seconde max, User-Agent identifiable\n8\t# - validation : les coordonnées doivent tomber dans la région attendue\n9\t# (bounding box par ville), sinon flag geocode_failed — jamais de\n10\t# coordonnées bidon\n11\t# -----------------------------------------------------------------------------\n12\tfrom __future__ import annotations\n13\t\n14\timport json\n15\timport sqlite3\n16\t\n17\timport re\n18\timport time\n19\t\n20\timport requests\n21\t\n22\tfrom . import db\n23\tfrom .normalize import strip_accents\n24\t\n25\tNOMINATIM_URL = \"https://nominatim.openstreetmap.org/search\"\n26\t# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre\n27\t# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)\n28\tAQ_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n29\t \"Adresse_Geocodage/GeocodeServer/findAddressCandidates\")\n30\tAQ_MIN_SCORE = 75\n31\t# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête\n32\t# User-Agent contient des accents (latin-1)\n33\tUSER_AGENT = \"ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)\"\n34\tREQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s\n35\tREQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte\n36\tRETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours\n37\t\n38\t# Bounding boxes (lat_min, lat_max, lng_min, lng_max)\n39\t_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n40\t# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord\n41\t# et la Gaspésie (expansion provinciale) — même boîte que schema.finalize()\n42\t_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n43\t\n44\t_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n45\t \"l'ancienne-lorette\", \"ancienne-lorette\"}\n46\t\n47\t\n48\tdef _bbox_for(city: str) -> tuple[float, float, float, float]:\n49\t key = strip_accents((city or \"\").strip().lower())\n50\t return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n51\t\n52\t\n53\tdef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n54\t return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n55\t\n56\t\n57\tdef norm_key(address: str) -> str:\n58\t \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\"\n59\t s = strip_accents((address or \"\").lower())\n60\t s = re.sub(r\"\\b(?:app?t?|appartement|unite|suite|#)\\.?\\s*[\\w-]+\\b\", \" \", s)\n61\t s = re.sub(r\"[^a-z0-9]+\", \" \", s)\n62\t return re.sub(r\"\\s+\", \" \", s).strip()\n63\t\n64\t\n65\tclass Geocoder:\n66\t def __init__(self, con) -> None:\n67\t self.con = con\n68\t self.session = requests.Session()\n69\t self.session.headers[\"User-Agent\"] = USER_AGENT\n70\t self._last = 0.0\n71\t\n72\t @staticmethod\n73\t def _clean(address: str) -> str:\n74\t \"\"\"Nettoyages qui aident Nominatim sur les adresses québécoises.\"\"\"\n75\t s = address.strip()\n76\t # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique\n77\t s = re.sub(r\"^(\\d+)-(\\d+)\\s\", r\"\\2 \", s)\n78\t # « 6275 et 6375 boulevard X » -> premier civique\n79\t s = re.sub(r\"^(\\d+)\\s+et\\s+\\d+\\s\", r\"\\1 \", s)\n80\t # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu\n81\t s = re.sub(r\"montr[ée]al\\s*-\\s*\", \"\", s, flags=re.I)\n82\t # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau\n83\t s = re.sub(r\",?\\s*(?:bureau|suite|local|app\\.?|apt\\.?)\\s*[\\w-]+\\b\", \"\", s, flags=re.I)\n84\t # « Vanier (Québec) » -> « Vanier, Québec »\n85\t s = re.sub(r\"\\s*\\((qu[ée]bec)\\)\", r\", \\1\", s, flags=re.I)\n86\t # abréviations cardinales : « Rue Salaberry O » -> « Ouest »\n87\t s = re.sub(r\"\\bO\\.?(?=,|\\s*$)\", \"Ouest\", s)\n88\t s = re.sub(r\"\\bE\\.?(?=,|\\s*$)\", \"Est\", s)\n89\t return s\n90\t\n91\t def _build_query(self, address: str, city: str) -> str:\n92\t q = self._clean(address)\n93\t key = strip_accents(q.lower())\n94\t if city and strip_accents(city.lower()) not in key:\n95\t q += f\", {city}\"\n96\t if \"quebec\" not in strip_accents(q.lower()) and \"qc\" not in q.lower():\n97\t q += \", Québec\"\n98\t return q + \", Canada\"\n99\t\n100\t def _query_nominatim(self, params: dict) -> tuple[float, float] | None:\n101\t \"\"\"Une requête Nominatim, throttlée.\"\"\"\n102\t wait = REQUEST_DELAY - (time.time() - self._last)\n103\t if wait > 0:\n104\t time.sleep(wait)\n105\t try:\n106\t resp = self.session.get(NOMINATIM_URL, params={\n107\t \"format\": \"jsonv2\", \"limit\": 1, \"countrycodes\": \"ca\", **params,\n108\t }, timeout=20)\n109\t self._last = time.time()\n110\t resp.raise_for_status()\n111\t hits = resp.json()\n112\t except Exception:\n113\t self._last = time.time()\n114\t return None\n115\t if not hits:\n116\t return None\n117\t try:\n118\t return float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n119\t except (KeyError, ValueError):\n120\t return None\n121\t\n122\t def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] | None:\n123\t \"\"\"Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).\n124\t\n125\t Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE\n126\t pour éviter les correspondances approximatives sur une autre rue.\n127\t \"\"\"\n128\t premier = self._clean(address).split(\",\")[0].strip()\n129\t ville = (city or \"Québec\").strip()\n130\t wait = REQUEST_DELAY_AQ - (time.time() - self._last)\n131\t if wait > 0:\n132\t time.sleep(wait)\n133\t try:\n134\t resp = self.session.get(AQ_URL, params={\n135\t \"SingleLine\": f\"{premier}, {ville}\",\n136\t \"f\": \"json\", \"outSR\": 4326, \"maxLocations\": 1,\n137\t }, timeout=20)\n138\t self._last = time.time()\n139\t resp.raise_for_status()\n140\t cands = resp.json().get(\"candidates\") or []\n141\t except Exception:\n142\t self._last = time.time()\n143\t return None\n144\t if not cands or cands[0].get(\"score\", 0) < AQ_MIN_SCORE:\n145\t return None\n146\t loc = cands[0].get(\"location\") or {}\n147\t try:\n148\t return float(loc[\"y\"]), float(loc[\"x\"])\n149\t except (KeyError, ValueError):\n150\t return None\n151\t\n152\t def _attempts(self, address: str, city: str) -> list[dict]:\n153\t \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n154\t\n155\t 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n156\t 2) recherche libre complète\n157\t 3) structurée rue seule -> centroïde de rue (repli acceptable pour la\n158\t carte quand le numéro civique est absent d'OpenStreetMap)\n159\t \"\"\"\n160\t premier = self._clean(address).split(\",\")[0].strip()\n161\t ville = (city or \"\").strip()\n162\t if not ville:\n163\t k = strip_accents(address.lower())\n164\t ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n165\t commun = {\"city\": ville, \"state\": \"Québec\", \"country\": \"Canada\"}\n166\t\n167\t tries: list[dict] = []\n168\t m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n169\t if m:\n170\t tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n171\t tries.append({\"q\": self._build_query(address, city)})\n172\t if m:\n173\t tries.append({\"street\": m.group(2), **commun})\n174\t return tries\n175\t\n176\t def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n177\t \"\"\"Adresse -> (lat, lng), via cache puis Nominatim. None si introuvable.\"\"\"\n178\t key = norm_key(address)\n179\t if not key or len(key) < 6:\n180\t return None\n181\t row = self.con.execute(\n182\t \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n183\t (key,)).fetchone()\n184\t if row is not None:\n185\t if not row[\"failed\"]:\n186\t return (row[\"lat\"], row[\"lng\"])\n187\t if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n188\t return None # échec récent : ne pas marteler l'API\n189\t\n190\t bbox = _bbox_for(city)\n191\t coords = None\n192\t # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n193\t # limite stricte. Nominatim (1 req/s) seulement en repli.\n194\t provider = \"adresses_quebec\"\n195\t c = self._query_adresses_quebec(address, city)\n196\t if c is not None and _in_bbox(*c, bbox):\n197\t coords = c\n198\t if coords is None:\n199\t provider = \"nominatim\"\n200\t for params in self._attempts(address, city):\n201\t c = self._query_nominatim(params)\n202\t if c is not None and _in_bbox(*c, bbox):\n203\t coords = c\n204\t break\n205\t ok = coords is not None\n206\t self.con.execute(\n207\t \"INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)\"\n208\t \" VALUES (?,?,?,?,?,?)\"\n209\t \" ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,\"\n210\t \" lng=excluded.lng, provider=excluded.provider,\"\n211\t \" failed=excluded.failed, ts=excluded.ts\",\n212\t (key, coords[0] if ok else None, coords[1] if ok else None,\n213\t provider, 0 if ok else 1, time.time()))\n214\t self.con.commit()\n215\t return coords if ok else None\n216\t\n217\t\n218\tdef run(limit: int | None = None) -> dict:\n219\t \"\"\"Géocode les annonces actives sans coordonnées, par adresse unique.\n220\t\n221\t `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de\n222\t cache sont gratuits et toujours appliqués).\n223\t \"\"\"\n224\t con = db.connect()\n225\t geo = Geocoder(con)\n226\t rows = con.execute(\n227\t \"\"\"SELECT uid, address, city FROM listings\n228\t WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n229\t AND dup_hidden=0\n230\t ORDER BY address\"\"\").fetchall()\n231\t\n232\t # regrouper par immeuble (adresse normalisée)\n233\t groupes: dict[str, list] = {}\n234\t for r in rows:\n235\t groupes.setdefault(norm_key(r[\"address\"]), []).append(r)\n236\t\n237\t done = failed = requests_made = 0\n238\t for key, members in groupes.items():\n239\t if not key:\n240\t continue\n241\t cached = con.execute(\n242\t \"SELECT failed FROM geocode_cache WHERE address=?\", (key,)).fetchone()\n243\t if cached is None:\n244\t if limit is not None and requests_made >= limit:\n245\t continue\n246\t requests_made += 1\n247\t try:\n248\t coords = geo.resolve(members[0][\"address\"], members[0][\"city\"])\n249\t if coords:\n250\t for r in members:\n251\t con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n252\t (coords[0], coords[1], r[\"uid\"]))\n253\t done += len(members)\n254\t else:\n255\t # introuvable/hors zone : flag ; jamais de coordonnées bidon\n256\t for r in members:\n257\t con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\",\n258\t (r[\"uid\"],))\n259\t failed += len(members)\n260\t con.commit()\n261\t except sqlite3.OperationalError:\n262\t # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,\n263\t # elle sera reprise au prochain passage — jamais crasher tout le run.\n264\t try:\n265\t con.rollback()\n266\t except sqlite3.Error:\n267\t pass\n268\t time.sleep(1.0)\n269\t continue\n270\t\n271\t con.close()\n272\t stats = {\"geocoded\": done, \"failed\": failed,\n273\t \"unique_addresses\": len(groupes), \"api_requests\": requests_made}\n274\t print(f\"[immo-ka] geocode {stats}\")\n275\t return stats\n276\t\n277\t\n278\tAQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n279\t \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\n280\tBATCH_SIZE = 200\n281\t\n282\t\n283\tdef run_batch(limit: int | None = None) -> dict:\n284\t \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n285\t adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de\n286\t milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim).\"\"\"\n287\t con = db.connect()\n288\t geo = Geocoder(con) # pour réutiliser _clean / bbox\n289\t rows = con.execute(\n290\t \"\"\"SELECT uid, address, city FROM listings\n291\t WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n292\t AND dup_hidden=0 ORDER BY address\"\"\").fetchall()\n293\t # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache\n294\t uniq: dict[str, dict] = {}\n295\t for r in rows:\n296\t k = norm_key(r[\"address\"])\n297\t if not k or len(k) < 6:\n298\t continue\n299\t u = uniq.setdefault(k, {\"address\": r[\"address\"], \"city\": r[\"city\"],\n300\t \"members\": []})\n301\t u[\"members\"].append(r[\"uid\"])\n302\t pending = []\n303\t for k, u in uniq.items():\n304\t c = con.execute(\"SELECT lat,lng,failed FROM geocode_cache WHERE address=?\",\n305\t (k,)).fetchone()\n306\t if c is not None and not c[\"failed\"]: # déjà résolu : appliquer direct\n307\t for uid in u[\"members\"]:\n308\t con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n309\t (c[\"lat\"], c[\"lng\"], uid))\n310\t continue\n311\t if c is not None and c[\"failed\"]:\n312\t continue\n313\t pending.append((k, u))\n314\t con.commit()\n315\t if limit is not None:\n316\t pending = pending[:limit]\n317\t\n318\t session = requests.Session()\n319\t session.headers[\"User-Agent\"] = USER_AGENT\n320\t done = failed = 0\n321\t for i in range(0, len(pending), BATCH_SIZE):\n322\t chunk = pending[i:i + BATCH_SIZE]\n323\t records = {\"records\": [\n324\t {\"attributes\": {\"OBJECTID\": j,\n325\t \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n326\t f\"{(u['city'] or 'Québec').strip()}\"}}\n327\t for j, (_k, u) in enumerate(chunk)]}\n328\t try:\n329\t # POST obligatoire : le param `addresses` (JSON de N records) est trop\n330\t # long pour une URL GET dès quelques dizaines d'adresses.\n331\t resp = session.post(AQ_BATCH_URL, data={\n332\t \"addresses\": json.dumps(records, ensure_ascii=False),\n333\t \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n334\t locs = resp.json().get(\"locations\", [])\n335\t except Exception as e:\n336\t print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n337\t time.sleep(1.0)\n338\t continue\n339\t by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n340\t for j, (k, u) in enumerate(chunk):\n341\t loc = by_id.get(j)\n342\t coords = None\n343\t if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n344\t lc = loc.get(\"location\") or {}\n345\t try:\n346\t cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n347\t if _in_bbox(*cand, _bbox_for(u[\"city\"])):\n348\t coords = cand\n349\t except (KeyError, ValueError, TypeError):\n350\t coords = None\n351\t try:\n352\t if coords:\n353\t for uid in u[\"members\"]:\n354\t con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n355\t (coords[0], coords[1], uid))\n356\t con.execute(\n357\t \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n358\t \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n359\t \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n360\t \" failed=0, ts=excluded.ts\",\n361\t (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n362\t done += len(u[\"members\"])\n363\t else:\n364\t for uid in u[\"members\"]:\n365\t con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n366\t con.execute(\n367\t \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n368\t \" VALUES (?,?,?,?,1,?) ON CONFLICT(address) DO UPDATE SET\"\n369\t \" failed=1, ts=excluded.ts\",\n370\t (k, None, None, \"adresses_quebec_batch\", time.time()))\n371\t failed += len(u[\"members\"])\n372\t con.commit()\n373\t except sqlite3.OperationalError:\n374\t try: con.rollback()\n375\t except sqlite3.Error: pass\n376\t time.sleep(1.0)\n377\t print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n378\t f\"(résolues {done}, échecs {failed})\")\n379\t con.close()\n380\t stats = {\"geocoded\": done, \"failed\": failed, \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n381\t print(f\"[immo-ka] geocode-batch {stats}\")\n382\t return stats\n383\t\n\n\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n\n"}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"06bf52a7-ced5-4907-a447-d3ede7f9b431","timestamp":"2026-08-25T13:10:59.504Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Reading immoka/db.py","usage":{"total_tokens":12580,"tool_uses":8,"duration_ms":7651},"last_tool_name":"Read","uuid":"ced10395-1e2d-400d-a098-c29c6452c5fe","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} 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{"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01KVH3SywXaGCTWyWNSgtXF5","type":"tool_result","content":"1\t# -----------------------------------------------------------------------------\n2\t# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n3\t# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n4\t# db.py : persistance SQLite — upsert avec détection de changements,\n5\t# cycle de vie avec délai de grâce (2 syncs), détection de dérive,\n6\t# historique de prix, cache des pages détail.\n7\t# -----------------------------------------------------------------------------\n8\tfrom __future__ import annotations\n9\t\n10\timport json\n11\timport sqlite3\n12\timport statistics\n13\timport time\n14\tfrom pathlib import Path\n15\t\n16\tfrom .schema import PropertyListing\n17\t\n18\tDB_PATH = Path(__file__).resolve().parent.parent / \"data\" / \"immoka.db\"\n19\t\n20\t# Nombre d'exécutions consécutives où une propriété doit être absente de la\n21\t# source avant d'être désactivée (délai de grâce contre les ratés ponctuels).\n22\tMISS_GRACE = 2\n23\t\n24\t# Dérive : si une source retourne <= DRIFT_RATIO × sa médiane historique\n25\t# (médiane >= DRIFT_MIN_BASE annonces), on alerte et on suspend les retraits.\n26\tDRIFT_RATIO = 0.25\n27\tDRIFT_MIN_BASE = 8\n28\tDRIFT_HISTORY = 5\n29\t\n30\t_SCHEMA = \"\"\"\n31\tCREATE TABLE IF NOT EXISTS listings (\n32\t uid TEXT PRIMARY KEY,\n33\t source TEXT NOT NULL,\n34\t external_id TEXT NOT NULL,\n35\t url TEXT,\n36\t title TEXT,\n37\t address TEXT,\n38\t sector TEXT,\n39\t city TEXT,\n40\t region TEXT,\n41\t property_type TEXT,\n42\t price REAL,\n43\t price_label TEXT,\n44\t bedrooms INTEGER,\n45\t bathrooms INTEGER,\n46\t powder_rooms INTEGER,\n47\t area_sqft REAL,\n48\t lot_sqft REAL,\n49\t year_built INTEGER,\n50\t mls TEXT,\n51\t status TEXT DEFAULT 'a-vendre',\n52\t broker_name TEXT,\n53\t broker_phone TEXT,\n54\t agency TEXT,\n55\t description TEXT,\n56\t features TEXT, -- JSON (liste de textes source)\n57\t details TEXT, -- JSON (champs structurés)\n58\t images TEXT, -- JSON\n59\t lat REAL,\n60\t lng REAL,\n61\t geocode_failed INTEGER DEFAULT 0,\n62\t content_hash TEXT,\n63\t first_seen REAL,\n64\t last_seen REAL,\n65\t updated_at REAL,\n66\t miss_count INTEGER DEFAULT 0,\n67\t active INTEGER DEFAULT 1,\n68\t dup_hidden INTEGER DEFAULT 0 -- 1 = doublon de sous-agence masqué (dédup Centris)\n69\t);\n70\tCREATE INDEX IF NOT EXISTS idx_listings_source ON listings(source);\n71\tCREATE INDEX IF NOT EXISTS idx_listings_city ON listings(city);\n72\tCREATE INDEX IF NOT EXISTS idx_listings_type ON listings(property_type);\n73\tCREATE INDEX IF NOT EXISTS idx_listings_active ON listings(active);\n74\tCREATE INDEX IF NOT EXISTS idx_listings_extid ON listings(external_id);\n75\t\n76\tCREATE TABLE IF NOT EXISTS sync_log (\n77\t id INTEGER PRIMARY KEY AUTOINCREMENT,\n78\t source TEXT,\n79\t ts REAL,\n80\t found INTEGER,\n81\t added INTEGER,\n82\t updated INTEGER,\n83\t removed INTEGER,\n84\t ok INTEGER,\n85\t message TEXT,\n86\t stats TEXT -- JSON : taux de champs null, missed, alerte…\n87\t);\n88\t\n89\tCREATE TABLE IF NOT EXISTS detail_cache (\n90\t source TEXT NOT NULL,\n91\t external_id TEXT NOT NULL,\n92\t key TEXT, -- hash du contenu « liste » de l'annonce\n93\t payload TEXT, -- JSON opaque propre au connecteur\n94\t fetched_at REAL,\n95\t PRIMARY KEY (source, external_id)\n96\t);\n97\t\n98\tCREATE TABLE IF NOT EXISTS price_log (\n99\t uid TEXT NOT NULL,\n100\t ts REAL NOT NULL,\n101\t price REAL -- prix observé (baisses/hausses de prix demandé)\n102\t);\n103\tCREATE INDEX IF NOT EXISTS idx_price_log_uid ON price_log(uid);\n104\t\n105\tCREATE TABLE IF NOT EXISTS geocode_cache (\n106\t address TEXT PRIMARY KEY,\n107\t lat REAL,\n108\t lng REAL,\n109\t provider TEXT,\n110\t failed INTEGER DEFAULT 0,\n111\t ts REAL\n112\t);\n113\t\n114\tCREATE TABLE IF NOT EXISTS poi_cache (\n115\t coord_key TEXT PRIMARY KEY, -- \"lat,lng\" arrondi à 4 décimales (~11 m)\n116\t lat REAL,\n117\t lng REAL,\n118\t pois TEXT, -- JSON : [{cat, name, dist_m}] (plus proche/catégorie)\n119\t ts REAL\n120\t);\n121\t\"\"\"\n122\t\n123\t\n124\t_SCHEMA_READY = False # le schéma/migration ne s'exécute qu'UNE fois par process\n125\t\n126\t\n127\tdef _init_schema(con: sqlite3.Connection) -> None:\n128\t \"\"\"Création de schéma + migration — coûteuse (write-lock). À faire une seule\n129\t fois par process : l'exécuter à chaque connexion sérialisait les requêtes du\n130\t web sur un verrou d'écriture (deadlock/starvation sous charge).\"\"\"\n131\t con.executescript(_SCHEMA)\n132\t cols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(listings)\")}\n133\t if \"agency\" not in cols:\n134\t con.execute(\"ALTER TABLE listings ADD COLUMN agency TEXT\")\n135\t if \"dup_hidden\" not in cols:\n136\t con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n137\t if \"dauid\" not in cols: # aire de diffusion 2021 (stats de quartier)\n138\t con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")\n139\t if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n140\t con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n141\t con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n142\t con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n143\t con.commit()\n144\t\n145\t\n146\tdef refresh_dedup(con: sqlite3.Connection) -> int:\n147\t \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n148\t colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n149\t au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n150\t\n\n\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n\n"}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"4c59927f-cbf8-4f13-ae5d-ec09d27d1dbc","timestamp":"2026-08-25T13:10:59.707Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Running grep -r \"geocode\\|run_batch\" /Users/simon-pierreb…","usage":{"total_tokens":27273,"tool_uses":9,"duration_ms":10018},"last_tool_name":"Bash","uuid":"81a6d0e3-714d-488b-b337-c7bb1c92f66b","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXGj2VA8dGZs1NckoZm","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01KNeBy7d8k4dJJzukHumbqz","name":"Bash","input":{"command":"grep -r \"geocode\\|run_batch\" /Users/simon-pierreboucher/apps/immo-ka --include=\"*.py\" | grep -E \"(import|from|def|\\.run|\\.run_batch)\" | head -30"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":7,"cache_creation_input_tokens":14689,"cache_read_input_tokens":12545,"cache_creation":{"ephemeral_5m_input_tokens":14689,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"dfe8f7e9-37fd-4c46-a716-d59c533e66a7"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Finding scripts/**/*.py","usage":{"total_tokens":27275,"tool_uses":10,"duration_ms":10119},"last_tool_name":"Glob","uuid":"848b3b86-ab65-4500-b923-e87c042016df","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXGj2VA8dGZs1NckoZm","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01RnemZtLLqdyhHiJTPFKo6J","name":"Glob","input":{"pattern":"scripts/**/*.py","path":"/Users/simon-pierreboucher/apps/immo-ka"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":7,"cache_creation_input_tokens":14689,"cache_read_input_tokens":12545,"cache_creation":{"ephemeral_5m_input_tokens":14689,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"0a526e1c-5f3f-45a4-bdd0-13890b105cc6"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01RnemZtLLqdyhHiJTPFKo6J","type":"tool_result","content":"scripts/refresh_via_capitale.py\nscripts/gen_connector_docs.py\nscripts/valider_rendu.py\nscripts/build_demenageurs.py\nscripts/build_inspecteurs.py"}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"0435909f-0351-43a4-aae8-7ca6e25a3ae8","timestamp":"2026-08-25T13:11:02.196Z"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01KNeBy7d8k4dJJzukHumbqz","type":"tool_result","content":"/Users/simon-pierreboucher/apps/immo-ka/run.py: from immoka import geocode\n/Users/simon-pierreboucher/apps/immo-ka/run.py: geocode.run_batch(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n/Users/simon-pierreboucher/apps/immo-ka/run.py: from immoka import geocode\n/Users/simon-pierreboucher/apps/immo-ka/run.py: geocode.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n/Users/simon-pierreboucher/apps/immo-ka/immoka/ingest.py: from . import geocode\n/Users/simon-pierreboucher/apps/immo-ka/immoka/ingest.py: geocode.run_batch()\n/Users/simon-pierreboucher/apps/immo-ka/immoka/ingest.py: ia = imgaudit.run_batch(limit=2000)\n/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py:def run_batch(limit: int | None = None) -> dict:\n/Users/simon-pierreboucher/apps/immo-ka/immoka/imgaudit.py:def run_batch(limit: int = 2000, workers: int = 8) -> dict:\n/Users/simon-pierreboucher/apps/immo-ka/geocode.py:def run_batch(limit: int | None = None) -> dict:","is_error":false}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"09bd4480-2169-429a-945f-6a74336600f5","timestamp":"2026-08-25T13:11:02.860Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Reading run.py","usage":{"total_tokens":28013,"tool_uses":11,"duration_ms":12073},"last_tool_name":"Read","uuid":"db7d3ff7-f4dc-4a10-a745-6d1ea99d4eb6","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} 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{"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01P37Ekc2ftEZeAEU89hPUnV","type":"tool_result","content":"1\t#!/usr/bin/env python3\n2\t# -----------------------------------------------------------------------------\n3\t# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n4\t# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n5\t# run.py : point d'entrée — `sync`, `watch`, `serve`\n6\t# -----------------------------------------------------------------------------\n7\t\"\"\"Utilisation :\n8\t python run.py sync [source ...] # synchronise les propriétés\n9\t python run.py watch [minutes] # synchronise en boucle (défaut 60 min)\n10\t python run.py serve [port] # démarre l'API + le frontend (défaut 8090)\n11\t python run.py list # liste les connecteurs enregistrés\n12\t python run.py geocode [n] # géocode les annonces sans coordonnées (max n requêtes)\n13\t python run.py poi [n] # commodités de proximité par immeuble (max n requêtes)\n14\t python run.py quartier [n] # rattache chaque annonce à son aire de diffusion (DAUID)\n15\t python run.py mortgage-sync [slug…] # collecte les taux hypothécaires (toutes banques ou celles listées)\n16\t python run.py mortgage-watch [min] # collecte en boucle (défaut IMMOKA_MORTGAGE_INTERVAL_MIN=180)\n17\t python run.py mortgage-status # santé des providers de taux (OK/WARNING/ERROR)\n18\t\"\"\"\n19\tfrom __future__ import annotations\n20\t\n21\timport os\n22\timport sys\n23\tfrom pathlib import Path\n24\t\n25\t# Charger .env (FIRECRAWL_API_KEY, etc.) sans dépendance externe\n26\t_env = Path(__file__).parent / \".env\"\n27\tif _env.exists():\n28\t for line in _env.read_text().splitlines():\n29\t line = line.strip()\n30\t if line and not line.startswith(\"#\") and \"=\" in line:\n31\t k, _, v = line.partition(\"=\")\n32\t os.environ.setdefault(k.strip(), v.strip())\n33\t\n34\t\n35\tdef main() -> None:\n36\t cmd = sys.argv[1] if len(sys.argv) > 1 else \"serve\"\n37\t if cmd == \"sync\":\n38\t from immoka import ingest\n39\t ingest.run(sys.argv[2:] or None)\n40\t elif cmd == \"watch\":\n41\t from immoka import ingest\n42\t minutes = int(sys.argv[2]) if len(sys.argv) > 2 else 60\n43\t ingest.watch(minutes * 60)\n44\t elif cmd == \"list\":\n45\t from immoka.connectors import CONNECTORS\n46\t for sid in sorted(CONNECTORS):\n47\t print(sid)\n48\t print(f\"-- {len(CONNECTORS)} connecteur(s)\")\n49\t elif cmd == \"geocode\":\n50\t from immoka import geocode\n51\t geocode.run_batch(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n52\t elif cmd == \"geocode1\": # ancien mode 1-par-1 (+ repli Nominatim)\n53\t from immoka import geocode\n54\t geocode.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n55\t elif cmd == \"poi\":\n56\t from immoka import poi\n57\t poi.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n58\t elif cmd == \"air-refresh\":\n59\t from immoka import air\n60\t air.refresh()\n61\t elif cmd == \"gaz-refresh\":\n62\t from immoka import gaz\n63\t print(f\"[gaz] {gaz.refresh()} stations\")\n64\t elif cmd == \"hydro-precompute\":\n65\t from immoka import hydro\n66\t n = int(sys.argv[2]) if len(sys.argv) > 2 else 100\n67\t b = int(sys.argv[3]) if len(sys.argv) > 3 else 40\n68\t hydro.precompute(limit=n, budget=b)\n69\t elif cmd == \"inondation-build\":\n70\t from immoka import inondation\n71\t inondation.build()\n72\t elif cmd == \"quartier\":\n73\t from immoka import quartier\n74\t quartier.enrich(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n75\t elif cmd == \"vraiprix\":\n76\t from immoka import vraiprix\n77\t vraiprix.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n78\t elif cmd == \"vraiprix_local\": # appariement local (vraiprix.db) : rapide\n79\t from immoka import vraiprix_local\n80\t reval = \"reval\" in sys.argv[2:]\n81\t lim = next((int(a) for a in sys.argv[2:] if a.isdigit()), None)\n82\t if \"role\" in sys.argv[2:]: # backfill rôle d'évaluation (jointure par id)\n83\t vraiprix_local.enrich_role(lim)\n84\t else:\n85\t vraiprix_local.run(lim, revalidate=reval)\n86\t elif cmd == \"mortgage-sync\":\n87\t from immoka.mortgage import scheduler\n88\t scheduler.run(sys.argv[2:] or None)\n89\t elif cmd == \"mortgage-watch\":\n90\t from immoka.mortgage import scheduler\n91\t minutes = int(sys.argv[2]) if len(sys.argv) > 2 else None\n92\t scheduler.watch(minutes)\n93\t elif cmd == \"mortgage-status\":\n94\t from immoka.mortgage import store\n95\t con = store.connect()\n96\t for h in store.provider_health(con):\n97\t print(f\"{h['level']:8s} {h['provider']:15s} \"\n98\t f\"statut={h.get('status') or '-'} \"\n99\t f\"produits_courants={h.get('current_products', 0)} \"\n100\t f\"dernière_passe=il y a {h.get('age_minutes', '?')} min\")\n101\t elif cmd == \"serve\":\n102\t import uvicorn\n103\t port = int(sys.argv[2]) if len(sys.argv) > 2 else 8090\n104\t uvicorn.run(\"immoka.web:app\", host=\"0.0.0.0\", port=port)\n105\t else:\n106\t print(__doc__)\n107\t sys.exit(1)\n108\t\n109\t\n110\tif __name__ == \"__main__\":\n111\t main()\n112\t\n\n\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n\n"}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"2de0880d-0a56-442a-889a-ab025894c59b","timestamp":"2026-08-25T13:11:04.128Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Searching for duproprio.*1126225|rue.*perdrix|jonquiere|saguenay","usage":{"total_tokens":28015,"tool_uses":12,"duration_ms":13043},"last_tool_name":"Grep","uuid":"317a8077-34e0-4bf2-a4b1-9219cc6a5ad4","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXGxX6TUWNd4hPud9gZ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01VFAaeiZR9JHomHxnjNyd99","name":"Grep","input":{"pattern":"duproprio.*1126225|rue.*perdrix|jonquiere|saguenay","path":"/Users/simon-pierreboucher/apps/immo-ka","type":"py","output_mode":"files_with_matches"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":81,"cache_creation_input_tokens":660,"cache_read_input_tokens":27234,"cache_creation":{"ephemeral_5m_input_tokens":660,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"2a89e2bd-30eb-4036-b7b3-6b6227831744"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01VFAaeiZR9JHomHxnjNyd99","type":"tool_result","content":"Found 3 files\nimmoka/connectors/realtor_ca.py\nimmoka/connectors/sothebys_quebec.py\nimmoka/connectors/via_capitale.py"}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"e7e5a70f-2505-43a2-88fd-5707df18c174","timestamp":"2026-08-25T13:11:05.122Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Reading immoka/ingest.py","usage":{"total_tokens":30266,"tool_uses":13,"duration_ms":15099},"last_tool_name":"Read","uuid":"5a94b9f9-211a-4512-9c35-2eda96ba5bfc","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXH8TdzWPHR96Hj1Vhx","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Yb33nhMFB94xfie7qpG4Bo","name":"Read","input":{"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/ingest.py","limit":100},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":7,"cache_creation_input_tokens":2321,"cache_read_input_tokens":27894,"cache_creation":{"ephemeral_5m_input_tokens":2321,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"688be15c-c3d5-41c4-8616-aee7ee74407d"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Yb33nhMFB94xfie7qpG4Bo","type":"tool_result","content":"1\t# -----------------------------------------------------------------------------\n2\t# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n3\t# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n4\t# ingest.py : pipeline d'ingestion — exécute les connecteurs et synchronise\n5\t# la base (ajouts / mises à jour / retraits) = contenu toujours à jour\n6\t# -----------------------------------------------------------------------------\n7\tfrom __future__ import annotations\n8\t\n9\timport sys\n10\timport time\n11\timport traceback\n12\t\n13\tfrom . import db\n14\tfrom .connectors import CONNECTORS\n15\t\n16\t\n17\tdef run(sources: list[str] | None = None) -> list[dict]:\n18\t \"\"\"Exécute l'ingestion pour toutes les sources (ou celles demandées).\"\"\"\n19\t con = db.connect()\n20\t results = []\n21\t targets = sources or list(CONNECTORS.keys())\n22\t for sid in targets:\n23\t cls = CONNECTORS.get(sid)\n24\t if cls is None:\n25\t print(f\"[immo-ka] connecteur inconnu : {sid}\", file=sys.stderr)\n26\t continue\n27\t t0 = time.time()\n28\t print(f\"[immo-ka] sync {sid} ...\")\n29\t try:\n30\t listings = cls().fetch()\n31\t finalized, dropped = [], 0\n32\t for lst in listings:\n33\t try:\n34\t finalized.append(lst.finalize())\n35\t except Exception: # une annonce malformée ne bloque pas la source\n36\t dropped += 1\n37\t stats = db.sync_source(con, sid, finalized)\n38\t stats[\"seconds\"] = round(time.time() - t0, 1)\n39\t if dropped:\n40\t stats[\"dropped\"] = dropped\n41\t if stats.get(\"alert\"):\n42\t print(f\"[immo-ka] ⚠ ALERTE {sid} : {stats['alert']}\")\n43\t print(f\"[immo-ka] {stats}\")\n44\t results.append(stats)\n45\t except Exception as exc: # robustesse : une source ne bloque pas les autres\n46\t db.log_failure(con, sid, f\"{exc}\")\n47\t traceback.print_exc()\n48\t results.append({\"source\": sid, \"error\": str(exc)})\n49\t # recalcule la déduplication (pré-calculée pour des lectures instantanées)\n50\t try:\n51\t hidden = db.refresh_dedup(con)\n52\t print(f\"[immo-ka] dédup: {hidden} doublon(s) masqué(s) \"\n53\t \"(sous-agences Centris + adresse inter-sources)\")\n54\t except Exception:\n55\t traceback.print_exc()\n56\t # contrôle qualité : score de complétude, cohérence immobilière, seuil de\n57\t # publication (quarantaine) et champs dérivés (prix/pi², transaction)\n58\t try:\n59\t from . import quality\n60\t q = quality.refresh(con)\n61\t print(f\"[immo-ka] qualité: {q['publiees']} publiée(s), \"\n62\t f\"{q['quarantaine']} en quarantaine, \"\n63\t f\"{q['recalculees']} recalculée(s)\")\n64\t except Exception:\n65\t traceback.print_exc()\n66\t # statistiques du planificateur SQLite : sans elles, les requêtes bbox\n67\t # de la carte (Ka Maps) n'utilisent pas idx_listings_geo\n68\t try:\n69\t con.execute(\"PRAGMA optimize\")\n70\t except Exception:\n71\t pass\n72\t con.close()\n73\t return results\n74\t\n75\t\n76\tdef watch(interval_seconds: int = 3600) -> None:\n77\t \"\"\"Boucle de synchronisation périodique (équivalent webhook, via PM2/cron).\n78\t\n79\t Après chaque synchronisation, l'enrichissement continu de la carte\n80\t (Ka Maps) : géocodage EN LOT des nouvelles adresses (Adresses Québec),\n81\t puis appariement Vrai-Prix local (estimations + coordonnées du rôle)\n82\t quand data/vraiprix.db (ou VRAIPRIX_DB) est disponible.\n83\t \"\"\"\n84\t while True:\n85\t run()\n86\t try: # nouvelles adresses → coordonnées (cache : quasi gratuit ensuite)\n87\t from . import geocode\n88\t geocode.run_batch()\n89\t except Exception as exc:\n90\t print(f\"[immo-ka] geocode: erreur non bloquante: {exc}\", file=sys.stderr)\n91\t try: # estimations Vrai-Prix + géocodage bonus depuis le rôle\n92\t from . import vraiprix_local\n93\t if vraiprix_local.available():\n94\t vraiprix_local.run(limit=5000)\n95\t # rôle d'évaluation (valeurs/année/superficies officielles) pour\n96\t # les annonces déjà appariées — jointure par id, quasi gratuite\n97\t vraiprix_local.enrich_role(limit=20000)\n98\t except Exception as exc:\n99\t print(f\"[immo-ka] vraiprix_local: erreur non bloquante: {exc}\", file=sys.stderr)\n100\t try: # audit budgété des images (liens morts, minuscules, corrompues)\n\n\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n\n"}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"19561e18-8703-4202-a7e7-3226a21b665e","timestamp":"2026-08-25T13:11:07.159Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Searching for jonquiere|saguenay","usage":{"total_tokens":30268,"tool_uses":14,"duration_ms":15738},"last_tool_name":"Grep","uuid":"acefd924-1159-4b5b-9085-d91ff1557c80","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXH8TdzWPHR96Hj1Vhx","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_013yEKHUrcVg1fwhTR2dB2up","name":"Grep","input":{"pattern":"jonquiere|saguenay","path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/connectors","type":"py","output_mode":"files_with_matches"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":7,"cache_creation_input_tokens":2321,"cache_read_input_tokens":27894,"cache_creation":{"ephemeral_5m_input_tokens":2321,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"da833ced-5fcc-4d01-8555-1707af9c38e8"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013yEKHUrcVg1fwhTR2dB2up","type":"tool_result","content":"Found 3 files\nimmoka/connectors/realtor_ca.py\nimmoka/connectors/sothebys_quebec.py\nimmoka/connectors/via_capitale.py"}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"5a20f170-2cbf-4418-843d-1f4b87fd556d","timestamp":"2026-08-25T13:11:07.815Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Running ls /Users/simon-pierreboucher/apps/immo-ka/immoka…","usage":{"total_tokens":32197,"tool_uses":15,"duration_ms":17450},"last_tool_name":"Bash","uuid":"1ebb45f5-b19d-490b-b0a2-c1e316de827c","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} 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{"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_012y6XS7Cm2iTvewfCv91Lf8","type":"tool_result","content":"duproprio.py\nproprio_direct.py","is_error":false}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ae49b476-aa31-45f8-b0a0-4785ec36e7cf","timestamp":"2026-08-25T13:11:09.531Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Reading immoka/connectors/duproprio.py","usage":{"total_tokens":32447,"tool_uses":16,"duration_ms":19035},"last_tool_name":"Read","uuid":"4e6f1141-783c-44d0-9745-c83adb5cc06c","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} 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{"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Ncd9Vic12hbofMcudUTV4p","type":"tool_result","content":"1\t# -----------------------------------------------------------------------------\n2\t# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n3\t# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n4\t# connectors/duproprio.py : DuProprio (FSBO — vente sans courtier)\n5\t#\n6\t# DuProprio est la grande plateforme québécoise de vente « à vendre par le\n7\t# propriétaire » (sans agence). Segment complémentaire absent de toutes les\n8\t# bannières de courtage. Énumération EXHAUSTIVE via les sitemaps FR par région\n9\t# du Québec (`/sitemaps/fr/-listings.xml.gz`) : l'URL encode déjà\n10\t# région, ville, type et l'id DuProprio (= external_id). La fiche détail\n11\t# (JSON-LD Product) fournit prix, description et galerie ; enrichissement\n12\t# plafonné + cache (comme les autres connecteurs). Scrapfly en secours si le\n13\t# fetch direct est bloqué.\n14\t# -----------------------------------------------------------------------------\n15\tfrom __future__ import annotations\n16\t\n17\timport gzip\n18\timport io\n19\timport os\n20\timport re\n21\t\n22\tfrom .base import BaseConnector\n23\tfrom . import _detailutil as du\n24\tfrom ..normalize import normalize_property_type, parse_price\n25\tfrom ..schema import PropertyListing\n26\t\n27\tSITEMAP_INDEX = \"https://duproprio.com/sitemaps/fr/index.xml.gz\"\n28\tDETAIL_LIMIT = int(os.environ.get(\"IMMOKA_DUPROPRIO_DETAIL_LIMIT\", \"500\"))\n29\tAGENCY = \"DuProprio (sans courtier)\"\n30\t\n31\t_LOC_RE = re.compile(r\"([^<]+)\")\n32\t# /fr///-a-vendre/-\n33\t_URL_RE = re.compile(\n34\t r\"https://duproprio\\.com/fr/([a-z0-9-]+)/([a-z0-9-]+)/([a-z0-9-]+?)-a-vendre/([a-z0-9-]+?)-(\\d{5,})/?$\",\n35\t re.I)\n36\t_PHOTO_RE = re.compile(\n37\t r\"https://photos\\.duproprio\\.com/photos/public/for_sale/\\d+/\\d+/[^\\\"'\\\\ ]+?\\.jpg\", re.I)\n38\t_LDPROD_RE = re.compile(r']+application/ld\\+json[^>]*>(.*?)', re.S | re.I)\n39\t\n40\t\n41\tclass DuProprioConnector(BaseConnector):\n42\t source_id = \"duproprio\"\n43\t request_delay = 0.4\n44\t\n45\t def fetch(self) -> list[PropertyListing]:\n46\t by_id: dict[str, PropertyListing] = {}\n47\t for sm in self._region_listing_sitemaps():\n48\t for url in self._sitemap_locs(sm):\n49\t lst = self._to_listing(url)\n50\t if lst and lst.external_id not in by_id:\n51\t by_id[lst.external_id] = lst\n52\t listings = list(by_id.values())\n53\t du.enrich(self, listings, DETAIL_LIMIT, _parse_dp_detail,\n54\t key=\"v2\", fetch_html=self._fetch_detail)\n55\t return listings\n56\t\n57\t # -- sitemaps --------------------------------------------------------------\n58\t def _region_listing_sitemaps(self) -> list[str]:\n59\t xml = self._get_gz(SITEMAP_INDEX)\n60\t # uniquement les sitemaps d'INSCRIPTIONS par région (Québec)\n61\t return [u for u in _LOC_RE.findall(xml) if u.endswith(\"-listings.xml.gz\")]\n62\t\n63\t def _sitemap_locs(self, url: str) -> list[str]:\n64\t return [u for u in _LOC_RE.findall(self._get_gz(url)) if \"/fr/\" in u]\n65\t\n66\t def _get_gz(self, url: str) -> str:\n67\t try:\n68\t raw = self.get(url).content\n69\t except Exception:\n70\t return \"\"\n71\t try:\n72\t return gzip.GzipFile(fileobj=io.BytesIO(raw)).read().decode(\"utf-8\", \"ignore\")\n73\t except OSError:\n74\t return raw.decode(\"utf-8\", \"ignore\") # déjà décompressé\n75\t\n76\t # -- mapping ---------------------------------------------------------------\n77\t def _to_listing(self, url: str) -> PropertyListing | None:\n78\t m = _URL_RE.match(url.strip())\n79\t if not m:\n80\t return None\n81\t region_s, city_s, type_s, addr_s, did = m.groups()\n82\t return PropertyListing(\n83\t source=self.source_id, external_id=did, url=url,\n84\t title=_deslug(addr_s),\n85\t address=_deslug(re.sub(r\"^(hab|com|ter|multi|imm)-\", \"\", addr_s)),\n86\t city=_deslug(city_s),\n87\t region=_region(region_s),\n88\t property_type=normalize_property_type(type_s.replace(\"-\", \" \")),\n89\t agency=AGENCY, broker_name=\"\",\n90\t )\n91\t\n92\t def _fetch_detail(self, url: str) -> str:\n93\t html = \"\"\n94\t try:\n95\t html = self.get(url).text\n96\t except Exception:\n97\t html = \"\"\n98\t if \"application/ld+json\" not in html: # bloqué -> Scrapfly (ASP)\n99\t try:\n100\t html = self.get_scrapfly(url, render_js=False, asp=True)\n\n\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n\n"}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"4cda5e18-fe98-45ee-be59-b8fb30348140","timestamp":"2026-08-25T13:11:11.090Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Running sqlite3 /Users/simon-pierreboucher/apps/immo-ka/d…","usage":{"total_tokens":32450,"tool_uses":17,"duration_ms":19465},"last_tool_name":"Bash","uuid":"41084418-b788-4613-8e0c-3779c4131fe2","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXHSzMpqPxmwHEMcBXu","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01B1bPHDLZrogQ91WRyZvSzA","name":"Bash","input":{"command":"sqlite3 /Users/simon-pierreboucher/apps/immo-ka/data/immoka.db \"SELECT uid, address, city, lat, lng, geocode_failed FROM listings WHERE uid LIKE '%duproprio:1126225%';\" 2>/dev/null"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":5,"cache_creation_input_tokens":246,"cache_read_input_tokens":32140,"cache_creation":{"ephemeral_5m_input_tokens":246,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"c240c647-5f68-4a65-b54a-b1dcb75e3d7a"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01B1bPHDLZrogQ91WRyZvSzA","type":"tool_result","content":"duproprio:1126225|4671 Rue Des Perdrix|Jonquiere Lac Kenogami|46.737384770386|-71.3733209994043|1","is_error":false}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"a940ba37-a5f5-4fb9-93bd-fc05df271c9f","timestamp":"2026-08-25T13:11:11.628Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Running sqlite3 /Users/simon-pierreboucher/apps/immo-ka/d…","usage":{"total_tokens":34491,"tool_uses":18,"duration_ms":22151},"last_tool_name":"Bash","uuid":"d7817352-f3d1-493f-b428-1acdb46e360e","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXHbzMLxg1QCPDAxiEV","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01S78LpSizyhXWm137HDWc1d","name":"Bash","input":{"command":"sqlite3 /Users/simon-pierreboucher/apps/immo-ka/data/immoka.db \".headers on\" \"SELECT uid, address, city, lat, lng, geocode_failed FROM listings WHERE uid LIKE '%duproprio:1126225%';\""},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":7,"cache_creation_input_tokens":2035,"cache_read_input_tokens":32386,"cache_creation":{"ephemeral_5m_input_tokens":2035,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"68bb11d0-a661-4f07-82a9-9380217b1250"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01S78LpSizyhXWm137HDWc1d","type":"tool_result","content":"uid|address|city|lat|lng|geocode_failed\nduproprio:1126225|4671 Rue Des Perdrix|Jonquiere Lac Kenogami|46.737384770386|-71.3733209994043|1","is_error":false}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"c8e11baf-4269-4a23-b8cd-bb379305244e","timestamp":"2026-08-25T13:11:14.312Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Running sqlite3 /Users/simon-pierreboucher/apps/immo-ka/d…","usage":{"total_tokens":34750,"tool_uses":19,"duration_ms":24474},"last_tool_name":"Bash","uuid":"05cc6b4d-f3d2-47e7-ac43-2eaefacabaed","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXHoQhG7TReGejWPALM","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01NUBF9rmDy61EqFhhJWWFrP","name":"Bash","input":{"command":"sqlite3 /Users/simon-pierreboucher/apps/immo-ka/data/immoka.db \"SELECT address, lat, lng, provider, failed FROM geocode_cache WHERE address LIKE '%rue%perdrix%' OR address LIKE '%4671%';\" 2>/dev/null | head -20"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":6,"cache_creation_input_tokens":256,"cache_read_input_tokens":34421,"cache_creation":{"ephemeral_5m_input_tokens":256,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"485fcc4d-2aa3-4875-b3bd-795e292803df"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01NUBF9rmDy61EqFhhJWWFrP","type":"tool_result","content":"12 rue de la perdrix|||nominatim|1\n141 143 rue de la perdrix|45.181848791657|-72.179175728108|adresses_quebec|0\n14671 rue sherbrooke e|45.67844|-73.5024508|nominatim|0\n2 rue des perdrix du lac grace|45.763312757|-74.3156786|adresses_quebec_batch|0\n4667 rue des perdrix|||adresses_quebec_batch|1\n4671 rue des perdrix|||adresses_quebec_batch|1\n4675 rue des perdrix|48.311814736|-71.30269974|adresses_quebec_batch|0\n4715 rue de la perdrix grise|46.738391984|-71.375401419|adresses_quebec_batch|0\nrue de la perdrix saint andre d|45.518278746|-74.276420952|adresses_quebec_batch|0\n2490 rue des perdrix|45.862397652|-72.511092856|adresses_quebec_batch|0\n141 rue de la perdrix|45.182104984|-72.179179617|adresses_quebec_batch|0\nrue des perdrix|45.317942285|-73.749705505|adresses_quebec_batch|0\n2620 rue des perdrix|45.861378566|-72.51192557|adresses_quebec_batch|0\n1030 rue des perdrix|45.531924938|-73.20726515|adresses_quebec_batch|0\n391 rue des perdrix|45.729796604|-74.09843236|adresses_quebec_batch|0\n583 rue des perdrix|45.425785708|-72.702733946|adresses_quebec_batch|0","is_error":false}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"1cafca4c-a1f7-46eb-8235-5de9bd24fd46","timestamp":"2026-08-25T13:11:16.566Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Running sqlite3 /Users/simon-pierreboucher/apps/immo-ka/d…","usage":{"total_tokens":35388,"tool_uses":20,"duration_ms":26027},"last_tool_name":"Bash","uuid":"0a1cd9da-cd3f-41f6-893d-261c6509f427","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXHyGH2zRoRzz1qBYZG","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01UAJDNWeqnXZ6qC5KVfxZaz","name":"Bash","input":{"command":"sqlite3 /Users/simon-pierreboucher/apps/immo-ka/data/immoka.db \"SELECT address, lat, lng, provider, failed FROM geocode_cache WHERE address = '4671 rue des perdrix';\""},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":6,"cache_creation_input_tokens":630,"cache_read_input_tokens":34677,"cache_creation":{"ephemeral_5m_input_tokens":630,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"b202f287-1653-46a1-9533-3fd72a49b985"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01UAJDNWeqnXZ6qC5KVfxZaz","type":"tool_result","content":"4671 rue des perdrix|||adresses_quebec_batch|1","is_error":false}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"d0299df7-f0c2-422d-a62d-61f12ca7136b","timestamp":"2026-08-25T13:11:18.109Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Running python3 << 'EOF'\n# Jonquière est en Saguenay : aut…","usage":{"total_tokens":35577,"tool_uses":21,"duration_ms":29862},"last_tool_name":"Bash","uuid":"a12c034e-b592-4b8c-9823-7ae848ff9f3b","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXJ5nSNpBMbhDqeBDTS","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01PWrQssR59s1TbktdM28zes","name":"Bash","input":{"command":"python3 << 'EOF'\n# Jonquière est en Saguenay : autour de 48.2°N, 71.1°W\n# Les coordonnées trouvées : 46.737, -71.373\n# C'est clairement ailleurs!\n\njonquiere_expected = (48.2, -71.1) # approx\nfound_coords = (46.737384770386, -71.3733209994043)\n\nprint(f\"Jonquière attendue (approx): {jonquiere_expected}\")\nprint(f\"Coordonnées trouvées: {found_coords}\")\n\n# Regardons où c'est :\n# 46.73 N, -71.37 W = c'est du côté de Québec/Saint-Augustin\n# Le connecteur duproprio a peut-être les vraies coordonnées!\n\nprint(\"\\nLes coordonnées trouvées pointent vers la région de Québec\")\nprint(\"Alors que Jonquière (Saguenay) est beaucoup plus au nord (48.2°N)\")\nEOF\n"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":6,"cache_creation_input_tokens":185,"cache_read_input_tokens":35307,"cache_creation":{"ephemeral_5m_input_tokens":185,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"2c4522ae-4015-4f7b-ad27-57e1fadf9ad4"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01PWrQssR59s1TbktdM28zes","type":"tool_result","content":"Jonquière attendue (approx): (48.2, -71.1)\nCoordonnées trouvées: (46.737384770386, -71.3733209994043)\n\nLes coordonnées trouvées pointent vers la région de Québec\nAlors que Jonquière (Saguenay) est beaucoup plus au nord (48.2°N)","is_error":false}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"7f011715-f26f-467f-a156-8ac8d3246ed1","timestamp":"2026-08-25T13:11:21.973Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Running python3 << 'EOF'\n# D'après geocode.py:\n# - _BBOX_QU…","usage":{"total_tokens":36178,"tool_uses":22,"duration_ms":36803},"last_tool_name":"Bash","uuid":"8d4e1ccf-589d-487c-ac83-81d827b70e54","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXJNDu9iE1z59oMhqwD","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_011i52WhA4QcoRA2tgb2Ymne","name":"Bash","input":{"command":"python3 << 'EOF'\n# D'après geocode.py:\n# - _BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n# - _BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00) # reste du Québec\n\n# Pour la ville \"Jonquiere Lac Kenogami\", la clé normalisée est:\ncity_raw = \"Jonquiere Lac Kenogami\"\n# strip_accents((city or \"\").strip().lower()) -> \"jonquiere lac kenogami\"\n# key = \"jonquiere lac kenogami\"\n\n# La fonction _bbox_for() cherche dans _VILLES_QUEBEC:\nvilles_quebec = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\nkey = \"jonquiere lac kenogami\"\n# strip_accents(key) ne change rien, c'est \"jonquiere lac kenogami\"\n# Ce ne correspond PAS aux villes de la boîte QUEBEC\n# Donc on obtient _BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n\n# Le problème : _BBOX_SUD_QC couvre TOUT le Québec, du sud jusqu'à la Côte-Nord!\n# 63.00°N couvre largement Jonquière (~48.2°N)\n\n# Si le géocodeur a trouvé une rue \"4671 rue des perdrix\" à Saint-Augustin \n# (46.73°N, -71.37°W), ça passe le filtre de _BBOX_SUD_QC:\nlat, lng = 46.737384770386, -71.3733209994043\nbbox = (44.50, 63.00, -80.00, -56.00)\n\nin_bbox = bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\nprint(f\"Coords trouvées: ({lat}, {lng})\")\nprint(f\"Bbox: {bbox}\")\nprint(f\"Dans la bbox SUD_QC? {in_bbox}\")\nprint(f\" lat {lat} entre {bbox[0]} et {bbox[1]}? {bbox[0] <= lat <= bbox[1]}\")\nprint(f\" lng {lng} entre {bbox[2]} et {bbox[3]}? {bbox[2] <= lng <= bbox[3]}\")\n\n# Donc la validation par bbox ne suffit pas!\n# Le vrai problème : Jonquière est au Saguenay, pas au Québec (région)\n# Mais la ville est encodée comme \"Jonquiere Lac Kenogami\" (sans région)\n# Et le géocodeur a trouvé une rue ailleurs...\nEOF\n"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":5,"cache_creation_input_tokens":594,"cache_read_input_tokens":35492,"cache_creation":{"ephemeral_5m_input_tokens":594,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"4f41ad14-9d7b-451b-9f9a-1fbafa68c724"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_011i52WhA4QcoRA2tgb2Ymne","type":"tool_result","content":"Coords trouvées: (46.737384770386, -71.3733209994043)\nBbox: (44.5, 63.0, -80.0, -56.0)\nDans la bbox SUD_QC? True\n lat 46.737384770386 entre 44.5 et 63.0? True\n lng -71.3733209994043 entre -80.0 et -56.0? True","is_error":false}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"366198cf-8891-4cfc-b2d7-8b499966b1b1","timestamp":"2026-08-25T13:11:28.897Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Running grep -r \"re.*geocod\\|fix.*geocod\\|recalc.*geocod\\…","usage":{"total_tokens":37133,"tool_uses":23,"duration_ms":38785},"last_tool_name":"Bash","uuid":"4c09c354-1213-40a4-94ec-468881eab0e0","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXJsmQKUQtMpW1URFpK","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Hd6TFd9JGScJUmTW9RUU23","name":"Bash","input":{"command":"grep -r \"re.*geocod\\|fix.*geocod\\|recalc.*geocod\\|reset.*geocod\" /Users/simon-pierreboucher/apps/immo-ka --include=\"*.py\" 2>/dev/null | head -20"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":6,"cache_creation_input_tokens":948,"cache_read_input_tokens":36086,"cache_creation":{"ephemeral_5m_input_tokens":948,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"3f67f55d-09f1-46ac-af65-cff7a5a1e56d"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Hd6TFd9JGScJUmTW9RUU23","type":"tool_result","content":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py: WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py: \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\n/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py: \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py: WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n/Users/simon-pierreboucher/apps/immo-ka/geocode.py: WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n/Users/simon-pierreboucher/apps/immo-ka/geocode.py: \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\n/Users/simon-pierreboucher/apps/immo-ka/geocode.py: \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n/Users/simon-pierreboucher/apps/immo-ka/geocode.py: WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0","is_error":false}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"2cc108e5-75cf-4284-b3e0-fc165e87d33b","timestamp":"2026-08-25T13:11:31.683Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Reading immoka/connectors/duproprio.py","usage":{"total_tokens":37695,"tool_uses":24,"duration_ms":41251},"last_tool_name":"Read","uuid":"67ed9e4d-fe34-403d-9a73-0100443a7c6a","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXK5qBsTMQ8ZLKW2k4y","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_018u3sUxEFuetFqFn56U9F9X","name":"Read","input":{"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/connectors/duproprio.py","limit":200},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":6,"cache_creation_input_tokens":558,"cache_read_input_tokens":37034,"cache_creation":{"ephemeral_5m_input_tokens":558,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"6228334f-2482-4bad-b260-21c2f60a906a"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_018u3sUxEFuetFqFn56U9F9X","type":"tool_result","content":"1\t# -----------------------------------------------------------------------------\n2\t# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n3\t# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n4\t# connectors/duproprio.py : DuProprio (FSBO — vente sans courtier)\n5\t#\n6\t# DuProprio est la grande plateforme québécoise de vente « à vendre par le\n7\t# propriétaire » (sans agence). Segment complémentaire absent de toutes les\n8\t# bannières de courtage. Énumération EXHAUSTIVE via les sitemaps FR par région\n9\t# du Québec (`/sitemaps/fr/-listings.xml.gz`) : l'URL encode déjà\n10\t# région, ville, type et l'id DuProprio (= external_id). La fiche détail\n11\t# (JSON-LD Product) fournit prix, description et galerie ; enrichissement\n12\t# plafonné + cache (comme les autres connecteurs). Scrapfly en secours si le\n13\t# fetch direct est bloqué.\n14\t# -----------------------------------------------------------------------------\n15\tfrom __future__ import annotations\n16\t\n17\timport gzip\n18\timport io\n19\timport os\n20\timport re\n21\t\n22\tfrom .base import BaseConnector\n23\tfrom . import _detailutil as du\n24\tfrom ..normalize import normalize_property_type, parse_price\n25\tfrom ..schema import PropertyListing\n26\t\n27\tSITEMAP_INDEX = \"https://duproprio.com/sitemaps/fr/index.xml.gz\"\n28\tDETAIL_LIMIT = int(os.environ.get(\"IMMOKA_DUPROPRIO_DETAIL_LIMIT\", \"500\"))\n29\tAGENCY = \"DuProprio (sans courtier)\"\n30\t\n31\t_LOC_RE = re.compile(r\"([^<]+)\")\n32\t# /fr///-a-vendre/-\n33\t_URL_RE = re.compile(\n34\t r\"https://duproprio\\.com/fr/([a-z0-9-]+)/([a-z0-9-]+)/([a-z0-9-]+?)-a-vendre/([a-z0-9-]+?)-(\\d{5,})/?$\",\n35\t re.I)\n36\t_PHOTO_RE = re.compile(\n37\t r\"https://photos\\.duproprio\\.com/photos/public/for_sale/\\d+/\\d+/[^\\\"'\\\\ ]+?\\.jpg\", re.I)\n38\t_LDPROD_RE = re.compile(r']+application/ld\\+json[^>]*>(.*?)', re.S | re.I)\n39\t\n40\t\n41\tclass DuProprioConnector(BaseConnector):\n42\t source_id = \"duproprio\"\n43\t request_delay = 0.4\n44\t\n45\t def fetch(self) -> list[PropertyListing]:\n46\t by_id: dict[str, PropertyListing] = {}\n47\t for sm in self._region_listing_sitemaps():\n48\t for url in self._sitemap_locs(sm):\n49\t lst = self._to_listing(url)\n50\t if lst and lst.external_id not in by_id:\n51\t by_id[lst.external_id] = lst\n52\t listings = list(by_id.values())\n53\t du.enrich(self, listings, DETAIL_LIMIT, _parse_dp_detail,\n54\t key=\"v2\", fetch_html=self._fetch_detail)\n55\t return listings\n56\t\n57\t # -- sitemaps --------------------------------------------------------------\n58\t def _region_listing_sitemaps(self) -> list[str]:\n59\t xml = self._get_gz(SITEMAP_INDEX)\n60\t # uniquement les sitemaps d'INSCRIPTIONS par région (Québec)\n61\t return [u for u in _LOC_RE.findall(xml) if u.endswith(\"-listings.xml.gz\")]\n62\t\n63\t def _sitemap_locs(self, url: str) -> list[str]:\n64\t return [u for u in _LOC_RE.findall(self._get_gz(url)) if \"/fr/\" in u]\n65\t\n66\t def _get_gz(self, url: str) -> str:\n67\t try:\n68\t raw = self.get(url).content\n69\t except Exception:\n70\t return \"\"\n71\t try:\n72\t return gzip.GzipFile(fileobj=io.BytesIO(raw)).read().decode(\"utf-8\", \"ignore\")\n73\t except OSError:\n74\t return raw.decode(\"utf-8\", \"ignore\") # déjà décompressé\n75\t\n76\t # -- mapping ---------------------------------------------------------------\n77\t def _to_listing(self, url: str) -> PropertyListing | None:\n78\t m = _URL_RE.match(url.strip())\n79\t if not m:\n80\t return None\n81\t region_s, city_s, type_s, addr_s, did = m.groups()\n82\t return PropertyListing(\n83\t source=self.source_id, external_id=did, url=url,\n84\t title=_deslug(addr_s),\n85\t address=_deslug(re.sub(r\"^(hab|com|ter|multi|imm)-\", \"\", addr_s)),\n86\t city=_deslug(city_s),\n87\t region=_region(region_s),\n88\t property_type=normalize_property_type(type_s.replace(\"-\", \" \")),\n89\t agency=AGENCY, broker_name=\"\",\n90\t )\n91\t\n92\t def _fetch_detail(self, url: str) -> str:\n93\t html = \"\"\n94\t try:\n95\t html = self.get(url).text\n96\t except Exception:\n97\t html = \"\"\n98\t if \"application/ld+json\" not in html: # bloqué -> Scrapfly (ASP)\n99\t try:\n100\t html = self.get_scrapfly(url, render_js=False, asp=True)\n101\t except Exception:\n102\t pass\n103\t return html\n104\t\n105\t\n106\t# ---------------------------------------------------------------------------\n107\tdef _parse_dp_detail(html: str) -> dict:\n108\t import json, html as _h\n109\t out: dict = {}\n110\t for block in _LDPROD_RE.findall(html):\n111\t try:\n112\t d = json.loads(block)\n113\t except ValueError:\n114\t continue\n115\t if isinstance(d, dict) and d.get(\"@type\") == \"Product\":\n116\t off = d.get(\"offers\") or {}\n117\t p = parse_price(str(off.get(\"price\") or \"\")) if off.get(\"price\") else None\n118\t if p:\n119\t out[\"price\"] = p\n120\t out[\"price_label\"] = f\"{p:,.0f} $\".replace(\",\", \" \")\n121\t if d.get(\"description\"):\n122\t out[\"description\"] = _h.unescape(str(d[\"description\"])).strip()[:4000]\n123\t break\n124\t # coordonnées GPS du JSON-LD Residence (geo) — géocodage gratuit\n125\t for block in _LDPROD_RE.findall(html):\n126\t try:\n127\t d = json.loads(block)\n128\t except ValueError:\n129\t continue\n130\t geo = d.get(\"geo\") if isinstance(d, dict) else None\n131\t if isinstance(geo, dict):\n132\t try:\n133\t lat, lng = float(geo.get(\"latitude\")), float(geo.get(\"longitude\"))\n134\t except (TypeError, ValueError):\n135\t continue\n136\t if 44.5 <= lat <= 63.0 and -80.0 <= lng <= -56.0:\n137\t out[\"lat\"], out[\"lng\"] = lat, lng\n138\t break\n139\t # galerie COMPLÈTE : le JSON « \"photos\":[{...}] » de la page liste toutes les\n140\t # photos (le JSON-LD/HTML n'en montre qu'une). On prend la plus haute résolution.\n141\t imgs, seen = [], set()\n142\t mgal = re.search(r'\"photos\"\\s*:\\s*(\\[\\{.*?\\}\\])', html, re.S)\n143\t if mgal:\n144\t try:\n145\t for ph in json.loads(mgal.group(1)):\n146\t fmt = ph.get(\"formats\") or {}\n147\t rel = fmt.get(\"1600\") or fmt.get(\"1024\") or fmt.get(\"600\")\n148\t if rel:\n149\t u = rel if rel.startswith(\"http\") else f\"https://photos.duproprio.com/{rel.lstrip('/')}\"\n150\t if u not in seen:\n151\t seen.add(u); imgs.append(u)\n152\t except ValueError:\n153\t pass\n154\t if not imgs: # repli : URLs photos dans le HTML brut\n155\t for u in _PHOTO_RE.findall(html):\n156\t if u not in seen:\n157\t seen.add(u); imgs.append(u)\n158\t if imgs:\n159\t out[\"images\"] = imgs\n160\t text = re.sub(r\"\\s+\", \" \", _h_unescape(html))\n161\t mb = re.search(r\"(\\d+)\\s*chambre\", text, re.I)\n162\t if mb:\n163\t out[\"bedrooms\"] = int(mb.group(1))\n164\t ms = re.search(r\"(\\d+)\\s*salle[s]?\\s*de\\s*bain\", text, re.I)\n165\t if ms:\n166\t out[\"bathrooms\"] = int(ms.group(1))\n167\t\n168\t details: dict = {}\n169\t features: list[str] = []\n170\t\n171\t # --- Dimensions des pièces (tableau des pièces) --------------------------\n172\t rooms = []\n173\t for blk in re.split(r'listing-rooms-details__table__item-container',\n174\t html)[1:41]:\n175\t blk = blk.split(\"item-container\")[0]\n176\t def cell(marker):\n177\t m = re.search(marker + r'[^>]*>(.*?)', blk, re.S)\n178\t return re.sub(r\"\\s+\", \" \", _h_unescape(m.group(1))).strip() if m else \"\"\n179\t nom = cell(r'item--room\"')\n180\t niveau = cell(r'item--storey\"').replace(\"Étage :\", \"\").strip()\n181\t dim = cell(r'item--dimensions\"').replace(\"Dimensions :\", \"\").strip()\n182\t rev = cell(r'item--flooring\"').replace(\"Plancher :\", \"\").strip()\n183\t if nom:\n184\t rooms.append({\"nom\": nom, \"niveau\": niveau,\n185\t \"dimensions\": dim, \"revetement\": rev})\n186\t if rooms:\n187\t details[\"pieces\"] = rooms[:30]\n188\t\n189\t # --- Caractéristiques de la propriété (rangées pointillées) ---------------\n190\t for lm, vm in re.findall(\n191\t r'listing-box__dotted-row\">\\s*
(.*?)
\\s*
\\s*
\\s*'\n192\t r'
(.*?)
', html, re.S):\n193\t label = re.sub(r\"\\s+\", \" \", _h_unescape(lm)).strip()\n194\t value = re.sub(r\"\\s+\", \" \", _h_unescape(vm)).strip()\n195\t if not label or not value or label == \"Prix demandé\":\n196\t continue\n197\t if label == \"Année de construction\":\n198\t my = re.search(r\"(19|20)\\d{2}\", value)\n199\t if my:\n200\t out[\"year_built\"] = int(my.group(0))\n\n\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n\n"}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"4ac2354b-8ecb-437c-9dad-6fb8604f1fd6","timestamp":"2026-08-25T13:11:33.306Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Running grep -n \"region\\|city\\|saguenay\\|jonquiere\" /User…","usage":{"total_tokens":37697,"tool_uses":25,"duration_ms":41533},"last_tool_name":"Bash","uuid":"9b39f223-9d7d-47e6-9497-63667b12acc2","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXK5qBsTMQ8ZLKW2k4y","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01PYJJziHGCiGHqjTZh8DyEw","name":"Bash","input":{"command":"grep -n \"region\\|city\\|saguenay\\|jonquiere\" /Users/simon-pierreboucher/apps/immo-ka/immoka/connectors/duproprio.py"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":6,"cache_creation_input_tokens":558,"cache_read_input_tokens":37034,"cache_creation":{"ephemeral_5m_input_tokens":558,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"2d4be697-3ce8-4f33-80e5-c5f1bef3f993"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01PYJJziHGCiGHqjTZh8DyEw","type":"tool_result","content":"9:# du Québec (`/sitemaps/fr/-listings.xml.gz`) : l'URL encode déjà\n32:# /fr///-a-vendre/-\n47: for sm in self._region_listing_sitemaps():\n58: def _region_listing_sitemaps(self) -> list[str]:\n81: region_s, city_s, type_s, addr_s, did = m.groups()\n86: city=_deslug(city_s),\n87: region=_region(region_s),\n239:def _region(slug: str) -> str:","is_error":false}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"dbc06ebf-3202-4202-944a-be88c7dc0605","timestamp":"2026-08-25T13:11:33.606Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Reading immoka/connectors/duproprio.py","usage":{"total_tokens":41395,"tool_uses":26,"duration_ms":43216},"last_tool_name":"Read","uuid":"da62a606-6cb7-4376-ba85-13adcf5a58c8","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXKE8WXCbt8XzxBYkU3","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01RkEdnANKFEWPdo6KQKGupX","name":"Read","input":{"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/connectors/duproprio.py","offset":235},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":7,"cache_creation_input_tokens":3693,"cache_read_input_tokens":37592,"cache_creation":{"ephemeral_5m_input_tokens":3693,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"b5f9dc24-33fd-4b24-ae8e-996c9465be75"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01RkEdnANKFEWPdo6KQKGupX","type":"tool_result","content":"235\tdef _deslug(s: str) -> str:\n236\t return re.sub(r\"\\s+\", \" \", s.replace(\"-\", \" \").replace(\"_\", \" \")).strip().title()\n237\t\n238\t\n239\tdef _region(slug: str) -> str:\n240\t r = _deslug(slug)\n241\t return (r.replace(\"Quebec\", \"Québec\").replace(\"Montreal\", \"Montréal\")\n242\t .replace(\"Monteregie\", \"Montérégie\").replace(\"Laurentides\", \"Laurentides\")\n243\t .replace(\"Mauricie\", \"Mauricie\").replace(\"Estrie\", \"Estrie\"))\n244\t\n\n\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n\n"}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"fbf44c94-2cb3-4ba0-94ad-4eef057dd185","timestamp":"2026-08-25T13:11:35.271Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Running grep -n \"class PropertyListing\\|def finalize\" /Us…","usage":{"total_tokens":41771,"tool_uses":27,"duration_ms":44576},"last_tool_name":"Bash","uuid":"0520d117-edee-412f-86c4-dd3f1a653852","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXKM5U2pcJ44o3sae5z","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_012Rut848xoH4CKWaYPh2gK3","name":"Bash","input":{"command":"grep -n \"class PropertyListing\\|def finalize\" /Users/simon-pierreboucher/apps/immo-ka/immoka/schema.py | head -10"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":6,"cache_creation_input_tokens":375,"cache_read_input_tokens":41285,"cache_creation":{"ephemeral_5m_input_tokens":375,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"bf2b4c94-0969-4e93-8c08-d869ef7e8a7d"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_012Rut848xoH4CKWaYPh2gK3","type":"tool_result","content":"40:class PropertyListing:\n84: def finalize(self) -> \"PropertyListing\":","is_error":false}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"b567eb79-73f2-4365-acf0-05e9cbc1053c","timestamp":"2026-08-25T13:11:36.658Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Reading immoka/schema.py","usage":{"total_tokens":42064,"tool_uses":28,"duration_ms":45547},"last_tool_name":"Read","uuid":"e7048e54-eb69-4bf6-b5cf-d705e603003c","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXKSzAnxgisdfPk5eny","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01MoLpd8RctXxmYABoGMmMub","name":"Read","input":{"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/schema.py","offset":40,"limit":100},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":5,"cache_creation_input_tokens":270,"cache_read_input_tokens":41660,"cache_creation":{"ephemeral_5m_input_tokens":270,"ephemeral_1h_input_tokens":0},"output_tokens":24,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"3be644e5-502f-400d-9951-56f0c1ef3e0f"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01MoLpd8RctXxmYABoGMmMub","type":"tool_result","content":"40\tclass PropertyListing:\n41\t \"\"\"Propriété à vendre standardisée Immo-Ka.\"\"\"\n42\t\n43\t source: str # id de l'agence (voir data/sources.json)\n44\t external_id: str # identifiant chez la source (souvent le n° Centris/MLS)\n45\t url: str # page de la propriété chez la source\n46\t title: str = \"\" # ex. \"Maison à étages à vendre — Lévis\"\n47\t address: str = \"\" # adresse civique\n48\t sector: str = \"\" # quartier/arrondissement\n49\t city: str = \"\" # Québec, Lévis, Montréal…\n50\t region: str = \"\" # région administrative (Capitale-Nationale…)\n51\t property_type: str = \"\" # Maison, Condo, Duplex, Terrain… (canonique)\n52\t price: float | None = None # prix demandé ($ CAD)\n53\t price_label: str = \"\" # texte original (ex. \"459 000 $ +tx\")\n54\t bedrooms: int | None = None # chambres\n55\t bathrooms: int | None = None # salles de bains\n56\t powder_rooms: int | None = None # salles d'eau\n57\t area_sqft: float | None = None # superficie habitable (pi²)\n58\t lot_sqft: float | None = None # superficie du terrain (pi²)\n59\t year_built: int | None = None\n60\t mls: str = \"\" # numéro Centris/MLS si affiché par la source\n61\t status: str = \"a-vendre\" # a-vendre | vendu | conditionnel\n62\t broker_name: str = \"\" # courtier inscripteur\n63\t broker_phone: str = \"\"\n64\t agency: str = \"\" # sous-agence / bureau (ex. « Royal LePage Altitude »,\n65\t # « Groupe Sutton - Synergie ») — affichage des\n66\t # Sources par sous-agence\n67\t description: str = \"\"\n68\t features: list[str] = field(default_factory=list) # caractéristiques (texte source)\n69\t details: dict = field(default_factory=dict) # champs structurés (JSON)\n70\t images: list[str] = field(default_factory=list) # URLs absolues\n71\t lat: float | None = None\n72\t lng: float | None = None\n73\t\n74\t @property\n75\t def uid(self) -> str:\n76\t return f\"{self.source}:{self.external_id}\"\n77\t\n78\t def content_hash(self) -> str:\n79\t \"\"\"Hash du contenu pour la détection de changements (pseudo-webhook).\"\"\"\n80\t payload = asdict(self)\n81\t blob = json.dumps(payload, sort_keys=True, ensure_ascii=False)\n82\t return hashlib.sha256(blob.encode(\"utf-8\")).hexdigest()\n83\t\n84\t def finalize(self) -> \"PropertyListing\":\n85\t \"\"\"Applique la normalisation commune. Appelé par le pipeline d'ingestion.\n86\t\n87\t Idempotent ; ne remplace jamais une valeur explicite du connecteur.\n88\t \"\"\"\n89\t self.title = clean_title(self.title)\n90\t self.address = clean_address(self.address)\n91\t self.city = (self.city or \"\").strip()\n92\t self.property_type = normalize_property_type(self.property_type)\n93\t self.description = clean_description(self.description)\n94\t\n95\t # galerie : URLs valides seulement, placeholders retirés, doublons\n96\t # (même photo en deux tailles) dédupliqués — voir immoka/imgaudit.py\n97\t from .imgaudit import clean_gallery\n98\t self.images = clean_gallery(self.images)\n99\t\n100\t if self.price is None:\n101\t self.price = parse_price(self.price_label)\n102\t if self.price_label and price_is_from(self.price_label):\n103\t self.details.setdefault(\"price_from\", True)\n104\t\n105\t # promotion details -> colonnes : les champs structurés de la fiche\n106\t # (tableau Centris) priment sur l'extraction de texte libre ci-dessous\n107\t if not self.property_type:\n108\t for k in (\"Type de propriété\", \"Genre de propriété\"):\n109\t if self.details.get(k):\n110\t self.property_type = normalize_property_type(str(self.details[k]))\n111\t break\n112\t if self.year_built is None and self.details.get(\"Année de construction\"):\n113\t self.year_built = parse_year(self.details[\"Année de construction\"])\n114\t if self.area_sqft is None and self.details.get(\"Superficie habitable\"):\n115\t self.area_sqft = parse_area_sqft(str(self.details[\"Superficie habitable\"]))\n116\t if self.lot_sqft is None and self.details.get(\"Superficie du terrain\"):\n117\t self.lot_sqft = parse_lot_sqft(str(self.details[\"Superficie du terrain\"]))\n118\t\n119\t texte = \" \".join(filter(None, (self.title, self.description,\n120\t \" \".join(self.features))))\n121\t if self.bedrooms is None or self.bathrooms is None:\n122\t beds, baths = extract_bedrooms_bathrooms(texte)\n123\t if self.bedrooms is None:\n124\t self.bedrooms = beds\n125\t if self.bathrooms is None:\n126\t self.bathrooms = baths\n127\t if self.area_sqft is None:\n128\t self.area_sqft = parse_area_sqft(texte)\n129\t if self.lot_sqft is None and \"terrain\" in strip_accents(texte.lower()):\n130\t self.lot_sqft = parse_lot_sqft(texte)\n131\t self.year_built = parse_int(self.year_built)\n132\t\n133\t # sous-agence : à défaut, on retombe sur le courtier/agence inscripteur\n134\t if not self.agency:\n135\t self.agency = self.broker_name\n136\t\n137\t # coordonnées fournies par la source : rejeter tout point hors de la\n138\t # province (lat/lng inversés, 0/0, coquilles)\n139\t if self.lat is not None and self.lng is not None:\n\n\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n\n"}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"6e1c4fe1-badd-4a43-a395-236bf22e1b6b","timestamp":"2026-08-25T13:11:37.604Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Reading immoka/schema.py","usage":{"total_tokens":44045,"tool_uses":29,"duration_ms":46918},"last_tool_name":"Read","uuid":"3c42833e-b029-4bd7-9fbc-d5c1bfdc07a6","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXKX5V9Aw81fLrF4L9e","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_013MnrMrD8oYgjdDtXLAthzb","name":"Read","input":{"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/schema.py","offset":139,"limit":30},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":6,"cache_creation_input_tokens":1962,"cache_read_input_tokens":41930,"cache_creation":{"ephemeral_5m_input_tokens":1962,"ephemeral_1h_input_tokens":0},"output_tokens":18,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"a63c5caf-7a70-423e-90d5-650fbe9f5613"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013MnrMrD8oYgjdDtXLAthzb","type":"tool_result","content":"139\t if self.lat is not None and self.lng is not None:\n140\t if not (44.5 <= self.lat <= 63.0 and -80.0 <= self.lng <= -56.0):\n141\t self.lat = self.lng = None\n142\t\n143\t return self\n144\t\n\n\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n\n"}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"58b5296c-4623-4c93-a18b-b73561a14872","timestamp":"2026-08-25T13:11:38.972Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Running sqlite3 /Users/simon-pierreboucher/apps/immo-ka/d…","usage":{"total_tokens":44328,"tool_uses":30,"duration_ms":50190},"last_tool_name":"Bash","uuid":"84238da1-e5b7-4fd5-a873-1e785a586533","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-haiku-4-5-20251001","id":"msg_011CePXKdvEqySoH5JajWP2c","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01B8XgtHGg31f4QLQ1FGGVZ1","name":"Bash","input":{"command":"sqlite3 /Users/simon-pierreboucher/apps/immo-ka/data/immoka.db << 'EOF'\n-- Cherchons les autres \"rue des perdrix\" pour voir laquelle est mal placée\nSELECT address, lat, lng, city FROM listings \nWHERE address LIKE '%rue des perdrix%' \nORDER BY lat DESC;\nEOF\n"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":6,"cache_creation_input_tokens":281,"cache_read_input_tokens":43892,"cache_creation":{"ephemeral_5m_input_tokens":281,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"b6419659-9502-4784-9b39-aa3f186bd1b7"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01B8XgtHGg31f4QLQ1FGGVZ1","type":"tool_result","content":"4667 Rue Des Perdrix|48.3124502075353|-71.301495125162|Jonquiere Lac Kenogami\n4675 Rue des Perdrix|48.311814736|-71.30269974|Saguenay\n4671 Rue Des Perdrix|46.737384770386|-71.3733209994043|Jonquiere Lac Kenogami\nRue des Perdrix|46.2985|-75.9913|Messines\nRue des Perdrix|46.29845553|-75.99131899|Messines\n18 Rue des Perdrix|46.2966|-75.9928|Messines\n18 Rue des Perdrix|46.2965846|-75.9928336|Messines\n18 Rue des Perdrix|46.296584|-75.992833|Messines\n2490 Rue des Perdrix|45.862397652|-72.511092856|Drummondville\n2490 Rue des Perdrix|45.862397652|-72.511092856|Drummondville\n2490 Rue des Perdrix|45.86239|-72.51109|Drummondville\n2490 Rue des Perdrix|45.862389|-72.511092|Drummondville\n2490, Rue des Perdrix|45.8623886108398|-72.5110931396484|Drummondville\n2620 Rue Des Perdrix|45.861378566|-72.51192557|Drummondville\n2620 Rue des Perdrix|45.861375|-72.5119246|Drummondville\n2620 Rue des Perdrix|45.86137|-72.511924|Drummondville\n2620 Rue des Perdrix|45.86137|-72.511924|Drummondville\n2620 Rue des Perdrix|45.86137|-72.511924|Drummondville\n2 Rue Des Perdrix Du Lac Grace|45.763312757|-74.3156786|Gore\n391 Rue des Perdrix|45.72989778|-74.09855129|Saint-Colomban\n1030 Rue des Perdrix|45.531917|-73.207264|Otterburn Park\n19 Rue Des Perdrix|45.426225|-75.772662|Gatineau Hull\n19 Rue des Perdrix|45.426225|-75.772662|Gatineau\n19 Rue des Perdrix|45.4262|-75.7727|Gatineau (Hull)\n583 Rue Des Perdrix|45.425785708|-72.702733946|Granby\nrue des Perdrix|45.317942285|-73.749705505|Mercier\n50 rue des Perdrix|45.3172435|-73.7455296|Mercier\n18 Rue Des Perdrix|||Messines\n2620 Rue Des Perdrix|||Drummondville","is_error":false}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"7ce0818b-9472-4e8f-84d0-978c76ba4eae","timestamp":"2026-08-25T13:11:42.442Z"}} {"type":"claude","event":{"type":"system","subtype":"task_progress","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","description":"Running sqlite3 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'%Perdrix%');\nEOF\n"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":6,"cache_creation_input_tokens":981,"cache_read_input_tokens":44173,"cache_creation":{"ephemeral_5m_input_tokens":981,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"3a62d4bb-dc61-41b7-b15b-662aa17f8525"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01RJh2fywiCdDmpz6ErLHdMn","type":"tool_result","content":"46.768498728|-71.346593478\n|\n|\n46.737384770386|-71.3733209994043\n45.52914841|-73.75889093\n45.52914841|-73.75889093","is_error":false}]},"parent_tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"41d668ba-d088-4566-a494-95880874be72","timestamp":"2026-08-25T13:11:45.940Z"}} {"type":"claude","event":{"type":"system","subtype":"task_notification","task_id":"a848b62bfd7b36047","tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","status":"completed","output_file":"","summary":"Trouver le moteur de géocodage","usage":{"total_tokens":45776,"tool_uses":31,"duration_ms":84230},"uuid":"55252b02-5255-4755-bf1a-eb415fc6497e","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01QEiqru3y7CyYP7d3YJPD1R","type":"tool_result","content":[{"type":"text","text":"OK ! Créons un résumé concis de mes findings.\n\n---\n\n## Rapport: Moteur de géocodage Immo-Ka et bug de l'annonce duproprio:1126225\n\n### 1. FICHIERS ET LIGNES DU CODE DE GÉOCODAGE\n\n**Fichier principal:** `/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py` (et `/Users/simon-pierreboucher/apps/immo-ka/geocode.py` – copie identique)\n\nClés fonctions :\n- `class Geocoder` (lignes 64-215)\n - `resolve()` (lignes 176-215) : adresse → (lat, lng), avec validation bbox\n - `_query_adresses_quebec()` (lignes 122-150) : requête API Adresses Québec (MERN, ArcGIS)\n - `_query_nominatim()` (lignes 100-120) : requête API Nominatim (OpenStreetMap)\n - `_attempts()` (lignes 152-174) : stratégies de requête (civique+rue → libre → rue seule)\n - `_build_query()` (lignes 91-98) : construction de la requête avec ville, région, Canada\n\n- `run_batch()` (lignes 283-382) : géocodage EN LOT via Adresses Québec (~35 requêtes pour ~75k listings au lieu de dizaines de milliers). C'est le mode favori.\n- `run()` (lignes 218-275) : mode 1-par-1 (plus lent, avec repli Nominatim)\n\nPoint de déclenchement: `/Users/simon-pierreboucher/apps/immo-ka/run.py` (lignes 49-54)\n```bash\npython run.py geocode [n] # run_batch() — recommandé\npython run.py geocode1 [n] # run() — ancien mode\n```\n\nDéclenché automatiquement après sync dans `watch()`: `/Users/simon-pierreboucher/apps/immo-ka/immoka/ingest.py` (lignes 86-88)\n\n---\n\n### 2. CONSTRUCTION DE L'ADRESSE\n\nDans `_build_query()` (geocode.py lignes 91-98) :\n```python\nq = self._clean(address) # nettoyage (unités, abréviations…)\nif city and city.lower() not in q.lower():\n q += f\", {city}\" # ajoute la ville si absente\nif \"quebec\" not in q.lower():\n q += \", Québec\" # ajoute région si absent\nreturn q + \", Canada\" # format final\n```\n\nChamps utilisés (depuis `listings` BD) :\n- `address` : adresse civique (4671 Rue Des Perdrix)\n- `city` : ville (Jonquiere Lac Kenogami) ← **CHAMP CRITIQUE pour éviter les ambiguïtés**\n\n**Problème identifié :** La clé normalisée pour le cache (`norm_key()`, lignes 57-62) retire les accents/casse/espaces et efface le n° d'appartement. Pour \"4671 Rue Des Perdrix\" extrait de l'URL DuProprio, elle devient \"4671 rue des perdrix\" — une clé éphémère qui sera partagée si plusieurs rues portent ce numéro (probablement unique par commune, mais la requête API peut ne pas respecter cette localité).\n\n---\n\n### 3. STOCKAGE DES COORDONNÉES\n\nTable `listings` (immoka/db.py lignes 30-69) :\n- Colonnes: `lat REAL`, `lng REAL`, `geocode_failed INTEGER DEFAULT 0`\n- Clé primaire: `uid` (format: `source:external_id`, ex. `duproprio:1126225`)\n\nCache géocodage: Table `geocode_cache` (lignes 105-112) :\n- Clé: `address TEXT PRIMARY KEY` (adresse normalisée)\n- Colonnes: `lat`, `lng`, `provider` (adresses_quebec, nominatim, adresses_quebec_batch), `failed`, `ts`\n\nL'annonce `duproprio:1126225` a :\n- `address = \"4671 Rue Des Perdrix\"` (tel qu'extrait de l'URL)\n- `city = \"Jonquiere Lac Kenogami\"`\n- `lat = 46.737384770386, lng = -71.3733209994043` (coordonnées ERRONÉES de Saint-Augustin/Messines)\n- `geocode_failed = 1` (flag d'échec du géocodeur)\n\n**Note :** Ces coordonnées (46.737, -71.373) ne viennent PAS du géocodeur (qui aurait setté `geocode_failed=0` si succès). Elles proviennent du JSON-LD de DuProprio lui-même (connecteur duproprio.py lignes 124-138 : parse du `geo.latitude/longitude` du Product JSON-LD), validé dans `schema.finalize()` (schema.py ligne 140).\n\n---\n\n### 4. VALIDATION DU RÉSULTAT\n\n**Bounding box (immoka/geocode.py lignes 37-49) :**\n```python\n_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00) # reste du Québec (province entière!)\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n```\n\nValidation (lignes 195-204, `resolve()`) :\n```python\nif c is not None and _in_bbox(*c, bbox):\n coords = c\n```\n\n**LE BUG:** Jonquière n'est pas dans `_VILLES_QUEBEC` (qui contient uniquement Québec, Lévis, St-Augustin, L'Ancienne-Lorette) → utilise `_BBOX_SUD_QC` = (44.50 à 63.00°N, -80 à -56°W). Cette bbox couvre TOUT le Québec et accepte n'importe quelle rue des Perdrix trouvée n'importe où dans la province. **Pas de comparaison de nom de ville.**\n\nAdresses Québec (MERN, ArcGIS) retourne un `Score` (seuil `AQ_MIN_SCORE = 75`), mais c'est insuffisant si l'API trouve une correspondance partielle (ex. rue correcte, mais mauvaise ville).\n\n---\n\n### 5. DÉCLENCHEMENT DU GÉOCODAGE\n\n**Sync → Watch → Batch :**\n1. `python run.py sync [sources]` → `immoka/ingest.py:run()` (exécute les connecteurs)\n2. `python run.py watch [minutes]` → boucle infinie, syn + géocodage batch automatique\n - Ligne 88: `geocode.run_batch()` appliqué après chaque sync\n3. Condition de géocodage (`run_batch()`, ligne 291) : `WHERE active=1 AND lat IS NULL AND ...`\n - Géocode seulement si `lat IS NULL` (pas de coordonnées)\n - L'annonce 1126225 a des coordonnées (fournies par DuProprio) → **N'SERA PAS RE-GÉOCODÉE par le batch**\n\n**Pas de script CLI existant pour re-géocoder des annonces spécifiques** — seules les annonces sans `lat/lng` sont traitées. Corriger l'annonce 1126225 nécessiterait:\n- Soit `UPDATE listings SET lat=NULL WHERE uid='duproprio:1126225'` + relancer `geocode`\n- Soit `DELETE FROM geocode_cache WHERE address='4671 rue des perdrix'` + relancer\n\n---\n\n### 6. DIAGNOSTIC PRÉCIS DU BUG duproprio:1126225\n\nL'annonce \"4671, rue des Perdrix, Jonquière (Lac-Kénogami)\" est géocodée à Saint-Augustin (46.74°N, -71.37°W) au lieu de Saguenay (48.2°N, -71.1°W) **car :**\n\n1. **Source des mauvaises coordonnées :** Le JSON-LD Product de DuProprio lui-même encode lat/lng erronées (46.737, -71.373). Ces coordonnées passent la validation `finalize()` (sont dans la province).\n\n2. **Géocodeur ne re-vérifie pas :** Une fois que DuProprio fournit `lat/lng`, le géocodeur (`resolve()`) ne sera appelé que si `lat IS NULL`. Ici, `lat IS NOT NULL` → pas de ré-tentative.\n\n3. **Pas de fallback géocodage-ville :** Même si le géocodeur essayait, la clé normalisée \"4671 rue des perdrix\" est ambiguë sur tout le Québec. La bbox `_BBOX_SUD_QC` accepte n'importe quelle rue des Perdrix. Il n'y a pas de validation croisée du nom de ville (`\"Jonquiere Lac Kenogami\"` vs résultat du géocodeur).\n\n**Autres annonces rue des Perdrix à Jonquière :**\n- 4667 : 48.312°N, -71.301°W ✓ Correct (SAGUENAY)\n- 4675 : 48.311°N, -71.302°W ✓ Correct (SAGUENAY)\n- 4671 : 46.737°N, -71.373°W ✗ SAINT-AUGUSTIN\n\nLes coordonnées correctes seraient ~48.31°N, -71.30°W (Saguenay), pas 46.74°N, -71.37°W.\n\n---\n\n### RÉSUMÉ CONCIS\n\n| Aspect | Détail |\n|--------|--------|\n| **Moteur** | Adresses Québec (MERN/ArcGIS) + repli Nominatim |\n| **API** | https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/Adresse_Geocodage/GeocodeServer/findAddressCandidates |\n| **Fichiers clés** | immoka/geocode.py (176-215 resolve, 122-150 AQ query), immoka/ingest.py (86-88 auto-trigger) |\n| **Adresse construite** | address + city + \"Québec, Canada\" |\n| **Coordonnées stockées** | listings.lat/lng, geocode_cache.lat/lng |\n| **Validation** | Bounding box par ville (_BBOX_QUEBEC si Québec/Lévis/St-Aug, sinon _BBOX_SUD_QC = 44.5-63°N, -80--56°W) — **pas de validation de nom de ville** |\n| **Déclenchement** | Auto après `sync` dans `watch()` ; manuel via `python run.py geocode [n]` |\n| **Script re-géocode** | Aucun CLI — faut manuellement `UPDATE lat=NULL + relancer geocode` |\n| **Bug 1126225** | DuProprio fournit mauvaises coords (46.74, -71.37) = Saint-Aug au lieu de Saguenay (48.31, -71.30); géocodeur ne ré-tente pas car lat/lng != NULL |"}]}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"2bc3b07e-310d-4dbb-a40c-92b581cbf92e","timestamp":"2026-08-25T13:12:16.283Z","tool_use_result":{"status":"completed","prompt":"Dans le repo /Users/simon-pierreboucher/apps/immo-ka (app immobilière Node/JS), trouve le moteur de géocodage : le code qui transforme une adresse d'annonce en coordonnées lat/lng (probablement via Nominatim, Google, Mapbox, Photon ou autre). Thoroughness: medium.\n\nJe cherche à corriger un bug : l'annonce \"4671, rue des Perdrix, Jonquière (Lac-Kénogami)\" (source duproprio, uid duproprio:1126225) est géocodée à Saint-Augustin au lieu de Saguenay — le géocodeur a probablement matché une rue des Perdrix ailleurs sans valider la ville.\n\nRapporte :\n1. Le(s) fichier(s) + numéros de ligne du code de géocodage (construction de la requête, appel API, sélection du résultat, validation éventuelle).\n2. Comment l'adresse est construite (quels champs : rue, ville, région, code postal).\n3. Où les coordonnées sont stockées (colonne BD, table).\n4. S'il existe déjà une validation du résultat (bounding box, comparaison de ville, etc.).\n5. Comment le géocodage est déclenché (au sync ? script batch ? à la volée ?).\n\nRecherche aussi rapidement s'il y a un script/CLI pour re-géocoder des fiches existantes. Rapport concis avec chemins et lignes précises.","agentId":"a848b62bfd7b36047","agentType":"Explore","content":[{"type":"text","text":"OK ! Créons un résumé concis de mes findings.\n\n---\n\n## Rapport: Moteur de géocodage Immo-Ka et bug de l'annonce duproprio:1126225\n\n### 1. FICHIERS ET LIGNES DU CODE DE GÉOCODAGE\n\n**Fichier principal:** `/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py` (et `/Users/simon-pierreboucher/apps/immo-ka/geocode.py` – copie identique)\n\nClés fonctions :\n- `class Geocoder` (lignes 64-215)\n - `resolve()` (lignes 176-215) : adresse → (lat, lng), avec validation bbox\n - `_query_adresses_quebec()` (lignes 122-150) : requête API Adresses Québec (MERN, ArcGIS)\n - `_query_nominatim()` (lignes 100-120) : requête API Nominatim (OpenStreetMap)\n - `_attempts()` (lignes 152-174) : stratégies de requête (civique+rue → libre → rue seule)\n - `_build_query()` (lignes 91-98) : construction de la requête avec ville, région, Canada\n\n- `run_batch()` (lignes 283-382) : géocodage EN LOT via Adresses Québec (~35 requêtes pour ~75k listings au lieu de dizaines de milliers). C'est le mode favori.\n- `run()` (lignes 218-275) : mode 1-par-1 (plus lent, avec repli Nominatim)\n\nPoint de déclenchement: `/Users/simon-pierreboucher/apps/immo-ka/run.py` (lignes 49-54)\n```bash\npython run.py geocode [n] # run_batch() — recommandé\npython run.py geocode1 [n] # run() — ancien mode\n```\n\nDéclenché automatiquement après sync dans `watch()`: `/Users/simon-pierreboucher/apps/immo-ka/immoka/ingest.py` (lignes 86-88)\n\n---\n\n### 2. CONSTRUCTION DE L'ADRESSE\n\nDans `_build_query()` (geocode.py lignes 91-98) :\n```python\nq = self._clean(address) # nettoyage (unités, abréviations…)\nif city and city.lower() not in q.lower():\n q += f\", {city}\" # ajoute la ville si absente\nif \"quebec\" not in q.lower():\n q += \", Québec\" # ajoute région si absent\nreturn q + \", Canada\" # format final\n```\n\nChamps utilisés (depuis `listings` BD) :\n- `address` : adresse civique (4671 Rue Des Perdrix)\n- `city` : ville (Jonquiere Lac Kenogami) ← **CHAMP CRITIQUE pour éviter les ambiguïtés**\n\n**Problème identifié :** La clé normalisée pour le cache (`norm_key()`, lignes 57-62) retire les accents/casse/espaces et efface le n° d'appartement. Pour \"4671 Rue Des Perdrix\" extrait de l'URL DuProprio, elle devient \"4671 rue des perdrix\" — une clé éphémère qui sera partagée si plusieurs rues portent ce numéro (probablement unique par commune, mais la requête API peut ne pas respecter cette localité).\n\n---\n\n### 3. STOCKAGE DES COORDONNÉES\n\nTable `listings` (immoka/db.py lignes 30-69) :\n- Colonnes: `lat REAL`, `lng REAL`, `geocode_failed INTEGER DEFAULT 0`\n- Clé primaire: `uid` (format: `source:external_id`, ex. `duproprio:1126225`)\n\nCache géocodage: Table `geocode_cache` (lignes 105-112) :\n- Clé: `address TEXT PRIMARY KEY` (adresse normalisée)\n- Colonnes: `lat`, `lng`, `provider` (adresses_quebec, nominatim, adresses_quebec_batch), `failed`, `ts`\n\nL'annonce `duproprio:1126225` a :\n- `address = \"4671 Rue Des Perdrix\"` (tel qu'extrait de l'URL)\n- `city = \"Jonquiere Lac Kenogami\"`\n- `lat = 46.737384770386, lng = -71.3733209994043` (coordonnées ERRONÉES de Saint-Augustin/Messines)\n- `geocode_failed = 1` (flag d'échec du géocodeur)\n\n**Note :** Ces coordonnées (46.737, -71.373) ne viennent PAS du géocodeur (qui aurait setté `geocode_failed=0` si succès). Elles proviennent du JSON-LD de DuProprio lui-même (connecteur duproprio.py lignes 124-138 : parse du `geo.latitude/longitude` du Product JSON-LD), validé dans `schema.finalize()` (schema.py ligne 140).\n\n---\n\n### 4. VALIDATION DU RÉSULTAT\n\n**Bounding box (immoka/geocode.py lignes 37-49) :**\n```python\n_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00) # reste du Québec (province entière!)\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n```\n\nValidation (lignes 195-204, `resolve()`) :\n```python\nif c is not None and _in_bbox(*c, bbox):\n coords = c\n```\n\n**LE BUG:** Jonquière n'est pas dans `_VILLES_QUEBEC` (qui contient uniquement Québec, Lévis, St-Augustin, L'Ancienne-Lorette) → utilise `_BBOX_SUD_QC` = (44.50 à 63.00°N, -80 à -56°W). Cette bbox couvre TOUT le Québec et accepte n'importe quelle rue des Perdrix trouvée n'importe où dans la province. **Pas de comparaison de nom de ville.**\n\nAdresses Québec (MERN, ArcGIS) retourne un `Score` (seuil `AQ_MIN_SCORE = 75`), mais c'est insuffisant si l'API trouve une correspondance partielle (ex. rue correcte, mais mauvaise ville).\n\n---\n\n### 5. DÉCLENCHEMENT DU GÉOCODAGE\n\n**Sync → Watch → Batch :**\n1. `python run.py sync [sources]` → `immoka/ingest.py:run()` (exécute les connecteurs)\n2. `python run.py watch [minutes]` → boucle infinie, syn + géocodage batch automatique\n - Ligne 88: `geocode.run_batch()` appliqué après chaque sync\n3. Condition de géocodage (`run_batch()`, ligne 291) : `WHERE active=1 AND lat IS NULL AND ...`\n - Géocode seulement si `lat IS NULL` (pas de coordonnées)\n - L'annonce 1126225 a des coordonnées (fournies par DuProprio) → **N'SERA PAS RE-GÉOCODÉE par le batch**\n\n**Pas de script CLI existant pour re-géocoder des annonces spécifiques** — seules les annonces sans `lat/lng` sont traitées. Corriger l'annonce 1126225 nécessiterait:\n- Soit `UPDATE listings SET lat=NULL WHERE uid='duproprio:1126225'` + relancer `geocode`\n- Soit `DELETE FROM geocode_cache WHERE address='4671 rue des perdrix'` + relancer\n\n---\n\n### 6. DIAGNOSTIC PRÉCIS DU BUG duproprio:1126225\n\nL'annonce \"4671, rue des Perdrix, Jonquière (Lac-Kénogami)\" est géocodée à Saint-Augustin (46.74°N, -71.37°W) au lieu de Saguenay (48.2°N, -71.1°W) **car :**\n\n1. **Source des mauvaises coordonnées :** Le JSON-LD Product de DuProprio lui-même encode lat/lng erronées (46.737, -71.373). Ces coordonnées passent la validation `finalize()` (sont dans la province).\n\n2. **Géocodeur ne re-vérifie pas :** Une fois que DuProprio fournit `lat/lng`, le géocodeur (`resolve()`) ne sera appelé que si `lat IS NULL`. Ici, `lat IS NOT NULL` → pas de ré-tentative.\n\n3. **Pas de fallback géocodage-ville :** Même si le géocodeur essayait, la clé normalisée \"4671 rue des perdrix\" est ambiguë sur tout le Québec. La bbox `_BBOX_SUD_QC` accepte n'importe quelle rue des Perdrix. Il n'y a pas de validation croisée du nom de ville (`\"Jonquiere Lac Kenogami\"` vs résultat du géocodeur).\n\n**Autres annonces rue des Perdrix à Jonquière :**\n- 4667 : 48.312°N, -71.301°W ✓ Correct (SAGUENAY)\n- 4675 : 48.311°N, -71.302°W ✓ Correct (SAGUENAY)\n- 4671 : 46.737°N, -71.373°W ✗ SAINT-AUGUSTIN\n\nLes coordonnées correctes seraient ~48.31°N, -71.30°W (Saguenay), pas 46.74°N, -71.37°W.\n\n---\n\n### RÉSUMÉ CONCIS\n\n| Aspect | Détail |\n|--------|--------|\n| **Moteur** | Adresses Québec (MERN/ArcGIS) + repli Nominatim |\n| **API** | https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/Adresse_Geocodage/GeocodeServer/findAddressCandidates |\n| **Fichiers clés** | immoka/geocode.py (176-215 resolve, 122-150 AQ query), immoka/ingest.py (86-88 auto-trigger) |\n| **Adresse construite** | address + city + \"Québec, Canada\" |\n| **Coordonnées stockées** | listings.lat/lng, geocode_cache.lat/lng |\n| **Validation** | Bounding box par ville (_BBOX_QUEBEC si Québec/Lévis/St-Aug, sinon _BBOX_SUD_QC = 44.5-63°N, -80--56°W) — **pas de validation de nom de ville** |\n| **Déclenchement** | Auto après `sync` dans `watch()` ; manuel via `python run.py geocode [n]` |\n| **Script re-géocode** | Aucun CLI — faut manuellement `UPDATE lat=NULL + relancer geocode` |\n| **Bug 1126225** | DuProprio fournit mauvaises coords (46.74, -71.37) = Saint-Aug au lieu de Saguenay (48.31, -71.30); géocodeur ne ré-tente pas car lat/lng != NULL 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-----------------------------------------------------------------------------\n2\t# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n3\t# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n4\t# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)\n5\t# - cache persistant (table geocode_cache) : une adresse n'est géocodée\n6\t# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce\n7\t# - politesse : 1 requête/seconde max, User-Agent identifiable\n8\t# - validation : les coordonnées doivent tomber dans la région attendue\n9\t# (bounding box par ville), sinon flag geocode_failed — jamais de\n10\t# coordonnées bidon\n11\t# -----------------------------------------------------------------------------\n12\tfrom __future__ import annotations\n13\t\n14\timport json\n15\timport sqlite3\n16\t\n17\timport re\n18\timport time\n19\t\n20\timport requests\n21\t\n22\tfrom . import db\n23\tfrom .normalize import strip_accents\n24\t\n25\tNOMINATIM_URL = \"https://nominatim.openstreetmap.org/search\"\n26\t# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre\n27\t# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)\n28\tAQ_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n29\t \"Adresse_Geocodage/GeocodeServer/findAddressCandidates\")\n30\tAQ_MIN_SCORE = 75\n31\t# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête\n32\t# User-Agent contient des accents (latin-1)\n33\tUSER_AGENT = \"ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)\"\n34\tREQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s\n35\tREQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte\n36\tRETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours\n37\t\n38\t# Bounding boxes (lat_min, lat_max, lng_min, lng_max)\n39\t_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n40\t# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord\n41\t# et la Gaspésie (expansion provinciale) — même boîte que schema.finalize()\n42\t_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n43\t\n44\t_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n45\t \"l'ancienne-lorette\", \"ancienne-lorette\"}\n46\t\n47\t\n48\tdef _bbox_for(city: str) -> tuple[float, float, float, float]:\n49\t key = strip_accents((city or \"\").strip().lower())\n50\t return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n51\t\n52\t\n53\tdef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n54\t return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n55\t\n56\t\n57\tdef norm_key(address: str) -> str:\n58\t \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\"\n59\t s = strip_accents((address or \"\").lower())\n60\t s = re.sub(r\"\\b(?:app?t?|appartement|unite|suite|#)\\.?\\s*[\\w-]+\\b\", \" \", s)\n61\t s = re.sub(r\"[^a-z0-9]+\", \" \", s)\n62\t return re.sub(r\"\\s+\", \" \", s).strip()\n63\t\n64\t\n65\tclass Geocoder:\n66\t def __init__(self, con) -> None:\n67\t self.con = con\n68\t self.session = requests.Session()\n69\t self.session.headers[\"User-Agent\"] = USER_AGENT\n70\t self._last = 0.0\n71\t\n72\t @staticmethod\n73\t def _clean(address: str) -> str:\n74\t \"\"\"Nettoyages qui aident Nominatim sur les adresses québécoises.\"\"\"\n75\t s = address.strip()\n76\t # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique\n77\t s = re.sub(r\"^(\\d+)-(\\d+)\\s\", r\"\\2 \", s)\n78\t # « 6275 et 6375 boulevard X » -> premier civique\n79\t s = re.sub(r\"^(\\d+)\\s+et\\s+\\d+\\s\", r\"\\1 \", s)\n80\t # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu\n81\t s = re.sub(r\"montr[ée]al\\s*-\\s*\", \"\", s, flags=re.I)\n82\t # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau\n83\t s = re.sub(r\",?\\s*(?:bureau|suite|local|app\\.?|apt\\.?)\\s*[\\w-]+\\b\", \"\", s, flags=re.I)\n84\t # « Vanier (Québec) » -> « Vanier, Québec »\n85\t s = re.sub(r\"\\s*\\((qu[ée]bec)\\)\", r\", \\1\", s, flags=re.I)\n86\t # abréviations cardinales : « Rue Salaberry O » -> « Ouest »\n87\t s = re.sub(r\"\\bO\\.?(?=,|\\s*$)\", \"Ouest\", s)\n88\t s = re.sub(r\"\\bE\\.?(?=,|\\s*$)\", \"Est\", s)\n89\t return s\n90\t\n91\t def _build_query(self, address: str, city: str) -> str:\n92\t q = self._clean(address)\n93\t key = strip_accents(q.lower())\n94\t if city and strip_accents(city.lower()) not in key:\n95\t q += f\", {city}\"\n96\t if \"quebec\" not in strip_accents(q.lower()) and \"qc\" not in q.lower():\n97\t q += \", Québec\"\n98\t return q + \", Canada\"\n99\t\n100\t def _query_nominatim(self, params: dict) -> tuple[float, float] | None:\n101\t \"\"\"Une requête Nominatim, throttlée.\"\"\"\n102\t wait = REQUEST_DELAY - (time.time() - self._last)\n103\t if wait > 0:\n104\t time.sleep(wait)\n105\t try:\n106\t resp = self.session.get(NOMINATIM_URL, params={\n107\t \"format\": \"jsonv2\", \"limit\": 1, \"countrycodes\": \"ca\", **params,\n108\t }, timeout=20)\n109\t self._last = time.time()\n110\t resp.raise_for_status()\n111\t hits = resp.json()\n112\t except Exception:\n113\t self._last = time.time()\n114\t return None\n115\t if not hits:\n116\t return None\n117\t try:\n118\t return float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n119\t except (KeyError, ValueError):\n120\t return None\n121\t\n122\t def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] | None:\n123\t \"\"\"Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).\n124\t\n125\t Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE\n126\t pour éviter les correspondances approximatives sur une autre rue.\n127\t \"\"\"\n128\t premier = self._clean(address).split(\",\")[0].strip()\n129\t ville = (city or \"Québec\").strip()\n130\t wait = REQUEST_DELAY_AQ - (time.time() - self._last)\n131\t if wait > 0:\n132\t time.sleep(wait)\n133\t try:\n134\t resp = self.session.get(AQ_URL, params={\n135\t \"SingleLine\": f\"{premier}, {ville}\",\n136\t \"f\": \"json\", \"outSR\": 4326, \"maxLocations\": 1,\n137\t }, timeout=20)\n138\t self._last = time.time()\n139\t resp.raise_for_status()\n140\t cands = resp.json().get(\"candidates\") or []\n141\t except Exception:\n142\t self._last = time.time()\n143\t return None\n144\t if not cands or cands[0].get(\"score\", 0) < AQ_MIN_SCORE:\n145\t return None\n146\t loc = cands[0].get(\"location\") or {}\n147\t try:\n148\t return float(loc[\"y\"]), float(loc[\"x\"])\n149\t except (KeyError, ValueError):\n150\t return None\n151\t\n152\t def _attempts(self, address: str, city: str) -> list[dict]:\n153\t \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n154\t\n155\t 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n156\t 2) recherche libre complète\n157\t 3) structurée rue seule -> centroïde de rue (repli acceptable pour la\n158\t carte quand le numéro civique est absent d'OpenStreetMap)\n159\t \"\"\"\n160\t premier = self._clean(address).split(\",\")[0].strip()\n161\t ville = (city or \"\").strip()\n162\t if not ville:\n163\t k = strip_accents(address.lower())\n164\t ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n165\t commun = {\"city\": ville, \"state\": \"Québec\", \"country\": \"Canada\"}\n166\t\n167\t tries: list[dict] = []\n168\t m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n169\t if m:\n170\t tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n171\t tries.append({\"q\": self._build_query(address, city)})\n172\t if m:\n173\t tries.append({\"street\": m.group(2), **commun})\n174\t return tries\n175\t\n176\t def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n177\t \"\"\"Adresse -> (lat, lng), via cache puis Nominatim. None si introuvable.\"\"\"\n178\t key = norm_key(address)\n179\t if not key or len(key) < 6:\n180\t return None\n181\t row = self.con.execute(\n182\t \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n183\t (key,)).fetchone()\n184\t if row is not None:\n185\t if not row[\"failed\"]:\n186\t return (row[\"lat\"], row[\"lng\"])\n187\t if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n188\t return None # échec récent : ne pas marteler l'API\n189\t\n190\t bbox = _bbox_for(city)\n191\t coords = None\n192\t # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n193\t # limite stricte. Nominatim (1 req/s) seulement en repli.\n194\t provider = \"adresses_quebec\"\n195\t c = self._query_adresses_quebec(address, city)\n196\t if c is not None and _in_bbox(*c, bbox):\n197\t coords = c\n198\t if coords is None:\n199\t provider = \"nominatim\"\n200\t for params in self._attempts(address, city):\n201\t c = self._query_nominatim(params)\n202\t if c is not None and _in_bbox(*c, bbox):\n203\t coords = c\n204\t break\n205\t ok = coords is not None\n206\t self.con.execute(\n207\t \"INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)\"\n208\t \" VALUES (?,?,?,?,?,?)\"\n209\t \" ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,\"\n210\t \" lng=excluded.lng, provider=excluded.provider,\"\n211\t \" failed=excluded.failed, ts=excluded.ts\",\n212\t (key, coords[0] if ok else None, coords[1] if ok else None,\n213\t provider, 0 if ok else 1, time.time()))\n214\t self.con.commit()\n215\t return coords if ok else None\n216\t\n217\t\n218\tdef run(limit: int | None = None) -> dict:\n219\t \"\"\"Géocode les annonces actives sans coordonnées, par adresse unique.\n220\t\n221\t `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de\n222\t cache sont gratuits et toujours appliqués).\n223\t \"\"\"\n224\t con = db.connect()\n225\t geo = Geocoder(con)\n226\t rows = con.execute(\n227\t \"\"\"SELECT uid, address, city FROM listings\n228\t WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n229\t AND dup_hidden=0\n230\t ORDER BY address\"\"\").fetchall()\n231\t\n232\t # regrouper par immeuble (adresse normalisée)\n233\t groupes: dict[str, list] = {}\n234\t for r in rows:\n235\t groupes.setdefault(norm_key(r[\"address\"]), []).append(r)\n236\t\n237\t done = failed = requests_made = 0\n238\t for key, members in groupes.items():\n239\t if not key:\n240\t continue\n241\t cached = con.execute(\n242\t \"SELECT failed FROM geocode_cache WHERE address=?\", (key,)).fetchone()\n243\t if cached is None:\n244\t if limit is not None and requests_made >= limit:\n245\t continue\n246\t requests_made += 1\n247\t try:\n248\t coords = geo.resolve(members[0][\"address\"], members[0][\"city\"])\n249\t if coords:\n250\t for r in members:\n251\t con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n252\t (coords[0], coords[1], r[\"uid\"]))\n253\t done += len(members)\n254\t else:\n255\t # introuvable/hors zone : flag ; jamais de coordonnées bidon\n256\t for r in members:\n257\t con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\",\n258\t (r[\"uid\"],))\n259\t failed += len(members)\n260\t con.commit()\n261\t except sqlite3.OperationalError:\n262\t # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,\n263\t # elle sera reprise au prochain passage — jamais crasher tout le run.\n264\t try:\n265\t con.rollback()\n266\t except sqlite3.Error:\n267\t pass\n268\t time.sleep(1.0)\n269\t continue\n270\t\n271\t con.close()\n272\t stats = {\"geocoded\": done, \"failed\": failed,\n273\t \"unique_addresses\": len(groupes), \"api_requests\": requests_made}\n274\t print(f\"[immo-ka] geocode {stats}\")\n275\t return stats\n276\t\n277\t\n278\tAQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n279\t \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\n280\tBATCH_SIZE = 200\n281\t\n282\t\n283\tdef run_batch(limit: int | None = None) -> dict:\n284\t \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n285\t adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de\n286\t milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim).\"\"\"\n287\t con = db.connect()\n288\t geo = Geocoder(con) # pour réutiliser _clean / bbox\n289\t rows = con.execute(\n290\t \"\"\"SELECT uid, address, city FROM listings\n291\t WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n292\t AND dup_hidden=0 ORDER BY address\"\"\").fetchall()\n293\t # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache\n294\t uniq: dict[str, dict] = {}\n295\t for r in rows:\n296\t k = norm_key(r[\"address\"])\n297\t if not k or len(k) < 6:\n298\t continue\n299\t u = uniq.setdefault(k, {\"address\": r[\"address\"], \"city\": r[\"city\"],\n300\t \"members\": []})\n301\t u[\"members\"].append(r[\"uid\"])\n302\t pending = []\n303\t for k, u in uniq.items():\n304\t c = con.execute(\"SELECT lat,lng,failed FROM geocode_cache WHERE address=?\",\n305\t (k,)).fetchone()\n306\t if c is not None and not c[\"failed\"]: # déjà résolu : appliquer direct\n307\t for uid in u[\"members\"]:\n308\t con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n309\t (c[\"lat\"], c[\"lng\"], uid))\n310\t continue\n311\t if c is not None and c[\"failed\"]:\n312\t continue\n313\t pending.append((k, u))\n314\t con.commit()\n315\t if limit is not None:\n316\t pending = pending[:limit]\n317\t\n318\t session = requests.Session()\n319\t session.headers[\"User-Agent\"] = USER_AGENT\n320\t done = failed = 0\n321\t for i in range(0, len(pending), BATCH_SIZE):\n322\t chunk = pending[i:i + BATCH_SIZE]\n323\t records = {\"records\": [\n324\t {\"attributes\": {\"OBJECTID\": j,\n325\t \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n326\t f\"{(u['city'] or 'Québec').strip()}\"}}\n327\t for j, (_k, u) in enumerate(chunk)]}\n328\t try:\n329\t # POST obligatoire : le param `addresses` (JSON de N records) est trop\n330\t # long pour une URL GET dès quelques dizaines d'adresses.\n331\t resp = session.post(AQ_BATCH_URL, data={\n332\t \"addresses\": json.dumps(records, ensure_ascii=False),\n333\t \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n334\t locs = resp.json().get(\"locations\", [])\n335\t except Exception as e:\n336\t print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n337\t time.sleep(1.0)\n338\t continue\n339\t by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n340\t for j, (k, u) in enumerate(chunk):\n341\t loc = by_id.get(j)\n342\t coords = None\n343\t if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n344\t lc = loc.get(\"location\") or {}\n345\t try:\n346\t cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n347\t if _in_bbox(*cand, _bbox_for(u[\"city\"])):\n348\t coords = cand\n349\t except (KeyError, ValueError, TypeError):\n350\t coords = None\n351\t try:\n352\t if coords:\n353\t for uid in u[\"members\"]:\n354\t con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n355\t (coords[0], coords[1], uid))\n356\t con.execute(\n357\t \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n358\t \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n359\t \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n360\t \" failed=0, ts=excluded.ts\",\n361\t (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n362\t done += len(u[\"members\"])\n363\t else:\n364\t for uid in u[\"members\"]:\n365\t con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n366\t con.execute(\n367\t \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n368\t \" VALUES (?,?,?,?,1,?) ON CONFLICT(address) DO UPDATE SET\"\n369\t \" failed=1, ts=excluded.ts\",\n370\t (k, None, None, \"adresses_quebec_batch\", time.time()))\n371\t failed += len(u[\"members\"])\n372\t con.commit()\n373\t except sqlite3.OperationalError:\n374\t try: con.rollback()\n375\t except sqlite3.Error: pass\n376\t time.sleep(1.0)\n377\t print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n378\t f\"(résolues {done}, échecs {failed})\")\n379\t con.close()\n380\t stats = {\"geocoded\": done, \"failed\": failed, \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n381\t print(f\"[immo-ka] geocode-batch {stats}\")\n382\t return stats\n383\t"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ed12881f-214d-472f-8b9c-67708b416e43","timestamp":"2026-08-25T13:12:28.203Z","tool_use_result":{"type":"text","file":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","content":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)\n# - cache persistant (table geocode_cache) : une adresse n'est géocodée\n# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce\n# - politesse : 1 requête/seconde max, User-Agent identifiable\n# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport sqlite3\n\nimport re\nimport time\n\nimport requests\n\nfrom . import db\nfrom .normalize import strip_accents\n\nNOMINATIM_URL = \"https://nominatim.openstreetmap.org/search\"\n# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre\n# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)\nAQ_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/findAddressCandidates\")\nAQ_MIN_SCORE = 75\n# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête\n# User-Agent contient des accents (latin-1)\nUSER_AGENT = \"ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)\"\nREQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s\nREQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte\nRETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours\n\n# Bounding boxes (lat_min, lat_max, lng_min, lng_max)\n_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord\n# et la Gaspésie (expansion provinciale) — même boîte que schema.finalize()\n_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n\n_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n\n\ndef norm_key(address: str) -> str:\n \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\"\n s = strip_accents((address or \"\").lower())\n s = re.sub(r\"\\b(?:app?t?|appartement|unite|suite|#)\\.?\\s*[\\w-]+\\b\", \" \", s)\n s = re.sub(r\"[^a-z0-9]+\", \" \", s)\n return re.sub(r\"\\s+\", \" \", s).strip()\n\n\nclass Geocoder:\n def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0\n\n @staticmethod\n def _clean(address: str) -> str:\n \"\"\"Nettoyages qui aident Nominatim sur les adresses québécoises.\"\"\"\n s = address.strip()\n # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique\n s = re.sub(r\"^(\\d+)-(\\d+)\\s\", r\"\\2 \", s)\n # « 6275 et 6375 boulevard X » -> premier civique\n s = re.sub(r\"^(\\d+)\\s+et\\s+\\d+\\s\", r\"\\1 \", s)\n # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu\n s = re.sub(r\"montr[ée]al\\s*-\\s*\", \"\", s, flags=re.I)\n # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau\n s = re.sub(r\",?\\s*(?:bureau|suite|local|app\\.?|apt\\.?)\\s*[\\w-]+\\b\", \"\", s, flags=re.I)\n # « Vanier (Québec) » -> « Vanier, Québec »\n s = re.sub(r\"\\s*\\((qu[ée]bec)\\)\", r\", \\1\", s, flags=re.I)\n # abréviations cardinales : « Rue Salaberry O » -> « Ouest »\n s = re.sub(r\"\\bO\\.?(?=,|\\s*$)\", \"Ouest\", s)\n s = re.sub(r\"\\bE\\.?(?=,|\\s*$)\", \"Est\", s)\n return s\n\n def _build_query(self, address: str, city: str) -> str:\n q = self._clean(address)\n key = strip_accents(q.lower())\n if city and strip_accents(city.lower()) not in key:\n q += f\", {city}\"\n if \"quebec\" not in strip_accents(q.lower()) and \"qc\" not in q.lower():\n q += \", Québec\"\n return q + \", Canada\"\n\n def _query_nominatim(self, params: dict) -> tuple[float, float] | None:\n \"\"\"Une requête Nominatim, throttlée.\"\"\"\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"format\": \"jsonv2\", \"limit\": 1, \"countrycodes\": \"ca\", **params,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None\n if not hits:\n return None\n try:\n return float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n except (KeyError, ValueError):\n return None\n\n def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).\n\n Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE\n pour éviter les correspondances approximatives sur une autre rue.\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"Québec\").strip()\n wait = REQUEST_DELAY_AQ - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(AQ_URL, params={\n \"SingleLine\": f\"{premier}, {ville}\",\n \"f\": \"json\", \"outSR\": 4326, \"maxLocations\": 1,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n cands = resp.json().get(\"candidates\") or []\n except Exception:\n self._last = time.time()\n return None\n if not cands or cands[0].get(\"score\", 0) < AQ_MIN_SCORE:\n return None\n loc = cands[0].get(\"location\") or {}\n try:\n return float(loc[\"y\"]), float(loc[\"x\"])\n except (KeyError, ValueError):\n return None\n\n def _attempts(self, address: str, city: str) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) recherche libre complète\n 3) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n commun = {\"city\": ville, \"state\": \"Québec\", \"country\": \"Canada\"}\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis Nominatim. None si introuvable.\"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n bbox = _bbox_for(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if c is not None and _in_bbox(*c, bbox):\n coords = c\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city):\n c = self._query_nominatim(params)\n if c is not None and _in_bbox(*c, bbox):\n coords = c\n break\n ok = coords is not None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?)\"\n \" ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,\"\n \" lng=excluded.lng, provider=excluded.provider,\"\n \" failed=excluded.failed, ts=excluded.ts\",\n (key, coords[0] if ok else None, coords[1] if ok else None,\n provider, 0 if ok else 1, time.time()))\n self.con.commit()\n return coords if ok else None\n\n\ndef run(limit: int | None = None) -> dict:\n \"\"\"Géocode les annonces actives sans coordonnées, par adresse unique.\n\n `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de\n cache sont gratuits et toujours appliqués).\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0\n ORDER BY address\"\"\").fetchall()\n\n # regrouper par immeuble (adresse normalisée)\n groupes: dict[str, list] = {}\n for r in rows:\n groupes.setdefault(norm_key(r[\"address\"]), []).append(r)\n\n done = failed = requests_made = 0\n for key, members in groupes.items():\n if not key:\n continue\n cached = con.execute(\n \"SELECT failed FROM geocode_cache WHERE address=?\", (key,)).fetchone()\n if cached is None:\n if limit is not None and requests_made >= limit:\n continue\n requests_made += 1\n try:\n coords = geo.resolve(members[0][\"address\"], members[0][\"city\"])\n if coords:\n for r in members:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], r[\"uid\"]))\n done += len(members)\n else:\n # introuvable/hors zone : flag ; jamais de coordonnées bidon\n for r in members:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\",\n (r[\"uid\"],))\n failed += len(members)\n con.commit()\n except sqlite3.OperationalError:\n # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,\n # elle sera reprise au prochain passage — jamais crasher tout le run.\n try:\n con.rollback()\n except sqlite3.Error:\n pass\n time.sleep(1.0)\n continue\n\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed,\n \"unique_addresses\": len(groupes), \"api_requests\": requests_made}\n print(f\"[immo-ka] geocode {stats}\")\n return stats\n\n\nAQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200\n\n\ndef run_batch(limit: int | None = None) -> dict:\n \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de\n milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim).\"\"\"\n con = db.connect()\n geo = Geocoder(con) # pour réutiliser _clean / bbox\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0 ORDER BY address\"\"\").fetchall()\n # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache\n uniq: dict[str, dict] = {}\n for r in rows:\n k = norm_key(r[\"address\"])\n if not k or len(k) < 6:\n continue\n u = uniq.setdefault(k, {\"address\": r[\"address\"], \"city\": r[\"city\"],\n \"members\": []})\n u[\"members\"].append(r[\"uid\"])\n pending = []\n for k, u in uniq.items():\n c = con.execute(\"SELECT lat,lng,failed FROM geocode_cache WHERE address=?\",\n (k,)).fetchone()\n if c is not None and not c[\"failed\"]: # déjà résolu : appliquer direct\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (c[\"lat\"], c[\"lng\"], uid))\n continue\n if c is not None and c[\"failed\"]:\n continue\n pending.append((k, u))\n con.commit()\n if limit is not None:\n pending = pending[:limit]\n\n session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n if _in_bbox(*cand, _bbox_for(u[\"city\"])):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,1,?) ON CONFLICT(address) DO UPDATE SET\"\n \" failed=1, ts=excluded.ts\",\n (k, None, None, \"adresses_quebec_batch\", time.time()))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, échecs {failed})\")\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed, \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats\n","numLines":383,"startLine":1,"totalLines":383}}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXNNoymZvHYGnWqomNY","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01RtaDMwtRnLp94g4Q1bQuEF","name":"Bash","input":{"command":"sqlite3 ~/apps/immo-ka/data/immoka.db \"SELECT uid,address,city,region,lat,lng,geocode_failed FROM listings WHERE uid='duproprio:1126225';\" 2>/dev/null || ls ~/apps/immo-ka/data/","description":"Vérifier l'état BD de l'annonce buggée"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":4669,"cache_read_input_tokens":33940,"cache_creation":{"ephemeral_5m_input_tokens":4669,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"8a7d3a44-2183-4075-a31f-bc721392185a"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01RtaDMwtRnLp94g4Q1bQuEF","type":"tool_result","content":"duproprio:1126225|4671 Rue Des Perdrix|Jonquiere Lac Kenogami|Saguenay Lac Saint Jean|46.737384770386|-71.3733209994043|1","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"808a04d6-e031-4299-8f9e-79e85a9c32cc","timestamp":"2026-08-25T13:12:29.775Z","tool_use_result":{"stdout":"duproprio:1126225|4671 Rue Des Perdrix|Jonquiere Lac Kenogami|Saguenay Lac Saint Jean|46.737384770386|-71.3733209994043|1","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"e558ce42-1d92-4b6f-8fe1-608f730555a8","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXPNcMLXF2ftnUbQ3hx","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":8442,"cache_read_input_tokens":38609,"cache_creation":{"ephemeral_5m_input_tokens":8442,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"111c8814-9910-483b-9167-6b87757aa020"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXPNcMLXF2ftnUbQ3hx","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":8442,"cache_read_input_tokens":38609,"cache_creation":{"ephemeral_5m_input_tokens":8442,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"d03e2a3c-4e97-4f37-a3bd-3a91f4405a75"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXPNcMLXF2ftnUbQ3hx","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_0162NiZ9GZcPN5DtWveELErL","name":"Bash","input":{"command":"curl -s \"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/Adresse_Geocodage/GeocodeServer/findAddressCandidates\" --get --data-urlencode \"SingleLine=4671 Rue Des Perdrix, Jonquiere Lac Kenogami\" --data \"f=json&outSR=4326&maxLocations=5\" -H \"User-Agent: ImmoKaBot/1.0\" | python3 -m json.tool | head -60","description":"Tester AQ avec la ville brute DuProprio"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":8442,"cache_read_input_tokens":38609,"cache_creation":{"ephemeral_5m_input_tokens":8442,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"cb0c19e9-2550-4083-871e-ab599d09c7d6"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0162NiZ9GZcPN5DtWveELErL","type":"tool_result","content":"{\n \"spatialReference\": {\n \"wkid\": 4326,\n \"latestWkid\": 4326\n },\n \"candidates\": []\n}","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"569f5cb4-2014-49c9-8912-b15f96a68bef","timestamp":"2026-08-25T13:12:53.157Z","tool_use_result":{"stdout":"{\n \"spatialReference\": {\n 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{"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01BZH1QP4gxA9x6zb4KTFJjH","type":"tool_result","content":"6:# DuProprio est la grande plateforme québécoise de vente « à vendre par le\n124: # coordonnées GPS du JSON-LD Residence (geo) — géocodage gratuit\n130: geo = d.get(\"geo\") if isinstance(d, dict) else None\n131: if isinstance(geo, dict):\n133: lat, lng = float(geo.get(\"latitude\")), float(geo.get(\"longitude\"))\n136: if 44.5 <= lat <= 63.0 and -80.0 <= lng <= -56.0:\n137: out[\"lat\"], out[\"lng\"] = lat, lng"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"6f5b1459-f7aa-4be8-8126-09ad3ef6c98a","timestamp":"2026-08-25T13:12:56.387Z","tool_use_result":{"mode":"content","numFiles":0,"filenames":[],"content":"6:# DuProprio est la grande plateforme québécoise de vente « à vendre par le\n124: # coordonnées GPS du JSON-LD Residence (geo) — géocodage gratuit\n130: geo = d.get(\"geo\") if isinstance(d, dict) else None\n131: if isinstance(geo, dict):\n133: lat, lng = float(geo.get(\"latitude\")), float(geo.get(\"longitude\"))\n136: if 44.5 <= lat <= 63.0 and -80.0 <= lng <= -56.0:\n137: out[\"lat\"], out[\"lng\"] = lat, lng","numLines":7}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"d2ee25f7-2e2a-4b33-857e-1c8e614d2c6c","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} 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perdrix|||adresses_quebec_batch|1|2026-08-12 21:30:24\n4675 rue des perdrix|48.311814736|-71.30269974|adresses_quebec_batch|0|2026-08-12 21:30:24\n4715 rue de la perdrix grise|46.738391984|-71.375401419|adresses_quebec_batch|0|2026-08-12 21:30:26\n6 av de la perdrix|47.099158351|-70.347759787|adresses_quebec_batch|0|2026-08-12 21:30:59\n8 chemin des perdrix|||adresses_quebec_batch|1|2026-08-12 21:31:29\nch de la perdrix|46.210455812|-74.392684836|adresses_quebec_batch|0|2026-08-12 21:31:54\nrue de la perdrix saint andre d|45.518278746|-74.276420952|adresses_quebec_batch|0|2026-08-12 21:32:01\n2490 rue des perdrix|45.862397652|-72.511092856|adresses_quebec_batch|0|2026-08-13 02:46:21\n83 ch de la perdrix|45.399330431|-70.983396124|adresses_quebec_batch|0|2026-08-13 02:46:27\n141 rue de la perdrix|45.182104984|-72.179179617|adresses_quebec_batch|0|2026-08-13 08:56:11\n54 chemin de la perdrix|46.209467365|-74.39435253|adresses_quebec_batch|0|2026-08-13 08:56:32\nchemin de la 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la perdrix|||nominatim|1|2026-08-12 19:11:03\n141 143 rue de la perdrix|45.181848791657|-72.179175728108|adresses_quebec|0|2026-08-12 19:54:32\n15 chemin de la perdrix|45.583339999834|-75.674730493858|adresses_quebec|0|2026-08-12 20:06:44\n167 ch des perdrix|46.774650987584|-75.917043060225|adresses_quebec|0|2026-08-12 21:09:03\n2 rue des perdrix du lac grace|45.763312757|-74.3156786|adresses_quebec_batch|0|2026-08-12 21:28:35\n23 chemin de la perdrix|45.583618134|-75.675854132|adresses_quebec_batch|0|2026-08-12 21:29:01\n3 avenue de la perdrix|47.099806981|-70.348390409|adresses_quebec_batch|0|2026-08-12 21:29:31\n4667 rue des perdrix|||adresses_quebec_batch|1|2026-08-12 21:30:24\n4671 rue des perdrix|||adresses_quebec_batch|1|2026-08-12 21:30:24\n4675 rue des perdrix|48.311814736|-71.30269974|adresses_quebec_batch|0|2026-08-12 21:30:24\n4715 rue de la perdrix grise|46.738391984|-71.375401419|adresses_quebec_batch|0|2026-08-12 21:30:26\n6 av de la 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perdrix|45.861378566|-72.51192557|adresses_quebec_batch|0|2026-08-13 14:06:47\n1030 rue des perdrix|45.531924938|-73.20726515|adresses_quebec_batch|0|2026-08-17 03:50:25\n391 rue des perdrix|45.729796604|-74.09843236|adresses_quebec_batch|0|2026-08-17 03:50:33\n394 ch de la perdrix|||adresses_quebec_batch|1|2026-08-17 03:50:33\n583 rue des perdrix|45.425785708|-72.702733946|adresses_quebec_batch|0|2026-08-23 17:47:01","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXRLAKhwfYRmypJAxQz","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01ST8ugVymVY8j8FHJ8A3wKe","name":"Bash","input":{"command":"curl -s \"https://duproprio.com/fr/saguenay-lac-st-jean/jonquiere-lac-kenogami/maison-a-etages-a-vendre/hab-4671-rue-des-perdrix-1126225\" -H \"User-Agent: Mozilla/5.0\" | python3 -c \"\nimport sys,re,json\nhtml=sys.stdin.read()\nfor m in re.finditer(r'', html, re.S):\n try: d=json.loads(m.group(1))\n except: continue\n items = d if isinstance(d,list) else [d]\n for it in items:\n if isinstance(it,dict) and 'geo' in it:\n print(it.get('@type'), it.get('geo'))\nprint('len_html', len(html))\"","description":"Vérifier le geo JSON-LD sur la page DuProprio"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":2482,"cache_read_input_tokens":47051,"cache_creation":{"ephemeral_5m_input_tokens":2482,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"5976da75-9c48-47fd-8cfb-1955e57096fd"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01ST8ugVymVY8j8FHJ8A3wKe","type":"tool_result","content":"len_html 102936","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"1b470d4c-5362-426b-aded-7523c56fc0a3","timestamp":"2026-08-25T13:13:13.211Z","tool_use_result":{"stdout":"len_html 102936","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"46858a42-6d31-4650-8f30-b550ac19b853","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} 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{"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXSa7jgEb38ULKxWYiP","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":2343,"cache_read_input_tokens":49533,"cache_creation":{"ephemeral_5m_input_tokens":2343,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"77500a85-f94e-46d9-94ef-315c01e15af9"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXSa7jgEb38ULKxWYiP","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_017FPQeDHUGM4Pd6PRFtTkFe","name":"Bash","input":{"command":"curl -s \"https://duproprio.com/fr/saguenay-lac-st-jean/jonquiere-lac-kenogami/maison-a-etages-a-vendre/hab-4671-rue-des-perdrix-1126225\" -H \"User-Agent: Mozilla/5.0\" -o /tmp/dp.html; grep -o '\"latitude\"[^,}]*' /tmp/dp.html | head; grep -o '\"longitude\"[^,}]*' /tmp/dp.html | head; grep -o 'latitude[^,}\"]*[0-9.]*' /tmp/dp.html | head -5","description":"Chercher lat/lng dans la page DuProprio"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":2343,"cache_read_input_tokens":49533,"cache_creation":{"ephemeral_5m_input_tokens":2343,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"370dde37-70db-43e3-ba01-a5a8594c9f44"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_017FPQeDHUGM4Pd6PRFtTkFe","type":"tool_result","content":"(Bash completed with no output)","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"e765cdaa-f131-43cb-95e0-01d526a52d75","timestamp":"2026-08-25T13:13:36.170Z","tool_use_result":{"stdout":"","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXSa7jgEb38ULKxWYiP","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01GhQKFPAmAyD5bm9j3xceQR","name":"Read","input":{"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/connectors/duproprio.py","offset":100,"limit":60},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":2343,"cache_read_input_tokens":49533,"cache_creation":{"ephemeral_5m_input_tokens":2343,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"45eb4f7e-f515-4cd2-9ede-a9da4e33c76d"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01GhQKFPAmAyD5bm9j3xceQR","type":"tool_result","content":"100\t html = self.get_scrapfly(url, render_js=False, asp=True)\n101\t except Exception:\n102\t pass\n103\t return html\n104\t\n105\t\n106\t# ---------------------------------------------------------------------------\n107\tdef _parse_dp_detail(html: str) -> dict:\n108\t import json, html as _h\n109\t out: dict = {}\n110\t for block in _LDPROD_RE.findall(html):\n111\t try:\n112\t d = json.loads(block)\n113\t except ValueError:\n114\t continue\n115\t if isinstance(d, dict) and d.get(\"@type\") == \"Product\":\n116\t off = d.get(\"offers\") or {}\n117\t p = parse_price(str(off.get(\"price\") or \"\")) if off.get(\"price\") else None\n118\t if p:\n119\t out[\"price\"] = p\n120\t out[\"price_label\"] = f\"{p:,.0f} $\".replace(\",\", \" \")\n121\t if d.get(\"description\"):\n122\t out[\"description\"] = _h.unescape(str(d[\"description\"])).strip()[:4000]\n123\t break\n124\t # coordonnées GPS du JSON-LD Residence (geo) — géocodage gratuit\n125\t for block in _LDPROD_RE.findall(html):\n126\t try:\n127\t d = json.loads(block)\n128\t except ValueError:\n129\t continue\n130\t geo = d.get(\"geo\") if isinstance(d, dict) else None\n131\t if isinstance(geo, dict):\n132\t try:\n133\t lat, lng = float(geo.get(\"latitude\")), float(geo.get(\"longitude\"))\n134\t except (TypeError, ValueError):\n135\t continue\n136\t if 44.5 <= lat <= 63.0 and -80.0 <= lng <= -56.0:\n137\t out[\"lat\"], out[\"lng\"] = lat, lng\n138\t break\n139\t # galerie COMPLÈTE : le JSON « \"photos\":[{...}] » de la page liste toutes les\n140\t # photos (le JSON-LD/HTML n'en montre qu'une). On prend la plus haute résolution.\n141\t imgs, seen = [], set()\n142\t mgal = re.search(r'\"photos\"\\s*:\\s*(\\[\\{.*?\\}\\])', html, re.S)\n143\t if mgal:\n144\t try:\n145\t for ph in json.loads(mgal.group(1)):\n146\t fmt = ph.get(\"formats\") or {}\n147\t rel = fmt.get(\"1600\") or fmt.get(\"1024\") or fmt.get(\"600\")\n148\t if rel:\n149\t u = rel if rel.startswith(\"http\") else f\"https://photos.duproprio.com/{rel.lstrip('/')}\"\n150\t if u not in seen:\n151\t seen.add(u); imgs.append(u)\n152\t except ValueError:\n153\t pass\n154\t if not imgs: # repli : URLs photos dans le HTML brut\n155\t for u in _PHOTO_RE.findall(html):\n156\t if u not in seen:\n157\t seen.add(u); imgs.append(u)\n158\t if imgs:\n159\t out[\"images\"] = imgs"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"3d05043b-d1d5-4167-ac37-293c810c7fbc","timestamp":"2026-08-25T13:13:36.803Z","tool_use_result":{"type":"text","file":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/connectors/duproprio.py","content":" html = self.get_scrapfly(url, render_js=False, asp=True)\n except Exception:\n pass\n return html\n\n\n# ---------------------------------------------------------------------------\ndef _parse_dp_detail(html: str) -> dict:\n import json, html as _h\n out: dict = {}\n for block in _LDPROD_RE.findall(html):\n try:\n d = json.loads(block)\n except ValueError:\n continue\n if isinstance(d, dict) and d.get(\"@type\") == \"Product\":\n off = d.get(\"offers\") or {}\n p = parse_price(str(off.get(\"price\") or \"\")) if off.get(\"price\") else None\n if p:\n out[\"price\"] = p\n out[\"price_label\"] = f\"{p:,.0f} $\".replace(\",\", \" \")\n if d.get(\"description\"):\n out[\"description\"] = _h.unescape(str(d[\"description\"])).strip()[:4000]\n break\n # coordonnées GPS du JSON-LD Residence (geo) — géocodage gratuit\n for block in _LDPROD_RE.findall(html):\n try:\n d = json.loads(block)\n except ValueError:\n continue\n geo = d.get(\"geo\") if isinstance(d, dict) else None\n if isinstance(geo, dict):\n try:\n lat, lng = float(geo.get(\"latitude\")), float(geo.get(\"longitude\"))\n except (TypeError, ValueError):\n continue\n if 44.5 <= lat <= 63.0 and -80.0 <= lng <= -56.0:\n out[\"lat\"], out[\"lng\"] = lat, lng\n break\n # galerie COMPLÈTE : le JSON « \"photos\":[{...}] » de la page liste toutes les\n # photos (le JSON-LD/HTML n'en montre qu'une). On prend la plus haute résolution.\n imgs, seen = [], set()\n mgal = re.search(r'\"photos\"\\s*:\\s*(\\[\\{.*?\\}\\])', html, re.S)\n if mgal:\n try:\n for ph in json.loads(mgal.group(1)):\n fmt = ph.get(\"formats\") or {}\n rel = fmt.get(\"1600\") or fmt.get(\"1024\") or fmt.get(\"600\")\n if rel:\n u = rel if rel.startswith(\"http\") else f\"https://photos.duproprio.com/{rel.lstrip('/')}\"\n if u not in seen:\n seen.add(u); imgs.append(u)\n except ValueError:\n pass\n if not imgs: # repli : URLs photos dans le HTML brut\n for u in _PHOTO_RE.findall(html):\n if u not in seen:\n seen.add(u); imgs.append(u)\n if imgs:\n out[\"images\"] = imgs","numLines":60,"startLine":100,"totalLines":244}}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"f7999f94-9426-4182-92b3-0025ece4ef6a","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} 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{"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01QbRohGri2JBPMeRpajC7tD","type":"tool_result","content":"10:`finalize()` applique ensuite la couche de normalisation commune\n71: lat: float | None = None\n72: lng: float | None = None\n84: def finalize(self) -> \"PropertyListing\":\n138: # province (lat/lng inversés, 0/0, coquilles)\n139: if self.lat is not None and self.lng is not None:\n140: if not (44.5 <= self.lat <= 63.0 and -80.0 <= self.lng <= -56.0):\n141: self.lat = self.lng = None"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"77f79830-c62a-4f87-8e37-3aa724ef9413","timestamp":"2026-08-25T13:14:12.199Z","tool_use_result":{"mode":"content","numFiles":0,"filenames":[],"content":"10:`finalize()` applique ensuite la couche de normalisation commune\n71: lat: float | None = None\n72: lng: float | None = None\n84: def finalize(self) -> \"PropertyListing\":\n138: # province (lat/lng inversés, 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{"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXWvQEtv4FqTu2zk9Fe","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01FS58fUoDSxW2BKskset1Zq","name":"Bash","input":{"command":"for q in \"4671 Rue Des Perdrix, Jonquière\" \"Jonquière\" \"Jonquiere Lac Kenogami\"; do echo \"== $q\"; curl -s \"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/Adresse_Geocodage/GeocodeServer/findAddressCandidates\" --get --data-urlencode \"SingleLine=$q\" --data \"f=json&outSR=4326&maxLocations=2\" -H \"User-Agent: ImmoKaBot/1.0\" | python3 -c \"import json,sys; d=json.load(sys.stdin); [print(' ',c['score'],c['address'],round(c['location']['y'],3),round(c['location']['x'],3)) for c in d.get('candidates',[])] or print(' (aucun)')\"; done","description":"Tester AQ : adresse accentuée + villes seules"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":3308,"cache_read_input_tokens":54633,"cache_creation":{"ephemeral_5m_input_tokens":3308,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"22738a5d-7aa1-4519-8a41-40326cd3333f"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01FS58fUoDSxW2BKskset1Zq","type":"tool_result","content":"== 4671 Rue Des Perdrix, Jonquière\n (aucun)\n== Jonquière\n (aucun)\n== Jonquiere Lac Kenogami\n (aucun)","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"b6bb72b7-7f72-44ac-9860-c5e3d64b3e58","timestamp":"2026-08-25T13:14:28.044Z","tool_use_result":{"stdout":"== 4671 Rue Des Perdrix, 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{"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01XkVXHaXB29KKhCf5eVhxF3","type":"tool_result","content":"1\t# -----------------------------------------------------------------------------\n2\t# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n3\t# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n4\t# ingest.py : pipeline d'ingestion — exécute les connecteurs et synchronise\n5\t# la base (ajouts / mises à jour / retraits) = contenu toujours à jour\n6\t# -----------------------------------------------------------------------------\n7\tfrom __future__ import annotations\n8\t\n9\timport sys\n10\timport time\n11\timport traceback\n12\t\n13\tfrom . import db\n14\tfrom .connectors import CONNECTORS\n15\t\n16\t\n17\tdef run(sources: list[str] | None = None) -> list[dict]:\n18\t \"\"\"Exécute l'ingestion pour toutes les sources (ou celles demandées).\"\"\"\n19\t con = db.connect()\n20\t results = []\n21\t targets = sources or list(CONNECTORS.keys())\n22\t for sid in targets:\n23\t cls = CONNECTORS.get(sid)\n24\t if cls is None:\n25\t print(f\"[immo-ka] connecteur inconnu : {sid}\", file=sys.stderr)\n26\t continue\n27\t t0 = time.time()\n28\t print(f\"[immo-ka] sync {sid} ...\")\n29\t try:\n30\t listings = cls().fetch()\n31\t finalized, dropped = [], 0\n32\t for lst in listings:\n33\t try:\n34\t finalized.append(lst.finalize())\n35\t except Exception: # une annonce malformée ne bloque pas la source\n36\t dropped += 1\n37\t stats = db.sync_source(con, sid, finalized)\n38\t stats[\"seconds\"] = round(time.time() - t0, 1)\n39\t if dropped:\n40\t stats[\"dropped\"] = dropped\n41\t if stats.get(\"alert\"):\n42\t print(f\"[immo-ka] ⚠ ALERTE {sid} : {stats['alert']}\")\n43\t print(f\"[immo-ka] {stats}\")\n44\t results.append(stats)\n45\t except Exception as exc: # robustesse : une source ne bloque pas les autres\n46\t db.log_failure(con, sid, f\"{exc}\")\n47\t traceback.print_exc()\n48\t results.append({\"source\": sid, \"error\": str(exc)})\n49\t # recalcule la déduplication (pré-calculée pour des lectures instantanées)\n50\t try:\n51\t hidden = db.refresh_dedup(con)\n52\t print(f\"[immo-ka] dédup: {hidden} doublon(s) masqué(s) \"\n53\t \"(sous-agences Centris + adresse inter-sources)\")\n54\t except Exception:\n55\t traceback.print_exc()\n56\t # contrôle qualité : score de complétude, cohérence immobilière, seuil de\n57\t # publication (quarantaine) et champs dérivés (prix/pi², transaction)\n58\t try:\n59\t from . import quality\n60\t q = quality.refresh(con)\n61\t print(f\"[immo-ka] qualité: {q['publiees']} publiée(s), \"\n62\t f\"{q['quarantaine']} en quarantaine, \"\n63\t f\"{q['recalculees']} recalculée(s)\")\n64\t except Exception:\n65\t traceback.print_exc()\n66\t # statistiques du planificateur SQLite : sans elles, les requêtes bbox\n67\t # de la carte (Ka Maps) n'utilisent pas idx_listings_geo\n68\t try:\n69\t con.execute(\"PRAGMA optimize\")\n70\t except Exception:\n71\t pass\n72\t con.close()\n73\t return results\n74\t\n75\t\n76\tdef watch(interval_seconds: int = 3600) -> None:\n77\t \"\"\"Boucle de synchronisation périodique (équivalent webhook, via PM2/cron).\n78\t\n79\t Après chaque synchronisation, l'enrichissement continu de la carte\n80\t (Ka Maps) : géocodage EN LOT des nouvelles adresses (Adresses Québec),\n81\t puis appariement Vrai-Prix local (estimations + coordonnées du rôle)\n82\t quand data/vraiprix.db (ou VRAIPRIX_DB) est disponible.\n83\t \"\"\"\n84\t while True:\n85\t run()\n86\t try: # nouvelles adresses → coordonnées (cache : quasi gratuit ensuite)\n87\t from . import geocode\n88\t geocode.run_batch()\n89\t except Exception as exc:\n90\t print(f\"[immo-ka] geocode: erreur non bloquante: {exc}\", file=sys.stderr)\n91\t try: # estimations Vrai-Prix + géocodage bonus depuis le rôle\n92\t from . import vraiprix_local\n93\t if vraiprix_local.available():\n94\t vraiprix_local.run(limit=5000)\n95\t # rôle d'évaluation (valeurs/année/superficies officielles) pour\n96\t # les annonces déjà appariées — jointure par id, quasi gratuite\n97\t vraiprix_local.enrich_role(limit=20000)\n98\t except Exception as exc:\n99\t print(f\"[immo-ka] vraiprix_local: erreur non bloquante: {exc}\", file=sys.stderr)\n100\t try: # audit budgété des images (liens morts, minuscules, corrompues)\n101\t from . import imgaudit\n102\t ia = imgaudit.run_batch(limit=2000)\n103\t print(f\"[immo-ka] images: {ia['urls_verifiees']} URL vérifiée(s), \"\n104\t f\"{ia['images_retirees']} retirée(s), \"\n105\t f\"{ia['sans_image_valide']} annonce(s) sans image valide\")\n106\t except Exception as exc:\n107\t print(f\"[immo-ka] imgaudit: erreur non bloquante: {exc}\", file=sys.stderr)\n108\t try: # estimation Hydro-Québec des nouvelles annonces (cache persistant, coût borné)\n109\t from . import hydro\n110\t hydro.precompute(limit=100, budget=30)\n111\t except Exception as exc:\n112\t print(f\"[immoka] hydro: erreur non bloquante: {exc}\", file=sys.stderr)\n113\t try: # taux hypothécaires — collecte espacée (IMMOKA_MORTGAGE_INTERVAL_MIN)\n114\t from .mortgage import scheduler as mortgage_scheduler\n115\t mortgage_scheduler.maybe_run()\n116\t except Exception as exc:\n117\t print(f\"[immo-ka] mortgage: erreur non bloquante: {exc}\", file=sys.stderr)\n118\t print(f\"[immo-ka] prochaine synchronisation dans {interval_seconds // 60} min\")\n119\t time.sleep(interval_seconds)\n120\t"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"d3434c80-71d7-406c-97b2-fa517a07f47d","timestamp":"2026-08-25T13:15:58.796Z","tool_use_result":{"type":"text","file":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/ingest.py","content":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# ingest.py : pipeline d'ingestion — exécute les connecteurs et synchronise\n# la base (ajouts / mises à jour / retraits) = contenu toujours à jour\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport sys\nimport time\nimport traceback\n\nfrom . import db\nfrom .connectors import CONNECTORS\n\n\ndef run(sources: list[str] | None = None) -> list[dict]:\n \"\"\"Exécute l'ingestion pour toutes les sources (ou celles demandées).\"\"\"\n con = db.connect()\n results = []\n targets = sources or list(CONNECTORS.keys())\n for sid in targets:\n cls = CONNECTORS.get(sid)\n if cls is None:\n print(f\"[immo-ka] connecteur inconnu : {sid}\", file=sys.stderr)\n continue\n t0 = time.time()\n print(f\"[immo-ka] sync {sid} ...\")\n try:\n listings = cls().fetch()\n finalized, dropped = [], 0\n for lst in listings:\n try:\n finalized.append(lst.finalize())\n except Exception: # une annonce malformée ne bloque pas la source\n dropped += 1\n stats = db.sync_source(con, sid, finalized)\n stats[\"seconds\"] = round(time.time() - t0, 1)\n if dropped:\n stats[\"dropped\"] = dropped\n if stats.get(\"alert\"):\n print(f\"[immo-ka] ⚠ ALERTE {sid} : {stats['alert']}\")\n print(f\"[immo-ka] {stats}\")\n results.append(stats)\n except Exception as exc: # robustesse : une source ne bloque pas les autres\n db.log_failure(con, sid, f\"{exc}\")\n traceback.print_exc()\n results.append({\"source\": sid, \"error\": str(exc)})\n # recalcule la déduplication (pré-calculée pour des lectures instantanées)\n try:\n hidden = db.refresh_dedup(con)\n print(f\"[immo-ka] dédup: {hidden} doublon(s) masqué(s) \"\n \"(sous-agences Centris + adresse inter-sources)\")\n except Exception:\n traceback.print_exc()\n # contrôle qualité : score de complétude, cohérence immobilière, seuil de\n # publication (quarantaine) et champs dérivés (prix/pi², transaction)\n try:\n from . import quality\n q = quality.refresh(con)\n print(f\"[immo-ka] qualité: {q['publiees']} publiée(s), \"\n f\"{q['quarantaine']} en quarantaine, \"\n f\"{q['recalculees']} recalculée(s)\")\n except Exception:\n traceback.print_exc()\n # statistiques du planificateur SQLite : sans elles, les requêtes bbox\n # de la carte (Ka Maps) n'utilisent pas idx_listings_geo\n try:\n con.execute(\"PRAGMA optimize\")\n except Exception:\n pass\n con.close()\n return results\n\n\ndef watch(interval_seconds: int = 3600) -> None:\n \"\"\"Boucle de synchronisation périodique (équivalent webhook, via PM2/cron).\n\n Après chaque synchronisation, l'enrichissement continu de la carte\n (Ka Maps) : géocodage EN LOT des nouvelles adresses (Adresses Québec),\n puis appariement Vrai-Prix local (estimations + coordonnées du rôle)\n quand data/vraiprix.db (ou VRAIPRIX_DB) est disponible.\n \"\"\"\n while True:\n run()\n try: # nouvelles adresses → coordonnées (cache : quasi gratuit ensuite)\n from . import geocode\n geocode.run_batch()\n except Exception as exc:\n print(f\"[immo-ka] geocode: erreur non bloquante: {exc}\", file=sys.stderr)\n try: # estimations Vrai-Prix + géocodage bonus depuis le rôle\n from . import vraiprix_local\n if vraiprix_local.available():\n vraiprix_local.run(limit=5000)\n # rôle d'évaluation (valeurs/année/superficies officielles) pour\n # les annonces déjà appariées — jointure par id, quasi gratuite\n vraiprix_local.enrich_role(limit=20000)\n except Exception as exc:\n print(f\"[immo-ka] vraiprix_local: erreur non bloquante: {exc}\", file=sys.stderr)\n try: # audit budgété des images (liens morts, minuscules, corrompues)\n from . import imgaudit\n ia = imgaudit.run_batch(limit=2000)\n print(f\"[immo-ka] images: {ia['urls_verifiees']} URL vérifiée(s), \"\n f\"{ia['images_retirees']} retirée(s), \"\n f\"{ia['sans_image_valide']} annonce(s) sans image valide\")\n except Exception as exc:\n print(f\"[immo-ka] imgaudit: erreur non bloquante: {exc}\", file=sys.stderr)\n try: # estimation Hydro-Québec des nouvelles annonces (cache persistant, coût borné)\n from . import hydro\n hydro.precompute(limit=100, budget=30)\n except Exception as exc:\n print(f\"[immoka] hydro: erreur non bloquante: {exc}\", file=sys.stderr)\n try: # taux hypothécaires — collecte espacée (IMMOKA_MORTGAGE_INTERVAL_MIN)\n from .mortgage import scheduler as mortgage_scheduler\n mortgage_scheduler.maybe_run()\n except Exception as exc:\n print(f\"[immo-ka] mortgage: erreur non bloquante: {exc}\", file=sys.stderr)\n print(f\"[immo-ka] prochaine synchronisation dans {interval_seconds // 60} min\")\n time.sleep(interval_seconds)\n","numLines":120,"startLine":1,"totalLines":120}}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXaeyQzAyRMzr5gDL6A","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Ct22RNf5ZKRYRtrHkKRtiZ","name":"Read","input":{"file_path":"/Users/simon-pierreboucher/apps/immo-ka/run.py"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1939,"cache_read_input_tokens":59470,"cache_creation":{"ephemeral_5m_input_tokens":1939,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"47421fe7-ebd2-41a8-862a-06ba0fe2e59d"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Ct22RNf5ZKRYRtrHkKRtiZ","type":"tool_result","content":"1\t#!/usr/bin/env python3\n2\t# -----------------------------------------------------------------------------\n3\t# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n4\t# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n5\t# run.py : point d'entrée — `sync`, `watch`, `serve`\n6\t# -----------------------------------------------------------------------------\n7\t\"\"\"Utilisation :\n8\t python run.py sync [source ...] # synchronise les propriétés\n9\t python run.py watch [minutes] # synchronise en boucle (défaut 60 min)\n10\t python run.py serve [port] # démarre l'API + le frontend (défaut 8090)\n11\t python run.py list # liste les connecteurs enregistrés\n12\t python run.py geocode [n] # géocode les annonces sans coordonnées (max n requêtes)\n13\t python run.py poi [n] # commodités de proximité par immeuble (max n requêtes)\n14\t python run.py quartier [n] # rattache chaque annonce à son aire de diffusion (DAUID)\n15\t python run.py mortgage-sync [slug…] # collecte les taux hypothécaires (toutes banques ou celles listées)\n16\t python run.py mortgage-watch [min] # collecte en boucle (défaut IMMOKA_MORTGAGE_INTERVAL_MIN=180)\n17\t python run.py mortgage-status # santé des providers de taux (OK/WARNING/ERROR)\n18\t\"\"\"\n19\tfrom __future__ import annotations\n20\t\n21\timport os\n22\timport sys\n23\tfrom pathlib import Path\n24\t\n25\t# Charger .env (FIRECRAWL_API_KEY, etc.) sans dépendance externe\n26\t_env = Path(__file__).parent / \".env\"\n27\tif _env.exists():\n28\t for line in _env.read_text().splitlines():\n29\t line = line.strip()\n30\t if line and not line.startswith(\"#\") and \"=\" in line:\n31\t k, _, v = line.partition(\"=\")\n32\t os.environ.setdefault(k.strip(), v.strip())\n33\t\n34\t\n35\tdef main() -> None:\n36\t cmd = sys.argv[1] if len(sys.argv) > 1 else \"serve\"\n37\t if cmd == \"sync\":\n38\t from immoka import ingest\n39\t ingest.run(sys.argv[2:] or None)\n40\t elif cmd == \"watch\":\n41\t from immoka import ingest\n42\t minutes = int(sys.argv[2]) if len(sys.argv) > 2 else 60\n43\t ingest.watch(minutes * 60)\n44\t elif cmd == \"list\":\n45\t from immoka.connectors import CONNECTORS\n46\t for sid in sorted(CONNECTORS):\n47\t print(sid)\n48\t print(f\"-- {len(CONNECTORS)} connecteur(s)\")\n49\t elif cmd == \"geocode\":\n50\t from immoka import geocode\n51\t geocode.run_batch(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n52\t elif cmd == \"geocode1\": # ancien mode 1-par-1 (+ repli Nominatim)\n53\t from immoka import geocode\n54\t geocode.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n55\t elif cmd == \"poi\":\n56\t from immoka import poi\n57\t poi.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n58\t elif cmd == \"air-refresh\":\n59\t from immoka import air\n60\t air.refresh()\n61\t elif cmd == \"gaz-refresh\":\n62\t from immoka import gaz\n63\t print(f\"[gaz] {gaz.refresh()} stations\")\n64\t elif cmd == \"hydro-precompute\":\n65\t from immoka import hydro\n66\t n = int(sys.argv[2]) if len(sys.argv) > 2 else 100\n67\t b = int(sys.argv[3]) if len(sys.argv) > 3 else 40\n68\t hydro.precompute(limit=n, budget=b)\n69\t elif cmd == \"inondation-build\":\n70\t from immoka import inondation\n71\t inondation.build()\n72\t elif cmd == \"quartier\":\n73\t from immoka import quartier\n74\t quartier.enrich(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n75\t elif cmd == \"vraiprix\":\n76\t from immoka import vraiprix\n77\t vraiprix.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n78\t elif cmd == \"vraiprix_local\": # appariement local (vraiprix.db) : rapide\n79\t from immoka import vraiprix_local\n80\t reval = \"reval\" in sys.argv[2:]\n81\t lim = next((int(a) for a in sys.argv[2:] if a.isdigit()), None)\n82\t if \"role\" in sys.argv[2:]: # backfill rôle d'évaluation (jointure par id)\n83\t vraiprix_local.enrich_role(lim)\n84\t else:\n85\t vraiprix_local.run(lim, revalidate=reval)\n86\t elif cmd == \"mortgage-sync\":\n87\t from immoka.mortgage import scheduler\n88\t scheduler.run(sys.argv[2:] or None)\n89\t elif cmd == \"mortgage-watch\":\n90\t from immoka.mortgage import scheduler\n91\t minutes = int(sys.argv[2]) if len(sys.argv) > 2 else None\n92\t scheduler.watch(minutes)\n93\t elif cmd == \"mortgage-status\":\n94\t from immoka.mortgage import store\n95\t con = store.connect()\n96\t for h in store.provider_health(con):\n97\t print(f\"{h['level']:8s} {h['provider']:15s} \"\n98\t f\"statut={h.get('status') or '-'} \"\n99\t f\"produits_courants={h.get('current_products', 0)} \"\n100\t f\"dernière_passe=il y a {h.get('age_minutes', '?')} min\")\n101\t elif cmd == \"serve\":\n102\t import uvicorn\n103\t port = int(sys.argv[2]) if len(sys.argv) > 2 else 8090\n104\t uvicorn.run(\"immoka.web:app\", host=\"0.0.0.0\", port=port)\n105\t else:\n106\t print(__doc__)\n107\t sys.exit(1)\n108\t\n109\t\n110\tif __name__ == \"__main__\":\n111\t main()\n112\t"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"f211dd57-5434-4f56-9b44-4fe33556c078","timestamp":"2026-08-25T13:15:59.158Z","tool_use_result":{"type":"text","file":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/run.py","content":"#!/usr/bin/env python3\n# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# run.py : point d'entrée — `sync`, `watch`, `serve`\n# -----------------------------------------------------------------------------\n\"\"\"Utilisation :\n python run.py sync [source ...] # synchronise les propriétés\n python run.py watch [minutes] # synchronise en boucle (défaut 60 min)\n python run.py serve [port] # démarre l'API + le frontend (défaut 8090)\n python run.py list # liste les connecteurs enregistrés\n python run.py geocode [n] # géocode les annonces sans coordonnées (max n requêtes)\n python run.py poi [n] # commodités de proximité par immeuble (max n requêtes)\n python run.py quartier [n] # rattache chaque annonce à son aire de diffusion (DAUID)\n python run.py mortgage-sync [slug…] # collecte les taux hypothécaires (toutes banques ou celles listées)\n python run.py mortgage-watch [min] # collecte en boucle (défaut IMMOKA_MORTGAGE_INTERVAL_MIN=180)\n python run.py mortgage-status # santé des providers de taux (OK/WARNING/ERROR)\n\"\"\"\nfrom __future__ import annotations\n\nimport os\nimport sys\nfrom pathlib import Path\n\n# Charger .env (FIRECRAWL_API_KEY, etc.) sans dépendance externe\n_env = Path(__file__).parent / \".env\"\nif _env.exists():\n for line in _env.read_text().splitlines():\n line = line.strip()\n if line and not line.startswith(\"#\") and \"=\" in line:\n k, _, v = line.partition(\"=\")\n os.environ.setdefault(k.strip(), v.strip())\n\n\ndef main() -> None:\n cmd = sys.argv[1] if len(sys.argv) > 1 else \"serve\"\n if cmd == \"sync\":\n from immoka import ingest\n ingest.run(sys.argv[2:] or None)\n elif cmd == \"watch\":\n from immoka import ingest\n minutes = int(sys.argv[2]) if len(sys.argv) > 2 else 60\n ingest.watch(minutes * 60)\n elif cmd == \"list\":\n from immoka.connectors import CONNECTORS\n for sid in sorted(CONNECTORS):\n print(sid)\n print(f\"-- {len(CONNECTORS)} connecteur(s)\")\n elif cmd == \"geocode\":\n from immoka import geocode\n geocode.run_batch(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"geocode1\": # ancien mode 1-par-1 (+ repli Nominatim)\n from immoka import geocode\n geocode.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"poi\":\n from immoka import poi\n poi.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"air-refresh\":\n from immoka import air\n air.refresh()\n elif cmd == \"gaz-refresh\":\n from immoka import gaz\n print(f\"[gaz] {gaz.refresh()} stations\")\n elif cmd == \"hydro-precompute\":\n from immoka import hydro\n n = int(sys.argv[2]) if len(sys.argv) > 2 else 100\n b = int(sys.argv[3]) if len(sys.argv) > 3 else 40\n hydro.precompute(limit=n, budget=b)\n elif cmd == \"inondation-build\":\n from immoka import inondation\n inondation.build()\n elif cmd == \"quartier\":\n from immoka import quartier\n quartier.enrich(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"vraiprix\":\n from immoka import vraiprix\n vraiprix.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"vraiprix_local\": # appariement local (vraiprix.db) : rapide\n from immoka import vraiprix_local\n reval = \"reval\" in sys.argv[2:]\n lim = next((int(a) for a in sys.argv[2:] if a.isdigit()), None)\n if \"role\" in sys.argv[2:]: # backfill rôle d'évaluation (jointure par id)\n vraiprix_local.enrich_role(lim)\n else:\n vraiprix_local.run(lim, revalidate=reval)\n elif cmd == \"mortgage-sync\":\n from immoka.mortgage import scheduler\n scheduler.run(sys.argv[2:] or None)\n elif cmd == \"mortgage-watch\":\n from immoka.mortgage import scheduler\n minutes = int(sys.argv[2]) if len(sys.argv) > 2 else None\n scheduler.watch(minutes)\n elif cmd == \"mortgage-status\":\n from immoka.mortgage import store\n con = store.connect()\n for h in store.provider_health(con):\n print(f\"{h['level']:8s} {h['provider']:15s} \"\n f\"statut={h.get('status') or '-'} \"\n f\"produits_courants={h.get('current_products', 0)} \"\n f\"dernière_passe=il y a {h.get('age_minutes', '?')} min\")\n elif cmd == \"serve\":\n import uvicorn\n port = int(sys.argv[2]) if len(sys.argv) > 2 else 8090\n uvicorn.run(\"immoka.web:app\", host=\"0.0.0.0\", port=port)\n else:\n print(__doc__)\n sys.exit(1)\n\n\nif __name__ == \"__main__\":\n main()\n","numLines":112,"startLine":1,"totalLines":112}}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"8795ab23-a76b-4080-9d2c-6fbcfe9bb5e4","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXep6CnNJaTpw1GKPgg","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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{"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXep6CnNJaTpw1GKPgg","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":8320,"cache_read_input_tokens":61409,"cache_creation":{"ephemeral_5m_input_tokens":8320,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"8ac40e46-9757-48d6-95e2-28fa07267856"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXep6CnNJaTpw1GKPgg","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_014aYHZcSKesap9gvo77BhMU","name":"Grep","input":{"pattern":"lat|lng|geocode_cache|def sync_source|UPDATE listings SET","path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","output_mode":"content","-n":true},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":8320,"cache_read_input_tokens":61409,"cache_creation":{"ephemeral_5m_input_tokens":8320,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"e5b09ab9-7336-478b-8b33-6b09b0ff9139"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_014aYHZcSKesap9gvo77BhMU","type":"tool_result","content":"59: lat REAL,\n60: lng REAL,\n105:CREATE TABLE IF NOT EXISTS geocode_cache (\n107: lat REAL,\n108: lng REAL,\n115: coord_key TEXT PRIMARY KEY, -- \"lat,lng\" arrondi à 4 décimales (~11 m)\n116: lat REAL,\n117: lng REAL,\n142: con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n160: con.execute(\"UPDATE listings SET dup_hidden=0\")\n164: f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG}\"\n170: f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG} AND dup_hidden=0\"\n174: # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle\n268: con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n287: \" area_sqft, lot_sqft, year_built, lat, lng, broker_phone\")\n310: # GPS : toujours la PAIRE du même donneur (jamais lat et lng mélangés)\n311: if (keep[\"lat\"] is None and \"lat\" not in merged_num\n312: and d[\"lat\"] is not None and d[\"lng\"] is not None):\n313: merged_num[\"lat\"], merged_num[\"lng\"] = d[\"lat\"], d[\"lng\"]\n324: con.execute(f\"UPDATE listings SET {', '.join(sets)} WHERE uid=?\", args)\n374:def sync_source(con: sqlite3.Connection, source: str,\n415: lat=lst.lat, lng=lst.lng, content_hash=h, now=now,\n423: agency, description, features, details, images, lat, lng,\n430: :agency,:description,:features,:details,:images,:lat,:lng,\n441: \"\"\"UPDATE listings SET url=:url, title=:title,\n453: lat=COALESCE(:lat, lat), lng=COALESCE(:lng, lng),\n463: \"UPDATE listings SET last_seen=?, miss_count=0, active=1 WHERE uid=?\",\n478: \"UPDATE listings SET active=0, miss_count=?, updated_at=?\"\n482: con.execute(\"UPDATE listings SET miss_count=miss_count+1 WHERE uid=?\","}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"333578b6-a56a-42d2-b461-1f0a772d2261","timestamp":"2026-08-25T13:16:37.313Z","tool_use_result":{"mode":"content","numFiles":0,"filenames":[],"content":"59: lat REAL,\n60: lng REAL,\n105:CREATE TABLE IF NOT EXISTS geocode_cache (\n107: lat REAL,\n108: lng REAL,\n115: coord_key TEXT PRIMARY KEY, -- \"lat,lng\" arrondi à 4 décimales (~11 m)\n116: lat REAL,\n117: lng REAL,\n142: con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n160: con.execute(\"UPDATE listings SET dup_hidden=0\")\n164: f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG}\"\n170: f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG} AND dup_hidden=0\"\n174: # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle\n268: con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n287: \" area_sqft, lot_sqft, year_built, lat, lng, broker_phone\")\n310: # GPS : toujours la PAIRE du même donneur (jamais lat et lng mélangés)\n311: if (keep[\"lat\"] is None and \"lat\" not in merged_num\n312: and d[\"lat\"] is not None and d[\"lng\"] is not None):\n313: merged_num[\"lat\"], merged_num[\"lng\"] = d[\"lat\"], d[\"lng\"]\n324: con.execute(f\"UPDATE listings SET {', '.join(sets)} WHERE uid=?\", args)\n374:def sync_source(con: sqlite3.Connection, source: str,\n415: lat=lst.lat, lng=lst.lng, content_hash=h, now=now,\n423: agency, description, features, details, images, lat, lng,\n430: :agency,:description,:features,:details,:images,:lat,:lng,\n441: \"\"\"UPDATE listings SET url=:url, title=:title,\n453: lat=COALESCE(:lat, lat), lng=COALESCE(:lng, lng),\n463: \"UPDATE listings SET last_seen=?, miss_count=0, active=1 WHERE uid=?\",\n478: \"UPDATE listings SET active=0, miss_count=?, updated_at=?\"\n482: con.execute(\"UPDATE listings SET miss_count=miss_count+1 WHERE uid=?\",","numLines":29}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"3816419b-2cd4-4e23-8ff7-892fbba70663","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXhd1Hk48x1xtKTrmPk","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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{"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXhd1Hk48x1xtKTrmPk","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Gc1VTuGvJamjY1fFdzJnVy","name":"Bash","input":{"command":"curl -s \"https://nominatim.openstreetmap.org/search\" --get --data-urlencode \"street=4671 Rue des Perdrix\" --data-urlencode \"city=Jonquière\" --data-urlencode \"state=Québec\" --data-urlencode \"country=Canada\" --data \"format=jsonv2&limit=2&countrycodes=ca\" -H \"User-Agent: ImmoKaBot/1.0 (contact@spboucher.ai)\" | python3 -c \"import json,sys; [print(' ',h.get('type'),round(float(h['lat']),3),round(float(h['lon']),3),h.get('display_name','')[:80]) for h in json.load(sys.stdin)] or print('(aucun)')\"; sleep 1.2; curl -s \"https://nominatim.openstreetmap.org/search\" --get --data-urlencode \"q=Jonquiere Lac Kenogami, Québec, Canada\" --data \"format=jsonv2&limit=1&countrycodes=ca&addressdetails=1\" -H \"User-Agent: ImmoKaBot/1.0 (contact@spboucher.ai)\" | python3 -c \"import json,sys; h=json.load(sys.stdin)[0]; print(h.get('address'))\"","description":"Nominatim structuré + addressdetails pour la municipalité"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":2887,"cache_read_input_tokens":69729,"cache_creation":{"ephemeral_5m_input_tokens":2887,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"a481c793-c458-4c7d-8ffa-d5f44986c840"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Gc1VTuGvJamjY1fFdzJnVy","type":"tool_result","content":" unclassified 48.314 -71.299 Rue des Perdrix, Arrondissement de Jonquière, Saguenay, Saguenay–Lac-Saint-Jean,\n unclassified 48.312 -71.303 Rue des Perdrix, Arrondissement de Jonquière, Saguenay, Saguenay–Lac-Saint-Jean,\n{'building': 'Bell Canada JNQRPQ06', 'house_number': 'Jonquiere', 'road': 'Rue Saint-Jacques', 'quarter': 'Kénogami', 'suburb': 'Arrondissement de Jonquière', 'city': 'Saguenay', 'state_district': 'Saguenay–Lac-Saint-Jean', 'state': 'Québec', 'ISO3166-2-lvl4': 'CA-QC', 'postcode': 'G7X 8T5', 'country': 'Canada', 'country_code': 'ca'}","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"1dea207c-6623-492b-938e-bd05170ef17d","timestamp":"2026-08-25T13:17:41.097Z","tool_use_result":{"stdout":" unclassified 48.314 -71.299 Rue des Perdrix, Arrondissement de Jonquière, Saguenay, Saguenay–Lac-Saint-Jean,\n unclassified 48.312 -71.303 Rue des Perdrix, Arrondissement de Jonquière, Saguenay, Saguenay–Lac-Saint-Jean,\n{'building': 'Bell Canada JNQRPQ06', 'house_number': 'Jonquiere', 'road': 'Rue Saint-Jacques', 'quarter': 'Kénogami', 'suburb': 'Arrondissement de Jonquière', 'city': 'Saguenay', 'state_district': 'Saguenay–Lac-Saint-Jean', 'state': 'Québec', 'ISO3166-2-lvl4': 'CA-QC', 'postcode': 'G7X 8T5', 'country': 'Canada', 'country_code': 'ca'}","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"e91acbb3-e591-422a-a320-69d587ca08fe","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} 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NULL,\n101\t price REAL -- prix observé (baisses/hausses de prix demandé)\n102\t);\n103\tCREATE INDEX IF NOT EXISTS idx_price_log_uid ON price_log(uid);\n104\t\n105\tCREATE TABLE IF NOT EXISTS geocode_cache (\n106\t address TEXT PRIMARY KEY,\n107\t lat REAL,\n108\t lng REAL,\n109\t provider TEXT,\n110\t failed INTEGER DEFAULT 0,\n111\t ts REAL\n112\t);\n113\t\n114\tCREATE TABLE IF NOT EXISTS poi_cache (\n115\t coord_key TEXT PRIMARY KEY, -- \"lat,lng\" arrondi à 4 décimales (~11 m)\n116\t lat REAL,\n117\t lng REAL,\n118\t pois TEXT, -- JSON : [{cat, name, dist_m}] (plus proche/catégorie)\n119\t ts REAL\n120\t);\n121\t\"\"\"\n122\t\n123\t\n124\t_SCHEMA_READY = False # le schéma/migration ne s'exécute qu'UNE fois par process\n125\t\n126\t\n127\tdef _init_schema(con: sqlite3.Connection) -> None:\n128\t \"\"\"Création de schéma + migration — coûteuse (write-lock). À faire une seule\n129\t fois par process : l'exécuter à chaque connexion sérialisait les requêtes du\n130\t web sur un verrou d'écriture (deadlock/starvation sous charge).\"\"\"\n131\t con.executescript(_SCHEMA)\n132\t cols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(listings)\")}\n133\t if \"agency\" not in cols:\n134\t con.execute(\"ALTER TABLE listings ADD COLUMN agency TEXT\")\n135\t if \"dup_hidden\" not in cols:\n136\t con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n137\t if \"dauid\" not in cols: # aire de diffusion 2021 (stats de quartier)\n138\t con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")\n139\t if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n140\t con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n141\t con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n142\t con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n143\t con.commit()\n144\t\n145\t\n146\tdef refresh_dedup(con: sqlite3.Connection) -> int:\n147\t \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n148\t colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n149\t au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n150\t\n151\t Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée\n152\t si une fiche de plus haute priorité — même n° Centris (external_id), active —\n153\t existe : le flux central/agence principale d'abord, sinon la sous-agence au\n154\t plus petit uid. Les fiches non sous-agence ne sont jamais masquées par\n155\t cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n156\t INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).\n157\t Retourne le nombre total de fiches masquées.\"\"\"\n158\t AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n159\t NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\""}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"6b50cfc4-8601-4a68-9184-650f7957dc24","timestamp":"2026-08-25T13:17:56.275Z","tool_use_result":{"type":"text","file":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","content":" ts REAL NOT NULL,\n price REAL -- prix observé (baisses/hausses de prix demandé)\n);\nCREATE INDEX IF NOT EXISTS idx_price_log_uid ON price_log(uid);\n\nCREATE TABLE IF NOT EXISTS geocode_cache (\n address TEXT PRIMARY KEY,\n lat REAL,\n lng REAL,\n provider TEXT,\n failed INTEGER DEFAULT 0,\n ts REAL\n);\n\nCREATE TABLE IF NOT EXISTS poi_cache (\n coord_key TEXT PRIMARY KEY, -- \"lat,lng\" arrondi à 4 décimales (~11 m)\n lat REAL,\n lng REAL,\n pois TEXT, -- JSON : [{cat, name, dist_m}] (plus proche/catégorie)\n ts REAL\n);\n\"\"\"\n\n\n_SCHEMA_READY = False # le schéma/migration ne s'exécute qu'UNE fois par process\n\n\ndef _init_schema(con: sqlite3.Connection) -> None:\n \"\"\"Création de schéma + migration — coûteuse (write-lock). À faire une seule\n fois par process : l'exécuter à chaque connexion sérialisait les requêtes du\n web sur un verrou d'écriture (deadlock/starvation sous charge).\"\"\"\n con.executescript(_SCHEMA)\n cols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(listings)\")}\n if \"agency\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN agency TEXT\")\n if \"dup_hidden\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n if \"dauid\" not in cols: # aire de diffusion 2021 (stats de quartier)\n con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")\n if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n con.commit()\n\n\ndef refresh_dedup(con: sqlite3.Connection) -> int:\n \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n\n Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée\n si une fiche de plus haute priorité — même n° Centris (external_id), active —\n existe : le flux central/agence principale d'abord, sinon la sous-agence au\n plus petit uid. Les fiches non sous-agence ne sont jamais masquées par\n cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).\n Retourne le nombre total de fiches masquées.\"\"\"\n AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"","numLines":60,"startLine":100,"totalLines":556}}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"9df5ca31-7705-42fe-a670-f7ed73bf0126","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXoSxi79QHrfaYtDjJu","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"8582f1af-5e59-4980-aa0f-7e20912447b5","timestamp":"2026-08-25T13:19:15.274Z","tool_use_result":{"oldTodos":[],"newTodos":[{"content":"geocode.py : centroïde de ville (médiane BD + Nominatim caché) et validation ≤40 km","status":"in_progress","activeForm":"Ajout de la validation par centroïde de ville"},{"content":"resolve() : retry AQ avec municipalité officielle + variantes Nominatim","status":"pending","activeForm":"Ajout des variantes de municipalité"},{"content":"run_batch : validation centroïde + rattrapage resolve() des échecs","status":"pending","activeForm":"Renforcement du géocodage batch"},{"content":"run_audit : détecter/corriger les fiches aux coordonnées incohérentes","status":"pending","activeForm":"Création de l'audit géocodage"},{"content":"Garde ingestion : rejeter les coords de connecteur contredisant la ville","status":"pending","activeForm":"Ajout de la garde à l'ingestion"},{"content":"db.py : colonne muni dans geocode_cache + CLI geocode-audit + watch","status":"pending","activeForm":"Migration BD et CLI"},{"content":"Corriger duproprio:1126225 + lancer l'audit + vérifier le site","status":"pending","activeForm":"Correction des fiches et vérification"},{"content":"pm2 restart + commit + push origin main","status":"pending","activeForm":"Redéploiement et commit"}],"verificationNudgeNeeded":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"f990549e-9368-4a24-bd2f-7f382d6738e9","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXuGu9cttC5NJhofko9","type":"message","role":"assistant","content":[{"type":"text","text":"Maintenant les modifications dans `immoka/geocode.py`."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":5975,"cache_read_input_tokens":82548,"cache_creation":{"ephemeral_5m_input_tokens":5975,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"8262ad7c-03c4-4b6a-9927-344779aa608a"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXuGu9cttC5NJhofko9","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Rws4u4wVz7PrkH7rfWMT96","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","old_string":"# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport sqlite3\n\nimport re\nimport time\n\nimport requests","new_string":"# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# - rigueur : chaque résultat est validé contre le CENTROÏDE de la ville\n# annoncée (médiane des fiches déjà géocodées, sinon Nominatim, en cache) —\n# à plus de VILLE_RADIUS_KM du centroïde, le candidat est rejeté. Corrige\n# la classe de bug « rue homonyme dans une autre ville » (ex. rue des\n# Perdrix de Jonquière géocodée à Saint-Augustin).\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport math\nimport sqlite3\nimport statistics\n\nimport re\nimport time\n\nimport requests"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":5975,"cache_read_input_tokens":82548,"cache_creation":{"ephemeral_5m_input_tokens":5975,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"b1007d67-78cc-41e5-84b1-40083ef54360"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Rws4u4wVz7PrkH7rfWMT96","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"a2af058d-87d6-4cd9-9955-70f942346e6e","timestamp":"2026-08-25T13:19:24.982Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","oldString":"# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport sqlite3\n\nimport re\nimport time\n\nimport requests","newString":"# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# - rigueur : chaque résultat est validé contre le CENTROÏDE de la ville\n# annoncée (médiane des fiches déjà géocodées, sinon Nominatim, en cache) —\n# à plus de VILLE_RADIUS_KM du centroïde, le candidat est rejeté. Corrige\n# la classe de bug « rue homonyme dans une autre ville » (ex. rue des\n# Perdrix de Jonquière géocodée à Saint-Augustin).\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport math\nimport sqlite3\nimport statistics\n\nimport re\nimport time\n\nimport requests","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)\n# - cache persistant (table geocode_cache) : une adresse n'est géocodée\n# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce\n# - politesse : 1 requête/seconde max, User-Agent identifiable\n# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport sqlite3\n\nimport re\nimport time\n\nimport requests\n\nfrom . import db\nfrom .normalize import strip_accents\n\nNOMINATIM_URL = \"https://nominatim.openstreetmap.org/search\"\n# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre\n# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)\nAQ_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/findAddressCandidates\")\nAQ_MIN_SCORE = 75\n# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête\n# User-Agent contient des accents (latin-1)\nUSER_AGENT = \"ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)\"\nREQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s\nREQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte\nRETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours\n\n# Bounding boxes (lat_min, lat_max, lng_min, lng_max)\n_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord\n# et la Gaspésie (expansion provinciale) — même boîte que schema.finalize()\n_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n\n_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n\n\ndef norm_key(address: str) -> str:\n \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\"\n s = strip_accents((address or \"\").lower())\n s = re.sub(r\"\\b(?:app?t?|appartement|unite|suite|#)\\.?\\s*[\\w-]+\\b\", \" \", s)\n s = re.sub(r\"[^a-z0-9]+\", \" \", s)\n return re.sub(r\"\\s+\", \" \", s).strip()\n\n\nclass Geocoder:\n def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0\n\n @staticmethod\n def _clean(address: str) -> str:\n \"\"\"Nettoyages qui aident Nominatim sur les adresses québécoises.\"\"\"\n s = address.strip()\n # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique\n s = re.sub(r\"^(\\d+)-(\\d+)\\s\", r\"\\2 \", s)\n # « 6275 et 6375 boulevard X » -> premier civique\n s = re.sub(r\"^(\\d+)\\s+et\\s+\\d+\\s\", r\"\\1 \", s)\n # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu\n s = re.sub(r\"montr[ée]al\\s*-\\s*\", \"\", s, flags=re.I)\n # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau\n s = re.sub(r\",?\\s*(?:bureau|suite|local|app\\.?|apt\\.?)\\s*[\\w-]+\\b\", \"\", s, flags=re.I)\n # « Vanier (Québec) » -> « Vanier, Québec »\n s = re.sub(r\"\\s*\\((qu[ée]bec)\\)\", r\", \\1\", s, flags=re.I)\n # abréviations cardinales : « Rue Salaberry O » -> « Ouest »\n s = re.sub(r\"\\bO\\.?(?=,|\\s*$)\", \"Ouest\", s)\n s = re.sub(r\"\\bE\\.?(?=,|\\s*$)\", \"Est\", s)\n return s\n\n def _build_query(self, address: str, city: str) -> str:\n q = self._clean(address)\n key = strip_accents(q.lower())\n if city and strip_accents(city.lower()) not in key:\n q += f\", {city}\"\n if \"quebec\" not in strip_accents(q.lower()) and \"qc\" not in q.lower():\n q += \", Québec\"\n return q + \", Canada\"\n\n def _query_nominatim(self, params: dict) -> tuple[float, float] | None:\n \"\"\"Une requête Nominatim, throttlée.\"\"\"\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"format\": \"jsonv2\", \"limit\": 1, \"countrycodes\": \"ca\", **params,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None\n if not hits:\n return None\n try:\n return float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n except (KeyError, ValueError):\n return None\n\n def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).\n\n Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE\n pour éviter les correspondances approximatives sur une autre rue.\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"Québec\").strip()\n wait = REQUEST_DELAY_AQ - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(AQ_URL, params={\n \"SingleLine\": f\"{premier}, {ville}\",\n \"f\": \"json\", \"outSR\": 4326, \"maxLocations\": 1,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n cands = resp.json().get(\"candidates\") or []\n except Exception:\n self._last = time.time()\n return None\n if not cands or cands[0].get(\"score\", 0) < AQ_MIN_SCORE:\n return None\n loc = cands[0].get(\"location\") or {}\n try:\n return float(loc[\"y\"]), float(loc[\"x\"])\n except (KeyError, ValueError):\n return None\n\n def _attempts(self, address: str, city: str) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) recherche libre complète\n 3) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n commun = {\"city\": ville, \"state\": \"Québec\", \"country\": \"Canada\"}\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis Nominatim. None si introuvable.\"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n bbox = _bbox_for(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if c is not None and _in_bbox(*c, bbox):\n coords = c\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city):\n c = self._query_nominatim(params)\n if c is not None and _in_bbox(*c, bbox):\n coords = c\n break\n ok = coords is not None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?)\"\n \" ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,\"\n \" lng=excluded.lng, provider=excluded.provider,\"\n \" failed=excluded.failed, ts=excluded.ts\",\n (key, coords[0] if ok else None, coords[1] if ok else None,\n provider, 0 if ok else 1, time.time()))\n self.con.commit()\n return coords if ok else None\n\n\ndef run(limit: int | None = None) -> dict:\n \"\"\"Géocode les annonces actives sans coordonnées, par adresse unique.\n\n `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de\n cache sont gratuits et toujours appliqués).\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0\n ORDER BY address\"\"\").fetchall()\n\n # regrouper par immeuble (adresse normalisée)\n groupes: dict[str, list] = {}\n for r in rows:\n groupes.setdefault(norm_key(r[\"address\"]), []).append(r)\n\n done = failed = requests_made = 0\n for key, members in groupes.items():\n if not key:\n continue\n cached = con.execute(\n \"SELECT failed FROM geocode_cache WHERE address=?\", (key,)).fetchone()\n if cached is None:\n if limit is not None and requests_made >= limit:\n continue\n requests_made += 1\n try:\n coords = geo.resolve(members[0][\"address\"], members[0][\"city\"])\n if coords:\n for r in members:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], r[\"uid\"]))\n done += len(members)\n else:\n # introuvable/hors zone : flag ; jamais de coordonnées bidon\n for r in members:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\",\n (r[\"uid\"],))\n failed += len(members)\n con.commit()\n except sqlite3.OperationalError:\n # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,\n # elle sera reprise au prochain passage — jamais crasher tout le run.\n try:\n con.rollback()\n except sqlite3.Error:\n pass\n time.sleep(1.0)\n continue\n\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed,\n \"unique_addresses\": len(groupes), \"api_requests\": requests_made}\n print(f\"[immo-ka] geocode {stats}\")\n return stats\n\n\nAQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200\n\n\ndef run_batch(limit: int | None = None) -> dict:\n \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de\n milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim).\"\"\"\n con = db.connect()\n geo = Geocoder(con) # pour réutiliser _clean / bbox\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0 ORDER BY address\"\"\").fetchall()\n # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache\n uniq: dict[str, dict] = {}\n for r in rows:\n k = norm_key(r[\"address\"])\n if not k or len(k) < 6:\n continue\n u = uniq.setdefault(k, {\"address\": r[\"address\"], \"city\": r[\"city\"],\n \"members\": []})\n u[\"members\"].append(r[\"uid\"])\n pending = []\n for k, u in uniq.items():\n c = con.execute(\"SELECT lat,lng,failed FROM geocode_cache WHERE address=?\",\n (k,)).fetchone()\n if c is not None and not c[\"failed\"]: # déjà résolu : appliquer direct\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (c[\"lat\"], c[\"lng\"], uid))\n continue\n if c is not None and c[\"failed\"]:\n continue\n pending.append((k, u))\n con.commit()\n if limit is not None:\n pending = pending[:limit]\n\n session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n if _in_bbox(*cand, _bbox_for(u[\"city\"])):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,1,?) ON CONFLICT(address) DO UPDATE SET\"\n \" failed=1, ts=excluded.ts\",\n (k, None, None, \"adresses_quebec_batch\", time.time()))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, échecs {failed})\")\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed, \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats\n","structuredPatch":[{"oldStart":8,"oldLines":11,"newStart":8,"newLines":18,"lines":[" # - validation : les coordonnées doivent tomber dans la région attendue"," # (bounding box par ville), sinon flag geocode_failed — jamais de"," # coordonnées bidon","+# - rigueur : chaque résultat est validé contre le CENTROÏDE de la ville","+# annoncée (médiane des fiches déjà géocodées, sinon Nominatim, en cache) —","+# à plus de VILLE_RADIUS_KM du centroïde, le candidat est rejeté. Corrige","+# la classe de bug « rue homonyme dans une autre ville » (ex. rue des","+# Perdrix de Jonquière géocodée à Saint-Augustin)."," # -----------------------------------------------------------------------------"," from __future__ import annotations"," "," import json","+import math"," import sqlite3","+import statistics"," "," import re"," import time"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"e3e36e2a-3773-4408-bf01-167b3b724ae0","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXuzPk5xom6uVDP5LKM","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01MSCdYThVaavKRwiCHvrKrK","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","old_string":"_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]","new_string":"_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n# Validation « rigoureuse » : distance max entre un résultat de géocodage et le\n# centroïde de la ville annoncée. 40 km tolère les grandes municipalités\n# fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues\n# homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).\nVILLE_RADIUS_KM = 40.0\nVILLE_MIN_SAMPLES = 5 # médiane de fiches : min d'échantillons pour être fiable\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n\n\ndef _dist_km(lat1: float, lng1: float, lat2: float, lng2: float) -> float:\n \"\"\"Distance haversine en kilomètres.\"\"\"\n p1, p2 = math.radians(lat1), math.radians(lat2)\n a = (math.sin((p2 - p1) / 2) ** 2\n + math.cos(p1) * math.cos(p2) * math.sin(math.radians(lng2 - lng1) / 2) ** 2)\n return 2 * 6371.0 * math.asin(math.sqrt(a))"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":616,"cache_read_input_tokens":88523,"cache_creation":{"ephemeral_5m_input_tokens":616,"ephemeral_1h_input_tokens":0},"output_tokens":20,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"d1acf0a3-0245-4734-bff2-cb58e82da891"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01MSCdYThVaavKRwiCHvrKrK","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"80aab315-2dd2-437a-9962-5b2c859e0884","timestamp":"2026-08-25T13:19:37.148Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","oldString":"_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]","newString":"_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n# Validation « rigoureuse » : distance max entre un résultat de géocodage et le\n# centroïde de la ville annoncée. 40 km tolère les grandes municipalités\n# fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues\n# homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).\nVILLE_RADIUS_KM = 40.0\nVILLE_MIN_SAMPLES = 5 # médiane de fiches : min d'échantillons pour être fiable\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n\n\ndef _dist_km(lat1: float, lng1: float, lat2: float, lng2: float) -> float:\n \"\"\"Distance haversine en kilomètres.\"\"\"\n p1, p2 = math.radians(lat1), math.radians(lat2)\n a = (math.sin((p2 - p1) / 2) ** 2\n + math.cos(p1) * math.cos(p2) * math.sin(math.radians(lng2 - lng1) / 2) ** 2)\n return 2 * 6371.0 * math.asin(math.sqrt(a))","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)\n# - cache persistant (table geocode_cache) : une adresse n'est géocodée\n# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce\n# - politesse : 1 requête/seconde max, User-Agent identifiable\n# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# - rigueur : chaque résultat est validé contre le CENTROÏDE de la ville\n# annoncée (médiane des fiches déjà géocodées, sinon Nominatim, en cache) —\n# à plus de VILLE_RADIUS_KM du centroïde, le candidat est rejeté. Corrige\n# la classe de bug « rue homonyme dans une autre ville » (ex. rue des\n# Perdrix de Jonquière géocodée à Saint-Augustin).\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport math\nimport sqlite3\nimport statistics\n\nimport re\nimport time\n\nimport requests\n\nfrom . import db\nfrom .normalize import strip_accents\n\nNOMINATIM_URL = \"https://nominatim.openstreetmap.org/search\"\n# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre\n# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)\nAQ_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/findAddressCandidates\")\nAQ_MIN_SCORE = 75\n# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête\n# User-Agent contient des accents (latin-1)\nUSER_AGENT = \"ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)\"\nREQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s\nREQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte\nRETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours\n\n# Bounding boxes (lat_min, lat_max, lng_min, lng_max)\n_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord\n# et la Gaspésie (expansion provinciale) — même boîte que schema.finalize()\n_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n\n_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n\n\ndef norm_key(address: str) -> str:\n \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\"\n s = strip_accents((address or \"\").lower())\n s = re.sub(r\"\\b(?:app?t?|appartement|unite|suite|#)\\.?\\s*[\\w-]+\\b\", \" \", s)\n s = re.sub(r\"[^a-z0-9]+\", \" \", s)\n return re.sub(r\"\\s+\", \" \", s).strip()\n\n\nclass Geocoder:\n def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0\n\n @staticmethod\n def _clean(address: str) -> str:\n \"\"\"Nettoyages qui aident Nominatim sur les adresses québécoises.\"\"\"\n s = address.strip()\n # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique\n s = re.sub(r\"^(\\d+)-(\\d+)\\s\", r\"\\2 \", s)\n # « 6275 et 6375 boulevard X » -> premier civique\n s = re.sub(r\"^(\\d+)\\s+et\\s+\\d+\\s\", r\"\\1 \", s)\n # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu\n s = re.sub(r\"montr[ée]al\\s*-\\s*\", \"\", s, flags=re.I)\n # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau\n s = re.sub(r\",?\\s*(?:bureau|suite|local|app\\.?|apt\\.?)\\s*[\\w-]+\\b\", \"\", s, flags=re.I)\n # « Vanier (Québec) » -> « Vanier, Québec »\n s = re.sub(r\"\\s*\\((qu[ée]bec)\\)\", r\", \\1\", s, flags=re.I)\n # abréviations cardinales : « Rue Salaberry O » -> « Ouest »\n s = re.sub(r\"\\bO\\.?(?=,|\\s*$)\", \"Ouest\", s)\n s = re.sub(r\"\\bE\\.?(?=,|\\s*$)\", \"Est\", s)\n return s\n\n def _build_query(self, address: str, city: str) -> str:\n q = self._clean(address)\n key = strip_accents(q.lower())\n if city and strip_accents(city.lower()) not in key:\n q += f\", {city}\"\n if \"quebec\" not in strip_accents(q.lower()) and \"qc\" not in q.lower():\n q += \", Québec\"\n return q + \", Canada\"\n\n def _query_nominatim(self, params: dict) -> tuple[float, float] | None:\n \"\"\"Une requête Nominatim, throttlée.\"\"\"\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"format\": \"jsonv2\", \"limit\": 1, \"countrycodes\": \"ca\", **params,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None\n if not hits:\n return None\n try:\n return float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n except (KeyError, ValueError):\n return None\n\n def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).\n\n Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE\n pour éviter les correspondances approximatives sur une autre rue.\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"Québec\").strip()\n wait = REQUEST_DELAY_AQ - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(AQ_URL, params={\n \"SingleLine\": f\"{premier}, {ville}\",\n \"f\": \"json\", \"outSR\": 4326, \"maxLocations\": 1,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n cands = resp.json().get(\"candidates\") or []\n except Exception:\n self._last = time.time()\n return None\n if not cands or cands[0].get(\"score\", 0) < AQ_MIN_SCORE:\n return None\n loc = cands[0].get(\"location\") or {}\n try:\n return float(loc[\"y\"]), float(loc[\"x\"])\n except (KeyError, ValueError):\n return None\n\n def _attempts(self, address: str, city: str) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) recherche libre complète\n 3) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n commun = {\"city\": ville, \"state\": \"Québec\", \"country\": \"Canada\"}\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis Nominatim. None si introuvable.\"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n bbox = _bbox_for(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if c is not None and _in_bbox(*c, bbox):\n coords = c\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city):\n c = self._query_nominatim(params)\n if c is not None and _in_bbox(*c, bbox):\n coords = c\n break\n ok = coords is not None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?)\"\n \" ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,\"\n \" lng=excluded.lng, provider=excluded.provider,\"\n \" failed=excluded.failed, ts=excluded.ts\",\n (key, coords[0] if ok else None, coords[1] if ok else None,\n provider, 0 if ok else 1, time.time()))\n self.con.commit()\n return coords if ok else None\n\n\ndef run(limit: int | None = None) -> dict:\n \"\"\"Géocode les annonces actives sans coordonnées, par adresse unique.\n\n `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de\n cache sont gratuits et toujours appliqués).\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0\n ORDER BY address\"\"\").fetchall()\n\n # regrouper par immeuble (adresse normalisée)\n groupes: dict[str, list] = {}\n for r in rows:\n groupes.setdefault(norm_key(r[\"address\"]), []).append(r)\n\n done = failed = requests_made = 0\n for key, members in groupes.items():\n if not key:\n continue\n cached = con.execute(\n \"SELECT failed FROM geocode_cache WHERE address=?\", (key,)).fetchone()\n if cached is None:\n if limit is not None and requests_made >= limit:\n continue\n requests_made += 1\n try:\n coords = geo.resolve(members[0][\"address\"], members[0][\"city\"])\n if coords:\n for r in members:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], r[\"uid\"]))\n done += len(members)\n else:\n # introuvable/hors zone : flag ; jamais de coordonnées bidon\n for r in members:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\",\n (r[\"uid\"],))\n failed += len(members)\n con.commit()\n except sqlite3.OperationalError:\n # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,\n # elle sera reprise au prochain passage — jamais crasher tout le run.\n try:\n con.rollback()\n except sqlite3.Error:\n pass\n time.sleep(1.0)\n continue\n\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed,\n \"unique_addresses\": len(groupes), \"api_requests\": requests_made}\n print(f\"[immo-ka] geocode {stats}\")\n return stats\n\n\nAQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200\n\n\ndef run_batch(limit: int | None = None) -> dict:\n \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de\n milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim).\"\"\"\n con = db.connect()\n geo = Geocoder(con) # pour réutiliser _clean / bbox\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0 ORDER BY address\"\"\").fetchall()\n # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache\n uniq: dict[str, dict] = {}\n for r in rows:\n k = norm_key(r[\"address\"])\n if not k or len(k) < 6:\n continue\n u = uniq.setdefault(k, {\"address\": r[\"address\"], \"city\": r[\"city\"],\n \"members\": []})\n u[\"members\"].append(r[\"uid\"])\n pending = []\n for k, u in uniq.items():\n c = con.execute(\"SELECT lat,lng,failed FROM geocode_cache WHERE address=?\",\n (k,)).fetchone()\n if c is not None and not c[\"failed\"]: # déjà résolu : appliquer direct\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (c[\"lat\"], c[\"lng\"], uid))\n continue\n if c is not None and c[\"failed\"]:\n continue\n pending.append((k, u))\n con.commit()\n if limit is not None:\n pending = pending[:limit]\n\n session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n if _in_bbox(*cand, _bbox_for(u[\"city\"])):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,1,?) ON CONFLICT(address) DO UPDATE SET\"\n \" failed=1, ts=excluded.ts\",\n (k, None, None, \"adresses_quebec_batch\", time.time()))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, échecs {failed})\")\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed, \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats\n","structuredPatch":[{"oldStart":51,"oldLines":7,"newStart":51,"newLines":14,"lines":[" _VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\","," \"l'ancienne-lorette\", \"ancienne-lorette\"}"," ","+# Validation « rigoureuse » : distance max entre un résultat de géocodage et le","+# centroïde de la ville annoncée. 40 km tolère les grandes municipalités","+# fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues","+# homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).","+VILLE_RADIUS_KM = 40.0","+VILLE_MIN_SAMPLES = 5 # médiane de fiches : min d'échantillons pour être fiable"," ","+"," def _bbox_for(city: str) -> tuple[float, float, float, float]:"," key = strip_accents((city or \"\").strip().lower())"," return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC"]},{"oldStart":61,"oldLines":6,"newStart":68,"newLines":14,"lines":[" return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]"," "," ","+def _dist_km(lat1: float, lng1: float, lat2: float, lng2: float) -> float:","+ \"\"\"Distance haversine en kilomètres.\"\"\"","+ p1, p2 = math.radians(lat1), math.radians(lat2)","+ a = (math.sin((p2 - p1) / 2) ** 2","+ + math.cos(p1) * math.cos(p2) * math.sin(math.radians(lng2 - lng1) / 2) ** 2)","+ return 2 * 6371.0 * math.asin(math.sqrt(a))","+","+"," def norm_key(address: str) -> str:"," \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\""," s = strip_accents((address or \"\").lower())"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"fcee4884-d4cf-4d18-8e77-c2cda4f12111","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXvt6kQdDpnNHQqX3qW","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1026,"cache_read_input_tokens":89139,"cache_creation":{"ephemeral_5m_input_tokens":1026,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"63bfb6b7-a588-4416-89fc-a5f7bcba3008"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXvt6kQdDpnNHQqX3qW","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01BWPnDmkBMSbNQhxrtPTGsF","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","old_string":" def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0","new_string":" def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0\n self._villes: dict[str, dict | None] = {} # norm(ville) -> {lat,lng,muni}\n self._med: dict[str, tuple] | None = None # norm(ville) -> (lat,lng,n)\n self.ville_api_calls = 0 # requêtes Nominatim « ville »"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1026,"cache_read_input_tokens":89139,"cache_creation":{"ephemeral_5m_input_tokens":1026,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"d4399610-d2fa-437f-86f1-8a8047da3985"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01BWPnDmkBMSbNQhxrtPTGsF","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"c9378d59-abfb-436c-bc86-ba81be0506b9","timestamp":"2026-08-25T13:19:47.110Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","oldString":" def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0","newString":" def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0\n self._villes: dict[str, dict | None] = {} # norm(ville) -> {lat,lng,muni}\n self._med: dict[str, tuple] | None = None # norm(ville) -> (lat,lng,n)\n self.ville_api_calls = 0 # requêtes Nominatim « ville »","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)\n# - cache persistant (table geocode_cache) : une adresse n'est géocodée\n# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce\n# - politesse : 1 requête/seconde max, User-Agent identifiable\n# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# - rigueur : chaque résultat est validé contre le CENTROÏDE de la ville\n# annoncée (médiane des fiches déjà géocodées, sinon Nominatim, en cache) —\n# à plus de VILLE_RADIUS_KM du centroïde, le candidat est rejeté. Corrige\n# la classe de bug « rue homonyme dans une autre ville » (ex. rue des\n# Perdrix de Jonquière géocodée à Saint-Augustin).\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport math\nimport sqlite3\nimport statistics\n\nimport re\nimport time\n\nimport requests\n\nfrom . import db\nfrom .normalize import strip_accents\n\nNOMINATIM_URL = \"https://nominatim.openstreetmap.org/search\"\n# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre\n# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)\nAQ_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/findAddressCandidates\")\nAQ_MIN_SCORE = 75\n# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête\n# User-Agent contient des accents (latin-1)\nUSER_AGENT = \"ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)\"\nREQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s\nREQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte\nRETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours\n\n# Bounding boxes (lat_min, lat_max, lng_min, lng_max)\n_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord\n# et la Gaspésie (expansion provinciale) — même boîte que schema.finalize()\n_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n\n_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n# Validation « rigoureuse » : distance max entre un résultat de géocodage et le\n# centroïde de la ville annoncée. 40 km tolère les grandes municipalités\n# fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues\n# homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).\nVILLE_RADIUS_KM = 40.0\nVILLE_MIN_SAMPLES = 5 # médiane de fiches : min d'échantillons pour être fiable\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n\n\ndef _dist_km(lat1: float, lng1: float, lat2: float, lng2: float) -> float:\n \"\"\"Distance haversine en kilomètres.\"\"\"\n p1, p2 = math.radians(lat1), math.radians(lat2)\n a = (math.sin((p2 - p1) / 2) ** 2\n + math.cos(p1) * math.cos(p2) * math.sin(math.radians(lng2 - lng1) / 2) ** 2)\n return 2 * 6371.0 * math.asin(math.sqrt(a))\n\n\ndef norm_key(address: str) -> str:\n \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\"\n s = strip_accents((address or \"\").lower())\n s = re.sub(r\"\\b(?:app?t?|appartement|unite|suite|#)\\.?\\s*[\\w-]+\\b\", \" \", s)\n s = re.sub(r\"[^a-z0-9]+\", \" \", s)\n return re.sub(r\"\\s+\", \" \", s).strip()\n\n\nclass Geocoder:\n def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0\n\n @staticmethod\n def _clean(address: str) -> str:\n \"\"\"Nettoyages qui aident Nominatim sur les adresses québécoises.\"\"\"\n s = address.strip()\n # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique\n s = re.sub(r\"^(\\d+)-(\\d+)\\s\", r\"\\2 \", s)\n # « 6275 et 6375 boulevard X » -> premier civique\n s = re.sub(r\"^(\\d+)\\s+et\\s+\\d+\\s\", r\"\\1 \", s)\n # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu\n s = re.sub(r\"montr[ée]al\\s*-\\s*\", \"\", s, flags=re.I)\n # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau\n s = re.sub(r\",?\\s*(?:bureau|suite|local|app\\.?|apt\\.?)\\s*[\\w-]+\\b\", \"\", s, flags=re.I)\n # « Vanier (Québec) » -> « Vanier, Québec »\n s = re.sub(r\"\\s*\\((qu[ée]bec)\\)\", r\", \\1\", s, flags=re.I)\n # abréviations cardinales : « Rue Salaberry O » -> « Ouest »\n s = re.sub(r\"\\bO\\.?(?=,|\\s*$)\", \"Ouest\", s)\n s = re.sub(r\"\\bE\\.?(?=,|\\s*$)\", \"Est\", s)\n return s\n\n def _build_query(self, address: str, city: str) -> str:\n q = self._clean(address)\n key = strip_accents(q.lower())\n if city and strip_accents(city.lower()) not in key:\n q += f\", {city}\"\n if \"quebec\" not in strip_accents(q.lower()) and \"qc\" not in q.lower():\n q += \", Québec\"\n return q + \", Canada\"\n\n def _query_nominatim(self, params: dict) -> tuple[float, float] | None:\n \"\"\"Une requête Nominatim, throttlée.\"\"\"\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"format\": \"jsonv2\", \"limit\": 1, \"countrycodes\": \"ca\", **params,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None\n if not hits:\n return None\n try:\n return float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n except (KeyError, ValueError):\n return None\n\n def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).\n\n Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE\n pour éviter les correspondances approximatives sur une autre rue.\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"Québec\").strip()\n wait = REQUEST_DELAY_AQ - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(AQ_URL, params={\n \"SingleLine\": f\"{premier}, {ville}\",\n \"f\": \"json\", \"outSR\": 4326, \"maxLocations\": 1,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n cands = resp.json().get(\"candidates\") or []\n except Exception:\n self._last = time.time()\n return None\n if not cands or cands[0].get(\"score\", 0) < AQ_MIN_SCORE:\n return None\n loc = cands[0].get(\"location\") or {}\n try:\n return float(loc[\"y\"]), float(loc[\"x\"])\n except (KeyError, ValueError):\n return None\n\n def _attempts(self, address: str, city: str) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) recherche libre complète\n 3) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n commun = {\"city\": ville, \"state\": \"Québec\", \"country\": \"Canada\"}\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis Nominatim. None si introuvable.\"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n bbox = _bbox_for(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if c is not None and _in_bbox(*c, bbox):\n coords = c\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city):\n c = self._query_nominatim(params)\n if c is not None and _in_bbox(*c, bbox):\n coords = c\n break\n ok = coords is not None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?)\"\n \" ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,\"\n \" lng=excluded.lng, provider=excluded.provider,\"\n \" failed=excluded.failed, ts=excluded.ts\",\n (key, coords[0] if ok else None, coords[1] if ok else None,\n provider, 0 if ok else 1, time.time()))\n self.con.commit()\n return coords if ok else None\n\n\ndef run(limit: int | None = None) -> dict:\n \"\"\"Géocode les annonces actives sans coordonnées, par adresse unique.\n\n `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de\n cache sont gratuits et toujours appliqués).\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0\n ORDER BY address\"\"\").fetchall()\n\n # regrouper par immeuble (adresse normalisée)\n groupes: dict[str, list] = {}\n for r in rows:\n groupes.setdefault(norm_key(r[\"address\"]), []).append(r)\n\n done = failed = requests_made = 0\n for key, members in groupes.items():\n if not key:\n continue\n cached = con.execute(\n \"SELECT failed FROM geocode_cache WHERE address=?\", (key,)).fetchone()\n if cached is None:\n if limit is not None and requests_made >= limit:\n continue\n requests_made += 1\n try:\n coords = geo.resolve(members[0][\"address\"], members[0][\"city\"])\n if coords:\n for r in members:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], r[\"uid\"]))\n done += len(members)\n else:\n # introuvable/hors zone : flag ; jamais de coordonnées bidon\n for r in members:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\",\n (r[\"uid\"],))\n failed += len(members)\n con.commit()\n except sqlite3.OperationalError:\n # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,\n # elle sera reprise au prochain passage — jamais crasher tout le run.\n try:\n con.rollback()\n except sqlite3.Error:\n pass\n time.sleep(1.0)\n continue\n\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed,\n \"unique_addresses\": len(groupes), \"api_requests\": requests_made}\n print(f\"[immo-ka] geocode {stats}\")\n return stats\n\n\nAQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200\n\n\ndef run_batch(limit: int | None = None) -> dict:\n \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de\n milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim).\"\"\"\n con = db.connect()\n geo = Geocoder(con) # pour réutiliser _clean / bbox\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0 ORDER BY address\"\"\").fetchall()\n # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache\n uniq: dict[str, dict] = {}\n for r in rows:\n k = norm_key(r[\"address\"])\n if not k or len(k) < 6:\n continue\n u = uniq.setdefault(k, {\"address\": r[\"address\"], \"city\": r[\"city\"],\n \"members\": []})\n u[\"members\"].append(r[\"uid\"])\n pending = []\n for k, u in uniq.items():\n c = con.execute(\"SELECT lat,lng,failed FROM geocode_cache WHERE address=?\",\n (k,)).fetchone()\n if c is not None and not c[\"failed\"]: # déjà résolu : appliquer direct\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (c[\"lat\"], c[\"lng\"], uid))\n continue\n if c is not None and c[\"failed\"]:\n continue\n pending.append((k, u))\n con.commit()\n if limit is not None:\n pending = pending[:limit]\n\n session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n if _in_bbox(*cand, _bbox_for(u[\"city\"])):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,1,?) ON CONFLICT(address) DO UPDATE SET\"\n \" failed=1, ts=excluded.ts\",\n (k, None, None, \"adresses_quebec_batch\", time.time()))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, échecs {failed})\")\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed, \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats\n","structuredPatch":[{"oldStart":90,"oldLines":6,"newStart":90,"newLines":9,"lines":[" self.session = requests.Session()"," self.session.headers[\"User-Agent\"] = USER_AGENT"," self._last = 0.0","+ self._villes: dict[str, dict | None] = {} # norm(ville) -> {lat,lng,muni}","+ self._med: dict[str, tuple] | None = None # norm(ville) -> (lat,lng,n)","+ self.ville_api_calls = 0 # requêtes Nominatim « ville »"," "," @staticmethod"," def _clean(address: str) -> str:"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"db5d3d12-ee42-4502-83c8-fd3cebfaa440","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXwcgqCR5HCqZZVfhwt","type":"message","role":"assistant","content":[{"type":"text","text":"Maintenant les méthodes de centroïde de ville, insérées avant `resolve()`, et la refonte de `resolve()` + `_attempts`."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":493,"cache_read_input_tokens":90165,"cache_creation":{"ephemeral_5m_input_tokens":493,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"3c5b9f27-ce49-49db-bbc6-4b24b7bb9fcf"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXwcgqCR5HCqZZVfhwt","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Lco3xpUDhueFENrxq9whbY","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","old_string":" def _attempts(self, address: str, city: str) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) recherche libre complète\n 3) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n commun = {\"city\": ville, \"state\": \"Québec\", \"country\": \"Canada\"}\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis Nominatim. None si introuvable.\"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n bbox = _bbox_for(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if c is not None and _in_bbox(*c, bbox):\n coords = c\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city):\n c = self._query_nominatim(params)\n if c is not None and _in_bbox(*c, bbox):\n coords = c\n break\n ok = coords is not None","new_string":" def _attempts(self, address: str, city: str, muni: str | None = None) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) idem avec la municipalité OFFICIELLE (« Saguenay ») quand la ville\n annoncée est un secteur (« Jonquière (Lac-Kénogami) ») inconnu des API\n 3) recherche libre complète\n 4) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n villes = [ville]\n # premier mot de la ville (« Jonquiere Lac Kenogami » -> « Jonquiere »)\n if \" \" in ville:\n villes.append(ville.split(\" \")[0])\n if muni and norm_key(muni) not in {norm_key(v) for v in villes}:\n villes.append(muni)\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n # ----- centroïde de ville (validation rigoureuse) ------------------------\n def _medians(self) -> dict[str, tuple]:\n \"\"\"Centroïde (médiane lat/lng) par ville, depuis les fiches déjà\n géocodées — gratuit, robuste aux erreurs isolées dès n >= 5.\"\"\"\n if self._med is None:\n acc: dict[str, list] = {}\n for r in self.con.execute(\n \"\"\"SELECT city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\"):\n acc.setdefault(norm_key(r[\"city\"]), []).append((r[\"lat\"], r[\"lng\"]))\n self._med = {k: (statistics.median(p[0] for p in v),\n statistics.median(p[1] for p in v), len(v))\n for k, v in acc.items()}\n return self._med\n\n def resolve_ville(self, city: str, allow_api: bool = True) -> dict | None:\n \"\"\"Ville -> {lat, lng, muni} (muni = municipalité officielle, ex.\n « Jonquière (Lac-Kénogami) » -> Saguenay). Cache : geocode_cache,\n clé « ville: ». None si irrésoluble.\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n if k in self._villes:\n return self._villes[k]\n key = \"ville:\" + k\n row = self.con.execute(\n \"SELECT lat, lng, muni, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n v = {\"lat\": row[\"lat\"], \"lng\": row[\"lng\"], \"muni\": row[\"muni\"]}\n self._villes[k] = v\n return v\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n self._villes[k] = None\n return None\n if not allow_api:\n return None # pas de mémoire : on réessaiera quand l'API sera permise\n self.ville_api_calls += 1\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n v = None\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"q\": f\"{city}, Québec, Canada\", \"format\": \"jsonv2\", \"limit\": 1,\n \"countrycodes\": \"ca\", \"addressdetails\": 1}, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None # erreur réseau : ne pas cacher un échec définitif\n if hits:\n try:\n lat, lng = float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n if _in_bbox(lat, lng, _BBOX_SUD_QC):\n a = hits[0].get(\"address\") or {}\n muni = (a.get(\"city\") or a.get(\"town\") or a.get(\"village\")\n or a.get(\"municipality\"))\n v = {\"lat\": lat, \"lng\": lng, \"muni\": muni}\n except (KeyError, ValueError, TypeError):\n v = None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, muni, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, muni=excluded.muni,\"\n \" provider=excluded.provider, failed=excluded.failed, ts=excluded.ts\",\n (key, v[\"lat\"] if v else None, v[\"lng\"] if v else None,\n v[\"muni\"] if v else None, \"ville_nominatim\", 0 if v else 1, time.time()))\n self.con.commit()\n self._villes[k] = v\n return v\n\n def city_reference(self, city: str, allow_api: bool = True) -> tuple[float, float] | None:\n \"\"\"Centroïde de référence d'une ville : médiane des fiches (n >= 5),\n sinon résolution Nominatim. None si inconnue (-> validation bbox seule).\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n med = self._medians().get(k)\n if med and med[2] >= VILLE_MIN_SAMPLES:\n return (med[0], med[1])\n v = self.resolve_ville(city, allow_api=allow_api)\n return (v[\"lat\"], v[\"lng\"]) if v else None\n\n def coords_ok(self, c: tuple[float, float] | None, city: str,\n ref: tuple[float, float] | None = None) -> bool:\n \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM du\n centroïde de la ville annoncée (quand il est connu).\"\"\"\n if c is None or not _in_bbox(*c, _bbox_for(city)):\n return False\n if ref is None:\n ref = self.city_reference(city)\n return ref is None or _dist_km(c[0], c[1], ref[0], ref[1]) <= VILLE_RADIUS_KM\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis AQ/Nominatim. None si introuvable.\n\n Rigueur : chaque candidat doit être cohérent avec la ville annoncée\n (centroïde <= VILLE_RADIUS_KM). Si la ville annoncée est un secteur\n inconnu d'Adresses Québec, on réessaie avec la municipalité officielle.\n \"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n ref = self.city_reference(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if self.coords_ok(c, city, ref):\n coords = c\n muni = None\n if coords is None:\n # ville annoncée = secteur (« Jonquière (Lac-Kénogami) ») ? AQ ne\n # connaît que les municipalités officielles -> retenter avec elle.\n v = self.resolve_ville(city)\n muni = (v or {}).get(\"muni\")\n if muni and norm_key(muni) != norm_key(city or \"\"):\n c = self._query_adresses_quebec(address, muni)\n if self.coords_ok(c, city, ref):\n coords, provider = c, \"adresses_quebec_muni\"\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city, muni):\n c = self._query_nominatim(params)\n if self.coords_ok(c, city, ref):\n coords = c\n break\n ok = coords is not None"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":493,"cache_read_input_tokens":90165,"cache_creation":{"ephemeral_5m_input_tokens":493,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ad63e5cc-f5b0-4667-ae7c-9f09d95de12f"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Lco3xpUDhueFENrxq9whbY","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"d8fb06b3-e608-432f-b424-dbf9b32056f3","timestamp":"2026-08-25T13:20:28.862Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","oldString":" def _attempts(self, address: str, city: str) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) recherche libre complète\n 3) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n commun = {\"city\": ville, \"state\": \"Québec\", \"country\": \"Canada\"}\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis Nominatim. None si introuvable.\"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n bbox = _bbox_for(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if c is not None and _in_bbox(*c, bbox):\n coords = c\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city):\n c = self._query_nominatim(params)\n if c is not None and _in_bbox(*c, bbox):\n coords = c\n break\n ok = coords is not None","newString":" def _attempts(self, address: str, city: str, muni: str | None = None) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) idem avec la municipalité OFFICIELLE (« Saguenay ») quand la ville\n annoncée est un secteur (« Jonquière (Lac-Kénogami) ») inconnu des API\n 3) recherche libre complète\n 4) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n villes = [ville]\n # premier mot de la ville (« Jonquiere Lac Kenogami » -> « Jonquiere »)\n if \" \" in ville:\n villes.append(ville.split(\" \")[0])\n if muni and norm_key(muni) not in {norm_key(v) for v in villes}:\n villes.append(muni)\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n # ----- centroïde de ville (validation rigoureuse) ------------------------\n def _medians(self) -> dict[str, tuple]:\n \"\"\"Centroïde (médiane lat/lng) par ville, depuis les fiches déjà\n géocodées — gratuit, robuste aux erreurs isolées dès n >= 5.\"\"\"\n if self._med is None:\n acc: dict[str, list] = {}\n for r in self.con.execute(\n \"\"\"SELECT city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\"):\n acc.setdefault(norm_key(r[\"city\"]), []).append((r[\"lat\"], r[\"lng\"]))\n self._med = {k: (statistics.median(p[0] for p in v),\n statistics.median(p[1] for p in v), len(v))\n for k, v in acc.items()}\n return self._med\n\n def resolve_ville(self, city: str, allow_api: bool = True) -> dict | None:\n \"\"\"Ville -> {lat, lng, muni} (muni = municipalité officielle, ex.\n « Jonquière (Lac-Kénogami) » -> Saguenay). Cache : geocode_cache,\n clé « ville: ». None si irrésoluble.\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n if k in self._villes:\n return self._villes[k]\n key = \"ville:\" + k\n row = self.con.execute(\n \"SELECT lat, lng, muni, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n v = {\"lat\": row[\"lat\"], \"lng\": row[\"lng\"], \"muni\": row[\"muni\"]}\n self._villes[k] = v\n return v\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n self._villes[k] = None\n return None\n if not allow_api:\n return None # pas de mémoire : on réessaiera quand l'API sera permise\n self.ville_api_calls += 1\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n v = None\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"q\": f\"{city}, Québec, Canada\", \"format\": \"jsonv2\", \"limit\": 1,\n \"countrycodes\": \"ca\", \"addressdetails\": 1}, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None # erreur réseau : ne pas cacher un échec définitif\n if hits:\n try:\n lat, lng = float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n if _in_bbox(lat, lng, _BBOX_SUD_QC):\n a = hits[0].get(\"address\") or {}\n muni = (a.get(\"city\") or a.get(\"town\") or a.get(\"village\")\n or a.get(\"municipality\"))\n v = {\"lat\": lat, \"lng\": lng, \"muni\": muni}\n except (KeyError, ValueError, TypeError):\n v = None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, muni, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, muni=excluded.muni,\"\n \" provider=excluded.provider, failed=excluded.failed, ts=excluded.ts\",\n (key, v[\"lat\"] if v else None, v[\"lng\"] if v else None,\n v[\"muni\"] if v else None, \"ville_nominatim\", 0 if v else 1, time.time()))\n self.con.commit()\n self._villes[k] = v\n return v\n\n def city_reference(self, city: str, allow_api: bool = True) -> tuple[float, float] | None:\n \"\"\"Centroïde de référence d'une ville : médiane des fiches (n >= 5),\n sinon résolution Nominatim. None si inconnue (-> validation bbox seule).\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n med = self._medians().get(k)\n if med and med[2] >= VILLE_MIN_SAMPLES:\n return (med[0], med[1])\n v = self.resolve_ville(city, allow_api=allow_api)\n return (v[\"lat\"], v[\"lng\"]) if v else None\n\n def coords_ok(self, c: tuple[float, float] | None, city: str,\n ref: tuple[float, float] | None = None) -> bool:\n \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM du\n centroïde de la ville annoncée (quand il est connu).\"\"\"\n if c is None or not _in_bbox(*c, _bbox_for(city)):\n return False\n if ref is None:\n ref = self.city_reference(city)\n return ref is None or _dist_km(c[0], c[1], ref[0], ref[1]) <= VILLE_RADIUS_KM\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis AQ/Nominatim. None si introuvable.\n\n Rigueur : chaque candidat doit être cohérent avec la ville annoncée\n (centroïde <= VILLE_RADIUS_KM). Si la ville annoncée est un secteur\n inconnu d'Adresses Québec, on réessaie avec la municipalité officielle.\n \"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n ref = self.city_reference(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if self.coords_ok(c, city, ref):\n coords = c\n muni = None\n if coords is None:\n # ville annoncée = secteur (« Jonquière (Lac-Kénogami) ») ? AQ ne\n # connaît que les municipalités officielles -> retenter avec elle.\n v = self.resolve_ville(city)\n muni = (v or {}).get(\"muni\")\n if muni and norm_key(muni) != norm_key(city or \"\"):\n c = self._query_adresses_quebec(address, muni)\n if self.coords_ok(c, city, ref):\n coords, provider = c, \"adresses_quebec_muni\"\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city, muni):\n c = self._query_nominatim(params)\n if self.coords_ok(c, city, ref):\n coords = c\n break\n ok = coords is not None","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)\n# - cache persistant (table geocode_cache) : une adresse n'est géocodée\n# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce\n# - politesse : 1 requête/seconde max, User-Agent identifiable\n# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# - rigueur : chaque résultat est validé contre le CENTROÏDE de la ville\n# annoncée (médiane des fiches déjà géocodées, sinon Nominatim, en cache) —\n# à plus de VILLE_RADIUS_KM du centroïde, le candidat est rejeté. Corrige\n# la classe de bug « rue homonyme dans une autre ville » (ex. rue des\n# Perdrix de Jonquière géocodée à Saint-Augustin).\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport math\nimport sqlite3\nimport statistics\n\nimport re\nimport time\n\nimport requests\n\nfrom . import db\nfrom .normalize import strip_accents\n\nNOMINATIM_URL = \"https://nominatim.openstreetmap.org/search\"\n# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre\n# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)\nAQ_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/findAddressCandidates\")\nAQ_MIN_SCORE = 75\n# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête\n# User-Agent contient des accents (latin-1)\nUSER_AGENT = \"ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)\"\nREQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s\nREQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte\nRETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours\n\n# Bounding boxes (lat_min, lat_max, lng_min, lng_max)\n_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord\n# et la Gaspésie (expansion provinciale) — même boîte que schema.finalize()\n_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n\n_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n# Validation « rigoureuse » : distance max entre un résultat de géocodage et le\n# centroïde de la ville annoncée. 40 km tolère les grandes municipalités\n# fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues\n# homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).\nVILLE_RADIUS_KM = 40.0\nVILLE_MIN_SAMPLES = 5 # médiane de fiches : min d'échantillons pour être fiable\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n\n\ndef _dist_km(lat1: float, lng1: float, lat2: float, lng2: float) -> float:\n \"\"\"Distance haversine en kilomètres.\"\"\"\n p1, p2 = math.radians(lat1), math.radians(lat2)\n a = (math.sin((p2 - p1) / 2) ** 2\n + math.cos(p1) * math.cos(p2) * math.sin(math.radians(lng2 - lng1) / 2) ** 2)\n return 2 * 6371.0 * math.asin(math.sqrt(a))\n\n\ndef norm_key(address: str) -> str:\n \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\"\n s = strip_accents((address or \"\").lower())\n s = re.sub(r\"\\b(?:app?t?|appartement|unite|suite|#)\\.?\\s*[\\w-]+\\b\", \" \", s)\n s = re.sub(r\"[^a-z0-9]+\", \" \", s)\n return re.sub(r\"\\s+\", \" \", s).strip()\n\n\nclass Geocoder:\n def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0\n self._villes: dict[str, dict | None] = {} # norm(ville) -> {lat,lng,muni}\n self._med: dict[str, tuple] | None = None # norm(ville) -> (lat,lng,n)\n self.ville_api_calls = 0 # requêtes Nominatim « ville »\n\n @staticmethod\n def _clean(address: str) -> str:\n \"\"\"Nettoyages qui aident Nominatim sur les adresses québécoises.\"\"\"\n s = address.strip()\n # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique\n s = re.sub(r\"^(\\d+)-(\\d+)\\s\", r\"\\2 \", s)\n # « 6275 et 6375 boulevard X » -> premier civique\n s = re.sub(r\"^(\\d+)\\s+et\\s+\\d+\\s\", r\"\\1 \", s)\n # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu\n s = re.sub(r\"montr[ée]al\\s*-\\s*\", \"\", s, flags=re.I)\n # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau\n s = re.sub(r\",?\\s*(?:bureau|suite|local|app\\.?|apt\\.?)\\s*[\\w-]+\\b\", \"\", s, flags=re.I)\n # « Vanier (Québec) » -> « Vanier, Québec »\n s = re.sub(r\"\\s*\\((qu[ée]bec)\\)\", r\", \\1\", s, flags=re.I)\n # abréviations cardinales : « Rue Salaberry O » -> « Ouest »\n s = re.sub(r\"\\bO\\.?(?=,|\\s*$)\", \"Ouest\", s)\n s = re.sub(r\"\\bE\\.?(?=,|\\s*$)\", \"Est\", s)\n return s\n\n def _build_query(self, address: str, city: str) -> str:\n q = self._clean(address)\n key = strip_accents(q.lower())\n if city and strip_accents(city.lower()) not in key:\n q += f\", {city}\"\n if \"quebec\" not in strip_accents(q.lower()) and \"qc\" not in q.lower():\n q += \", Québec\"\n return q + \", Canada\"\n\n def _query_nominatim(self, params: dict) -> tuple[float, float] | None:\n \"\"\"Une requête Nominatim, throttlée.\"\"\"\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"format\": \"jsonv2\", \"limit\": 1, \"countrycodes\": \"ca\", **params,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None\n if not hits:\n return None\n try:\n return float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n except (KeyError, ValueError):\n return None\n\n def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).\n\n Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE\n pour éviter les correspondances approximatives sur une autre rue.\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"Québec\").strip()\n wait = REQUEST_DELAY_AQ - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(AQ_URL, params={\n \"SingleLine\": f\"{premier}, {ville}\",\n \"f\": \"json\", \"outSR\": 4326, \"maxLocations\": 1,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n cands = resp.json().get(\"candidates\") or []\n except Exception:\n self._last = time.time()\n return None\n if not cands or cands[0].get(\"score\", 0) < AQ_MIN_SCORE:\n return None\n loc = cands[0].get(\"location\") or {}\n try:\n return float(loc[\"y\"]), float(loc[\"x\"])\n except (KeyError, ValueError):\n return None\n\n def _attempts(self, address: str, city: str) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) recherche libre complète\n 3) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n commun = {\"city\": ville, \"state\": \"Québec\", \"country\": \"Canada\"}\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis Nominatim. None si introuvable.\"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n bbox = _bbox_for(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if c is not None and _in_bbox(*c, bbox):\n coords = c\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city):\n c = self._query_nominatim(params)\n if c is not None and _in_bbox(*c, bbox):\n coords = c\n break\n ok = coords is not None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?)\"\n \" ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,\"\n \" lng=excluded.lng, provider=excluded.provider,\"\n \" failed=excluded.failed, ts=excluded.ts\",\n (key, coords[0] if ok else None, coords[1] if ok else None,\n provider, 0 if ok else 1, time.time()))\n self.con.commit()\n return coords if ok else None\n\n\ndef run(limit: int | None = None) -> dict:\n \"\"\"Géocode les annonces actives sans coordonnées, par adresse unique.\n\n `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de\n cache sont gratuits et toujours appliqués).\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0\n ORDER BY address\"\"\").fetchall()\n\n # regrouper par immeuble (adresse normalisée)\n groupes: dict[str, list] = {}\n for r in rows:\n groupes.setdefault(norm_key(r[\"address\"]), []).append(r)\n\n done = failed = requests_made = 0\n for key, members in groupes.items():\n if not key:\n continue\n cached = con.execute(\n \"SELECT failed FROM geocode_cache WHERE address=?\", (key,)).fetchone()\n if cached is None:\n if limit is not None and requests_made >= limit:\n continue\n requests_made += 1\n try:\n coords = geo.resolve(members[0][\"address\"], members[0][\"city\"])\n if coords:\n for r in members:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], r[\"uid\"]))\n done += len(members)\n else:\n # introuvable/hors zone : flag ; jamais de coordonnées bidon\n for r in members:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\",\n (r[\"uid\"],))\n failed += len(members)\n con.commit()\n except sqlite3.OperationalError:\n # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,\n # elle sera reprise au prochain passage — jamais crasher tout le run.\n try:\n con.rollback()\n except sqlite3.Error:\n pass\n time.sleep(1.0)\n continue\n\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed,\n \"unique_addresses\": len(groupes), \"api_requests\": requests_made}\n print(f\"[immo-ka] geocode {stats}\")\n return stats\n\n\nAQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200\n\n\ndef run_batch(limit: int | None = None) -> dict:\n \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de\n milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim).\"\"\"\n con = db.connect()\n geo = Geocoder(con) # pour réutiliser _clean / bbox\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0 ORDER BY address\"\"\").fetchall()\n # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache\n uniq: dict[str, dict] = {}\n for r in rows:\n k = norm_key(r[\"address\"])\n if not k or len(k) < 6:\n continue\n u = uniq.setdefault(k, {\"address\": r[\"address\"], \"city\": r[\"city\"],\n \"members\": []})\n u[\"members\"].append(r[\"uid\"])\n pending = []\n for k, u in uniq.items():\n c = con.execute(\"SELECT lat,lng,failed FROM geocode_cache WHERE address=?\",\n (k,)).fetchone()\n if c is not None and not c[\"failed\"]: # déjà résolu : appliquer direct\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (c[\"lat\"], c[\"lng\"], uid))\n continue\n if c is not None and c[\"failed\"]:\n continue\n pending.append((k, u))\n con.commit()\n if limit is not None:\n pending = pending[:limit]\n\n session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n if _in_bbox(*cand, _bbox_for(u[\"city\"])):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,1,?) ON CONFLICT(address) DO UPDATE SET\"\n \" failed=1, ts=excluded.ts\",\n (k, None, None, \"adresses_quebec_batch\", time.time()))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, échecs {failed})\")\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed, \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats\n","structuredPatch":[{"oldStart":174,"oldLines":12,"newStart":174,"newLines":14,"lines":[" except (KeyError, ValueError):"," return None"," ","- def _attempts(self, address: str, city: str) -> list[dict]:","+ def _attempts(self, address: str, city: str, muni: str | None = None) -> list[dict]:"," \"\"\"Stratégies de requête, de la plus précise à la moins précise."," "," 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)","- 2) recherche libre complète","- 3) structurée rue seule -> centroïde de rue (repli acceptable pour la","+ 2) idem avec la municipalité OFFICIELLE (« Saguenay ») quand la ville","+ annoncée est un secteur (« Jonquière (Lac-Kénogami) ») inconnu des API","+ 3) recherche libre complète","+ 4) structurée rue seule -> centroïde de rue (repli acceptable pour la"," carte quand le numéro civique est absent d'OpenStreetMap)"," \"\"\""," premier = self._clean(address).split(\",\")[0].strip()"]},{"oldStart":187,"oldLines":19,"newStart":189,"newLines":129,"lines":[" if not ville:"," k = strip_accents(address.lower())"," ville = \"Lévis\" if \"levis\" in k else \"Québec\"","- commun = {\"city\": ville, \"state\": \"Québec\", \"country\": \"Canada\"}","+ villes = [ville]","+ # premier mot de la ville (« Jonquiere Lac Kenogami » -> « Jonquiere »)","+ if \" \" in ville:","+ villes.append(ville.split(\" \")[0])","+ if muni and norm_key(muni) not in {norm_key(v) for v in villes}:","+ villes.append(muni)"," "," tries: list[dict] = []"," m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)","- if m:","- tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})","+ for v in villes:","+ commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}","+ if m:","+ tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})"," tries.append({\"q\": self._build_query(address, city)})","- if m:","- tries.append({\"street\": m.group(2), **commun})","+ for v in villes:","+ commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}","+ if m:","+ tries.append({\"street\": m.group(2), **commun})"," return tries"," ","+ # ----- centroïde de ville (validation rigoureuse) ------------------------","+ def _medians(self) -> dict[str, tuple]:","+ \"\"\"Centroïde (médiane lat/lng) par ville, depuis les fiches déjà","+ géocodées — gratuit, robuste aux erreurs isolées dès n >= 5.\"\"\"","+ if self._med is None:","+ acc: dict[str, list] = {}","+ for r in self.con.execute(","+ \"\"\"SELECT city, lat, lng FROM listings","+ WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\"):","+ acc.setdefault(norm_key(r[\"city\"]), []).append((r[\"lat\"], r[\"lng\"]))","+ self._med = {k: (statistics.median(p[0] for p in v),","+ statistics.median(p[1] for p in v), len(v))","+ for k, v in acc.items()}","+ return self._med","+","+ def resolve_ville(self, city: str, allow_api: bool = True) -> dict | None:","+ \"\"\"Ville -> {lat, lng, muni} (muni = municipalité officielle, ex.","+ « Jonquière (Lac-Kénogami) » -> Saguenay). Cache : geocode_cache,","+ clé « ville: ». None si irrésoluble.\"\"\"","+ k = norm_key(city or \"\")","+ if not k:","+ return None","+ if k in self._villes:","+ return self._villes[k]","+ key = \"ville:\" + k","+ row = self.con.execute(","+ \"SELECT lat, lng, muni, failed, ts FROM geocode_cache WHERE address=?\",","+ (key,)).fetchone()","+ if row is not None:","+ if not row[\"failed\"]:","+ v = {\"lat\": row[\"lat\"], \"lng\": row[\"lng\"], \"muni\": row[\"muni\"]}","+ self._villes[k] = v","+ return v","+ if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:","+ self._villes[k] = None","+ return None","+ if not allow_api:","+ return None # pas de mémoire : on réessaiera quand l'API sera permise","+ self.ville_api_calls += 1","+ wait = REQUEST_DELAY - (time.time() - self._last)","+ if wait > 0:","+ time.sleep(wait)","+ v = None","+ try:","+ resp = self.session.get(NOMINATIM_URL, params={","+ \"q\": f\"{city}, Québec, Canada\", \"format\": \"jsonv2\", \"limit\": 1,","+ \"countrycodes\": \"ca\", \"addressdetails\": 1}, timeout=20)","+ self._last = time.time()","+ resp.raise_for_status()","+ hits = resp.json()","+ except Exception:","+ self._last = time.time()","+ return None # erreur réseau : ne pas cacher un échec définitif","+ if hits:","+ try:","+ lat, lng = float(hits[0][\"lat\"]), float(hits[0][\"lon\"])","+ if _in_bbox(lat, lng, _BBOX_SUD_QC):","+ a = hits[0].get(\"address\") or {}","+ muni = (a.get(\"city\") or a.get(\"town\") or a.get(\"village\")","+ or a.get(\"municipality\"))","+ v = {\"lat\": lat, \"lng\": lng, \"muni\": muni}","+ except (KeyError, ValueError, TypeError):","+ v = None","+ self.con.execute(","+ \"INSERT INTO geocode_cache (address, lat, lng, muni, provider, failed, ts)\"","+ \" VALUES (?,?,?,?,?,?,?) ON CONFLICT(address) DO UPDATE SET\"","+ \" lat=excluded.lat, lng=excluded.lng, muni=excluded.muni,\"","+ \" provider=excluded.provider, failed=excluded.failed, ts=excluded.ts\",","+ (key, v[\"lat\"] if v else None, v[\"lng\"] if v else None,","+ v[\"muni\"] if v else None, \"ville_nominatim\", 0 if v else 1, time.time()))","+ self.con.commit()","+ self._villes[k] = v","+ return v","+","+ def city_reference(self, city: str, allow_api: bool = True) -> tuple[float, float] | None:","+ \"\"\"Centroïde de référence d'une ville : médiane des fiches (n >= 5),","+ sinon résolution Nominatim. None si inconnue (-> validation bbox seule).\"\"\"","+ k = norm_key(city or \"\")","+ if not k:","+ return None","+ med = self._medians().get(k)","+ if med and med[2] >= VILLE_MIN_SAMPLES:","+ return (med[0], med[1])","+ v = self.resolve_ville(city, allow_api=allow_api)","+ return (v[\"lat\"], v[\"lng\"]) if v else None","+","+ def coords_ok(self, c: tuple[float, float] | None, city: str,","+ ref: tuple[float, float] | None = None) -> bool:","+ \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM du","+ centroïde de la ville annoncée (quand il est connu).\"\"\"","+ if c is None or not _in_bbox(*c, _bbox_for(city)):","+ return False","+ if ref is None:","+ ref = self.city_reference(city)","+ return ref is None or _dist_km(c[0], c[1], ref[0], ref[1]) <= VILLE_RADIUS_KM","+"," def resolve(self, address: str, city: str) -> tuple[float, float] | None:","- \"\"\"Adresse -> (lat, lng), via cache puis Nominatim. None si introuvable.\"\"\"","+ \"\"\"Adresse -> (lat, lng), via cache puis AQ/Nominatim. None si introuvable.","+","+ Rigueur : chaque candidat doit être cohérent avec la ville annoncée","+ (centroïde <= VILLE_RADIUS_KM). Si la ville annoncée est un secteur","+ inconnu d'Adresses Québec, on réessaie avec la municipalité officielle.","+ \"\"\""," key = norm_key(address)"," if not key or len(key) < 6:"," return None"]},{"oldStart":212,"oldLines":19,"newStart":324,"newLines":29,"lines":[" if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:"," return None # échec récent : ne pas marteler l'API"," ","- bbox = _bbox_for(city)","+ ref = self.city_reference(city)"," coords = None"," # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de"," # limite stricte. Nominatim (1 req/s) seulement en repli."," provider = \"adresses_quebec\""," c = self._query_adresses_quebec(address, city)","- if c is not None and _in_bbox(*c, bbox):","+ if self.coords_ok(c, city, ref):"," coords = c","+ muni = None"," if coords is None:","+ # ville annoncée = secteur (« Jonquière (Lac-Kénogami) ») ? AQ ne","+ # connaît que les municipalités officielles -> retenter avec elle.","+ v = self.resolve_ville(city)","+ muni = (v or {}).get(\"muni\")","+ if muni and norm_key(muni) != norm_key(city or \"\"):","+ c = self._query_adresses_quebec(address, muni)","+ if self.coords_ok(c, city, ref):","+ coords, provider = c, \"adresses_quebec_muni\"","+ if coords is None:"," provider = \"nominatim\"","- for params in self._attempts(address, city):","+ for params in self._attempts(address, city, muni):"," c = self._query_nominatim(params)","- if c is not None and _in_bbox(*c, bbox):","+ if self.coords_ok(c, city, ref):"," coords = c"," break"," ok = coords is not None"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"6d303477-5efc-4357-a995-2ad1e0bbc35c","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXzghGDELRBZ1AyJrAC","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":4346,"cache_read_input_tokens":90658,"cache_creation":{"ephemeral_5m_input_tokens":4346,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"b9036fec-671b-4941-bf1b-8a4f21bbc88b"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXzghGDELRBZ1AyJrAC","type":"message","role":"assistant","content":[{"type":"text","text":"`resolve()` est renforcé. Maintenant `run_batch` : validation par centroïde et rattrapage individuel des échecs."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":4346,"cache_read_input_tokens":90658,"cache_creation":{"ephemeral_5m_input_tokens":4346,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"de472ed3-fd9c-4fe9-a24d-defb8ec19ae3"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXzghGDELRBZ1AyJrAC","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01FT8opdFaeMtmntwnmVNBLB","name":"TodoWrite","input":{"todos":[{"content":"geocode.py : centroïde de ville (médiane BD + Nominatim caché) et validation ≤40 km","status":"completed","activeForm":"Ajout de la validation par centroïde de ville"},{"content":"resolve() : retry AQ avec municipalité officielle + variantes Nominatim","status":"completed","activeForm":"Ajout des variantes de municipalité"},{"content":"run_batch : validation centroïde + rattrapage resolve() des échecs","status":"in_progress","activeForm":"Renforcement du géocodage batch"},{"content":"run_audit : détecter/corriger les fiches aux coordonnées incohérentes","status":"pending","activeForm":"Création de l'audit géocodage"},{"content":"Garde ingestion : rejeter les coords de connecteur contredisant la ville","status":"pending","activeForm":"Ajout de la garde à l'ingestion"},{"content":"db.py : colonne muni dans geocode_cache + CLI geocode-audit + watch","status":"pending","activeForm":"Migration BD et CLI"},{"content":"Corriger duproprio:1126225 + lancer l'audit + vérifier le site","status":"pending","activeForm":"Correction des fiches et vérification"},{"content":"pm2 restart + commit + push origin main","status":"pending","activeForm":"Redéploiement et commit"}]},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":4346,"cache_read_input_tokens":90658,"cache_creation":{"ephemeral_5m_input_tokens":4346,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ffd3f390-703c-4d4f-bb51-abee6da1317f"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01FT8opdFaeMtmntwnmVNBLB","type":"tool_result","content":"Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"87f70d2f-b827-4704-a47f-68732c322586","timestamp":"2026-08-25T13:20:43.565Z","tool_use_result":{"oldTodos":[{"content":"geocode.py : centroïde de ville (médiane BD + Nominatim caché) et validation ≤40 km","status":"in_progress","activeForm":"Ajout de la validation par centroïde de ville"},{"content":"resolve() : retry AQ avec municipalité officielle + variantes Nominatim","status":"pending","activeForm":"Ajout des variantes de municipalité"},{"content":"run_batch : validation centroïde + rattrapage resolve() des échecs","status":"pending","activeForm":"Renforcement du géocodage batch"},{"content":"run_audit : détecter/corriger les fiches aux coordonnées incohérentes","status":"pending","activeForm":"Création de l'audit géocodage"},{"content":"Garde ingestion : rejeter les coords de connecteur contredisant la ville","status":"pending","activeForm":"Ajout de la garde à l'ingestion"},{"content":"db.py : colonne muni dans geocode_cache + CLI geocode-audit + watch","status":"pending","activeForm":"Migration BD et CLI"},{"content":"Corriger duproprio:1126225 + lancer l'audit + vérifier le site","status":"pending","activeForm":"Correction des fiches et vérification"},{"content":"pm2 restart + commit + push origin main","status":"pending","activeForm":"Redéploiement et commit"}],"newTodos":[{"content":"geocode.py : centroïde de ville (médiane BD + Nominatim caché) et validation ≤40 km","status":"completed","activeForm":"Ajout de la validation par centroïde de ville"},{"content":"resolve() : retry AQ avec municipalité officielle + variantes Nominatim","status":"completed","activeForm":"Ajout des variantes de municipalité"},{"content":"run_batch : validation centroïde + rattrapage resolve() des échecs","status":"in_progress","activeForm":"Renforcement du géocodage batch"},{"content":"run_audit : détecter/corriger les fiches aux coordonnées incohérentes","status":"pending","activeForm":"Création de l'audit géocodage"},{"content":"Garde ingestion : rejeter les coords de connecteur contredisant la ville","status":"pending","activeForm":"Ajout de la garde à l'ingestion"},{"content":"db.py : colonne muni dans geocode_cache + CLI geocode-audit + watch","status":"pending","activeForm":"Migration BD et CLI"},{"content":"Corriger duproprio:1126225 + lancer l'audit + vérifier le site","status":"pending","activeForm":"Correction des fiches et vérification"},{"content":"pm2 restart + commit + push origin main","status":"pending","activeForm":"Redéploiement et commit"}],"verificationNudgeNeeded":false}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePXzghGDELRBZ1AyJrAC","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01PNPjKNdBv8ScMpaz9Rdpwd","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","old_string":" session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n if _in_bbox(*cand, _bbox_for(u[\"city\"])):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,1,?) ON CONFLICT(address) DO UPDATE SET\"\n \" failed=1, ts=excluded.ts\",\n (k, None, None, \"adresses_quebec_batch\", time.time()))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, échecs {failed})\")\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed, \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats","new_string":" session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n rescue: list[tuple[str, dict]] = [] # échecs du lot -> resolve() individuel\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n # bbox + cohérence avec le centroïde de la ville annoncée\n if geo.coords_ok(cand, u[\"city\"]):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n con.commit()\n else:\n # pas de verdict tout de suite : resolve() réessaiera avec la\n # municipalité officielle + Nominatim (borné par RESCUE_MAX)\n rescue.append((k, u))\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, à rattraper {len(rescue)})\")\n\n # Rattrapage 1-par-1 des échecs du lot : variantes de municipalité (AQ) puis\n # Nominatim, validées par centroïde. resolve() écrit lui-même le verdict au\n # cache (succès ou échec 30 j) ; au-delà de RESCUE_MAX, on laisse les fiches\n # intactes (ni cache ni flag) -> reprises aux prochains passages.\n rescued = 0\n for k, u in rescue[:RESCUE_MAX]:\n try:\n coords = geo.resolve(u[\"address\"], u[\"city\"])\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n done += len(u[\"members\"])\n rescued += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n con.close()\n stats = {\"geocoded\": done, \"rescued\": rescued, \"failed\": failed,\n \"deferred\": max(0, len(rescue) - RESCUE_MAX),\n \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats\n\n\ndef run_audit(nominatim_budget: int | None = None, apply: bool = True) -> dict:\n \"\"\"Audit de cohérence géographique des fiches DÉJÀ géocodées.\n\n Détecte les coordonnées à plus de VILLE_RADIUS_KM du centroïde de leur\n ville (rue homonyme d'une autre région, geo erroné fourni par la source…),\n puis les remet en file de géocodage : lat/lng annulés, geocode_failed remis\n à 0, entrée de cache purgée. `nominatim_budget` borne les résolutions de\n villes inconnues (1 req/s) ; None = illimité. `apply=False` = rapport seul.\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\").fetchall()\n flagged, villes_inconnues = [], 0\n for r in rows:\n allow = nominatim_budget is None or geo.ville_api_calls < nominatim_budget\n ref = geo.city_reference(r[\"city\"], allow_api=allow)\n if ref is None:\n villes_inconnues += 1\n continue\n d = _dist_km(r[\"lat\"], r[\"lng\"], ref[0], ref[1])\n if d > VILLE_RADIUS_KM:\n flagged.append((r, d))\n if apply:\n for r, d in flagged:\n con.execute(\"DELETE FROM geocode_cache WHERE address=?\",\n (norm_key(r[\"address\"]),))\n con.execute(\"\"\"UPDATE listings SET lat=NULL, lng=NULL,\n geocode_failed=0 WHERE uid=?\"\"\", (r[\"uid\"],))\n con.commit()\n for r, d in flagged[:20]:\n print(f\"[immo-ka] audit: {r['uid']} « {r['address']}, {r['city']} » \"\n f\"à {d:.0f} km de sa ville\")\n con.close()\n stats = {\"verifiees\": len(rows), \"incoherentes\": len(flagged),\n \"villes_inconnues\": villes_inconnues, \"corrigees\": apply}\n print(f\"[immo-ka] geocode-audit {stats}\")\n return stats"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":4346,"cache_read_input_tokens":90658,"cache_creation":{"ephemeral_5m_input_tokens":4346,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"b24af8e4-3a2a-4a9b-bb26-89a9806914e0"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01PNPjKNdBv8ScMpaz9Rdpwd","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"83a60182-c068-41e3-a662-1144b9450e59","timestamp":"2026-08-25T13:21:17.580Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","oldString":" session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n if _in_bbox(*cand, _bbox_for(u[\"city\"])):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,1,?) ON CONFLICT(address) DO UPDATE SET\"\n \" failed=1, ts=excluded.ts\",\n (k, None, None, \"adresses_quebec_batch\", time.time()))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, échecs {failed})\")\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed, \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats","newString":" session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n rescue: list[tuple[str, dict]] = [] # échecs du lot -> resolve() individuel\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n # bbox + cohérence avec le centroïde de la ville annoncée\n if geo.coords_ok(cand, u[\"city\"]):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n con.commit()\n else:\n # pas de verdict tout de suite : resolve() réessaiera avec la\n # municipalité officielle + Nominatim (borné par RESCUE_MAX)\n rescue.append((k, u))\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, à rattraper {len(rescue)})\")\n\n # Rattrapage 1-par-1 des échecs du lot : variantes de municipalité (AQ) puis\n # Nominatim, validées par centroïde. resolve() écrit lui-même le verdict au\n # cache (succès ou échec 30 j) ; au-delà de RESCUE_MAX, on laisse les fiches\n # intactes (ni cache ni flag) -> reprises aux prochains passages.\n rescued = 0\n for k, u in rescue[:RESCUE_MAX]:\n try:\n coords = geo.resolve(u[\"address\"], u[\"city\"])\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n done += len(u[\"members\"])\n rescued += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n con.close()\n stats = {\"geocoded\": done, \"rescued\": rescued, \"failed\": failed,\n \"deferred\": max(0, len(rescue) - RESCUE_MAX),\n \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats\n\n\ndef run_audit(nominatim_budget: int | None = None, apply: bool = True) -> dict:\n \"\"\"Audit de cohérence géographique des fiches DÉJÀ géocodées.\n\n Détecte les coordonnées à plus de VILLE_RADIUS_KM du centroïde de leur\n ville (rue homonyme d'une autre région, geo erroné fourni par la source…),\n puis les remet en file de géocodage : lat/lng annulés, geocode_failed remis\n à 0, entrée de cache purgée. `nominatim_budget` borne les résolutions de\n villes inconnues (1 req/s) ; None = illimité. `apply=False` = rapport seul.\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\").fetchall()\n flagged, villes_inconnues = [], 0\n for r in rows:\n allow = nominatim_budget is None or geo.ville_api_calls < nominatim_budget\n ref = geo.city_reference(r[\"city\"], allow_api=allow)\n if ref is None:\n villes_inconnues += 1\n continue\n d = _dist_km(r[\"lat\"], r[\"lng\"], ref[0], ref[1])\n if d > VILLE_RADIUS_KM:\n flagged.append((r, d))\n if apply:\n for r, d in flagged:\n con.execute(\"DELETE FROM geocode_cache WHERE address=?\",\n (norm_key(r[\"address\"]),))\n con.execute(\"\"\"UPDATE listings SET lat=NULL, lng=NULL,\n geocode_failed=0 WHERE uid=?\"\"\", (r[\"uid\"],))\n con.commit()\n for r, d in flagged[:20]:\n print(f\"[immo-ka] audit: {r['uid']} « {r['address']}, {r['city']} » \"\n f\"à {d:.0f} km de sa ville\")\n con.close()\n stats = {\"verifiees\": len(rows), \"incoherentes\": len(flagged),\n \"villes_inconnues\": villes_inconnues, \"corrigees\": apply}\n print(f\"[immo-ka] geocode-audit {stats}\")\n return stats","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)\n# - cache persistant (table geocode_cache) : une adresse n'est géocodée\n# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce\n# - politesse : 1 requête/seconde max, User-Agent identifiable\n# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# - rigueur : chaque résultat est validé contre le CENTROÏDE de la ville\n# annoncée (médiane des fiches déjà géocodées, sinon Nominatim, en cache) —\n# à plus de VILLE_RADIUS_KM du centroïde, le candidat est rejeté. Corrige\n# la classe de bug « rue homonyme dans une autre ville » (ex. rue des\n# Perdrix de Jonquière géocodée à Saint-Augustin).\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport math\nimport sqlite3\nimport statistics\n\nimport re\nimport time\n\nimport requests\n\nfrom . import db\nfrom .normalize import strip_accents\n\nNOMINATIM_URL = \"https://nominatim.openstreetmap.org/search\"\n# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre\n# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)\nAQ_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/findAddressCandidates\")\nAQ_MIN_SCORE = 75\n# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête\n# User-Agent contient des accents (latin-1)\nUSER_AGENT = \"ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)\"\nREQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s\nREQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte\nRETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours\n\n# Bounding boxes (lat_min, lat_max, lng_min, lng_max)\n_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord\n# et la Gaspésie (expansion provinciale) — même boîte que schema.finalize()\n_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n\n_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n# Validation « rigoureuse » : distance max entre un résultat de géocodage et le\n# centroïde de la ville annoncée. 40 km tolère les grandes municipalités\n# fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues\n# homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).\nVILLE_RADIUS_KM = 40.0\nVILLE_MIN_SAMPLES = 5 # médiane de fiches : min d'échantillons pour être fiable\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n\n\ndef _dist_km(lat1: float, lng1: float, lat2: float, lng2: float) -> float:\n \"\"\"Distance haversine en kilomètres.\"\"\"\n p1, p2 = math.radians(lat1), math.radians(lat2)\n a = (math.sin((p2 - p1) / 2) ** 2\n + math.cos(p1) * math.cos(p2) * math.sin(math.radians(lng2 - lng1) / 2) ** 2)\n return 2 * 6371.0 * math.asin(math.sqrt(a))\n\n\ndef norm_key(address: str) -> str:\n \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\"\n s = strip_accents((address or \"\").lower())\n s = re.sub(r\"\\b(?:app?t?|appartement|unite|suite|#)\\.?\\s*[\\w-]+\\b\", \" \", s)\n s = re.sub(r\"[^a-z0-9]+\", \" \", s)\n return re.sub(r\"\\s+\", \" \", s).strip()\n\n\nclass Geocoder:\n def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0\n self._villes: dict[str, dict | None] = {} # norm(ville) -> {lat,lng,muni}\n self._med: dict[str, tuple] | None = None # norm(ville) -> (lat,lng,n)\n self.ville_api_calls = 0 # requêtes Nominatim « ville »\n\n @staticmethod\n def _clean(address: str) -> str:\n \"\"\"Nettoyages qui aident Nominatim sur les adresses québécoises.\"\"\"\n s = address.strip()\n # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique\n s = re.sub(r\"^(\\d+)-(\\d+)\\s\", r\"\\2 \", s)\n # « 6275 et 6375 boulevard X » -> premier civique\n s = re.sub(r\"^(\\d+)\\s+et\\s+\\d+\\s\", r\"\\1 \", s)\n # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu\n s = re.sub(r\"montr[ée]al\\s*-\\s*\", \"\", s, flags=re.I)\n # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau\n s = re.sub(r\",?\\s*(?:bureau|suite|local|app\\.?|apt\\.?)\\s*[\\w-]+\\b\", \"\", s, flags=re.I)\n # « Vanier (Québec) » -> « Vanier, Québec »\n s = re.sub(r\"\\s*\\((qu[ée]bec)\\)\", r\", \\1\", s, flags=re.I)\n # abréviations cardinales : « Rue Salaberry O » -> « Ouest »\n s = re.sub(r\"\\bO\\.?(?=,|\\s*$)\", \"Ouest\", s)\n s = re.sub(r\"\\bE\\.?(?=,|\\s*$)\", \"Est\", s)\n return s\n\n def _build_query(self, address: str, city: str) -> str:\n q = self._clean(address)\n key = strip_accents(q.lower())\n if city and strip_accents(city.lower()) not in key:\n q += f\", {city}\"\n if \"quebec\" not in strip_accents(q.lower()) and \"qc\" not in q.lower():\n q += \", Québec\"\n return q + \", Canada\"\n\n def _query_nominatim(self, params: dict) -> tuple[float, float] | None:\n \"\"\"Une requête Nominatim, throttlée.\"\"\"\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"format\": \"jsonv2\", \"limit\": 1, \"countrycodes\": \"ca\", **params,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None\n if not hits:\n return None\n try:\n return float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n except (KeyError, ValueError):\n return None\n\n def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).\n\n Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE\n pour éviter les correspondances approximatives sur une autre rue.\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"Québec\").strip()\n wait = REQUEST_DELAY_AQ - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(AQ_URL, params={\n \"SingleLine\": f\"{premier}, {ville}\",\n \"f\": \"json\", \"outSR\": 4326, \"maxLocations\": 1,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n cands = resp.json().get(\"candidates\") or []\n except Exception:\n self._last = time.time()\n return None\n if not cands or cands[0].get(\"score\", 0) < AQ_MIN_SCORE:\n return None\n loc = cands[0].get(\"location\") or {}\n try:\n return float(loc[\"y\"]), float(loc[\"x\"])\n except (KeyError, ValueError):\n return None\n\n def _attempts(self, address: str, city: str, muni: str | None = None) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) idem avec la municipalité OFFICIELLE (« Saguenay ») quand la ville\n annoncée est un secteur (« Jonquière (Lac-Kénogami) ») inconnu des API\n 3) recherche libre complète\n 4) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n villes = [ville]\n # premier mot de la ville (« Jonquiere Lac Kenogami » -> « Jonquiere »)\n if \" \" in ville:\n villes.append(ville.split(\" \")[0])\n if muni and norm_key(muni) not in {norm_key(v) for v in villes}:\n villes.append(muni)\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n # ----- centroïde de ville (validation rigoureuse) ------------------------\n def _medians(self) -> dict[str, tuple]:\n \"\"\"Centroïde (médiane lat/lng) par ville, depuis les fiches déjà\n géocodées — gratuit, robuste aux erreurs isolées dès n >= 5.\"\"\"\n if self._med is None:\n acc: dict[str, list] = {}\n for r in self.con.execute(\n \"\"\"SELECT city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\"):\n acc.setdefault(norm_key(r[\"city\"]), []).append((r[\"lat\"], r[\"lng\"]))\n self._med = {k: (statistics.median(p[0] for p in v),\n statistics.median(p[1] for p in v), len(v))\n for k, v in acc.items()}\n return self._med\n\n def resolve_ville(self, city: str, allow_api: bool = True) -> dict | None:\n \"\"\"Ville -> {lat, lng, muni} (muni = municipalité officielle, ex.\n « Jonquière (Lac-Kénogami) » -> Saguenay). Cache : geocode_cache,\n clé « ville: ». None si irrésoluble.\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n if k in self._villes:\n return self._villes[k]\n key = \"ville:\" + k\n row = self.con.execute(\n \"SELECT lat, lng, muni, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n v = {\"lat\": row[\"lat\"], \"lng\": row[\"lng\"], \"muni\": row[\"muni\"]}\n self._villes[k] = v\n return v\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n self._villes[k] = None\n return None\n if not allow_api:\n return None # pas de mémoire : on réessaiera quand l'API sera permise\n self.ville_api_calls += 1\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n v = None\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"q\": f\"{city}, Québec, Canada\", \"format\": \"jsonv2\", \"limit\": 1,\n \"countrycodes\": \"ca\", \"addressdetails\": 1}, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None # erreur réseau : ne pas cacher un échec définitif\n if hits:\n try:\n lat, lng = float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n if _in_bbox(lat, lng, _BBOX_SUD_QC):\n a = hits[0].get(\"address\") or {}\n muni = (a.get(\"city\") or a.get(\"town\") or a.get(\"village\")\n or a.get(\"municipality\"))\n v = {\"lat\": lat, \"lng\": lng, \"muni\": muni}\n except (KeyError, ValueError, TypeError):\n v = None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, muni, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, muni=excluded.muni,\"\n \" provider=excluded.provider, failed=excluded.failed, ts=excluded.ts\",\n (key, v[\"lat\"] if v else None, v[\"lng\"] if v else None,\n v[\"muni\"] if v else None, \"ville_nominatim\", 0 if v else 1, time.time()))\n self.con.commit()\n self._villes[k] = v\n return v\n\n def city_reference(self, city: str, allow_api: bool = True) -> tuple[float, float] | None:\n \"\"\"Centroïde de référence d'une ville : médiane des fiches (n >= 5),\n sinon résolution Nominatim. None si inconnue (-> validation bbox seule).\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n med = self._medians().get(k)\n if med and med[2] >= VILLE_MIN_SAMPLES:\n return (med[0], med[1])\n v = self.resolve_ville(city, allow_api=allow_api)\n return (v[\"lat\"], v[\"lng\"]) if v else None\n\n def coords_ok(self, c: tuple[float, float] | None, city: str,\n ref: tuple[float, float] | None = None) -> bool:\n \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM du\n centroïde de la ville annoncée (quand il est connu).\"\"\"\n if c is None or not _in_bbox(*c, _bbox_for(city)):\n return False\n if ref is None:\n ref = self.city_reference(city)\n return ref is None or _dist_km(c[0], c[1], ref[0], ref[1]) <= VILLE_RADIUS_KM\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis AQ/Nominatim. None si introuvable.\n\n Rigueur : chaque candidat doit être cohérent avec la ville annoncée\n (centroïde <= VILLE_RADIUS_KM). Si la ville annoncée est un secteur\n inconnu d'Adresses Québec, on réessaie avec la municipalité officielle.\n \"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n ref = self.city_reference(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if self.coords_ok(c, city, ref):\n coords = c\n muni = None\n if coords is None:\n # ville annoncée = secteur (« Jonquière (Lac-Kénogami) ») ? AQ ne\n # connaît que les municipalités officielles -> retenter avec elle.\n v = self.resolve_ville(city)\n muni = (v or {}).get(\"muni\")\n if muni and norm_key(muni) != norm_key(city or \"\"):\n c = self._query_adresses_quebec(address, muni)\n if self.coords_ok(c, city, ref):\n coords, provider = c, \"adresses_quebec_muni\"\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city, muni):\n c = self._query_nominatim(params)\n if self.coords_ok(c, city, ref):\n coords = c\n break\n ok = coords is not None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?)\"\n \" ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,\"\n \" lng=excluded.lng, provider=excluded.provider,\"\n \" failed=excluded.failed, ts=excluded.ts\",\n (key, coords[0] if ok else None, coords[1] if ok else None,\n provider, 0 if ok else 1, time.time()))\n self.con.commit()\n return coords if ok else None\n\n\ndef run(limit: int | None = None) -> dict:\n \"\"\"Géocode les annonces actives sans coordonnées, par adresse unique.\n\n `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de\n cache sont gratuits et toujours appliqués).\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0\n ORDER BY address\"\"\").fetchall()\n\n # regrouper par immeuble (adresse normalisée)\n groupes: dict[str, list] = {}\n for r in rows:\n groupes.setdefault(norm_key(r[\"address\"]), []).append(r)\n\n done = failed = requests_made = 0\n for key, members in groupes.items():\n if not key:\n continue\n cached = con.execute(\n \"SELECT failed FROM geocode_cache WHERE address=?\", (key,)).fetchone()\n if cached is None:\n if limit is not None and requests_made >= limit:\n continue\n requests_made += 1\n try:\n coords = geo.resolve(members[0][\"address\"], members[0][\"city\"])\n if coords:\n for r in members:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], r[\"uid\"]))\n done += len(members)\n else:\n # introuvable/hors zone : flag ; jamais de coordonnées bidon\n for r in members:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\",\n (r[\"uid\"],))\n failed += len(members)\n con.commit()\n except sqlite3.OperationalError:\n # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,\n # elle sera reprise au prochain passage — jamais crasher tout le run.\n try:\n con.rollback()\n except sqlite3.Error:\n pass\n time.sleep(1.0)\n continue\n\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed,\n \"unique_addresses\": len(groupes), \"api_requests\": requests_made}\n print(f\"[immo-ka] geocode {stats}\")\n return stats\n\n\nAQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200\n\n\ndef run_batch(limit: int | None = None) -> dict:\n \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de\n milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim).\"\"\"\n con = db.connect()\n geo = Geocoder(con) # pour réutiliser _clean / bbox\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0 ORDER BY address\"\"\").fetchall()\n # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache\n uniq: dict[str, dict] = {}\n for r in rows:\n k = norm_key(r[\"address\"])\n if not k or len(k) < 6:\n continue\n u = uniq.setdefault(k, {\"address\": r[\"address\"], \"city\": r[\"city\"],\n \"members\": []})\n u[\"members\"].append(r[\"uid\"])\n pending = []\n for k, u in uniq.items():\n c = con.execute(\"SELECT lat,lng,failed FROM geocode_cache WHERE address=?\",\n (k,)).fetchone()\n if c is not None and not c[\"failed\"]: # déjà résolu : appliquer direct\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (c[\"lat\"], c[\"lng\"], uid))\n continue\n if c is not None and c[\"failed\"]:\n continue\n pending.append((k, u))\n con.commit()\n if limit is not None:\n pending = pending[:limit]\n\n session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n if _in_bbox(*cand, _bbox_for(u[\"city\"])):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,1,?) ON CONFLICT(address) DO UPDATE SET\"\n \" failed=1, ts=excluded.ts\",\n (k, None, None, \"adresses_quebec_batch\", time.time()))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, échecs {failed})\")\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed, \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats\n","structuredPatch":[{"oldStart":465,"oldLines":6,"newStart":465,"newLines":7,"lines":[" session = requests.Session()"," session.headers[\"User-Agent\"] = USER_AGENT"," done = failed = 0","+ rescue: list[tuple[str, dict]] = [] # échecs du lot -> resolve() individuel"," for i in range(0, len(pending), BATCH_SIZE):"," chunk = pending[i:i + BATCH_SIZE]"," records = {\"records\": ["]},{"oldStart":491,"oldLines":7,"newStart":492,"newLines":8,"lines":[" lc = loc.get(\"location\") or {}"," try:"," cand = (float(lc[\"y\"]), float(lc[\"x\"]))","- if _in_bbox(*cand, _bbox_for(u[\"city\"])):","+ # bbox + cohérence avec le centroïde de la ville annoncée","+ if geo.coords_ok(cand, u[\"city\"]):"," coords = cand"," except (KeyError, ValueError, TypeError):"," coords = None"]},{"oldStart":507,"oldLines":23,"newStart":509,"newLines":85,"lines":[" \" failed=0, ts=excluded.ts\","," (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))"," done += len(u[\"members\"])","+ con.commit()"," else:","- for uid in u[\"members\"]:","- con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))","- con.execute(","- \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"","- \" VALUES (?,?,?,?,1,?) ON CONFLICT(address) DO UPDATE SET\"","- \" failed=1, ts=excluded.ts\",","- (k, None, None, \"adresses_quebec_batch\", time.time()))","- failed += len(u[\"members\"])","- con.commit()","+ # pas de verdict tout de suite : resolve() réessaiera avec la","+ # municipalité officielle + Nominatim (borné par RESCUE_MAX)","+ rescue.append((k, u))"," except sqlite3.OperationalError:"," try: con.rollback()"," except sqlite3.Error: pass"," time.sleep(1.0)"," print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"","- f\"(résolues {done}, échecs {failed})\")","+ f\"(résolues {done}, à rattraper {len(rescue)})\")","+","+ # Rattrapage 1-par-1 des échecs du lot : variantes de municipalité (AQ) puis","+ # Nominatim, validées par centroïde. resolve() écrit lui-même le verdict au","+ # cache (succès ou échec 30 j) ; au-delà de RESCUE_MAX, on laisse les fiches","+ # intactes (ni cache ni flag) -> reprises aux prochains passages.","+ rescued = 0","+ for k, u in rescue[:RESCUE_MAX]:","+ try:","+ coords = geo.resolve(u[\"address\"], u[\"city\"])","+ if coords:","+ for uid in u[\"members\"]:","+ con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",","+ (coords[0], coords[1], uid))","+ done += len(u[\"members\"])","+ rescued += len(u[\"members\"])","+ else:","+ for uid in u[\"members\"]:","+ con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))","+ failed += len(u[\"members\"])","+ con.commit()","+ except sqlite3.OperationalError:","+ try: con.rollback()","+ except sqlite3.Error: pass","+ time.sleep(1.0)"," con.close()","- stats = {\"geocoded\": done, \"failed\": failed, \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}","+ stats = {\"geocoded\": done, \"rescued\": rescued, \"failed\": failed,","+ \"deferred\": max(0, len(rescue) - RESCUE_MAX),","+ \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}"," print(f\"[immo-ka] geocode-batch {stats}\")"," return stats","+","+","+def run_audit(nominatim_budget: int | None = None, apply: bool = True) -> dict:","+ \"\"\"Audit de cohérence géographique des fiches DÉJÀ géocodées.","+","+ Détecte les coordonnées à plus de VILLE_RADIUS_KM du centroïde de leur","+ ville (rue homonyme d'une autre région, geo erroné fourni par la source…),","+ puis les remet en file de géocodage : lat/lng annulés, geocode_failed remis","+ à 0, entrée de cache purgée. `nominatim_budget` borne les résolutions de","+ villes inconnues (1 req/s) ; None = illimité. `apply=False` = rapport seul.","+ \"\"\"","+ con = db.connect()","+ geo = Geocoder(con)","+ rows = con.execute(","+ \"\"\"SELECT uid, address, city, lat, lng FROM listings","+ WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\").fetchall()","+ flagged, villes_inconnues = [], 0","+ for r in rows:","+ allow = nominatim_budget is None or geo.ville_api_calls < nominatim_budget","+ ref = geo.city_reference(r[\"city\"], allow_api=allow)","+ if ref is None:","+ villes_inconnues += 1","+ continue","+ d = _dist_km(r[\"lat\"], r[\"lng\"], ref[0], ref[1])","+ if d > VILLE_RADIUS_KM:","+ flagged.append((r, d))","+ if apply:","+ for r, d in flagged:","+ con.execute(\"DELETE FROM geocode_cache WHERE address=?\",","+ (norm_key(r[\"address\"]),))","+ con.execute(\"\"\"UPDATE listings SET lat=NULL, lng=NULL,","+ geocode_failed=0 WHERE uid=?\"\"\", (r[\"uid\"],))","+ con.commit()","+ for r, d in flagged[:20]:","+ print(f\"[immo-ka] audit: {r['uid']} « {r['address']}, {r['city']} » \"","+ f\"à {d:.0f} km de sa ville\")","+ con.close()","+ stats = {\"verifiees\": len(rows), \"incoherentes\": len(flagged),","+ \"villes_inconnues\": villes_inconnues, \"corrigees\": apply}","+ print(f\"[immo-ka] geocode-audit {stats}\")","+ return stats"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"8ad469de-bb00-415f-b457-aad582daf4a2","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY4HFjKnrTyDA8zf6jz","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":5004,"cache_read_input_tokens":95004,"cache_creation":{"ephemeral_5m_input_tokens":5004,"ephemeral_1h_input_tokens":0},"output_tokens":5,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"558b6e04-83c5-4171-8b97-5d675b5280f4"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY4HFjKnrTyDA8zf6jz","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01HHYvgfcHdmsJ7q932ak2uo","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","old_string":"AQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200","new_string":"AQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200\nRESCUE_MAX = 150 # rattrapages resolve() max par passe (Nominatim = 1 req/s)\n\n\ndef strip_bad_source_coords(con, listings) -> int:\n \"\"\"Garde d'ingestion : annule les lat/lng fournis par un connecteur quand\n ils contredisent la ville annoncée (> VILLE_RADIUS_KM du centroïde connu).\n Cache seulement (médianes + villes déjà résolues) : aucun appel réseau,\n la synchronisation reste rapide. Retourne le nombre de paires annulées.\"\"\"\n geo = Geocoder(con)\n n = 0\n for lst in listings:\n if lst.lat is None or lst.lng is None or not (lst.city or \"\").strip():\n continue\n ref = geo.city_reference(lst.city, allow_api=False)\n if ref and _dist_km(lst.lat, lst.lng, ref[0], ref[1]) > VILLE_RADIUS_KM:\n lst.lat = lst.lng = None\n n += 1\n return n"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":5004,"cache_read_input_tokens":95004,"cache_creation":{"ephemeral_5m_input_tokens":5004,"ephemeral_1h_input_tokens":0},"output_tokens":5,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"148a42cc-b749-4051-8f30-b53d47dc17c6"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01HHYvgfcHdmsJ7q932ak2uo","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"912aa447-7ea8-42eb-9b9e-7fbb75bf25b7","timestamp":"2026-08-25T13:21:29.773Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","oldString":"AQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200","newString":"AQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200\nRESCUE_MAX = 150 # rattrapages resolve() max par passe (Nominatim = 1 req/s)\n\n\ndef strip_bad_source_coords(con, listings) -> int:\n \"\"\"Garde d'ingestion : annule les lat/lng fournis par un connecteur quand\n ils contredisent la ville annoncée (> VILLE_RADIUS_KM du centroïde connu).\n Cache seulement (médianes + villes déjà résolues) : aucun appel réseau,\n la synchronisation reste rapide. Retourne le nombre de paires annulées.\"\"\"\n geo = Geocoder(con)\n n = 0\n for lst in listings:\n if lst.lat is None or lst.lng is None or not (lst.city or \"\").strip():\n continue\n ref = geo.city_reference(lst.city, allow_api=False)\n if ref and _dist_km(lst.lat, lst.lng, ref[0], ref[1]) > VILLE_RADIUS_KM:\n lst.lat = lst.lng = None\n n += 1\n return n","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)\n# - cache persistant (table geocode_cache) : une adresse n'est géocodée\n# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce\n# - politesse : 1 requête/seconde max, User-Agent identifiable\n# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# - rigueur : chaque résultat est validé contre le CENTROÏDE de la ville\n# annoncée (médiane des fiches déjà géocodées, sinon Nominatim, en cache) —\n# à plus de VILLE_RADIUS_KM du centroïde, le candidat est rejeté. Corrige\n# la classe de bug « rue homonyme dans une autre ville » (ex. rue des\n# Perdrix de Jonquière géocodée à Saint-Augustin).\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport math\nimport sqlite3\nimport statistics\n\nimport re\nimport time\n\nimport requests\n\nfrom . import db\nfrom .normalize import strip_accents\n\nNOMINATIM_URL = \"https://nominatim.openstreetmap.org/search\"\n# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre\n# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)\nAQ_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/findAddressCandidates\")\nAQ_MIN_SCORE = 75\n# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête\n# User-Agent contient des accents (latin-1)\nUSER_AGENT = \"ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)\"\nREQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s\nREQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte\nRETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours\n\n# Bounding boxes (lat_min, lat_max, lng_min, lng_max)\n_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord\n# et la Gaspésie (expansion provinciale) — même boîte que schema.finalize()\n_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n\n_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n# Validation « rigoureuse » : distance max entre un résultat de géocodage et le\n# centroïde de la ville annoncée. 40 km tolère les grandes municipalités\n# fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues\n# homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).\nVILLE_RADIUS_KM = 40.0\nVILLE_MIN_SAMPLES = 5 # médiane de fiches : min d'échantillons pour être fiable\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n\n\ndef _dist_km(lat1: float, lng1: float, lat2: float, lng2: float) -> float:\n \"\"\"Distance haversine en kilomètres.\"\"\"\n p1, p2 = math.radians(lat1), math.radians(lat2)\n a = (math.sin((p2 - p1) / 2) ** 2\n + math.cos(p1) * math.cos(p2) * math.sin(math.radians(lng2 - lng1) / 2) ** 2)\n return 2 * 6371.0 * math.asin(math.sqrt(a))\n\n\ndef norm_key(address: str) -> str:\n \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\"\n s = strip_accents((address or \"\").lower())\n s = re.sub(r\"\\b(?:app?t?|appartement|unite|suite|#)\\.?\\s*[\\w-]+\\b\", \" \", s)\n s = re.sub(r\"[^a-z0-9]+\", \" \", s)\n return re.sub(r\"\\s+\", \" \", s).strip()\n\n\nclass Geocoder:\n def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0\n self._villes: dict[str, dict | None] = {} # norm(ville) -> {lat,lng,muni}\n self._med: dict[str, tuple] | None = None # norm(ville) -> (lat,lng,n)\n self.ville_api_calls = 0 # requêtes Nominatim « ville »\n\n @staticmethod\n def _clean(address: str) -> str:\n \"\"\"Nettoyages qui aident Nominatim sur les adresses québécoises.\"\"\"\n s = address.strip()\n # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique\n s = re.sub(r\"^(\\d+)-(\\d+)\\s\", r\"\\2 \", s)\n # « 6275 et 6375 boulevard X » -> premier civique\n s = re.sub(r\"^(\\d+)\\s+et\\s+\\d+\\s\", r\"\\1 \", s)\n # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu\n s = re.sub(r\"montr[ée]al\\s*-\\s*\", \"\", s, flags=re.I)\n # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau\n s = re.sub(r\",?\\s*(?:bureau|suite|local|app\\.?|apt\\.?)\\s*[\\w-]+\\b\", \"\", s, flags=re.I)\n # « Vanier (Québec) » -> « Vanier, Québec »\n s = re.sub(r\"\\s*\\((qu[ée]bec)\\)\", r\", \\1\", s, flags=re.I)\n # abréviations cardinales : « Rue Salaberry O » -> « Ouest »\n s = re.sub(r\"\\bO\\.?(?=,|\\s*$)\", \"Ouest\", s)\n s = re.sub(r\"\\bE\\.?(?=,|\\s*$)\", \"Est\", s)\n return s\n\n def _build_query(self, address: str, city: str) -> str:\n q = self._clean(address)\n key = strip_accents(q.lower())\n if city and strip_accents(city.lower()) not in key:\n q += f\", {city}\"\n if \"quebec\" not in strip_accents(q.lower()) and \"qc\" not in q.lower():\n q += \", Québec\"\n return q + \", Canada\"\n\n def _query_nominatim(self, params: dict) -> tuple[float, float] | None:\n \"\"\"Une requête Nominatim, throttlée.\"\"\"\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"format\": \"jsonv2\", \"limit\": 1, \"countrycodes\": \"ca\", **params,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None\n if not hits:\n return None\n try:\n return float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n except (KeyError, ValueError):\n return None\n\n def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).\n\n Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE\n pour éviter les correspondances approximatives sur une autre rue.\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"Québec\").strip()\n wait = REQUEST_DELAY_AQ - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(AQ_URL, params={\n \"SingleLine\": f\"{premier}, {ville}\",\n \"f\": \"json\", \"outSR\": 4326, \"maxLocations\": 1,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n cands = resp.json().get(\"candidates\") or []\n except Exception:\n self._last = time.time()\n return None\n if not cands or cands[0].get(\"score\", 0) < AQ_MIN_SCORE:\n return None\n loc = cands[0].get(\"location\") or {}\n try:\n return float(loc[\"y\"]), float(loc[\"x\"])\n except (KeyError, ValueError):\n return None\n\n def _attempts(self, address: str, city: str, muni: str | None = None) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) idem avec la municipalité OFFICIELLE (« Saguenay ») quand la ville\n annoncée est un secteur (« Jonquière (Lac-Kénogami) ») inconnu des API\n 3) recherche libre complète\n 4) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n villes = [ville]\n # premier mot de la ville (« Jonquiere Lac Kenogami » -> « Jonquiere »)\n if \" \" in ville:\n villes.append(ville.split(\" \")[0])\n if muni and norm_key(muni) not in {norm_key(v) for v in villes}:\n villes.append(muni)\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n # ----- centroïde de ville (validation rigoureuse) ------------------------\n def _medians(self) -> dict[str, tuple]:\n \"\"\"Centroïde (médiane lat/lng) par ville, depuis les fiches déjà\n géocodées — gratuit, robuste aux erreurs isolées dès n >= 5.\"\"\"\n if self._med is None:\n acc: dict[str, list] = {}\n for r in self.con.execute(\n \"\"\"SELECT city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\"):\n acc.setdefault(norm_key(r[\"city\"]), []).append((r[\"lat\"], r[\"lng\"]))\n self._med = {k: (statistics.median(p[0] for p in v),\n statistics.median(p[1] for p in v), len(v))\n for k, v in acc.items()}\n return self._med\n\n def resolve_ville(self, city: str, allow_api: bool = True) -> dict | None:\n \"\"\"Ville -> {lat, lng, muni} (muni = municipalité officielle, ex.\n « Jonquière (Lac-Kénogami) » -> Saguenay). Cache : geocode_cache,\n clé « ville: ». None si irrésoluble.\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n if k in self._villes:\n return self._villes[k]\n key = \"ville:\" + k\n row = self.con.execute(\n \"SELECT lat, lng, muni, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n v = {\"lat\": row[\"lat\"], \"lng\": row[\"lng\"], \"muni\": row[\"muni\"]}\n self._villes[k] = v\n return v\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n self._villes[k] = None\n return None\n if not allow_api:\n return None # pas de mémoire : on réessaiera quand l'API sera permise\n self.ville_api_calls += 1\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n v = None\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"q\": f\"{city}, Québec, Canada\", \"format\": \"jsonv2\", \"limit\": 1,\n \"countrycodes\": \"ca\", \"addressdetails\": 1}, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None # erreur réseau : ne pas cacher un échec définitif\n if hits:\n try:\n lat, lng = float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n if _in_bbox(lat, lng, _BBOX_SUD_QC):\n a = hits[0].get(\"address\") or {}\n muni = (a.get(\"city\") or a.get(\"town\") or a.get(\"village\")\n or a.get(\"municipality\"))\n v = {\"lat\": lat, \"lng\": lng, \"muni\": muni}\n except (KeyError, ValueError, TypeError):\n v = None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, muni, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, muni=excluded.muni,\"\n \" provider=excluded.provider, failed=excluded.failed, ts=excluded.ts\",\n (key, v[\"lat\"] if v else None, v[\"lng\"] if v else None,\n v[\"muni\"] if v else None, \"ville_nominatim\", 0 if v else 1, time.time()))\n self.con.commit()\n self._villes[k] = v\n return v\n\n def city_reference(self, city: str, allow_api: bool = True) -> tuple[float, float] | None:\n \"\"\"Centroïde de référence d'une ville : médiane des fiches (n >= 5),\n sinon résolution Nominatim. None si inconnue (-> validation bbox seule).\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n med = self._medians().get(k)\n if med and med[2] >= VILLE_MIN_SAMPLES:\n return (med[0], med[1])\n v = self.resolve_ville(city, allow_api=allow_api)\n return (v[\"lat\"], v[\"lng\"]) if v else None\n\n def coords_ok(self, c: tuple[float, float] | None, city: str,\n ref: tuple[float, float] | None = None) -> bool:\n \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM du\n centroïde de la ville annoncée (quand il est connu).\"\"\"\n if c is None or not _in_bbox(*c, _bbox_for(city)):\n return False\n if ref is None:\n ref = self.city_reference(city)\n return ref is None or _dist_km(c[0], c[1], ref[0], ref[1]) <= VILLE_RADIUS_KM\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis AQ/Nominatim. None si introuvable.\n\n Rigueur : chaque candidat doit être cohérent avec la ville annoncée\n (centroïde <= VILLE_RADIUS_KM). Si la ville annoncée est un secteur\n inconnu d'Adresses Québec, on réessaie avec la municipalité officielle.\n \"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n ref = self.city_reference(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if self.coords_ok(c, city, ref):\n coords = c\n muni = None\n if coords is None:\n # ville annoncée = secteur (« Jonquière (Lac-Kénogami) ») ? AQ ne\n # connaît que les municipalités officielles -> retenter avec elle.\n v = self.resolve_ville(city)\n muni = (v or {}).get(\"muni\")\n if muni and norm_key(muni) != norm_key(city or \"\"):\n c = self._query_adresses_quebec(address, muni)\n if self.coords_ok(c, city, ref):\n coords, provider = c, \"adresses_quebec_muni\"\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city, muni):\n c = self._query_nominatim(params)\n if self.coords_ok(c, city, ref):\n coords = c\n break\n ok = coords is not None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?)\"\n \" ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,\"\n \" lng=excluded.lng, provider=excluded.provider,\"\n \" failed=excluded.failed, ts=excluded.ts\",\n (key, coords[0] if ok else None, coords[1] if ok else None,\n provider, 0 if ok else 1, time.time()))\n self.con.commit()\n return coords if ok else None\n\n\ndef run(limit: int | None = None) -> dict:\n \"\"\"Géocode les annonces actives sans coordonnées, par adresse unique.\n\n `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de\n cache sont gratuits et toujours appliqués).\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0\n ORDER BY address\"\"\").fetchall()\n\n # regrouper par immeuble (adresse normalisée)\n groupes: dict[str, list] = {}\n for r in rows:\n groupes.setdefault(norm_key(r[\"address\"]), []).append(r)\n\n done = failed = requests_made = 0\n for key, members in groupes.items():\n if not key:\n continue\n cached = con.execute(\n \"SELECT failed FROM geocode_cache WHERE address=?\", (key,)).fetchone()\n if cached is None:\n if limit is not None and requests_made >= limit:\n continue\n requests_made += 1\n try:\n coords = geo.resolve(members[0][\"address\"], members[0][\"city\"])\n if coords:\n for r in members:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], r[\"uid\"]))\n done += len(members)\n else:\n # introuvable/hors zone : flag ; jamais de coordonnées bidon\n for r in members:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\",\n (r[\"uid\"],))\n failed += len(members)\n con.commit()\n except sqlite3.OperationalError:\n # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,\n # elle sera reprise au prochain passage — jamais crasher tout le run.\n try:\n con.rollback()\n except sqlite3.Error:\n pass\n time.sleep(1.0)\n continue\n\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed,\n \"unique_addresses\": len(groupes), \"api_requests\": requests_made}\n print(f\"[immo-ka] geocode {stats}\")\n return stats\n\n\nAQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200\n\n\ndef run_batch(limit: int | None = None) -> dict:\n \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de\n milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim).\"\"\"\n con = db.connect()\n geo = Geocoder(con) # pour réutiliser _clean / bbox\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0 ORDER BY address\"\"\").fetchall()\n # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache\n uniq: dict[str, dict] = {}\n for r in rows:\n k = norm_key(r[\"address\"])\n if not k or len(k) < 6:\n continue\n u = uniq.setdefault(k, {\"address\": r[\"address\"], \"city\": r[\"city\"],\n \"members\": []})\n u[\"members\"].append(r[\"uid\"])\n pending = []\n for k, u in uniq.items():\n c = con.execute(\"SELECT lat,lng,failed FROM geocode_cache WHERE address=?\",\n (k,)).fetchone()\n if c is not None and not c[\"failed\"]: # déjà résolu : appliquer direct\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (c[\"lat\"], c[\"lng\"], uid))\n continue\n if c is not None and c[\"failed\"]:\n continue\n pending.append((k, u))\n con.commit()\n if limit is not None:\n pending = pending[:limit]\n\n session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n rescue: list[tuple[str, dict]] = [] # échecs du lot -> resolve() individuel\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n # bbox + cohérence avec le centroïde de la ville annoncée\n if geo.coords_ok(cand, u[\"city\"]):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n con.commit()\n else:\n # pas de verdict tout de suite : resolve() réessaiera avec la\n # municipalité officielle + Nominatim (borné par RESCUE_MAX)\n rescue.append((k, u))\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, à rattraper {len(rescue)})\")\n\n # Rattrapage 1-par-1 des échecs du lot : variantes de municipalité (AQ) puis\n # Nominatim, validées par centroïde. resolve() écrit lui-même le verdict au\n # cache (succès ou échec 30 j) ; au-delà de RESCUE_MAX, on laisse les fiches\n # intactes (ni cache ni flag) -> reprises aux prochains passages.\n rescued = 0\n for k, u in rescue[:RESCUE_MAX]:\n try:\n coords = geo.resolve(u[\"address\"], u[\"city\"])\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n done += len(u[\"members\"])\n rescued += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n con.close()\n stats = {\"geocoded\": done, \"rescued\": rescued, \"failed\": failed,\n \"deferred\": max(0, len(rescue) - RESCUE_MAX),\n \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats\n\n\ndef run_audit(nominatim_budget: int | None = None, apply: bool = True) -> dict:\n \"\"\"Audit de cohérence géographique des fiches DÉJÀ géocodées.\n\n Détecte les coordonnées à plus de VILLE_RADIUS_KM du centroïde de leur\n ville (rue homonyme d'une autre région, geo erroné fourni par la source…),\n puis les remet en file de géocodage : lat/lng annulés, geocode_failed remis\n à 0, entrée de cache purgée. `nominatim_budget` borne les résolutions de\n villes inconnues (1 req/s) ; None = illimité. `apply=False` = rapport seul.\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\").fetchall()\n flagged, villes_inconnues = [], 0\n for r in rows:\n allow = nominatim_budget is None or geo.ville_api_calls < nominatim_budget\n ref = geo.city_reference(r[\"city\"], allow_api=allow)\n if ref is None:\n villes_inconnues += 1\n continue\n d = _dist_km(r[\"lat\"], r[\"lng\"], ref[0], ref[1])\n if d > VILLE_RADIUS_KM:\n flagged.append((r, d))\n if apply:\n for r, d in flagged:\n con.execute(\"DELETE FROM geocode_cache WHERE address=?\",\n (norm_key(r[\"address\"]),))\n con.execute(\"\"\"UPDATE listings SET lat=NULL, lng=NULL,\n geocode_failed=0 WHERE uid=?\"\"\", (r[\"uid\"],))\n con.commit()\n for r, d in flagged[:20]:\n print(f\"[immo-ka] audit: {r['uid']} « {r['address']}, {r['city']} » \"\n f\"à {d:.0f} km de sa ville\")\n con.close()\n stats = {\"verifiees\": len(rows), \"incoherentes\": len(flagged),\n \"villes_inconnues\": villes_inconnues, \"corrigees\": apply}\n print(f\"[immo-ka] geocode-audit {stats}\")\n return stats\n","structuredPatch":[{"oldStart":425,"oldLines":8,"newStart":425,"newLines":26,"lines":[" AQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\""," \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")"," BATCH_SIZE = 200","+RESCUE_MAX = 150 # rattrapages resolve() max par passe (Nominatim = 1 req/s)"," "," ","+def strip_bad_source_coords(con, listings) -> int:","+ \"\"\"Garde d'ingestion : annule les lat/lng fournis par un connecteur quand","+ ils contredisent la ville annoncée (> VILLE_RADIUS_KM du centroïde connu).","+ Cache seulement (médianes + villes déjà résolues) : aucun appel réseau,","+ la synchronisation reste rapide. Retourne le nombre de paires annulées.\"\"\"","+ geo = Geocoder(con)","+ n = 0","+ for lst in listings:","+ if lst.lat is None or lst.lng is None or not (lst.city or \"\").strip():","+ continue","+ ref = geo.city_reference(lst.city, allow_api=False)","+ if ref and _dist_km(lst.lat, lst.lng, ref[0], ref[1]) > VILLE_RADIUS_KM:","+ lst.lat = lst.lng = None","+ n += 1","+ return n","+","+"," def run_batch(limit: int | None = None) -> dict:"," \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000"," adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"08d71535-6ae2-4e6b-9baf-ee0ed9badd04","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY5C9BSeNedoj96nEuY","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":811,"cache_read_input_tokens":100008,"cache_creation":{"ephemeral_5m_input_tokens":811,"ephemeral_1h_input_tokens":0},"output_tokens":5,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ef3a73b0-cc23-4cbc-865d-080199080223"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY5C9BSeNedoj96nEuY","type":"message","role":"assistant","content":[{"type":"text","text":"Maintenant la migration BD (`muni`), la garde dans `ingest.py`, l'audit dans `watch()` et la CLI."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":811,"cache_read_input_tokens":100008,"cache_creation":{"ephemeral_5m_input_tokens":811,"ephemeral_1h_input_tokens":0},"output_tokens":5,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"3e38c073-23d6-4580-9337-b73d0aa02d2a"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY5C9BSeNedoj96nEuY","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01WEcNbccRk76TGaLBZZhrB4","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","old_string":"CREATE TABLE IF NOT EXISTS geocode_cache (\n address TEXT PRIMARY KEY,\n lat REAL,\n lng REAL,\n provider TEXT,\n failed INTEGER DEFAULT 0,\n ts REAL\n);","new_string":"CREATE TABLE IF NOT EXISTS geocode_cache (\n address TEXT PRIMARY KEY,\n lat REAL,\n lng REAL,\n provider TEXT,\n failed INTEGER DEFAULT 0,\n ts REAL,\n muni TEXT -- municipalité officielle (clés « ville:… »)\n);"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":811,"cache_read_input_tokens":100008,"cache_creation":{"ephemeral_5m_input_tokens":811,"ephemeral_1h_input_tokens":0},"output_tokens":5,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"8664d4c7-ae99-4dac-acb5-bfb84887d83a"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01WEcNbccRk76TGaLBZZhrB4","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/db.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"da5c18c3-bea1-4922-ae7a-b83612504ed4","timestamp":"2026-08-25T13:21:41.773Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","oldString":"CREATE TABLE IF NOT EXISTS geocode_cache (\n address TEXT PRIMARY KEY,\n lat REAL,\n lng REAL,\n provider TEXT,\n failed INTEGER DEFAULT 0,\n ts REAL\n);","newString":"CREATE TABLE IF NOT EXISTS geocode_cache (\n address TEXT PRIMARY KEY,\n lat REAL,\n lng REAL,\n provider TEXT,\n failed INTEGER DEFAULT 0,\n ts REAL,\n muni TEXT -- municipalité officielle (clés « ville:… »)\n);","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# db.py : persistance SQLite — upsert avec détection de changements,\n# cycle de vie avec délai de grâce (2 syncs), détection de dérive,\n# historique de prix, cache des pages détail.\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport sqlite3\nimport statistics\nimport time\nfrom pathlib import Path\n\nfrom .schema import PropertyListing\n\nDB_PATH = Path(__file__).resolve().parent.parent / \"data\" / \"immoka.db\"\n\n# Nombre d'exécutions consécutives où une propriété doit être absente de la\n# source avant d'être désactivée (délai de grâce contre les ratés ponctuels).\nMISS_GRACE = 2\n\n# Dérive : si une source retourne <= DRIFT_RATIO × sa médiane historique\n# (médiane >= DRIFT_MIN_BASE annonces), on alerte et on suspend les retraits.\nDRIFT_RATIO = 0.25\nDRIFT_MIN_BASE = 8\nDRIFT_HISTORY = 5\n\n_SCHEMA = \"\"\"\nCREATE TABLE IF NOT EXISTS listings (\n uid TEXT PRIMARY KEY,\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n url TEXT,\n title TEXT,\n address TEXT,\n sector TEXT,\n city TEXT,\n region TEXT,\n property_type TEXT,\n price REAL,\n price_label TEXT,\n bedrooms INTEGER,\n bathrooms INTEGER,\n powder_rooms INTEGER,\n area_sqft REAL,\n lot_sqft REAL,\n year_built INTEGER,\n mls TEXT,\n status TEXT DEFAULT 'a-vendre',\n broker_name TEXT,\n broker_phone TEXT,\n agency TEXT,\n description TEXT,\n features TEXT, -- JSON (liste de textes source)\n details TEXT, -- JSON (champs structurés)\n images TEXT, -- JSON\n lat REAL,\n lng REAL,\n geocode_failed INTEGER DEFAULT 0,\n content_hash TEXT,\n first_seen REAL,\n last_seen REAL,\n updated_at REAL,\n miss_count INTEGER DEFAULT 0,\n active INTEGER DEFAULT 1,\n dup_hidden INTEGER DEFAULT 0 -- 1 = doublon de sous-agence masqué (dédup Centris)\n);\nCREATE INDEX IF NOT EXISTS idx_listings_source ON listings(source);\nCREATE INDEX IF NOT EXISTS idx_listings_city ON listings(city);\nCREATE INDEX IF NOT EXISTS idx_listings_type ON listings(property_type);\nCREATE INDEX IF NOT EXISTS idx_listings_active ON listings(active);\nCREATE INDEX IF NOT EXISTS idx_listings_extid ON listings(external_id);\n\nCREATE TABLE IF NOT EXISTS sync_log (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n source TEXT,\n ts REAL,\n found INTEGER,\n added INTEGER,\n updated INTEGER,\n removed INTEGER,\n ok INTEGER,\n message TEXT,\n stats TEXT -- JSON : taux de champs null, missed, alerte…\n);\n\nCREATE TABLE IF NOT EXISTS detail_cache (\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n key TEXT, -- hash du contenu « liste » de l'annonce\n payload TEXT, -- JSON opaque propre au connecteur\n fetched_at REAL,\n PRIMARY KEY (source, external_id)\n);\n\nCREATE TABLE IF NOT EXISTS price_log (\n uid TEXT NOT NULL,\n ts REAL NOT NULL,\n price REAL -- prix observé (baisses/hausses de prix demandé)\n);\nCREATE INDEX IF NOT EXISTS idx_price_log_uid ON price_log(uid);\n\nCREATE TABLE IF NOT EXISTS geocode_cache (\n address TEXT PRIMARY KEY,\n lat REAL,\n lng REAL,\n provider TEXT,\n failed INTEGER DEFAULT 0,\n ts REAL\n);\n\nCREATE TABLE IF NOT EXISTS poi_cache (\n coord_key TEXT PRIMARY KEY, -- \"lat,lng\" arrondi à 4 décimales (~11 m)\n lat REAL,\n lng REAL,\n pois TEXT, -- JSON : [{cat, name, dist_m}] (plus proche/catégorie)\n ts REAL\n);\n\"\"\"\n\n\n_SCHEMA_READY = False # le schéma/migration ne s'exécute qu'UNE fois par process\n\n\ndef _init_schema(con: sqlite3.Connection) -> None:\n \"\"\"Création de schéma + migration — coûteuse (write-lock). À faire une seule\n fois par process : l'exécuter à chaque connexion sérialisait les requêtes du\n web sur un verrou d'écriture (deadlock/starvation sous charge).\"\"\"\n con.executescript(_SCHEMA)\n cols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(listings)\")}\n if \"agency\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN agency TEXT\")\n if \"dup_hidden\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n if \"dauid\" not in cols: # aire de diffusion 2021 (stats de quartier)\n con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")\n if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n con.commit()\n\n\ndef refresh_dedup(con: sqlite3.Connection) -> int:\n \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n\n Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée\n si une fiche de plus haute priorité — même n° Centris (external_id), active —\n existe : le flux central/agence principale d'abord, sinon la sous-agence au\n plus petit uid. Les fiches non sous-agence ne sont jamais masquées par\n cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).\n Retourne le nombre total de fiches masquées.\"\"\"\n AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n con.execute(\"UPDATE listings SET dup_hidden=0\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")\n # 3) dédup INTER-SOURCES par adresse : la même propriété publiée sur deux\n # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle\n # conservatrice : même adresse normalisée (civique + rue + ville) + même\n # type + prix identique à ±1 % → on garde la fiche la plus autoritaire.\n try:\n n_addr = dedup_by_address(con)\n if n_addr:\n print(f\"[immo-ka] dédup adresse: {n_addr} doublon(s) inter-sources masqué(s)\")\n except Exception:\n import traceback\n traceback.print_exc()\n n = con.execute(\"SELECT COUNT(*) c FROM listings WHERE dup_hidden=1\").fetchone()[\"c\"]\n con.commit()\n return n\n\n\n# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main)\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\"}\n\n\ndef _source_rank(source: str) -> int:\n \"\"\"Autorité d'une source pour la dédup d'adresse :\n 0 = source primaire (bannière/agence/FSBO), 1 = sous-agence (_ag_),\n 2 = petites annonces (republication probable).\"\"\"\n if source in _PETITES_ANNONCES:\n return 2\n if \"_ag_\" in source:\n return 1\n return 0\n\n\ndef dedup_by_address(con: sqlite3.Connection) -> int:\n \"\"\"Passe de déduplication conservatrice par ADRESSE (inter-sources).\n\n Clé : n° civique(s) + mots significatifs de la rue + ville normalisée +\n type canonique + n° d'app/unité (vide s'il n'y en a pas — deux unités\n différentes d'un même immeuble ne partagent JAMAIS la même clé, et une\n adresse sans unité ne s'apparie pas à une adresse avec unité). Dans une\n clé, seules les fiches au prix identique à ±1 % sont considérées comme\n doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis le plus petit uid. Retourne le nb masqué.\"\"\"\n import re as _re\n from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE\n groups: dict[tuple, list] = {}\n for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):\n civs, words = _addr_parts(r[\"address\"])\n if not civs or not words:\n continue\n a = _norm(r[\"address\"]).split(\",\")[0]\n mapt = _re.search(_APP_RE, a)\n apt = \"\"\n if mapt:\n toks = _re.findall(r\"[a-z0-9]+\", mapt.group(0))\n # dernier token = le n° d'unité (le 1er est le mot-clé app/unité/#)\n apt = toks[-1] if toks else \"\"\n key = (\"-\".join(civs), \" \".join(sorted(set(words))),\n _muni_norm(r[\"city\"]), _norm(r[\"property_type\"]), apt)\n groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))\n hidden = 0\n for rows in groups.values():\n if len(rows) < 2:\n continue\n rows.sort() # par prix croissant\n cluster: list = []\n for row in rows:\n if cluster and row[0] > cluster[0][0] * 1.01:\n hidden += _mask_cluster(con, cluster)\n cluster = []\n cluster.append(row)\n hidden += _mask_cluster(con, cluster)\n return hidden\n\n\ndef _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:\n \"\"\"Masque les doublons d'un groupe (même clé d'adresse, prix ±1 %), puis\n FUSIONNE en « golden record » : les champs vides de la fiche conservée sont\n complétés depuis les doublons masqués (description plus longue, galerie plus\n riche, superficies, année, GPS, téléphone) — le meilleur des deux sources.\"\"\"\n if len(cluster) < 2:\n return 0\n sources = [c[3] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[2] != keep[2]:\n con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n donors.append(c[2])\n n += 1\n try:\n _merge_golden(con, keep[2], donors)\n except Exception:\n pass # la fusion est un bonus — ne jamais casser la dédup\n return n\n\n\n_MERGE_NUM_FIELDS = (\"bedrooms\", \"bathrooms\", \"powder_rooms\", \"area_sqft\",\n \"lot_sqft\", \"year_built\")\n\n\ndef _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:\n \"\"\"Complète les champs vides de `keep_uid` depuis ses doublons masqués.\"\"\"\n if not donor_uids:\n return\n cols = (\"uid, description, images, bedrooms, bathrooms, powder_rooms,\"\n \" area_sqft, lot_sqft, year_built, lat, lng, broker_phone\")\n keep = con.execute(f\"SELECT {cols} FROM listings WHERE uid=?\",\n (keep_uid,)).fetchone()\n if keep is None:\n return\n sets, args = [], []\n kimgs = len(json.loads(keep[\"images\"] or \"[]\"))\n kdesc = len(keep[\"description\"] or \"\")\n best_imgs, best_desc = None, None\n donor_rows = con.execute(\n f\"SELECT {cols} FROM listings WHERE uid IN \"\n f\"({','.join('?' * len(donor_uids))})\", donor_uids).fetchall()\n merged_num: dict = {}\n for d in donor_rows:\n di = json.loads(d[\"images\"] or \"[]\")\n if len(di) > max(kimgs, len(json.loads(best_imgs or \"[]\"))):\n best_imgs = d[\"images\"]\n dd = d[\"description\"] or \"\"\n if len(dd) > max(kdesc, 80, len(best_desc or \"\")):\n best_desc = dd\n for f in _MERGE_NUM_FIELDS:\n if keep[f] is None and merged_num.get(f) is None and d[f] is not None:\n merged_num[f] = d[f]\n # GPS : toujours la PAIRE du même donneur (jamais lat et lng mélangés)\n if (keep[\"lat\"] is None and \"lat\" not in merged_num\n and d[\"lat\"] is not None and d[\"lng\"] is not None):\n merged_num[\"lat\"], merged_num[\"lng\"] = d[\"lat\"], d[\"lng\"]\n if not keep[\"broker_phone\"] and d[\"broker_phone\"] and \"broker_phone\" not in merged_num:\n merged_num[\"broker_phone\"] = d[\"broker_phone\"]\n if best_imgs is not None:\n sets.append(\"images=?\"); args.append(best_imgs)\n if best_desc is not None and kdesc < 80:\n sets.append(\"description=?\"); args.append(best_desc)\n for f, v in merged_num.items():\n sets.append(f\"{f}=?\"); args.append(v)\n if sets:\n args.append(keep_uid)\n con.execute(f\"UPDATE listings SET {', '.join(sets)} WHERE uid=?\", args)\n\n\ndef connect() -> sqlite3.Connection:\n global _SCHEMA_READY\n DB_PATH.parent.mkdir(parents=True, exist_ok=True)\n con = sqlite3.connect(DB_PATH, timeout=60)\n con.row_factory = sqlite3.Row\n # WAL + busy_timeout : accès concurrents (watcher + web) sans « db is locked ».\n con.execute(\"PRAGMA journal_mode=WAL\")\n # 120 s : couvre les longues transactions (refresh_dedup ~70 s) sans que les\n # autres écrivains (géocodage, vraiprix) ne lèvent « database is locked ».\n con.execute(\"PRAGMA busy_timeout=120000\")\n con.execute(\"PRAGMA synchronous=NORMAL\")\n if not _SCHEMA_READY:\n _init_schema(con)\n _SCHEMA_READY = True\n return con\n\n\n# ---------------------------------------------------------------------------\n# Synchronisation d'une source\n# ---------------------------------------------------------------------------\n\ndef _drift_alert(con: sqlite3.Connection, source: str, found: int,\n null_price_rate: float) -> str | None:\n \"\"\"Détecte une dérive du connecteur (chute du volume ou des prix extraits).\"\"\"\n hist = con.execute(\n \"SELECT found, stats FROM sync_log WHERE source=? AND ok=1\"\n \" ORDER BY ts DESC LIMIT ?\", (source, DRIFT_HISTORY)).fetchall()\n if len(hist) < 3:\n return None\n med_found = statistics.median(r[\"found\"] for r in hist)\n if med_found >= DRIFT_MIN_BASE and found <= DRIFT_RATIO * med_found:\n return (f\"dérive: {found} propriété(s) trouvée(s) contre une médiane de \"\n f\"{med_found:.0f} — retraits suspendus, vérifier le connecteur\")\n if found >= DRIFT_MIN_BASE and null_price_rate >= 0.8:\n rates = []\n for r in hist:\n try:\n rates.append(json.loads(r[\"stats\"] or \"{}\")[\"null_price_rate\"])\n except (KeyError, ValueError, TypeError):\n continue\n if rates and statistics.median(rates) <= 0.3:\n return (f\"dérive: {null_price_rate:.0%} des propriétés sans prix \"\n f\"(habituellement {statistics.median(rates):.0%}) — \"\n \"le format de la source a probablement changé\")\n return None\n\n\ndef sync_source(con: sqlite3.Connection, source: str,\n listings: list[PropertyListing]) -> dict:\n \"\"\"Synchronise les propriétés d'une source.\n\n - nouvelle propriété -> insertion\n - propriété modifiée -> mise à jour (comparaison de content_hash)\n - propriété disparue -> miss_count += 1, puis active=0 après MISS_GRACE\n exécutions consécutives (vendue ou retirée)\n - dérive détectée -> alerte consignée, retraits suspendus\n \"\"\"\n now = time.time()\n added = updated = 0\n seen_uids = set()\n\n n = len(listings)\n null_price = sum(1 for l in listings if l.price is None)\n null_addr = sum(1 for l in listings if not l.address)\n null_price_rate = round(null_price / n, 3) if n else 0.0\n\n alert = _drift_alert(con, source, n, null_price_rate)\n\n for lst in listings:\n seen_uids.add(lst.uid)\n h = lst.content_hash()\n row = con.execute(\"SELECT content_hash, price FROM listings WHERE uid=?\",\n (lst.uid,)).fetchone()\n params = dict(\n uid=lst.uid, source=lst.source, external_id=lst.external_id,\n url=lst.url, title=lst.title, address=lst.address,\n sector=lst.sector, city=lst.city, region=lst.region,\n property_type=lst.property_type, price=lst.price,\n price_label=lst.price_label, bedrooms=lst.bedrooms,\n bathrooms=lst.bathrooms, powder_rooms=lst.powder_rooms,\n area_sqft=lst.area_sqft, lot_sqft=lst.lot_sqft,\n year_built=lst.year_built, mls=lst.mls, status=lst.status,\n broker_name=lst.broker_name, broker_phone=lst.broker_phone,\n agency=lst.agency,\n description=lst.description,\n features=json.dumps(lst.features, ensure_ascii=False),\n details=json.dumps(lst.details, ensure_ascii=False),\n images=json.dumps(lst.images, ensure_ascii=False),\n lat=lst.lat, lng=lst.lng, content_hash=h, now=now,\n )\n if row is None:\n con.execute(\n \"\"\"INSERT INTO listings (uid, source, external_id, url, title,\n address, sector, city, region, property_type, price,\n price_label, bedrooms, bathrooms, powder_rooms, area_sqft,\n lot_sqft, year_built, mls, status, broker_name, broker_phone,\n agency, description, features, details, images, lat, lng,\n content_hash, first_seen, last_seen, updated_at,\n miss_count, active)\n VALUES (:uid,:source,:external_id,:url,:title,:address,\n :sector,:city,:region,:property_type,:price,:price_label,\n :bedrooms,:bathrooms,:powder_rooms,:area_sqft,:lot_sqft,\n :year_built,:mls,:status,:broker_name,:broker_phone,\n :agency,:description,:features,:details,:images,:lat,:lng,\n :content_hash,:now,:now,:now,0,1)\"\"\", params)\n if lst.price is not None:\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n added += 1\n elif row[\"content_hash\"] != h:\n # COALESCE : ne jamais écraser par null des coordonnées géocodées ni\n # les année/superficies remplies par enrichissement (rôle d'évaluation,\n # fiche détail) quand la source liste ne les fournit pas\n con.execute(\n \"\"\"UPDATE listings SET url=:url, title=:title,\n address=:address, sector=:sector, city=:city, region=:region,\n property_type=:property_type, price=:price,\n price_label=:price_label, bedrooms=:bedrooms,\n bathrooms=:bathrooms, powder_rooms=:powder_rooms,\n area_sqft=COALESCE(:area_sqft, area_sqft),\n lot_sqft=COALESCE(:lot_sqft, lot_sqft),\n year_built=COALESCE(:year_built, year_built),\n mls=:mls, status=:status,\n broker_name=:broker_name, broker_phone=:broker_phone,\n agency=:agency, description=:description, features=:features,\n details=:details, images=:images,\n lat=COALESCE(:lat, lat), lng=COALESCE(:lng, lng),\n content_hash=:content_hash, last_seen=:now,\n updated_at=:now, miss_count=0, active=1\n WHERE uid=:uid\"\"\", params)\n if lst.price != row[\"price\"]: # baisse/hausse de prix -> historique\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n updated += 1\n else:\n con.execute(\n \"UPDATE listings SET last_seen=?, miss_count=0, active=1 WHERE uid=?\",\n (now, lst.uid))\n\n # Propriétés de cette source qui n'apparaissent plus : délai de grâce,\n # puis désactivation (vendue/retirée). Suspendu si dérive détectée.\n removed = missed = 0\n if not alert:\n for r in con.execute(\n \"SELECT uid, miss_count FROM listings WHERE source=? AND active=1\",\n (source,)).fetchall():\n if r[\"uid\"] in seen_uids:\n continue\n missed += 1\n if r[\"miss_count\"] + 1 >= MISS_GRACE:\n con.execute(\n \"UPDATE listings SET active=0, miss_count=?, updated_at=?\"\n \" WHERE uid=?\", (r[\"miss_count\"] + 1, now, r[\"uid\"]))\n removed += 1\n else:\n con.execute(\"UPDATE listings SET miss_count=miss_count+1 WHERE uid=?\",\n (r[\"uid\"],))\n\n stats = {\n \"null_price_rate\": null_price_rate,\n \"null_address_rate\": round(null_addr / n, 3) if n else 0.0,\n \"missed\": missed,\n }\n if alert:\n stats[\"alert\"] = alert\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok,\"\n \" message, stats) VALUES (?,?,?,?,?,?,1,?,?)\",\n (source, now, n, added, updated, removed, alert or \"ok\",\n json.dumps(stats, ensure_ascii=False)))\n con.commit()\n out = {\"source\": source, \"found\": n, \"added\": added,\n \"updated\": updated, \"removed\": removed}\n if alert:\n out[\"alert\"] = alert\n return out\n\n\ndef log_failure(con: sqlite3.Connection, source: str, message: str) -> None:\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok, message)\"\n \" VALUES (?,?,0,0,0,0,0,?)\", (source, time.time(), message))\n con.commit()\n\n\n# ---------------------------------------------------------------------------\n# Cache des pages détail (« détail si nouveau/modifié »)\n# ---------------------------------------------------------------------------\n\ndef get_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str) -> dict | None:\n \"\"\"Payload détail mis en cache si la clé (hash liste) n'a pas changé.\"\"\"\n row = con.execute(\n \"SELECT key, payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"key\"] == key and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef get_stale_detail(con: sqlite3.Connection, source: str,\n external_id: str) -> dict | None:\n \"\"\"Payload détail SANS vérifier la clé — repli « périmé plutôt que rien »\n quand le budget de re-fetch d'un cycle est épuisé (ex. bump de version de\n clé) : la fiche garde photos/détails existants en attendant son re-parse.\"\"\"\n row = con.execute(\n \"SELECT payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef put_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str, payload: dict) -> None:\n con.execute(\n \"INSERT INTO detail_cache (source, external_id, key, payload, fetched_at)\"\n \" VALUES (?,?,?,?,?)\"\n \" ON CONFLICT(source, external_id) DO UPDATE SET\"\n \" key=excluded.key, payload=excluded.payload, fetched_at=excluded.fetched_at\",\n (source, external_id, key, json.dumps(payload, ensure_ascii=False),\n time.time()))\n con.commit()\n","structuredPatch":[{"oldStart":108,"oldLines":7,"newStart":108,"newLines":8,"lines":[" lng REAL,"," provider TEXT,"," failed INTEGER DEFAULT 0,","- ts REAL","+ ts REAL,","+ muni TEXT -- municipalité officielle (clés « ville:… »)"," );"," "," CREATE TABLE IF NOT EXISTS poi_cache ("]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY5C9BSeNedoj96nEuY","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01W4FihQaqKBK6eZCpFeT4Xj","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","old_string":" if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")","new_string":" if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n gcols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(geocode_cache)\")}\n if \"muni\" not in gcols: # municipalité officielle (entrées « ville:… »)\n con.execute(\"ALTER TABLE geocode_cache ADD COLUMN muni TEXT\")"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":811,"cache_read_input_tokens":100008,"cache_creation":{"ephemeral_5m_input_tokens":811,"ephemeral_1h_input_tokens":0},"output_tokens":5,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"14b1b7ee-51c5-4b56-ac58-c924df21b7de"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01W4FihQaqKBK6eZCpFeT4Xj","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/db.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ed1c886c-26c2-4907-953f-ae449121e119","timestamp":"2026-08-25T13:21:44.631Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","oldString":" if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")","newString":" if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n gcols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(geocode_cache)\")}\n if \"muni\" not in gcols: # municipalité officielle (entrées « ville:… »)\n con.execute(\"ALTER TABLE geocode_cache ADD COLUMN muni TEXT\")","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# db.py : persistance SQLite — upsert avec détection de changements,\n# cycle de vie avec délai de grâce (2 syncs), détection de dérive,\n# historique de prix, cache des pages détail.\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport sqlite3\nimport statistics\nimport time\nfrom pathlib import Path\n\nfrom .schema import PropertyListing\n\nDB_PATH = Path(__file__).resolve().parent.parent / \"data\" / \"immoka.db\"\n\n# Nombre d'exécutions consécutives où une propriété doit être absente de la\n# source avant d'être désactivée (délai de grâce contre les ratés ponctuels).\nMISS_GRACE = 2\n\n# Dérive : si une source retourne <= DRIFT_RATIO × sa médiane historique\n# (médiane >= DRIFT_MIN_BASE annonces), on alerte et on suspend les retraits.\nDRIFT_RATIO = 0.25\nDRIFT_MIN_BASE = 8\nDRIFT_HISTORY = 5\n\n_SCHEMA = \"\"\"\nCREATE TABLE IF NOT EXISTS listings (\n uid TEXT PRIMARY KEY,\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n url TEXT,\n title TEXT,\n address TEXT,\n sector TEXT,\n city TEXT,\n region TEXT,\n property_type TEXT,\n price REAL,\n price_label TEXT,\n bedrooms INTEGER,\n bathrooms INTEGER,\n powder_rooms INTEGER,\n area_sqft REAL,\n lot_sqft REAL,\n year_built INTEGER,\n mls TEXT,\n status TEXT DEFAULT 'a-vendre',\n broker_name TEXT,\n broker_phone TEXT,\n agency TEXT,\n description TEXT,\n features TEXT, -- JSON (liste de textes source)\n details TEXT, -- JSON (champs structurés)\n images TEXT, -- JSON\n lat REAL,\n lng REAL,\n geocode_failed INTEGER DEFAULT 0,\n content_hash TEXT,\n first_seen REAL,\n last_seen REAL,\n updated_at REAL,\n miss_count INTEGER DEFAULT 0,\n active INTEGER DEFAULT 1,\n dup_hidden INTEGER DEFAULT 0 -- 1 = doublon de sous-agence masqué (dédup Centris)\n);\nCREATE INDEX IF NOT EXISTS idx_listings_source ON listings(source);\nCREATE INDEX IF NOT EXISTS idx_listings_city ON listings(city);\nCREATE INDEX IF NOT EXISTS idx_listings_type ON listings(property_type);\nCREATE INDEX IF NOT EXISTS idx_listings_active ON listings(active);\nCREATE INDEX IF NOT EXISTS idx_listings_extid ON listings(external_id);\n\nCREATE TABLE IF NOT EXISTS sync_log (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n source TEXT,\n ts REAL,\n found INTEGER,\n added INTEGER,\n updated INTEGER,\n removed INTEGER,\n ok INTEGER,\n message TEXT,\n stats TEXT -- JSON : taux de champs null, missed, alerte…\n);\n\nCREATE TABLE IF NOT EXISTS detail_cache (\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n key TEXT, -- hash du contenu « liste » de l'annonce\n payload TEXT, -- JSON opaque propre au connecteur\n fetched_at REAL,\n PRIMARY KEY (source, external_id)\n);\n\nCREATE TABLE IF NOT EXISTS price_log (\n uid TEXT NOT NULL,\n ts REAL NOT NULL,\n price REAL -- prix observé (baisses/hausses de prix demandé)\n);\nCREATE INDEX IF NOT EXISTS idx_price_log_uid ON price_log(uid);\n\nCREATE TABLE IF NOT EXISTS geocode_cache (\n address TEXT PRIMARY KEY,\n lat REAL,\n lng REAL,\n provider TEXT,\n failed INTEGER DEFAULT 0,\n ts REAL,\n muni TEXT -- municipalité officielle (clés « ville:… »)\n);\n\nCREATE TABLE IF NOT EXISTS poi_cache (\n coord_key TEXT PRIMARY KEY, -- \"lat,lng\" arrondi à 4 décimales (~11 m)\n lat REAL,\n lng REAL,\n pois TEXT, -- JSON : [{cat, name, dist_m}] (plus proche/catégorie)\n ts REAL\n);\n\"\"\"\n\n\n_SCHEMA_READY = False # le schéma/migration ne s'exécute qu'UNE fois par process\n\n\ndef _init_schema(con: sqlite3.Connection) -> None:\n \"\"\"Création de schéma + migration — coûteuse (write-lock). À faire une seule\n fois par process : l'exécuter à chaque connexion sérialisait les requêtes du\n web sur un verrou d'écriture (deadlock/starvation sous charge).\"\"\"\n con.executescript(_SCHEMA)\n cols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(listings)\")}\n if \"agency\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN agency TEXT\")\n if \"dup_hidden\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n if \"dauid\" not in cols: # aire de diffusion 2021 (stats de quartier)\n con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")\n if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n con.commit()\n\n\ndef refresh_dedup(con: sqlite3.Connection) -> int:\n \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n\n Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée\n si une fiche de plus haute priorité — même n° Centris (external_id), active —\n existe : le flux central/agence principale d'abord, sinon la sous-agence au\n plus petit uid. Les fiches non sous-agence ne sont jamais masquées par\n cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).\n Retourne le nombre total de fiches masquées.\"\"\"\n AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n con.execute(\"UPDATE listings SET dup_hidden=0\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")\n # 3) dédup INTER-SOURCES par adresse : la même propriété publiée sur deux\n # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle\n # conservatrice : même adresse normalisée (civique + rue + ville) + même\n # type + prix identique à ±1 % → on garde la fiche la plus autoritaire.\n try:\n n_addr = dedup_by_address(con)\n if n_addr:\n print(f\"[immo-ka] dédup adresse: {n_addr} doublon(s) inter-sources masqué(s)\")\n except Exception:\n import traceback\n traceback.print_exc()\n n = con.execute(\"SELECT COUNT(*) c FROM listings WHERE dup_hidden=1\").fetchone()[\"c\"]\n con.commit()\n return n\n\n\n# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main)\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\"}\n\n\ndef _source_rank(source: str) -> int:\n \"\"\"Autorité d'une source pour la dédup d'adresse :\n 0 = source primaire (bannière/agence/FSBO), 1 = sous-agence (_ag_),\n 2 = petites annonces (republication probable).\"\"\"\n if source in _PETITES_ANNONCES:\n return 2\n if \"_ag_\" in source:\n return 1\n return 0\n\n\ndef dedup_by_address(con: sqlite3.Connection) -> int:\n \"\"\"Passe de déduplication conservatrice par ADRESSE (inter-sources).\n\n Clé : n° civique(s) + mots significatifs de la rue + ville normalisée +\n type canonique + n° d'app/unité (vide s'il n'y en a pas — deux unités\n différentes d'un même immeuble ne partagent JAMAIS la même clé, et une\n adresse sans unité ne s'apparie pas à une adresse avec unité). Dans une\n clé, seules les fiches au prix identique à ±1 % sont considérées comme\n doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis le plus petit uid. Retourne le nb masqué.\"\"\"\n import re as _re\n from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE\n groups: dict[tuple, list] = {}\n for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):\n civs, words = _addr_parts(r[\"address\"])\n if not civs or not words:\n continue\n a = _norm(r[\"address\"]).split(\",\")[0]\n mapt = _re.search(_APP_RE, a)\n apt = \"\"\n if mapt:\n toks = _re.findall(r\"[a-z0-9]+\", mapt.group(0))\n # dernier token = le n° d'unité (le 1er est le mot-clé app/unité/#)\n apt = toks[-1] if toks else \"\"\n key = (\"-\".join(civs), \" \".join(sorted(set(words))),\n _muni_norm(r[\"city\"]), _norm(r[\"property_type\"]), apt)\n groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))\n hidden = 0\n for rows in groups.values():\n if len(rows) < 2:\n continue\n rows.sort() # par prix croissant\n cluster: list = []\n for row in rows:\n if cluster and row[0] > cluster[0][0] * 1.01:\n hidden += _mask_cluster(con, cluster)\n cluster = []\n cluster.append(row)\n hidden += _mask_cluster(con, cluster)\n return hidden\n\n\ndef _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:\n \"\"\"Masque les doublons d'un groupe (même clé d'adresse, prix ±1 %), puis\n FUSIONNE en « golden record » : les champs vides de la fiche conservée sont\n complétés depuis les doublons masqués (description plus longue, galerie plus\n riche, superficies, année, GPS, téléphone) — le meilleur des deux sources.\"\"\"\n if len(cluster) < 2:\n return 0\n sources = [c[3] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[2] != keep[2]:\n con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n donors.append(c[2])\n n += 1\n try:\n _merge_golden(con, keep[2], donors)\n except Exception:\n pass # la fusion est un bonus — ne jamais casser la dédup\n return n\n\n\n_MERGE_NUM_FIELDS = (\"bedrooms\", \"bathrooms\", \"powder_rooms\", \"area_sqft\",\n \"lot_sqft\", \"year_built\")\n\n\ndef _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:\n \"\"\"Complète les champs vides de `keep_uid` depuis ses doublons masqués.\"\"\"\n if not donor_uids:\n return\n cols = (\"uid, description, images, bedrooms, bathrooms, powder_rooms,\"\n \" area_sqft, lot_sqft, year_built, lat, lng, broker_phone\")\n keep = con.execute(f\"SELECT {cols} FROM listings WHERE uid=?\",\n (keep_uid,)).fetchone()\n if keep is None:\n return\n sets, args = [], []\n kimgs = len(json.loads(keep[\"images\"] or \"[]\"))\n kdesc = len(keep[\"description\"] or \"\")\n best_imgs, best_desc = None, None\n donor_rows = con.execute(\n f\"SELECT {cols} FROM listings WHERE uid IN \"\n f\"({','.join('?' * len(donor_uids))})\", donor_uids).fetchall()\n merged_num: dict = {}\n for d in donor_rows:\n di = json.loads(d[\"images\"] or \"[]\")\n if len(di) > max(kimgs, len(json.loads(best_imgs or \"[]\"))):\n best_imgs = d[\"images\"]\n dd = d[\"description\"] or \"\"\n if len(dd) > max(kdesc, 80, len(best_desc or \"\")):\n best_desc = dd\n for f in _MERGE_NUM_FIELDS:\n if keep[f] is None and merged_num.get(f) is None and d[f] is not None:\n merged_num[f] = d[f]\n # GPS : toujours la PAIRE du même donneur (jamais lat et lng mélangés)\n if (keep[\"lat\"] is None and \"lat\" not in merged_num\n and d[\"lat\"] is not None and d[\"lng\"] is not None):\n merged_num[\"lat\"], merged_num[\"lng\"] = d[\"lat\"], d[\"lng\"]\n if not keep[\"broker_phone\"] and d[\"broker_phone\"] and \"broker_phone\" not in merged_num:\n merged_num[\"broker_phone\"] = d[\"broker_phone\"]\n if best_imgs is not None:\n sets.append(\"images=?\"); args.append(best_imgs)\n if best_desc is not None and kdesc < 80:\n sets.append(\"description=?\"); args.append(best_desc)\n for f, v in merged_num.items():\n sets.append(f\"{f}=?\"); args.append(v)\n if sets:\n args.append(keep_uid)\n con.execute(f\"UPDATE listings SET {', '.join(sets)} WHERE uid=?\", args)\n\n\ndef connect() -> sqlite3.Connection:\n global _SCHEMA_READY\n DB_PATH.parent.mkdir(parents=True, exist_ok=True)\n con = sqlite3.connect(DB_PATH, timeout=60)\n con.row_factory = sqlite3.Row\n # WAL + busy_timeout : accès concurrents (watcher + web) sans « db is locked ».\n con.execute(\"PRAGMA journal_mode=WAL\")\n # 120 s : couvre les longues transactions (refresh_dedup ~70 s) sans que les\n # autres écrivains (géocodage, vraiprix) ne lèvent « database is locked ».\n con.execute(\"PRAGMA busy_timeout=120000\")\n con.execute(\"PRAGMA synchronous=NORMAL\")\n if not _SCHEMA_READY:\n _init_schema(con)\n _SCHEMA_READY = True\n return con\n\n\n# ---------------------------------------------------------------------------\n# Synchronisation d'une source\n# ---------------------------------------------------------------------------\n\ndef _drift_alert(con: sqlite3.Connection, source: str, found: int,\n null_price_rate: float) -> str | None:\n \"\"\"Détecte une dérive du connecteur (chute du volume ou des prix extraits).\"\"\"\n hist = con.execute(\n \"SELECT found, stats FROM sync_log WHERE source=? AND ok=1\"\n \" ORDER BY ts DESC LIMIT ?\", (source, DRIFT_HISTORY)).fetchall()\n if len(hist) < 3:\n return None\n med_found = statistics.median(r[\"found\"] for r in hist)\n if med_found >= DRIFT_MIN_BASE and found <= DRIFT_RATIO * med_found:\n return (f\"dérive: {found} propriété(s) trouvée(s) contre une médiane de \"\n f\"{med_found:.0f} — retraits suspendus, vérifier le connecteur\")\n if found >= DRIFT_MIN_BASE and null_price_rate >= 0.8:\n rates = []\n for r in hist:\n try:\n rates.append(json.loads(r[\"stats\"] or \"{}\")[\"null_price_rate\"])\n except (KeyError, ValueError, TypeError):\n continue\n if rates and statistics.median(rates) <= 0.3:\n return (f\"dérive: {null_price_rate:.0%} des propriétés sans prix \"\n f\"(habituellement {statistics.median(rates):.0%}) — \"\n \"le format de la source a probablement changé\")\n return None\n\n\ndef sync_source(con: sqlite3.Connection, source: str,\n listings: list[PropertyListing]) -> dict:\n \"\"\"Synchronise les propriétés d'une source.\n\n - nouvelle propriété -> insertion\n - propriété modifiée -> mise à jour (comparaison de content_hash)\n - propriété disparue -> miss_count += 1, puis active=0 après MISS_GRACE\n exécutions consécutives (vendue ou retirée)\n - dérive détectée -> alerte consignée, retraits suspendus\n \"\"\"\n now = time.time()\n added = updated = 0\n seen_uids = set()\n\n n = len(listings)\n null_price = sum(1 for l in listings if l.price is None)\n null_addr = sum(1 for l in listings if not l.address)\n null_price_rate = round(null_price / n, 3) if n else 0.0\n\n alert = _drift_alert(con, source, n, null_price_rate)\n\n for lst in listings:\n seen_uids.add(lst.uid)\n h = lst.content_hash()\n row = con.execute(\"SELECT content_hash, price FROM listings WHERE uid=?\",\n (lst.uid,)).fetchone()\n params = dict(\n uid=lst.uid, source=lst.source, external_id=lst.external_id,\n url=lst.url, title=lst.title, address=lst.address,\n sector=lst.sector, city=lst.city, region=lst.region,\n property_type=lst.property_type, price=lst.price,\n price_label=lst.price_label, bedrooms=lst.bedrooms,\n bathrooms=lst.bathrooms, powder_rooms=lst.powder_rooms,\n area_sqft=lst.area_sqft, lot_sqft=lst.lot_sqft,\n year_built=lst.year_built, mls=lst.mls, status=lst.status,\n broker_name=lst.broker_name, broker_phone=lst.broker_phone,\n agency=lst.agency,\n description=lst.description,\n features=json.dumps(lst.features, ensure_ascii=False),\n details=json.dumps(lst.details, ensure_ascii=False),\n images=json.dumps(lst.images, ensure_ascii=False),\n lat=lst.lat, lng=lst.lng, content_hash=h, now=now,\n )\n if row is None:\n con.execute(\n \"\"\"INSERT INTO listings (uid, source, external_id, url, title,\n address, sector, city, region, property_type, price,\n price_label, bedrooms, bathrooms, powder_rooms, area_sqft,\n lot_sqft, year_built, mls, status, broker_name, broker_phone,\n agency, description, features, details, images, lat, lng,\n content_hash, first_seen, last_seen, updated_at,\n miss_count, active)\n VALUES (:uid,:source,:external_id,:url,:title,:address,\n :sector,:city,:region,:property_type,:price,:price_label,\n :bedrooms,:bathrooms,:powder_rooms,:area_sqft,:lot_sqft,\n :year_built,:mls,:status,:broker_name,:broker_phone,\n :agency,:description,:features,:details,:images,:lat,:lng,\n :content_hash,:now,:now,:now,0,1)\"\"\", params)\n if lst.price is not None:\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n added += 1\n elif row[\"content_hash\"] != h:\n # COALESCE : ne jamais écraser par null des coordonnées géocodées ni\n # les année/superficies remplies par enrichissement (rôle d'évaluation,\n # fiche détail) quand la source liste ne les fournit pas\n con.execute(\n \"\"\"UPDATE listings SET url=:url, title=:title,\n address=:address, sector=:sector, city=:city, region=:region,\n property_type=:property_type, price=:price,\n price_label=:price_label, bedrooms=:bedrooms,\n bathrooms=:bathrooms, powder_rooms=:powder_rooms,\n area_sqft=COALESCE(:area_sqft, area_sqft),\n lot_sqft=COALESCE(:lot_sqft, lot_sqft),\n year_built=COALESCE(:year_built, year_built),\n mls=:mls, status=:status,\n broker_name=:broker_name, broker_phone=:broker_phone,\n agency=:agency, description=:description, features=:features,\n details=:details, images=:images,\n lat=COALESCE(:lat, lat), lng=COALESCE(:lng, lng),\n content_hash=:content_hash, last_seen=:now,\n updated_at=:now, miss_count=0, active=1\n WHERE uid=:uid\"\"\", params)\n if lst.price != row[\"price\"]: # baisse/hausse de prix -> historique\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n updated += 1\n else:\n con.execute(\n \"UPDATE listings SET last_seen=?, miss_count=0, active=1 WHERE uid=?\",\n (now, lst.uid))\n\n # Propriétés de cette source qui n'apparaissent plus : délai de grâce,\n # puis désactivation (vendue/retirée). Suspendu si dérive détectée.\n removed = missed = 0\n if not alert:\n for r in con.execute(\n \"SELECT uid, miss_count FROM listings WHERE source=? AND active=1\",\n (source,)).fetchall():\n if r[\"uid\"] in seen_uids:\n continue\n missed += 1\n if r[\"miss_count\"] + 1 >= MISS_GRACE:\n con.execute(\n \"UPDATE listings SET active=0, miss_count=?, updated_at=?\"\n \" WHERE uid=?\", (r[\"miss_count\"] + 1, now, r[\"uid\"]))\n removed += 1\n else:\n con.execute(\"UPDATE listings SET miss_count=miss_count+1 WHERE uid=?\",\n (r[\"uid\"],))\n\n stats = {\n \"null_price_rate\": null_price_rate,\n \"null_address_rate\": round(null_addr / n, 3) if n else 0.0,\n \"missed\": missed,\n }\n if alert:\n stats[\"alert\"] = alert\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok,\"\n \" message, stats) VALUES (?,?,?,?,?,?,1,?,?)\",\n (source, now, n, added, updated, removed, alert or \"ok\",\n json.dumps(stats, ensure_ascii=False)))\n con.commit()\n out = {\"source\": source, \"found\": n, \"added\": added,\n \"updated\": updated, \"removed\": removed}\n if alert:\n out[\"alert\"] = alert\n return out\n\n\ndef log_failure(con: sqlite3.Connection, source: str, message: str) -> None:\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok, message)\"\n \" VALUES (?,?,0,0,0,0,0,?)\", (source, time.time(), message))\n con.commit()\n\n\n# ---------------------------------------------------------------------------\n# Cache des pages détail (« détail si nouveau/modifié »)\n# ---------------------------------------------------------------------------\n\ndef get_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str) -> dict | None:\n \"\"\"Payload détail mis en cache si la clé (hash liste) n'a pas changé.\"\"\"\n row = con.execute(\n \"SELECT key, payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"key\"] == key and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef get_stale_detail(con: sqlite3.Connection, source: str,\n external_id: str) -> dict | None:\n \"\"\"Payload détail SANS vérifier la clé — repli « périmé plutôt que rien »\n quand le budget de re-fetch d'un cycle est épuisé (ex. bump de version de\n clé) : la fiche garde photos/détails existants en attendant son re-parse.\"\"\"\n row = con.execute(\n \"SELECT payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef put_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str, payload: dict) -> None:\n con.execute(\n \"INSERT INTO detail_cache (source, external_id, key, payload, fetched_at)\"\n \" VALUES (?,?,?,?,?)\"\n \" ON CONFLICT(source, external_id) DO UPDATE SET\"\n \" key=excluded.key, payload=excluded.payload, fetched_at=excluded.fetched_at\",\n (source, external_id, key, json.dumps(payload, ensure_ascii=False),\n time.time()))\n con.commit()\n","structuredPatch":[{"oldStart":139,"oldLines":6,"newStart":139,"newLines":9,"lines":[" con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")"," if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse"," con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")","+ gcols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(geocode_cache)\")}","+ if \"muni\" not in gcols: # municipalité officielle (entrées « ville:… »)","+ con.execute(\"ALTER TABLE geocode_cache ADD COLUMN muni TEXT\")"," con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")"," con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")"," con.commit()"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY5C9BSeNedoj96nEuY","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_017SowBbjedrKT8Tc2FD4u9Y","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/ingest.py","old_string":" listings = cls().fetch()\n finalized, dropped = [], 0\n for lst in listings:\n try:\n finalized.append(lst.finalize())\n except Exception: # une annonce malformée ne bloque pas la source\n dropped += 1\n stats = db.sync_source(con, sid, finalized)","new_string":" listings = cls().fetch()\n finalized, dropped = [], 0\n for lst in listings:\n try:\n finalized.append(lst.finalize())\n except Exception: # une annonce malformée ne bloque pas la source\n dropped += 1\n try:\n # garde géographique : coordonnées fournies par la source mais\n # incompatibles avec la ville annoncée -> annulées (le géocodeur\n # rigoureux prendra le relais). Cache seulement, aucun réseau.\n from . import geocode\n bad = geocode.strip_bad_source_coords(con, finalized)\n if bad:\n print(f\"[immo-ka] {bad} coordonnée(s) source incohérente(s) rejetée(s)\")\n except Exception:\n traceback.print_exc()\n stats = db.sync_source(con, sid, finalized)"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":811,"cache_read_input_tokens":100008,"cache_creation":{"ephemeral_5m_input_tokens":811,"ephemeral_1h_input_tokens":0},"output_tokens":5,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"716b3b2d-b4b6-43cf-bcb8-a5f32e1b5309"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_017SowBbjedrKT8Tc2FD4u9Y","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/ingest.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"bb996787-09de-44b4-84a7-799f06c8f250","timestamp":"2026-08-25T13:21:49.591Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/ingest.py","oldString":" listings = cls().fetch()\n finalized, dropped = [], 0\n for lst in listings:\n try:\n finalized.append(lst.finalize())\n except Exception: # une annonce malformée ne bloque pas la source\n dropped += 1\n stats = db.sync_source(con, sid, finalized)","newString":" listings = cls().fetch()\n finalized, dropped = [], 0\n for lst in listings:\n try:\n finalized.append(lst.finalize())\n except Exception: # une annonce malformée ne bloque pas la source\n dropped += 1\n try:\n # garde géographique : coordonnées fournies par la source mais\n # incompatibles avec la ville annoncée -> annulées (le géocodeur\n # rigoureux prendra le relais). Cache seulement, aucun réseau.\n from . import geocode\n bad = geocode.strip_bad_source_coords(con, finalized)\n if bad:\n print(f\"[immo-ka] {bad} coordonnée(s) source incohérente(s) rejetée(s)\")\n except Exception:\n traceback.print_exc()\n stats = db.sync_source(con, sid, finalized)","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# ingest.py : pipeline d'ingestion — exécute les connecteurs et synchronise\n# la base (ajouts / mises à jour / retraits) = contenu toujours à jour\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport sys\nimport time\nimport traceback\n\nfrom . import db\nfrom .connectors import CONNECTORS\n\n\ndef run(sources: list[str] | None = None) -> list[dict]:\n \"\"\"Exécute l'ingestion pour toutes les sources (ou celles demandées).\"\"\"\n con = db.connect()\n results = []\n targets = sources or list(CONNECTORS.keys())\n for sid in targets:\n cls = CONNECTORS.get(sid)\n if cls is None:\n print(f\"[immo-ka] connecteur inconnu : {sid}\", file=sys.stderr)\n continue\n t0 = time.time()\n print(f\"[immo-ka] sync {sid} ...\")\n try:\n listings = cls().fetch()\n finalized, dropped = [], 0\n for lst in listings:\n try:\n finalized.append(lst.finalize())\n except Exception: # une annonce malformée ne bloque pas la source\n dropped += 1\n stats = db.sync_source(con, sid, finalized)\n stats[\"seconds\"] = round(time.time() - t0, 1)\n if dropped:\n stats[\"dropped\"] = dropped\n if stats.get(\"alert\"):\n print(f\"[immo-ka] ⚠ ALERTE {sid} : {stats['alert']}\")\n print(f\"[immo-ka] {stats}\")\n results.append(stats)\n except Exception as exc: # robustesse : une source ne bloque pas les autres\n db.log_failure(con, sid, f\"{exc}\")\n traceback.print_exc()\n results.append({\"source\": sid, \"error\": str(exc)})\n # recalcule la déduplication (pré-calculée pour des lectures instantanées)\n try:\n hidden = db.refresh_dedup(con)\n print(f\"[immo-ka] dédup: {hidden} doublon(s) masqué(s) \"\n \"(sous-agences Centris + adresse inter-sources)\")\n except Exception:\n traceback.print_exc()\n # contrôle qualité : score de complétude, cohérence immobilière, seuil de\n # publication (quarantaine) et champs dérivés (prix/pi², transaction)\n try:\n from . import quality\n q = quality.refresh(con)\n print(f\"[immo-ka] qualité: {q['publiees']} publiée(s), \"\n f\"{q['quarantaine']} en quarantaine, \"\n f\"{q['recalculees']} recalculée(s)\")\n except Exception:\n traceback.print_exc()\n # statistiques du planificateur SQLite : sans elles, les requêtes bbox\n # de la carte (Ka Maps) n'utilisent pas idx_listings_geo\n try:\n con.execute(\"PRAGMA optimize\")\n except Exception:\n pass\n con.close()\n return results\n\n\ndef watch(interval_seconds: int = 3600) -> None:\n \"\"\"Boucle de synchronisation périodique (équivalent webhook, via PM2/cron).\n\n Après chaque synchronisation, l'enrichissement continu de la carte\n (Ka Maps) : géocodage EN LOT des nouvelles adresses (Adresses Québec),\n puis appariement Vrai-Prix local (estimations + coordonnées du rôle)\n quand data/vraiprix.db (ou VRAIPRIX_DB) est disponible.\n \"\"\"\n while True:\n run()\n try: # nouvelles adresses → coordonnées (cache : quasi gratuit ensuite)\n from . import geocode\n geocode.run_batch()\n except Exception as exc:\n print(f\"[immo-ka] geocode: erreur non bloquante: {exc}\", file=sys.stderr)\n try: # estimations Vrai-Prix + géocodage bonus depuis le rôle\n from . import vraiprix_local\n if vraiprix_local.available():\n vraiprix_local.run(limit=5000)\n # rôle d'évaluation (valeurs/année/superficies officielles) pour\n # les annonces déjà appariées — jointure par id, quasi gratuite\n vraiprix_local.enrich_role(limit=20000)\n except Exception as exc:\n print(f\"[immo-ka] vraiprix_local: erreur non bloquante: {exc}\", file=sys.stderr)\n try: # audit budgété des images (liens morts, minuscules, corrompues)\n from . import imgaudit\n ia = imgaudit.run_batch(limit=2000)\n print(f\"[immo-ka] images: {ia['urls_verifiees']} URL vérifiée(s), \"\n f\"{ia['images_retirees']} retirée(s), \"\n f\"{ia['sans_image_valide']} annonce(s) sans image valide\")\n except Exception as exc:\n print(f\"[immo-ka] imgaudit: erreur non bloquante: {exc}\", file=sys.stderr)\n try: # estimation Hydro-Québec des nouvelles annonces (cache persistant, coût borné)\n from . import hydro\n hydro.precompute(limit=100, budget=30)\n except Exception as exc:\n print(f\"[immoka] hydro: erreur non bloquante: {exc}\", file=sys.stderr)\n try: # taux hypothécaires — collecte espacée (IMMOKA_MORTGAGE_INTERVAL_MIN)\n from .mortgage import scheduler as mortgage_scheduler\n mortgage_scheduler.maybe_run()\n except Exception as exc:\n print(f\"[immo-ka] mortgage: erreur non bloquante: {exc}\", file=sys.stderr)\n print(f\"[immo-ka] prochaine synchronisation dans {interval_seconds // 60} min\")\n time.sleep(interval_seconds)\n","structuredPatch":[{"oldStart":34,"oldLines":6,"newStart":34,"newLines":16,"lines":[" finalized.append(lst.finalize())"," except Exception: # une annonce malformée ne bloque pas la source"," dropped += 1","+ try:","+ # garde géographique : coordonnées fournies par la source mais","+ # incompatibles avec la ville annoncée -> annulées (le géocodeur","+ # rigoureux prendra le relais). Cache seulement, aucun réseau.","+ from . import geocode","+ bad = geocode.strip_bad_source_coords(con, finalized)","+ if bad:","+ print(f\"[immo-ka] {bad} coordonnée(s) source incohérente(s) rejetée(s)\")","+ except Exception:","+ traceback.print_exc()"," stats = db.sync_source(con, sid, finalized)"," stats[\"seconds\"] = round(time.time() - t0, 1)"," if dropped:"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY5C9BSeNedoj96nEuY","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01LQCho4RSErh73NHzK5BaQ5","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/ingest.py","old_string":" try: # nouvelles adresses → coordonnées (cache : quasi gratuit ensuite)\n from . import geocode\n geocode.run_batch()\n except Exception as exc:\n print(f\"[immo-ka] geocode: erreur non bloquante: {exc}\", file=sys.stderr)","new_string":" try: # nouvelles adresses → coordonnées (cache : quasi gratuit ensuite)\n from . import geocode\n # audit de cohérence d'abord : les fiches mal localisées (rue\n # homonyme, geo source erroné) sont remises en file, puis le lot\n # les re-géocode rigoureusement (budget Nominatim borné par passe)\n geocode.run_audit(nominatim_budget=50)\n geocode.run_batch()\n except Exception as exc:\n print(f\"[immo-ka] geocode: erreur non bloquante: {exc}\", file=sys.stderr)"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":811,"cache_read_input_tokens":100008,"cache_creation":{"ephemeral_5m_input_tokens":811,"ephemeral_1h_input_tokens":0},"output_tokens":5,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"103c2b15-bfeb-43b7-ba2a-e03c17e8955c"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01LQCho4RSErh73NHzK5BaQ5","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/ingest.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"150c0dd0-a74d-4e78-b305-610a68763bc5","timestamp":"2026-08-25T13:21:53.794Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/ingest.py","oldString":" try: # nouvelles adresses → coordonnées (cache : quasi gratuit ensuite)\n from . import geocode\n geocode.run_batch()\n except Exception as exc:\n print(f\"[immo-ka] geocode: erreur non bloquante: {exc}\", file=sys.stderr)","newString":" try: # nouvelles adresses → coordonnées (cache : quasi gratuit ensuite)\n from . import geocode\n # audit de cohérence d'abord : les fiches mal localisées (rue\n # homonyme, geo source erroné) sont remises en file, puis le lot\n # les re-géocode rigoureusement (budget Nominatim borné par passe)\n geocode.run_audit(nominatim_budget=50)\n geocode.run_batch()\n except Exception as exc:\n print(f\"[immo-ka] geocode: erreur non bloquante: {exc}\", file=sys.stderr)","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# ingest.py : pipeline d'ingestion — exécute les connecteurs et synchronise\n# la base (ajouts / mises à jour / retraits) = contenu toujours à jour\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport sys\nimport time\nimport traceback\n\nfrom . import db\nfrom .connectors import CONNECTORS\n\n\ndef run(sources: list[str] | None = None) -> list[dict]:\n \"\"\"Exécute l'ingestion pour toutes les sources (ou celles demandées).\"\"\"\n con = db.connect()\n results = []\n targets = sources or list(CONNECTORS.keys())\n for sid in targets:\n cls = CONNECTORS.get(sid)\n if cls is None:\n print(f\"[immo-ka] connecteur inconnu : {sid}\", file=sys.stderr)\n continue\n t0 = time.time()\n print(f\"[immo-ka] sync {sid} ...\")\n try:\n listings = cls().fetch()\n finalized, dropped = [], 0\n for lst in listings:\n try:\n finalized.append(lst.finalize())\n except Exception: # une annonce malformée ne bloque pas la source\n dropped += 1\n try:\n # garde géographique : coordonnées fournies par la source mais\n # incompatibles avec la ville annoncée -> annulées (le géocodeur\n # rigoureux prendra le relais). Cache seulement, aucun réseau.\n from . import geocode\n bad = geocode.strip_bad_source_coords(con, finalized)\n if bad:\n print(f\"[immo-ka] {bad} coordonnée(s) source incohérente(s) rejetée(s)\")\n except Exception:\n traceback.print_exc()\n stats = db.sync_source(con, sid, finalized)\n stats[\"seconds\"] = round(time.time() - t0, 1)\n if dropped:\n stats[\"dropped\"] = dropped\n if stats.get(\"alert\"):\n print(f\"[immo-ka] ⚠ ALERTE {sid} : {stats['alert']}\")\n print(f\"[immo-ka] {stats}\")\n results.append(stats)\n except Exception as exc: # robustesse : une source ne bloque pas les autres\n db.log_failure(con, sid, f\"{exc}\")\n traceback.print_exc()\n results.append({\"source\": sid, \"error\": str(exc)})\n # recalcule la déduplication (pré-calculée pour des lectures instantanées)\n try:\n hidden = db.refresh_dedup(con)\n print(f\"[immo-ka] dédup: {hidden} doublon(s) masqué(s) \"\n \"(sous-agences Centris + adresse inter-sources)\")\n except Exception:\n traceback.print_exc()\n # contrôle qualité : score de complétude, cohérence immobilière, seuil de\n # publication (quarantaine) et champs dérivés (prix/pi², transaction)\n try:\n from . import quality\n q = quality.refresh(con)\n print(f\"[immo-ka] qualité: {q['publiees']} publiée(s), \"\n f\"{q['quarantaine']} en quarantaine, \"\n f\"{q['recalculees']} recalculée(s)\")\n except Exception:\n traceback.print_exc()\n # statistiques du planificateur SQLite : sans elles, les requêtes bbox\n # de la carte (Ka Maps) n'utilisent pas idx_listings_geo\n try:\n con.execute(\"PRAGMA optimize\")\n except Exception:\n pass\n con.close()\n return results\n\n\ndef watch(interval_seconds: int = 3600) -> None:\n \"\"\"Boucle de synchronisation périodique (équivalent webhook, via PM2/cron).\n\n Après chaque synchronisation, l'enrichissement continu de la carte\n (Ka Maps) : géocodage EN LOT des nouvelles adresses (Adresses Québec),\n puis appariement Vrai-Prix local (estimations + coordonnées du rôle)\n quand data/vraiprix.db (ou VRAIPRIX_DB) est disponible.\n \"\"\"\n while True:\n run()\n try: # nouvelles adresses → coordonnées (cache : quasi gratuit ensuite)\n from . import geocode\n geocode.run_batch()\n except Exception as exc:\n print(f\"[immo-ka] geocode: erreur non bloquante: {exc}\", file=sys.stderr)\n try: # estimations Vrai-Prix + géocodage bonus depuis le rôle\n from . import vraiprix_local\n if vraiprix_local.available():\n vraiprix_local.run(limit=5000)\n # rôle d'évaluation (valeurs/année/superficies officielles) pour\n # les annonces déjà appariées — jointure par id, quasi gratuite\n vraiprix_local.enrich_role(limit=20000)\n except Exception as exc:\n print(f\"[immo-ka] vraiprix_local: erreur non bloquante: {exc}\", file=sys.stderr)\n try: # audit budgété des images (liens morts, minuscules, corrompues)\n from . import imgaudit\n ia = imgaudit.run_batch(limit=2000)\n print(f\"[immo-ka] images: {ia['urls_verifiees']} URL vérifiée(s), \"\n f\"{ia['images_retirees']} retirée(s), \"\n f\"{ia['sans_image_valide']} annonce(s) sans image valide\")\n except Exception as exc:\n print(f\"[immo-ka] imgaudit: erreur non bloquante: {exc}\", file=sys.stderr)\n try: # estimation Hydro-Québec des nouvelles annonces (cache persistant, coût borné)\n from . import hydro\n hydro.precompute(limit=100, budget=30)\n except Exception as exc:\n print(f\"[immoka] hydro: erreur non bloquante: {exc}\", file=sys.stderr)\n try: # taux hypothécaires — collecte espacée (IMMOKA_MORTGAGE_INTERVAL_MIN)\n from .mortgage import scheduler as mortgage_scheduler\n mortgage_scheduler.maybe_run()\n except Exception as exc:\n print(f\"[immo-ka] mortgage: erreur non bloquante: {exc}\", file=sys.stderr)\n print(f\"[immo-ka] prochaine synchronisation dans {interval_seconds // 60} min\")\n time.sleep(interval_seconds)\n","structuredPatch":[{"oldStart":95,"oldLines":6,"newStart":95,"newLines":10,"lines":[" run()"," try: # nouvelles adresses → coordonnées (cache : quasi gratuit ensuite)"," from . import geocode","+ # audit de cohérence d'abord : les fiches mal localisées (rue","+ # homonyme, geo source erroné) sont remises en file, puis le lot","+ # les re-géocode rigoureusement (budget Nominatim borné par passe)","+ geocode.run_audit(nominatim_budget=50)"," geocode.run_batch()"," except Exception as exc:"," print(f\"[immo-ka] geocode: erreur non bloquante: {exc}\", file=sys.stderr)"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY5C9BSeNedoj96nEuY","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01VEaKCq8GjGesYKJ9ynFXsb","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/run.py","old_string":" elif cmd == \"geocode1\": # ancien mode 1-par-1 (+ repli Nominatim)\n from immoka import geocode\n geocode.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)","new_string":" elif cmd == \"geocode1\": # ancien mode 1-par-1 (+ repli Nominatim)\n from immoka import geocode\n geocode.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"geocode-audit\": # cohérence coordonnées <-> ville annoncée\n from immoka import geocode\n budget = int(sys.argv[2]) if len(sys.argv) > 2 else None\n geocode.run_audit(nominatim_budget=budget,\n apply=\"dry\" not in sys.argv[2:])"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":811,"cache_read_input_tokens":100008,"cache_creation":{"ephemeral_5m_input_tokens":811,"ephemeral_1h_input_tokens":0},"output_tokens":5,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"62675cd2-6f68-4302-b698-6a2b377d43fe"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01VEaKCq8GjGesYKJ9ynFXsb","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/run.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ad482d3f-a0d5-411a-a6e5-6ee495016ab0","timestamp":"2026-08-25T13:21:56.632Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/run.py","oldString":" elif cmd == \"geocode1\": # ancien mode 1-par-1 (+ repli Nominatim)\n from immoka import geocode\n geocode.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)","newString":" elif cmd == \"geocode1\": # ancien mode 1-par-1 (+ repli Nominatim)\n from immoka import geocode\n geocode.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"geocode-audit\": # cohérence coordonnées <-> ville annoncée\n from immoka import geocode\n budget = int(sys.argv[2]) if len(sys.argv) > 2 else None\n geocode.run_audit(nominatim_budget=budget,\n apply=\"dry\" not in sys.argv[2:])","originalFile":"#!/usr/bin/env python3\n# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# run.py : point d'entrée — `sync`, `watch`, `serve`\n# -----------------------------------------------------------------------------\n\"\"\"Utilisation :\n python run.py sync [source ...] # synchronise les propriétés\n python run.py watch [minutes] # synchronise en boucle (défaut 60 min)\n python run.py serve [port] # démarre l'API + le frontend (défaut 8090)\n python run.py list # liste les connecteurs enregistrés\n python run.py geocode [n] # géocode les annonces sans coordonnées (max n requêtes)\n python run.py poi [n] # commodités de proximité par immeuble (max n requêtes)\n python run.py quartier [n] # rattache chaque annonce à son aire de diffusion (DAUID)\n python run.py mortgage-sync [slug…] # collecte les taux hypothécaires (toutes banques ou celles listées)\n python run.py mortgage-watch [min] # collecte en boucle (défaut IMMOKA_MORTGAGE_INTERVAL_MIN=180)\n python run.py mortgage-status # santé des providers de taux (OK/WARNING/ERROR)\n\"\"\"\nfrom __future__ import annotations\n\nimport os\nimport sys\nfrom pathlib import Path\n\n# Charger .env (FIRECRAWL_API_KEY, etc.) sans dépendance externe\n_env = Path(__file__).parent / \".env\"\nif _env.exists():\n for line in _env.read_text().splitlines():\n line = line.strip()\n if line and not line.startswith(\"#\") and \"=\" in line:\n k, _, v = line.partition(\"=\")\n os.environ.setdefault(k.strip(), v.strip())\n\n\ndef main() -> None:\n cmd = sys.argv[1] if len(sys.argv) > 1 else \"serve\"\n if cmd == \"sync\":\n from immoka import ingest\n ingest.run(sys.argv[2:] or None)\n elif cmd == \"watch\":\n from immoka import ingest\n minutes = int(sys.argv[2]) if len(sys.argv) > 2 else 60\n ingest.watch(minutes * 60)\n elif cmd == \"list\":\n from immoka.connectors import CONNECTORS\n for sid in sorted(CONNECTORS):\n print(sid)\n print(f\"-- {len(CONNECTORS)} connecteur(s)\")\n elif cmd == \"geocode\":\n from immoka import geocode\n geocode.run_batch(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"geocode1\": # ancien mode 1-par-1 (+ repli Nominatim)\n from immoka import geocode\n geocode.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"poi\":\n from immoka import poi\n poi.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"air-refresh\":\n from immoka import air\n air.refresh()\n elif cmd == \"gaz-refresh\":\n from immoka import gaz\n print(f\"[gaz] {gaz.refresh()} stations\")\n elif cmd == \"hydro-precompute\":\n from immoka import hydro\n n = int(sys.argv[2]) if len(sys.argv) > 2 else 100\n b = int(sys.argv[3]) if len(sys.argv) > 3 else 40\n hydro.precompute(limit=n, budget=b)\n elif cmd == \"inondation-build\":\n from immoka import inondation\n inondation.build()\n elif cmd == \"quartier\":\n from immoka import quartier\n quartier.enrich(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"vraiprix\":\n from immoka import vraiprix\n vraiprix.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"vraiprix_local\": # appariement local (vraiprix.db) : rapide\n from immoka import vraiprix_local\n reval = \"reval\" in sys.argv[2:]\n lim = next((int(a) for a in sys.argv[2:] if a.isdigit()), None)\n if \"role\" in sys.argv[2:]: # backfill rôle d'évaluation (jointure par id)\n vraiprix_local.enrich_role(lim)\n else:\n vraiprix_local.run(lim, revalidate=reval)\n elif cmd == \"mortgage-sync\":\n from immoka.mortgage import scheduler\n scheduler.run(sys.argv[2:] or None)\n elif cmd == \"mortgage-watch\":\n from immoka.mortgage import scheduler\n minutes = int(sys.argv[2]) if len(sys.argv) > 2 else None\n scheduler.watch(minutes)\n elif cmd == \"mortgage-status\":\n from immoka.mortgage import store\n con = store.connect()\n for h in store.provider_health(con):\n print(f\"{h['level']:8s} {h['provider']:15s} \"\n f\"statut={h.get('status') or '-'} \"\n f\"produits_courants={h.get('current_products', 0)} \"\n f\"dernière_passe=il y a {h.get('age_minutes', '?')} min\")\n elif cmd == \"serve\":\n import uvicorn\n port = int(sys.argv[2]) if len(sys.argv) > 2 else 8090\n uvicorn.run(\"immoka.web:app\", host=\"0.0.0.0\", port=port)\n else:\n print(__doc__)\n sys.exit(1)\n\n\nif __name__ == \"__main__\":\n main()\n","structuredPatch":[{"oldStart":52,"oldLines":6,"newStart":52,"newLines":11,"lines":[" elif cmd == \"geocode1\": # ancien mode 1-par-1 (+ repli Nominatim)"," from immoka import geocode"," geocode.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)","+ elif cmd == \"geocode-audit\": # cohérence coordonnées <-> ville annoncée","+ from immoka import geocode","+ budget = int(sys.argv[2]) if len(sys.argv) > 2 else None","+ geocode.run_audit(nominatim_budget=budget,","+ apply=\"dry\" not in sys.argv[2:])"," elif cmd == \"poi\":"," from immoka import poi"," poi.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"f87c1c0b-80fd-4a31-a36e-a8bb57bdb774","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY7AHrhoJAqGkkYdbtj","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":2833,"cache_read_input_tokens":100819,"cache_creation":{"ephemeral_5m_input_tokens":2833,"ephemeral_1h_input_tokens":0},"output_tokens":5,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"d8c72d51-9cf6-4c71-a1dc-adf0bf6bad7d"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY7AHrhoJAqGkkYdbtj","type":"message","role":"assistant","content":[{"type":"text","text":"Petit correctif du parsing CLI (`dry` vs budget numérique) et mise à jour du docstring d'usage."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":2833,"cache_read_input_tokens":100819,"cache_creation":{"ephemeral_5m_input_tokens":2833,"ephemeral_1h_input_tokens":0},"output_tokens":5,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"737f972f-09df-4553-9e21-1388cd0427cd"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY7AHrhoJAqGkkYdbtj","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01PvuvEqztVhHg9Jz9SyMjWR","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/run.py","old_string":" elif cmd == \"geocode-audit\": # cohérence coordonnées <-> ville annoncée\n from immoka import geocode\n budget = int(sys.argv[2]) if len(sys.argv) > 2 else None\n geocode.run_audit(nominatim_budget=budget,\n apply=\"dry\" not in sys.argv[2:])","new_string":" elif cmd == \"geocode-audit\": # cohérence coordonnées <-> ville annoncée\n from immoka import geocode\n budget = next((int(a) for a in sys.argv[2:] if a.isdigit()), None)\n geocode.run_audit(nominatim_budget=budget,\n apply=\"dry\" not in sys.argv[2:])"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":2833,"cache_read_input_tokens":100819,"cache_creation":{"ephemeral_5m_input_tokens":2833,"ephemeral_1h_input_tokens":0},"output_tokens":5,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"11af4479-7515-4ec3-90c4-8fe73e5b7815"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01PvuvEqztVhHg9Jz9SyMjWR","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/run.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"dd2bbee4-9122-430a-9ba2-45bc2390b79a","timestamp":"2026-08-25T13:22:16.221Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/run.py","oldString":" elif cmd == \"geocode-audit\": # cohérence coordonnées <-> ville annoncée\n from immoka import geocode\n budget = int(sys.argv[2]) if len(sys.argv) > 2 else None\n geocode.run_audit(nominatim_budget=budget,\n apply=\"dry\" not in sys.argv[2:])","newString":" elif cmd == \"geocode-audit\": # cohérence coordonnées <-> ville annoncée\n from immoka import geocode\n budget = next((int(a) for a in sys.argv[2:] if a.isdigit()), None)\n geocode.run_audit(nominatim_budget=budget,\n apply=\"dry\" not in sys.argv[2:])","originalFile":"#!/usr/bin/env python3\n# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# run.py : point d'entrée — `sync`, `watch`, `serve`\n# -----------------------------------------------------------------------------\n\"\"\"Utilisation :\n python run.py sync [source ...] # synchronise les propriétés\n python run.py watch [minutes] # synchronise en boucle (défaut 60 min)\n python run.py serve [port] # démarre l'API + le frontend (défaut 8090)\n python run.py list # liste les connecteurs enregistrés\n python run.py geocode [n] # géocode les annonces sans coordonnées (max n requêtes)\n python run.py poi [n] # commodités de proximité par immeuble (max n requêtes)\n python run.py quartier [n] # rattache chaque annonce à son aire de diffusion (DAUID)\n python run.py mortgage-sync [slug…] # collecte les taux hypothécaires (toutes banques ou celles listées)\n python run.py mortgage-watch [min] # collecte en boucle (défaut IMMOKA_MORTGAGE_INTERVAL_MIN=180)\n python run.py mortgage-status # santé des providers de taux (OK/WARNING/ERROR)\n\"\"\"\nfrom __future__ import annotations\n\nimport os\nimport sys\nfrom pathlib import Path\n\n# Charger .env (FIRECRAWL_API_KEY, etc.) sans dépendance externe\n_env = Path(__file__).parent / \".env\"\nif _env.exists():\n for line in _env.read_text().splitlines():\n line = line.strip()\n if line and not line.startswith(\"#\") and \"=\" in line:\n k, _, v = line.partition(\"=\")\n os.environ.setdefault(k.strip(), v.strip())\n\n\ndef main() -> None:\n cmd = sys.argv[1] if len(sys.argv) > 1 else \"serve\"\n if cmd == \"sync\":\n from immoka import ingest\n ingest.run(sys.argv[2:] or None)\n elif cmd == \"watch\":\n from immoka import ingest\n minutes = int(sys.argv[2]) if len(sys.argv) > 2 else 60\n ingest.watch(minutes * 60)\n elif cmd == \"list\":\n from immoka.connectors import CONNECTORS\n for sid in sorted(CONNECTORS):\n print(sid)\n print(f\"-- {len(CONNECTORS)} connecteur(s)\")\n elif cmd == \"geocode\":\n from immoka import geocode\n geocode.run_batch(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"geocode1\": # ancien mode 1-par-1 (+ repli Nominatim)\n from immoka import geocode\n geocode.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"geocode-audit\": # cohérence coordonnées <-> ville annoncée\n from immoka import geocode\n budget = int(sys.argv[2]) if len(sys.argv) > 2 else None\n geocode.run_audit(nominatim_budget=budget,\n apply=\"dry\" not in sys.argv[2:])\n elif cmd == \"poi\":\n from immoka import poi\n poi.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"air-refresh\":\n from immoka import air\n air.refresh()\n elif cmd == \"gaz-refresh\":\n from immoka import gaz\n print(f\"[gaz] {gaz.refresh()} stations\")\n elif cmd == \"hydro-precompute\":\n from immoka import hydro\n n = int(sys.argv[2]) if len(sys.argv) > 2 else 100\n b = int(sys.argv[3]) if len(sys.argv) > 3 else 40\n hydro.precompute(limit=n, budget=b)\n elif cmd == \"inondation-build\":\n from immoka import inondation\n inondation.build()\n elif cmd == \"quartier\":\n from immoka import quartier\n quartier.enrich(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"vraiprix\":\n from immoka import vraiprix\n vraiprix.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"vraiprix_local\": # appariement local (vraiprix.db) : rapide\n from immoka import vraiprix_local\n reval = \"reval\" in sys.argv[2:]\n lim = next((int(a) for a in sys.argv[2:] if a.isdigit()), None)\n if \"role\" in sys.argv[2:]: # backfill rôle d'évaluation (jointure par id)\n vraiprix_local.enrich_role(lim)\n else:\n vraiprix_local.run(lim, revalidate=reval)\n elif cmd == \"mortgage-sync\":\n from immoka.mortgage import scheduler\n scheduler.run(sys.argv[2:] or None)\n elif cmd == \"mortgage-watch\":\n from immoka.mortgage import scheduler\n minutes = int(sys.argv[2]) if len(sys.argv) > 2 else None\n scheduler.watch(minutes)\n elif cmd == \"mortgage-status\":\n from immoka.mortgage import store\n con = store.connect()\n for h in store.provider_health(con):\n print(f\"{h['level']:8s} {h['provider']:15s} \"\n f\"statut={h.get('status') or '-'} \"\n f\"produits_courants={h.get('current_products', 0)} \"\n f\"dernière_passe=il y a {h.get('age_minutes', '?')} min\")\n elif cmd == \"serve\":\n import uvicorn\n port = int(sys.argv[2]) if len(sys.argv) > 2 else 8090\n uvicorn.run(\"immoka.web:app\", host=\"0.0.0.0\", port=port)\n else:\n print(__doc__)\n sys.exit(1)\n\n\nif __name__ == \"__main__\":\n main()\n","structuredPatch":[{"oldStart":54,"oldLines":7,"newStart":54,"newLines":7,"lines":[" geocode.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)"," elif cmd == \"geocode-audit\": # cohérence coordonnées <-> ville annoncée"," from immoka import geocode","- budget = int(sys.argv[2]) if len(sys.argv) > 2 else None","+ budget = next((int(a) for a in sys.argv[2:] if a.isdigit()), None)"," geocode.run_audit(nominatim_budget=budget,"," apply=\"dry\" not in sys.argv[2:])"," elif cmd == \"poi\":"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY7AHrhoJAqGkkYdbtj","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01F5UDky5UPTzC5VYztpBEPK","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/run.py","old_string":" python run.py geocode [n] # géocode les annonces sans coordonnées (max n requêtes)","new_string":" python run.py geocode [n] # géocode les annonces sans coordonnées (max n requêtes)\n python run.py geocode-audit [n] [dry] # audit coordonnées <-> ville (n = budget Nominatim)"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":2833,"cache_read_input_tokens":100819,"cache_creation":{"ephemeral_5m_input_tokens":2833,"ephemeral_1h_input_tokens":0},"output_tokens":5,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ec31ae8b-62e3-42ce-b0de-664a8cecd24a"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01F5UDky5UPTzC5VYztpBEPK","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/run.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"c42b0a38-aabc-47ee-b4a6-7f3e470dad31","timestamp":"2026-08-25T13:22:18.062Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/run.py","oldString":" python run.py geocode [n] # géocode les annonces sans coordonnées (max n requêtes)","newString":" python run.py geocode [n] # géocode les annonces sans coordonnées (max n requêtes)\n python run.py geocode-audit [n] [dry] # audit coordonnées <-> ville (n = budget Nominatim)","originalFile":"#!/usr/bin/env python3\n# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# run.py : point d'entrée — `sync`, `watch`, `serve`\n# -----------------------------------------------------------------------------\n\"\"\"Utilisation :\n python run.py sync [source ...] # synchronise les propriétés\n python run.py watch [minutes] # synchronise en boucle (défaut 60 min)\n python run.py serve [port] # démarre l'API + le frontend (défaut 8090)\n python run.py list # liste les connecteurs enregistrés\n python run.py geocode [n] # géocode les annonces sans coordonnées (max n requêtes)\n python run.py poi [n] # commodités de proximité par immeuble (max n requêtes)\n python run.py quartier [n] # rattache chaque annonce à son aire de diffusion (DAUID)\n python run.py mortgage-sync [slug…] # collecte les taux hypothécaires (toutes banques ou celles listées)\n python run.py mortgage-watch [min] # collecte en boucle (défaut IMMOKA_MORTGAGE_INTERVAL_MIN=180)\n python run.py mortgage-status # santé des providers de taux (OK/WARNING/ERROR)\n\"\"\"\nfrom __future__ import annotations\n\nimport os\nimport sys\nfrom pathlib import Path\n\n# Charger .env (FIRECRAWL_API_KEY, etc.) sans dépendance externe\n_env = Path(__file__).parent / \".env\"\nif _env.exists():\n for line in _env.read_text().splitlines():\n line = line.strip()\n if line and not line.startswith(\"#\") and \"=\" in line:\n k, _, v = line.partition(\"=\")\n os.environ.setdefault(k.strip(), v.strip())\n\n\ndef main() -> None:\n cmd = sys.argv[1] if len(sys.argv) > 1 else \"serve\"\n if cmd == \"sync\":\n from immoka import ingest\n ingest.run(sys.argv[2:] or None)\n elif cmd == \"watch\":\n from immoka import ingest\n minutes = int(sys.argv[2]) if len(sys.argv) > 2 else 60\n ingest.watch(minutes * 60)\n elif cmd == \"list\":\n from immoka.connectors import CONNECTORS\n for sid in sorted(CONNECTORS):\n print(sid)\n print(f\"-- {len(CONNECTORS)} connecteur(s)\")\n elif cmd == \"geocode\":\n from immoka import geocode\n geocode.run_batch(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"geocode1\": # ancien mode 1-par-1 (+ repli Nominatim)\n from immoka import geocode\n geocode.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"geocode-audit\": # cohérence coordonnées <-> ville annoncée\n from immoka import geocode\n budget = next((int(a) for a in sys.argv[2:] if a.isdigit()), None)\n geocode.run_audit(nominatim_budget=budget,\n apply=\"dry\" not in sys.argv[2:])\n elif cmd == \"poi\":\n from immoka import poi\n poi.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"air-refresh\":\n from immoka import air\n air.refresh()\n elif cmd == \"gaz-refresh\":\n from immoka import gaz\n print(f\"[gaz] {gaz.refresh()} stations\")\n elif cmd == \"hydro-precompute\":\n from immoka import hydro\n n = int(sys.argv[2]) if len(sys.argv) > 2 else 100\n b = int(sys.argv[3]) if len(sys.argv) > 3 else 40\n hydro.precompute(limit=n, budget=b)\n elif cmd == \"inondation-build\":\n from immoka import inondation\n inondation.build()\n elif cmd == \"quartier\":\n from immoka import quartier\n quartier.enrich(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"vraiprix\":\n from immoka import vraiprix\n vraiprix.run(int(sys.argv[2]) if len(sys.argv) > 2 else None)\n elif cmd == \"vraiprix_local\": # appariement local (vraiprix.db) : rapide\n from immoka import vraiprix_local\n reval = \"reval\" in sys.argv[2:]\n lim = next((int(a) for a in sys.argv[2:] if a.isdigit()), None)\n if \"role\" in sys.argv[2:]: # backfill rôle d'évaluation (jointure par id)\n vraiprix_local.enrich_role(lim)\n else:\n vraiprix_local.run(lim, revalidate=reval)\n elif cmd == \"mortgage-sync\":\n from immoka.mortgage import scheduler\n scheduler.run(sys.argv[2:] or None)\n elif cmd == \"mortgage-watch\":\n from immoka.mortgage import scheduler\n minutes = int(sys.argv[2]) if len(sys.argv) > 2 else None\n scheduler.watch(minutes)\n elif cmd == \"mortgage-status\":\n from immoka.mortgage import store\n con = store.connect()\n for h in store.provider_health(con):\n print(f\"{h['level']:8s} {h['provider']:15s} \"\n f\"statut={h.get('status') or '-'} \"\n f\"produits_courants={h.get('current_products', 0)} \"\n f\"dernière_passe=il y a {h.get('age_minutes', '?')} min\")\n elif cmd == \"serve\":\n import uvicorn\n port = int(sys.argv[2]) if len(sys.argv) > 2 else 8090\n uvicorn.run(\"immoka.web:app\", host=\"0.0.0.0\", port=port)\n else:\n print(__doc__)\n sys.exit(1)\n\n\nif __name__ == \"__main__\":\n main()\n","structuredPatch":[{"oldStart":10,"oldLines":6,"newStart":10,"newLines":7,"lines":[" python run.py serve [port] # démarre l'API + le frontend (défaut 8090)"," python run.py list # liste les connecteurs enregistrés"," python run.py geocode [n] # géocode les annonces sans coordonnées (max n requêtes)","+ python run.py geocode-audit [n] [dry] # audit coordonnées <-> ville (n = budget Nominatim)"," python run.py poi [n] # commodités de proximité par immeuble (max n requêtes)"," python run.py quartier [n] # rattache chaque annonce à son aire de diffusion (DAUID)"," python run.py mortgage-sync [slug…] # collecte les taux hypothécaires (toutes banques ou celles listées)"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"6590afb7-ea2b-46c6-a6c7-d0fef3c51f2c","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY8kKXFceQM7FajAE7r","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1941,"cache_read_input_tokens":103652,"cache_creation":{"ephemeral_5m_input_tokens":1941,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"fc82a766-c2e5-4e48-aa88-9fd919bf372f"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY8kKXFceQM7FajAE7r","type":"message","role":"assistant","content":[{"type":"text","text":"Code en place. Je compile et je teste sur le cas réel (rue des Perdrix)."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1941,"cache_read_input_tokens":103652,"cache_creation":{"ephemeral_5m_input_tokens":1941,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ea6061ea-cfee-4d4d-afa0-17f18a7392f9"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY8kKXFceQM7FajAE7r","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01QyzNNsFfRck4oBAtFfytgm","name":"TodoWrite","input":{"todos":[{"content":"geocode.py : centroïde de ville (médiane BD + Nominatim caché) et validation ≤40 km","status":"completed","activeForm":"Ajout de la validation par centroïde de ville"},{"content":"resolve() : retry AQ avec municipalité officielle + variantes Nominatim","status":"completed","activeForm":"Ajout des variantes de municipalité"},{"content":"run_batch : validation centroïde + rattrapage resolve() des échecs","status":"completed","activeForm":"Renforcement du géocodage batch"},{"content":"run_audit : détecter/corriger les fiches aux coordonnées incohérentes","status":"completed","activeForm":"Création de l'audit géocodage"},{"content":"Garde ingestion : rejeter les coords de connecteur contredisant la ville","status":"completed","activeForm":"Ajout de la garde à l'ingestion"},{"content":"db.py : colonne muni dans geocode_cache + CLI geocode-audit + watch","status":"completed","activeForm":"Migration BD et CLI"},{"content":"Corriger duproprio:1126225 + lancer l'audit + vérifier le site","status":"in_progress","activeForm":"Correction des fiches et vérification"},{"content":"pm2 restart + commit + push origin main","status":"pending","activeForm":"Redéploiement et commit"}]},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1941,"cache_read_input_tokens":103652,"cache_creation":{"ephemeral_5m_input_tokens":1941,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"f1bafcbc-0dbd-4d1d-a88d-36ffb1cbc237"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01QyzNNsFfRck4oBAtFfytgm","type":"tool_result","content":"Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"658a226d-6b08-4e0d-8133-3197d6866b07","timestamp":"2026-08-25T13:22:29.993Z","tool_use_result":{"oldTodos":[{"content":"geocode.py : centroïde de ville (médiane BD + Nominatim caché) et validation ≤40 km","status":"completed","activeForm":"Ajout de la validation par centroïde de ville"},{"content":"resolve() : retry AQ avec municipalité officielle + variantes Nominatim","status":"completed","activeForm":"Ajout des variantes de municipalité"},{"content":"run_batch : validation centroïde + rattrapage resolve() des échecs","status":"in_progress","activeForm":"Renforcement du géocodage batch"},{"content":"run_audit : détecter/corriger les fiches aux coordonnées incohérentes","status":"pending","activeForm":"Création de l'audit géocodage"},{"content":"Garde ingestion : rejeter les coords de connecteur contredisant la ville","status":"pending","activeForm":"Ajout de la garde à l'ingestion"},{"content":"db.py : colonne muni dans geocode_cache + CLI geocode-audit + watch","status":"pending","activeForm":"Migration BD et CLI"},{"content":"Corriger duproprio:1126225 + lancer l'audit + vérifier le site","status":"pending","activeForm":"Correction des fiches et vérification"},{"content":"pm2 restart + commit + push origin main","status":"pending","activeForm":"Redéploiement et commit"}],"newTodos":[{"content":"geocode.py : centroïde de ville (médiane BD + Nominatim caché) et validation ≤40 km","status":"completed","activeForm":"Ajout de la validation par centroïde de ville"},{"content":"resolve() : retry AQ avec municipalité officielle + variantes Nominatim","status":"completed","activeForm":"Ajout des variantes de municipalité"},{"content":"run_batch : validation centroïde + rattrapage resolve() des échecs","status":"completed","activeForm":"Renforcement du géocodage batch"},{"content":"run_audit : détecter/corriger les fiches aux coordonnées incohérentes","status":"completed","activeForm":"Création de l'audit géocodage"},{"content":"Garde ingestion : rejeter les coords de connecteur contredisant la ville","status":"completed","activeForm":"Ajout de la garde à l'ingestion"},{"content":"db.py : colonne muni dans geocode_cache + CLI geocode-audit + watch","status":"completed","activeForm":"Migration BD et CLI"},{"content":"Corriger duproprio:1126225 + lancer l'audit + vérifier le site","status":"in_progress","activeForm":"Correction des fiches et vérification"},{"content":"pm2 restart + commit + push origin main","status":"pending","activeForm":"Redéploiement et commit"}],"verificationNudgeNeeded":false}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY8kKXFceQM7FajAE7r","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01ScZ7jy1wMNGiEuBGDSSZw2","name":"Bash","input":{"command":"cd ~/apps/immo-ka && python3 -m py_compile immoka/geocode.py immoka/db.py immoka/ingest.py run.py && echo COMPILE-OK","description":"Vérifier la compilation des fichiers modifiés"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1941,"cache_read_input_tokens":103652,"cache_creation":{"ephemeral_5m_input_tokens":1941,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"e5cec7ba-4053-4f9b-ac37-88039a0c96eb"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01ScZ7jy1wMNGiEuBGDSSZw2","type":"tool_result","content":"COMPILE-OK","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"cb60286d-ca0f-452a-a5b7-bd5eda5989a8","timestamp":"2026-08-25T13:22:30.946Z","tool_use_result":{"stdout":"COMPILE-OK","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"60a72b40-36f4-4dea-a3f0-12d5ac804622","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePY9gpi212SD5kTjwenv","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01JPWYqyU7F6LdcmXg4Wy7DF","name":"Bash","input":{"command":"cd ~/apps/immo-ka && python3 -c \"\nfrom immoka import db, geocode\ncon = db.connect() # applique la migration muni\n# purge des entrées de cache douteuses/échouées de la rue des Perdrix à Jonquière\ncon.execute(\\\"DELETE FROM geocode_cache WHERE address IN ('4671 rue des perdrix','4667 rue des perdrix')\\\")\ncon.commit()\ngeo = geocode.Geocoder(con)\nprint('centroide ville:', geo.city_reference('Jonquiere Lac Kenogami'))\nprint('ville resolue :', geo.resolve_ville('Jonquiere Lac Kenogami'))\nprint('resolve 4671 :', geo.resolve('4671 Rue Des Perdrix', 'Jonquiere Lac Kenogami'))\nprint('resolve 4667 :', geo.resolve('4667 Rue Des Perdrix', 'Jonquiere Lac Kenogami'))\ncon.close()\"","description":"Tester resolve() sur le cas Perdrix/Jonquière"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":987,"cache_read_input_tokens":105593,"cache_creation":{"ephemeral_5m_input_tokens":987,"ephemeral_1h_input_tokens":0},"output_tokens":17,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"84b0af7b-d5e7-46d2-b4d6-488f2e7b359e"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01JPWYqyU7F6LdcmXg4Wy7DF","type":"tool_result","content":"centroide ville: (48.32646185119819, -71.31090790858877)\nville resolue : {'lat': 48.4192796, 'lng': -71.2476061, 'muni': 'Saguenay'}\nresolve 4671 : (48.311895748504, -71.302037494045)\nresolve 4667 : (48.312629701639, -71.301523715921)","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"9e10079e-4285-4550-af51-a521859b785d","timestamp":"2026-08-25T13:22:44.251Z","tool_use_result":{"stdout":"centroide ville: (48.32646185119819, -71.31090790858877)\nville resolue : {'lat': 48.4192796, 'lng': -71.2476061, 'muni': 'Saguenay'}\nresolve 4671 : (48.311895748504, -71.302037494045)\nresolve 4667 : (48.312629701639, -71.301523715921)","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"8e166b2d-a3f7-4106-8eab-aa66d3a0fd4d","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} 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{"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYAgLDRZH8oASPatCdE","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"CAIS2wMKqAEIERgCKkDQKTEfOfEOEdE3nOfO6EhVRm39fmLIn73nefC9jUez66L11fQ6Qbhi6Qrn3Ip+nCcj9xX8/xtix/L/T5PL4f/9Mg5jbGF1ZGUtZmFibGUtNTgBQgluYXJyYXRpb25aJDZmY2M4ZjgzLTFmOWMtNGQzMy1iYTA3LTRkNGRmMzdkNjdmNXIQqRe6IlAfDeGrOLHPwshiKIgBAagBr6621AawAQISDK47smv66woQXzNOCRoMgMmO128TYTYN2Y0HIjA+6XFNs0cjo4MXmF0cLsZX53xwO+UNaWKJYPTRoyWDIFPbObAiPCj17UBeOGgaXsMq3wE26IfAhdxo3nfc/O8z4Vy4smXsgiQcpcC+gVCp6S9oJOA+EjSLwLgagyajSd4aLYn+p5Zx14jqP/FEOIdgPKv9bqLA1OOitpMzwBgP5SVDxjgEFmPrWy9Rd7gq08NuQ4qoAUsIv3DRLY9hLUgRJUJ5fyWJfJbB4jIwwFVonLphJwMIg9F0Fe/qtAa8b7OW8mi1WhnaB19BNQksTAQb7r/x8BrNltsvrhiXa5lTQwfjYCRzMN0mysAoX00QrvZq4tq/MGpzwZoE/8klLErVr2Bu1qL0+XJzGwL2NwNIU0pmGAE="}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":550,"cache_read_input_tokens":106580,"cache_creation":{"ephemeral_5m_input_tokens":550,"ephemeral_1h_input_tokens":0},"output_tokens":6,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"874e1e0c-02e5-4483-9479-48da81b49405"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYAgLDRZH8oASPatCdE","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_011SYs7Ji3DtoQ8zjfqswpqU","name":"Bash","input":{"command":"cd ~/apps/immo-ka && python3 run.py geocode-audit 0 dry 2>&1 | tail -30","description":"Audit à blanc (cache seulement)","timeout":300000},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":550,"cache_read_input_tokens":106580,"cache_creation":{"ephemeral_5m_input_tokens":550,"ephemeral_1h_input_tokens":0},"output_tokens":6,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"917d4b19-fb4a-4595-99fd-03567d176755"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_011SYs7Ji3DtoQ8zjfqswpqU","type":"tool_result","content":"[immo-ka] audit: sutton:19513930 « 135 Rue Principale App 204, Chateauguay » à 368 km de sa ville\n[immo-ka] audit: remax_quebec:28107050 « 6869 Av. Royale, L'Ange-Gardien » à 364 km de sa ville\n[immo-ka] audit: remax_quebec:28138719 « Boul. Ste-Anne, L'Ange-Gardien » à 364 km de sa ville\n[immo-ka] audit: remax_quebec:14959988 « 6704 Boul. Ste-Anne, L'Ange-Gardien » à 364 km de sa ville\n[immo-ka] audit: remax_quebec:22852855 « 6658 - 6670 Av. Royale, L'Ange-Gardien » à 363 km de sa ville\n[immo-ka] audit: remax_quebec:15915631 « 6570 Boul. Ste-Anne app. 301, L'Ange-Gardien » à 363 km de sa ville\n[immo-ka] audit: remax_quebec:22980044 « 6e Rang O., Saint-Donat » à 509 km de sa ville\n[immo-ka] audit: remax_quebec:18269467 « 106 Av. Bérubé, Saint-Donat » à 512 km de sa ville\n[immo-ka] audit: remax_quebec:16433135 « 148 Ch. des Conquérants, Saint-Donat » à 512 km de sa ville\n[immo-ka] audit: remax_quebec:18712112 « 373 Rg St-Gérard E., Saint-Alexandre-de-Kamouraska » à 200 km de sa ville\n[immo-ka] audit: remax_quebec:20310176 « 128 Ch. Taché E., Saint-Cyprien » à 195 km de sa ville\n[immo-ka] audit: remax_quebec:16607738 « 19 Rue des Sommets, Saint-Séverin » à 115 km de sa ville\n[immo-ka] audit: remax_quebec:20334386 « 221 Rue Angéline Vachon, Saint-Séverin » à 115 km de sa ville\n[immo-ka] audit: remax_quebec:25795704 « 1327 3e Rang, Saint-Séverin » à 115 km de sa ville\n[immo-ka] audit: remax_quebec:20973866 « Rue Principale, Sainte-Claire » à 118 km de sa ville\n[immo-ka] audit: remax_quebec:21343569 « Rue Principale, Sainte-Claire » à 118 km de sa ville\n[immo-ka] audit: remax_quebec:10122251 « 710 Rue Principale, Sainte-Félicité » à 291 km de sa ville\n[immo-ka] audit: remax_quebec:17591945 « 698 Rue Principale, Sainte-Félicité » à 291 km de sa ville\n[immo-ka] audit: remax_quebec:18961477 « Rg Taché O., Sainte-Félicité » à 295 km de sa ville\n[immo-ka] audit: remax_quebec:20339472 « 167 Rue Principale, Sainte-Perpétue » à 219 km de sa ville\n[immo-ka] geocode-audit {'verifiees': 110574, 'incoherentes': 6255, 'villes_inconnues': 1953, 'corrigees': False}","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"f69e4bc6-cc87-4f12-a7ec-f557ea0a8cd3","timestamp":"2026-08-25T13:22:57.925Z","tool_use_result":{"stdout":"[immo-ka] audit: sutton:19513930 « 135 Rue Principale App 204, Chateauguay » à 368 km de sa ville\n[immo-ka] audit: remax_quebec:28107050 « 6869 Av. Royale, L'Ange-Gardien » à 364 km de sa ville\n[immo-ka] audit: remax_quebec:28138719 « Boul. Ste-Anne, L'Ange-Gardien » à 364 km de sa ville\n[immo-ka] audit: remax_quebec:14959988 « 6704 Boul. Ste-Anne, L'Ange-Gardien » à 364 km de sa ville\n[immo-ka] audit: remax_quebec:22852855 « 6658 - 6670 Av. Royale, L'Ange-Gardien » à 363 km de sa ville\n[immo-ka] audit: remax_quebec:15915631 « 6570 Boul. Ste-Anne app. 301, L'Ange-Gardien » à 363 km de sa ville\n[immo-ka] audit: remax_quebec:22980044 « 6e Rang O., Saint-Donat » à 509 km de sa ville\n[immo-ka] audit: remax_quebec:18269467 « 106 Av. Bérubé, Saint-Donat » à 512 km de sa ville\n[immo-ka] audit: remax_quebec:16433135 « 148 Ch. des Conquérants, Saint-Donat » à 512 km de sa ville\n[immo-ka] audit: remax_quebec:18712112 « 373 Rg St-Gérard E., Saint-Alexandre-de-Kamouraska » à 200 km de sa ville\n[immo-ka] audit: remax_quebec:20310176 « 128 Ch. Taché E., Saint-Cyprien » à 195 km de sa ville\n[immo-ka] audit: remax_quebec:16607738 « 19 Rue des Sommets, Saint-Séverin » à 115 km de sa ville\n[immo-ka] audit: remax_quebec:20334386 « 221 Rue Angéline Vachon, Saint-Séverin » à 115 km de sa ville\n[immo-ka] audit: remax_quebec:25795704 « 1327 3e Rang, Saint-Séverin » à 115 km de sa ville\n[immo-ka] audit: remax_quebec:20973866 « Rue Principale, Sainte-Claire » à 118 km de sa ville\n[immo-ka] audit: remax_quebec:21343569 « Rue Principale, Sainte-Claire » à 118 km de sa ville\n[immo-ka] audit: remax_quebec:10122251 « 710 Rue Principale, Sainte-Félicité » à 291 km de sa ville\n[immo-ka] audit: remax_quebec:17591945 « 698 Rue Principale, Sainte-Félicité » à 291 km de sa ville\n[immo-ka] audit: remax_quebec:18961477 « Rg Taché O., Sainte-Félicité » à 295 km de sa ville\n[immo-ka] audit: remax_quebec:20339472 « 167 Rue Principale, Sainte-Perpétue » à 219 km de sa ville\n[immo-ka] geocode-audit {'verifiees': 110574, 'incoherentes': 6255, 'villes_inconnues': 1953, 'corrigees': False}","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"e9331e6e-03c2-4960-81ff-354bea2dda34","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYBg1PwGJiqNPUggA11","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"CAISpUoKpwEIERgCKkC9Rdl9uI5v18ZeaEMBjALDbItTXn5YOB8kmwRkoqwXd4UvSk1F2KAuCUYMEMm6nukXaepe7MNRjjtGTHtLL/uTMg5jbGF1ZGUtZmFibGUtNTgBQgh0aGlua2luZ1okNmZjYzhmODMtMWY5Yy00ZDMzLWJhMDctNGQ0ZGYzN2Q2N2Y1chCpF7oiUB8N4as4sc/CyGIoiAEBqAHxrrbUBrABAhIMvhUtANVGR4WcUgDjGgx/WE4+LgAyNGpgIGYiMFR8WE7lbji6UQcwMTxQPdkQqUw8BgLmwaZJFg/2Op4AwSs1a5ZF83V9GU81oB7F0CqqSK/Wtp5mAy16uiT1gbrMV5NoSvcbedL/apEg/GUhasmrulM4yHFqAxopCPpL9kS0JJW+Uwwy6cIicT3KeKAEoQwhofbwWm+gIiq5t+bxiMzVvfN9R24xf3LchVDVhqyJ7RcUMOqUVHt8Qk+CVxlrXuGfJmiwQF8Zhsgb/4X+Bk/kZ9Q2r2Ugzq6+PDLOxcR8hcVTD2IuzOhgQXo/87PV1FEVb/WrfWVb1+AtN8/rdRr/VGR/pVza1IRfg9M/Jcqut+mVIBP1ZCMFdG2MRG2rkdGwVDKTBdUxGruNlpsjBn6XnTYAinLT4JXXJb05VDJ73u8KhvJB4B7e6dr/QBxLThfCNPkzMdKUo+YCX4Ey5e/qFMsaOTU0iudPZoO0k9XLpP0ApZu8tu/Op55pgv2TsgnZMSm2lhaQ8yylZLpoOe2EItv4cMZcHO1AYflmgFNjQw8gLHsqtqDRp5qEtHiNo1Em5qGLpsAywPGTsStKD0riO2u9qb1CWFONXogv1xb7NS51CrdJrE2WBW60rpl8UKiTE9h8qmzq2HuAExd3sRnOzWhEEue95T1mMU7NFUQdkbPjEjs7WfMn1jBJ5xkJ37lkuvmOxIwamE3ALZtPgPTUIKmzJAhaXynU4QBo/VDjm2W/nSylUyThcvElYOAjHv696dpqkBQlygfZ0EC7Fm2aJ+UGo8QiccWsWtuF/O28V7sMY/sD7lF+bYEUAghBUg+vSE9kSwab+xUjrYBra0oCqyIRNtIj55sVxhvyXyEeDpxuRbhEG43PTTpedBRiDvtVi0F9bD4a9DMdNQCVSvfbrdpIekrCVq4/mLc280TdASIeiTyDeuVP2Itq+WhLyxSOEbYqei08tKVaM43j9ep0JZPfKyOAalaEQwz+cKxCZ01ZEG1SKuP2r1U6AACUclfdSlm1AhjKsq+VZ+D87674trszFIDXq38BY1SooBgMwNugzSox70aiwNp9aHkMAPhm9PTQPgIidyp+x08blxHx3st3b17jNPFKAJy2pXF1w+tRQSo1UIw1EJ4luaDyMFTqGPcewdM+uG1AvHgL7XOlC6JxYyJTFYvhzdYUsuyAY5yVo6Uoj8RW8FHFkPtAUkyoW7P1Jyp0KECbH0CV39s4nOQoCyGeTcSCGFrw0WfDYtk1uOMWKZfJLg8nYYLqz0rVEwKa/bGVSPjnJEZyYMmbZQMiR/7kTeUJMHKw5u+fjtahJtewuUIB8AHQ6mbFkuNUjy9QTZkg7sT925HfuWpAHPidEbAcDFHUP5ugMULxuzJsqs4DPAyh4uaWmn6fhCvzhcVt1KZ8ZJdbjXahOY2wcA/IrEE9ZL1y5UD3g+eP4TyUFTpbS92/7yXrfG+iYI1B93FUyx19IbZzyBhElE9MRl21pEMEDgwFRa0oWoQgUuM2/i8i0vOwHZmndCckt5dv7SpnTYKkk5T9zPS68NpOeYESNNhSdv2BwAMTgD7s6WNdr7IEVz1WJCb9yDdnKYNHLcbt/vpmM9tiZQOUfUp/PsYx6rHRnzBqzuuypBflqaLQG3a5hkSbo39CPHg4WYB71KlOH4g8A8f8vqeakIIV/WZn2m4wvLrIgTAN+M+8cvi/uXzTZvEddph3tp1Ks5jLew4NGR4Sg1ZshbMndoqMqvqv2bn3WEOHoBXaZXdLpHYJbBz4lywW88yqh+xTIKcibckeo3hD/bIbggWLXr+tT9zf5hGyTs5zxfMDPcKAfVhEJsocB7Hl9MLiyJVu1FRS9kS9JyXy4D9WfSw6dkGf01q2MLhdFRkkoahLUquH5LPxDe+hyFFECkRi8aoqjH1l77TX1brl+bMiJX4CygAl1w8hmdIKbr90b74vzAsTJUmrz81bgh2MLRwla1Lbd6IbDn8IiFEwvSZ5PcqyGVqsz8bVu1MaKj+4DmBYdIga1yugQTqNRdpTlbbo2XxMhmHnZszXlOfPJPxALXVjzLOZeMoP8jJs5hz4y/6dNrr67kgpnTP+oRbiK4nlnJuj8+FkoRhkwJiCrglIN9I9dFBuXIZbPXojSaeacoLpRegIELKz2KqpFe2qwWTCb5YHSbk3IYt8Ji/PTLBu91AKB3qgCPCa8U6ntZd3rBo8Racdh5PrNesz/MlG4zAPzCjGy7PU1Irl70EyR8W0kCxODiXspqw3T6Uq4sDS3RZr3DcuyT9AASDr4HBDLbXdhP7a5pqh75hFvjfp/0iRUxtiv4KjyPgd3AQMqqumTnlyIDfybJVw03/EGl4jvCs8lQwkRA0ykEdfIMkPjEKZkaHsH8l6nd3SRwZRawYnOOwzhjap3rOOvHA5+Lbn5BB5eWqKfoJNI95FjxbQEl10/cXi0GyCYHN1ImCUXf4SOVKCXgUfE5x6ZnoJCX4GL7eqZg4z8An/g+Gyyz7uTsNIuTvmhGRlupcSBF5x6sqmYaw912BYYaw4mAXQ8Z8T/WYMnd+9Dn3r7sszcaqO2AwtqWimrz/abfcv89JtN1QopX2+2jnUhEkXJTgGZJDkvAQ0zkiK0xU1YWGct6atyak97WNR95vnPbjzo5lw5MRWKO3kXHsxC66YYCNtRYbxhJykfnxNBUd8uL5Yaxwg4sHTLXFwWaPXI2/PoAoFohQJlC/yrdsFITt+gmZ8jlr0Ivwgc+k4DQdc8vRNfBE6O0448BpPXU33rNpp22rvKzCZCpYCHZeJqcQVVPC137O5xhbazSELyUTIDq5gHQWfZHj1AJQlBxxXC+laLn/OxZIBksQ2Pjztot2rAPUONSoFQ0CVLz1dcz1txL/WC9ZcG2s64qZO6uvRgg1UPZkIi533CbmQ24Y3dtHKOAiHjV9Xtuau9ZBj9OSevK2k7o5eTOc3IXckp4PF8ldCDU5VqHT5M2K2GGQfcdqg4o5e2bNLW5z25/VAsBUIcS5IUV5r2tsWmDV7tmKi21GeIw9ZO4orpR2Wtqrx36tE1oz1mErGKsiQvCVI8lpLv8l8TJ67Ls4GuI7qetXx1LS3pfhN/91eOGl4vkPXbcAIUJJkQldt+DdDGp9buMipojZjrPGGHgB5QFdtalEbVvn94HN4XWNkQM2zOgrQvsssmVRKHkDYu4jwlJj0+oXlMXzJVePqwtoFlUfuxS5nPZq8hjR95ED/81gP8ZVUB96xxk4n+TfrtNNqkhC5Bx1MJm/A3W94CCWnBU+15BuWnkruAL2sUqjAtBka/K6l6CjAUEexbusKNmk+Cn59fXSh+7avcovkV7hYaw7///6V8pu/m93mmENjoZOKEEqOlwvCCfVKTCRnFFi7qpYst6wykEPKKYL+fixG9eSnG187Cbe1vSKvw9M1H6S7u8/xTtdwGErjkLpNmamd9Ei5muL0ChEg65psu1hLo56IG0axfx3lPYZoVyrCrnKbC10Xk45mA2NaWb+kLhou2xeikyK3QbUW2O/rg0w37VPUWbInv7Knspb15Pvwne0cZPvQ9v22Fcklk+SDV9WpQNZPyzxsUHxUD38nh9xG1o3weBM51kJToOOtfQPK/LonUONMIqPXj14EQSjGyOrOg41cxOVT8CQHVkG6ftQlwqTzfYVGo9vB/s6CD4VELRZ/qat2hqDkckkriMLxB/zA28Ad5iyNM7TRvLS9MleA0MaH4GBKNWaPbi1fxKM1CWziQcIoPqjmKgFuogOazvun77+lWGGY+adtxUyE3pykn9YHgnizNsQ7ZkQt2iC4IwJEZPuHOPNJnuEqbCqcrozUTbIazeU5KT3lynDDQZgmdKmar/X1oulYggoYZ/yaWMqEczmcmbfCp8zpZu7MqXyUTyVqTs+TOEfAvjH7w8mozNeQc7snF9fsxOcb9nrnyprxDzfW0/oZrLHkDLgizNgccaKN3pAdV9avq7tKF9kBGXgv4gaQq2Jys2dd/u6NcOXtrUgcByNEcrPblO1z0+1jWzWygeILMMAWCYlq2pIXM49sHcHc0+avZNB0RecdNEtL2HVl7WuAJe3DqKpgA+8PQipR9iRUKU1OSCf11z09rbZTb6DJpHDR3xnFcximl7sJF+aHNrbZ3fWMrFjbg6/Ou5Mu58VfC+IMrpVGiVFnV45ciRZBTRNnw2xR955RD5wtywqTIGWjuX2VWAxmhCqmAPJPBFJmZ9YPbaOa6ibDgwFA67Yia4W78VOn4q1+vA+52U9O6kE2Dlk8IK8du9btdpaG0h2Gio/8aFhtVqN6w7qNfNUERtBx3w8N0vf4aEqeubJyz1360yrsWxaInyOgS4higkL1J5fQ85MmlLsqjKTvq8SvOnDARz2PDGt2ySz1AYF/ytawrSRaQrltFMAxwG4fISwMJkqivH4fM7j2DNon+m2xnN8UOSdobACN70SeLDetjWEAr1GHs5nO/TV8+MWxcvrmwV4/fR9j3phlzUvNRHUghQQ/AbAlN5D6JFFiuU1Wu73EsKVS9mteAvOtsv/qLjymWxsZgz/xm6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homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).\n# ⚠ Le Québec compte de nombreuses municipalités HOMONYMES (deux L'Ange-Gardien,\n# deux Saint-Donat, deux Sainte-Félicité…) : la référence n'est donc jamais un\n# centroïde unique mais un ENSEMBLE de grappes de fiches (chaque homonyme garde\n# la sienne) + le point Nominatim de la ville.\nVILLE_RADIUS_KM = 40.0\nCLUSTER_MIN = 3 # une grappe de fiches devient une référence de confiance dès n >= 3"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1658,"cache_read_input_tokens":107130,"cache_creation":{"ephemeral_5m_input_tokens":1658,"ephemeral_1h_input_tokens":0},"output_tokens":6,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"276dcd72-8cd0-4b73-a4c4-36d8f9fd400a"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01VWHNJSaZw3Y2Zp8TSZCTSJ","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"c14d0183-9c2a-452a-84ed-1060eca9d980","timestamp":"2026-08-25T13:24:07.432Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","oldString":"# Validation « rigoureuse » : distance max entre un résultat de géocodage et le\n# centroïde de la ville annoncée. 40 km tolère les grandes municipalités\n# fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues\n# homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).\nVILLE_RADIUS_KM = 40.0\nVILLE_MIN_SAMPLES = 5 # médiane de fiches : min d'échantillons pour être fiable","newString":"# Validation « rigoureuse » : distance max entre un résultat de géocodage et une\n# référence de la ville annoncée. 40 km tolère les grandes municipalités\n# fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues\n# homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).\n# ⚠ Le Québec compte de nombreuses municipalités HOMONYMES (deux L'Ange-Gardien,\n# deux Saint-Donat, deux Sainte-Félicité…) : la référence n'est donc jamais un\n# centroïde unique mais un ENSEMBLE de grappes de fiches (chaque homonyme garde\n# la sienne) + le point Nominatim de la ville.\nVILLE_RADIUS_KM = 40.0\nCLUSTER_MIN = 3 # une grappe de fiches devient une référence de confiance dès n >= 3","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)\n# - cache persistant (table geocode_cache) : une adresse n'est géocodée\n# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce\n# - politesse : 1 requête/seconde max, User-Agent identifiable\n# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# - rigueur : chaque résultat est validé contre le CENTROÏDE de la ville\n# annoncée (médiane des fiches déjà géocodées, sinon Nominatim, en cache) —\n# à plus de VILLE_RADIUS_KM du centroïde, le candidat est rejeté. Corrige\n# la classe de bug « rue homonyme dans une autre ville » (ex. rue des\n# Perdrix de Jonquière géocodée à Saint-Augustin).\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport math\nimport sqlite3\nimport statistics\n\nimport re\nimport time\n\nimport requests\n\nfrom . import db\nfrom .normalize import strip_accents\n\nNOMINATIM_URL = \"https://nominatim.openstreetmap.org/search\"\n# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre\n# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)\nAQ_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/findAddressCandidates\")\nAQ_MIN_SCORE = 75\n# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête\n# User-Agent contient des accents (latin-1)\nUSER_AGENT = \"ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)\"\nREQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s\nREQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte\nRETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours\n\n# Bounding boxes (lat_min, lat_max, lng_min, lng_max)\n_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord\n# et la Gaspésie (expansion provinciale) — même boîte que schema.finalize()\n_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n\n_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n# Validation « rigoureuse » : distance max entre un résultat de géocodage et le\n# centroïde de la ville annoncée. 40 km tolère les grandes municipalités\n# fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues\n# homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).\nVILLE_RADIUS_KM = 40.0\nVILLE_MIN_SAMPLES = 5 # médiane de fiches : min d'échantillons pour être fiable\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n\n\ndef _dist_km(lat1: float, lng1: float, lat2: float, lng2: float) -> float:\n \"\"\"Distance haversine en kilomètres.\"\"\"\n p1, p2 = math.radians(lat1), math.radians(lat2)\n a = (math.sin((p2 - p1) / 2) ** 2\n + math.cos(p1) * math.cos(p2) * math.sin(math.radians(lng2 - lng1) / 2) ** 2)\n return 2 * 6371.0 * math.asin(math.sqrt(a))\n\n\ndef norm_key(address: str) -> str:\n \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\"\n s = strip_accents((address or \"\").lower())\n s = re.sub(r\"\\b(?:app?t?|appartement|unite|suite|#)\\.?\\s*[\\w-]+\\b\", \" \", s)\n s = re.sub(r\"[^a-z0-9]+\", \" \", s)\n return re.sub(r\"\\s+\", \" \", s).strip()\n\n\nclass Geocoder:\n def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0\n self._villes: dict[str, dict | None] = {} # norm(ville) -> {lat,lng,muni}\n self._med: dict[str, tuple] | None = None # norm(ville) -> (lat,lng,n)\n self.ville_api_calls = 0 # requêtes Nominatim « ville »\n\n @staticmethod\n def _clean(address: str) -> str:\n \"\"\"Nettoyages qui aident Nominatim sur les adresses québécoises.\"\"\"\n s = address.strip()\n # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique\n s = re.sub(r\"^(\\d+)-(\\d+)\\s\", r\"\\2 \", s)\n # « 6275 et 6375 boulevard X » -> premier civique\n s = re.sub(r\"^(\\d+)\\s+et\\s+\\d+\\s\", r\"\\1 \", s)\n # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu\n s = re.sub(r\"montr[ée]al\\s*-\\s*\", \"\", s, flags=re.I)\n # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau\n s = re.sub(r\",?\\s*(?:bureau|suite|local|app\\.?|apt\\.?)\\s*[\\w-]+\\b\", \"\", s, flags=re.I)\n # « Vanier (Québec) » -> « Vanier, Québec »\n s = re.sub(r\"\\s*\\((qu[ée]bec)\\)\", r\", \\1\", s, flags=re.I)\n # abréviations cardinales : « Rue Salaberry O » -> « Ouest »\n s = re.sub(r\"\\bO\\.?(?=,|\\s*$)\", \"Ouest\", s)\n s = re.sub(r\"\\bE\\.?(?=,|\\s*$)\", \"Est\", s)\n return s\n\n def _build_query(self, address: str, city: str) -> str:\n q = self._clean(address)\n key = strip_accents(q.lower())\n if city and strip_accents(city.lower()) not in key:\n q += f\", {city}\"\n if \"quebec\" not in strip_accents(q.lower()) and \"qc\" not in q.lower():\n q += \", Québec\"\n return q + \", Canada\"\n\n def _query_nominatim(self, params: dict) -> tuple[float, float] | None:\n \"\"\"Une requête Nominatim, throttlée.\"\"\"\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"format\": \"jsonv2\", \"limit\": 1, \"countrycodes\": \"ca\", **params,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None\n if not hits:\n return None\n try:\n return float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n except (KeyError, ValueError):\n return None\n\n def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).\n\n Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE\n pour éviter les correspondances approximatives sur une autre rue.\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"Québec\").strip()\n wait = REQUEST_DELAY_AQ - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(AQ_URL, params={\n \"SingleLine\": f\"{premier}, {ville}\",\n \"f\": \"json\", \"outSR\": 4326, \"maxLocations\": 1,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n cands = resp.json().get(\"candidates\") or []\n except Exception:\n self._last = time.time()\n return None\n if not cands or cands[0].get(\"score\", 0) < AQ_MIN_SCORE:\n return None\n loc = cands[0].get(\"location\") or {}\n try:\n return float(loc[\"y\"]), float(loc[\"x\"])\n except (KeyError, ValueError):\n return None\n\n def _attempts(self, address: str, city: str, muni: str | None = None) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) idem avec la municipalité OFFICIELLE (« Saguenay ») quand la ville\n annoncée est un secteur (« Jonquière (Lac-Kénogami) ») inconnu des API\n 3) recherche libre complète\n 4) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n villes = [ville]\n # premier mot de la ville (« Jonquiere Lac Kenogami » -> « Jonquiere »)\n if \" \" in ville:\n villes.append(ville.split(\" \")[0])\n if muni and norm_key(muni) not in {norm_key(v) for v in villes}:\n villes.append(muni)\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n # ----- centroïde de ville (validation rigoureuse) ------------------------\n def _medians(self) -> dict[str, tuple]:\n \"\"\"Centroïde (médiane lat/lng) par ville, depuis les fiches déjà\n géocodées — gratuit, robuste aux erreurs isolées dès n >= 5.\"\"\"\n if self._med is None:\n acc: dict[str, list] = {}\n for r in self.con.execute(\n \"\"\"SELECT city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\"):\n acc.setdefault(norm_key(r[\"city\"]), []).append((r[\"lat\"], r[\"lng\"]))\n self._med = {k: (statistics.median(p[0] for p in v),\n statistics.median(p[1] for p in v), len(v))\n for k, v in acc.items()}\n return self._med\n\n def resolve_ville(self, city: str, allow_api: bool = True) -> dict | None:\n \"\"\"Ville -> {lat, lng, muni} (muni = municipalité officielle, ex.\n « Jonquière (Lac-Kénogami) » -> Saguenay). Cache : geocode_cache,\n clé « ville: ». None si irrésoluble.\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n if k in self._villes:\n return self._villes[k]\n key = \"ville:\" + k\n row = self.con.execute(\n \"SELECT lat, lng, muni, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n v = {\"lat\": row[\"lat\"], \"lng\": row[\"lng\"], \"muni\": row[\"muni\"]}\n self._villes[k] = v\n return v\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n self._villes[k] = None\n return None\n if not allow_api:\n return None # pas de mémoire : on réessaiera quand l'API sera permise\n self.ville_api_calls += 1\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n v = None\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"q\": f\"{city}, Québec, Canada\", \"format\": \"jsonv2\", \"limit\": 1,\n \"countrycodes\": \"ca\", \"addressdetails\": 1}, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None # erreur réseau : ne pas cacher un échec définitif\n if hits:\n try:\n lat, lng = float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n if _in_bbox(lat, lng, _BBOX_SUD_QC):\n a = hits[0].get(\"address\") or {}\n muni = (a.get(\"city\") or a.get(\"town\") or a.get(\"village\")\n or a.get(\"municipality\"))\n v = {\"lat\": lat, \"lng\": lng, \"muni\": muni}\n except (KeyError, ValueError, TypeError):\n v = None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, muni, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, muni=excluded.muni,\"\n \" provider=excluded.provider, failed=excluded.failed, ts=excluded.ts\",\n (key, v[\"lat\"] if v else None, v[\"lng\"] if v else None,\n v[\"muni\"] if v else None, \"ville_nominatim\", 0 if v else 1, time.time()))\n self.con.commit()\n self._villes[k] = v\n return v\n\n def city_reference(self, city: str, allow_api: bool = True) -> tuple[float, float] | None:\n \"\"\"Centroïde de référence d'une ville : médiane des fiches (n >= 5),\n sinon résolution Nominatim. None si inconnue (-> validation bbox seule).\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n med = self._medians().get(k)\n if med and med[2] >= VILLE_MIN_SAMPLES:\n return (med[0], med[1])\n v = self.resolve_ville(city, allow_api=allow_api)\n return (v[\"lat\"], v[\"lng\"]) if v else None\n\n def coords_ok(self, c: tuple[float, float] | None, city: str,\n ref: tuple[float, float] | None = None) -> bool:\n \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM du\n centroïde de la ville annoncée (quand il est connu).\"\"\"\n if c is None or not _in_bbox(*c, _bbox_for(city)):\n return False\n if ref is None:\n ref = self.city_reference(city)\n return ref is None or _dist_km(c[0], c[1], ref[0], ref[1]) <= VILLE_RADIUS_KM\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis AQ/Nominatim. None si introuvable.\n\n Rigueur : chaque candidat doit être cohérent avec la ville annoncée\n (centroïde <= VILLE_RADIUS_KM). Si la ville annoncée est un secteur\n inconnu d'Adresses Québec, on réessaie avec la municipalité officielle.\n \"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n ref = self.city_reference(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if self.coords_ok(c, city, ref):\n coords = c\n muni = None\n if coords is None:\n # ville annoncée = secteur (« Jonquière (Lac-Kénogami) ») ? AQ ne\n # connaît que les municipalités officielles -> retenter avec elle.\n v = self.resolve_ville(city)\n muni = (v or {}).get(\"muni\")\n if muni and norm_key(muni) != norm_key(city or \"\"):\n c = self._query_adresses_quebec(address, muni)\n if self.coords_ok(c, city, ref):\n coords, provider = c, \"adresses_quebec_muni\"\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city, muni):\n c = self._query_nominatim(params)\n if self.coords_ok(c, city, ref):\n coords = c\n break\n ok = coords is not None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?)\"\n \" ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,\"\n \" lng=excluded.lng, provider=excluded.provider,\"\n \" failed=excluded.failed, ts=excluded.ts\",\n (key, coords[0] if ok else None, coords[1] if ok else None,\n provider, 0 if ok else 1, time.time()))\n self.con.commit()\n return coords if ok else None\n\n\ndef run(limit: int | None = None) -> dict:\n \"\"\"Géocode les annonces actives sans coordonnées, par adresse unique.\n\n `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de\n cache sont gratuits et toujours appliqués).\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0\n ORDER BY address\"\"\").fetchall()\n\n # regrouper par immeuble (adresse normalisée)\n groupes: dict[str, list] = {}\n for r in rows:\n groupes.setdefault(norm_key(r[\"address\"]), []).append(r)\n\n done = failed = requests_made = 0\n for key, members in groupes.items():\n if not key:\n continue\n cached = con.execute(\n \"SELECT failed FROM geocode_cache WHERE address=?\", (key,)).fetchone()\n if cached is None:\n if limit is not None and requests_made >= limit:\n continue\n requests_made += 1\n try:\n coords = geo.resolve(members[0][\"address\"], members[0][\"city\"])\n if coords:\n for r in members:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], r[\"uid\"]))\n done += len(members)\n else:\n # introuvable/hors zone : flag ; jamais de coordonnées bidon\n for r in members:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\",\n (r[\"uid\"],))\n failed += len(members)\n con.commit()\n except sqlite3.OperationalError:\n # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,\n # elle sera reprise au prochain passage — jamais crasher tout le run.\n try:\n con.rollback()\n except sqlite3.Error:\n pass\n time.sleep(1.0)\n continue\n\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed,\n \"unique_addresses\": len(groupes), \"api_requests\": requests_made}\n print(f\"[immo-ka] geocode {stats}\")\n return stats\n\n\nAQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200\nRESCUE_MAX = 150 # rattrapages resolve() max par passe (Nominatim = 1 req/s)\n\n\ndef strip_bad_source_coords(con, listings) -> int:\n \"\"\"Garde d'ingestion : annule les lat/lng fournis par un connecteur quand\n ils contredisent la ville annoncée (> VILLE_RADIUS_KM du centroïde connu).\n Cache seulement (médianes + villes déjà résolues) : aucun appel réseau,\n la synchronisation reste rapide. Retourne le nombre de paires annulées.\"\"\"\n geo = Geocoder(con)\n n = 0\n for lst in listings:\n if lst.lat is None or lst.lng is None or not (lst.city or \"\").strip():\n continue\n ref = geo.city_reference(lst.city, allow_api=False)\n if ref and _dist_km(lst.lat, lst.lng, ref[0], ref[1]) > VILLE_RADIUS_KM:\n lst.lat = lst.lng = None\n n += 1\n return n\n\n\ndef run_batch(limit: int | None = None) -> dict:\n \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de\n milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim).\"\"\"\n con = db.connect()\n geo = Geocoder(con) # pour réutiliser _clean / bbox\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0 ORDER BY address\"\"\").fetchall()\n # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache\n uniq: dict[str, dict] = {}\n for r in rows:\n k = norm_key(r[\"address\"])\n if not k or len(k) < 6:\n continue\n u = uniq.setdefault(k, {\"address\": r[\"address\"], \"city\": r[\"city\"],\n \"members\": []})\n u[\"members\"].append(r[\"uid\"])\n pending = []\n for k, u in uniq.items():\n c = con.execute(\"SELECT lat,lng,failed FROM geocode_cache WHERE address=?\",\n (k,)).fetchone()\n if c is not None and not c[\"failed\"]: # déjà résolu : appliquer direct\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (c[\"lat\"], c[\"lng\"], uid))\n continue\n if c is not None and c[\"failed\"]:\n continue\n pending.append((k, u))\n con.commit()\n if limit is not None:\n pending = pending[:limit]\n\n session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n rescue: list[tuple[str, dict]] = [] # échecs du lot -> resolve() individuel\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n # bbox + cohérence avec le centroïde de la ville annoncée\n if geo.coords_ok(cand, u[\"city\"]):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n con.commit()\n else:\n # pas de verdict tout de suite : resolve() réessaiera avec la\n # municipalité officielle + Nominatim (borné par RESCUE_MAX)\n rescue.append((k, u))\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, à rattraper {len(rescue)})\")\n\n # Rattrapage 1-par-1 des échecs du lot : variantes de municipalité (AQ) puis\n # Nominatim, validées par centroïde. resolve() écrit lui-même le verdict au\n # cache (succès ou échec 30 j) ; au-delà de RESCUE_MAX, on laisse les fiches\n # intactes (ni cache ni flag) -> reprises aux prochains passages.\n rescued = 0\n for k, u in rescue[:RESCUE_MAX]:\n try:\n coords = geo.resolve(u[\"address\"], u[\"city\"])\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n done += len(u[\"members\"])\n rescued += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n con.close()\n stats = {\"geocoded\": done, \"rescued\": rescued, \"failed\": failed,\n \"deferred\": max(0, len(rescue) - RESCUE_MAX),\n \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats\n\n\ndef run_audit(nominatim_budget: int | None = None, apply: bool = True) -> dict:\n \"\"\"Audit de cohérence géographique des fiches DÉJÀ géocodées.\n\n Détecte les coordonnées à plus de VILLE_RADIUS_KM du centroïde de leur\n ville (rue homonyme d'une autre région, geo erroné fourni par la source…),\n puis les remet en file de géocodage : lat/lng annulés, geocode_failed remis\n à 0, entrée de cache purgée. `nominatim_budget` borne les résolutions de\n villes inconnues (1 req/s) ; None = illimité. `apply=False` = rapport seul.\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\").fetchall()\n flagged, villes_inconnues = [], 0\n for r in rows:\n allow = nominatim_budget is None or geo.ville_api_calls < nominatim_budget\n ref = geo.city_reference(r[\"city\"], allow_api=allow)\n if ref is None:\n villes_inconnues += 1\n continue\n d = _dist_km(r[\"lat\"], r[\"lng\"], ref[0], ref[1])\n if d > VILLE_RADIUS_KM:\n flagged.append((r, d))\n if apply:\n for r, d in flagged:\n con.execute(\"DELETE FROM geocode_cache WHERE address=?\",\n (norm_key(r[\"address\"]),))\n con.execute(\"\"\"UPDATE listings SET lat=NULL, lng=NULL,\n geocode_failed=0 WHERE uid=?\"\"\", (r[\"uid\"],))\n con.commit()\n for r, d in flagged[:20]:\n print(f\"[immo-ka] audit: {r['uid']} « {r['address']}, {r['city']} » \"\n f\"à {d:.0f} km de sa ville\")\n con.close()\n stats = {\"verifiees\": len(rows), \"incoherentes\": len(flagged),\n \"villes_inconnues\": villes_inconnues, \"corrigees\": apply}\n print(f\"[immo-ka] geocode-audit {stats}\")\n return stats\n","structuredPatch":[{"oldStart":51,"oldLines":12,"newStart":51,"newLines":16,"lines":[" _VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\","," \"l'ancienne-lorette\", \"ancienne-lorette\"}"," ","-# Validation « rigoureuse » : distance max entre un résultat de géocodage et le","-# centroïde de la ville annoncée. 40 km tolère les grandes municipalités","+# Validation « rigoureuse » : distance max entre un résultat de géocodage et une","+# référence de la ville annoncée. 40 km tolère les grandes municipalités"," # fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues"," # homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).","+# ⚠ Le Québec compte de nombreuses municipalités HOMONYMES (deux L'Ange-Gardien,","+# deux Saint-Donat, deux Sainte-Félicité…) : la référence n'est donc jamais un","+# centroïde unique mais un ENSEMBLE de grappes de fiches (chaque homonyme garde","+# la sienne) + le point Nominatim de la ville."," VILLE_RADIUS_KM = 40.0","-VILLE_MIN_SAMPLES = 5 # médiane de fiches : min d'échantillons pour être fiable","+CLUSTER_MIN = 3 # une grappe de fiches devient une référence de confiance dès n >= 3"," "," "," def _bbox_for(city: str) -> tuple[float, float, float, float]:"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"11cb8129-d3f1-4a74-b0c7-056156aa03b3","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYGowH5cxsxJdBuDxwW","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_012WdswRkNR1gd5veVFKKBmi","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","old_string":" # ----- centroïde de ville (validation rigoureuse) ------------------------\n def _medians(self) -> dict[str, tuple]:\n \"\"\"Centroïde (médiane lat/lng) par ville, depuis les fiches déjà\n géocodées — gratuit, robuste aux erreurs isolées dès n >= 5.\"\"\"\n if self._med is None:\n acc: dict[str, list] = {}\n for r in self.con.execute(\n \"\"\"SELECT city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\"):\n acc.setdefault(norm_key(r[\"city\"]), []).append((r[\"lat\"], r[\"lng\"]))\n self._med = {k: (statistics.median(p[0] for p in v),\n statistics.median(p[1] for p in v), len(v))\n for k, v in acc.items()}\n return self._med","new_string":" # ----- références de ville (validation rigoureuse) -----------------------\n def _clusters(self) -> dict[str, list[tuple]]:\n \"\"\"Grappes de coordonnées par ville, depuis les fiches déjà géocodées\n (regroupement glouton, rayon VILLE_RADIUS_KM). Chaque grappe :\n (lat médiane, lng médiane, n). Les municipalités homonymes produisent\n naturellement une grappe chacune — aucune n'écrase l'autre.\"\"\"\n if self._med is None:\n acc: dict[str, list] = {}\n for r in self.con.execute(\n \"\"\"SELECT city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\"):\n acc.setdefault(norm_key(r[\"city\"]), []).append((r[\"lat\"], r[\"lng\"]))\n out: dict[str, list[tuple]] = {}\n for k, pts in acc.items():\n clusters: list[list] = [] # [ [lat_c, lng_c, [points]] ]\n for lat, lng in pts:\n for cl in clusters:\n if _dist_km(lat, lng, cl[0], cl[1]) <= VILLE_RADIUS_KM:\n cl[2].append((lat, lng))\n cl[0] = statistics.median(p[0] for p in cl[2])\n cl[1] = statistics.median(p[1] for p in cl[2])\n break\n else:\n clusters.append([lat, lng, [(lat, lng)]])\n out[k] = [(cl[0], cl[1], len(cl[2])) for cl in clusters]\n self._med = out\n return self._med"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":4440,"cache_read_input_tokens":108788,"cache_creation":{"ephemeral_5m_input_tokens":4440,"ephemeral_1h_input_tokens":0},"output_tokens":15,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"9cacde7a-1be1-4db3-8c52-cefb12fbbcc1"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_012WdswRkNR1gd5veVFKKBmi","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"9648c587-6b46-4bfc-9d87-bf79b8f76610","timestamp":"2026-08-25T13:24:19.561Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","oldString":" # ----- centroïde de ville (validation rigoureuse) ------------------------\n def _medians(self) -> dict[str, tuple]:\n \"\"\"Centroïde (médiane lat/lng) par ville, depuis les fiches déjà\n géocodées — gratuit, robuste aux erreurs isolées dès n >= 5.\"\"\"\n if self._med is None:\n acc: dict[str, list] = {}\n for r in self.con.execute(\n \"\"\"SELECT city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\"):\n acc.setdefault(norm_key(r[\"city\"]), []).append((r[\"lat\"], r[\"lng\"]))\n self._med = {k: (statistics.median(p[0] for p in v),\n statistics.median(p[1] for p in v), len(v))\n for k, v in acc.items()}\n return self._med","newString":" # ----- références de ville (validation rigoureuse) -----------------------\n def _clusters(self) -> dict[str, list[tuple]]:\n \"\"\"Grappes de coordonnées par ville, depuis les fiches déjà géocodées\n (regroupement glouton, rayon VILLE_RADIUS_KM). Chaque grappe :\n (lat médiane, lng médiane, n). Les municipalités homonymes produisent\n naturellement une grappe chacune — aucune n'écrase l'autre.\"\"\"\n if self._med is None:\n acc: dict[str, list] = {}\n for r in self.con.execute(\n \"\"\"SELECT city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\"):\n acc.setdefault(norm_key(r[\"city\"]), []).append((r[\"lat\"], r[\"lng\"]))\n out: dict[str, list[tuple]] = {}\n for k, pts in acc.items():\n clusters: list[list] = [] # [ [lat_c, lng_c, [points]] ]\n for lat, lng in pts:\n for cl in clusters:\n if _dist_km(lat, lng, cl[0], cl[1]) <= VILLE_RADIUS_KM:\n cl[2].append((lat, lng))\n cl[0] = statistics.median(p[0] for p in cl[2])\n cl[1] = statistics.median(p[1] for p in cl[2])\n break\n else:\n clusters.append([lat, lng, [(lat, lng)]])\n out[k] = [(cl[0], cl[1], len(cl[2])) for cl in clusters]\n self._med = out\n return self._med","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)\n# - cache persistant (table geocode_cache) : une adresse n'est géocodée\n# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce\n# - politesse : 1 requête/seconde max, User-Agent identifiable\n# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# - rigueur : chaque résultat est validé contre le CENTROÏDE de la ville\n# annoncée (médiane des fiches déjà géocodées, sinon Nominatim, en cache) —\n# à plus de VILLE_RADIUS_KM du centroïde, le candidat est rejeté. Corrige\n# la classe de bug « rue homonyme dans une autre ville » (ex. rue des\n# Perdrix de Jonquière géocodée à Saint-Augustin).\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport math\nimport sqlite3\nimport statistics\n\nimport re\nimport time\n\nimport requests\n\nfrom . import db\nfrom .normalize import strip_accents\n\nNOMINATIM_URL = \"https://nominatim.openstreetmap.org/search\"\n# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre\n# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)\nAQ_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/findAddressCandidates\")\nAQ_MIN_SCORE = 75\n# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête\n# User-Agent contient des accents (latin-1)\nUSER_AGENT = \"ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)\"\nREQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s\nREQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte\nRETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours\n\n# Bounding boxes (lat_min, lat_max, lng_min, lng_max)\n_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord\n# et la Gaspésie (expansion provinciale) — même boîte que schema.finalize()\n_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n\n_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n# Validation « rigoureuse » : distance max entre un résultat de géocodage et une\n# référence de la ville annoncée. 40 km tolère les grandes municipalités\n# fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues\n# homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).\n# ⚠ Le Québec compte de nombreuses municipalités HOMONYMES (deux L'Ange-Gardien,\n# deux Saint-Donat, deux Sainte-Félicité…) : la référence n'est donc jamais un\n# centroïde unique mais un ENSEMBLE de grappes de fiches (chaque homonyme garde\n# la sienne) + le point Nominatim de la ville.\nVILLE_RADIUS_KM = 40.0\nCLUSTER_MIN = 3 # une grappe de fiches devient une référence de confiance dès n >= 3\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n\n\ndef _dist_km(lat1: float, lng1: float, lat2: float, lng2: float) -> float:\n \"\"\"Distance haversine en kilomètres.\"\"\"\n p1, p2 = math.radians(lat1), math.radians(lat2)\n a = (math.sin((p2 - p1) / 2) ** 2\n + math.cos(p1) * math.cos(p2) * math.sin(math.radians(lng2 - lng1) / 2) ** 2)\n return 2 * 6371.0 * math.asin(math.sqrt(a))\n\n\ndef norm_key(address: str) -> str:\n \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\"\n s = strip_accents((address or \"\").lower())\n s = re.sub(r\"\\b(?:app?t?|appartement|unite|suite|#)\\.?\\s*[\\w-]+\\b\", \" \", s)\n s = re.sub(r\"[^a-z0-9]+\", \" \", s)\n return re.sub(r\"\\s+\", \" \", s).strip()\n\n\nclass Geocoder:\n def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0\n self._villes: dict[str, dict | None] = {} # norm(ville) -> {lat,lng,muni}\n self._med: dict[str, tuple] | None = None # norm(ville) -> (lat,lng,n)\n self.ville_api_calls = 0 # requêtes Nominatim « ville »\n\n @staticmethod\n def _clean(address: str) -> str:\n \"\"\"Nettoyages qui aident Nominatim sur les adresses québécoises.\"\"\"\n s = address.strip()\n # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique\n s = re.sub(r\"^(\\d+)-(\\d+)\\s\", r\"\\2 \", s)\n # « 6275 et 6375 boulevard X » -> premier civique\n s = re.sub(r\"^(\\d+)\\s+et\\s+\\d+\\s\", r\"\\1 \", s)\n # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu\n s = re.sub(r\"montr[ée]al\\s*-\\s*\", \"\", s, flags=re.I)\n # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau\n s = re.sub(r\",?\\s*(?:bureau|suite|local|app\\.?|apt\\.?)\\s*[\\w-]+\\b\", \"\", s, flags=re.I)\n # « Vanier (Québec) » -> « Vanier, Québec »\n s = re.sub(r\"\\s*\\((qu[ée]bec)\\)\", r\", \\1\", s, flags=re.I)\n # abréviations cardinales : « Rue Salaberry O » -> « Ouest »\n s = re.sub(r\"\\bO\\.?(?=,|\\s*$)\", \"Ouest\", s)\n s = re.sub(r\"\\bE\\.?(?=,|\\s*$)\", \"Est\", s)\n return s\n\n def _build_query(self, address: str, city: str) -> str:\n q = self._clean(address)\n key = strip_accents(q.lower())\n if city and strip_accents(city.lower()) not in key:\n q += f\", {city}\"\n if \"quebec\" not in strip_accents(q.lower()) and \"qc\" not in q.lower():\n q += \", Québec\"\n return q + \", Canada\"\n\n def _query_nominatim(self, params: dict) -> tuple[float, float] | None:\n \"\"\"Une requête Nominatim, throttlée.\"\"\"\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"format\": \"jsonv2\", \"limit\": 1, \"countrycodes\": \"ca\", **params,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None\n if not hits:\n return None\n try:\n return float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n except (KeyError, ValueError):\n return None\n\n def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).\n\n Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE\n pour éviter les correspondances approximatives sur une autre rue.\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"Québec\").strip()\n wait = REQUEST_DELAY_AQ - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(AQ_URL, params={\n \"SingleLine\": f\"{premier}, {ville}\",\n \"f\": \"json\", \"outSR\": 4326, \"maxLocations\": 1,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n cands = resp.json().get(\"candidates\") or []\n except Exception:\n self._last = time.time()\n return None\n if not cands or cands[0].get(\"score\", 0) < AQ_MIN_SCORE:\n return None\n loc = cands[0].get(\"location\") or {}\n try:\n return float(loc[\"y\"]), float(loc[\"x\"])\n except (KeyError, ValueError):\n return None\n\n def _attempts(self, address: str, city: str, muni: str | None = None) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) idem avec la municipalité OFFICIELLE (« Saguenay ») quand la ville\n annoncée est un secteur (« Jonquière (Lac-Kénogami) ») inconnu des API\n 3) recherche libre complète\n 4) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n villes = [ville]\n # premier mot de la ville (« Jonquiere Lac Kenogami » -> « Jonquiere »)\n if \" \" in ville:\n villes.append(ville.split(\" \")[0])\n if muni and norm_key(muni) not in {norm_key(v) for v in villes}:\n villes.append(muni)\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n # ----- centroïde de ville (validation rigoureuse) ------------------------\n def _medians(self) -> dict[str, tuple]:\n \"\"\"Centroïde (médiane lat/lng) par ville, depuis les fiches déjà\n géocodées — gratuit, robuste aux erreurs isolées dès n >= 5.\"\"\"\n if self._med is None:\n acc: dict[str, list] = {}\n for r in self.con.execute(\n \"\"\"SELECT city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\"):\n acc.setdefault(norm_key(r[\"city\"]), []).append((r[\"lat\"], r[\"lng\"]))\n self._med = {k: (statistics.median(p[0] for p in v),\n statistics.median(p[1] for p in v), len(v))\n for k, v in acc.items()}\n return self._med\n\n def resolve_ville(self, city: str, allow_api: bool = True) -> dict | None:\n \"\"\"Ville -> {lat, lng, muni} (muni = municipalité officielle, ex.\n « Jonquière (Lac-Kénogami) » -> Saguenay). Cache : geocode_cache,\n clé « ville: ». None si irrésoluble.\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n if k in self._villes:\n return self._villes[k]\n key = \"ville:\" + k\n row = self.con.execute(\n \"SELECT lat, lng, muni, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n v = {\"lat\": row[\"lat\"], \"lng\": row[\"lng\"], \"muni\": row[\"muni\"]}\n self._villes[k] = v\n return v\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n self._villes[k] = None\n return None\n if not allow_api:\n return None # pas de mémoire : on réessaiera quand l'API sera permise\n self.ville_api_calls += 1\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n v = None\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"q\": f\"{city}, Québec, Canada\", \"format\": \"jsonv2\", \"limit\": 1,\n \"countrycodes\": \"ca\", \"addressdetails\": 1}, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None # erreur réseau : ne pas cacher un échec définitif\n if hits:\n try:\n lat, lng = float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n if _in_bbox(lat, lng, _BBOX_SUD_QC):\n a = hits[0].get(\"address\") or {}\n muni = (a.get(\"city\") or a.get(\"town\") or a.get(\"village\")\n or a.get(\"municipality\"))\n v = {\"lat\": lat, \"lng\": lng, \"muni\": muni}\n except (KeyError, ValueError, TypeError):\n v = None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, muni, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, muni=excluded.muni,\"\n \" provider=excluded.provider, failed=excluded.failed, ts=excluded.ts\",\n (key, v[\"lat\"] if v else None, v[\"lng\"] if v else None,\n v[\"muni\"] if v else None, \"ville_nominatim\", 0 if v else 1, time.time()))\n self.con.commit()\n self._villes[k] = v\n return v\n\n def city_reference(self, city: str, allow_api: bool = True) -> tuple[float, float] | None:\n \"\"\"Centroïde de référence d'une ville : médiane des fiches (n >= 5),\n sinon résolution Nominatim. None si inconnue (-> validation bbox seule).\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n med = self._medians().get(k)\n if med and med[2] >= VILLE_MIN_SAMPLES:\n return (med[0], med[1])\n v = self.resolve_ville(city, allow_api=allow_api)\n return (v[\"lat\"], v[\"lng\"]) if v else None\n\n def coords_ok(self, c: tuple[float, float] | None, city: str,\n ref: tuple[float, float] | None = None) -> bool:\n \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM du\n centroïde de la ville annoncée (quand il est connu).\"\"\"\n if c is None or not _in_bbox(*c, _bbox_for(city)):\n return False\n if ref is None:\n ref = self.city_reference(city)\n return ref is None or _dist_km(c[0], c[1], ref[0], ref[1]) <= VILLE_RADIUS_KM\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis AQ/Nominatim. None si introuvable.\n\n Rigueur : chaque candidat doit être cohérent avec la ville annoncée\n (centroïde <= VILLE_RADIUS_KM). Si la ville annoncée est un secteur\n inconnu d'Adresses Québec, on réessaie avec la municipalité officielle.\n \"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n ref = self.city_reference(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if self.coords_ok(c, city, ref):\n coords = c\n muni = None\n if coords is None:\n # ville annoncée = secteur (« Jonquière (Lac-Kénogami) ») ? AQ ne\n # connaît que les municipalités officielles -> retenter avec elle.\n v = self.resolve_ville(city)\n muni = (v or {}).get(\"muni\")\n if muni and norm_key(muni) != norm_key(city or \"\"):\n c = self._query_adresses_quebec(address, muni)\n if self.coords_ok(c, city, ref):\n coords, provider = c, \"adresses_quebec_muni\"\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city, muni):\n c = self._query_nominatim(params)\n if self.coords_ok(c, city, ref):\n coords = c\n break\n ok = coords is not None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?)\"\n \" ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,\"\n \" lng=excluded.lng, provider=excluded.provider,\"\n \" failed=excluded.failed, ts=excluded.ts\",\n (key, coords[0] if ok else None, coords[1] if ok else None,\n provider, 0 if ok else 1, time.time()))\n self.con.commit()\n return coords if ok else None\n\n\ndef run(limit: int | None = None) -> dict:\n \"\"\"Géocode les annonces actives sans coordonnées, par adresse unique.\n\n `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de\n cache sont gratuits et toujours appliqués).\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0\n ORDER BY address\"\"\").fetchall()\n\n # regrouper par immeuble (adresse normalisée)\n groupes: dict[str, list] = {}\n for r in rows:\n groupes.setdefault(norm_key(r[\"address\"]), []).append(r)\n\n done = failed = requests_made = 0\n for key, members in groupes.items():\n if not key:\n continue\n cached = con.execute(\n \"SELECT failed FROM geocode_cache WHERE address=?\", (key,)).fetchone()\n if cached is None:\n if limit is not None and requests_made >= limit:\n continue\n requests_made += 1\n try:\n coords = geo.resolve(members[0][\"address\"], members[0][\"city\"])\n if coords:\n for r in members:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], r[\"uid\"]))\n done += len(members)\n else:\n # introuvable/hors zone : flag ; jamais de coordonnées bidon\n for r in members:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\",\n (r[\"uid\"],))\n failed += len(members)\n con.commit()\n except sqlite3.OperationalError:\n # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,\n # elle sera reprise au prochain passage — jamais crasher tout le run.\n try:\n con.rollback()\n except sqlite3.Error:\n pass\n time.sleep(1.0)\n continue\n\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed,\n \"unique_addresses\": len(groupes), \"api_requests\": requests_made}\n print(f\"[immo-ka] geocode {stats}\")\n return stats\n\n\nAQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200\nRESCUE_MAX = 150 # rattrapages resolve() max par passe (Nominatim = 1 req/s)\n\n\ndef strip_bad_source_coords(con, listings) -> int:\n \"\"\"Garde d'ingestion : annule les lat/lng fournis par un connecteur quand\n ils contredisent la ville annoncée (> VILLE_RADIUS_KM du centroïde connu).\n Cache seulement (médianes + villes déjà résolues) : aucun appel réseau,\n la synchronisation reste rapide. Retourne le nombre de paires annulées.\"\"\"\n geo = Geocoder(con)\n n = 0\n for lst in listings:\n if lst.lat is None or lst.lng is None or not (lst.city or \"\").strip():\n continue\n ref = geo.city_reference(lst.city, allow_api=False)\n if ref and _dist_km(lst.lat, lst.lng, ref[0], ref[1]) > VILLE_RADIUS_KM:\n lst.lat = lst.lng = None\n n += 1\n return n\n\n\ndef run_batch(limit: int | None = None) -> dict:\n \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de\n milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim).\"\"\"\n con = db.connect()\n geo = Geocoder(con) # pour réutiliser _clean / bbox\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0 ORDER BY address\"\"\").fetchall()\n # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache\n uniq: dict[str, dict] = {}\n for r in rows:\n k = norm_key(r[\"address\"])\n if not k or len(k) < 6:\n continue\n u = uniq.setdefault(k, {\"address\": r[\"address\"], \"city\": r[\"city\"],\n \"members\": []})\n u[\"members\"].append(r[\"uid\"])\n pending = []\n for k, u in uniq.items():\n c = con.execute(\"SELECT lat,lng,failed FROM geocode_cache WHERE address=?\",\n (k,)).fetchone()\n if c is not None and not c[\"failed\"]: # déjà résolu : appliquer direct\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (c[\"lat\"], c[\"lng\"], uid))\n continue\n if c is not None and c[\"failed\"]:\n continue\n pending.append((k, u))\n con.commit()\n if limit is not None:\n pending = pending[:limit]\n\n session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n rescue: list[tuple[str, dict]] = [] # échecs du lot -> resolve() individuel\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n # bbox + cohérence avec le centroïde de la ville annoncée\n if geo.coords_ok(cand, u[\"city\"]):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n con.commit()\n else:\n # pas de verdict tout de suite : resolve() réessaiera avec la\n # municipalité officielle + Nominatim (borné par RESCUE_MAX)\n rescue.append((k, u))\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, à rattraper {len(rescue)})\")\n\n # Rattrapage 1-par-1 des échecs du lot : variantes de municipalité (AQ) puis\n # Nominatim, validées par centroïde. resolve() écrit lui-même le verdict au\n # cache (succès ou échec 30 j) ; au-delà de RESCUE_MAX, on laisse les fiches\n # intactes (ni cache ni flag) -> reprises aux prochains passages.\n rescued = 0\n for k, u in rescue[:RESCUE_MAX]:\n try:\n coords = geo.resolve(u[\"address\"], u[\"city\"])\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n done += len(u[\"members\"])\n rescued += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n con.close()\n stats = {\"geocoded\": done, \"rescued\": rescued, \"failed\": failed,\n \"deferred\": max(0, len(rescue) - RESCUE_MAX),\n \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats\n\n\ndef run_audit(nominatim_budget: int | None = None, apply: bool = True) -> dict:\n \"\"\"Audit de cohérence géographique des fiches DÉJÀ géocodées.\n\n Détecte les coordonnées à plus de VILLE_RADIUS_KM du centroïde de leur\n ville (rue homonyme d'une autre région, geo erroné fourni par la source…),\n puis les remet en file de géocodage : lat/lng annulés, geocode_failed remis\n à 0, entrée de cache purgée. `nominatim_budget` borne les résolutions de\n villes inconnues (1 req/s) ; None = illimité. `apply=False` = rapport seul.\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\").fetchall()\n flagged, villes_inconnues = [], 0\n for r in rows:\n allow = nominatim_budget is None or geo.ville_api_calls < nominatim_budget\n ref = geo.city_reference(r[\"city\"], allow_api=allow)\n if ref is None:\n villes_inconnues += 1\n continue\n d = _dist_km(r[\"lat\"], r[\"lng\"], ref[0], ref[1])\n if d > VILLE_RADIUS_KM:\n flagged.append((r, d))\n if apply:\n for r, d in flagged:\n con.execute(\"DELETE FROM geocode_cache WHERE address=?\",\n (norm_key(r[\"address\"]),))\n con.execute(\"\"\"UPDATE listings SET lat=NULL, lng=NULL,\n geocode_failed=0 WHERE uid=?\"\"\", (r[\"uid\"],))\n con.commit()\n for r, d in flagged[:20]:\n print(f\"[immo-ka] audit: {r['uid']} « {r['address']}, {r['city']} » \"\n f\"à {d:.0f} km de sa ville\")\n con.close()\n stats = {\"verifiees\": len(rows), \"incoherentes\": len(flagged),\n \"villes_inconnues\": villes_inconnues, \"corrigees\": apply}\n print(f\"[immo-ka] geocode-audit {stats}\")\n return stats\n","structuredPatch":[{"oldStart":213,"oldLines":19,"newStart":213,"newLines":32,"lines":[" tries.append({\"street\": m.group(2), **commun})"," return tries"," ","- # ----- centroïde de ville (validation rigoureuse) ------------------------","- def _medians(self) -> dict[str, tuple]:","- \"\"\"Centroïde (médiane lat/lng) par ville, depuis les fiches déjà","- géocodées — gratuit, robuste aux erreurs isolées dès n >= 5.\"\"\"","+ # ----- références de ville (validation rigoureuse) -----------------------","+ def _clusters(self) -> dict[str, list[tuple]]:","+ \"\"\"Grappes de coordonnées par ville, depuis les fiches déjà géocodées","+ (regroupement glouton, rayon VILLE_RADIUS_KM). Chaque grappe :","+ (lat médiane, lng médiane, n). Les municipalités homonymes produisent","+ naturellement une grappe chacune — aucune n'écrase l'autre.\"\"\""," if self._med is None:"," acc: dict[str, list] = {}"," for r in self.con.execute("," \"\"\"SELECT city, lat, lng FROM listings"," WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\"):"," acc.setdefault(norm_key(r[\"city\"]), []).append((r[\"lat\"], r[\"lng\"]))","- self._med = {k: (statistics.median(p[0] for p in v),","- statistics.median(p[1] for p in v), len(v))","- for k, v in acc.items()}","+ out: dict[str, list[tuple]] = {}","+ for k, pts in acc.items():","+ clusters: list[list] = [] # [ [lat_c, lng_c, [points]] ]","+ for lat, lng in pts:","+ for cl in clusters:","+ if _dist_km(lat, lng, cl[0], cl[1]) <= VILLE_RADIUS_KM:","+ cl[2].append((lat, lng))","+ cl[0] = statistics.median(p[0] for p in cl[2])","+ cl[1] = statistics.median(p[1] for p in cl[2])","+ break","+ else:","+ clusters.append([lat, lng, [(lat, lng)]])","+ out[k] = [(cl[0], cl[1], len(cl[2])) for cl in clusters]","+ self._med = out"," return self._med"," "," def resolve_ville(self, city: str, allow_api: bool = True) -> dict | None:"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"2ae59b8f-5875-4404-9ad8-66fc72989296","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYHhmV1y4hSgFLUGrRJ","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1084,"cache_read_input_tokens":113228,"cache_creation":{"ephemeral_5m_input_tokens":1084,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"734cf73f-0883-45d9-b02f-f33b189a6c93"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYHhmV1y4hSgFLUGrRJ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Wq6N3b13rGfMwBFg982Ejq","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","old_string":" def city_reference(self, city: str, allow_api: bool = True) -> tuple[float, float] | None:\n \"\"\"Centroïde de référence d'une ville : médiane des fiches (n >= 5),\n sinon résolution Nominatim. None si inconnue (-> validation bbox seule).\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n med = self._medians().get(k)\n if med and med[2] >= VILLE_MIN_SAMPLES:\n return (med[0], med[1])\n v = self.resolve_ville(city, allow_api=allow_api)\n return (v[\"lat\"], v[\"lng\"]) if v else None\n\n def coords_ok(self, c: tuple[float, float] | None, city: str,\n ref: tuple[float, float] | None = None) -> bool:\n \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM du\n centroïde de la ville annoncée (quand il est connu).\"\"\"\n if c is None or not _in_bbox(*c, _bbox_for(city)):\n return False\n if ref is None:\n ref = self.city_reference(city)\n return ref is None or _dist_km(c[0], c[1], ref[0], ref[1]) <= VILLE_RADIUS_KM","new_string":" def city_refs(self, city: str, allow_api: bool = True) -> list[tuple[float, float]]:\n \"\"\"Points de référence d'une ville : grappes de fiches dignes de\n confiance (n >= CLUSTER_MIN — une par municipalité homonyme) + point\n Nominatim de la ville. Liste vide = ville inconnue (-> bbox seule).\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return []\n refs = [(cl[0], cl[1]) for cl in self._clusters().get(k, [])\n if cl[2] >= CLUSTER_MIN]\n v = self.resolve_ville(city, allow_api=allow_api)\n if v:\n refs.append((v[\"lat\"], v[\"lng\"]))\n return refs\n\n def coords_ok(self, c: tuple[float, float] | None, city: str,\n refs: list[tuple[float, float]] | None = None) -> bool:\n \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM d'au moins\n une référence de la ville annoncée (quand elle en a).\"\"\"\n if c is None or not _in_bbox(*c, _bbox_for(city)):\n return False\n if refs is None:\n refs = self.city_refs(city)\n return not refs or any(_dist_km(c[0], c[1], r[0], r[1]) <= VILLE_RADIUS_KM\n for r in refs)"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1084,"cache_read_input_tokens":113228,"cache_creation":{"ephemeral_5m_input_tokens":1084,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"d7388952-5fa6-4011-9b6f-6f3a9280ef5e"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Wq6N3b13rGfMwBFg982Ejq","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"b7115452-594d-448e-9713-3f9bd33da822","timestamp":"2026-08-25T13:24:34.121Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","oldString":" def city_reference(self, city: str, allow_api: bool = True) -> tuple[float, float] | None:\n \"\"\"Centroïde de référence d'une ville : médiane des fiches (n >= 5),\n sinon résolution Nominatim. None si inconnue (-> validation bbox seule).\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n med = self._medians().get(k)\n if med and med[2] >= VILLE_MIN_SAMPLES:\n return (med[0], med[1])\n v = self.resolve_ville(city, allow_api=allow_api)\n return (v[\"lat\"], v[\"lng\"]) if v else None\n\n def coords_ok(self, c: tuple[float, float] | None, city: str,\n ref: tuple[float, float] | None = None) -> bool:\n \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM du\n centroïde de la ville annoncée (quand il est connu).\"\"\"\n if c is None or not _in_bbox(*c, _bbox_for(city)):\n return False\n if ref is None:\n ref = self.city_reference(city)\n return ref is None or _dist_km(c[0], c[1], ref[0], ref[1]) <= VILLE_RADIUS_KM","newString":" def city_refs(self, city: str, allow_api: bool = True) -> list[tuple[float, float]]:\n \"\"\"Points de référence d'une ville : grappes de fiches dignes de\n confiance (n >= CLUSTER_MIN — une par municipalité homonyme) + point\n Nominatim de la ville. Liste vide = ville inconnue (-> bbox seule).\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return []\n refs = [(cl[0], cl[1]) for cl in self._clusters().get(k, [])\n if cl[2] >= CLUSTER_MIN]\n v = self.resolve_ville(city, allow_api=allow_api)\n if v:\n refs.append((v[\"lat\"], v[\"lng\"]))\n return refs\n\n def coords_ok(self, c: tuple[float, float] | None, city: str,\n refs: list[tuple[float, float]] | None = None) -> bool:\n \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM d'au moins\n une référence de la ville annoncée (quand elle en a).\"\"\"\n if c is None or not _in_bbox(*c, _bbox_for(city)):\n return False\n if refs is None:\n refs = self.city_refs(city)\n return not refs or any(_dist_km(c[0], c[1], r[0], r[1]) <= VILLE_RADIUS_KM\n for r in refs)","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)\n# - cache persistant (table geocode_cache) : une adresse n'est géocodée\n# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce\n# - politesse : 1 requête/seconde max, User-Agent identifiable\n# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# - rigueur : chaque résultat est validé contre le CENTROÏDE de la ville\n# annoncée (médiane des fiches déjà géocodées, sinon Nominatim, en cache) —\n# à plus de VILLE_RADIUS_KM du centroïde, le candidat est rejeté. Corrige\n# la classe de bug « rue homonyme dans une autre ville » (ex. rue des\n# Perdrix de Jonquière géocodée à Saint-Augustin).\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport math\nimport sqlite3\nimport statistics\n\nimport re\nimport time\n\nimport requests\n\nfrom . import db\nfrom .normalize import strip_accents\n\nNOMINATIM_URL = \"https://nominatim.openstreetmap.org/search\"\n# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre\n# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)\nAQ_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/findAddressCandidates\")\nAQ_MIN_SCORE = 75\n# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête\n# User-Agent contient des accents (latin-1)\nUSER_AGENT = \"ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)\"\nREQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s\nREQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte\nRETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours\n\n# Bounding boxes (lat_min, lat_max, lng_min, lng_max)\n_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord\n# et la Gaspésie (expansion provinciale) — même boîte que schema.finalize()\n_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n\n_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n# Validation « rigoureuse » : distance max entre un résultat de géocodage et une\n# référence de la ville annoncée. 40 km tolère les grandes municipalités\n# fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues\n# homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).\n# ⚠ Le Québec compte de nombreuses municipalités HOMONYMES (deux L'Ange-Gardien,\n# deux Saint-Donat, deux Sainte-Félicité…) : la référence n'est donc jamais un\n# centroïde unique mais un ENSEMBLE de grappes de fiches (chaque homonyme garde\n# la sienne) + le point Nominatim de la ville.\nVILLE_RADIUS_KM = 40.0\nCLUSTER_MIN = 3 # une grappe de fiches devient une référence de confiance dès n >= 3\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n\n\ndef _dist_km(lat1: float, lng1: float, lat2: float, lng2: float) -> float:\n \"\"\"Distance haversine en kilomètres.\"\"\"\n p1, p2 = math.radians(lat1), math.radians(lat2)\n a = (math.sin((p2 - p1) / 2) ** 2\n + math.cos(p1) * math.cos(p2) * math.sin(math.radians(lng2 - lng1) / 2) ** 2)\n return 2 * 6371.0 * math.asin(math.sqrt(a))\n\n\ndef norm_key(address: str) -> str:\n \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\"\n s = strip_accents((address or \"\").lower())\n s = re.sub(r\"\\b(?:app?t?|appartement|unite|suite|#)\\.?\\s*[\\w-]+\\b\", \" \", s)\n s = re.sub(r\"[^a-z0-9]+\", \" \", s)\n return re.sub(r\"\\s+\", \" \", s).strip()\n\n\nclass Geocoder:\n def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0\n self._villes: dict[str, dict | None] = {} # norm(ville) -> {lat,lng,muni}\n self._med: dict[str, tuple] | None = None # norm(ville) -> (lat,lng,n)\n self.ville_api_calls = 0 # requêtes Nominatim « ville »\n\n @staticmethod\n def _clean(address: str) -> str:\n \"\"\"Nettoyages qui aident Nominatim sur les adresses québécoises.\"\"\"\n s = address.strip()\n # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique\n s = re.sub(r\"^(\\d+)-(\\d+)\\s\", r\"\\2 \", s)\n # « 6275 et 6375 boulevard X » -> premier civique\n s = re.sub(r\"^(\\d+)\\s+et\\s+\\d+\\s\", r\"\\1 \", s)\n # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu\n s = re.sub(r\"montr[ée]al\\s*-\\s*\", \"\", s, flags=re.I)\n # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau\n s = re.sub(r\",?\\s*(?:bureau|suite|local|app\\.?|apt\\.?)\\s*[\\w-]+\\b\", \"\", s, flags=re.I)\n # « Vanier (Québec) » -> « Vanier, Québec »\n s = re.sub(r\"\\s*\\((qu[ée]bec)\\)\", r\", \\1\", s, flags=re.I)\n # abréviations cardinales : « Rue Salaberry O » -> « Ouest »\n s = re.sub(r\"\\bO\\.?(?=,|\\s*$)\", \"Ouest\", s)\n s = re.sub(r\"\\bE\\.?(?=,|\\s*$)\", \"Est\", s)\n return s\n\n def _build_query(self, address: str, city: str) -> str:\n q = self._clean(address)\n key = strip_accents(q.lower())\n if city and strip_accents(city.lower()) not in key:\n q += f\", {city}\"\n if \"quebec\" not in strip_accents(q.lower()) and \"qc\" not in q.lower():\n q += \", Québec\"\n return q + \", Canada\"\n\n def _query_nominatim(self, params: dict) -> tuple[float, float] | None:\n \"\"\"Une requête Nominatim, throttlée.\"\"\"\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"format\": \"jsonv2\", \"limit\": 1, \"countrycodes\": \"ca\", **params,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None\n if not hits:\n return None\n try:\n return float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n except (KeyError, ValueError):\n return None\n\n def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).\n\n Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE\n pour éviter les correspondances approximatives sur une autre rue.\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"Québec\").strip()\n wait = REQUEST_DELAY_AQ - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(AQ_URL, params={\n \"SingleLine\": f\"{premier}, {ville}\",\n \"f\": \"json\", \"outSR\": 4326, \"maxLocations\": 1,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n cands = resp.json().get(\"candidates\") or []\n except Exception:\n self._last = time.time()\n return None\n if not cands or cands[0].get(\"score\", 0) < AQ_MIN_SCORE:\n return None\n loc = cands[0].get(\"location\") or {}\n try:\n return float(loc[\"y\"]), float(loc[\"x\"])\n except (KeyError, ValueError):\n return None\n\n def _attempts(self, address: str, city: str, muni: str | None = None) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) idem avec la municipalité OFFICIELLE (« Saguenay ») quand la ville\n annoncée est un secteur (« Jonquière (Lac-Kénogami) ») inconnu des API\n 3) recherche libre complète\n 4) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n villes = [ville]\n # premier mot de la ville (« Jonquiere Lac Kenogami » -> « Jonquiere »)\n if \" \" in ville:\n villes.append(ville.split(\" \")[0])\n if muni and norm_key(muni) not in {norm_key(v) for v in villes}:\n villes.append(muni)\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n # ----- références de ville (validation rigoureuse) -----------------------\n def _clusters(self) -> dict[str, list[tuple]]:\n \"\"\"Grappes de coordonnées par ville, depuis les fiches déjà géocodées\n (regroupement glouton, rayon VILLE_RADIUS_KM). Chaque grappe :\n (lat médiane, lng médiane, n). Les municipalités homonymes produisent\n naturellement une grappe chacune — aucune n'écrase l'autre.\"\"\"\n if self._med is None:\n acc: dict[str, list] = {}\n for r in self.con.execute(\n \"\"\"SELECT city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\"):\n acc.setdefault(norm_key(r[\"city\"]), []).append((r[\"lat\"], r[\"lng\"]))\n out: dict[str, list[tuple]] = {}\n for k, pts in acc.items():\n clusters: list[list] = [] # [ [lat_c, lng_c, [points]] ]\n for lat, lng in pts:\n for cl in clusters:\n if _dist_km(lat, lng, cl[0], cl[1]) <= VILLE_RADIUS_KM:\n cl[2].append((lat, lng))\n cl[0] = statistics.median(p[0] for p in cl[2])\n cl[1] = statistics.median(p[1] for p in cl[2])\n break\n else:\n clusters.append([lat, lng, [(lat, lng)]])\n out[k] = [(cl[0], cl[1], len(cl[2])) for cl in clusters]\n self._med = out\n return self._med\n\n def resolve_ville(self, city: str, allow_api: bool = True) -> dict | None:\n \"\"\"Ville -> {lat, lng, muni} (muni = municipalité officielle, ex.\n « Jonquière (Lac-Kénogami) » -> Saguenay). Cache : geocode_cache,\n clé « ville: ». None si irrésoluble.\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n if k in self._villes:\n return self._villes[k]\n key = \"ville:\" + k\n row = self.con.execute(\n \"SELECT lat, lng, muni, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n v = {\"lat\": row[\"lat\"], \"lng\": row[\"lng\"], \"muni\": row[\"muni\"]}\n self._villes[k] = v\n return v\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n self._villes[k] = None\n return None\n if not allow_api:\n return None # pas de mémoire : on réessaiera quand l'API sera permise\n self.ville_api_calls += 1\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n v = None\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"q\": f\"{city}, Québec, Canada\", \"format\": \"jsonv2\", \"limit\": 1,\n \"countrycodes\": \"ca\", \"addressdetails\": 1}, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None # erreur réseau : ne pas cacher un échec définitif\n if hits:\n try:\n lat, lng = float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n if _in_bbox(lat, lng, _BBOX_SUD_QC):\n a = hits[0].get(\"address\") or {}\n muni = (a.get(\"city\") or a.get(\"town\") or a.get(\"village\")\n or a.get(\"municipality\"))\n v = {\"lat\": lat, \"lng\": lng, \"muni\": muni}\n except (KeyError, ValueError, TypeError):\n v = None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, muni, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, muni=excluded.muni,\"\n \" provider=excluded.provider, failed=excluded.failed, ts=excluded.ts\",\n (key, v[\"lat\"] if v else None, v[\"lng\"] if v else None,\n v[\"muni\"] if v else None, \"ville_nominatim\", 0 if v else 1, time.time()))\n self.con.commit()\n self._villes[k] = v\n return v\n\n def city_reference(self, city: str, allow_api: bool = True) -> tuple[float, float] | None:\n \"\"\"Centroïde de référence d'une ville : médiane des fiches (n >= 5),\n sinon résolution Nominatim. None si inconnue (-> validation bbox seule).\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n med = self._medians().get(k)\n if med and med[2] >= VILLE_MIN_SAMPLES:\n return (med[0], med[1])\n v = self.resolve_ville(city, allow_api=allow_api)\n return (v[\"lat\"], v[\"lng\"]) if v else None\n\n def coords_ok(self, c: tuple[float, float] | None, city: str,\n ref: tuple[float, float] | None = None) -> bool:\n \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM du\n centroïde de la ville annoncée (quand il est connu).\"\"\"\n if c is None or not _in_bbox(*c, _bbox_for(city)):\n return False\n if ref is None:\n ref = self.city_reference(city)\n return ref is None or _dist_km(c[0], c[1], ref[0], ref[1]) <= VILLE_RADIUS_KM\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis AQ/Nominatim. None si introuvable.\n\n Rigueur : chaque candidat doit être cohérent avec la ville annoncée\n (centroïde <= VILLE_RADIUS_KM). Si la ville annoncée est un secteur\n inconnu d'Adresses Québec, on réessaie avec la municipalité officielle.\n \"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n ref = self.city_reference(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if self.coords_ok(c, city, ref):\n coords = c\n muni = None\n if coords is None:\n # ville annoncée = secteur (« Jonquière (Lac-Kénogami) ») ? AQ ne\n # connaît que les municipalités officielles -> retenter avec elle.\n v = self.resolve_ville(city)\n muni = (v or {}).get(\"muni\")\n if muni and norm_key(muni) != norm_key(city or \"\"):\n c = self._query_adresses_quebec(address, muni)\n if self.coords_ok(c, city, ref):\n coords, provider = c, \"adresses_quebec_muni\"\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city, muni):\n c = self._query_nominatim(params)\n if self.coords_ok(c, city, ref):\n coords = c\n break\n ok = coords is not None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?)\"\n \" ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,\"\n \" lng=excluded.lng, provider=excluded.provider,\"\n \" failed=excluded.failed, ts=excluded.ts\",\n (key, coords[0] if ok else None, coords[1] if ok else None,\n provider, 0 if ok else 1, time.time()))\n self.con.commit()\n return coords if ok else None\n\n\ndef run(limit: int | None = None) -> dict:\n \"\"\"Géocode les annonces actives sans coordonnées, par adresse unique.\n\n `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de\n cache sont gratuits et toujours appliqués).\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0\n ORDER BY address\"\"\").fetchall()\n\n # regrouper par immeuble (adresse normalisée)\n groupes: dict[str, list] = {}\n for r in rows:\n groupes.setdefault(norm_key(r[\"address\"]), []).append(r)\n\n done = failed = requests_made = 0\n for key, members in groupes.items():\n if not key:\n continue\n cached = con.execute(\n \"SELECT failed FROM geocode_cache WHERE address=?\", (key,)).fetchone()\n if cached is None:\n if limit is not None and requests_made >= limit:\n continue\n requests_made += 1\n try:\n coords = geo.resolve(members[0][\"address\"], members[0][\"city\"])\n if coords:\n for r in members:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], r[\"uid\"]))\n done += len(members)\n else:\n # introuvable/hors zone : flag ; jamais de coordonnées bidon\n for r in members:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\",\n (r[\"uid\"],))\n failed += len(members)\n con.commit()\n except sqlite3.OperationalError:\n # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,\n # elle sera reprise au prochain passage — jamais crasher tout le run.\n try:\n con.rollback()\n except sqlite3.Error:\n pass\n time.sleep(1.0)\n continue\n\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed,\n \"unique_addresses\": len(groupes), \"api_requests\": requests_made}\n print(f\"[immo-ka] geocode {stats}\")\n return stats\n\n\nAQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200\nRESCUE_MAX = 150 # rattrapages resolve() max par passe (Nominatim = 1 req/s)\n\n\ndef strip_bad_source_coords(con, listings) -> int:\n \"\"\"Garde d'ingestion : annule les lat/lng fournis par un connecteur quand\n ils contredisent la ville annoncée (> VILLE_RADIUS_KM du centroïde connu).\n Cache seulement (médianes + villes déjà résolues) : aucun appel réseau,\n la synchronisation reste rapide. Retourne le nombre de paires annulées.\"\"\"\n geo = Geocoder(con)\n n = 0\n for lst in listings:\n if lst.lat is None or lst.lng is None or not (lst.city or \"\").strip():\n continue\n ref = geo.city_reference(lst.city, allow_api=False)\n if ref and _dist_km(lst.lat, lst.lng, ref[0], ref[1]) > VILLE_RADIUS_KM:\n lst.lat = lst.lng = None\n n += 1\n return n\n\n\ndef run_batch(limit: int | None = None) -> dict:\n \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de\n milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim).\"\"\"\n con = db.connect()\n geo = Geocoder(con) # pour réutiliser _clean / bbox\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0 ORDER BY address\"\"\").fetchall()\n # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache\n uniq: dict[str, dict] = {}\n for r in rows:\n k = norm_key(r[\"address\"])\n if not k or len(k) < 6:\n continue\n u = uniq.setdefault(k, {\"address\": r[\"address\"], \"city\": r[\"city\"],\n \"members\": []})\n u[\"members\"].append(r[\"uid\"])\n pending = []\n for k, u in uniq.items():\n c = con.execute(\"SELECT lat,lng,failed FROM geocode_cache WHERE address=?\",\n (k,)).fetchone()\n if c is not None and not c[\"failed\"]: # déjà résolu : appliquer direct\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (c[\"lat\"], c[\"lng\"], uid))\n continue\n if c is not None and c[\"failed\"]:\n continue\n pending.append((k, u))\n con.commit()\n if limit is not None:\n pending = pending[:limit]\n\n session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n rescue: list[tuple[str, dict]] = [] # échecs du lot -> resolve() individuel\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n # bbox + cohérence avec le centroïde de la ville annoncée\n if geo.coords_ok(cand, u[\"city\"]):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n con.commit()\n else:\n # pas de verdict tout de suite : resolve() réessaiera avec la\n # municipalité officielle + Nominatim (borné par RESCUE_MAX)\n rescue.append((k, u))\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, à rattraper {len(rescue)})\")\n\n # Rattrapage 1-par-1 des échecs du lot : variantes de municipalité (AQ) puis\n # Nominatim, validées par centroïde. resolve() écrit lui-même le verdict au\n # cache (succès ou échec 30 j) ; au-delà de RESCUE_MAX, on laisse les fiches\n # intactes (ni cache ni flag) -> reprises aux prochains passages.\n rescued = 0\n for k, u in rescue[:RESCUE_MAX]:\n try:\n coords = geo.resolve(u[\"address\"], u[\"city\"])\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n done += len(u[\"members\"])\n rescued += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n con.close()\n stats = {\"geocoded\": done, \"rescued\": rescued, \"failed\": failed,\n \"deferred\": max(0, len(rescue) - RESCUE_MAX),\n \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats\n\n\ndef run_audit(nominatim_budget: int | None = None, apply: bool = True) -> dict:\n \"\"\"Audit de cohérence géographique des fiches DÉJÀ géocodées.\n\n Détecte les coordonnées à plus de VILLE_RADIUS_KM du centroïde de leur\n ville (rue homonyme d'une autre région, geo erroné fourni par la source…),\n puis les remet en file de géocodage : lat/lng annulés, geocode_failed remis\n à 0, entrée de cache purgée. `nominatim_budget` borne les résolutions de\n villes inconnues (1 req/s) ; None = illimité. `apply=False` = rapport seul.\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\").fetchall()\n flagged, villes_inconnues = [], 0\n for r in rows:\n allow = nominatim_budget is None or geo.ville_api_calls < nominatim_budget\n ref = geo.city_reference(r[\"city\"], allow_api=allow)\n if ref is None:\n villes_inconnues += 1\n continue\n d = _dist_km(r[\"lat\"], r[\"lng\"], ref[0], ref[1])\n if d > VILLE_RADIUS_KM:\n flagged.append((r, d))\n if apply:\n for r, d in flagged:\n con.execute(\"DELETE FROM geocode_cache WHERE address=?\",\n (norm_key(r[\"address\"]),))\n con.execute(\"\"\"UPDATE listings SET lat=NULL, lng=NULL,\n geocode_failed=0 WHERE uid=?\"\"\", (r[\"uid\"],))\n con.commit()\n for r, d in flagged[:20]:\n print(f\"[immo-ka] audit: {r['uid']} « {r['address']}, {r['city']} » \"\n f\"à {d:.0f} km de sa ville\")\n con.close()\n stats = {\"verifiees\": len(rows), \"incoherentes\": len(flagged),\n \"villes_inconnues\": villes_inconnues, \"corrigees\": apply}\n print(f\"[immo-ka] geocode-audit {stats}\")\n return stats\n","structuredPatch":[{"oldStart":300,"oldLines":27,"newStart":300,"newLines":30,"lines":[" self._villes[k] = v"," return v"," ","- def city_reference(self, city: str, allow_api: bool = True) -> tuple[float, float] | None:","- \"\"\"Centroïde de référence d'une ville : médiane des fiches (n >= 5),","- sinon résolution Nominatim. None si inconnue (-> validation bbox seule).\"\"\"","+ def city_refs(self, city: str, allow_api: bool = True) -> list[tuple[float, float]]:","+ \"\"\"Points de référence d'une ville : grappes de fiches dignes de","+ confiance (n >= CLUSTER_MIN — une par municipalité homonyme) + point","+ Nominatim de la ville. Liste vide = ville inconnue (-> bbox seule).\"\"\""," k = norm_key(city or \"\")"," if not k:","- return None","- med = self._medians().get(k)","- if med and med[2] >= VILLE_MIN_SAMPLES:","- return (med[0], med[1])","+ return []","+ refs = [(cl[0], cl[1]) for cl in self._clusters().get(k, [])","+ if cl[2] >= CLUSTER_MIN]"," v = self.resolve_ville(city, allow_api=allow_api)","- return (v[\"lat\"], v[\"lng\"]) if v else None","+ if v:","+ refs.append((v[\"lat\"], v[\"lng\"]))","+ return refs"," "," def coords_ok(self, c: tuple[float, float] | None, city: str,","- ref: tuple[float, float] | None = None) -> bool:","- \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM du","- centroïde de la ville annoncée (quand il est connu).\"\"\"","+ refs: list[tuple[float, float]] | None = None) -> bool:","+ \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM d'au moins","+ une référence de la ville annoncée (quand elle en a).\"\"\""," if c is None or not _in_bbox(*c, _bbox_for(city)):"," return False","- if ref is None:","- ref = self.city_reference(city)","- return ref is None or _dist_km(c[0], c[1], ref[0], ref[1]) <= VILLE_RADIUS_KM","+ if refs is None:","+ refs = self.city_refs(city)","+ return not refs or any(_dist_km(c[0], c[1], r[0], r[1]) <= VILLE_RADIUS_KM","+ for r in refs)"," "," def resolve(self, address: str, city: str) -> tuple[float, float] | None:"," \"\"\"Adresse -> (lat, lng), via cache puis AQ/Nominatim. None si introuvable."]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"30703f09-246f-4a2b-9199-d90a381cb617","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYJmTG8ndxKm3MSeHZZ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01CW62WRWc6eGii5qPV8g6V6","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","old_string":" ref = self.city_reference(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if self.coords_ok(c, city, ref):\n coords = c\n muni = None\n if coords is None:\n # ville annoncée = secteur (« Jonquière (Lac-Kénogami) ») ? AQ ne\n # connaît que les municipalités officielles -> retenter avec elle.\n v = self.resolve_ville(city)\n muni = (v or {}).get(\"muni\")\n if muni and norm_key(muni) != norm_key(city or \"\"):\n c = self._query_adresses_quebec(address, muni)\n if self.coords_ok(c, city, ref):\n coords, provider = c, \"adresses_quebec_muni\"\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city, muni):\n c = self._query_nominatim(params)\n if self.coords_ok(c, city, ref):\n coords = c\n break\n ok = coords is not None","new_string":" refs = self.city_refs(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if self.coords_ok(c, city, refs):\n coords = c\n muni = None\n if coords is None:\n # ville annoncée = secteur (« Jonquière (Lac-Kénogami) ») ? AQ ne\n # connaît que les municipalités officielles -> retenter avec elle.\n v = self.resolve_ville(city)\n muni = (v or {}).get(\"muni\")\n if muni and norm_key(muni) != norm_key(city or \"\"):\n c = self._query_adresses_quebec(address, muni)\n if self.coords_ok(c, city, refs):\n coords, provider = c, \"adresses_quebec_muni\"\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city, muni):\n c = self._query_nominatim(params)\n if self.coords_ok(c, city, refs):\n coords = c\n break\n ok = coords is not None"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1169,"cache_read_input_tokens":114312,"cache_creation":{"ephemeral_5m_input_tokens":1169,"ephemeral_1h_input_tokens":0},"output_tokens":20,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"d103edc4-c376-4d85-a48d-73c91b1bb341"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01CW62WRWc6eGii5qPV8g6V6","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"5af7cf8f-f365-424b-bdbe-13cf37ed1d51","timestamp":"2026-08-25T13:24:45.717Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","oldString":" ref = self.city_reference(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if self.coords_ok(c, city, ref):\n coords = c\n muni = None\n if coords is None:\n # ville annoncée = secteur (« Jonquière (Lac-Kénogami) ») ? AQ ne\n # connaît que les municipalités officielles -> retenter avec elle.\n v = self.resolve_ville(city)\n muni = (v or {}).get(\"muni\")\n if muni and norm_key(muni) != norm_key(city or \"\"):\n c = self._query_adresses_quebec(address, muni)\n if self.coords_ok(c, city, ref):\n coords, provider = c, \"adresses_quebec_muni\"\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city, muni):\n c = self._query_nominatim(params)\n if self.coords_ok(c, city, ref):\n coords = c\n break\n ok = coords is not None","newString":" refs = self.city_refs(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if self.coords_ok(c, city, refs):\n coords = c\n muni = None\n if coords is None:\n # ville annoncée = secteur (« Jonquière (Lac-Kénogami) ») ? AQ ne\n # connaît que les municipalités officielles -> retenter avec elle.\n v = self.resolve_ville(city)\n muni = (v or {}).get(\"muni\")\n if muni and norm_key(muni) != norm_key(city or \"\"):\n c = self._query_adresses_quebec(address, muni)\n if self.coords_ok(c, city, refs):\n coords, provider = c, \"adresses_quebec_muni\"\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city, muni):\n c = self._query_nominatim(params)\n if self.coords_ok(c, city, refs):\n coords = c\n break\n ok = coords is not None","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)\n# - cache persistant (table geocode_cache) : une adresse n'est géocodée\n# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce\n# - politesse : 1 requête/seconde max, User-Agent identifiable\n# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# - rigueur : chaque résultat est validé contre le CENTROÏDE de la ville\n# annoncée (médiane des fiches déjà géocodées, sinon Nominatim, en cache) —\n# à plus de VILLE_RADIUS_KM du centroïde, le candidat est rejeté. Corrige\n# la classe de bug « rue homonyme dans une autre ville » (ex. rue des\n# Perdrix de Jonquière géocodée à Saint-Augustin).\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport math\nimport sqlite3\nimport statistics\n\nimport re\nimport time\n\nimport requests\n\nfrom . import db\nfrom .normalize import strip_accents\n\nNOMINATIM_URL = \"https://nominatim.openstreetmap.org/search\"\n# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre\n# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)\nAQ_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/findAddressCandidates\")\nAQ_MIN_SCORE = 75\n# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête\n# User-Agent contient des accents (latin-1)\nUSER_AGENT = \"ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)\"\nREQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s\nREQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte\nRETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours\n\n# Bounding boxes (lat_min, lat_max, lng_min, lng_max)\n_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord\n# et la Gaspésie (expansion provinciale) — même boîte que schema.finalize()\n_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n\n_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n# Validation « rigoureuse » : distance max entre un résultat de géocodage et une\n# référence de la ville annoncée. 40 km tolère les grandes municipalités\n# fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues\n# homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).\n# ⚠ Le Québec compte de nombreuses municipalités HOMONYMES (deux L'Ange-Gardien,\n# deux Saint-Donat, deux Sainte-Félicité…) : la référence n'est donc jamais un\n# centroïde unique mais un ENSEMBLE de grappes de fiches (chaque homonyme garde\n# la sienne) + le point Nominatim de la ville.\nVILLE_RADIUS_KM = 40.0\nCLUSTER_MIN = 3 # une grappe de fiches devient une référence de confiance dès n >= 3\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n\n\ndef _dist_km(lat1: float, lng1: float, lat2: float, lng2: float) -> float:\n \"\"\"Distance haversine en kilomètres.\"\"\"\n p1, p2 = math.radians(lat1), math.radians(lat2)\n a = (math.sin((p2 - p1) / 2) ** 2\n + math.cos(p1) * math.cos(p2) * math.sin(math.radians(lng2 - lng1) / 2) ** 2)\n return 2 * 6371.0 * math.asin(math.sqrt(a))\n\n\ndef norm_key(address: str) -> str:\n \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\"\n s = strip_accents((address or \"\").lower())\n s = re.sub(r\"\\b(?:app?t?|appartement|unite|suite|#)\\.?\\s*[\\w-]+\\b\", \" \", s)\n s = re.sub(r\"[^a-z0-9]+\", \" \", s)\n return re.sub(r\"\\s+\", \" \", s).strip()\n\n\nclass Geocoder:\n def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0\n self._villes: dict[str, dict | None] = {} # norm(ville) -> {lat,lng,muni}\n self._med: dict[str, tuple] | None = None # norm(ville) -> (lat,lng,n)\n self.ville_api_calls = 0 # requêtes Nominatim « ville »\n\n @staticmethod\n def _clean(address: str) -> str:\n \"\"\"Nettoyages qui aident Nominatim sur les adresses québécoises.\"\"\"\n s = address.strip()\n # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique\n s = re.sub(r\"^(\\d+)-(\\d+)\\s\", r\"\\2 \", s)\n # « 6275 et 6375 boulevard X » -> premier civique\n s = re.sub(r\"^(\\d+)\\s+et\\s+\\d+\\s\", r\"\\1 \", s)\n # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu\n s = re.sub(r\"montr[ée]al\\s*-\\s*\", \"\", s, flags=re.I)\n # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau\n s = re.sub(r\",?\\s*(?:bureau|suite|local|app\\.?|apt\\.?)\\s*[\\w-]+\\b\", \"\", s, flags=re.I)\n # « Vanier (Québec) » -> « Vanier, Québec »\n s = re.sub(r\"\\s*\\((qu[ée]bec)\\)\", r\", \\1\", s, flags=re.I)\n # abréviations cardinales : « Rue Salaberry O » -> « Ouest »\n s = re.sub(r\"\\bO\\.?(?=,|\\s*$)\", \"Ouest\", s)\n s = re.sub(r\"\\bE\\.?(?=,|\\s*$)\", \"Est\", s)\n return s\n\n def _build_query(self, address: str, city: str) -> str:\n q = self._clean(address)\n key = strip_accents(q.lower())\n if city and strip_accents(city.lower()) not in key:\n q += f\", {city}\"\n if \"quebec\" not in strip_accents(q.lower()) and \"qc\" not in q.lower():\n q += \", Québec\"\n return q + \", Canada\"\n\n def _query_nominatim(self, params: dict) -> tuple[float, float] | None:\n \"\"\"Une requête Nominatim, throttlée.\"\"\"\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"format\": \"jsonv2\", \"limit\": 1, \"countrycodes\": \"ca\", **params,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None\n if not hits:\n return None\n try:\n return float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n except (KeyError, ValueError):\n return None\n\n def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).\n\n Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE\n pour éviter les correspondances approximatives sur une autre rue.\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"Québec\").strip()\n wait = REQUEST_DELAY_AQ - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(AQ_URL, params={\n \"SingleLine\": f\"{premier}, {ville}\",\n \"f\": \"json\", \"outSR\": 4326, \"maxLocations\": 1,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n cands = resp.json().get(\"candidates\") or []\n except Exception:\n self._last = time.time()\n return None\n if not cands or cands[0].get(\"score\", 0) < AQ_MIN_SCORE:\n return None\n loc = cands[0].get(\"location\") or {}\n try:\n return float(loc[\"y\"]), float(loc[\"x\"])\n except (KeyError, ValueError):\n return None\n\n def _attempts(self, address: str, city: str, muni: str | None = None) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) idem avec la municipalité OFFICIELLE (« Saguenay ») quand la ville\n annoncée est un secteur (« Jonquière (Lac-Kénogami) ») inconnu des API\n 3) recherche libre complète\n 4) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n villes = [ville]\n # premier mot de la ville (« Jonquiere Lac Kenogami » -> « Jonquiere »)\n if \" \" in ville:\n villes.append(ville.split(\" \")[0])\n if muni and norm_key(muni) not in {norm_key(v) for v in villes}:\n villes.append(muni)\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n # ----- références de ville (validation rigoureuse) -----------------------\n def _clusters(self) -> dict[str, list[tuple]]:\n \"\"\"Grappes de coordonnées par ville, depuis les fiches déjà géocodées\n (regroupement glouton, rayon VILLE_RADIUS_KM). Chaque grappe :\n (lat médiane, lng médiane, n). Les municipalités homonymes produisent\n naturellement une grappe chacune — aucune n'écrase l'autre.\"\"\"\n if self._med is None:\n acc: dict[str, list] = {}\n for r in self.con.execute(\n \"\"\"SELECT city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\"):\n acc.setdefault(norm_key(r[\"city\"]), []).append((r[\"lat\"], r[\"lng\"]))\n out: dict[str, list[tuple]] = {}\n for k, pts in acc.items():\n clusters: list[list] = [] # [ [lat_c, lng_c, [points]] ]\n for lat, lng in pts:\n for cl in clusters:\n if _dist_km(lat, lng, cl[0], cl[1]) <= VILLE_RADIUS_KM:\n cl[2].append((lat, lng))\n cl[0] = statistics.median(p[0] for p in cl[2])\n cl[1] = statistics.median(p[1] for p in cl[2])\n break\n else:\n clusters.append([lat, lng, [(lat, lng)]])\n out[k] = [(cl[0], cl[1], len(cl[2])) for cl in clusters]\n self._med = out\n return self._med\n\n def resolve_ville(self, city: str, allow_api: bool = True) -> dict | None:\n \"\"\"Ville -> {lat, lng, muni} (muni = municipalité officielle, ex.\n « Jonquière (Lac-Kénogami) » -> Saguenay). Cache : geocode_cache,\n clé « ville: ». None si irrésoluble.\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n if k in self._villes:\n return self._villes[k]\n key = \"ville:\" + k\n row = self.con.execute(\n \"SELECT lat, lng, muni, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n v = {\"lat\": row[\"lat\"], \"lng\": row[\"lng\"], \"muni\": row[\"muni\"]}\n self._villes[k] = v\n return v\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n self._villes[k] = None\n return None\n if not allow_api:\n return None # pas de mémoire : on réessaiera quand l'API sera permise\n self.ville_api_calls += 1\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n v = None\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"q\": f\"{city}, Québec, Canada\", \"format\": \"jsonv2\", \"limit\": 1,\n \"countrycodes\": \"ca\", \"addressdetails\": 1}, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None # erreur réseau : ne pas cacher un échec définitif\n if hits:\n try:\n lat, lng = float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n if _in_bbox(lat, lng, _BBOX_SUD_QC):\n a = hits[0].get(\"address\") or {}\n muni = (a.get(\"city\") or a.get(\"town\") or a.get(\"village\")\n or a.get(\"municipality\"))\n v = {\"lat\": lat, \"lng\": lng, \"muni\": muni}\n except (KeyError, ValueError, TypeError):\n v = None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, muni, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, muni=excluded.muni,\"\n \" provider=excluded.provider, failed=excluded.failed, ts=excluded.ts\",\n (key, v[\"lat\"] if v else None, v[\"lng\"] if v else None,\n v[\"muni\"] if v else None, \"ville_nominatim\", 0 if v else 1, time.time()))\n self.con.commit()\n self._villes[k] = v\n return v\n\n def city_refs(self, city: str, allow_api: bool = True) -> list[tuple[float, float]]:\n \"\"\"Points de référence d'une ville : grappes de fiches dignes de\n confiance (n >= CLUSTER_MIN — une par municipalité homonyme) + point\n Nominatim de la ville. Liste vide = ville inconnue (-> bbox seule).\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return []\n refs = [(cl[0], cl[1]) for cl in self._clusters().get(k, [])\n if cl[2] >= CLUSTER_MIN]\n v = self.resolve_ville(city, allow_api=allow_api)\n if v:\n refs.append((v[\"lat\"], v[\"lng\"]))\n return refs\n\n def coords_ok(self, c: tuple[float, float] | None, city: str,\n refs: list[tuple[float, float]] | None = None) -> bool:\n \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM d'au moins\n une référence de la ville annoncée (quand elle en a).\"\"\"\n if c is None or not _in_bbox(*c, _bbox_for(city)):\n return False\n if refs is None:\n refs = self.city_refs(city)\n return not refs or any(_dist_km(c[0], c[1], r[0], r[1]) <= VILLE_RADIUS_KM\n for r in refs)\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis AQ/Nominatim. None si introuvable.\n\n Rigueur : chaque candidat doit être cohérent avec la ville annoncée\n (centroïde <= VILLE_RADIUS_KM). Si la ville annoncée est un secteur\n inconnu d'Adresses Québec, on réessaie avec la municipalité officielle.\n \"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n ref = self.city_reference(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if self.coords_ok(c, city, ref):\n coords = c\n muni = None\n if coords is None:\n # ville annoncée = secteur (« Jonquière (Lac-Kénogami) ») ? AQ ne\n # connaît que les municipalités officielles -> retenter avec elle.\n v = self.resolve_ville(city)\n muni = (v or {}).get(\"muni\")\n if muni and norm_key(muni) != norm_key(city or \"\"):\n c = self._query_adresses_quebec(address, muni)\n if self.coords_ok(c, city, ref):\n coords, provider = c, \"adresses_quebec_muni\"\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city, muni):\n c = self._query_nominatim(params)\n if self.coords_ok(c, city, ref):\n coords = c\n break\n ok = coords is not None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?)\"\n \" ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,\"\n \" lng=excluded.lng, provider=excluded.provider,\"\n \" failed=excluded.failed, ts=excluded.ts\",\n (key, coords[0] if ok else None, coords[1] if ok else None,\n provider, 0 if ok else 1, time.time()))\n self.con.commit()\n return coords if ok else None\n\n\ndef run(limit: int | None = None) -> dict:\n \"\"\"Géocode les annonces actives sans coordonnées, par adresse unique.\n\n `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de\n cache sont gratuits et toujours appliqués).\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0\n ORDER BY address\"\"\").fetchall()\n\n # regrouper par immeuble (adresse normalisée)\n groupes: dict[str, list] = {}\n for r in rows:\n groupes.setdefault(norm_key(r[\"address\"]), []).append(r)\n\n done = failed = requests_made = 0\n for key, members in groupes.items():\n if not key:\n continue\n cached = con.execute(\n \"SELECT failed FROM geocode_cache WHERE address=?\", (key,)).fetchone()\n if cached is None:\n if limit is not None and requests_made >= limit:\n continue\n requests_made += 1\n try:\n coords = geo.resolve(members[0][\"address\"], members[0][\"city\"])\n if coords:\n for r in members:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], r[\"uid\"]))\n done += len(members)\n else:\n # introuvable/hors zone : flag ; jamais de coordonnées bidon\n for r in members:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\",\n (r[\"uid\"],))\n failed += len(members)\n con.commit()\n except sqlite3.OperationalError:\n # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,\n # elle sera reprise au prochain passage — jamais crasher tout le run.\n try:\n con.rollback()\n except sqlite3.Error:\n pass\n time.sleep(1.0)\n continue\n\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed,\n \"unique_addresses\": len(groupes), \"api_requests\": requests_made}\n print(f\"[immo-ka] geocode {stats}\")\n return stats\n\n\nAQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200\nRESCUE_MAX = 150 # rattrapages resolve() max par passe (Nominatim = 1 req/s)\n\n\ndef strip_bad_source_coords(con, listings) -> int:\n \"\"\"Garde d'ingestion : annule les lat/lng fournis par un connecteur quand\n ils contredisent la ville annoncée (> VILLE_RADIUS_KM du centroïde connu).\n Cache seulement (médianes + villes déjà résolues) : aucun appel réseau,\n la synchronisation reste rapide. Retourne le nombre de paires annulées.\"\"\"\n geo = Geocoder(con)\n n = 0\n for lst in listings:\n if lst.lat is None or lst.lng is None or not (lst.city or \"\").strip():\n continue\n ref = geo.city_reference(lst.city, allow_api=False)\n if ref and _dist_km(lst.lat, lst.lng, ref[0], ref[1]) > VILLE_RADIUS_KM:\n lst.lat = lst.lng = None\n n += 1\n return n\n\n\ndef run_batch(limit: int | None = None) -> dict:\n \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de\n milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim).\"\"\"\n con = db.connect()\n geo = Geocoder(con) # pour réutiliser _clean / bbox\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0 ORDER BY address\"\"\").fetchall()\n # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache\n uniq: dict[str, dict] = {}\n for r in rows:\n k = norm_key(r[\"address\"])\n if not k or len(k) < 6:\n continue\n u = uniq.setdefault(k, {\"address\": r[\"address\"], \"city\": r[\"city\"],\n \"members\": []})\n u[\"members\"].append(r[\"uid\"])\n pending = []\n for k, u in uniq.items():\n c = con.execute(\"SELECT lat,lng,failed FROM geocode_cache WHERE address=?\",\n (k,)).fetchone()\n if c is not None and not c[\"failed\"]: # déjà résolu : appliquer direct\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (c[\"lat\"], c[\"lng\"], uid))\n continue\n if c is not None and c[\"failed\"]:\n continue\n pending.append((k, u))\n con.commit()\n if limit is not None:\n pending = pending[:limit]\n\n session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n rescue: list[tuple[str, dict]] = [] # échecs du lot -> resolve() individuel\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n # bbox + cohérence avec le centroïde de la ville annoncée\n if geo.coords_ok(cand, u[\"city\"]):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n con.commit()\n else:\n # pas de verdict tout de suite : resolve() réessaiera avec la\n # municipalité officielle + Nominatim (borné par RESCUE_MAX)\n rescue.append((k, u))\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, à rattraper {len(rescue)})\")\n\n # Rattrapage 1-par-1 des échecs du lot : variantes de municipalité (AQ) puis\n # Nominatim, validées par centroïde. resolve() écrit lui-même le verdict au\n # cache (succès ou échec 30 j) ; au-delà de RESCUE_MAX, on laisse les fiches\n # intactes (ni cache ni flag) -> reprises aux prochains passages.\n rescued = 0\n for k, u in rescue[:RESCUE_MAX]:\n try:\n coords = geo.resolve(u[\"address\"], u[\"city\"])\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n done += len(u[\"members\"])\n rescued += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n con.close()\n stats = {\"geocoded\": done, \"rescued\": rescued, \"failed\": failed,\n \"deferred\": max(0, len(rescue) - RESCUE_MAX),\n \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats\n\n\ndef run_audit(nominatim_budget: int | None = None, apply: bool = True) -> dict:\n \"\"\"Audit de cohérence géographique des fiches DÉJÀ géocodées.\n\n Détecte les coordonnées à plus de VILLE_RADIUS_KM du centroïde de leur\n ville (rue homonyme d'une autre région, geo erroné fourni par la source…),\n puis les remet en file de géocodage : lat/lng annulés, geocode_failed remis\n à 0, entrée de cache purgée. `nominatim_budget` borne les résolutions de\n villes inconnues (1 req/s) ; None = illimité. `apply=False` = rapport seul.\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\").fetchall()\n flagged, villes_inconnues = [], 0\n for r in rows:\n allow = nominatim_budget is None or geo.ville_api_calls < nominatim_budget\n ref = geo.city_reference(r[\"city\"], allow_api=allow)\n if ref is None:\n villes_inconnues += 1\n continue\n d = _dist_km(r[\"lat\"], r[\"lng\"], ref[0], ref[1])\n if d > VILLE_RADIUS_KM:\n flagged.append((r, d))\n if apply:\n for r, d in flagged:\n con.execute(\"DELETE FROM geocode_cache WHERE address=?\",\n (norm_key(r[\"address\"]),))\n con.execute(\"\"\"UPDATE listings SET lat=NULL, lng=NULL,\n geocode_failed=0 WHERE uid=?\"\"\", (r[\"uid\"],))\n con.commit()\n for r, d in flagged[:20]:\n print(f\"[immo-ka] audit: {r['uid']} « {r['address']}, {r['city']} » \"\n f\"à {d:.0f} km de sa ville\")\n con.close()\n stats = {\"verifiees\": len(rows), \"incoherentes\": len(flagged),\n \"villes_inconnues\": villes_inconnues, \"corrigees\": apply}\n print(f\"[immo-ka] geocode-audit {stats}\")\n return stats\n","structuredPatch":[{"oldStart":344,"oldLines":13,"newStart":344,"newLines":13,"lines":[" if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:"," return None # échec récent : ne pas marteler l'API"," ","- ref = self.city_reference(city)","+ refs = self.city_refs(city)"," coords = None"," # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de"," # limite stricte. Nominatim (1 req/s) seulement en repli."," provider = \"adresses_quebec\""," c = self._query_adresses_quebec(address, city)","- if self.coords_ok(c, city, ref):","+ if self.coords_ok(c, city, refs):"," coords = c"," muni = None"," if coords is None:"]},{"oldStart":360,"oldLines":13,"newStart":360,"newLines":13,"lines":[" muni = (v or {}).get(\"muni\")"," if muni and norm_key(muni) != norm_key(city or \"\"):"," c = self._query_adresses_quebec(address, muni)","- if self.coords_ok(c, city, ref):","+ if self.coords_ok(c, city, refs):"," coords, provider = c, \"adresses_quebec_muni\""," if coords is None:"," provider = \"nominatim\""," for params in self._attempts(address, city, muni):"," c = self._query_nominatim(params)","- if self.coords_ok(c, city, ref):","+ if self.coords_ok(c, city, refs):"," coords = c"," break"," ok = coords is not None"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYJmTG8ndxKm3MSeHZZ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_017YN51jfoDqcytNyABkRdVU","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","old_string":" geo = Geocoder(con)\n n = 0\n for lst in listings:\n if lst.lat is None or lst.lng is None or not (lst.city or \"\").strip():\n continue\n ref = geo.city_reference(lst.city, allow_api=False)\n if ref and _dist_km(lst.lat, lst.lng, ref[0], ref[1]) > VILLE_RADIUS_KM:\n lst.lat = lst.lng = None\n n += 1\n return n","new_string":" geo = Geocoder(con)\n n = 0\n for lst in listings:\n if lst.lat is None or lst.lng is None or not (lst.city or \"\").strip():\n continue\n refs = geo.city_refs(lst.city, allow_api=False)\n if refs and not geo.coords_ok((lst.lat, lst.lng), lst.city, refs):\n lst.lat = lst.lng = None\n n += 1\n return n"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1169,"cache_read_input_tokens":114312,"cache_creation":{"ephemeral_5m_input_tokens":1169,"ephemeral_1h_input_tokens":0},"output_tokens":20,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"dff306cf-e4b3-4b16-9ac2-6f83e251788f"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_017YN51jfoDqcytNyABkRdVU","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"c01c9bb0-749a-4a69-a5d7-3eaf8496de99","timestamp":"2026-08-25T13:24:48.893Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","oldString":" geo = Geocoder(con)\n n = 0\n for lst in listings:\n if lst.lat is None or lst.lng is None or not (lst.city or \"\").strip():\n continue\n ref = geo.city_reference(lst.city, allow_api=False)\n if ref and _dist_km(lst.lat, lst.lng, ref[0], ref[1]) > VILLE_RADIUS_KM:\n lst.lat = lst.lng = None\n n += 1\n return n","newString":" geo = Geocoder(con)\n n = 0\n for lst in listings:\n if lst.lat is None or lst.lng is None or not (lst.city or \"\").strip():\n continue\n refs = geo.city_refs(lst.city, allow_api=False)\n if refs and not geo.coords_ok((lst.lat, lst.lng), lst.city, refs):\n lst.lat = lst.lng = None\n n += 1\n return n","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)\n# - cache persistant (table geocode_cache) : une adresse n'est géocodée\n# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce\n# - politesse : 1 requête/seconde max, User-Agent identifiable\n# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# - rigueur : chaque résultat est validé contre le CENTROÏDE de la ville\n# annoncée (médiane des fiches déjà géocodées, sinon Nominatim, en cache) —\n# à plus de VILLE_RADIUS_KM du centroïde, le candidat est rejeté. Corrige\n# la classe de bug « rue homonyme dans une autre ville » (ex. rue des\n# Perdrix de Jonquière géocodée à Saint-Augustin).\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport math\nimport sqlite3\nimport statistics\n\nimport re\nimport time\n\nimport requests\n\nfrom . import db\nfrom .normalize import strip_accents\n\nNOMINATIM_URL = \"https://nominatim.openstreetmap.org/search\"\n# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre\n# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)\nAQ_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/findAddressCandidates\")\nAQ_MIN_SCORE = 75\n# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête\n# User-Agent contient des accents (latin-1)\nUSER_AGENT = \"ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)\"\nREQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s\nREQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte\nRETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours\n\n# Bounding boxes (lat_min, lat_max, lng_min, lng_max)\n_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord\n# et la Gaspésie (expansion provinciale) — même boîte que schema.finalize()\n_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n\n_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n# Validation « rigoureuse » : distance max entre un résultat de géocodage et une\n# référence de la ville annoncée. 40 km tolère les grandes municipalités\n# fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues\n# homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).\n# ⚠ Le Québec compte de nombreuses municipalités HOMONYMES (deux L'Ange-Gardien,\n# deux Saint-Donat, deux Sainte-Félicité…) : la référence n'est donc jamais un\n# centroïde unique mais un ENSEMBLE de grappes de fiches (chaque homonyme garde\n# la sienne) + le point Nominatim de la ville.\nVILLE_RADIUS_KM = 40.0\nCLUSTER_MIN = 3 # une grappe de fiches devient une référence de confiance dès n >= 3\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n\n\ndef _dist_km(lat1: float, lng1: float, lat2: float, lng2: float) -> float:\n \"\"\"Distance haversine en kilomètres.\"\"\"\n p1, p2 = math.radians(lat1), math.radians(lat2)\n a = (math.sin((p2 - p1) / 2) ** 2\n + math.cos(p1) * math.cos(p2) * math.sin(math.radians(lng2 - lng1) / 2) ** 2)\n return 2 * 6371.0 * math.asin(math.sqrt(a))\n\n\ndef norm_key(address: str) -> str:\n \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\"\n s = strip_accents((address or \"\").lower())\n s = re.sub(r\"\\b(?:app?t?|appartement|unite|suite|#)\\.?\\s*[\\w-]+\\b\", \" \", s)\n s = re.sub(r\"[^a-z0-9]+\", \" \", s)\n return re.sub(r\"\\s+\", \" \", s).strip()\n\n\nclass Geocoder:\n def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0\n self._villes: dict[str, dict | None] = {} # norm(ville) -> {lat,lng,muni}\n self._med: dict[str, tuple] | None = None # norm(ville) -> (lat,lng,n)\n self.ville_api_calls = 0 # requêtes Nominatim « ville »\n\n @staticmethod\n def _clean(address: str) -> str:\n \"\"\"Nettoyages qui aident Nominatim sur les adresses québécoises.\"\"\"\n s = address.strip()\n # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique\n s = re.sub(r\"^(\\d+)-(\\d+)\\s\", r\"\\2 \", s)\n # « 6275 et 6375 boulevard X » -> premier civique\n s = re.sub(r\"^(\\d+)\\s+et\\s+\\d+\\s\", r\"\\1 \", s)\n # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu\n s = re.sub(r\"montr[ée]al\\s*-\\s*\", \"\", s, flags=re.I)\n # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau\n s = re.sub(r\",?\\s*(?:bureau|suite|local|app\\.?|apt\\.?)\\s*[\\w-]+\\b\", \"\", s, flags=re.I)\n # « Vanier (Québec) » -> « Vanier, Québec »\n s = re.sub(r\"\\s*\\((qu[ée]bec)\\)\", r\", \\1\", s, flags=re.I)\n # abréviations cardinales : « Rue Salaberry O » -> « Ouest »\n s = re.sub(r\"\\bO\\.?(?=,|\\s*$)\", \"Ouest\", s)\n s = re.sub(r\"\\bE\\.?(?=,|\\s*$)\", \"Est\", s)\n return s\n\n def _build_query(self, address: str, city: str) -> str:\n q = self._clean(address)\n key = strip_accents(q.lower())\n if city and strip_accents(city.lower()) not in key:\n q += f\", {city}\"\n if \"quebec\" not in strip_accents(q.lower()) and \"qc\" not in q.lower():\n q += \", Québec\"\n return q + \", Canada\"\n\n def _query_nominatim(self, params: dict) -> tuple[float, float] | None:\n \"\"\"Une requête Nominatim, throttlée.\"\"\"\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"format\": \"jsonv2\", \"limit\": 1, \"countrycodes\": \"ca\", **params,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None\n if not hits:\n return None\n try:\n return float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n except (KeyError, ValueError):\n return None\n\n def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).\n\n Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE\n pour éviter les correspondances approximatives sur une autre rue.\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"Québec\").strip()\n wait = REQUEST_DELAY_AQ - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(AQ_URL, params={\n \"SingleLine\": f\"{premier}, {ville}\",\n \"f\": \"json\", \"outSR\": 4326, \"maxLocations\": 1,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n cands = resp.json().get(\"candidates\") or []\n except Exception:\n self._last = time.time()\n return None\n if not cands or cands[0].get(\"score\", 0) < AQ_MIN_SCORE:\n return None\n loc = cands[0].get(\"location\") or {}\n try:\n return float(loc[\"y\"]), float(loc[\"x\"])\n except (KeyError, ValueError):\n return None\n\n def _attempts(self, address: str, city: str, muni: str | None = None) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) idem avec la municipalité OFFICIELLE (« Saguenay ») quand la ville\n annoncée est un secteur (« Jonquière (Lac-Kénogami) ») inconnu des API\n 3) recherche libre complète\n 4) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n villes = [ville]\n # premier mot de la ville (« Jonquiere Lac Kenogami » -> « Jonquiere »)\n if \" \" in ville:\n villes.append(ville.split(\" \")[0])\n if muni and norm_key(muni) not in {norm_key(v) for v in villes}:\n villes.append(muni)\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n # ----- références de ville (validation rigoureuse) -----------------------\n def _clusters(self) -> dict[str, list[tuple]]:\n \"\"\"Grappes de coordonnées par ville, depuis les fiches déjà géocodées\n (regroupement glouton, rayon VILLE_RADIUS_KM). Chaque grappe :\n (lat médiane, lng médiane, n). Les municipalités homonymes produisent\n naturellement une grappe chacune — aucune n'écrase l'autre.\"\"\"\n if self._med is None:\n acc: dict[str, list] = {}\n for r in self.con.execute(\n \"\"\"SELECT city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\"):\n acc.setdefault(norm_key(r[\"city\"]), []).append((r[\"lat\"], r[\"lng\"]))\n out: dict[str, list[tuple]] = {}\n for k, pts in acc.items():\n clusters: list[list] = [] # [ [lat_c, lng_c, [points]] ]\n for lat, lng in pts:\n for cl in clusters:\n if _dist_km(lat, lng, cl[0], cl[1]) <= VILLE_RADIUS_KM:\n cl[2].append((lat, lng))\n cl[0] = statistics.median(p[0] for p in cl[2])\n cl[1] = statistics.median(p[1] for p in cl[2])\n break\n else:\n clusters.append([lat, lng, [(lat, lng)]])\n out[k] = [(cl[0], cl[1], len(cl[2])) for cl in clusters]\n self._med = out\n return self._med\n\n def resolve_ville(self, city: str, allow_api: bool = True) -> dict | None:\n \"\"\"Ville -> {lat, lng, muni} (muni = municipalité officielle, ex.\n « Jonquière (Lac-Kénogami) » -> Saguenay). Cache : geocode_cache,\n clé « ville: ». None si irrésoluble.\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n if k in self._villes:\n return self._villes[k]\n key = \"ville:\" + k\n row = self.con.execute(\n \"SELECT lat, lng, muni, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n v = {\"lat\": row[\"lat\"], \"lng\": row[\"lng\"], \"muni\": row[\"muni\"]}\n self._villes[k] = v\n return v\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n self._villes[k] = None\n return None\n if not allow_api:\n return None # pas de mémoire : on réessaiera quand l'API sera permise\n self.ville_api_calls += 1\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n v = None\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"q\": f\"{city}, Québec, Canada\", \"format\": \"jsonv2\", \"limit\": 1,\n \"countrycodes\": \"ca\", \"addressdetails\": 1}, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None # erreur réseau : ne pas cacher un échec définitif\n if hits:\n try:\n lat, lng = float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n if _in_bbox(lat, lng, _BBOX_SUD_QC):\n a = hits[0].get(\"address\") or {}\n muni = (a.get(\"city\") or a.get(\"town\") or a.get(\"village\")\n or a.get(\"municipality\"))\n v = {\"lat\": lat, \"lng\": lng, \"muni\": muni}\n except (KeyError, ValueError, TypeError):\n v = None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, muni, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, muni=excluded.muni,\"\n \" provider=excluded.provider, failed=excluded.failed, ts=excluded.ts\",\n (key, v[\"lat\"] if v else None, v[\"lng\"] if v else None,\n v[\"muni\"] if v else None, \"ville_nominatim\", 0 if v else 1, time.time()))\n self.con.commit()\n self._villes[k] = v\n return v\n\n def city_refs(self, city: str, allow_api: bool = True) -> list[tuple[float, float]]:\n \"\"\"Points de référence d'une ville : grappes de fiches dignes de\n confiance (n >= CLUSTER_MIN — une par municipalité homonyme) + point\n Nominatim de la ville. Liste vide = ville inconnue (-> bbox seule).\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return []\n refs = [(cl[0], cl[1]) for cl in self._clusters().get(k, [])\n if cl[2] >= CLUSTER_MIN]\n v = self.resolve_ville(city, allow_api=allow_api)\n if v:\n refs.append((v[\"lat\"], v[\"lng\"]))\n return refs\n\n def coords_ok(self, c: tuple[float, float] | None, city: str,\n refs: list[tuple[float, float]] | None = None) -> bool:\n \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM d'au moins\n une référence de la ville annoncée (quand elle en a).\"\"\"\n if c is None or not _in_bbox(*c, _bbox_for(city)):\n return False\n if refs is None:\n refs = self.city_refs(city)\n return not refs or any(_dist_km(c[0], c[1], r[0], r[1]) <= VILLE_RADIUS_KM\n for r in refs)\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis AQ/Nominatim. None si introuvable.\n\n Rigueur : chaque candidat doit être cohérent avec la ville annoncée\n (centroïde <= VILLE_RADIUS_KM). Si la ville annoncée est un secteur\n inconnu d'Adresses Québec, on réessaie avec la municipalité officielle.\n \"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n refs = self.city_refs(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if self.coords_ok(c, city, refs):\n coords = c\n muni = None\n if coords is None:\n # ville annoncée = secteur (« Jonquière (Lac-Kénogami) ») ? AQ ne\n # connaît que les municipalités officielles -> retenter avec elle.\n v = self.resolve_ville(city)\n muni = (v or {}).get(\"muni\")\n if muni and norm_key(muni) != norm_key(city or \"\"):\n c = self._query_adresses_quebec(address, muni)\n if self.coords_ok(c, city, refs):\n coords, provider = c, \"adresses_quebec_muni\"\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city, muni):\n c = self._query_nominatim(params)\n if self.coords_ok(c, city, refs):\n coords = c\n break\n ok = coords is not None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?)\"\n \" ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,\"\n \" lng=excluded.lng, provider=excluded.provider,\"\n \" failed=excluded.failed, ts=excluded.ts\",\n (key, coords[0] if ok else None, coords[1] if ok else None,\n provider, 0 if ok else 1, time.time()))\n self.con.commit()\n return coords if ok else None\n\n\ndef run(limit: int | None = None) -> dict:\n \"\"\"Géocode les annonces actives sans coordonnées, par adresse unique.\n\n `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de\n cache sont gratuits et toujours appliqués).\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0\n ORDER BY address\"\"\").fetchall()\n\n # regrouper par immeuble (adresse normalisée)\n groupes: dict[str, list] = {}\n for r in rows:\n groupes.setdefault(norm_key(r[\"address\"]), []).append(r)\n\n done = failed = requests_made = 0\n for key, members in groupes.items():\n if not key:\n continue\n cached = con.execute(\n \"SELECT failed FROM geocode_cache WHERE address=?\", (key,)).fetchone()\n if cached is None:\n if limit is not None and requests_made >= limit:\n continue\n requests_made += 1\n try:\n coords = geo.resolve(members[0][\"address\"], members[0][\"city\"])\n if coords:\n for r in members:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], r[\"uid\"]))\n done += len(members)\n else:\n # introuvable/hors zone : flag ; jamais de coordonnées bidon\n for r in members:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\",\n (r[\"uid\"],))\n failed += len(members)\n con.commit()\n except sqlite3.OperationalError:\n # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,\n # elle sera reprise au prochain passage — jamais crasher tout le run.\n try:\n con.rollback()\n except sqlite3.Error:\n pass\n time.sleep(1.0)\n continue\n\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed,\n \"unique_addresses\": len(groupes), \"api_requests\": requests_made}\n print(f\"[immo-ka] geocode {stats}\")\n return stats\n\n\nAQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200\nRESCUE_MAX = 150 # rattrapages resolve() max par passe (Nominatim = 1 req/s)\n\n\ndef strip_bad_source_coords(con, listings) -> int:\n \"\"\"Garde d'ingestion : annule les lat/lng fournis par un connecteur quand\n ils contredisent la ville annoncée (> VILLE_RADIUS_KM du centroïde connu).\n Cache seulement (médianes + villes déjà résolues) : aucun appel réseau,\n la synchronisation reste rapide. Retourne le nombre de paires annulées.\"\"\"\n geo = Geocoder(con)\n n = 0\n for lst in listings:\n if lst.lat is None or lst.lng is None or not (lst.city or \"\").strip():\n continue\n ref = geo.city_reference(lst.city, allow_api=False)\n if ref and _dist_km(lst.lat, lst.lng, ref[0], ref[1]) > VILLE_RADIUS_KM:\n lst.lat = lst.lng = None\n n += 1\n return n\n\n\ndef run_batch(limit: int | None = None) -> dict:\n \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de\n milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim).\"\"\"\n con = db.connect()\n geo = Geocoder(con) # pour réutiliser _clean / bbox\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0 ORDER BY address\"\"\").fetchall()\n # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache\n uniq: dict[str, dict] = {}\n for r in rows:\n k = norm_key(r[\"address\"])\n if not k or len(k) < 6:\n continue\n u = uniq.setdefault(k, {\"address\": r[\"address\"], \"city\": r[\"city\"],\n \"members\": []})\n u[\"members\"].append(r[\"uid\"])\n pending = []\n for k, u in uniq.items():\n c = con.execute(\"SELECT lat,lng,failed FROM geocode_cache WHERE address=?\",\n (k,)).fetchone()\n if c is not None and not c[\"failed\"]: # déjà résolu : appliquer direct\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (c[\"lat\"], c[\"lng\"], uid))\n continue\n if c is not None and c[\"failed\"]:\n continue\n pending.append((k, u))\n con.commit()\n if limit is not None:\n pending = pending[:limit]\n\n session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n rescue: list[tuple[str, dict]] = [] # échecs du lot -> resolve() individuel\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n # bbox + cohérence avec le centroïde de la ville annoncée\n if geo.coords_ok(cand, u[\"city\"]):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n con.commit()\n else:\n # pas de verdict tout de suite : resolve() réessaiera avec la\n # municipalité officielle + Nominatim (borné par RESCUE_MAX)\n rescue.append((k, u))\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, à rattraper {len(rescue)})\")\n\n # Rattrapage 1-par-1 des échecs du lot : variantes de municipalité (AQ) puis\n # Nominatim, validées par centroïde. resolve() écrit lui-même le verdict au\n # cache (succès ou échec 30 j) ; au-delà de RESCUE_MAX, on laisse les fiches\n # intactes (ni cache ni flag) -> reprises aux prochains passages.\n rescued = 0\n for k, u in rescue[:RESCUE_MAX]:\n try:\n coords = geo.resolve(u[\"address\"], u[\"city\"])\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n done += len(u[\"members\"])\n rescued += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n con.close()\n stats = {\"geocoded\": done, \"rescued\": rescued, \"failed\": failed,\n \"deferred\": max(0, len(rescue) - RESCUE_MAX),\n \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats\n\n\ndef run_audit(nominatim_budget: int | None = None, apply: bool = True) -> dict:\n \"\"\"Audit de cohérence géographique des fiches DÉJÀ géocodées.\n\n Détecte les coordonnées à plus de VILLE_RADIUS_KM du centroïde de leur\n ville (rue homonyme d'une autre région, geo erroné fourni par la source…),\n puis les remet en file de géocodage : lat/lng annulés, geocode_failed remis\n à 0, entrée de cache purgée. `nominatim_budget` borne les résolutions de\n villes inconnues (1 req/s) ; None = illimité. `apply=False` = rapport seul.\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\").fetchall()\n flagged, villes_inconnues = [], 0\n for r in rows:\n allow = nominatim_budget is None or geo.ville_api_calls < nominatim_budget\n ref = geo.city_reference(r[\"city\"], allow_api=allow)\n if ref is None:\n villes_inconnues += 1\n continue\n d = _dist_km(r[\"lat\"], r[\"lng\"], ref[0], ref[1])\n if d > VILLE_RADIUS_KM:\n flagged.append((r, d))\n if apply:\n for r, d in flagged:\n con.execute(\"DELETE FROM geocode_cache WHERE address=?\",\n (norm_key(r[\"address\"]),))\n con.execute(\"\"\"UPDATE listings SET lat=NULL, lng=NULL,\n geocode_failed=0 WHERE uid=?\"\"\", (r[\"uid\"],))\n con.commit()\n for r, d in flagged[:20]:\n print(f\"[immo-ka] audit: {r['uid']} « {r['address']}, {r['city']} » \"\n f\"à {d:.0f} km de sa ville\")\n con.close()\n stats = {\"verifiees\": len(rows), \"incoherentes\": len(flagged),\n \"villes_inconnues\": villes_inconnues, \"corrigees\": apply}\n print(f\"[immo-ka] geocode-audit {stats}\")\n return stats\n","structuredPatch":[{"oldStart":458,"oldLines":8,"newStart":458,"newLines":8,"lines":[" for lst in listings:"," if lst.lat is None or lst.lng is None or not (lst.city or \"\").strip():"," continue","- ref = geo.city_reference(lst.city, allow_api=False)","- if ref and _dist_km(lst.lat, lst.lng, ref[0], ref[1]) > VILLE_RADIUS_KM:","+ refs = geo.city_refs(lst.city, allow_api=False)","+ if refs and not geo.coords_ok((lst.lat, lst.lng), lst.city, refs):"," lst.lat = lst.lng = None"," n += 1"," return n"]}],"userModified":false,"replaceAll":false}}} 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{"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYKsHXU2XekobQo3m6H","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1603,"cache_read_input_tokens":115481,"cache_creation":{"ephemeral_5m_input_tokens":1603,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"006bd872-f644-43c3-b0d4-619a5d14f4c5"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYKsHXU2XekobQo3m6H","type":"message","role":"assistant","content":[{"type":"text","text":"Maintenant la réécriture de `run_audit` avec la logique multi-références et budget."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1603,"cache_read_input_tokens":115481,"cache_creation":{"ephemeral_5m_input_tokens":1603,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"daec890f-9cd4-4ec6-938c-b2a372e8dd74"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYKsHXU2XekobQo3m6H","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01X3uji3riq7LfAMaiagbKet","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","old_string":" Détecte les coordonnées à plus de VILLE_RADIUS_KM du centroïde de leur\n ville (rue homonyme d'une autre région, geo erroné fourni par la source…),\n puis les remet en file de géocodage : lat/lng annulés, geocode_failed remis\n à 0, entrée de cache purgée. `nominatim_budget` borne les résolutions de\n villes inconnues (1 req/s) ; None = illimité. `apply=False` = rapport seul.\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\").fetchall()\n flagged, villes_inconnues = [], 0\n for r in rows:\n allow = nominatim_budget is None or geo.ville_api_calls < nominatim_budget\n ref = geo.city_reference(r[\"city\"], allow_api=allow)\n if ref is None:\n villes_inconnues += 1\n continue\n d = _dist_km(r[\"lat\"], r[\"lng\"], ref[0], ref[1])\n if d > VILLE_RADIUS_KM:\n flagged.append((r, d))\n if apply:\n for r, d in flagged:\n con.execute(\"DELETE FROM geocode_cache WHERE address=?\",\n (norm_key(r[\"address\"]),))\n con.execute(\"\"\"UPDATE listings SET lat=NULL, lng=NULL,\n geocode_failed=0 WHERE uid=?\"\"\", (r[\"uid\"],))\n con.commit()\n for r, d in flagged[:20]:\n print(f\"[immo-ka] audit: {r['uid']} « {r['address']}, {r['city']} » \"\n f\"à {d:.0f} km de sa ville\")\n con.close()\n stats = {\"verifiees\": len(rows), \"incoherentes\": len(flagged),\n \"villes_inconnues\": villes_inconnues, \"corrigees\": apply}\n print(f\"[immo-ka] geocode-audit {stats}\")\n return stats","new_string":" Détecte les coordonnées à plus de VILLE_RADIUS_KM de TOUTE référence de\n leur ville — grappes de fiches (une par municipalité homonyme) + point\n Nominatim — puis les remet en file de géocodage : lat/lng annulés,\n geocode_failed remis à 0, entrée de cache purgée. Une fiche n'est JAMAIS\n flaguée sans référence indépendante confirmant l'incohérence (les\n homonymes et villes irrésolues sont épargnés). `nominatim_budget` borne\n les résolutions de villes inconnues (1 req/s) ; None = illimité.\n `apply=False` = rapport seul.\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\").fetchall()\n flagged, inconnues, reportees = [], 0, 0\n for r in rows:\n k = norm_key(r[\"city\"])\n clusters = [(cl[0], cl[1]) for cl in geo._clusters().get(k, [])\n if cl[2] >= CLUSTER_MIN]\n dists = [_dist_km(r[\"lat\"], r[\"lng\"], c[0], c[1]) for c in clusters]\n if dists and min(dists) <= VILLE_RADIUS_KM:\n continue # cohérente avec une grappe de sa ville\n budget_ok = nominatim_budget is None or geo.ville_api_calls < nominatim_budget\n v = geo.resolve_ville(r[\"city\"], allow_api=budget_ok)\n if v is not None:\n d = _dist_km(r[\"lat\"], r[\"lng\"], v[\"lat\"], v[\"lng\"])\n if d <= VILLE_RADIUS_KM:\n continue # cohérente avec le point Nominatim de la ville\n flagged.append((r, min(dists + [d])))\n elif not clusters:\n inconnues += 1 # aucune référence : on ne flague pas\n elif not budget_ok:\n reportees += 1 # ville pas encore résolue : prochaine passe\n else:\n flagged.append((r, min(dists))) # ville irrésoluble, grappes loin\n if apply:\n for r, d in flagged:\n con.execute(\"DELETE FROM geocode_cache WHERE address=?\",\n (norm_key(r[\"address\"]),))\n con.execute(\"\"\"UPDATE listings SET lat=NULL, lng=NULL,\n geocode_failed=0 WHERE uid=?\"\"\", (r[\"uid\"],))\n con.commit()\n for r, d in flagged[:20]:\n print(f\"[immo-ka] audit: {r['uid']} « {r['address']}, {r['city']} » \"\n f\"à {d:.0f} km de sa ville\")\n con.close()\n stats = {\"verifiees\": len(rows), \"incoherentes\": len(flagged),\n \"villes_inconnues\": inconnues, \"reportees\": reportees,\n \"corrigees\": apply}\n print(f\"[immo-ka] geocode-audit {stats}\")\n return stats"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1603,"cache_read_input_tokens":115481,"cache_creation":{"ephemeral_5m_input_tokens":1603,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"6516a78c-3b98-4c13-930b-a78af588c741"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01X3uji3riq7LfAMaiagbKet","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"6a9dc1d2-bd39-45b6-8133-6f966602d1ce","timestamp":"2026-08-25T13:25:20.640Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/geocode.py","oldString":" Détecte les coordonnées à plus de VILLE_RADIUS_KM du centroïde de leur\n ville (rue homonyme d'une autre région, geo erroné fourni par la source…),\n puis les remet en file de géocodage : lat/lng annulés, geocode_failed remis\n à 0, entrée de cache purgée. `nominatim_budget` borne les résolutions de\n villes inconnues (1 req/s) ; None = illimité. `apply=False` = rapport seul.\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\").fetchall()\n flagged, villes_inconnues = [], 0\n for r in rows:\n allow = nominatim_budget is None or geo.ville_api_calls < nominatim_budget\n ref = geo.city_reference(r[\"city\"], allow_api=allow)\n if ref is None:\n villes_inconnues += 1\n continue\n d = _dist_km(r[\"lat\"], r[\"lng\"], ref[0], ref[1])\n if d > VILLE_RADIUS_KM:\n flagged.append((r, d))\n if apply:\n for r, d in flagged:\n con.execute(\"DELETE FROM geocode_cache WHERE address=?\",\n (norm_key(r[\"address\"]),))\n con.execute(\"\"\"UPDATE listings SET lat=NULL, lng=NULL,\n geocode_failed=0 WHERE uid=?\"\"\", (r[\"uid\"],))\n con.commit()\n for r, d in flagged[:20]:\n print(f\"[immo-ka] audit: {r['uid']} « {r['address']}, {r['city']} » \"\n f\"à {d:.0f} km de sa ville\")\n con.close()\n stats = {\"verifiees\": len(rows), \"incoherentes\": len(flagged),\n \"villes_inconnues\": villes_inconnues, \"corrigees\": apply}\n print(f\"[immo-ka] geocode-audit {stats}\")\n return stats","newString":" Détecte les coordonnées à plus de VILLE_RADIUS_KM de TOUTE référence de\n leur ville — grappes de fiches (une par municipalité homonyme) + point\n Nominatim — puis les remet en file de géocodage : lat/lng annulés,\n geocode_failed remis à 0, entrée de cache purgée. Une fiche n'est JAMAIS\n flaguée sans référence indépendante confirmant l'incohérence (les\n homonymes et villes irrésolues sont épargnés). `nominatim_budget` borne\n les résolutions de villes inconnues (1 req/s) ; None = illimité.\n `apply=False` = rapport seul.\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\").fetchall()\n flagged, inconnues, reportees = [], 0, 0\n for r in rows:\n k = norm_key(r[\"city\"])\n clusters = [(cl[0], cl[1]) for cl in geo._clusters().get(k, [])\n if cl[2] >= CLUSTER_MIN]\n dists = [_dist_km(r[\"lat\"], r[\"lng\"], c[0], c[1]) for c in clusters]\n if dists and min(dists) <= VILLE_RADIUS_KM:\n continue # cohérente avec une grappe de sa ville\n budget_ok = nominatim_budget is None or geo.ville_api_calls < nominatim_budget\n v = geo.resolve_ville(r[\"city\"], allow_api=budget_ok)\n if v is not None:\n d = _dist_km(r[\"lat\"], r[\"lng\"], v[\"lat\"], v[\"lng\"])\n if d <= VILLE_RADIUS_KM:\n continue # cohérente avec le point Nominatim de la ville\n flagged.append((r, min(dists + [d])))\n elif not clusters:\n inconnues += 1 # aucune référence : on ne flague pas\n elif not budget_ok:\n reportees += 1 # ville pas encore résolue : prochaine passe\n else:\n flagged.append((r, min(dists))) # ville irrésoluble, grappes loin\n if apply:\n for r, d in flagged:\n con.execute(\"DELETE FROM geocode_cache WHERE address=?\",\n (norm_key(r[\"address\"]),))\n con.execute(\"\"\"UPDATE listings SET lat=NULL, lng=NULL,\n geocode_failed=0 WHERE uid=?\"\"\", (r[\"uid\"],))\n con.commit()\n for r, d in flagged[:20]:\n print(f\"[immo-ka] audit: {r['uid']} « {r['address']}, {r['city']} » \"\n f\"à {d:.0f} km de sa ville\")\n con.close()\n stats = {\"verifiees\": len(rows), \"incoherentes\": len(flagged),\n \"villes_inconnues\": inconnues, \"reportees\": reportees,\n \"corrigees\": apply}\n print(f\"[immo-ka] geocode-audit {stats}\")\n return stats","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)\n# - cache persistant (table geocode_cache) : une adresse n'est géocodée\n# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce\n# - politesse : 1 requête/seconde max, User-Agent identifiable\n# - validation : les coordonnées doivent tomber dans la région attendue\n# (bounding box par ville), sinon flag geocode_failed — jamais de\n# coordonnées bidon\n# - rigueur : chaque résultat est validé contre le CENTROÏDE de la ville\n# annoncée (médiane des fiches déjà géocodées, sinon Nominatim, en cache) —\n# à plus de VILLE_RADIUS_KM du centroïde, le candidat est rejeté. Corrige\n# la classe de bug « rue homonyme dans une autre ville » (ex. rue des\n# Perdrix de Jonquière géocodée à Saint-Augustin).\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport math\nimport sqlite3\nimport statistics\n\nimport re\nimport time\n\nimport requests\n\nfrom . import db\nfrom .normalize import strip_accents\n\nNOMINATIM_URL = \"https://nominatim.openstreetmap.org/search\"\n# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre\n# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)\nAQ_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/findAddressCandidates\")\nAQ_MIN_SCORE = 75\n# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête\n# User-Agent contient des accents (latin-1)\nUSER_AGENT = \"ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)\"\nREQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s\nREQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte\nRETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours\n\n# Bounding boxes (lat_min, lat_max, lng_min, lng_max)\n_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin\n# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord\n# et la Gaspésie (expansion provinciale) — même boîte que schema.finalize()\n_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)\n\n_VILLES_QUEBEC = {\"quebec\", \"levis\", \"saint-augustin-de-desmaures\",\n \"l'ancienne-lorette\", \"ancienne-lorette\"}\n\n# Validation « rigoureuse » : distance max entre un résultat de géocodage et une\n# référence de la ville annoncée. 40 km tolère les grandes municipalités\n# fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues\n# homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).\n# ⚠ Le Québec compte de nombreuses municipalités HOMONYMES (deux L'Ange-Gardien,\n# deux Saint-Donat, deux Sainte-Félicité…) : la référence n'est donc jamais un\n# centroïde unique mais un ENSEMBLE de grappes de fiches (chaque homonyme garde\n# la sienne) + le point Nominatim de la ville.\nVILLE_RADIUS_KM = 40.0\nCLUSTER_MIN = 3 # une grappe de fiches devient une référence de confiance dès n >= 3\n\n\ndef _bbox_for(city: str) -> tuple[float, float, float, float]:\n key = strip_accents((city or \"\").strip().lower())\n return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_SUD_QC\n\n\ndef _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:\n return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]\n\n\ndef _dist_km(lat1: float, lng1: float, lat2: float, lng2: float) -> float:\n \"\"\"Distance haversine en kilomètres.\"\"\"\n p1, p2 = math.radians(lat1), math.radians(lat2)\n a = (math.sin((p2 - p1) / 2) ** 2\n + math.cos(p1) * math.cos(p2) * math.sin(math.radians(lng2 - lng1) / 2) ** 2)\n return 2 * 6371.0 * math.asin(math.sqrt(a))\n\n\ndef norm_key(address: str) -> str:\n \"\"\"Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.).\"\"\"\n s = strip_accents((address or \"\").lower())\n s = re.sub(r\"\\b(?:app?t?|appartement|unite|suite|#)\\.?\\s*[\\w-]+\\b\", \" \", s)\n s = re.sub(r\"[^a-z0-9]+\", \" \", s)\n return re.sub(r\"\\s+\", \" \", s).strip()\n\n\nclass Geocoder:\n def __init__(self, con) -> None:\n self.con = con\n self.session = requests.Session()\n self.session.headers[\"User-Agent\"] = USER_AGENT\n self._last = 0.0\n self._villes: dict[str, dict | None] = {} # norm(ville) -> {lat,lng,muni}\n self._med: dict[str, tuple] | None = None # norm(ville) -> (lat,lng,n)\n self.ville_api_calls = 0 # requêtes Nominatim « ville »\n\n @staticmethod\n def _clean(address: str) -> str:\n \"\"\"Nettoyages qui aident Nominatim sur les adresses québécoises.\"\"\"\n s = address.strip()\n # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique\n s = re.sub(r\"^(\\d+)-(\\d+)\\s\", r\"\\2 \", s)\n # « 6275 et 6375 boulevard X » -> premier civique\n s = re.sub(r\"^(\\d+)\\s+et\\s+\\d+\\s\", r\"\\1 \", s)\n # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu\n s = re.sub(r\"montr[ée]al\\s*-\\s*\", \"\", s, flags=re.I)\n # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau\n s = re.sub(r\",?\\s*(?:bureau|suite|local|app\\.?|apt\\.?)\\s*[\\w-]+\\b\", \"\", s, flags=re.I)\n # « Vanier (Québec) » -> « Vanier, Québec »\n s = re.sub(r\"\\s*\\((qu[ée]bec)\\)\", r\", \\1\", s, flags=re.I)\n # abréviations cardinales : « Rue Salaberry O » -> « Ouest »\n s = re.sub(r\"\\bO\\.?(?=,|\\s*$)\", \"Ouest\", s)\n s = re.sub(r\"\\bE\\.?(?=,|\\s*$)\", \"Est\", s)\n return s\n\n def _build_query(self, address: str, city: str) -> str:\n q = self._clean(address)\n key = strip_accents(q.lower())\n if city and strip_accents(city.lower()) not in key:\n q += f\", {city}\"\n if \"quebec\" not in strip_accents(q.lower()) and \"qc\" not in q.lower():\n q += \", Québec\"\n return q + \", Canada\"\n\n def _query_nominatim(self, params: dict) -> tuple[float, float] | None:\n \"\"\"Une requête Nominatim, throttlée.\"\"\"\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"format\": \"jsonv2\", \"limit\": 1, \"countrycodes\": \"ca\", **params,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None\n if not hits:\n return None\n try:\n return float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n except (KeyError, ValueError):\n return None\n\n def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).\n\n Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE\n pour éviter les correspondances approximatives sur une autre rue.\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"Québec\").strip()\n wait = REQUEST_DELAY_AQ - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n try:\n resp = self.session.get(AQ_URL, params={\n \"SingleLine\": f\"{premier}, {ville}\",\n \"f\": \"json\", \"outSR\": 4326, \"maxLocations\": 1,\n }, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n cands = resp.json().get(\"candidates\") or []\n except Exception:\n self._last = time.time()\n return None\n if not cands or cands[0].get(\"score\", 0) < AQ_MIN_SCORE:\n return None\n loc = cands[0].get(\"location\") or {}\n try:\n return float(loc[\"y\"]), float(loc[\"x\"])\n except (KeyError, ValueError):\n return None\n\n def _attempts(self, address: str, city: str, muni: str | None = None) -> list[dict]:\n \"\"\"Stratégies de requête, de la plus précise à la moins précise.\n\n 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)\n 2) idem avec la municipalité OFFICIELLE (« Saguenay ») quand la ville\n annoncée est un secteur (« Jonquière (Lac-Kénogami) ») inconnu des API\n 3) recherche libre complète\n 4) structurée rue seule -> centroïde de rue (repli acceptable pour la\n carte quand le numéro civique est absent d'OpenStreetMap)\n \"\"\"\n premier = self._clean(address).split(\",\")[0].strip()\n ville = (city or \"\").strip()\n if not ville:\n k = strip_accents(address.lower())\n ville = \"Lévis\" if \"levis\" in k else \"Québec\"\n villes = [ville]\n # premier mot de la ville (« Jonquiere Lac Kenogami » -> « Jonquiere »)\n if \" \" in ville:\n villes.append(ville.split(\" \")[0])\n if muni and norm_key(muni) not in {norm_key(v) for v in villes}:\n villes.append(muni)\n\n tries: list[dict] = []\n m = re.match(r\"^(\\d+)[,\\s]+(.{4,})$\", premier)\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": f\"{m.group(1)} {m.group(2)}\", **commun})\n tries.append({\"q\": self._build_query(address, city)})\n for v in villes:\n commun = {\"city\": v, \"state\": \"Québec\", \"country\": \"Canada\"}\n if m:\n tries.append({\"street\": m.group(2), **commun})\n return tries\n\n # ----- références de ville (validation rigoureuse) -----------------------\n def _clusters(self) -> dict[str, list[tuple]]:\n \"\"\"Grappes de coordonnées par ville, depuis les fiches déjà géocodées\n (regroupement glouton, rayon VILLE_RADIUS_KM). Chaque grappe :\n (lat médiane, lng médiane, n). Les municipalités homonymes produisent\n naturellement une grappe chacune — aucune n'écrase l'autre.\"\"\"\n if self._med is None:\n acc: dict[str, list] = {}\n for r in self.con.execute(\n \"\"\"SELECT city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\"):\n acc.setdefault(norm_key(r[\"city\"]), []).append((r[\"lat\"], r[\"lng\"]))\n out: dict[str, list[tuple]] = {}\n for k, pts in acc.items():\n clusters: list[list] = [] # [ [lat_c, lng_c, [points]] ]\n for lat, lng in pts:\n for cl in clusters:\n if _dist_km(lat, lng, cl[0], cl[1]) <= VILLE_RADIUS_KM:\n cl[2].append((lat, lng))\n cl[0] = statistics.median(p[0] for p in cl[2])\n cl[1] = statistics.median(p[1] for p in cl[2])\n break\n else:\n clusters.append([lat, lng, [(lat, lng)]])\n out[k] = [(cl[0], cl[1], len(cl[2])) for cl in clusters]\n self._med = out\n return self._med\n\n def resolve_ville(self, city: str, allow_api: bool = True) -> dict | None:\n \"\"\"Ville -> {lat, lng, muni} (muni = municipalité officielle, ex.\n « Jonquière (Lac-Kénogami) » -> Saguenay). Cache : geocode_cache,\n clé « ville: ». None si irrésoluble.\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return None\n if k in self._villes:\n return self._villes[k]\n key = \"ville:\" + k\n row = self.con.execute(\n \"SELECT lat, lng, muni, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n v = {\"lat\": row[\"lat\"], \"lng\": row[\"lng\"], \"muni\": row[\"muni\"]}\n self._villes[k] = v\n return v\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n self._villes[k] = None\n return None\n if not allow_api:\n return None # pas de mémoire : on réessaiera quand l'API sera permise\n self.ville_api_calls += 1\n wait = REQUEST_DELAY - (time.time() - self._last)\n if wait > 0:\n time.sleep(wait)\n v = None\n try:\n resp = self.session.get(NOMINATIM_URL, params={\n \"q\": f\"{city}, Québec, Canada\", \"format\": \"jsonv2\", \"limit\": 1,\n \"countrycodes\": \"ca\", \"addressdetails\": 1}, timeout=20)\n self._last = time.time()\n resp.raise_for_status()\n hits = resp.json()\n except Exception:\n self._last = time.time()\n return None # erreur réseau : ne pas cacher un échec définitif\n if hits:\n try:\n lat, lng = float(hits[0][\"lat\"]), float(hits[0][\"lon\"])\n if _in_bbox(lat, lng, _BBOX_SUD_QC):\n a = hits[0].get(\"address\") or {}\n muni = (a.get(\"city\") or a.get(\"town\") or a.get(\"village\")\n or a.get(\"municipality\"))\n v = {\"lat\": lat, \"lng\": lng, \"muni\": muni}\n except (KeyError, ValueError, TypeError):\n v = None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, muni, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, muni=excluded.muni,\"\n \" provider=excluded.provider, failed=excluded.failed, ts=excluded.ts\",\n (key, v[\"lat\"] if v else None, v[\"lng\"] if v else None,\n v[\"muni\"] if v else None, \"ville_nominatim\", 0 if v else 1, time.time()))\n self.con.commit()\n self._villes[k] = v\n return v\n\n def city_refs(self, city: str, allow_api: bool = True) -> list[tuple[float, float]]:\n \"\"\"Points de référence d'une ville : grappes de fiches dignes de\n confiance (n >= CLUSTER_MIN — une par municipalité homonyme) + point\n Nominatim de la ville. Liste vide = ville inconnue (-> bbox seule).\"\"\"\n k = norm_key(city or \"\")\n if not k:\n return []\n refs = [(cl[0], cl[1]) for cl in self._clusters().get(k, [])\n if cl[2] >= CLUSTER_MIN]\n v = self.resolve_ville(city, allow_api=allow_api)\n if v:\n refs.append((v[\"lat\"], v[\"lng\"]))\n return refs\n\n def coords_ok(self, c: tuple[float, float] | None, city: str,\n refs: list[tuple[float, float]] | None = None) -> bool:\n \"\"\"Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM d'au moins\n une référence de la ville annoncée (quand elle en a).\"\"\"\n if c is None or not _in_bbox(*c, _bbox_for(city)):\n return False\n if refs is None:\n refs = self.city_refs(city)\n return not refs or any(_dist_km(c[0], c[1], r[0], r[1]) <= VILLE_RADIUS_KM\n for r in refs)\n\n def resolve(self, address: str, city: str) -> tuple[float, float] | None:\n \"\"\"Adresse -> (lat, lng), via cache puis AQ/Nominatim. None si introuvable.\n\n Rigueur : chaque candidat doit être cohérent avec la ville annoncée\n (centroïde <= VILLE_RADIUS_KM). Si la ville annoncée est un secteur\n inconnu d'Adresses Québec, on réessaie avec la municipalité officielle.\n \"\"\"\n key = norm_key(address)\n if not key or len(key) < 6:\n return None\n row = self.con.execute(\n \"SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?\",\n (key,)).fetchone()\n if row is not None:\n if not row[\"failed\"]:\n return (row[\"lat\"], row[\"lng\"])\n if time.time() - (row[\"ts\"] or 0) < RETRY_FAILED_AFTER:\n return None # échec récent : ne pas marteler l'API\n\n refs = self.city_refs(city)\n coords = None\n # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de\n # limite stricte. Nominatim (1 req/s) seulement en repli.\n provider = \"adresses_quebec\"\n c = self._query_adresses_quebec(address, city)\n if self.coords_ok(c, city, refs):\n coords = c\n muni = None\n if coords is None:\n # ville annoncée = secteur (« Jonquière (Lac-Kénogami) ») ? AQ ne\n # connaît que les municipalités officielles -> retenter avec elle.\n v = self.resolve_ville(city)\n muni = (v or {}).get(\"muni\")\n if muni and norm_key(muni) != norm_key(city or \"\"):\n c = self._query_adresses_quebec(address, muni)\n if self.coords_ok(c, city, refs):\n coords, provider = c, \"adresses_quebec_muni\"\n if coords is None:\n provider = \"nominatim\"\n for params in self._attempts(address, city, muni):\n c = self._query_nominatim(params)\n if self.coords_ok(c, city, refs):\n coords = c\n break\n ok = coords is not None\n self.con.execute(\n \"INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)\"\n \" VALUES (?,?,?,?,?,?)\"\n \" ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,\"\n \" lng=excluded.lng, provider=excluded.provider,\"\n \" failed=excluded.failed, ts=excluded.ts\",\n (key, coords[0] if ok else None, coords[1] if ok else None,\n provider, 0 if ok else 1, time.time()))\n self.con.commit()\n return coords if ok else None\n\n\ndef run(limit: int | None = None) -> dict:\n \"\"\"Géocode les annonces actives sans coordonnées, par adresse unique.\n\n `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de\n cache sont gratuits et toujours appliqués).\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0\n ORDER BY address\"\"\").fetchall()\n\n # regrouper par immeuble (adresse normalisée)\n groupes: dict[str, list] = {}\n for r in rows:\n groupes.setdefault(norm_key(r[\"address\"]), []).append(r)\n\n done = failed = requests_made = 0\n for key, members in groupes.items():\n if not key:\n continue\n cached = con.execute(\n \"SELECT failed FROM geocode_cache WHERE address=?\", (key,)).fetchone()\n if cached is None:\n if limit is not None and requests_made >= limit:\n continue\n requests_made += 1\n try:\n coords = geo.resolve(members[0][\"address\"], members[0][\"city\"])\n if coords:\n for r in members:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], r[\"uid\"]))\n done += len(members)\n else:\n # introuvable/hors zone : flag ; jamais de coordonnées bidon\n for r in members:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\",\n (r[\"uid\"],))\n failed += len(members)\n con.commit()\n except sqlite3.OperationalError:\n # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,\n # elle sera reprise au prochain passage — jamais crasher tout le run.\n try:\n con.rollback()\n except sqlite3.Error:\n pass\n time.sleep(1.0)\n continue\n\n con.close()\n stats = {\"geocoded\": done, \"failed\": failed,\n \"unique_addresses\": len(groupes), \"api_requests\": requests_made}\n print(f\"[immo-ka] geocode {stats}\")\n return stats\n\n\nAQ_BATCH_URL = (\"https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/\"\n \"Adresse_Geocodage/GeocodeServer/geocodeAddresses\")\nBATCH_SIZE = 200\nRESCUE_MAX = 150 # rattrapages resolve() max par passe (Nominatim = 1 req/s)\n\n\ndef strip_bad_source_coords(con, listings) -> int:\n \"\"\"Garde d'ingestion : annule les lat/lng fournis par un connecteur quand\n ils contredisent la ville annoncée (> VILLE_RADIUS_KM du centroïde connu).\n Cache seulement (médianes + villes déjà résolues) : aucun appel réseau,\n la synchronisation reste rapide. Retourne le nombre de paires annulées.\"\"\"\n geo = Geocoder(con)\n n = 0\n for lst in listings:\n if lst.lat is None or lst.lng is None or not (lst.city or \"\").strip():\n continue\n refs = geo.city_refs(lst.city, allow_api=False)\n if refs and not geo.coords_ok((lst.lat, lst.lng), lst.city, refs):\n lst.lat = lst.lng = None\n n += 1\n return n\n\n\ndef run_batch(limit: int | None = None) -> dict:\n \"\"\"Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000\n adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de\n milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim).\"\"\"\n con = db.connect()\n geo = Geocoder(con) # pour réutiliser _clean / bbox\n rows = con.execute(\n \"\"\"SELECT uid, address, city FROM listings\n WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0\n AND dup_hidden=0 ORDER BY address\"\"\").fetchall()\n # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache\n uniq: dict[str, dict] = {}\n for r in rows:\n k = norm_key(r[\"address\"])\n if not k or len(k) < 6:\n continue\n u = uniq.setdefault(k, {\"address\": r[\"address\"], \"city\": r[\"city\"],\n \"members\": []})\n u[\"members\"].append(r[\"uid\"])\n pending = []\n for k, u in uniq.items():\n c = con.execute(\"SELECT lat,lng,failed FROM geocode_cache WHERE address=?\",\n (k,)).fetchone()\n if c is not None and not c[\"failed\"]: # déjà résolu : appliquer direct\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (c[\"lat\"], c[\"lng\"], uid))\n continue\n if c is not None and c[\"failed\"]:\n continue\n pending.append((k, u))\n con.commit()\n if limit is not None:\n pending = pending[:limit]\n\n session = requests.Session()\n session.headers[\"User-Agent\"] = USER_AGENT\n done = failed = 0\n rescue: list[tuple[str, dict]] = [] # échecs du lot -> resolve() individuel\n for i in range(0, len(pending), BATCH_SIZE):\n chunk = pending[i:i + BATCH_SIZE]\n records = {\"records\": [\n {\"attributes\": {\"OBJECTID\": j,\n \"SingleLine\": f\"{geo._clean(u['address']).split(',')[0].strip()}, \"\n f\"{(u['city'] or 'Québec').strip()}\"}}\n for j, (_k, u) in enumerate(chunk)]}\n try:\n # POST obligatoire : le param `addresses` (JSON de N records) est trop\n # long pour une URL GET dès quelques dizaines d'adresses.\n resp = session.post(AQ_BATCH_URL, data={\n \"addresses\": json.dumps(records, ensure_ascii=False),\n \"f\": \"json\", \"outSR\": 4326}, timeout=90)\n locs = resp.json().get(\"locations\", [])\n except Exception as e:\n print(f\"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}\")\n time.sleep(1.0)\n continue\n by_id = {l[\"attributes\"].get(\"ResultID\"): l for l in locs}\n for j, (k, u) in enumerate(chunk):\n loc = by_id.get(j)\n coords = None\n if loc and loc[\"attributes\"].get(\"Score\", 0) >= AQ_MIN_SCORE:\n lc = loc.get(\"location\") or {}\n try:\n cand = (float(lc[\"y\"]), float(lc[\"x\"]))\n # bbox + cohérence avec le centroïde de la ville annoncée\n if geo.coords_ok(cand, u[\"city\"]):\n coords = cand\n except (KeyError, ValueError, TypeError):\n coords = None\n try:\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n con.execute(\n \"INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)\"\n \" VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET\"\n \" lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,\"\n \" failed=0, ts=excluded.ts\",\n (k, coords[0], coords[1], \"adresses_quebec_batch\", time.time()))\n done += len(u[\"members\"])\n con.commit()\n else:\n # pas de verdict tout de suite : resolve() réessaiera avec la\n # municipalité officielle + Nominatim (borné par RESCUE_MAX)\n rescue.append((k, u))\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n print(f\"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} \"\n f\"(résolues {done}, à rattraper {len(rescue)})\")\n\n # Rattrapage 1-par-1 des échecs du lot : variantes de municipalité (AQ) puis\n # Nominatim, validées par centroïde. resolve() écrit lui-même le verdict au\n # cache (succès ou échec 30 j) ; au-delà de RESCUE_MAX, on laisse les fiches\n # intactes (ni cache ni flag) -> reprises aux prochains passages.\n rescued = 0\n for k, u in rescue[:RESCUE_MAX]:\n try:\n coords = geo.resolve(u[\"address\"], u[\"city\"])\n if coords:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET lat=?, lng=? WHERE uid=?\",\n (coords[0], coords[1], uid))\n done += len(u[\"members\"])\n rescued += len(u[\"members\"])\n else:\n for uid in u[\"members\"]:\n con.execute(\"UPDATE listings SET geocode_failed=1 WHERE uid=?\", (uid,))\n failed += len(u[\"members\"])\n con.commit()\n except sqlite3.OperationalError:\n try: con.rollback()\n except sqlite3.Error: pass\n time.sleep(1.0)\n con.close()\n stats = {\"geocoded\": done, \"rescued\": rescued, \"failed\": failed,\n \"deferred\": max(0, len(rescue) - RESCUE_MAX),\n \"batches\": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}\n print(f\"[immo-ka] geocode-batch {stats}\")\n return stats\n\n\ndef run_audit(nominatim_budget: int | None = None, apply: bool = True) -> dict:\n \"\"\"Audit de cohérence géographique des fiches DÉJÀ géocodées.\n\n Détecte les coordonnées à plus de VILLE_RADIUS_KM du centroïde de leur\n ville (rue homonyme d'une autre région, geo erroné fourni par la source…),\n puis les remet en file de géocodage : lat/lng annulés, geocode_failed remis\n à 0, entrée de cache purgée. `nominatim_budget` borne les résolutions de\n villes inconnues (1 req/s) ; None = illimité. `apply=False` = rapport seul.\n \"\"\"\n con = db.connect()\n geo = Geocoder(con)\n rows = con.execute(\n \"\"\"SELECT uid, address, city, lat, lng FROM listings\n WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\").fetchall()\n flagged, villes_inconnues = [], 0\n for r in rows:\n allow = nominatim_budget is None or geo.ville_api_calls < nominatim_budget\n ref = geo.city_reference(r[\"city\"], allow_api=allow)\n if ref is None:\n villes_inconnues += 1\n continue\n d = _dist_km(r[\"lat\"], r[\"lng\"], ref[0], ref[1])\n if d > VILLE_RADIUS_KM:\n flagged.append((r, d))\n if apply:\n for r, d in flagged:\n con.execute(\"DELETE FROM geocode_cache WHERE address=?\",\n (norm_key(r[\"address\"]),))\n con.execute(\"\"\"UPDATE listings SET lat=NULL, lng=NULL,\n geocode_failed=0 WHERE uid=?\"\"\", (r[\"uid\"],))\n con.commit()\n for r, d in flagged[:20]:\n print(f\"[immo-ka] audit: {r['uid']} « {r['address']}, {r['city']} » \"\n f\"à {d:.0f} km de sa ville\")\n con.close()\n stats = {\"verifiees\": len(rows), \"incoherentes\": len(flagged),\n \"villes_inconnues\": villes_inconnues, \"corrigees\": apply}\n print(f\"[immo-ka] geocode-audit {stats}\")\n return stats\n","structuredPatch":[{"oldStart":593,"oldLines":27,"newStart":593,"newLines":41,"lines":[" def run_audit(nominatim_budget: int | None = None, apply: bool = True) -> dict:"," \"\"\"Audit de cohérence géographique des fiches DÉJÀ géocodées."," ","- Détecte les coordonnées à plus de VILLE_RADIUS_KM du centroïde de leur","- ville (rue homonyme d'une autre région, geo erroné fourni par la source…),","- puis les remet en file de géocodage : lat/lng annulés, geocode_failed remis","- à 0, entrée de cache purgée. `nominatim_budget` borne les résolutions de","- villes inconnues (1 req/s) ; None = illimité. `apply=False` = rapport seul.","+ Détecte les coordonnées à plus de VILLE_RADIUS_KM de TOUTE référence de","+ leur ville — grappes de fiches (une par municipalité homonyme) + point","+ Nominatim — puis les remet en file de géocodage : lat/lng annulés,","+ geocode_failed remis à 0, entrée de cache purgée. Une fiche n'est JAMAIS","+ flaguée sans référence indépendante confirmant l'incohérence (les","+ homonymes et villes irrésolues sont épargnés). `nominatim_budget` borne","+ les résolutions de villes inconnues (1 req/s) ; None = illimité.","+ `apply=False` = rapport seul."," \"\"\""," con = db.connect()"," geo = Geocoder(con)"," rows = con.execute("," \"\"\"SELECT uid, address, city, lat, lng FROM listings"," WHERE active=1 AND lat IS NOT NULL AND city<>''\"\"\").fetchall()","- flagged, villes_inconnues = [], 0","+ flagged, inconnues, reportees = [], 0, 0"," for r in rows:","- allow = nominatim_budget is None or geo.ville_api_calls < nominatim_budget","- ref = geo.city_reference(r[\"city\"], allow_api=allow)","- if ref is None:","- villes_inconnues += 1","- continue","- d = _dist_km(r[\"lat\"], r[\"lng\"], ref[0], ref[1])","- if d > VILLE_RADIUS_KM:","- flagged.append((r, d))","+ k = norm_key(r[\"city\"])","+ clusters = [(cl[0], cl[1]) for cl in geo._clusters().get(k, [])","+ if cl[2] >= CLUSTER_MIN]","+ dists = [_dist_km(r[\"lat\"], r[\"lng\"], c[0], c[1]) for c in clusters]","+ if dists and min(dists) <= VILLE_RADIUS_KM:","+ continue # cohérente avec une grappe de sa ville","+ budget_ok = nominatim_budget is None or geo.ville_api_calls < nominatim_budget","+ v = geo.resolve_ville(r[\"city\"], allow_api=budget_ok)","+ if v is not None:","+ d = _dist_km(r[\"lat\"], r[\"lng\"], v[\"lat\"], v[\"lng\"])","+ if d <= VILLE_RADIUS_KM:","+ continue # cohérente avec le point Nominatim de la ville","+ flagged.append((r, min(dists + [d])))","+ elif not clusters:","+ inconnues += 1 # aucune référence : on ne flague pas","+ elif not budget_ok:","+ reportees += 1 # ville pas encore résolue : prochaine passe","+ else:","+ flagged.append((r, min(dists))) # ville irrésoluble, grappes loin"," if apply:"," for r, d in flagged:"," con.execute(\"DELETE FROM geocode_cache WHERE address=?\","]},{"oldStart":626,"oldLines":6,"newStart":640,"newLines":7,"lines":[" f\"à {d:.0f} km de sa ville\")"," con.close()"," stats = {\"verifiees\": len(rows), \"incoherentes\": len(flagged),","- \"villes_inconnues\": villes_inconnues, \"corrigees\": apply}","+ \"villes_inconnues\": inconnues, \"reportees\": reportees,","+ \"corrigees\": apply}"," print(f\"[immo-ka] geocode-audit {stats}\")"," return stats"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"dd10324c-413f-4d16-8873-7efc1f6e2d5d","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYNDL6GY5rgseLkSQLk","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":3163,"cache_read_input_tokens":117084,"cache_creation":{"ephemeral_5m_input_tokens":3163,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ac27b426-ac07-4475-b7a6-b945937931fd"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYNDL6GY5rgseLkSQLk","type":"message","role":"assistant","content":[{"type":"text","text":"Je recompile et relance l'audit à blanc pour valider la nouvelle logique anti-homonymes."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":3163,"cache_read_input_tokens":117084,"cache_creation":{"ephemeral_5m_input_tokens":3163,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"08f51738-e3b4-471e-b977-ab263dba8a5e"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYNDL6GY5rgseLkSQLk","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01JWmzXP6qDAX4Nny4cK2NGW","name":"Bash","input":{"command":"cd ~/apps/immo-ka && python3 - <<'EOF'\nimport re\np = \"immoka/geocode.py\"\ns = open(p).read()\ns = s.replace(\"self._med: dict[str, tuple] | None = None # norm(ville) -> (lat,lng,n)\",\n \"self._med: dict[str, list[tuple]] | None = None # norm(ville) -> grappes (lat,lng,n)\")\nopen(p, \"w\").write(s)\nEOF\npython3 -m py_compile immoka/geocode.py && python3 run.py geocode-audit 0 dry 2>&1 | tail -25","description":"Audit à blanc avec grappes anti-homonymes","timeout":600000},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":3163,"cache_read_input_tokens":117084,"cache_creation":{"ephemeral_5m_input_tokens":3163,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"5b95f8ee-5a72-45ca-8479-ea71661308fc"}} 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329 km de sa ville\n[immo-ka] audit: duproprio:1096887 « Chemin Des Pinsons, Jonquiere Lac Kenogami » à 329 km de sa ville\n[immo-ka] geocode-audit {'verifiees': 110574, 'incoherentes': 3, 'villes_inconnues': 1063, 'reportees': 1596, 'corrigees': False}","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"a745f752-903b-4a94-9240-5cd8a47791d8","timestamp":"2026-08-25T13:25:38.422Z","tool_use_result":{"stdout":"[immo-ka] audit: duproprio:1126225 « 4671 Rue Des Perdrix, Jonquiere Lac Kenogami » à 179 km de sa ville\n[immo-ka] audit: duproprio:1104338 « Chemin Des Pinsons, Jonquiere Lac Kenogami » à 329 km de sa ville\n[immo-ka] audit: duproprio:1096887 « Chemin Des Pinsons, Jonquiere Lac Kenogami » à 329 km de sa ville\n[immo-ka] geocode-audit {'verifiees': 110574, 'incoherentes': 3, 'villes_inconnues': 1063, 'reportees': 1596, 'corrigees': False}","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} 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{"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYPXMpyRbgtKuzuUFgi","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01NggHsc9kUtLzuqEvJwi4Y2","name":"Bash","input":{"command":"cd ~/apps/immo-ka && python3 run.py geocode-audit 0 2>&1 | tail -5 && python3 run.py geocode 2>&1 | tail -5","description":"Appliquer l'audit puis re-géocoder","timeout":300000},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":4698,"cache_read_input_tokens":120247,"cache_creation":{"ephemeral_5m_input_tokens":4698,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"9cce6ab1-c60d-41c3-bba0-411855a313a6"}} {"type":"claude","event":{"type":"system","subtype":"task_started","task_id":"bg61clk3o","tool_use_id":"toolu_01NggHsc9kUtLzuqEvJwi4Y2","description":"Appliquer l'audit puis re-géocoder","task_type":"local_bash","uuid":"395ff608-fefc-4906-983a-cd864b30ae4d","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"system","subtype":"task_notification","task_id":"bg61clk3o","tool_use_id":"toolu_01NggHsc9kUtLzuqEvJwi4Y2","status":"completed","output_file":"","summary":"Appliquer l'audit puis re-géocoder","uuid":"8ff07360-9666-4770-9e24-4bd959003abe","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01NggHsc9kUtLzuqEvJwi4Y2","type":"tool_result","content":"[immo-ka] audit: duproprio:1126225 « 4671 Rue Des Perdrix, Jonquiere Lac Kenogami » à 179 km de sa ville\n[immo-ka] audit: duproprio:1104338 « Chemin Des Pinsons, Jonquiere Lac Kenogami » à 329 km de sa ville\n[immo-ka] audit: duproprio:1096887 « Chemin Des Pinsons, Jonquiere Lac Kenogami » à 329 km de sa ville\n[immo-ka] geocode-audit {'verifiees': 110574, 'incoherentes': 3, 'villes_inconnues': 1063, 'reportees': 1596, 'corrigees': True}\n[immo-ka] geocode-batch 2/2 (résolues 0, à rattraper 2)\n[immo-ka] geocode-batch {'geocoded': 3, 'rescued': 3, 'failed': 0, 'deferred': 0, 'batches': 1}","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"aa3624a3-b71f-44da-a557-6db6b3cbbe67","timestamp":"2026-08-25T13:26:23.324Z","tool_use_result":{"stdout":"[immo-ka] audit: duproprio:1126225 « 4671 Rue Des Perdrix, Jonquiere Lac Kenogami » à 179 km de sa ville\n[immo-ka] audit: duproprio:1104338 « Chemin Des Pinsons, Jonquiere Lac Kenogami » à 329 km de sa ville\n[immo-ka] audit: duproprio:1096887 « Chemin Des Pinsons, Jonquiere Lac Kenogami » à 329 km de sa ville\n[immo-ka] geocode-audit {'verifiees': 110574, 'incoherentes': 3, 'villes_inconnues': 1063, 'reportees': 1596, 'corrigees': True}\n[immo-ka] geocode-batch 2/2 (résolues 0, à rattraper 2)\n[immo-ka] geocode-batch {'geocoded': 3, 'rescued': 3, 'failed': 0, 'deferred': 0, 'batches': 1}","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"5f119f07-6b9f-480f-9f46-c2890a4b13ec","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} 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{"type":"claude","event":{"type":"system","subtype":"task_notification","task_id":"buzvi7s7k","tool_use_id":"toolu_01FyhEQavvzxiUiorNKbBfSy","status":"completed","output_file":"","summary":"Restart PM2 + healthcheck + vérif API","uuid":"6fb72d17-9345-4f0a-83b9-2bd418b82d0d","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01FyhEQavvzxiUiorNKbBfSy","type":"tool_result","content":"[PM2] Applying action restartProcessId on app [immo-ka-web](ids: [ 9 ])\n[PM2] [immo-ka-web](9) ✓\n[PM2] Applying action restartProcessId on app [immo-ka-sync](ids: [ 11 ])\n[PM2] [immo-ka-sync](11) ✓\n│ 4 │ immo-ka-ngrok │ default │ N/A │ fork │ 79925 │ 8D │ 1 │ online │ 0% │ 307.2mb │ simon-p… │ disabled │\nhealth 200\n{\"uid\":\"duproprio:1126225\",\"source\":\"duproprio\",\"external_id\":\"1126225\",\"url\":\"https://duproprio.com/fr/saguenay-lac-saint-jean/jonquiere-lac-kenogami/maison-a-vendre/hab-4671-rue-des-perdrix-1126225\",\"title\":\"Hab 4671 Rue Des Perdrix\",\"address\":\"4671 Rue Des Perdrix\",\"sector\":\"\",\"city\":\"Jonquiere L","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"deb4ea8f-e0a7-4c29-ad7e-ef7655e62820","timestamp":"2026-08-25T13:27:01.326Z","tool_use_result":{"stdout":"[PM2] Applying action restartProcessId on app [immo-ka-web](ids: [ 9 ])\n[PM2] [immo-ka-web](9) ✓\n[PM2] Applying action restartProcessId on app [immo-ka-sync](ids: [ 11 ])\n[PM2] [immo-ka-sync](11) ✓\n│ 4 │ immo-ka-ngrok │ default │ N/A │ fork │ 79925 │ 8D │ 1 │ online │ 0% │ 307.2mb │ simon-p… │ disabled │\nhealth 200\n{\"uid\":\"duproprio:1126225\",\"source\":\"duproprio\",\"external_id\":\"1126225\",\"url\":\"https://duproprio.com/fr/saguenay-lac-saint-jean/jonquiere-lac-kenogami/maison-a-vendre/hab-4671-rue-des-perdrix-1126225\",\"title\":\"Hab 4671 Rue Des Perdrix\",\"address\":\"4671 Rue Des Perdrix\",\"sector\":\"\",\"city\":\"Jonquiere L","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"5a15673e-fdd7-4961-a330-d28ab257a97d","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYVdUMGeJBLUqeAYJeQ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01HBkDKYMFScgX1cwa6nQWG9","name":"Bash","input":{"command":"curl -s \"http://localhost:8096/api/listings/duproprio:1126225\" | python3 -c \"import json,sys; d=json.load(sys.stdin); print(d.get('lat'), d.get('lng'))\" ; curl -s -o /dev/null -w \"site public %{http_code}\\n\" \"https://www.immo-ka.com/propriete/duproprio%3A1126225/4671-rue-des-perdrix-jonquiere-lac-kenogami\"","description":"Vérifier lat/lng via API + site public"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1551,"cache_read_input_tokens":127606,"cache_creation":{"ephemeral_5m_input_tokens":1551,"ephemeral_1h_input_tokens":0},"output_tokens":20,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"8c102ae0-4088-469a-92f2-b4681b6a4a69"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01HBkDKYMFScgX1cwa6nQWG9","type":"tool_result","content":"48.311895748504 -71.302037494045\nsite public 200","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"1a9bd630-8eec-4643-8a54-c61b8fada474","timestamp":"2026-08-25T13:27:10.799Z","tool_use_result":{"stdout":"48.311895748504 -71.302037494045\nsite public 200","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"09a6e12b-01f0-497e-a441-d767b621b1ea","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} 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{"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYWKjHKLTckCvFZGRw3","type":"message","role":"assistant","content":[{"type":"text","text":"Site et API OK avec les bonnes coordonnées. Je committe et pousse, puis je lance le grand nettoyage en arrière-plan."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":260,"cache_read_input_tokens":129157,"cache_creation":{"ephemeral_5m_input_tokens":260,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"68497679-7a70-4239-8f70-9830676fea07"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYWKjHKLTckCvFZGRw3","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_0137oXQYNySNGwgu9iL5xTPM","name":"Bash","input":{"command":"cd ~/apps/immo-ka && git status --short && git diff --stat","description":"Voir l'état git avant commit"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":260,"cache_read_input_tokens":129157,"cache_creation":{"ephemeral_5m_input_tokens":260,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"8969d1e1-9589-4317-bbf1-5fce8d1bc3e4"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0137oXQYNySNGwgu9iL5xTPM","type":"tool_result","content":" M immoka/db.py\n M immoka/geocode.py\n M immoka/ingest.py\n M run.py\n immoka/db.py | 6 +-\n immoka/geocode.py | 314 +++++++++++++++++++++++++++++++++++++++++++++++++-----\n immoka/ingest.py | 14 +++\n run.py | 6 ++\n 4 files changed, 314 insertions(+), 26 deletions(-)","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"81fc3b78-b8e0-42c7-a915-49a3145122fc","timestamp":"2026-08-25T13:27:18.011Z","tool_use_result":{"stdout":" M immoka/db.py\n M immoka/geocode.py\n M immoka/ingest.py\n M run.py\n immoka/db.py | 6 +-\n immoka/geocode.py | 314 +++++++++++++++++++++++++++++++++++++++++++++++++-----\n immoka/ingest.py | 14 +++\n run.py | 6 ++\n 4 files changed, 314 insertions(+), 26 deletions(-)","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"2ad77e24-7fa1-4ec5-b2a4-390a4547a3ae","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYWrsHVpVexxt8Dxx7j","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01A6kvuvwYvWADJ6NzVxXku8","name":"Bash","input":{"command":"cd ~/apps/immo-ka && git add immoka/db.py immoka/geocode.py immoka/ingest.py run.py && git commit -m \"$(cat <<'EOF'\nGéocodage rigoureux : validation par références de ville (grappes + Nominatim)\n\nCorrige la classe de bug « rue homonyme d'une autre ville » (4671 rue des\nPerdrix, Jonquière/Lac-Kénogami affichée à Saint-Augustin, ~180 km) :\n\n- chaque résultat de géocodage doit être à <= 40 km d'une référence de la\n ville annoncée : grappes de fiches déjà géocodées (une par municipalité\n HOMONYME — deux L'Ange-Gardien, deux Saint-Donat…) + point Nominatim de la\n ville (cache geocode_cache, clé « ville:… », colonne muni ajoutée)\n- resolve() : si la ville annoncée est un secteur inconnu d'Adresses Québec\n (« Jonquière (Lac-Kénogami) »), retry AQ avec la municipalité officielle\n (« Saguenay ») dérivée de Nominatim, puis variantes Nominatim structurées\n- run_batch : validation par références + rattrapage resolve() individuel des\n échecs du lot (RESCUE_MAX/passe, file auto-drainante)\n- run_audit (CLI geocode-audit [budget] [dry]) : détecte les fiches actives\n aux coordonnées incohérentes avec leur ville et les remet en file de\n géocodage ; intégré au cycle watch (budget Nominatim 50/passe)\n- garde d'ingestion : lat/lng fournis par un connecteur (ex. JSON-LD\n DuProprio erroné) rejetés s'ils contredisent la ville (cache seulement)\n\nAudit initial : 110 574 fiches vérifiées, 3 incohérentes corrigées et\nre-géocodées correctement (les municipalités homonymes ne sont pas flaguées).\n\nCo-Authored-By: Claude Opus 4.7 \nEOF\n)\" && git push origin main && git log --oneline -1","description":"Committer et pousser vers spbgit"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":791,"cache_read_input_tokens":129417,"cache_creation":{"ephemeral_5m_input_tokens":791,"ephemeral_1h_input_tokens":0},"output_tokens":20,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"30eb599a-ca9a-4109-a5e6-e9948cd44b13"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01A6kvuvwYvWADJ6NzVxXku8","type":"tool_result","content":"[main 2a0d7b3] Géocodage rigoureux : validation par références de ville (grappes + Nominatim)\n 4 files changed, 314 insertions(+), 26 deletions(-)\nTo gitsrv:srv/git/immo-ka.git\n 2b1f7ce..2a0d7b3 main -> main\n2a0d7b3 Géocodage rigoureux : validation par références de ville (grappes + Nominatim)","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"66b7952f-6c47-4e73-b13a-fba80e45311f","timestamp":"2026-08-25T13:27:33.880Z","tool_use_result":{"stdout":"[main 2a0d7b3] Géocodage rigoureux : validation par références de ville (grappes + Nominatim)\n 4 files changed, 314 insertions(+), 26 deletions(-)\nTo gitsrv:srv/git/immo-ka.git\n 2b1f7ce..2a0d7b3 main -> main\n2a0d7b3 Géocodage rigoureux : validation par références de ville (grappes + Nominatim)","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"7eb6fc02-4822-4c7a-9907-e69a9990178d","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYY2SmwQDwWkXvoE1Br","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":973,"cache_read_input_tokens":130208,"cache_creation":{"ephemeral_5m_input_tokens":973,"ephemeral_1h_input_tokens":0},"output_tokens":6,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"38efd803-12b1-495d-a216-e31d9fc092ae"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYY2SmwQDwWkXvoE1Br","type":"message","role":"assistant","content":[{"type":"text","text":"Poussé (`2a0d7b3`). Je lance maintenant l'audit complet en arrière-plan pour traiter les 1 596 villes non encore résolues (≈30 min à 1 req/s Nominatim), suivi d'une passe de re-géocodage."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":973,"cache_read_input_tokens":130208,"cache_creation":{"ephemeral_5m_input_tokens":973,"ephemeral_1h_input_tokens":0},"output_tokens":6,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"f2fcfb39-94ce-4f99-bd92-8048c2182b3e"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYY2SmwQDwWkXvoE1Br","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01P3RHFZbhcs3B37rCCK4MbS","name":"Bash","input":{"command":"cd ~/apps/immo-ka && nohup sh -c 'python3 run.py geocode-audit 2500 && python3 run.py geocode' > /tmp/immoka-geocode-audit-full.log 2>&1 &\necho \"lancé, log: /tmp/immoka-geocode-audit-full.log\"","description":"Audit complet + re-géocodage en arrière-plan","run_in_background":false},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":973,"cache_read_input_tokens":130208,"cache_creation":{"ephemeral_5m_input_tokens":973,"ephemeral_1h_input_tokens":0},"output_tokens":6,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"f7fb8ed3-336f-4902-8f2e-a99fa9b0bf20"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01P3RHFZbhcs3B37rCCK4MbS","type":"tool_result","content":"lancé, log: /tmp/immoka-geocode-audit-full.log","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"543220ba-ed39-4636-acff-c68ba5e12ee9","timestamp":"2026-08-25T13:27:43.234Z","tool_use_result":{"stdout":"lancé, log: /tmp/immoka-geocode-audit-full.log","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"3ecd24c8-fe95-43c7-a6a6-4d4ddf95adc4","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePYYiUovJ3J73JqVPrE4","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01NTQnuj5QLEFKg9EDiHtwy8","name":"TodoWrite","input":{"todos":[{"content":"geocode.py : centroïde de ville (médiane BD + Nominatim caché) et validation ≤40 km","status":"completed","activeForm":"Ajout de la validation par centroïde de ville"},{"content":"resolve() : retry AQ avec municipalité officielle + variantes Nominatim","status":"completed","activeForm":"Ajout des variantes de municipalité"},{"content":"run_batch : validation centroïde + rattrapage resolve() des échecs","status":"completed","activeForm":"Renforcement du géocodage batch"},{"content":"run_audit : détecter/corriger les fiches aux coordonnées incohérentes","status":"completed","activeForm":"Création de l'audit géocodage"},{"content":"Garde ingestion : rejeter les coords de connecteur contredisant la ville","status":"completed","activeForm":"Ajout de la garde à l'ingestion"},{"content":"db.py : colonne muni dans geocode_cache + CLI geocode-audit + watch","status":"completed","activeForm":"Migration BD et CLI"},{"content":"Corriger duproprio:1126225 + lancer l'audit + vérifier le site","status":"completed","activeForm":"Correction des fiches et vérification"},{"content":"pm2 restart + commit + push origin main","status":"completed","activeForm":"Redéploiement et commit"},{"content":"Audit complet en arrière-plan (1596 villes restantes) — vérifier le log","status":"in_progress","activeForm":"Audit complet en arrière-plan"}]},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":446,"cache_read_input_tokens":131181,"cache_creation":{"ephemeral_5m_input_tokens":446,"ephemeral_1h_input_tokens":0},"output_tokens":24,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"8bc695eb-caee-43d7-81a4-816c4f6fd012"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01NTQnuj5QLEFKg9EDiHtwy8","type":"tool_result","content":"Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"f11283ad-4344-4fe1-a8eb-767c02b06f89","timestamp":"2026-08-25T13:27:58.480Z","tool_use_result":{"oldTodos":[{"content":"geocode.py : centroïde de ville (médiane BD + Nominatim caché) et validation ≤40 km","status":"completed","activeForm":"Ajout de la validation par centroïde de ville"},{"content":"resolve() : retry AQ avec municipalité officielle + variantes Nominatim","status":"completed","activeForm":"Ajout des variantes de municipalité"},{"content":"run_batch : validation centroïde + rattrapage resolve() des échecs","status":"completed","activeForm":"Renforcement du géocodage batch"},{"content":"run_audit : détecter/corriger les fiches aux coordonnées incohérentes","status":"completed","activeForm":"Création de l'audit géocodage"},{"content":"Garde ingestion : rejeter les coords de connecteur contredisant la ville","status":"completed","activeForm":"Ajout de la garde à l'ingestion"},{"content":"db.py : colonne muni dans geocode_cache + CLI geocode-audit + watch","status":"completed","activeForm":"Migration BD et CLI"},{"content":"Corriger duproprio:1126225 + lancer l'audit + vérifier le site","status":"in_progress","activeForm":"Correction des fiches et vérification"},{"content":"pm2 restart + commit + push origin main","status":"pending","activeForm":"Redéploiement et commit"}],"newTodos":[{"content":"geocode.py : centroïde de ville (médiane BD + Nominatim caché) et validation ≤40 km","status":"completed","activeForm":"Ajout de la validation par centroïde de ville"},{"content":"resolve() : retry AQ avec municipalité officielle + variantes Nominatim","status":"completed","activeForm":"Ajout des variantes de municipalité"},{"content":"run_batch : validation centroïde + rattrapage resolve() des échecs","status":"completed","activeForm":"Renforcement du géocodage batch"},{"content":"run_audit 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playwright installé --no-save ; uid test domicilia:17516934\n4\t- [Fiche PDF immo-ka](project_pdf_fiche.md) — uids test riche/pauvre/vente ; piège /tmp/inspect.py → python -P ; pdftoppm pour inspecter\n5\t- [Recensement OACIQ](project_oaciq_census.md) — data/oaciq_census.json ; scrape GET registre.oaciq.com ; pièges (vaillancourt=domicilia, CIEMCQ, commerciaux)\n6\t"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"023a8520-7871-49ca-a635-853853f795c7","timestamp":"2026-08-25T13:28:48.709Z","tool_use_result":{"type":"text","file":{"filePath":"/Users/simon-pierreboucher/.claude/projects/-Users-simon-pierreboucher-apps-immo-ka/memory/MEMORY.md","content":"# MEMORY\n\n- [Vérifs Playwright immo-ka](project_playwright_checks.md) — check-order avec BASE=http://localhost:8096 ; playwright installé --no-save ; uid test domicilia:17516934\n- [Fiche PDF immo-ka](project_pdf_fiche.md) — uids test riche/pauvre/vente ; piège /tmp/inspect.py → python -P ; pdftoppm pour inspecter\n- [Recensement OACIQ](project_oaciq_census.md) — data/oaciq_census.json ; 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Le bug est corrigé et le moteur de géocodage est maintenant rigoureux.\n\n**Cause du bug** : la fiche `duproprio:1126225` avait des coordonnées erronées (près de la rue de la Perdrix *Grise* à Saint-Augustin, ~180 km) et rien ne validait les coordonnées contre la ville annoncée — la seule garde était une bbox couvrant toute la province. De plus, Adresses Québec ne connaît pas les noms de secteurs (« Jonquière (Lac-Kénogami) »), seulement « Saguenay », donc le géocodeur échouait sans pouvoir corriger.\n\n**Ce qui a été fait** (`immoka/geocode.py`, `ingest.py`, `db.py`, `run.py`) :\n- **Validation ≤ 40 km d'une référence de ville** : grappes de fiches déjà géocodées (une par municipalité **homonyme** — deux L'Ange-Gardien, deux Saint-Donat… j'ai détecté ce piège qui créait 6 200 faux positifs avec un centroïde unique) + point Nominatim de la ville, en cache.\n- **`resolve()` plus malin** : si la ville-secteur est inconnue d'AQ, retry avec la municipalité officielle (« Saguenay ») + variantes Nominatim structurées.\n- **`run_batch`** valide chaque candidat et rattrape les échecs 1 par 1.\n- **`geocode-audit`** (nouvelle CLI + intégré au cycle `watch`) : détecte et re-géocode les fiches incohérentes.\n- **Garde d'ingestion** : les lat/lng fournis par un connecteur (le JSON-LD DuProprio fautif ici) sont rejetés s'ils contredisent la ville.\n\n**Résultat** : audit de 110 574 fiches → 3 incohérentes (la vôtre + 2 Chemin des Pinsons du même secteur), toutes re-géocodées correctement — la fiche est maintenant à **(48.312, -71.302)**, au Lac-Kénogami. Vérifié via l'API locale et le site (200). PM2 redémarré (web + sync), commit `2a0d7b3` poussé sur origin/main. Un audit complet des ~1 600 villes restantes tourne en arrière-plan (`/tmp/immoka-geocode-audit-full.log`), suivi d'un re-géocodage automatique."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":468,"cache_read_input_tokens":134976,"cache_creation":{"ephemeral_5m_input_tokens":468,"ephemeral_1h_input_tokens":0},"output_tokens":7,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"38560e58-b9a5-4c75-9393-32639ee33ccb"}} {"type":"claude","event":{"type":"result","subtype":"success","is_error":false,"api_error_status":null,"duration_ms":1115518,"duration_api_ms":1068472,"num_turns":66,"result":"Terminé. Le bug est corrigé et le moteur de géocodage est maintenant rigoureux.\n\n**Cause du bug** : la fiche `duproprio:1126225` avait des coordonnées erronées (près de la rue de la Perdrix *Grise* à Saint-Augustin, ~180 km) et rien ne validait les coordonnées contre la ville annoncée — la seule garde était une bbox couvrant toute la province. 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{"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePaPqFqCKjUf4g167jcu","type":"message","role":"assistant","content":[{"type":"text","text":"Voici une annonce dont le coût Hydro-Québec est déjà en cache (il s'affiche instantanément sur la fiche, chargé côté client via `/api/hydro`) :\n\n**https://www.immo-ka.com/propriete/via_capitale%3A24955327/10-rue-thibault-saint-paul-de-la-croix**\n\n- 10 Rue Thibault, Saint-Paul-de-la-Croix (Via Capitale)\n- Coût Hydro estimé : **2 695 $/an (225 $/mois, 24 220 kWh)** — vérifié en cache et via l'API (`disponible: true, cache: true`), page publique en 200.\n\nDeux autres au besoin : `via_capitale:25618236` (2462 Rue Commerciale S., Témiscouata-sur-le-Lac, 4 422 $/an) et `via_capitale:17890693` (618 Rue du Bord-de-l'Eau, Grande-Rivière, 3 991 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{"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"97af07ff-0c29-4733-b5d5-e1ac149f5eec","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePacHr5NJzN36YYSmf4C","type":"message","role":"assistant","content":[{"type":"text","text":"**226 annonces** ont un coût Hydro en cache (275 entrées au total, 227 avec coût calculé), dont **113 encore actives et publiées** sur le site — les autres sont des annonces retirées/masquées depuis (le cache persiste dans `data/hydro.db`).\n\nLe précalcul avance lentement par design : ~100 nouvelles annonces max par cycle `watch` horaire avec un budget de 30 requêtes (`hydro.precompute(limit=100, budget=30)` dans `ingest.py`), pour ne pas marteler l'API non officielle d'Hydro-Québec. 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Les autres fiches calculent leur estimation à la volée quand un visiteur ouvre la page (puis ça reste en cache).","stop_reason":"end_turn","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","total_cost_usd":0.142995,"usage":{"input_tokens":6,"cache_creation_input_tokens":1108,"cache_read_input_tokens":422240,"output_tokens":810,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":1108},"inference_geo":"","iterations":[{"input_tokens":2,"output_tokens":251,"cache_read_input_tokens":141109,"cache_creation_input_tokens":299,"cache_creation":{"ephemeral_5m_input_tokens":299,"ephemeral_1h_input_tokens":0},"type":"message"}],"speed":"standard"},"modelUsage":{"claude-fable-5":{"inputTokens":6,"outputTokens":810,"cacheReadInputTokens":422240,"cacheCreationInputTokens":1108,"webSearchRequests":0,"costUSD":0.142995,"contextWindow":200000,"maxOutputTokens":32000}},"permission_denials":[],"terminal_reason":"completed","fast_mode_state":"off","uuid":"6366a999-cbd9-4e45-978d-49842cf75749"}} {"type":"status","state":"idle"} {"type":"user_prompt","text":"Peux tu me dire si j’ai des annonce du. Courtier Laberge à Québec.","ts":1787666588870} {"type":"status","state":"running"} 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{"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbFQedh1YXvmfzNqGXp","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_017Hskfd16wLp2mLa4hLLyVX","name":"Bash","input":{"command":"sqlite3 ~/apps/immo-ka/data/immoka.db \"PRAGMA table_info(listings);\" | awk -F'|' '{print $2}' | tr '\\n' ' '","description":"Voir les colonnes de listings"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":141693,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":141693,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ea0c8d4a-1011-4bee-abc5-b600b315add2"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_017Hskfd16wLp2mLa4hLLyVX","type":"tool_result","content":"uid source external_id url title address sector city region property_type price price_label bedrooms bathrooms powder_rooms area_sqft lot_sqft year_built mls status broker_name broker_phone description features details images lat lng geocode_failed content_hash first_seen last_seen updated_at miss_count active agency dup_hidden dauid vraiprix quality_score quality_issues published","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"a31e251b-cf70-4ad4-9480-75a5e4b136af","timestamp":"2026-08-25T14:03:18.234Z","tool_use_result":{"stdout":"uid source external_id url title address sector city region property_type price price_label bedrooms bathrooms powder_rooms area_sqft lot_sqft year_built mls status broker_name broker_phone description features details images lat lng 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{"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbGbCRB7bLK17cmtg3D","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01GRKJLDTK6q1nR83CvR83Y8","name":"Bash","input":{"command":"sqlite3 ~/apps/immo-ka/data/immoka.db \"SELECT broker_name, agency, city, active, COUNT(*) FROM listings WHERE broker_name LIKE '%laberge%' GROUP BY 1,2,3,4;\"","description":"Tous les Laberge, actifs ou non"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":285,"cache_read_input_tokens":142505,"cache_creation":{"ephemeral_5m_input_tokens":285,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"9ad46812-5115-444b-ab17-69a1fcadc8fe"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01GRKJLDTK6q1nR83CvR83Y8","type":"tool_result","content":"Simon Laberge|VIA CAPITALE ÉQUIPE|Québec|1|1\nSimon Laberge|VIA CAPITALE ÉQUIPE|Sainte-Anne-de-Beaupré|0|2\nVincent Laberge|PROPRIO DIRECT|Salaberry-de-Valleyfield|1|1\nVincent Laberge|Vendre.ca|Montréal (Île-Bizard)|1|2\nVincent Laberge|Vendre.ca|Saint-Zotique|1|1","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"0d86ed3e-9ebe-4f19-966a-155731680fd4","timestamp":"2026-08-25T14:03:34.277Z","tool_use_result":{"stdout":"Simon Laberge|VIA CAPITALE ÉQUIPE|Québec|1|1\nSimon Laberge|VIA CAPITALE ÉQUIPE|Sainte-Anne-de-Beaupré|0|2\nVincent Laberge|PROPRIO DIRECT|Salaberry-de-Valleyfield|1|1\nVincent Laberge|Vendre.ca|Montréal (Île-Bizard)|1|2\nVincent Laberge|Vendre.ca|Saint-Zotique|1|1","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbGbCRB7bLK17cmtg3D","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_017Wc7uSFfd5887X8m4Zs8D3","name":"Bash","input":{"command":"python3 -c \"\nimport json\nd = json.load(open('/Users/simon-pierreboucher/apps/immo-ka/data/oaciq_census.json'))\nbrokers = d.get('courtiers') or d.get('brokers') or d\nif isinstance(brokers, dict):\n for k in list(d)[:5]: print('cle:', k)\n\" 2>/dev/null; python3 -c \"\nimport json\nd = json.load(open('/Users/simon-pierreboucher/apps/immo-ka/data/oaciq_census.json'))\nitems = d if isinstance(d, list) else next((v for v in d.values() if isinstance(v, list)), [])\nhits = [b for b in items if isinstance(b, dict) and 'laberge' in json.dumps(b, ensure_ascii=False).lower() and ('queb' in json.dumps(b, ensure_ascii=False).lower() or 'québec' in json.dumps(b, ensure_ascii=False).lower())]\nfor b in hits[:10]: print({k: b.get(k) for k in 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{"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbHdAG2DfzV9TdZLUrK","type":"message","role":"assistant","content":[{"type":"text","text":"Oui — **Simon Laberge** (Via Capitale Équipe) a une annonce active à Québec. 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Charles-Trudel, Québec (Charlesbourg / Notre-Dame-des-Laurentides) — 369 000 $**\n - La propriété est présente sous 3 sources (realtor.ca, Via Capitale, FB Marketplace) ; la dédup affiche la version FB Marketplace : https://www.immo-ka.com/propriete/fb_marketplace%3A1034708775856596/3-chemin-charles-trudel-quebec (vérifiée, 200)\n - Il a aussi 2 fiches inactives (retirées) à Sainte-Anne-de-Beaupré.\n\n**Autres Laberge ailleurs** (homonymes, pas à Québec) — Vincent Laberge :\n- 131 3e Avenue, Saint-Zotique — 759 900 $ (Vendre.ca)\n- 158 et 160 Av. du Manoir, Montréal (Île-Bizard) — 975 000 $ (Vendre.ca)\n- 13-13A Rue St-Hippolyte, Salaberry-de-Valleyfield — 449 000 $ (Proprio Direct, masquée en doublon)\n\nÀ noter : la fiche Charles-Trudel affichée (version FB Marketplace) ne montre pas le nom du courtier — l'info « Simon Laberge / Via Capitale » vit dans les fiches sources masquées par la déduplication."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":322,"cache_read_input_tokens":145137,"cache_creation":{"ephemeral_5m_input_tokens":322,"ephemeral_1h_input_tokens":0},"output_tokens":5,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"3d06fc94-1bec-4eb8-b022-82352fe00f67"}} {"type":"claude","event":{"type":"result","subtype":"success","is_error":false,"api_error_status":null,"duration_ms":69528,"duration_api_ms":68855,"num_turns":8,"result":"Oui, vous avez des annonces du courtier **Laberge**, dont une à Québec :\n\n**À Québec** — Simon Laberge (VIA CAPITALE ÉQUIPE) :\n- **3 Ch. 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{"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbdW1DAKLG4RzPfSyUB","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":623,"cache_read_input_tokens":145459,"cache_creation":{"ephemeral_5m_input_tokens":623,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"b44e5045-06da-4f6f-8657-8aeaa7b9b9ce"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbdW1DAKLG4RzPfSyUB","type":"message","role":"assistant","content":[{"type":"text","text":"Oui, c'est faisable. Deux volets : (1) la déduplication doit **préférer la version courtier** (avec nom/agence) plutôt qu'une version anonyme (ex. FB Marketplace), et (2) une **nouvelle box sur la fiche** listant les autres versions (doublons) avec mention de la source et liens. Je commence par explorer la logique de dédup et la page fiche."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":623,"cache_read_input_tokens":145459,"cache_creation":{"ephemeral_5m_input_tokens":623,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"fc1d431f-827b-4ac7-b03a-c4124b618a10"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbdW1DAKLG4RzPfSyUB","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01MyXNaPakuH8VBC3XawpqHx","name":"Bash","input":{"command":"sed -n '146,290p' ~/apps/immo-ka/immoka/db.py","description":"Lire refresh_dedup et dedup_by_address"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":623,"cache_read_input_tokens":145459,"cache_creation":{"ephemeral_5m_input_tokens":623,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"cf8195ee-4780-4cee-9202-399b8473b013"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01MyXNaPakuH8VBC3XawpqHx","type":"tool_result","content":" con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n con.commit()\n\n\ndef refresh_dedup(con: sqlite3.Connection) -> int:\n \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n\n Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée\n si une fiche de plus haute priorité — même n° Centris (external_id), active —\n existe : le flux central/agence principale d'abord, sinon la sous-agence au\n plus petit uid. Les fiches non sous-agence ne sont jamais masquées par\n cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).\n Retourne le nombre total de fiches masquées.\"\"\"\n AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n con.execute(\"UPDATE listings SET dup_hidden=0\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")\n # 3) dédup INTER-SOURCES par adresse : la même propriété publiée sur deux\n # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle\n # conservatrice : même adresse normalisée (civique + rue + ville) + même\n # type + prix identique à ±1 % → on garde la fiche la plus autoritaire.\n try:\n n_addr = dedup_by_address(con)\n if n_addr:\n print(f\"[immo-ka] dédup adresse: {n_addr} doublon(s) inter-sources masqué(s)\")\n except Exception:\n import traceback\n traceback.print_exc()\n n = con.execute(\"SELECT COUNT(*) c FROM listings WHERE dup_hidden=1\").fetchone()[\"c\"]\n con.commit()\n return n\n\n\n# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main)\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\"}\n\n\ndef _source_rank(source: str) -> int:\n \"\"\"Autorité d'une source pour la dédup d'adresse :\n 0 = source primaire (bannière/agence/FSBO), 1 = sous-agence (_ag_),\n 2 = petites annonces (republication probable).\"\"\"\n if source in _PETITES_ANNONCES:\n return 2\n if \"_ag_\" in source:\n return 1\n return 0\n\n\ndef dedup_by_address(con: sqlite3.Connection) -> int:\n \"\"\"Passe de déduplication conservatrice par ADRESSE (inter-sources).\n\n Clé : n° civique(s) + mots significatifs de la rue + ville normalisée +\n type canonique + n° d'app/unité (vide s'il n'y en a pas — deux unités\n différentes d'un même immeuble ne partagent JAMAIS la même clé, et une\n adresse sans unité ne s'apparie pas à une adresse avec unité). Dans une\n clé, seules les fiches au prix identique à ±1 % sont considérées comme\n doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis le plus petit uid. Retourne le nb masqué.\"\"\"\n import re as _re\n from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE\n groups: dict[tuple, list] = {}\n for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):\n civs, words = _addr_parts(r[\"address\"])\n if not civs or not words:\n continue\n a = _norm(r[\"address\"]).split(\",\")[0]\n mapt = _re.search(_APP_RE, a)\n apt = \"\"\n if mapt:\n toks = _re.findall(r\"[a-z0-9]+\", mapt.group(0))\n # dernier token = le n° d'unité (le 1er est le mot-clé app/unité/#)\n apt = toks[-1] if toks else \"\"\n key = (\"-\".join(civs), \" \".join(sorted(set(words))),\n _muni_norm(r[\"city\"]), _norm(r[\"property_type\"]), apt)\n groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))\n hidden = 0\n for rows in groups.values():\n if len(rows) < 2:\n continue\n rows.sort() # par prix croissant\n cluster: list = []\n for row in rows:\n if cluster and row[0] > cluster[0][0] * 1.01:\n hidden += _mask_cluster(con, cluster)\n cluster = []\n cluster.append(row)\n hidden += _mask_cluster(con, cluster)\n return hidden\n\n\ndef _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:\n \"\"\"Masque les doublons d'un groupe (même clé d'adresse, prix ±1 %), puis\n FUSIONNE en « golden record » : les champs vides de la fiche conservée sont\n complétés depuis les doublons masqués (description plus longue, galerie plus\n riche, superficies, année, GPS, téléphone) — le meilleur des deux sources.\"\"\"\n if len(cluster) < 2:\n return 0\n sources = [c[3] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[2] != keep[2]:\n con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n donors.append(c[2])\n n += 1\n try:\n _merge_golden(con, keep[2], donors)\n except Exception:\n pass # la fusion est un bonus — ne jamais casser la dédup\n return n\n\n\n_MERGE_NUM_FIELDS = (\"bedrooms\", \"bathrooms\", \"powder_rooms\", \"area_sqft\",\n \"lot_sqft\", \"year_built\")\n\n\ndef _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:\n \"\"\"Complète les champs vides de `keep_uid` depuis ses doublons masqués.\"\"\"\n if not donor_uids:\n return\n cols = (\"uid, description, images, bedrooms, bathrooms, powder_rooms,\"","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"29da1b5c-218f-4534-8fdc-80873e961ed5","timestamp":"2026-08-25T14:08:28.362Z","tool_use_result":{"stdout":" con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n con.commit()\n\n\ndef refresh_dedup(con: sqlite3.Connection) -> int:\n \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n\n Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée\n si une fiche de plus haute priorité — même n° Centris (external_id), active —\n existe : le flux central/agence principale d'abord, sinon la sous-agence au\n plus petit uid. Les fiches non sous-agence ne sont jamais masquées par\n cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).\n Retourne le nombre total de fiches masquées.\"\"\"\n AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n con.execute(\"UPDATE listings SET dup_hidden=0\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")\n # 3) dédup INTER-SOURCES par adresse : la même propriété publiée sur deux\n # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle\n # conservatrice : même adresse normalisée (civique + rue + ville) + même\n # type + prix identique à ±1 % → on garde la fiche la plus autoritaire.\n try:\n n_addr = dedup_by_address(con)\n if n_addr:\n print(f\"[immo-ka] dédup adresse: {n_addr} doublon(s) inter-sources masqué(s)\")\n except Exception:\n import traceback\n traceback.print_exc()\n n = con.execute(\"SELECT COUNT(*) c FROM listings WHERE dup_hidden=1\").fetchone()[\"c\"]\n con.commit()\n return n\n\n\n# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main)\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\"}\n\n\ndef _source_rank(source: str) -> int:\n \"\"\"Autorité d'une source pour la dédup d'adresse :\n 0 = source primaire (bannière/agence/FSBO), 1 = sous-agence (_ag_),\n 2 = petites annonces (republication probable).\"\"\"\n if source in _PETITES_ANNONCES:\n return 2\n if \"_ag_\" in source:\n return 1\n return 0\n\n\ndef dedup_by_address(con: sqlite3.Connection) -> int:\n \"\"\"Passe de déduplication conservatrice par ADRESSE (inter-sources).\n\n Clé : n° civique(s) + mots significatifs de la rue + ville normalisée +\n type canonique + n° d'app/unité (vide s'il n'y en a pas — deux unités\n différentes d'un même immeuble ne partagent JAMAIS la même clé, et une\n adresse sans unité ne s'apparie pas à une adresse avec unité). Dans une\n clé, seules les fiches au prix identique à ±1 % sont considérées comme\n doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis le plus petit uid. Retourne le nb masqué.\"\"\"\n import re as _re\n from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE\n groups: dict[tuple, list] = {}\n for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):\n civs, words = _addr_parts(r[\"address\"])\n if not civs or not words:\n continue\n a = _norm(r[\"address\"]).split(\",\")[0]\n mapt = _re.search(_APP_RE, a)\n apt = \"\"\n if mapt:\n toks = _re.findall(r\"[a-z0-9]+\", mapt.group(0))\n # dernier token = le n° d'unité (le 1er est le mot-clé app/unité/#)\n apt = toks[-1] if toks else \"\"\n key = (\"-\".join(civs), \" \".join(sorted(set(words))),\n _muni_norm(r[\"city\"]), _norm(r[\"property_type\"]), apt)\n groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))\n hidden = 0\n for rows in groups.values():\n if len(rows) < 2:\n continue\n rows.sort() # par prix croissant\n cluster: list = []\n for row in rows:\n if cluster and row[0] > cluster[0][0] * 1.01:\n hidden += _mask_cluster(con, cluster)\n cluster = []\n cluster.append(row)\n hidden += _mask_cluster(con, cluster)\n return hidden\n\n\ndef _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:\n \"\"\"Masque les doublons d'un groupe (même clé d'adresse, prix ±1 %), puis\n FUSIONNE en « golden record » : les champs vides de la fiche conservée sont\n complétés depuis les doublons masqués (description plus longue, galerie plus\n riche, superficies, année, GPS, téléphone) — le meilleur des deux sources.\"\"\"\n if len(cluster) < 2:\n return 0\n sources = [c[3] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[2] != keep[2]:\n con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n donors.append(c[2])\n n += 1\n try:\n _merge_golden(con, keep[2], donors)\n except Exception:\n pass # la fusion est un bonus — ne jamais casser la dédup\n return n\n\n\n_MERGE_NUM_FIELDS = (\"bedrooms\", \"bathrooms\", \"powder_rooms\", \"area_sqft\",\n \"lot_sqft\", \"year_built\")\n\n\ndef _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:\n \"\"\"Complète les champs vides de `keep_uid` depuis ses doublons masqués.\"\"\"\n if not donor_uids:\n return\n cols = (\"uid, description, images, bedrooms, bathrooms, powder_rooms,\"","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbdW1DAKLG4RzPfSyUB","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01PrFanriTAbohJLRyZRBuyb","name":"Grep","input":{"pattern":"def listing_detail|/api/listings/|dup_hidden","path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/web.py","output_mode":"content","-n":true,"head_limit":25},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":623,"cache_read_input_tokens":145459,"cache_creation":{"ephemeral_5m_input_tokens":623,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"48c3533b-f1c3-4339-a2bd-b528154a3443"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01PrFanriTAbohJLRyZRBuyb","type":"tool_result","content":"61:# Déduplication PRÉ-CALCULÉE : la colonne `dup_hidden` (remplie par\n69:DEDUP_CLAUSE = \" AND dup_hidden=0 AND published=1\"\n196:@app.get(\"/api/listings/{uid}\")\n227:@app.get(\"/api/listings/{uid}/pdf\")"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"e793ec70-e3c7-4a34-8cf7-5b2bd2993e0f","timestamp":"2026-08-25T14:08:29.841Z","tool_use_result":{"mode":"content","numFiles":0,"filenames":[],"content":"61:# Déduplication PRÉ-CALCULÉE : la colonne `dup_hidden` (remplie par\n69:DEDUP_CLAUSE = \" AND dup_hidden=0 AND published=1\"\n196:@app.get(\"/api/listings/{uid}\")\n227:@app.get(\"/api/listings/{uid}/pdf\")","numLines":4}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"aaf44a63-521d-43f6-b613-5d09b04fbb00","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} 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onSwipe: (dir: 1 | -1) => void }) {\n28\t const [t, setT] = useState({ scale: 1, x: 0, y: 0 });\n29\t const pointers = useRef(new Map());\n30\t const start = useRef({ scale: 1, x: 0, y: 0, dist: 0, cx: 0, cy: 0, t: 0 });\n31\t const lastTap = useRef(0);\n32\t\n33\t // repartir à zéro quand on change de photo\n34\t useEffect(() => { setT({ scale: 1, x: 0, y: 0 }); }, [src]);\n35\t\n36\t const dist = () => {\n37\t const p = [...pointers.current.values()];\n38\t return p.length < 2 ? 0 : Math.hypot(p[0].x - p[1].x, p[0].y - p[1].y);\n39\t };\n40\t const center = () => {\n41\t const p = [...pointers.current.values()];\n42\t return p.length < 2\n43\t ? p[0] ?? { x: 0, y: 0 }\n44\t : { x: (p[0].x + p[1].x) / 2, y: (p[0].y + p[1].y) / 2 };\n45\t };\n46\t\n47\t const onDown = (e: React.PointerEvent) => {\n48\t (e.target as HTMLElement).setPointerCapture(e.pointerId);\n49\t pointers.current.set(e.pointerId, { x: e.clientX, y: e.clientY });\n50\t const c = center();\n51\t start.current = { scale: t.scale, x: t.x, y: t.y, dist: dist(), cx: c.x, cy: c.y, t: Date.now() };\n52\t };\n53\t const onMove = (e: React.PointerEvent) => {\n54\t if (!pointers.current.has(e.pointerId)) return;\n55\t pointers.current.set(e.pointerId, { x: e.clientX, y: e.clientY });\n56\t const s = start.current;\n57\t if (pointers.current.size >= 2 && s.dist > 0) {\n58\t // pincement : zoom autour du centre des deux doigts\n59\t const scale = Math.min(4, Math.max(1, (dist() / s.dist) * s.scale));\n60\t const c = center();\n61\t setT({ scale, x: s.x + (c.x - s.cx), y: s.y + (c.y - s.cy) });\n62\t } else if (pointers.current.size === 1 && t.scale > 1) {\n63\t // panoramique une fois zoomé\n64\t const p = pointers.current.get(e.pointerId)!;\n65\t setT({ scale: t.scale, x: s.x + (p.x - s.cx), y: s.y + (p.y - s.cy) });\n66\t }\n67\t };\n68\t const onUp = (e: React.PointerEvent) => {\n69\t const p = pointers.current.get(e.pointerId);\n70\t pointers.current.delete(e.pointerId);\n71\t const s = start.current;\n72\t if (pointers.current.size === 0 && p) {\n73\t const dx = p.x - s.cx, dy = p.y - s.cy, dt = Date.now() - s.t;\n74\t if (t.scale <= 1.05 && Math.abs(dx) > 56 && Math.abs(dx) > Math.abs(dy) * 1.5) {\n75\t onSwipe(dx < 0 ? 1 : -1); // balayage → photo suivante\n76\t } else if (dt < 260 && Math.abs(dx) < 8 && Math.abs(dy) < 8) {\n77\t const now = Date.now();\n78\t if (now - lastTap.current < 320) // double-tap : zoom ×2.4\n79\t setT(t.scale > 1 ? { scale: 1, x: 0, y: 0 } : { scale: 2.4, x: 0, y: 0 });\n80\t lastTap.current = now;\n81\t }\n82\t if (t.scale <= 1.02) setT({ scale: 1, x: 0, y: 0 });\n83\t }\n84\t };\n85\t\n86\t return (\n87\t 1 ? \"grab\" : \"zoom-out\",\n93\t }}\n94\t onClick={(e) => e.stopPropagation()}\n95\t onPointerDown={onDown} onPointerMove={onMove}\n96\t onPointerUp={onUp} onPointerCancel={onUp}\n97\t />\n98\t );\n99\t}\n100\t\n101\t// --- Galerie : balayage natif (scroll-snap) + vignettes + plein écran --------\n102\tfunction Galerie({ images, captions, titre, type }:\n103\t { images: string[]; captions?: string[]; titre: string; type?: string }) {\n104\t const [idx, setIdx] = useState(0);\n105\t const [zoom, setZoom] = useState(false);\n106\t const [dead, setDead] = useState>(new Set());\n107\t const track = useRef(null);\n108\t\n109\t // images qui ne chargent pas : retirées de la galerie à la volée (jamais\n110\t // d'icône d'image cassée) ; légendes gardées alignées\n111\t const alive = images\n112\t .map((u, i) => ({ u, cap: captions && captions.length === images.length ? captions[i] : \"\" }))\n113\t .filter(({ u }) => !dead.has(u));\n114\t const markDead = (u: string) => setDead((d) => new Set(d).add(u));\n115\t\n116\t const onScroll = () => {\n117\t const el = track.current;\n118\t if (el) setIdx(Math.round(el.scrollLeft / el.clientWidth));\n119\t };\n120\t const goto = (i: number) =>\n121\t track.current?.scrollTo({ left: i * track.current.clientWidth, behavior: \"smooth\" });\n122\t\n123\t useEffect(() => {\n124\t if (!zoom) return;\n125\t const onKey = (e: KeyboardEvent) => {\n126\t if (e.key === \"Escape\") setZoom(false);\n127\t if (e.key === \"ArrowLeft\") setIdx((i) => Math.max(0, i - 1));\n128\t if (e.key === \"ArrowRight\") setIdx((i) => Math.min(alive.length - 1, i + 1));\n129\t };\n130\t window.addEventListener(\"keydown\", onKey);\n131\t // figer l'arrière-plan pendant le plein écran (mobile)\n132\t document.body.style.overflow = \"hidden\";\n133\t return () => {\n134\t window.removeEventListener(\"keydown\", onKey);\n135\t document.body.style.overflow = \"\";\n136\t };\n137\t }, [zoom, alive.length]);\n138\t\n139\t if (alive.length === 0)\n140\t return
;\n141\t\n142\t const cur = Math.min(idx, alive.length - 1);\n143\t const swipe = (dir: 1 | -1) =>\n144\t setIdx((i) => Math.min(alive.length - 1, Math.max(0, i + dir)));\n145\t\n146\t return (\n147\t <>\n148\t
\n149\t
\n150\t {alive.map(({ u }, i) => (\n151\t {`${titre} markDead(u)} onClick={() => setZoom(true)} />\n154\t ))}\n155\t
\n156\t {alive[cur]?.cap && {alive[cur].cap}}\n157\t {cur + 1}/{alive.length}\n158\t {cur > 0 && }\n159\t {cur < alive.length - 1 && }\n160\t
\n161\t {alive.length > 1 && (\n162\t
\n163\t {alive.map(({ u }, i) => (\n164\t \n167\t ))}\n168\t
\n169\t )}\n170\t {zoom && (\n171\t
setZoom(false)} role=\"dialog\" aria-label=\"Photo agrandie\">\n172\t \n173\t {cur > 0 && }\n174\t \n175\t {cur < alive.length - 1 && }\n176\t \n177\t {alive[cur]?.cap ? `${alive[cur].cap} · ` : \"\"}{cur + 1} / {alive.length}\n178\t \n179\t
\n180\t )}\n181\t \n182\t );\n183\t}\n184\t\n185\t// clés techniques de `details` jamais montrées dans « Caractéristiques »\n186\tconst DETAIL_HIDDEN = new Set([\n187\t \"pieces\", \"price_from\", \"cover_thumb\", \"photo_captions\", \"img_audited\",\n188\t \"needs_image_review\", \"postal_code\", \"region\", \"transaction\",\n189\t \"prix_pi2\", \"prix_m2\", \"listing_origin_url\",\n190\t]);\n191\t\n192\t// icône de chaque tuile « spec » (Icons.tsx)\n193\tconst SPEC_ICONS: Record = {\n194\t \"Type\": \"home\", \"Chambres\": \"bed\", \"Salles de bain\": \"bath\",\n195\t \"Salles d'eau\": \"drop\", \"Superficie\": \"area\", \"Terrain\": \"land\",\n196\t \"Année\": \"calendar\", \"MLS / Centris\": \"tag\",\n197\t};\n198\t\n199\texport default function ListingPage() {\n200\t const { uid } = useParams<{ uid: string }>();\n201\t const [l, setL] = useState(null);\n202\t const [error, setError] = useState(null);\n203\t\n204\t useEffect(() => {\n205\t fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});\n206\t if (!uid) return;\n207\t setL(null); setError(null);\n208\t fetchListing(uid).then(setL).catch((e) => setError(String(e)));\n209\t window.scrollTo(0, 0);\n210\t }, [uid]);\n211\t\n212\t if (error)\n213\t return (\n214\t
\n215\t
\n216\t

Propriété introuvable

\n217\t

{error}

\n218\t Retour aux propriétés\n219\t
\n220\t );\n221\t\n222\t if (!l)\n223\t return (\n224\t
\n225\t
\n226\t
\n227\t
\n228\t
\n229\t
\n230\t );\n231\t\n232\t const specs: { k: string; v: string }[] = [];\n233\t if (l.property_type) specs.push({ k: \"Type\", v: l.property_type });\n234\t if (l.bedrooms != null) specs.push({ k: \"Chambres\", v: String(l.bedrooms) });\n235\t if (l.bathrooms != null) specs.push({ k: \"Salles de bain\", v: String(l.bathrooms) });\n236\t if (l.powder_rooms != null) specs.push({ k: \"Salles d'eau\", v: String(l.powder_rooms) });\n237\t if (l.area_sqft != null) specs.push({ k: \"Superficie\", v: fmtArea(l.area_sqft)! });\n238\t if (l.lot_sqft != null) specs.push({ k: \"Terrain\", v: fmtArea(l.lot_sqft)! });\n239\t if (l.year_built != null) specs.push({ k: \"Année\", v: String(l.year_built) });\n240\t if (l.mls) specs.push({ k: \"MLS / Centris\", v: l.mls });\n241\t\n242\t const rooms: Room[] = Array.isArray(l.details?.pieces) ? (l.details!.pieces as Room[]) : [];\n243\t const detEntries = Object.entries(l.details ?? {})\n244\t .filter(([k, v]) => !DETAIL_HIDDEN.has(k) && (typeof v === \"string\" || typeof v === \"number\") && String(v).trim());\n245\t\n246\t // taxes annuelles publiées (Centris) → mensualisées pour le coût réel\n247\t const taxesAnnuelles = [\"Taxes municipales\", \"Taxes scolaires\"]\n248\t .map((k) => {\n249\t const v = l.details?.[k];\n250\t const n = parseInt(String(v ?? \"\").replace(/[^\\d]/g, \"\"), 10);\n251\t return Number.isFinite(n) && n > 0 && n < 200_000 ? n : 0;\n252\t })\n253\t .reduce((a, b) => a + b, 0);\n254\t const estVente = l.details?.transaction !== \"location\";\n255\t\n256\t const hist = (l.price_history ?? []).filter((h) => h.price != null);\n257\t const baisse = hist.length >= 2 && hist[0].price !== hist[1].price\n258\t ? { de: hist[1].price!, a: hist[0].price! } : null;\n259\t const updated = l.updated_at ? fmtDate(l.updated_at) : null;\n260\t\n261\t return (\n262\t
\n263\t \n268\t\n269\t
\n270\t {/* -------- colonne gauche : galerie, prix/synthèse, description, ------\n271\t -------- caractéristiques, pièces — ordre du DOM = ordre visuel ---- */}\n272\t
\n273\t
\n274\t \n281\t
\n282\t\n283\t
\n284\t
\n285\t {l.details?.transaction === \"location\" ? \"Loyer mensuel\" : \"Prix demandé\"}\n286\t
\n287\t
\n288\t
\n289\t {fmtPrice(l.price, l.price_label)}\n290\t {l.details?.transaction === \"location\" && /mois}\n291\t
\n292\t {l.property_type && (\n293\t \n294\t {l.property_type}\n295\t {l.details?.transaction === \"location\" ? \" · location\" : \"\"}\n296\t {l.details?.price_from ? \" · à partir de\" : \"\"}\n297\t \n298\t )}\n299\t
\n300\t {l.price != null && l.area_sqft != null && l.area_sqft > 200 && (\n301\t
{Math.round(l.price / l.area_sqft).toLocaleString(\"fr-CA\")} $ / pi² habitable
\n302\t )}\n303\t

{l.address || l.title}

\n304\t
{[l.sector, l.city, l.region].filter(Boolean).join(\" · \")}
\n305\t\n306\t
\n307\t {specs.map((s) => (\n308\t
\n309\t \n310\t {s.k}\n311\t {s.v}\n312\t
\n313\t ))}\n314\t
\n315\t\n316\t {baisse && (\n317\t
\n318\t Prix passé de {fmtPrice(baisse.de)} à {fmtPrice(baisse.a)}\n319\t
\n320\t )}\n321\t\n322\t {l.vraiprix && l.vraiprix.value != null && (\n323\t
\n324\t
\n325\t Vrai‑Prix\n326\t {l.vraiprix.confidence && (\n327\t \n328\t confiance {l.vraiprix.confidence}\n329\t \n330\t )}\n331\t
\n332\t
Valeur marchande estimée
\n333\t
{fmtPrice(l.vraiprix.value)}
\n334\t {l.vraiprix.low != null && l.vraiprix.high != null && (() => {\n335\t const lo = l.vraiprix!.low as number, hi = l.vraiprix!.high as number;\n336\t const span = Math.max(1, hi - lo);\n337\t const pos = (v: number) => `${Math.max(2, Math.min(98, ((v - lo) / span) * 100))}%`;\n338\t return (\n339\t
\n340\t
\n341\t \n342\t \n343\t {l.price != null && l.price >= lo * 0.7 && l.price <= hi * 1.3 && (\n344\t \n345\t )}\n346\t
\n347\t
\n348\t {fmtPrice(lo)}\n349\t {fmtPrice(hi)}\n350\t
\n351\t {l.price != null && l.price >= lo * 0.7 && l.price <= hi * 1.3 && (\n352\t
\n353\t estimation\n354\t prix demandé\n355\t
\n356\t )}\n357\t
\n358\t );\n359\t })()}\n360\t {l.price != null && (\n361\t (() => {\n362\t const diff = l.price - (l.vraiprix!.value as number);\n363\t const pct = Math.round((diff / (l.vraiprix!.value as number)) * 100);\n364\t const cls = diff > 0 ? \"over\" : \"under\";\n365\t const txt = diff > 0\n366\t ? `Prix demandé ${pct}% au-dessus de l'estimation`\n367\t : `Prix demandé ${Math.abs(pct)}% sous l'estimation`;\n368\t if (Math.abs(pct) > 60) return null; // prix non comparable (loyer, terrain…)\n369\t return Math.abs(pct) >= 1\n370\t ?
{diff > 0 ? \"▲\" : \"▼\"} {txt}
\n371\t :
≈ Prix aligné sur l'estimation
;\n372\t })()\n373\t )}\n374\t \n375\t Voir l'analyse détaillée ↗\n376\t \n377\t
\n378\t )}\n379\t\n380\t {(l.broker_name || l.broker_phone) && (\n381\t
\n382\t
Courtier
\n383\t {l.broker_name &&
{l.broker_name}
}\n384\t {l.broker_phone && {l.broker_phone}}\n385\t
\n386\t )}\n387\t\n388\t \n389\t Voir l'annonce chez {sourceName(l.source)} \n390\t \n391\t \n392\t Télécharger la fiche (PDF) \n393\t \n394\t
\n395\t Agrégé par Immo-Ka — {sourceName(l.source)}{updated ? ` · synchronisé le ${updated}` : \"\"}.\n396\t
\n397\t
\n398\t\n399\t\n400\t {l.description && (\n401\t
\n402\t

Description

\n403\t

{l.description}

\n404\t
\n405\t )}\n406\t\n407\t {detEntries.length > 0 && (\n408\t
\n409\t

Caractéristiques

\n410\t
\n411\t {detEntries.map(([k, v]) => (\n412\t
\n413\t {k}\n414\t {/^https?:\\/\\//.test(String(v))\n415\t ? Ouvrir ↗\n416\t : {String(v)}}\n417\t
\n418\t ))}\n419\t
\n420\t
\n421\t )}\n422\t\n423\t {rooms.length > 0 && (\n424\t
\n425\t

Pièces

\n426\t
\n427\t \n428\t \n429\t \n430\t {rooms.map((r, i) => (\n431\t \n432\t \n433\t \n434\t \n435\t ))}\n436\t \n437\t
PièceNiveauDimensionsRevêtement
{r.nom || \"—\"}{r.niveau || \"—\"}{r.dimensions || \"—\"}{r.revetement || \"—\"}
\n438\t
\n439\t
\n440\t )}\n441\t\n442\t
\n443\t\n444\t {/* -------- colonne droite (desktop) : inclusions, carte ------------- */}\n445\t
\n446\t {l.features && l.features.length > 0 && (\n447\t
\n448\t

Inclusions

\n449\t
\n450\t {l.features.map((f, i) => {f})}\n451\t
\n452\t
\n453\t )}\n454\t\n455\t {l.lat != null && l.lng != null && (\n456\t
\n457\t

Emplacement

\n458\t Chargement de la carte…
}>\n459\t \n466\t \n467\t \n468\t )}\n469\t
\n470\t
\n471\t\n472\t {/* financement : taux hypothécaires réels + calculateur canadien */}\n473\t {estVente && (\n474\t 0 ? Math.round(taxesAnnuelles / 12) : null}\n477\t />\n478\t )}\n479\t\n480\t {/* quartier : pleine largeur, APRÈS les infos de propriété (ordre mobile correct) */}\n481\t \n482\t\n483\t \n484\t\n485\t \n486\t\n487\t \n488\t\n489\t \n490\t\n491\t {l.quartier && }\n492\t\n493\t
\n494\t Les prix et disponibilités sont ceux affichés par la source — chaque fiche renvoie à\n495\t l'annonce originale de l'agence.\n496\t
\n497\t\n498\t
\n499\t {fmtPrice(l.price, l.price_label)}\n500\t \n501\t Voir chez {sourceName(l.source)} ↗\n502\t \n503\t
\n504\t
\n505\t );\n506\t}\n507\t"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"39fa3558-ad27-4300-bcfd-d05f40e9a220","timestamp":"2026-08-25T14:09:32.166Z","tool_use_result":{"type":"text","file":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/frontend/src/pages/Listing.tsx","content":"// -----------------------------------------------------------------------------\n// Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n// Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n// pages/Listing.tsx : fiche complète d'une propriété\n// galerie + lightbox · specs · caractéristiques (details) · pièces ·\n// inclusions · description · historique de prix · courtier · mini-carte\n// -----------------------------------------------------------------------------\nimport { Suspense, lazy, useEffect, useRef, useState } from \"react\";\nimport { Link, useParams } from \"react-router-dom\";\nimport {\n Listing, Room, fetchListing, fetchSources, fmtArea, fmtDate, fmtPrice,\n registerSourceNames, sourceName,\n} from \"../api\";\n\nconst PropertyMap = lazy(() => import(\"../components/PropertyMap\"));\nimport Financement from \"../components/Financement\";\nimport QuartierBlock from \"../components/QuartierBlock\";\nimport RisqueInondation from \"../components/RisqueInondation\";\nimport QualiteAir from \"../components/QualiteAir\";\nimport EssenceProche from \"../components/EssenceProche\";\nimport HydroEstimation from \"../components/HydroEstimation\";\nimport CommercesProches from \"../components/CommercesProches\";\nimport { Ico } from \"../components/Icons\";\nimport { TypeFallback } from \"../components/PropertyImg\";\n\n// --- Lightbox : pincement pour zoomer + panoramique + balayage entre photos ---\nfunction ZoomImg({ src, onSwipe }: { src: string; onSwipe: (dir: 1 | -1) => void }) {\n const [t, setT] = useState({ scale: 1, x: 0, y: 0 });\n const pointers = useRef(new Map());\n const start = useRef({ scale: 1, x: 0, y: 0, dist: 0, cx: 0, cy: 0, t: 0 });\n const lastTap = useRef(0);\n\n // repartir à zéro quand on change de photo\n useEffect(() => { setT({ scale: 1, x: 0, y: 0 }); }, [src]);\n\n const dist = () => {\n const p = [...pointers.current.values()];\n return p.length < 2 ? 0 : Math.hypot(p[0].x - p[1].x, p[0].y - p[1].y);\n };\n const center = () => {\n const p = [...pointers.current.values()];\n return p.length < 2\n ? p[0] ?? { x: 0, y: 0 }\n : { x: (p[0].x + p[1].x) / 2, y: (p[0].y + p[1].y) / 2 };\n };\n\n const onDown = (e: React.PointerEvent) => {\n (e.target as HTMLElement).setPointerCapture(e.pointerId);\n pointers.current.set(e.pointerId, { x: e.clientX, y: e.clientY });\n const c = center();\n start.current = { scale: t.scale, x: t.x, y: t.y, dist: dist(), cx: c.x, cy: c.y, t: Date.now() };\n };\n const onMove = (e: React.PointerEvent) => {\n if (!pointers.current.has(e.pointerId)) return;\n pointers.current.set(e.pointerId, { x: e.clientX, y: e.clientY });\n const s = start.current;\n if (pointers.current.size >= 2 && s.dist > 0) {\n // pincement : zoom autour du centre des deux doigts\n const scale = Math.min(4, Math.max(1, (dist() / s.dist) * s.scale));\n const c = center();\n setT({ scale, x: s.x + (c.x - s.cx), y: s.y + (c.y - s.cy) });\n } else if (pointers.current.size === 1 && t.scale > 1) {\n // panoramique une fois zoomé\n const p = pointers.current.get(e.pointerId)!;\n setT({ scale: t.scale, x: s.x + (p.x - s.cx), y: s.y + (p.y - s.cy) });\n }\n };\n const onUp = (e: React.PointerEvent) => {\n const p = pointers.current.get(e.pointerId);\n pointers.current.delete(e.pointerId);\n const s = start.current;\n if (pointers.current.size === 0 && p) {\n const dx = p.x - s.cx, dy = p.y - s.cy, dt = Date.now() - s.t;\n if (t.scale <= 1.05 && Math.abs(dx) > 56 && Math.abs(dx) > Math.abs(dy) * 1.5) {\n onSwipe(dx < 0 ? 1 : -1); // balayage → photo suivante\n } else if (dt < 260 && Math.abs(dx) < 8 && Math.abs(dy) < 8) {\n const now = Date.now();\n if (now - lastTap.current < 320) // double-tap : zoom ×2.4\n setT(t.scale > 1 ? { scale: 1, x: 0, y: 0 } : { scale: 2.4, x: 0, y: 0 });\n lastTap.current = now;\n }\n if (t.scale <= 1.02) setT({ scale: 1, x: 0, y: 0 });\n }\n };\n\n return (\n 1 ? \"grab\" : \"zoom-out\",\n }}\n onClick={(e) => e.stopPropagation()}\n onPointerDown={onDown} onPointerMove={onMove}\n onPointerUp={onUp} onPointerCancel={onUp}\n />\n );\n}\n\n// --- Galerie : balayage natif (scroll-snap) + vignettes + plein écran --------\nfunction Galerie({ images, captions, titre, type }:\n { images: string[]; captions?: string[]; titre: string; type?: string }) {\n const [idx, setIdx] = useState(0);\n const [zoom, setZoom] = useState(false);\n const [dead, setDead] = useState>(new Set());\n const track = useRef(null);\n\n // images qui ne chargent pas : retirées de la galerie à la volée (jamais\n // d'icône d'image cassée) ; légendes gardées alignées\n const alive = images\n .map((u, i) => ({ u, cap: captions && captions.length === images.length ? captions[i] : \"\" }))\n .filter(({ u }) => !dead.has(u));\n const markDead = (u: string) => setDead((d) => new Set(d).add(u));\n\n const onScroll = () => {\n const el = track.current;\n if (el) setIdx(Math.round(el.scrollLeft / el.clientWidth));\n };\n const goto = (i: number) =>\n track.current?.scrollTo({ left: i * track.current.clientWidth, behavior: \"smooth\" });\n\n useEffect(() => {\n if (!zoom) return;\n const onKey = (e: KeyboardEvent) => {\n if (e.key === \"Escape\") setZoom(false);\n if (e.key === \"ArrowLeft\") setIdx((i) => Math.max(0, i - 1));\n if (e.key === \"ArrowRight\") setIdx((i) => Math.min(alive.length - 1, i + 1));\n };\n window.addEventListener(\"keydown\", onKey);\n // figer l'arrière-plan pendant le plein écran (mobile)\n document.body.style.overflow = \"hidden\";\n return () => {\n window.removeEventListener(\"keydown\", onKey);\n document.body.style.overflow = \"\";\n };\n }, [zoom, alive.length]);\n\n if (alive.length === 0)\n return
;\n\n const cur = Math.min(idx, alive.length - 1);\n const swipe = (dir: 1 | -1) =>\n setIdx((i) => Math.min(alive.length - 1, Math.max(0, i + dir)));\n\n return (\n <>\n
\n
\n {alive.map(({ u }, i) => (\n {`${titre} markDead(u)} onClick={() => setZoom(true)} />\n ))}\n
\n {alive[cur]?.cap && {alive[cur].cap}}\n {cur + 1}/{alive.length}\n {cur > 0 && }\n {cur < alive.length - 1 && }\n
\n {alive.length > 1 && (\n
\n {alive.map(({ u }, i) => (\n \n ))}\n
\n )}\n {zoom && (\n
setZoom(false)} role=\"dialog\" aria-label=\"Photo agrandie\">\n \n {cur > 0 && }\n \n {cur < alive.length - 1 && }\n \n {alive[cur]?.cap ? `${alive[cur].cap} · ` : \"\"}{cur + 1} / {alive.length}\n \n
\n )}\n \n );\n}\n\n// clés techniques de `details` jamais montrées dans « Caractéristiques »\nconst DETAIL_HIDDEN = new Set([\n \"pieces\", \"price_from\", \"cover_thumb\", \"photo_captions\", \"img_audited\",\n \"needs_image_review\", \"postal_code\", \"region\", \"transaction\",\n \"prix_pi2\", \"prix_m2\", \"listing_origin_url\",\n]);\n\n// icône de chaque tuile « spec » (Icons.tsx)\nconst SPEC_ICONS: Record = {\n \"Type\": \"home\", \"Chambres\": \"bed\", \"Salles de bain\": \"bath\",\n \"Salles d'eau\": \"drop\", \"Superficie\": \"area\", \"Terrain\": \"land\",\n \"Année\": \"calendar\", \"MLS / Centris\": \"tag\",\n};\n\nexport default function ListingPage() {\n const { uid } = useParams<{ uid: string }>();\n const [l, setL] = useState(null);\n const [error, setError] = useState(null);\n\n useEffect(() => {\n fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});\n if (!uid) return;\n setL(null); setError(null);\n fetchListing(uid).then(setL).catch((e) => setError(String(e)));\n window.scrollTo(0, 0);\n }, [uid]);\n\n if (error)\n return (\n
\n
\n

Propriété introuvable

\n

{error}

\n Retour aux propriétés\n
\n );\n\n if (!l)\n return (\n
\n
\n
\n
\n
\n
\n );\n\n const specs: { k: string; v: string }[] = [];\n if (l.property_type) specs.push({ k: \"Type\", v: l.property_type });\n if (l.bedrooms != null) specs.push({ k: \"Chambres\", v: String(l.bedrooms) });\n if (l.bathrooms != null) specs.push({ k: \"Salles de bain\", v: String(l.bathrooms) });\n if (l.powder_rooms != null) specs.push({ k: \"Salles d'eau\", v: String(l.powder_rooms) });\n if (l.area_sqft != null) specs.push({ k: \"Superficie\", v: fmtArea(l.area_sqft)! });\n if (l.lot_sqft != null) specs.push({ k: \"Terrain\", v: fmtArea(l.lot_sqft)! });\n if (l.year_built != null) specs.push({ k: \"Année\", v: String(l.year_built) });\n if (l.mls) specs.push({ k: \"MLS / Centris\", v: l.mls });\n\n const rooms: Room[] = Array.isArray(l.details?.pieces) ? (l.details!.pieces as Room[]) : [];\n const detEntries = Object.entries(l.details ?? {})\n .filter(([k, v]) => !DETAIL_HIDDEN.has(k) && (typeof v === \"string\" || typeof v === \"number\") && String(v).trim());\n\n // taxes annuelles publiées (Centris) → mensualisées pour le coût réel\n const taxesAnnuelles = [\"Taxes municipales\", \"Taxes scolaires\"]\n .map((k) => {\n const v = l.details?.[k];\n const n = parseInt(String(v ?? \"\").replace(/[^\\d]/g, \"\"), 10);\n return Number.isFinite(n) && n > 0 && n < 200_000 ? n : 0;\n })\n .reduce((a, b) => a + b, 0);\n const estVente = l.details?.transaction !== \"location\";\n\n const hist = (l.price_history ?? []).filter((h) => h.price != null);\n const baisse = hist.length >= 2 && hist[0].price !== hist[1].price\n ? { de: hist[1].price!, a: hist[0].price! } : null;\n const updated = l.updated_at ? fmtDate(l.updated_at) : null;\n\n return (\n
\n \n\n
\n {/* -------- colonne gauche : galerie, prix/synthèse, description, ------\n -------- caractéristiques, pièces — ordre du DOM = ordre visuel ---- */}\n
\n
\n \n
\n\n
\n
\n {l.details?.transaction === \"location\" ? \"Loyer mensuel\" : \"Prix demandé\"}\n
\n
\n
\n {fmtPrice(l.price, l.price_label)}\n {l.details?.transaction === \"location\" && /mois}\n
\n {l.property_type && (\n \n {l.property_type}\n {l.details?.transaction === \"location\" ? \" · location\" : \"\"}\n {l.details?.price_from ? \" · à partir de\" : \"\"}\n \n )}\n
\n {l.price != null && l.area_sqft != null && l.area_sqft > 200 && (\n
{Math.round(l.price / l.area_sqft).toLocaleString(\"fr-CA\")} $ / pi² habitable
\n )}\n

{l.address || l.title}

\n
{[l.sector, l.city, l.region].filter(Boolean).join(\" · \")}
\n\n
\n {specs.map((s) => (\n
\n \n {s.k}\n {s.v}\n
\n ))}\n
\n\n {baisse && (\n
\n Prix passé de {fmtPrice(baisse.de)} à {fmtPrice(baisse.a)}\n
\n )}\n\n {l.vraiprix && l.vraiprix.value != null && (\n
\n
\n Vrai‑Prix\n {l.vraiprix.confidence && (\n \n confiance {l.vraiprix.confidence}\n \n )}\n
\n
Valeur marchande estimée
\n
{fmtPrice(l.vraiprix.value)}
\n {l.vraiprix.low != null && l.vraiprix.high != null && (() => {\n const lo = l.vraiprix!.low as number, hi = l.vraiprix!.high as number;\n const span = Math.max(1, hi - lo);\n const pos = (v: number) => `${Math.max(2, Math.min(98, ((v - lo) / span) * 100))}%`;\n return (\n
\n
\n \n \n {l.price != null && l.price >= lo * 0.7 && l.price <= hi * 1.3 && (\n \n )}\n
\n
\n {fmtPrice(lo)}\n {fmtPrice(hi)}\n
\n {l.price != null && l.price >= lo * 0.7 && l.price <= hi * 1.3 && (\n
\n estimation\n prix demandé\n
\n )}\n
\n );\n })()}\n {l.price != null && (\n (() => {\n const diff = l.price - (l.vraiprix!.value as number);\n const pct = Math.round((diff / (l.vraiprix!.value as number)) * 100);\n const cls = diff > 0 ? \"over\" : \"under\";\n const txt = diff > 0\n ? `Prix demandé ${pct}% au-dessus de l'estimation`\n : `Prix demandé ${Math.abs(pct)}% sous l'estimation`;\n if (Math.abs(pct) > 60) return null; // prix non comparable (loyer, terrain…)\n return Math.abs(pct) >= 1\n ?
{diff > 0 ? \"▲\" : \"▼\"} {txt}
\n :
≈ Prix aligné sur l'estimation
;\n })()\n )}\n \n Voir l'analyse détaillée ↗\n \n
\n )}\n\n {(l.broker_name || l.broker_phone) && (\n
\n
Courtier
\n {l.broker_name &&
{l.broker_name}
}\n {l.broker_phone && {l.broker_phone}}\n
\n )}\n\n \n Voir l'annonce chez {sourceName(l.source)} \n \n \n Télécharger la fiche (PDF) \n \n
\n Agrégé par Immo-Ka — {sourceName(l.source)}{updated ? ` · synchronisé le ${updated}` : \"\"}.\n
\n
\n\n\n {l.description && (\n
\n

Description

\n

{l.description}

\n
\n )}\n\n {detEntries.length > 0 && (\n
\n

Caractéristiques

\n
\n {detEntries.map(([k, v]) => (\n
\n {k}\n {/^https?:\\/\\//.test(String(v))\n ? Ouvrir ↗\n : {String(v)}}\n
\n ))}\n
\n
\n )}\n\n {rooms.length > 0 && (\n
\n

Pièces

\n
\n \n \n \n {rooms.map((r, i) => (\n \n \n \n \n ))}\n \n
PièceNiveauDimensionsRevêtement
{r.nom || \"—\"}{r.niveau || \"—\"}{r.dimensions || \"—\"}{r.revetement || \"—\"}
\n
\n
\n )}\n\n
\n\n {/* -------- colonne droite (desktop) : inclusions, carte ------------- */}\n
\n {l.features && l.features.length > 0 && (\n
\n

Inclusions

\n
\n {l.features.map((f, i) => {f})}\n
\n
\n )}\n\n {l.lat != null && l.lng != null && (\n
\n

Emplacement

\n Chargement de la carte…
}>\n \n \n \n )}\n
\n
\n\n {/* financement : taux hypothécaires réels + calculateur canadien */}\n {estVente && (\n 0 ? Math.round(taxesAnnuelles / 12) : null}\n />\n )}\n\n {/* quartier : pleine largeur, APRÈS les infos de propriété (ordre mobile correct) */}\n \n\n \n\n \n\n \n\n \n\n {l.quartier && }\n\n
\n Les prix et disponibilités sont ceux affichés par la source — chaque fiche renvoie à\n l'annonce originale de l'agence.\n
\n\n
\n {fmtPrice(l.price, l.price_label)}\n \n Voir chez {sourceName(l.source)} ↗\n \n
\n
\n );\n}\n","numLines":507,"startLine":1,"totalLines":507}}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"7c7c5e2f-e6f1-48cf-9f93-52acc6a28446","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbjesRVHPM2NEb5keTs","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":10469,"cache_read_input_tokens":155961,"cache_creation":{"ephemeral_5m_input_tokens":10469,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"038f1e86-7b40-46ab-bb98-1b4b4aeb50a1"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbjesRVHPM2NEb5keTs","type":"message","role":"assistant","content":[{"type":"text","text":"Je regarde l'endpoint détail côté API et le type `Listing` du frontend."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":10469,"cache_read_input_tokens":155961,"cache_creation":{"ephemeral_5m_input_tokens":10469,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"fb814d74-087b-43d3-a024-b1b9f36728df"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbjesRVHPM2NEb5keTs","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Q6AURQ76LPMNJN3GujXt84","name":"Bash","input":{"command":"sed -n '190,235p' ~/apps/immo-ka/immoka/web.py","description":"Lire l'endpoint /api/listings/{uid}"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":10469,"cache_read_input_tokens":155961,"cache_creation":{"ephemeral_5m_input_tokens":10469,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ece21145-ce45-47e7-be54-a2a69b560257"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Q6AURQ76LPMNJN3GujXt84","type":"tool_result","content":" d = inondation.lookup(lat, lng)\n if d is None:\n raise HTTPException(404, \"Base des zones inondables non disponible\")\n return d\n\n\n@app.get(\"/api/listings/{uid}\")\ndef get_listing(uid: str):\n con = db.connect()\n row = con.execute(\"SELECT * FROM listings WHERE uid=?\", (uid,)).fetchone()\n d = None\n if row is not None:\n d = _row_to_dict(row)\n # historique de prix (baisses/hausses du prix demandé)\n d[\"price_history\"] = [dict(r) for r in con.execute(\n \"SELECT ts, price FROM price_log WHERE uid=? ORDER BY ts DESC LIMIT 10\",\n (uid,)).fetchall()]\n # commodités de proximité (cache par immeuble, voir immoka/poi.py)\n if d.get(\"lat\") is not None and d.get(\"lng\") is not None:\n key = f\"{round(d['lat'], 4)},{round(d['lng'], 4)}\"\n poi_row = con.execute(\n \"SELECT pois FROM poi_cache WHERE coord_key=?\", (key,)).fetchone()\n d[\"poi\"] = json.loads(poi_row[\"pois\"]) if poi_row else []\n else:\n d[\"poi\"] = []\n # statistiques de quartier (recensement, proximité, chaleur, criminalité)\n from . import quartier\n dauid = d.get(\"dauid\")\n d[\"quartier\"] = quartier.fiche_quartier(\n d.get(\"lat\"), d.get(\"lng\"), d.get(\"city\") or \"\",\n dauid if dauid and dauid != \"hors-zone\" else None)\n con.close()\n if d is None:\n raise HTTPException(404, \"Propriété introuvable\")\n return d\n\n\n@app.get(\"/api/listings/{uid}/pdf\")\ndef listing_pdf(uid: str):\n \"\"\"Fiche PDF complète de la propriété (immoka/pdffiche.py) — reflète tous\n les blocs de la fiche web : prix + verdict Vrai-Prix, photos, description,\n caractéristiques, pièces, analyses, environnement, quartier, QR.\"\"\"\n from . import pdffiche\n data = pdffiche.fiche_pdf(uid)\n if data is None:\n raise HTTPException(404, \"Propriété introuvable\")","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"bb6072d9-e567-43f0-93b3-73ac8d81c170","timestamp":"2026-08-25T14:09:40.919Z","tool_use_result":{"stdout":" d = inondation.lookup(lat, lng)\n if d is None:\n raise HTTPException(404, \"Base des zones inondables non disponible\")\n return d\n\n\n@app.get(\"/api/listings/{uid}\")\ndef get_listing(uid: str):\n con = db.connect()\n row = con.execute(\"SELECT * FROM listings WHERE uid=?\", (uid,)).fetchone()\n d = None\n if row is not None:\n d = _row_to_dict(row)\n # historique de prix (baisses/hausses du prix demandé)\n d[\"price_history\"] = [dict(r) for r in con.execute(\n \"SELECT ts, price FROM price_log WHERE uid=? ORDER BY ts DESC LIMIT 10\",\n (uid,)).fetchall()]\n # commodités de proximité (cache par immeuble, voir immoka/poi.py)\n if d.get(\"lat\") is not None and d.get(\"lng\") is not None:\n key = f\"{round(d['lat'], 4)},{round(d['lng'], 4)}\"\n poi_row = con.execute(\n \"SELECT pois FROM poi_cache WHERE coord_key=?\", (key,)).fetchone()\n d[\"poi\"] = json.loads(poi_row[\"pois\"]) if poi_row else []\n else:\n d[\"poi\"] = []\n # statistiques de quartier (recensement, proximité, chaleur, criminalité)\n from . import quartier\n dauid = d.get(\"dauid\")\n d[\"quartier\"] = quartier.fiche_quartier(\n d.get(\"lat\"), d.get(\"lng\"), d.get(\"city\") or \"\",\n dauid if dauid and dauid != \"hors-zone\" else None)\n con.close()\n if d is None:\n raise HTTPException(404, \"Propriété introuvable\")\n return d\n\n\n@app.get(\"/api/listings/{uid}/pdf\")\ndef listing_pdf(uid: str):\n \"\"\"Fiche PDF complète de la propriété (immoka/pdffiche.py) — reflète tous\n les blocs de la fiche web : prix + verdict Vrai-Prix, photos, description,\n caractéristiques, pièces, analyses, environnement, quartier, QR.\"\"\"\n from . import pdffiche\n data = pdffiche.fiche_pdf(uid)\n if data is None:\n raise HTTPException(404, \"Propriété introuvable\")","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbjesRVHPM2NEb5keTs","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01NEzqvo5w539h5QxQg8JumV","name":"Bash","input":{"command":"sed -n '1,90p' ~/apps/immo-ka/frontend/src/api.ts && grep -n \"fetchListing\" ~/apps/immo-ka/frontend/src/api.ts","description":"Lire le type Listing et fetchListing"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":10469,"cache_read_input_tokens":155961,"cache_creation":{"ephemeral_5m_input_tokens":10469,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"1f743f47-612c-4455-a787-8a850d9b237b"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01NEzqvo5w539h5QxQg8JumV","type":"tool_result","content":"// -----------------------------------------------------------------------------\n// Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n// Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n// api.ts : types + client API robuste (timeout, erreurs typées)\n// -----------------------------------------------------------------------------\n\nexport interface Room {\n nom?: string;\n niveau?: string;\n dimensions?: string;\n revetement?: string;\n}\n\n/** details : dictionnaire libre de caractéristiques Centris (libellé → valeur),\n * avec la clé spéciale `pieces` (liste des pièces + dimensions). */\nexport interface ListingDetails {\n pieces?: Room[];\n price_from?: boolean;\n [key: string]: unknown;\n}\n\nexport interface Listing {\n uid: string;\n source: string;\n external_id: string;\n url: string;\n title: string;\n address: string;\n sector: string;\n city: string;\n region: string;\n property_type: string;\n price: number | null;\n price_label: string;\n bedrooms: number | null;\n bathrooms: number | null;\n powder_rooms: number | null;\n area_sqft: number | null;\n lot_sqft: number | null;\n year_built: number | null;\n mls: string;\n status: string;\n broker_name: string;\n broker_phone: string;\n description: string;\n features: string[];\n details: ListingDetails;\n images: string[];\n lat: number | null;\n lng: number | null;\n price_history?: { ts: number; price: number | null }[];\n poi?: Poi[]; // commodités de proximité (fiche seulement)\n quartier?: Quartier | null; // stats de quartier (fiche seulement)\n vraiprix?: VraiPrix | null; // estimation de valeur marchande (Vrai-Prix)\n first_seen?: number;\n last_seen?: number;\n updated_at?: number;\n active?: number;\n}\n\nexport interface Facets {\n cities: string[];\n sectors: string[];\n property_types: string[];\n sources: { source: string; n: number }[];\n}\n\nexport interface Source {\n id: string;\n name: string;\n url: string;\n listing_url?: string;\n coverage?: string;\n type?: string;\n connector?: string | null;\n status: string;\n active_listings: number;\n last_sync: number | null;\n}\n\nexport interface Stats {\n total: number;\n sources: number;\n cities: number;\n avg_price: number | null;\n min_price: number | null;\n max_price: number | null;\n recent_syncs?: {\n source: string; ts: number; found: number; added: number;\n updated: number; removed: number; ok: number; message: string;\n170:export function fetchListings(f: ListingFilters, limit = 60, offset = 0) {\n178:export const fetchListing = (uid: string) =>","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"bd9f73fd-4916-4e3f-9bb4-96817c934de6","timestamp":"2026-08-25T14:09:41.644Z","tool_use_result":{"stdout":"// -----------------------------------------------------------------------------\n// Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n// Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n// api.ts : types + client API robuste (timeout, erreurs typées)\n// -----------------------------------------------------------------------------\n\nexport interface Room {\n nom?: string;\n niveau?: string;\n dimensions?: string;\n revetement?: string;\n}\n\n/** details : dictionnaire libre de caractéristiques Centris (libellé → valeur),\n * avec la clé spéciale `pieces` (liste des pièces + dimensions). */\nexport interface ListingDetails {\n pieces?: Room[];\n price_from?: boolean;\n [key: string]: unknown;\n}\n\nexport interface Listing {\n uid: string;\n source: string;\n external_id: string;\n url: string;\n title: string;\n address: string;\n sector: string;\n city: string;\n region: string;\n property_type: string;\n price: number | null;\n price_label: string;\n bedrooms: number | null;\n bathrooms: number | null;\n powder_rooms: number | null;\n area_sqft: number | null;\n lot_sqft: number | null;\n year_built: number | null;\n mls: string;\n status: string;\n broker_name: string;\n broker_phone: string;\n description: string;\n features: string[];\n details: ListingDetails;\n images: string[];\n lat: number | null;\n lng: number | null;\n price_history?: { ts: number; price: number | null }[];\n poi?: Poi[]; // commodités de proximité (fiche seulement)\n quartier?: Quartier | null; // stats de quartier (fiche seulement)\n vraiprix?: VraiPrix | null; // estimation de valeur marchande (Vrai-Prix)\n first_seen?: number;\n last_seen?: number;\n updated_at?: number;\n active?: number;\n}\n\nexport interface Facets {\n cities: string[];\n sectors: string[];\n property_types: string[];\n sources: { source: string; n: number }[];\n}\n\nexport interface Source {\n id: string;\n name: string;\n url: string;\n listing_url?: string;\n coverage?: string;\n type?: string;\n connector?: string | null;\n status: string;\n active_listings: number;\n last_sync: number | null;\n}\n\nexport interface Stats {\n total: number;\n sources: number;\n cities: number;\n avg_price: number | null;\n min_price: number | null;\n max_price: number | null;\n recent_syncs?: {\n source: string; ts: number; found: number; added: number;\n updated: number; removed: number; ok: number; message: string;\n170:export function fetchListings(f: ListingFilters, limit = 60, offset = 0) {\n178:export const fetchListing = (uid: string) =>","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"8f9c6801-2279-4d58-acb7-9787ff29d175","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"system","subtype":"status","status":"compacting","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"9a6cc26a-cf96-46a6-bcce-b1c830bd4951"}} {"type":"claude","event":{"type":"system","subtype":"status","status":null,"compact_result":"success","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"468209e4-49d6-439b-8b3d-f2c5f8d0ac08"}} {"type":"claude","event":{"type":"system","subtype":"compact_boundary","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"53631787-fe33-45b5-8242-1291f60b9afb","compact_metadata":{"trigger":"auto","pre_tokens":167973,"post_tokens":7417,"duration_ms":106058}}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"type":"text","text":"This session is being continued from a previous conversation that ran out of context. The summary below covers the earlier portion of the conversation.\n\nSummary:\n1. Primary Request and Intent:\n The user (French-speaking, informal style) made several requests in sequence on the **immo-ka** app (`/Users/simon-pierreboucher/apps/immo-ka`, a Québec real-estate listing aggregator):\n \n 1. **Fix geocoding bug (COMPLETED)**: Listing `duproprio:1126225` (4671 rue des Perdrix, Jonquière/Lac-Kénogami, Saguenay) was displayed at Saint-Augustin (~180 km away, similar street name elsewhere). Asked to fix the bug AND make the geocode engine more rigorous (\"peux tu faire geocode plus rigoureux\").\n 2. **Provide URL of a listing with hydro cost cached (COMPLETED)**: answered with via_capitale:24955327.\n 3. **Count hydro-cached listings (COMPLETED)**: 226 with cost, 113 active+published.\n 4. **Check for broker \"Laberge\" listings in Québec (COMPLETED)**: found Simon Laberge (Via Capitale Équipe), 3 Ch. Charles-Trudel, Québec — but noted the visible deduplicated version is the anonymous FB Marketplace fiche.\n 5. **CURRENT/ACTIVE REQUEST**: \"J'aimerais que lorsque duplication on affiche annonce du courtier avec mention et lien pour les duplication aussi dans une nouvelle box qu'on va devoir ajoute\" — When duplicates exist: (a) the dedup should display the BROKER's version of the listing (not an anonymous one like FB Marketplace), and (b) add a NEW BOX on the listing detail page showing the duplicate versions with source mention and links.\n\n2. Key Technical Concepts:\n - **Stack**: Python (FastAPI/uvicorn backend `immoka/web.py`), SQLite (`data/immoka.db` + satellite DBs `hydro.db`, etc.), React/Vite/TypeScript frontend (`frontend/src/`), PM2 processes (`immo-ka-web`, `immo-ka-sync`), local port 8096, deployed at www.immo-ka.com\n - **Geocoding**: Adresses Québec (MERN ArcGIS `findAddressCandidates` / `geocodeAddresses` batch, score threshold `AQ_MIN_SCORE=75`) primary; Nominatim (1 req/s, `REQUEST_DELAY=1.1`) fallback; cache table `geocode_cache` keyed by `norm_key(address)`\n - **Hard-won gotchas**: AQ only knows OFFICIAL municipality names (\"Saguenay\"), not boroughs/sectors (\"Jonquière (Lac-Kénogami)\"); Québec has HOMONYM municipalities (two L'Ange-Gardien, Saint-Donat, Sainte-Félicité, Saint-Cyprien…) so a single per-city-name centroid causes mass false positives — must use CLUSTERS\n - **New rigorous validation**: every geocode result must be ≤ `VILLE_RADIUS_KM=40` km of a city reference = clusters of already-geocoded listings (trusted at `CLUSTER_MIN=3`) + Nominatim city point (cached as `ville:` keys with new `muni` column)\n - **Deduplication** (`db.refresh_dedup`): 3 passes — (1) `_ag_` sub-agencies masked by canonical same external_id, (2) min-uid among remaining sub-agencies, (3) `dedup_by_address()` inter-source (address key + type + price ±1%), authority via `_source_rank` (0=primary incl. fb_marketplace, 1=`_ag_`, 2=`_PETITES_ANNONCES` {kijiji, lespac}), tie-break min uid; `_mask_cluster` + `_merge_golden` (golden record merge)\n - `db.sync_source` upsert uses `lat=COALESCE(:lat, lat)` — connector coords overwrite\n - Frontend uses `sourceName()`/`registerSourceNames()` helpers, `DEDUP_CLAUSE = \" AND dup_hidden=0 AND published=1\"` in web.py\n - Commit convention: French messages, `Co-Authored-By: Claude Opus 4.7 `, push to origin main\n\n3. Files and Code Sections:\n - **`immoka/geocode.py`** (heavily modified, committed): Added `_dist_km` (haversine), `VILLE_RADIUS_KM=40.0`, `CLUSTER_MIN=3`, `RESCUE_MAX=150`. In `Geocoder`: `self._villes`, `self._med` (clusters cache), `self.ville_api_calls`; `_clusters()` (greedy clustering per norm city, median centers); `resolve_ville(city, allow_api)` → `{lat, lng, muni}` via Nominatim addressdetails, cached with key `\"ville:\"+norm_key(city)`; `city_refs(city, allow_api)` → trusted clusters (n≥3) + ville point; `coords_ok(c, city, refs)`; `resolve()` now: AQ raw city → AQ with official muni (`adresses_quebec_muni`) → Nominatim `_attempts(address, city, muni)` (city variants incl. first word + muni); `run_batch()` validates via `coords_ok` and defers failures to a `rescue` list processed by `resolve()` (capped RESCUE_MAX, self-draining); `run_audit(nominatim_budget, apply)` — flags active listings > 40 km from ALL refs, decision table (near cluster→OK; ville resolved+near→OK; no refs→inconnues; budget exhausted→reportees; else flag), on apply: `DELETE FROM geocode_cache`, `SET lat=NULL, lng=NULL, geocode_failed=0`; `strip_bad_source_coords(con, listings)` — cache-only ingestion guard nulling connector lat/lng contradicting city\n - **`immoka/db.py`** (modified, committed): `geocode_cache` schema + migration adds `muni TEXT`; contains dedup logic examined for current feature:\n ```python\n _PETITES_ANNONCES = {\"kijiji\", \"lespac\"}\n def _source_rank(source): # 0=primary, 1=_ag_, 2=petites annonces\n # dedup_by_address: groups.setdefault(key, []).append((r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))\n # _mask_cluster: keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid) — sources at c[3]\n # then _merge_golden(con, keep[2], donors)\n ```\n Pass 1/2 SQL uses `UPDATE listings SET dup_hidden=1 WHERE ...`; `refresh_dedup` starts with `UPDATE listings SET dup_hidden=0`\n - **`immoka/ingest.py`** (modified, committed): per-source guard calling `geocode.strip_bad_source_coords(con, finalized)` before `db.sync_source`; `watch()` now calls `geocode.run_audit(nominatim_budget=50)` before `geocode.run_batch()`\n - **`run.py`** (modified, committed): added `geocode-audit [n] [dry]` command with `budget = next((int(a) for a in sys.argv[2:] if a.isdigit()), None)`\n - **`immoka/web.py`** (read, lines ~196-225): `get_listing(uid)` — `SELECT * FROM listings WHERE uid=?`, `_row_to_dict`, adds `price_history`, `poi`, `quartier`. This is where duplicates list must be added. `DEDUP_CLAUSE = \" AND dup_hidden=0 AND published=1\"` at line 69\n - **`frontend/src/pages/Listing.tsx`** (read fully, 506 lines): fiche page; broker box lines 380-386 (`className=\"broker\"`), CTA `Voir l'annonce chez {sourceName(l.source)}` lines 388-390, PDF CTA, `.fine` footer line 394-396; right column has Inclusions + Emplacement (PropertyMap); full-width sections after: Financement, RisqueInondation, QualiteAir, CommercesProches, EssenceProche, HydroEstimation, QuartierBlock; DOM order = visual order (project standard)\n - **`frontend/src/api.ts`** (read lines 1-90): `Listing` interface — needs new optional field for duplicates; `fetchListing` at line 178; helpers `sourceName`, `registerSourceNames`, `fmtPrice`\n - **`data/hydro.db`** table `hydro_cache` (cle, uid, cout_annuel, kwh, fetched_at); `/api/hydro?adresse=…&uid=…` endpoint in web.py line 149\n - **Memory files**: created `~/.claude/projects/-Users-simon-pierreboucher-apps-immo-ka/memory/project_geocode_engine.md`, updated `MEMORY.md` index\n\n4. Errors and fixes:\n - **Single-median centroid caused 6255 false positives**: first audit dry-run flagged L'Ange-Gardien, Saint-Donat, Sainte-Félicité listings etc. — discovered Québec homonym municipalities means one name = multiple legitimate locations. Fixed by replacing per-city median with greedy CLUSTERS (each homonym gets its own trusted cluster at n≥3) + Nominatim ville point; second dry-run flagged only 3 genuinely wrong listings\n - **AQ returns 0 candidates for borough/sector city names** (\"Jonquiere Lac Kenogami\", even \"Jonquière\"): fixed with official-municipality retry derived from Nominatim addressdetails (`address.city` = \"Saguenay\")\n - **CLI arg parse bug**: `geocode-audit dry` would crash on `int(sys.argv[2])`; fixed with `next((int(a) for a in sys.argv[2:] if a.isdigit()), None)`\n - **Type annotation mismatch** after cluster refactor: `self._med: dict[str, tuple]` → fixed to `dict[str, list[tuple]]` via inline python script edit\n - **Edit tool error on MEMORY.md**: \"File has not been read yet\" → read file first, then edited\n\n5. Problem Solving:\n - **Geocode bug root-caused**: bad coords near \"rue de la Perdrix Grise\" (Saint-Augustin) came from old permissive source/geocode pass; DuProprio page no longer has geo in JSON-LD; geocoder had failed (cache failed=1) leaving stale coords; only province-wide bbox validation existed\n - **Fixed & verified**: 4671 Rue Des Perdrix now (48.3119, -71.30204); API + public site verified 200; committed `2a0d7b3`, pushed; PM2 restarted\n - **Initial audit**: 110,574 verified, 3 incoherent fixed, 1,063 unknown cities, 1,596 deferred (budget); background full audit launched (`/tmp/immoka-geocode-audit-full.log`, `run.py geocode-audit 2500 && run.py geocode`) — was still running\n - **Laberge dedup investigation revealed the dedup flaw driving the current feature request**: fb_marketplace (rank 0, no broker) beats via_capitale (rank 0, broker Simon Laberge) by alphabetical uid tie-break\n\n6. All user messages:\n 1. \"peux tu corriger les bug dans le engine de geocode , pcq regarde ici regarde cette annonce https://www.immo-ka.com/propriete/duproprio%3A1126225/4671-rue-des-perdrix-jonquiere-lac-kenogami est localise a saint augustin alors querl est au saguenay nom de rue proche maios pas pentoute la meme chose opeux tu faire geocode plus rigoureux\"\n 2. \"Donne moi un URL d'une annonce immo ka qui a déjà le coût hydro affiche\"\n 3. \"Combien annonce sont en cache\"\n 4. \"Peux tu me dire si j'ai des annonce du. Courtier Laberge à Québec.\"\n 5. \"J'aimerais que lorsque duplication on affiche annonce du courtier avec mention et lien pour les duplication aussi dans une nouvelle box qu'on va devoir ajoute pense tu que tu peux faire Cela\"\n\n7. Pending Tasks:\n - **ACTIVE (user request #5)**: Implement broker-preferred dedup + duplicates box:\n 1. `db.py`: prefer broker version at equal source rank (add no-broker flag to cluster tuple in `dedup_by_address`, update `_mask_cluster` indexes accordingly: keep = min by (rank, nobroker, uid), sources index shifts to c[4]); consider adding `\"fb_marketplace\"` to `_PETITES_ANNONCES`; add `dup_of TEXT` column (migration in `_init_schema`) persisted by all 3 dedup passes (reset with `dup_hidden=0, dup_of=NULL` in refresh_dedup; pass 1: correlated subquery MIN canonical uid; pass 2: the kept MIN(d.uid); pass 3: keep_uid in `_mask_cluster`); dedup query in `dedup_by_address` should also SELECT broker_name/agency\n 2. `web.py` `get_listing`: add `d[\"duplicates\"]` = rows `SELECT uid, source, url, broker_name, agency, price_label FROM listings WHERE dup_of=? AND active=1`\n 3. `frontend/src/api.ts`: add `duplicates?: {...}[]` to `Listing` interface\n 4. `frontend/src/pages/Listing.tsx`: new box (e.g. \"Aussi publiée sur…\") with source mention (`sourceName()`), broker name if present, external links; respect DOM-order standard\n 5. Run `refresh_dedup` so the Charles-Trudel listing switches to the Via Capitale (Simon Laberge) version; rebuild frontend (Vite build), restart PM2 (immo-ka-web/immo-ka-sync), verify on the Charles-Trudel case, commit + push\n - **Background monitor (todo #9, in_progress)**: verify `/tmp/immoka-geocode-audit-full.log` completion (full geocode audit budget 2500 + re-geocode batch)\n\n8. Current Work:\n Working on user request #5 (broker-preferred dedup + duplicates box). Exploration phase just completed — no edits made yet for this feature. Just finished reading:\n - `db.py` dedup internals (refresh_dedup 3 passes, `_source_rank`, `dedup_by_address` grouping tuple `(price, rank, uid, source)`, `_mask_cluster` keep logic `min(key=(c[1], c[2]))`)\n - `frontend/src/pages/Listing.tsx` in full (broker box at lines 380-386, CTA/source link at 388-396, two-column `f-col` layout)\n - `web.py` `get_listing` endpoint (lines ~196-225)\n - `frontend/src/api.ts` `Listing` interface (lines 22-59) and `fetchListing` (line 178)\n Root cause confirmed and stated to user: \"dans `dedup_by_address`, à autorité égale (rang 0), c'est le plus petit uid qui gagne — `fb_marketplace:…` bat `via_capitale:…` alphabétiquement\". Plan announced to user: \"1. Priorité courtier… 2. Colonne `dup_of`… 3. API : la fiche visible expose ses doublons… 4. Nouvelle box sur la page fiche\". Test case: 3 Ch. Charles-Trudel, Québec — currently visible as `fb_marketplace:1034708775856596`, should become `via_capitale:23663023` (Simon Laberge, VIA CAPITALE ÉQUIPE) with duplicates box listing realtor_ag_ca:23663023 and fb_marketplace versions.\n\n9. Optional Next Step:\n Begin implementing the dedup changes in `immoka/db.py`, per the plan I announced to the user right after their request (\"Le plan : 1. **Priorité courtier** : à rang égal, une fiche avec courtier/agence bat une fiche anonyme + `fb_marketplace` rejoint les plateformes de republication. 2. **Colonne `dup_of`** : persister qui est masqué au profit de qui (les 3 passes de dédup). 3. **API** : la fiche visible expose ses doublons (source, courtier, lien). 4. **Nouvelle box** sur la page fiche : « Aussi publiée sur… » avec mention et liens.\"). Concretely: create a TodoWrite list for this feature, then edit `db.py` (`dup_of` column migration, broker-preference in `dedup_by_address`/`_mask_cluster`, dup_of persistence in all 3 `refresh_dedup` passes), then `web.py` duplicates in `get_listing`, then `api.ts` + `Listing.tsx` new box, rebuild frontend, run `refresh_dedup`, verify on the Charles-Trudel listing, PM2 restart, commit + push. Also check `/tmp/immoka-geocode-audit-full.log` (todo #9) while working.\n\nIf you need specific details from before compaction (like exact code snippets, error messages, or content you generated), read the full transcript at: /Users/simon-pierreboucher/.claude/projects/-Users-simon-pierreboucher-apps-immo-ka/4c9543da-fa95-4658-8db4-70aa0feada91.jsonl\nContinue the conversation from where it left off without asking the user any further questions. Resume directly — do not acknowledge the summary, do not recap what was happening, do not preface with \"I'll continue\" or similar. Pick up the last task as if the break never happened."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"46b22927-9bfc-43f1-9d18-f84af80578ec","timestamp":"2026-08-25T14:11:27.704Z","isSynthetic":true}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbtAZb5ZfsZivVD5rWN","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":23665,"cache_read_input_tokens":21776,"cache_creation":{"ephemeral_5m_input_tokens":23665,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"d806de77-9819-4ed4-b648-94eea31e0df0"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbtAZb5ZfsZivVD5rWN","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01QhbGDDdA8sj2Dcf6wyGvac","name":"ToolSearch","input":{"query":"select:TodoWrite","max_results":1},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":23665,"cache_read_input_tokens":21776,"cache_creation":{"ephemeral_5m_input_tokens":23665,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"751d9db1-6fb9-4748-8682-4adb8a32b9cf"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"type":"tool_result","tool_use_id":"toolu_01QhbGDDdA8sj2Dcf6wyGvac","content":[{"type":"tool_reference","tool_name":"TodoWrite"}]}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"481b47f0-2ca4-48f7-b53c-91fb209fd4f8","timestamp":"2026-08-25T14:11:34.027Z","tool_use_result":{"matches":["TodoWrite"],"query":"select:TodoWrite","total_deferred_tools":17}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbtAZb5ZfsZivVD5rWN","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01GmDtzw4tNyQKC83LvVP2B4","name":"Bash","input":{"command":"tail -5 /tmp/immoka-geocode-audit-full.log 2>/dev/null; echo \"---\"; grep -n \"dedup_by_address\\|_mask_cluster\\|_source_rank\\|refresh_dedup\\|dup_hidden\\|_merge_golden\\|_PETITES_ANNONCES\" /Users/simon-pierreboucher/apps/immo-ka/immoka/db.py | head -40","description":"Check audit log and locate dedup code in db.py"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":23665,"cache_read_input_tokens":21776,"cache_creation":{"ephemeral_5m_input_tokens":23665,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"73e891c1-8412-4bff-bbeb-40855339c93b"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01GmDtzw4tNyQKC83LvVP2B4","type":"tool_result","content":"[immo-ka] audit: engel_volkers:16494714 « 731 Rue Paul-Émile-Borduas, Granby, Estrie » à 103 km de sa ville\n[immo-ka] audit: engel_volkers:14926995 « 65 Rue du Hameau, Saint-Hippolyte, Laurentides » à 81 km de sa ville\n[immo-ka] audit: engel_volkers:26009868 « 26 Rue King, Saint-Pacôme, Bas-Saint-Laurent » à 547 km de sa ville\n[immo-ka] audit: engel_volkers:23002151 « 298 Rue Principale, Saint-Donat, Lanaudière » à 83 km de sa ville\n[immo-ka] geocode-audit {'verifiees': 110573, 'incoherentes': 1832, 'villes_inconnues': 157, 'reportees': 0, 'corrigees': True}\n---\n68: dup_hidden INTEGER DEFAULT 0 -- 1 = doublon de sous-agence masqué (dédup Centris)\n136: if \"dup_hidden\" not in cols:\n137: con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n145: con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n150:def refresh_dedup(con: sqlite3.Connection) -> int:\n152: colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n159: cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n164: con.execute(\"UPDATE listings SET dup_hidden=0\")\n168: f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG}\"\n174: f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG} AND dup_hidden=0\"\n176: f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")\n182: n_addr = dedup_by_address(con)\n188: n = con.execute(\"SELECT COUNT(*) c FROM listings WHERE dup_hidden=1\").fetchone()[\"c\"]\n195:_PETITES_ANNONCES = {\"kijiji\", \"lespac\"}\n198:def _source_rank(source: str) -> int:\n202: if source in _PETITES_ANNONCES:\n209:def dedup_by_address(con: sqlite3.Connection) -> int:\n226: \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n241: (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))\n250: hidden += _mask_cluster(con, cluster)\n253: hidden += _mask_cluster(con, cluster)\n257:def _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:\n272: con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n276: _merge_golden(con, keep[2], donors)\n286:def _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:\n338: # 120 s : couvre les longues transactions (refresh_dedup ~70 s) sans que les","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"22746aff-46ba-47ee-900e-73d90b82619f","timestamp":"2026-08-25T14:11:36.307Z","tool_use_result":{"stdout":"[immo-ka] audit: engel_volkers:16494714 « 731 Rue Paul-Émile-Borduas, Granby, Estrie » à 103 km de sa ville\n[immo-ka] audit: engel_volkers:14926995 « 65 Rue du Hameau, Saint-Hippolyte, Laurentides » à 81 km de sa ville\n[immo-ka] audit: engel_volkers:26009868 « 26 Rue King, Saint-Pacôme, Bas-Saint-Laurent » à 547 km de sa ville\n[immo-ka] audit: engel_volkers:23002151 « 298 Rue Principale, Saint-Donat, Lanaudière » à 83 km de sa ville\n[immo-ka] geocode-audit {'verifiees': 110573, 'incoherentes': 1832, 'villes_inconnues': 157, 'reportees': 0, 'corrigees': True}\n---\n68: dup_hidden INTEGER DEFAULT 0 -- 1 = doublon de sous-agence masqué (dédup Centris)\n136: if \"dup_hidden\" not in cols:\n137: con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n145: con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n150:def refresh_dedup(con: sqlite3.Connection) -> int:\n152: colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n159: cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n164: con.execute(\"UPDATE listings SET dup_hidden=0\")\n168: f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG}\"\n174: f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG} AND dup_hidden=0\"\n176: f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")\n182: n_addr = dedup_by_address(con)\n188: n = con.execute(\"SELECT COUNT(*) c FROM listings WHERE dup_hidden=1\").fetchone()[\"c\"]\n195:_PETITES_ANNONCES = {\"kijiji\", \"lespac\"}\n198:def _source_rank(source: str) -> int:\n202: if source in _PETITES_ANNONCES:\n209:def dedup_by_address(con: sqlite3.Connection) -> int:\n226: \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n241: (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))\n250: hidden += _mask_cluster(con, cluster)\n253: hidden += _mask_cluster(con, cluster)\n257:def _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:\n272: con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n276: _merge_golden(con, keep[2], donors)\n286:def _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:\n338: # 120 s : couvre les longues transactions (refresh_dedup ~70 s) sans que les","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"7acd7b8b-9c04-43d3-984d-46457bd03107","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbtoEiNSgc13C3L1fHx","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":5032,"cache_read_input_tokens":45441,"cache_creation":{"ephemeral_5m_input_tokens":5032,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"5ba640ff-8f4c-416d-9d9a-3c8a8f3e6cc8"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbtoEiNSgc13C3L1fHx","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01CdECKFkLQYL5WGH4rUwpde","name":"TodoWrite","input":{"todos":[{"content":"db.py : priorité courtier + colonne dup_of persistée par les 3 passes de dédup","status":"in_progress","activeForm":"Modifiant la dédup (priorité courtier + dup_of)"},{"content":"web.py : exposer les doublons dans get_listing","status":"pending","activeForm":"Exposant les doublons dans l'API"},{"content":"Frontend : type + box « Aussi publiée sur… » dans Listing.tsx","status":"pending","activeForm":"Ajoutant la box doublons au frontend"},{"content":"refresh_dedup + build + PM2 restart + vérif Charles-Trudel","status":"pending","activeForm":"Recalculant la dédup et vérifiant"},{"content":"Commit + push origin main","status":"pending","activeForm":"Committant et poussant"}]},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":5032,"cache_read_input_tokens":45441,"cache_creation":{"ephemeral_5m_input_tokens":5032,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"28930b19-1802-47e2-94fb-b6ff2a0a0483"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01CdECKFkLQYL5WGH4rUwpde","type":"tool_result","content":"Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"6b61db9d-eb51-464f-a39f-c0b86f6c47c7","timestamp":"2026-08-25T14:11:45.038Z","tool_use_result":{"oldTodos":[{"content":"geocode.py : centroïde de ville (médiane BD + Nominatim caché) et validation ≤40 km","status":"completed","activeForm":"Ajout de la validation par centroïde de ville"},{"content":"resolve() : retry AQ avec municipalité officielle + variantes Nominatim","status":"completed","activeForm":"Ajout des variantes de municipalité"},{"content":"run_batch : validation centroïde + rattrapage resolve() des échecs","status":"completed","activeForm":"Renforcement du géocodage batch"},{"content":"run_audit : détecter/corriger les fiches aux coordonnées incohérentes","status":"completed","activeForm":"Création de l'audit géocodage"},{"content":"Garde ingestion : rejeter les coords de connecteur contredisant la ville","status":"completed","activeForm":"Ajout de la garde à l'ingestion"},{"content":"db.py : colonne muni dans geocode_cache + CLI geocode-audit + watch","status":"completed","activeForm":"Migration BD et CLI"},{"content":"Corriger duproprio:1126225 + lancer l'audit + vérifier le site","status":"completed","activeForm":"Correction des fiches et vérification"},{"content":"pm2 restart + commit + push origin main","status":"completed","activeForm":"Redéploiement et commit"},{"content":"Audit complet en arrière-plan (1596 villes restantes) — vérifier le log","status":"in_progress","activeForm":"Audit complet en arrière-plan"}],"newTodos":[{"content":"db.py : priorité courtier + colonne dup_of persistée par les 3 passes de dédup","status":"in_progress","activeForm":"Modifiant la dédup (priorité courtier + dup_of)"},{"content":"web.py : exposer les doublons dans get_listing","status":"pending","activeForm":"Exposant les doublons dans l'API"},{"content":"Frontend : type + box « Aussi publiée sur… » dans Listing.tsx","status":"pending","activeForm":"Ajoutant la box doublons au frontend"},{"content":"refresh_dedup + build + PM2 restart + vérif Charles-Trudel","status":"pending","activeForm":"Recalculant la dédup et vérifiant"},{"content":"Commit + push origin main","status":"pending","activeForm":"Committant et poussant"}],"verificationNudgeNeeded":false}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbtoEiNSgc13C3L1fHx","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01GXtMk2RFimc9THxea5jNEr","name":"Read","input":{"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","offset":120,"limit":220},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":5032,"cache_read_input_tokens":45441,"cache_creation":{"ephemeral_5m_input_tokens":5032,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"f4d7a7a0-908b-481a-983e-d1600cbc59ac"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01GXtMk2RFimc9THxea5jNEr","type":"tool_result","content":"120\t ts REAL\n121\t);\n122\t\"\"\"\n123\t\n124\t\n125\t_SCHEMA_READY = False # le schéma/migration ne s'exécute qu'UNE fois par process\n126\t\n127\t\n128\tdef _init_schema(con: sqlite3.Connection) -> None:\n129\t \"\"\"Création de schéma + migration — coûteuse (write-lock). À faire une seule\n130\t fois par process : l'exécuter à chaque connexion sérialisait les requêtes du\n131\t web sur un verrou d'écriture (deadlock/starvation sous charge).\"\"\"\n132\t con.executescript(_SCHEMA)\n133\t cols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(listings)\")}\n134\t if \"agency\" not in cols:\n135\t con.execute(\"ALTER TABLE listings ADD COLUMN agency TEXT\")\n136\t if \"dup_hidden\" not in cols:\n137\t con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n138\t if \"dauid\" not in cols: # aire de diffusion 2021 (stats de quartier)\n139\t con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")\n140\t if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n141\t con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n142\t gcols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(geocode_cache)\")}\n143\t if \"muni\" not in gcols: # municipalité officielle (entrées « ville:… »)\n144\t con.execute(\"ALTER TABLE geocode_cache ADD COLUMN muni TEXT\")\n145\t con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n146\t con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n147\t con.commit()\n148\t\n149\t\n150\tdef refresh_dedup(con: sqlite3.Connection) -> int:\n151\t \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n152\t colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n153\t au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n154\t\n155\t Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée\n156\t si une fiche de plus haute priorité — même n° Centris (external_id), active —\n157\t existe : le flux central/agence principale d'abord, sinon la sous-agence au\n158\t plus petit uid. Les fiches non sous-agence ne sont jamais masquées par\n159\t cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n160\t INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).\n161\t Retourne le nombre total de fiches masquées.\"\"\"\n162\t AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n163\t NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n164\t con.execute(\"UPDATE listings SET dup_hidden=0\")\n165\t # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n166\t # canonique (non sous-agence) active — semi-jointure, rapide.\n167\t con.execute(\n168\t f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG}\"\n169\t f\" AND external_id IN (SELECT external_id FROM listings\"\n170\t f\" WHERE active=1 AND {NOTAG})\")\n171\t # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n172\t # petit uid par n° Centris.\n173\t con.execute(\n174\t f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG} AND dup_hidden=0\"\n175\t f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n176\t f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")\n177\t # 3) dédup INTER-SOURCES par adresse : la même propriété publiée sur deux\n178\t # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle\n179\t # conservatrice : même adresse normalisée (civique + rue + ville) + même\n180\t # type + prix identique à ±1 % → on garde la fiche la plus autoritaire.\n181\t try:\n182\t n_addr = dedup_by_address(con)\n183\t if n_addr:\n184\t print(f\"[immo-ka] dédup adresse: {n_addr} doublon(s) inter-sources masqué(s)\")\n185\t except Exception:\n186\t import traceback\n187\t traceback.print_exc()\n188\t n = con.execute(\"SELECT COUNT(*) c FROM listings WHERE dup_hidden=1\").fetchone()[\"c\"]\n189\t con.commit()\n190\t return n\n191\t\n192\t\n193\t# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n194\t# autoritaires que la source primaire (courtier / FSBO première main)\n195\t_PETITES_ANNONCES = {\"kijiji\", \"lespac\"}\n196\t\n197\t\n198\tdef _source_rank(source: str) -> int:\n199\t \"\"\"Autorité d'une source pour la dédup d'adresse :\n200\t 0 = source primaire (bannière/agence/FSBO), 1 = sous-agence (_ag_),\n201\t 2 = petites annonces (republication probable).\"\"\"\n202\t if source in _PETITES_ANNONCES:\n203\t return 2\n204\t if \"_ag_\" in source:\n205\t return 1\n206\t return 0\n207\t\n208\t\n209\tdef dedup_by_address(con: sqlite3.Connection) -> int:\n210\t \"\"\"Passe de déduplication conservatrice par ADRESSE (inter-sources).\n211\t\n212\t Clé : n° civique(s) + mots significatifs de la rue + ville normalisée +\n213\t type canonique + n° d'app/unité (vide s'il n'y en a pas — deux unités\n214\t différentes d'un même immeuble ne partagent JAMAIS la même clé, et une\n215\t adresse sans unité ne s'apparie pas à une adresse avec unité). Dans une\n216\t clé, seules les fiches au prix identique à ±1 % sont considérées comme\n217\t doublons ; si une même source apparaît deux fois dans le groupe (probables\n218\t unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n219\t la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n220\t petites annonces), puis le plus petit uid. Retourne le nb masqué.\"\"\"\n221\t import re as _re\n222\t from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE\n223\t groups: dict[tuple, list] = {}\n224\t for r in con.execute(\n225\t \"SELECT uid, source, address, city, price, property_type\"\n226\t \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n227\t \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):\n228\t civs, words = _addr_parts(r[\"address\"])\n229\t if not civs or not words:\n230\t continue\n231\t a = _norm(r[\"address\"]).split(\",\")[0]\n232\t mapt = _re.search(_APP_RE, a)\n233\t apt = \"\"\n234\t if mapt:\n235\t toks = _re.findall(r\"[a-z0-9]+\", mapt.group(0))\n236\t # dernier token = le n° d'unité (le 1er est le mot-clé app/unité/#)\n237\t apt = toks[-1] if toks else \"\"\n238\t key = (\"-\".join(civs), \" \".join(sorted(set(words))),\n239\t _muni_norm(r[\"city\"]), _norm(r[\"property_type\"]), apt)\n240\t groups.setdefault(key, []).append(\n241\t (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))\n242\t hidden = 0\n243\t for rows in groups.values():\n244\t if len(rows) < 2:\n245\t continue\n246\t rows.sort() # par prix croissant\n247\t cluster: list = []\n248\t for row in rows:\n249\t if cluster and row[0] > cluster[0][0] * 1.01:\n250\t hidden += _mask_cluster(con, cluster)\n251\t cluster = []\n252\t cluster.append(row)\n253\t hidden += _mask_cluster(con, cluster)\n254\t return hidden\n255\t\n256\t\n257\tdef _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:\n258\t \"\"\"Masque les doublons d'un groupe (même clé d'adresse, prix ±1 %), puis\n259\t FUSIONNE en « golden record » : les champs vides de la fiche conservée sont\n260\t complétés depuis les doublons masqués (description plus longue, galerie plus\n261\t riche, superficies, année, GPS, téléphone) — le meilleur des deux sources.\"\"\"\n262\t if len(cluster) < 2:\n263\t return 0\n264\t sources = [c[3] for c in cluster]\n265\t if len(set(sources)) != len(sources):\n266\t return 0 # même source en double = probables unités distinctes : prudence\n267\t keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)\n268\t n = 0\n269\t donors = []\n270\t for c in cluster:\n271\t if c[2] != keep[2]:\n272\t con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n273\t donors.append(c[2])\n274\t n += 1\n275\t try:\n276\t _merge_golden(con, keep[2], donors)\n277\t except Exception:\n278\t pass # la fusion est un bonus — ne jamais casser la dédup\n279\t return n\n280\t\n281\t\n282\t_MERGE_NUM_FIELDS = (\"bedrooms\", \"bathrooms\", \"powder_rooms\", \"area_sqft\",\n283\t \"lot_sqft\", \"year_built\")\n284\t\n285\t\n286\tdef _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:\n287\t \"\"\"Complète les champs vides de `keep_uid` depuis ses doublons masqués.\"\"\"\n288\t if not donor_uids:\n289\t return\n290\t cols = (\"uid, description, images, bedrooms, bathrooms, powder_rooms,\"\n291\t \" area_sqft, lot_sqft, year_built, lat, lng, broker_phone\")\n292\t keep = con.execute(f\"SELECT {cols} FROM listings WHERE uid=?\",\n293\t (keep_uid,)).fetchone()\n294\t if keep is None:\n295\t return\n296\t sets, args = [], []\n297\t kimgs = len(json.loads(keep[\"images\"] or \"[]\"))\n298\t kdesc = len(keep[\"description\"] or \"\")\n299\t best_imgs, best_desc = None, None\n300\t donor_rows = con.execute(\n301\t f\"SELECT {cols} FROM listings WHERE uid IN \"\n302\t f\"({','.join('?' * len(donor_uids))})\", donor_uids).fetchall()\n303\t merged_num: dict = {}\n304\t for d in donor_rows:\n305\t di = json.loads(d[\"images\"] or \"[]\")\n306\t if len(di) > max(kimgs, len(json.loads(best_imgs or \"[]\"))):\n307\t best_imgs = d[\"images\"]\n308\t dd = d[\"description\"] or \"\"\n309\t if len(dd) > max(kdesc, 80, len(best_desc or \"\")):\n310\t best_desc = dd\n311\t for f in _MERGE_NUM_FIELDS:\n312\t if keep[f] is None and merged_num.get(f) is None and d[f] is not None:\n313\t merged_num[f] = d[f]\n314\t # GPS : toujours la PAIRE du même donneur (jamais lat et lng mélangés)\n315\t if (keep[\"lat\"] is None and \"lat\" not in merged_num\n316\t and d[\"lat\"] is not None and d[\"lng\"] is not None):\n317\t merged_num[\"lat\"], merged_num[\"lng\"] = d[\"lat\"], d[\"lng\"]\n318\t if not keep[\"broker_phone\"] and d[\"broker_phone\"] and \"broker_phone\" not in merged_num:\n319\t merged_num[\"broker_phone\"] = d[\"broker_phone\"]\n320\t if best_imgs is not None:\n321\t sets.append(\"images=?\"); args.append(best_imgs)\n322\t if best_desc is not None and kdesc < 80:\n323\t sets.append(\"description=?\"); args.append(best_desc)\n324\t for f, v in merged_num.items():\n325\t sets.append(f\"{f}=?\"); args.append(v)\n326\t if sets:\n327\t args.append(keep_uid)\n328\t con.execute(f\"UPDATE listings SET {', '.join(sets)} WHERE uid=?\", args)\n329\t\n330\t\n331\tdef connect() -> sqlite3.Connection:\n332\t global _SCHEMA_READY\n333\t DB_PATH.parent.mkdir(parents=True, exist_ok=True)\n334\t con = sqlite3.connect(DB_PATH, timeout=60)\n335\t con.row_factory = sqlite3.Row\n336\t # WAL + busy_timeout : accès concurrents (watcher + web) sans « db is locked ».\n337\t con.execute(\"PRAGMA journal_mode=WAL\")\n338\t # 120 s : couvre les longues transactions (refresh_dedup ~70 s) sans que les\n339\t # autres écrivains (géocodage, vraiprix) ne lèvent « database is locked »."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"c985eeba-9989-46e6-b91b-650e60b9dc3a","timestamp":"2026-08-25T14:11:46.250Z","tool_use_result":{"type":"text","file":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","content":" ts REAL\n);\n\"\"\"\n\n\n_SCHEMA_READY = False # le schéma/migration ne s'exécute qu'UNE fois par process\n\n\ndef _init_schema(con: sqlite3.Connection) -> None:\n \"\"\"Création de schéma + migration — coûteuse (write-lock). À faire une seule\n fois par process : l'exécuter à chaque connexion sérialisait les requêtes du\n web sur un verrou d'écriture (deadlock/starvation sous charge).\"\"\"\n con.executescript(_SCHEMA)\n cols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(listings)\")}\n if \"agency\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN agency TEXT\")\n if \"dup_hidden\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n if \"dauid\" not in cols: # aire de diffusion 2021 (stats de quartier)\n con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")\n if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n gcols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(geocode_cache)\")}\n if \"muni\" not in gcols: # municipalité officielle (entrées « ville:… »)\n con.execute(\"ALTER TABLE geocode_cache ADD COLUMN muni TEXT\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n con.commit()\n\n\ndef refresh_dedup(con: sqlite3.Connection) -> int:\n \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n\n Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée\n si une fiche de plus haute priorité — même n° Centris (external_id), active —\n existe : le flux central/agence principale d'abord, sinon la sous-agence au\n plus petit uid. Les fiches non sous-agence ne sont jamais masquées par\n cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).\n Retourne le nombre total de fiches masquées.\"\"\"\n AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n con.execute(\"UPDATE listings SET dup_hidden=0\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")\n # 3) dédup INTER-SOURCES par adresse : la même propriété publiée sur deux\n # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle\n # conservatrice : même adresse normalisée (civique + rue + ville) + même\n # type + prix identique à ±1 % → on garde la fiche la plus autoritaire.\n try:\n n_addr = dedup_by_address(con)\n if n_addr:\n print(f\"[immo-ka] dédup adresse: {n_addr} doublon(s) inter-sources masqué(s)\")\n except Exception:\n import traceback\n traceback.print_exc()\n n = con.execute(\"SELECT COUNT(*) c FROM listings WHERE dup_hidden=1\").fetchone()[\"c\"]\n con.commit()\n return n\n\n\n# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main)\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\"}\n\n\ndef _source_rank(source: str) -> int:\n \"\"\"Autorité d'une source pour la dédup d'adresse :\n 0 = source primaire (bannière/agence/FSBO), 1 = sous-agence (_ag_),\n 2 = petites annonces (republication probable).\"\"\"\n if source in _PETITES_ANNONCES:\n return 2\n if \"_ag_\" in source:\n return 1\n return 0\n\n\ndef dedup_by_address(con: sqlite3.Connection) -> int:\n \"\"\"Passe de déduplication conservatrice par ADRESSE (inter-sources).\n\n Clé : n° civique(s) + mots significatifs de la rue + ville normalisée +\n type canonique + n° d'app/unité (vide s'il n'y en a pas — deux unités\n différentes d'un même immeuble ne partagent JAMAIS la même clé, et une\n adresse sans unité ne s'apparie pas à une adresse avec unité). Dans une\n clé, seules les fiches au prix identique à ±1 % sont considérées comme\n doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis le plus petit uid. Retourne le nb masqué.\"\"\"\n import re as _re\n from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE\n groups: dict[tuple, list] = {}\n for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):\n civs, words = _addr_parts(r[\"address\"])\n if not civs or not words:\n continue\n a = _norm(r[\"address\"]).split(\",\")[0]\n mapt = _re.search(_APP_RE, a)\n apt = \"\"\n if mapt:\n toks = _re.findall(r\"[a-z0-9]+\", mapt.group(0))\n # dernier token = le n° d'unité (le 1er est le mot-clé app/unité/#)\n apt = toks[-1] if toks else \"\"\n key = (\"-\".join(civs), \" \".join(sorted(set(words))),\n _muni_norm(r[\"city\"]), _norm(r[\"property_type\"]), apt)\n groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))\n hidden = 0\n for rows in groups.values():\n if len(rows) < 2:\n continue\n rows.sort() # par prix croissant\n cluster: list = []\n for row in rows:\n if cluster and row[0] > cluster[0][0] * 1.01:\n hidden += _mask_cluster(con, cluster)\n cluster = []\n cluster.append(row)\n hidden += _mask_cluster(con, cluster)\n return hidden\n\n\ndef _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:\n \"\"\"Masque les doublons d'un groupe (même clé d'adresse, prix ±1 %), puis\n FUSIONNE en « golden record » : les champs vides de la fiche conservée sont\n complétés depuis les doublons masqués (description plus longue, galerie plus\n riche, superficies, année, GPS, téléphone) — le meilleur des deux sources.\"\"\"\n if len(cluster) < 2:\n return 0\n sources = [c[3] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[2] != keep[2]:\n con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n donors.append(c[2])\n n += 1\n try:\n _merge_golden(con, keep[2], donors)\n except Exception:\n pass # la fusion est un bonus — ne jamais casser la dédup\n return n\n\n\n_MERGE_NUM_FIELDS = (\"bedrooms\", \"bathrooms\", \"powder_rooms\", \"area_sqft\",\n \"lot_sqft\", \"year_built\")\n\n\ndef _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:\n \"\"\"Complète les champs vides de `keep_uid` depuis ses doublons masqués.\"\"\"\n if not donor_uids:\n return\n cols = (\"uid, description, images, bedrooms, bathrooms, powder_rooms,\"\n \" area_sqft, lot_sqft, year_built, lat, lng, broker_phone\")\n keep = con.execute(f\"SELECT {cols} FROM listings WHERE uid=?\",\n (keep_uid,)).fetchone()\n if keep is None:\n return\n sets, args = [], []\n kimgs = len(json.loads(keep[\"images\"] or \"[]\"))\n kdesc = len(keep[\"description\"] or \"\")\n best_imgs, best_desc = None, None\n donor_rows = con.execute(\n f\"SELECT {cols} FROM listings WHERE uid IN \"\n f\"({','.join('?' * len(donor_uids))})\", donor_uids).fetchall()\n merged_num: dict = {}\n for d in donor_rows:\n di = json.loads(d[\"images\"] or \"[]\")\n if len(di) > max(kimgs, len(json.loads(best_imgs or \"[]\"))):\n best_imgs = d[\"images\"]\n dd = d[\"description\"] or \"\"\n if len(dd) > max(kdesc, 80, len(best_desc or \"\")):\n best_desc = dd\n for f in _MERGE_NUM_FIELDS:\n if keep[f] is None and merged_num.get(f) is None and d[f] is not None:\n merged_num[f] = d[f]\n # GPS : toujours la PAIRE du même donneur (jamais lat et lng mélangés)\n if (keep[\"lat\"] is None and \"lat\" not in merged_num\n and d[\"lat\"] is not None and d[\"lng\"] is not None):\n merged_num[\"lat\"], merged_num[\"lng\"] = d[\"lat\"], d[\"lng\"]\n if not keep[\"broker_phone\"] and d[\"broker_phone\"] and \"broker_phone\" not in merged_num:\n merged_num[\"broker_phone\"] = d[\"broker_phone\"]\n if best_imgs is not None:\n sets.append(\"images=?\"); args.append(best_imgs)\n if best_desc is not None and kdesc < 80:\n sets.append(\"description=?\"); args.append(best_desc)\n for f, v in merged_num.items():\n sets.append(f\"{f}=?\"); args.append(v)\n if sets:\n args.append(keep_uid)\n con.execute(f\"UPDATE listings SET {', '.join(sets)} WHERE uid=?\", args)\n\n\ndef connect() -> sqlite3.Connection:\n global _SCHEMA_READY\n DB_PATH.parent.mkdir(parents=True, exist_ok=True)\n con = sqlite3.connect(DB_PATH, timeout=60)\n con.row_factory = sqlite3.Row\n # WAL + busy_timeout : accès concurrents (watcher + web) sans « db is locked ».\n con.execute(\"PRAGMA journal_mode=WAL\")\n # 120 s : couvre les longues transactions (refresh_dedup ~70 s) sans que les\n # autres écrivains (géocodage, vraiprix) ne lèvent « database is locked ».","numLines":220,"startLine":120,"totalLines":560}}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"8554848c-7ba1-4b3b-932c-efc8364c3b40","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbuXoJjrKHxtUYjwt6G","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":5686,"cache_read_input_tokens":50473,"cache_creation":{"ephemeral_5m_input_tokens":5686,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ebb8580e-de80-41f8-9100-f8273a4f04c9"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbuXoJjrKHxtUYjwt6G","type":"message","role":"assistant","content":[{"type":"text","text":"L'audit géocodage complet est terminé (110 573 fiches vérifiées, 1 832 incohérentes corrigées). J'attaque maintenant la dédup « priorité courtier » + colonne `dup_of` dans db.py."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":5686,"cache_read_input_tokens":50473,"cache_creation":{"ephemeral_5m_input_tokens":5686,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"705d108b-612c-4c34-8891-33d81d158d92"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbuXoJjrKHxtUYjwt6G","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01UW6U5pWb6GiuLuq4PdSiie","name":"Bash","input":{"command":"sqlite3 /Users/simon-pierreboucher/apps/immo-ka/data/immoka.db \"PRAGMA table_info(listings)\" | cut -d'|' -f2 | tr '\\n' ' '","description":"List listings table columns"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":5686,"cache_read_input_tokens":50473,"cache_creation":{"ephemeral_5m_input_tokens":5686,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"463b231e-c217-4141-ae9b-cba559fd198b"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01UW6U5pWb6GiuLuq4PdSiie","type":"tool_result","content":"uid source external_id url title address sector city region property_type price price_label bedrooms bathrooms powder_rooms area_sqft lot_sqft year_built mls status broker_name broker_phone description features details images lat lng geocode_failed content_hash first_seen last_seen updated_at miss_count active agency dup_hidden dauid vraiprix quality_score quality_issues published","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"92089bca-ecbb-41cc-8ef9-4fa22f11c484","timestamp":"2026-08-25T14:12:11.582Z","tool_use_result":{"stdout":"uid source external_id url title address sector city region property_type price price_label bedrooms bathrooms powder_rooms area_sqft lot_sqft year_built mls status broker_name broker_phone description features details images lat lng geocode_failed content_hash first_seen last_seen updated_at miss_count active agency dup_hidden dauid vraiprix quality_score quality_issues published","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"b3ab25b3-1626-4ee5-bf87-c392ca0b02a4","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbwQM934dT3F2cGRHSm","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"CAISwgIKpwEIERgCKkCZbYytPi+Oirc4UEiopdt8K7EI/nvn3oH+iPXFob2FRVKXJ/iqc8nnD4DnCsRP3kucBFwlh2bWSQ3QpLqcZlrnMg5jbGF1ZGUtZmFibGUtNTgBQgh0aGlua2luZ1okNmZjYzhmODMtMWY5Yy00ZDMzLWJhMDctNGQ0ZGYzN2Q2N2Y1chCpF7oiUB8N4as4sc/CyGIoiAEBqAHAxbbUBrABAhIMLKBIdvFb0IPMDADAGgwf2OUmDKKPG4NGgPgiMGGjksowHlMEY1QN5zae8lA6DEHolyaFQ8OKCGYrC6NEI0gyic/l8EySGC3Os1stWypIHT2tN7zU5H57kdu0crj4LvLhbF2GIyOEQB+cLKLM23mY99OEJcAQKQh1y3mhyc4MrBZc+wZvY2aO2DVrsyUg6y7HEHbj0HVKGAE="}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":2005,"cache_read_input_tokens":56159,"cache_creation":{"ephemeral_5m_input_tokens":2005,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"3095f020-7c7c-49d9-b4cb-8b5612dcce59"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbwQM934dT3F2cGRHSm","type":"message","role":"assistant","content":[{"type":"text","text":"Colonnes `broker_name`/`agency` confirmées. J'édite db.py."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":2005,"cache_read_input_tokens":56159,"cache_creation":{"ephemeral_5m_input_tokens":2005,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"1b1620c8-35a7-406e-bdf6-a39b28c0e409"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbwQM934dT3F2cGRHSm","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01XP9TeoSBGAXC8ychZk6e8s","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","old_string":" if \"dup_hidden\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")","new_string":" if \"dup_hidden\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n if \"dup_of\" not in cols: # uid de la fiche visible au profit de laquelle\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_of TEXT\") # celle-ci est masquée"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":2005,"cache_read_input_tokens":56159,"cache_creation":{"ephemeral_5m_input_tokens":2005,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"8b57d088-155d-4109-a844-7b54d356d3b4"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01XP9TeoSBGAXC8ychZk6e8s","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/db.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"6e2aa61e-4e37-436f-8760-55ec13328594","timestamp":"2026-08-25T14:12:18.289Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","oldString":" if \"dup_hidden\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")","newString":" if \"dup_hidden\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n if \"dup_of\" not in cols: # uid de la fiche visible au profit de laquelle\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_of TEXT\") # celle-ci est masquée","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# db.py : persistance SQLite — upsert avec détection de changements,\n# cycle de vie avec délai de grâce (2 syncs), détection de dérive,\n# historique de prix, cache des pages détail.\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport sqlite3\nimport statistics\nimport time\nfrom pathlib import Path\n\nfrom .schema import PropertyListing\n\nDB_PATH = Path(__file__).resolve().parent.parent / \"data\" / \"immoka.db\"\n\n# Nombre d'exécutions consécutives où une propriété doit être absente de la\n# source avant d'être désactivée (délai de grâce contre les ratés ponctuels).\nMISS_GRACE = 2\n\n# Dérive : si une source retourne <= DRIFT_RATIO × sa médiane historique\n# (médiane >= DRIFT_MIN_BASE annonces), on alerte et on suspend les retraits.\nDRIFT_RATIO = 0.25\nDRIFT_MIN_BASE = 8\nDRIFT_HISTORY = 5\n\n_SCHEMA = \"\"\"\nCREATE TABLE IF NOT EXISTS listings (\n uid TEXT PRIMARY KEY,\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n url TEXT,\n title TEXT,\n address TEXT,\n sector TEXT,\n city TEXT,\n region TEXT,\n property_type TEXT,\n price REAL,\n price_label TEXT,\n bedrooms INTEGER,\n bathrooms INTEGER,\n powder_rooms INTEGER,\n area_sqft REAL,\n lot_sqft REAL,\n year_built INTEGER,\n mls TEXT,\n status TEXT DEFAULT 'a-vendre',\n broker_name TEXT,\n broker_phone TEXT,\n agency TEXT,\n description TEXT,\n features TEXT, -- JSON (liste de textes source)\n details TEXT, -- JSON (champs structurés)\n images TEXT, -- JSON\n lat REAL,\n lng REAL,\n geocode_failed INTEGER DEFAULT 0,\n content_hash TEXT,\n first_seen REAL,\n last_seen REAL,\n updated_at REAL,\n miss_count INTEGER DEFAULT 0,\n active INTEGER DEFAULT 1,\n dup_hidden INTEGER DEFAULT 0 -- 1 = doublon de sous-agence masqué (dédup Centris)\n);\nCREATE INDEX IF NOT EXISTS idx_listings_source ON listings(source);\nCREATE INDEX IF NOT EXISTS idx_listings_city ON listings(city);\nCREATE INDEX IF NOT EXISTS idx_listings_type ON listings(property_type);\nCREATE INDEX IF NOT EXISTS idx_listings_active ON listings(active);\nCREATE INDEX IF NOT EXISTS idx_listings_extid ON listings(external_id);\n\nCREATE TABLE IF NOT EXISTS sync_log (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n source TEXT,\n ts REAL,\n found INTEGER,\n added INTEGER,\n updated INTEGER,\n removed INTEGER,\n ok INTEGER,\n message TEXT,\n stats TEXT -- JSON : taux de champs null, missed, alerte…\n);\n\nCREATE TABLE IF NOT EXISTS detail_cache (\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n key TEXT, -- hash du contenu « liste » de l'annonce\n payload TEXT, -- JSON opaque propre au connecteur\n fetched_at REAL,\n PRIMARY KEY (source, external_id)\n);\n\nCREATE TABLE IF NOT EXISTS price_log (\n uid TEXT NOT NULL,\n ts REAL NOT NULL,\n price REAL -- prix observé (baisses/hausses de prix demandé)\n);\nCREATE INDEX IF NOT EXISTS idx_price_log_uid ON price_log(uid);\n\nCREATE TABLE IF NOT EXISTS geocode_cache (\n address TEXT PRIMARY KEY,\n lat REAL,\n lng REAL,\n provider TEXT,\n failed INTEGER DEFAULT 0,\n ts REAL,\n muni TEXT -- municipalité officielle (clés « ville:… »)\n);\n\nCREATE TABLE IF NOT EXISTS poi_cache (\n coord_key TEXT PRIMARY KEY, -- \"lat,lng\" arrondi à 4 décimales (~11 m)\n lat REAL,\n lng REAL,\n pois TEXT, -- JSON : [{cat, name, dist_m}] (plus proche/catégorie)\n ts REAL\n);\n\"\"\"\n\n\n_SCHEMA_READY = False # le schéma/migration ne s'exécute qu'UNE fois par process\n\n\ndef _init_schema(con: sqlite3.Connection) -> None:\n \"\"\"Création de schéma + migration — coûteuse (write-lock). À faire une seule\n fois par process : l'exécuter à chaque connexion sérialisait les requêtes du\n web sur un verrou d'écriture (deadlock/starvation sous charge).\"\"\"\n con.executescript(_SCHEMA)\n cols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(listings)\")}\n if \"agency\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN agency TEXT\")\n if \"dup_hidden\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n if \"dauid\" not in cols: # aire de diffusion 2021 (stats de quartier)\n con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")\n if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n gcols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(geocode_cache)\")}\n if \"muni\" not in gcols: # municipalité officielle (entrées « ville:… »)\n con.execute(\"ALTER TABLE geocode_cache ADD COLUMN muni TEXT\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n con.commit()\n\n\ndef refresh_dedup(con: sqlite3.Connection) -> int:\n \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n\n Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée\n si une fiche de plus haute priorité — même n° Centris (external_id), active —\n existe : le flux central/agence principale d'abord, sinon la sous-agence au\n plus petit uid. Les fiches non sous-agence ne sont jamais masquées par\n cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).\n Retourne le nombre total de fiches masquées.\"\"\"\n AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n con.execute(\"UPDATE listings SET dup_hidden=0\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")\n # 3) dédup INTER-SOURCES par adresse : la même propriété publiée sur deux\n # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle\n # conservatrice : même adresse normalisée (civique + rue + ville) + même\n # type + prix identique à ±1 % → on garde la fiche la plus autoritaire.\n try:\n n_addr = dedup_by_address(con)\n if n_addr:\n print(f\"[immo-ka] dédup adresse: {n_addr} doublon(s) inter-sources masqué(s)\")\n except Exception:\n import traceback\n traceback.print_exc()\n n = con.execute(\"SELECT COUNT(*) c FROM listings WHERE dup_hidden=1\").fetchone()[\"c\"]\n con.commit()\n return n\n\n\n# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main)\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\"}\n\n\ndef _source_rank(source: str) -> int:\n \"\"\"Autorité d'une source pour la dédup d'adresse :\n 0 = source primaire (bannière/agence/FSBO), 1 = sous-agence (_ag_),\n 2 = petites annonces (republication probable).\"\"\"\n if source in _PETITES_ANNONCES:\n return 2\n if \"_ag_\" in source:\n return 1\n return 0\n\n\ndef dedup_by_address(con: sqlite3.Connection) -> int:\n \"\"\"Passe de déduplication conservatrice par ADRESSE (inter-sources).\n\n Clé : n° civique(s) + mots significatifs de la rue + ville normalisée +\n type canonique + n° d'app/unité (vide s'il n'y en a pas — deux unités\n différentes d'un même immeuble ne partagent JAMAIS la même clé, et une\n adresse sans unité ne s'apparie pas à une adresse avec unité). Dans une\n clé, seules les fiches au prix identique à ±1 % sont considérées comme\n doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis le plus petit uid. Retourne le nb masqué.\"\"\"\n import re as _re\n from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE\n groups: dict[tuple, list] = {}\n for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):\n civs, words = _addr_parts(r[\"address\"])\n if not civs or not words:\n continue\n a = _norm(r[\"address\"]).split(\",\")[0]\n mapt = _re.search(_APP_RE, a)\n apt = \"\"\n if mapt:\n toks = _re.findall(r\"[a-z0-9]+\", mapt.group(0))\n # dernier token = le n° d'unité (le 1er est le mot-clé app/unité/#)\n apt = toks[-1] if toks else \"\"\n key = (\"-\".join(civs), \" \".join(sorted(set(words))),\n _muni_norm(r[\"city\"]), _norm(r[\"property_type\"]), apt)\n groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))\n hidden = 0\n for rows in groups.values():\n if len(rows) < 2:\n continue\n rows.sort() # par prix croissant\n cluster: list = []\n for row in rows:\n if cluster and row[0] > cluster[0][0] * 1.01:\n hidden += _mask_cluster(con, cluster)\n cluster = []\n cluster.append(row)\n hidden += _mask_cluster(con, cluster)\n return hidden\n\n\ndef _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:\n \"\"\"Masque les doublons d'un groupe (même clé d'adresse, prix ±1 %), puis\n FUSIONNE en « golden record » : les champs vides de la fiche conservée sont\n complétés depuis les doublons masqués (description plus longue, galerie plus\n riche, superficies, année, GPS, téléphone) — le meilleur des deux sources.\"\"\"\n if len(cluster) < 2:\n return 0\n sources = [c[3] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[2] != keep[2]:\n con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n donors.append(c[2])\n n += 1\n try:\n _merge_golden(con, keep[2], donors)\n except Exception:\n pass # la fusion est un bonus — ne jamais casser la dédup\n return n\n\n\n_MERGE_NUM_FIELDS = (\"bedrooms\", \"bathrooms\", \"powder_rooms\", \"area_sqft\",\n \"lot_sqft\", \"year_built\")\n\n\ndef _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:\n \"\"\"Complète les champs vides de `keep_uid` depuis ses doublons masqués.\"\"\"\n if not donor_uids:\n return\n cols = (\"uid, description, images, bedrooms, bathrooms, powder_rooms,\"\n \" area_sqft, lot_sqft, year_built, lat, lng, broker_phone\")\n keep = con.execute(f\"SELECT {cols} FROM listings WHERE uid=?\",\n (keep_uid,)).fetchone()\n if keep is None:\n return\n sets, args = [], []\n kimgs = len(json.loads(keep[\"images\"] or \"[]\"))\n kdesc = len(keep[\"description\"] or \"\")\n best_imgs, best_desc = None, None\n donor_rows = con.execute(\n f\"SELECT {cols} FROM listings WHERE uid IN \"\n f\"({','.join('?' * len(donor_uids))})\", donor_uids).fetchall()\n merged_num: dict = {}\n for d in donor_rows:\n di = json.loads(d[\"images\"] or \"[]\")\n if len(di) > max(kimgs, len(json.loads(best_imgs or \"[]\"))):\n best_imgs = d[\"images\"]\n dd = d[\"description\"] or \"\"\n if len(dd) > max(kdesc, 80, len(best_desc or \"\")):\n best_desc = dd\n for f in _MERGE_NUM_FIELDS:\n if keep[f] is None and merged_num.get(f) is None and d[f] is not None:\n merged_num[f] = d[f]\n # GPS : toujours la PAIRE du même donneur (jamais lat et lng mélangés)\n if (keep[\"lat\"] is None and \"lat\" not in merged_num\n and d[\"lat\"] is not None and d[\"lng\"] is not None):\n merged_num[\"lat\"], merged_num[\"lng\"] = d[\"lat\"], d[\"lng\"]\n if not keep[\"broker_phone\"] and d[\"broker_phone\"] and \"broker_phone\" not in merged_num:\n merged_num[\"broker_phone\"] = d[\"broker_phone\"]\n if best_imgs is not None:\n sets.append(\"images=?\"); args.append(best_imgs)\n if best_desc is not None and kdesc < 80:\n sets.append(\"description=?\"); args.append(best_desc)\n for f, v in merged_num.items():\n sets.append(f\"{f}=?\"); args.append(v)\n if sets:\n args.append(keep_uid)\n con.execute(f\"UPDATE listings SET {', '.join(sets)} WHERE uid=?\", args)\n\n\ndef connect() -> sqlite3.Connection:\n global _SCHEMA_READY\n DB_PATH.parent.mkdir(parents=True, exist_ok=True)\n con = sqlite3.connect(DB_PATH, timeout=60)\n con.row_factory = sqlite3.Row\n # WAL + busy_timeout : accès concurrents (watcher + web) sans « db is locked ».\n con.execute(\"PRAGMA journal_mode=WAL\")\n # 120 s : couvre les longues transactions (refresh_dedup ~70 s) sans que les\n # autres écrivains (géocodage, vraiprix) ne lèvent « database is locked ».\n con.execute(\"PRAGMA busy_timeout=120000\")\n con.execute(\"PRAGMA synchronous=NORMAL\")\n if not _SCHEMA_READY:\n _init_schema(con)\n _SCHEMA_READY = True\n return con\n\n\n# ---------------------------------------------------------------------------\n# Synchronisation d'une source\n# ---------------------------------------------------------------------------\n\ndef _drift_alert(con: sqlite3.Connection, source: str, found: int,\n null_price_rate: float) -> str | None:\n \"\"\"Détecte une dérive du connecteur (chute du volume ou des prix extraits).\"\"\"\n hist = con.execute(\n \"SELECT found, stats FROM sync_log WHERE source=? AND ok=1\"\n \" ORDER BY ts DESC LIMIT ?\", (source, DRIFT_HISTORY)).fetchall()\n if len(hist) < 3:\n return None\n med_found = statistics.median(r[\"found\"] for r in hist)\n if med_found >= DRIFT_MIN_BASE and found <= DRIFT_RATIO * med_found:\n return (f\"dérive: {found} propriété(s) trouvée(s) contre une médiane de \"\n f\"{med_found:.0f} — retraits suspendus, vérifier le connecteur\")\n if found >= DRIFT_MIN_BASE and null_price_rate >= 0.8:\n rates = []\n for r in hist:\n try:\n rates.append(json.loads(r[\"stats\"] or \"{}\")[\"null_price_rate\"])\n except (KeyError, ValueError, TypeError):\n continue\n if rates and statistics.median(rates) <= 0.3:\n return (f\"dérive: {null_price_rate:.0%} des propriétés sans prix \"\n f\"(habituellement {statistics.median(rates):.0%}) — \"\n \"le format de la source a probablement changé\")\n return None\n\n\ndef sync_source(con: sqlite3.Connection, source: str,\n listings: list[PropertyListing]) -> dict:\n \"\"\"Synchronise les propriétés d'une source.\n\n - nouvelle propriété -> insertion\n - propriété modifiée -> mise à jour (comparaison de content_hash)\n - propriété disparue -> miss_count += 1, puis active=0 après MISS_GRACE\n exécutions consécutives (vendue ou retirée)\n - dérive détectée -> alerte consignée, retraits suspendus\n \"\"\"\n now = time.time()\n added = updated = 0\n seen_uids = set()\n\n n = len(listings)\n null_price = sum(1 for l in listings if l.price is None)\n null_addr = sum(1 for l in listings if not l.address)\n null_price_rate = round(null_price / n, 3) if n else 0.0\n\n alert = _drift_alert(con, source, n, null_price_rate)\n\n for lst in listings:\n seen_uids.add(lst.uid)\n h = lst.content_hash()\n row = con.execute(\"SELECT content_hash, price FROM listings WHERE uid=?\",\n (lst.uid,)).fetchone()\n params = dict(\n uid=lst.uid, source=lst.source, external_id=lst.external_id,\n url=lst.url, title=lst.title, address=lst.address,\n sector=lst.sector, city=lst.city, region=lst.region,\n property_type=lst.property_type, price=lst.price,\n price_label=lst.price_label, bedrooms=lst.bedrooms,\n bathrooms=lst.bathrooms, powder_rooms=lst.powder_rooms,\n area_sqft=lst.area_sqft, lot_sqft=lst.lot_sqft,\n year_built=lst.year_built, mls=lst.mls, status=lst.status,\n broker_name=lst.broker_name, broker_phone=lst.broker_phone,\n agency=lst.agency,\n description=lst.description,\n features=json.dumps(lst.features, ensure_ascii=False),\n details=json.dumps(lst.details, ensure_ascii=False),\n images=json.dumps(lst.images, ensure_ascii=False),\n lat=lst.lat, lng=lst.lng, content_hash=h, now=now,\n )\n if row is None:\n con.execute(\n \"\"\"INSERT INTO listings (uid, source, external_id, url, title,\n address, sector, city, region, property_type, price,\n price_label, bedrooms, bathrooms, powder_rooms, area_sqft,\n lot_sqft, year_built, mls, status, broker_name, broker_phone,\n agency, description, features, details, images, lat, lng,\n content_hash, first_seen, last_seen, updated_at,\n miss_count, active)\n VALUES (:uid,:source,:external_id,:url,:title,:address,\n :sector,:city,:region,:property_type,:price,:price_label,\n :bedrooms,:bathrooms,:powder_rooms,:area_sqft,:lot_sqft,\n :year_built,:mls,:status,:broker_name,:broker_phone,\n :agency,:description,:features,:details,:images,:lat,:lng,\n :content_hash,:now,:now,:now,0,1)\"\"\", params)\n if lst.price is not None:\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n added += 1\n elif row[\"content_hash\"] != h:\n # COALESCE : ne jamais écraser par null des coordonnées géocodées ni\n # les année/superficies remplies par enrichissement (rôle d'évaluation,\n # fiche détail) quand la source liste ne les fournit pas\n con.execute(\n \"\"\"UPDATE listings SET url=:url, title=:title,\n address=:address, sector=:sector, city=:city, region=:region,\n property_type=:property_type, price=:price,\n price_label=:price_label, bedrooms=:bedrooms,\n bathrooms=:bathrooms, powder_rooms=:powder_rooms,\n area_sqft=COALESCE(:area_sqft, area_sqft),\n lot_sqft=COALESCE(:lot_sqft, lot_sqft),\n year_built=COALESCE(:year_built, year_built),\n mls=:mls, status=:status,\n broker_name=:broker_name, broker_phone=:broker_phone,\n agency=:agency, description=:description, features=:features,\n details=:details, images=:images,\n lat=COALESCE(:lat, lat), lng=COALESCE(:lng, lng),\n content_hash=:content_hash, last_seen=:now,\n updated_at=:now, miss_count=0, active=1\n WHERE uid=:uid\"\"\", params)\n if lst.price != row[\"price\"]: # baisse/hausse de prix -> historique\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n updated += 1\n else:\n con.execute(\n \"UPDATE listings SET last_seen=?, miss_count=0, active=1 WHERE uid=?\",\n (now, lst.uid))\n\n # Propriétés de cette source qui n'apparaissent plus : délai de grâce,\n # puis désactivation (vendue/retirée). Suspendu si dérive détectée.\n removed = missed = 0\n if not alert:\n for r in con.execute(\n \"SELECT uid, miss_count FROM listings WHERE source=? AND active=1\",\n (source,)).fetchall():\n if r[\"uid\"] in seen_uids:\n continue\n missed += 1\n if r[\"miss_count\"] + 1 >= MISS_GRACE:\n con.execute(\n \"UPDATE listings SET active=0, miss_count=?, updated_at=?\"\n \" WHERE uid=?\", (r[\"miss_count\"] + 1, now, r[\"uid\"]))\n removed += 1\n else:\n con.execute(\"UPDATE listings SET miss_count=miss_count+1 WHERE uid=?\",\n (r[\"uid\"],))\n\n stats = {\n \"null_price_rate\": null_price_rate,\n \"null_address_rate\": round(null_addr / n, 3) if n else 0.0,\n \"missed\": missed,\n }\n if alert:\n stats[\"alert\"] = alert\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok,\"\n \" message, stats) VALUES (?,?,?,?,?,?,1,?,?)\",\n (source, now, n, added, updated, removed, alert or \"ok\",\n json.dumps(stats, ensure_ascii=False)))\n con.commit()\n out = {\"source\": source, \"found\": n, \"added\": added,\n \"updated\": updated, \"removed\": removed}\n if alert:\n out[\"alert\"] = alert\n return out\n\n\ndef log_failure(con: sqlite3.Connection, source: str, message: str) -> None:\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok, message)\"\n \" VALUES (?,?,0,0,0,0,0,?)\", (source, time.time(), message))\n con.commit()\n\n\n# ---------------------------------------------------------------------------\n# Cache des pages détail (« détail si nouveau/modifié »)\n# ---------------------------------------------------------------------------\n\ndef get_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str) -> dict | None:\n \"\"\"Payload détail mis en cache si la clé (hash liste) n'a pas changé.\"\"\"\n row = con.execute(\n \"SELECT key, payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"key\"] == key and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef get_stale_detail(con: sqlite3.Connection, source: str,\n external_id: str) -> dict | None:\n \"\"\"Payload détail SANS vérifier la clé — repli « périmé plutôt que rien »\n quand le budget de re-fetch d'un cycle est épuisé (ex. bump de version de\n clé) : la fiche garde photos/détails existants en attendant son re-parse.\"\"\"\n row = con.execute(\n \"SELECT payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef put_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str, payload: dict) -> None:\n con.execute(\n \"INSERT INTO detail_cache (source, external_id, key, payload, fetched_at)\"\n \" VALUES (?,?,?,?,?)\"\n \" ON CONFLICT(source, external_id) DO UPDATE SET\"\n \" key=excluded.key, payload=excluded.payload, fetched_at=excluded.fetched_at\",\n (source, external_id, key, json.dumps(payload, ensure_ascii=False),\n time.time()))\n con.commit()\n","structuredPatch":[{"oldStart":135,"oldLines":6,"newStart":135,"newLines":8,"lines":[" con.execute(\"ALTER TABLE listings ADD COLUMN agency TEXT\")"," if \"dup_hidden\" not in cols:"," con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")","+ if \"dup_of\" not in cols: # uid de la fiche visible au profit de laquelle","+ con.execute(\"ALTER TABLE listings ADD COLUMN dup_of TEXT\") # celle-ci est masquée"," if \"dauid\" not in cols: # aire de diffusion 2021 (stats de quartier)"," con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")"," if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"d69859e5-9feb-4704-bc1a-e434f206371e","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbwtw6idsqxH8LFCKr3","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01BPVpddY85qFZCNbxReg3ET","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","old_string":" con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")","new_string":" con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_dupof ON listings(dup_of)\")"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":444,"cache_read_input_tokens":58164,"cache_creation":{"ephemeral_5m_input_tokens":444,"ephemeral_1h_input_tokens":0},"output_tokens":20,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"346322a8-0fa5-4bb4-885d-911c80309036"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01BPVpddY85qFZCNbxReg3ET","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/db.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ccf70dd1-2f3f-4946-9eaf-48080ed786a7","timestamp":"2026-08-25T14:12:23.364Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","oldString":" con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")","newString":" con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_dupof ON listings(dup_of)\")","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# db.py : persistance SQLite — upsert avec détection de changements,\n# cycle de vie avec délai de grâce (2 syncs), détection de dérive,\n# historique de prix, cache des pages détail.\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport sqlite3\nimport statistics\nimport time\nfrom pathlib import Path\n\nfrom .schema import PropertyListing\n\nDB_PATH = Path(__file__).resolve().parent.parent / \"data\" / \"immoka.db\"\n\n# Nombre d'exécutions consécutives où une propriété doit être absente de la\n# source avant d'être désactivée (délai de grâce contre les ratés ponctuels).\nMISS_GRACE = 2\n\n# Dérive : si une source retourne <= DRIFT_RATIO × sa médiane historique\n# (médiane >= DRIFT_MIN_BASE annonces), on alerte et on suspend les retraits.\nDRIFT_RATIO = 0.25\nDRIFT_MIN_BASE = 8\nDRIFT_HISTORY = 5\n\n_SCHEMA = \"\"\"\nCREATE TABLE IF NOT EXISTS listings (\n uid TEXT PRIMARY KEY,\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n url TEXT,\n title TEXT,\n address TEXT,\n sector TEXT,\n city TEXT,\n region TEXT,\n property_type TEXT,\n price REAL,\n price_label TEXT,\n bedrooms INTEGER,\n bathrooms INTEGER,\n powder_rooms INTEGER,\n area_sqft REAL,\n lot_sqft REAL,\n year_built INTEGER,\n mls TEXT,\n status TEXT DEFAULT 'a-vendre',\n broker_name TEXT,\n broker_phone TEXT,\n agency TEXT,\n description TEXT,\n features TEXT, -- JSON (liste de textes source)\n details TEXT, -- JSON (champs structurés)\n images TEXT, -- JSON\n lat REAL,\n lng REAL,\n geocode_failed INTEGER DEFAULT 0,\n content_hash TEXT,\n first_seen REAL,\n last_seen REAL,\n updated_at REAL,\n miss_count INTEGER DEFAULT 0,\n active INTEGER DEFAULT 1,\n dup_hidden INTEGER DEFAULT 0 -- 1 = doublon de sous-agence masqué (dédup Centris)\n);\nCREATE INDEX IF NOT EXISTS idx_listings_source ON listings(source);\nCREATE INDEX IF NOT EXISTS idx_listings_city ON listings(city);\nCREATE INDEX IF NOT EXISTS idx_listings_type ON listings(property_type);\nCREATE INDEX IF NOT EXISTS idx_listings_active ON listings(active);\nCREATE INDEX IF NOT EXISTS idx_listings_extid ON listings(external_id);\n\nCREATE TABLE IF NOT EXISTS sync_log (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n source TEXT,\n ts REAL,\n found INTEGER,\n added INTEGER,\n updated INTEGER,\n removed INTEGER,\n ok INTEGER,\n message TEXT,\n stats TEXT -- JSON : taux de champs null, missed, alerte…\n);\n\nCREATE TABLE IF NOT EXISTS detail_cache (\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n key TEXT, -- hash du contenu « liste » de l'annonce\n payload TEXT, -- JSON opaque propre au connecteur\n fetched_at REAL,\n PRIMARY KEY (source, external_id)\n);\n\nCREATE TABLE IF NOT EXISTS price_log (\n uid TEXT NOT NULL,\n ts REAL NOT NULL,\n price REAL -- prix observé (baisses/hausses de prix demandé)\n);\nCREATE INDEX IF NOT EXISTS idx_price_log_uid ON price_log(uid);\n\nCREATE TABLE IF NOT EXISTS geocode_cache (\n address TEXT PRIMARY KEY,\n lat REAL,\n lng REAL,\n provider TEXT,\n failed INTEGER DEFAULT 0,\n ts REAL,\n muni TEXT -- municipalité officielle (clés « ville:… »)\n);\n\nCREATE TABLE IF NOT EXISTS poi_cache (\n coord_key TEXT PRIMARY KEY, -- \"lat,lng\" arrondi à 4 décimales (~11 m)\n lat REAL,\n lng REAL,\n pois TEXT, -- JSON : [{cat, name, dist_m}] (plus proche/catégorie)\n ts REAL\n);\n\"\"\"\n\n\n_SCHEMA_READY = False # le schéma/migration ne s'exécute qu'UNE fois par process\n\n\ndef _init_schema(con: sqlite3.Connection) -> None:\n \"\"\"Création de schéma + migration — coûteuse (write-lock). À faire une seule\n fois par process : l'exécuter à chaque connexion sérialisait les requêtes du\n web sur un verrou d'écriture (deadlock/starvation sous charge).\"\"\"\n con.executescript(_SCHEMA)\n cols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(listings)\")}\n if \"agency\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN agency TEXT\")\n if \"dup_hidden\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n if \"dup_of\" not in cols: # uid de la fiche visible au profit de laquelle\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_of TEXT\") # celle-ci est masquée\n if \"dauid\" not in cols: # aire de diffusion 2021 (stats de quartier)\n con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")\n if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n gcols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(geocode_cache)\")}\n if \"muni\" not in gcols: # municipalité officielle (entrées « ville:… »)\n con.execute(\"ALTER TABLE geocode_cache ADD COLUMN muni TEXT\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n con.commit()\n\n\ndef refresh_dedup(con: sqlite3.Connection) -> int:\n \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n\n Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée\n si une fiche de plus haute priorité — même n° Centris (external_id), active —\n existe : le flux central/agence principale d'abord, sinon la sous-agence au\n plus petit uid. Les fiches non sous-agence ne sont jamais masquées par\n cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).\n Retourne le nombre total de fiches masquées.\"\"\"\n AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n con.execute(\"UPDATE listings SET dup_hidden=0\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")\n # 3) dédup INTER-SOURCES par adresse : la même propriété publiée sur deux\n # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle\n # conservatrice : même adresse normalisée (civique + rue + ville) + même\n # type + prix identique à ±1 % → on garde la fiche la plus autoritaire.\n try:\n n_addr = dedup_by_address(con)\n if n_addr:\n print(f\"[immo-ka] dédup adresse: {n_addr} doublon(s) inter-sources masqué(s)\")\n except Exception:\n import traceback\n traceback.print_exc()\n n = con.execute(\"SELECT COUNT(*) c FROM listings WHERE dup_hidden=1\").fetchone()[\"c\"]\n con.commit()\n return n\n\n\n# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main)\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\"}\n\n\ndef _source_rank(source: str) -> int:\n \"\"\"Autorité d'une source pour la dédup d'adresse :\n 0 = source primaire (bannière/agence/FSBO), 1 = sous-agence (_ag_),\n 2 = petites annonces (republication probable).\"\"\"\n if source in _PETITES_ANNONCES:\n return 2\n if \"_ag_\" in source:\n return 1\n return 0\n\n\ndef dedup_by_address(con: sqlite3.Connection) -> int:\n \"\"\"Passe de déduplication conservatrice par ADRESSE (inter-sources).\n\n Clé : n° civique(s) + mots significatifs de la rue + ville normalisée +\n type canonique + n° d'app/unité (vide s'il n'y en a pas — deux unités\n différentes d'un même immeuble ne partagent JAMAIS la même clé, et une\n adresse sans unité ne s'apparie pas à une adresse avec unité). Dans une\n clé, seules les fiches au prix identique à ±1 % sont considérées comme\n doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis le plus petit uid. Retourne le nb masqué.\"\"\"\n import re as _re\n from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE\n groups: dict[tuple, list] = {}\n for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):\n civs, words = _addr_parts(r[\"address\"])\n if not civs or not words:\n continue\n a = _norm(r[\"address\"]).split(\",\")[0]\n mapt = _re.search(_APP_RE, a)\n apt = \"\"\n if mapt:\n toks = _re.findall(r\"[a-z0-9]+\", mapt.group(0))\n # dernier token = le n° d'unité (le 1er est le mot-clé app/unité/#)\n apt = toks[-1] if toks else \"\"\n key = (\"-\".join(civs), \" \".join(sorted(set(words))),\n _muni_norm(r[\"city\"]), _norm(r[\"property_type\"]), apt)\n groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))\n hidden = 0\n for rows in groups.values():\n if len(rows) < 2:\n continue\n rows.sort() # par prix croissant\n cluster: list = []\n for row in rows:\n if cluster and row[0] > cluster[0][0] * 1.01:\n hidden += _mask_cluster(con, cluster)\n cluster = []\n cluster.append(row)\n hidden += _mask_cluster(con, cluster)\n return hidden\n\n\ndef _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:\n \"\"\"Masque les doublons d'un groupe (même clé d'adresse, prix ±1 %), puis\n FUSIONNE en « golden record » : les champs vides de la fiche conservée sont\n complétés depuis les doublons masqués (description plus longue, galerie plus\n riche, superficies, année, GPS, téléphone) — le meilleur des deux sources.\"\"\"\n if len(cluster) < 2:\n return 0\n sources = [c[3] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[2] != keep[2]:\n con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n donors.append(c[2])\n n += 1\n try:\n _merge_golden(con, keep[2], donors)\n except Exception:\n pass # la fusion est un bonus — ne jamais casser la dédup\n return n\n\n\n_MERGE_NUM_FIELDS = (\"bedrooms\", \"bathrooms\", \"powder_rooms\", \"area_sqft\",\n \"lot_sqft\", \"year_built\")\n\n\ndef _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:\n \"\"\"Complète les champs vides de `keep_uid` depuis ses doublons masqués.\"\"\"\n if not donor_uids:\n return\n cols = (\"uid, description, images, bedrooms, bathrooms, powder_rooms,\"\n \" area_sqft, lot_sqft, year_built, lat, lng, broker_phone\")\n keep = con.execute(f\"SELECT {cols} FROM listings WHERE uid=?\",\n (keep_uid,)).fetchone()\n if keep is None:\n return\n sets, args = [], []\n kimgs = len(json.loads(keep[\"images\"] or \"[]\"))\n kdesc = len(keep[\"description\"] or \"\")\n best_imgs, best_desc = None, None\n donor_rows = con.execute(\n f\"SELECT {cols} FROM listings WHERE uid IN \"\n f\"({','.join('?' * len(donor_uids))})\", donor_uids).fetchall()\n merged_num: dict = {}\n for d in donor_rows:\n di = json.loads(d[\"images\"] or \"[]\")\n if len(di) > max(kimgs, len(json.loads(best_imgs or \"[]\"))):\n best_imgs = d[\"images\"]\n dd = d[\"description\"] or \"\"\n if len(dd) > max(kdesc, 80, len(best_desc or \"\")):\n best_desc = dd\n for f in _MERGE_NUM_FIELDS:\n if keep[f] is None and merged_num.get(f) is None and d[f] is not None:\n merged_num[f] = d[f]\n # GPS : toujours la PAIRE du même donneur (jamais lat et lng mélangés)\n if (keep[\"lat\"] is None and \"lat\" not in merged_num\n and d[\"lat\"] is not None and d[\"lng\"] is not None):\n merged_num[\"lat\"], merged_num[\"lng\"] = d[\"lat\"], d[\"lng\"]\n if not keep[\"broker_phone\"] and d[\"broker_phone\"] and \"broker_phone\" not in merged_num:\n merged_num[\"broker_phone\"] = d[\"broker_phone\"]\n if best_imgs is not None:\n sets.append(\"images=?\"); args.append(best_imgs)\n if best_desc is not None and kdesc < 80:\n sets.append(\"description=?\"); args.append(best_desc)\n for f, v in merged_num.items():\n sets.append(f\"{f}=?\"); args.append(v)\n if sets:\n args.append(keep_uid)\n con.execute(f\"UPDATE listings SET {', '.join(sets)} WHERE uid=?\", args)\n\n\ndef connect() -> sqlite3.Connection:\n global _SCHEMA_READY\n DB_PATH.parent.mkdir(parents=True, exist_ok=True)\n con = sqlite3.connect(DB_PATH, timeout=60)\n con.row_factory = sqlite3.Row\n # WAL + busy_timeout : accès concurrents (watcher + web) sans « db is locked ».\n con.execute(\"PRAGMA journal_mode=WAL\")\n # 120 s : couvre les longues transactions (refresh_dedup ~70 s) sans que les\n # autres écrivains (géocodage, vraiprix) ne lèvent « database is locked ».\n con.execute(\"PRAGMA busy_timeout=120000\")\n con.execute(\"PRAGMA synchronous=NORMAL\")\n if not _SCHEMA_READY:\n _init_schema(con)\n _SCHEMA_READY = True\n return con\n\n\n# ---------------------------------------------------------------------------\n# Synchronisation d'une source\n# ---------------------------------------------------------------------------\n\ndef _drift_alert(con: sqlite3.Connection, source: str, found: int,\n null_price_rate: float) -> str | None:\n \"\"\"Détecte une dérive du connecteur (chute du volume ou des prix extraits).\"\"\"\n hist = con.execute(\n \"SELECT found, stats FROM sync_log WHERE source=? AND ok=1\"\n \" ORDER BY ts DESC LIMIT ?\", (source, DRIFT_HISTORY)).fetchall()\n if len(hist) < 3:\n return None\n med_found = statistics.median(r[\"found\"] for r in hist)\n if med_found >= DRIFT_MIN_BASE and found <= DRIFT_RATIO * med_found:\n return (f\"dérive: {found} propriété(s) trouvée(s) contre une médiane de \"\n f\"{med_found:.0f} — retraits suspendus, vérifier le connecteur\")\n if found >= DRIFT_MIN_BASE and null_price_rate >= 0.8:\n rates = []\n for r in hist:\n try:\n rates.append(json.loads(r[\"stats\"] or \"{}\")[\"null_price_rate\"])\n except (KeyError, ValueError, TypeError):\n continue\n if rates and statistics.median(rates) <= 0.3:\n return (f\"dérive: {null_price_rate:.0%} des propriétés sans prix \"\n f\"(habituellement {statistics.median(rates):.0%}) — \"\n \"le format de la source a probablement changé\")\n return None\n\n\ndef sync_source(con: sqlite3.Connection, source: str,\n listings: list[PropertyListing]) -> dict:\n \"\"\"Synchronise les propriétés d'une source.\n\n - nouvelle propriété -> insertion\n - propriété modifiée -> mise à jour (comparaison de content_hash)\n - propriété disparue -> miss_count += 1, puis active=0 après MISS_GRACE\n exécutions consécutives (vendue ou retirée)\n - dérive détectée -> alerte consignée, retraits suspendus\n \"\"\"\n now = time.time()\n added = updated = 0\n seen_uids = set()\n\n n = len(listings)\n null_price = sum(1 for l in listings if l.price is None)\n null_addr = sum(1 for l in listings if not l.address)\n null_price_rate = round(null_price / n, 3) if n else 0.0\n\n alert = _drift_alert(con, source, n, null_price_rate)\n\n for lst in listings:\n seen_uids.add(lst.uid)\n h = lst.content_hash()\n row = con.execute(\"SELECT content_hash, price FROM listings WHERE uid=?\",\n (lst.uid,)).fetchone()\n params = dict(\n uid=lst.uid, source=lst.source, external_id=lst.external_id,\n url=lst.url, title=lst.title, address=lst.address,\n sector=lst.sector, city=lst.city, region=lst.region,\n property_type=lst.property_type, price=lst.price,\n price_label=lst.price_label, bedrooms=lst.bedrooms,\n bathrooms=lst.bathrooms, powder_rooms=lst.powder_rooms,\n area_sqft=lst.area_sqft, lot_sqft=lst.lot_sqft,\n year_built=lst.year_built, mls=lst.mls, status=lst.status,\n broker_name=lst.broker_name, broker_phone=lst.broker_phone,\n agency=lst.agency,\n description=lst.description,\n features=json.dumps(lst.features, ensure_ascii=False),\n details=json.dumps(lst.details, ensure_ascii=False),\n images=json.dumps(lst.images, ensure_ascii=False),\n lat=lst.lat, lng=lst.lng, content_hash=h, now=now,\n )\n if row is None:\n con.execute(\n \"\"\"INSERT INTO listings (uid, source, external_id, url, title,\n address, sector, city, region, property_type, price,\n price_label, bedrooms, bathrooms, powder_rooms, area_sqft,\n lot_sqft, year_built, mls, status, broker_name, broker_phone,\n agency, description, features, details, images, lat, lng,\n content_hash, first_seen, last_seen, updated_at,\n miss_count, active)\n VALUES (:uid,:source,:external_id,:url,:title,:address,\n :sector,:city,:region,:property_type,:price,:price_label,\n :bedrooms,:bathrooms,:powder_rooms,:area_sqft,:lot_sqft,\n :year_built,:mls,:status,:broker_name,:broker_phone,\n :agency,:description,:features,:details,:images,:lat,:lng,\n :content_hash,:now,:now,:now,0,1)\"\"\", params)\n if lst.price is not None:\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n added += 1\n elif row[\"content_hash\"] != h:\n # COALESCE : ne jamais écraser par null des coordonnées géocodées ni\n # les année/superficies remplies par enrichissement (rôle d'évaluation,\n # fiche détail) quand la source liste ne les fournit pas\n con.execute(\n \"\"\"UPDATE listings SET url=:url, title=:title,\n address=:address, sector=:sector, city=:city, region=:region,\n property_type=:property_type, price=:price,\n price_label=:price_label, bedrooms=:bedrooms,\n bathrooms=:bathrooms, powder_rooms=:powder_rooms,\n area_sqft=COALESCE(:area_sqft, area_sqft),\n lot_sqft=COALESCE(:lot_sqft, lot_sqft),\n year_built=COALESCE(:year_built, year_built),\n mls=:mls, status=:status,\n broker_name=:broker_name, broker_phone=:broker_phone,\n agency=:agency, description=:description, features=:features,\n details=:details, images=:images,\n lat=COALESCE(:lat, lat), lng=COALESCE(:lng, lng),\n content_hash=:content_hash, last_seen=:now,\n updated_at=:now, miss_count=0, active=1\n WHERE uid=:uid\"\"\", params)\n if lst.price != row[\"price\"]: # baisse/hausse de prix -> historique\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n updated += 1\n else:\n con.execute(\n \"UPDATE listings SET last_seen=?, miss_count=0, active=1 WHERE uid=?\",\n (now, lst.uid))\n\n # Propriétés de cette source qui n'apparaissent plus : délai de grâce,\n # puis désactivation (vendue/retirée). Suspendu si dérive détectée.\n removed = missed = 0\n if not alert:\n for r in con.execute(\n \"SELECT uid, miss_count FROM listings WHERE source=? AND active=1\",\n (source,)).fetchall():\n if r[\"uid\"] in seen_uids:\n continue\n missed += 1\n if r[\"miss_count\"] + 1 >= MISS_GRACE:\n con.execute(\n \"UPDATE listings SET active=0, miss_count=?, updated_at=?\"\n \" WHERE uid=?\", (r[\"miss_count\"] + 1, now, r[\"uid\"]))\n removed += 1\n else:\n con.execute(\"UPDATE listings SET miss_count=miss_count+1 WHERE uid=?\",\n (r[\"uid\"],))\n\n stats = {\n \"null_price_rate\": null_price_rate,\n \"null_address_rate\": round(null_addr / n, 3) if n else 0.0,\n \"missed\": missed,\n }\n if alert:\n stats[\"alert\"] = alert\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok,\"\n \" message, stats) VALUES (?,?,?,?,?,?,1,?,?)\",\n (source, now, n, added, updated, removed, alert or \"ok\",\n json.dumps(stats, ensure_ascii=False)))\n con.commit()\n out = {\"source\": source, \"found\": n, \"added\": added,\n \"updated\": updated, \"removed\": removed}\n if alert:\n out[\"alert\"] = alert\n return out\n\n\ndef log_failure(con: sqlite3.Connection, source: str, message: str) -> None:\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok, message)\"\n \" VALUES (?,?,0,0,0,0,0,?)\", (source, time.time(), message))\n con.commit()\n\n\n# ---------------------------------------------------------------------------\n# Cache des pages détail (« détail si nouveau/modifié »)\n# ---------------------------------------------------------------------------\n\ndef get_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str) -> dict | None:\n \"\"\"Payload détail mis en cache si la clé (hash liste) n'a pas changé.\"\"\"\n row = con.execute(\n \"SELECT key, payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"key\"] == key and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef get_stale_detail(con: sqlite3.Connection, source: str,\n external_id: str) -> dict | None:\n \"\"\"Payload détail SANS vérifier la clé — repli « périmé plutôt que rien »\n quand le budget de re-fetch d'un cycle est épuisé (ex. bump de version de\n clé) : la fiche garde photos/détails existants en attendant son re-parse.\"\"\"\n row = con.execute(\n \"SELECT payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef put_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str, payload: dict) -> None:\n con.execute(\n \"INSERT INTO detail_cache (source, external_id, key, payload, fetched_at)\"\n \" VALUES (?,?,?,?,?)\"\n \" ON CONFLICT(source, external_id) DO UPDATE SET\"\n \" key=excluded.key, payload=excluded.payload, fetched_at=excluded.fetched_at\",\n (source, external_id, key, json.dumps(payload, ensure_ascii=False),\n time.time()))\n con.commit()\n","structuredPatch":[{"oldStart":145,"oldLines":6,"newStart":145,"newLines":7,"lines":[" if \"muni\" not in gcols: # municipalité officielle (entrées « ville:… »)"," con.execute(\"ALTER TABLE geocode_cache ADD COLUMN muni TEXT\")"," con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")","+ con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_dupof ON listings(dup_of)\")"," con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")"," con.commit()"," "]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"5a27e245-b8d5-4e21-bacc-763a5709608d","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbxGn1En5kMG1v56ujt","type":"message","role":"assistant","content":[{"type":"text","text":"Maintenant les 3 passes de dédup : reset `dup_of`, persistance dans les passes 1 et 2."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":330,"cache_read_input_tokens":58608,"cache_creation":{"ephemeral_5m_input_tokens":330,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"566ce04b-33af-431b-a4f1-a526a7478640"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbxGn1En5kMG1v56ujt","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_016SUnCHt23axbf3QxhKEJT8","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","old_string":" con.execute(\"UPDATE listings SET dup_hidden=0\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")","new_string":" con.execute(\"UPDATE listings SET dup_hidden=0, dup_of=NULL\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n # dup_of = la fiche canonique (pour la box « Aussi publiée sur… »).\n con.execute(\n f\"UPDATE listings SET dup_hidden=1,\"\n f\" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{NOTAG})\"\n f\" WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1,\"\n f\" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\"\n f\" WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":330,"cache_read_input_tokens":58608,"cache_creation":{"ephemeral_5m_input_tokens":330,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"0d4b254a-6f91-4d98-a34d-8cbfb18fbb0d"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_016SUnCHt23axbf3QxhKEJT8","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/db.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"f11e00de-5416-4f22-8adc-6f21eaf4d081","timestamp":"2026-08-25T14:12:37.879Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","oldString":" con.execute(\"UPDATE listings SET dup_hidden=0\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")","newString":" con.execute(\"UPDATE listings SET dup_hidden=0, dup_of=NULL\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n # dup_of = la fiche canonique (pour la box « Aussi publiée sur… »).\n con.execute(\n f\"UPDATE listings SET dup_hidden=1,\"\n f\" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{NOTAG})\"\n f\" WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1,\"\n f\" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\"\n f\" WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# db.py : persistance SQLite — upsert avec détection de changements,\n# cycle de vie avec délai de grâce (2 syncs), détection de dérive,\n# historique de prix, cache des pages détail.\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport sqlite3\nimport statistics\nimport time\nfrom pathlib import Path\n\nfrom .schema import PropertyListing\n\nDB_PATH = Path(__file__).resolve().parent.parent / \"data\" / \"immoka.db\"\n\n# Nombre d'exécutions consécutives où une propriété doit être absente de la\n# source avant d'être désactivée (délai de grâce contre les ratés ponctuels).\nMISS_GRACE = 2\n\n# Dérive : si une source retourne <= DRIFT_RATIO × sa médiane historique\n# (médiane >= DRIFT_MIN_BASE annonces), on alerte et on suspend les retraits.\nDRIFT_RATIO = 0.25\nDRIFT_MIN_BASE = 8\nDRIFT_HISTORY = 5\n\n_SCHEMA = \"\"\"\nCREATE TABLE IF NOT EXISTS listings (\n uid TEXT PRIMARY KEY,\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n url TEXT,\n title TEXT,\n address TEXT,\n sector TEXT,\n city TEXT,\n region TEXT,\n property_type TEXT,\n price REAL,\n price_label TEXT,\n bedrooms INTEGER,\n bathrooms INTEGER,\n powder_rooms INTEGER,\n area_sqft REAL,\n lot_sqft REAL,\n year_built INTEGER,\n mls TEXT,\n status TEXT DEFAULT 'a-vendre',\n broker_name TEXT,\n broker_phone TEXT,\n agency TEXT,\n description TEXT,\n features TEXT, -- JSON (liste de textes source)\n details TEXT, -- JSON (champs structurés)\n images TEXT, -- JSON\n lat REAL,\n lng REAL,\n geocode_failed INTEGER DEFAULT 0,\n content_hash TEXT,\n first_seen REAL,\n last_seen REAL,\n updated_at REAL,\n miss_count INTEGER DEFAULT 0,\n active INTEGER DEFAULT 1,\n dup_hidden INTEGER DEFAULT 0 -- 1 = doublon de sous-agence masqué (dédup Centris)\n);\nCREATE INDEX IF NOT EXISTS idx_listings_source ON listings(source);\nCREATE INDEX IF NOT EXISTS idx_listings_city ON listings(city);\nCREATE INDEX IF NOT EXISTS idx_listings_type ON listings(property_type);\nCREATE INDEX IF NOT EXISTS idx_listings_active ON listings(active);\nCREATE INDEX IF NOT EXISTS idx_listings_extid ON listings(external_id);\n\nCREATE TABLE IF NOT EXISTS sync_log (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n source TEXT,\n ts REAL,\n found INTEGER,\n added INTEGER,\n updated INTEGER,\n removed INTEGER,\n ok INTEGER,\n message TEXT,\n stats TEXT -- JSON : taux de champs null, missed, alerte…\n);\n\nCREATE TABLE IF NOT EXISTS detail_cache (\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n key TEXT, -- hash du contenu « liste » de l'annonce\n payload TEXT, -- JSON opaque propre au connecteur\n fetched_at REAL,\n PRIMARY KEY (source, external_id)\n);\n\nCREATE TABLE IF NOT EXISTS price_log (\n uid TEXT NOT NULL,\n ts REAL NOT NULL,\n price REAL -- prix observé (baisses/hausses de prix demandé)\n);\nCREATE INDEX IF NOT EXISTS idx_price_log_uid ON price_log(uid);\n\nCREATE TABLE IF NOT EXISTS geocode_cache (\n address TEXT PRIMARY KEY,\n lat REAL,\n lng REAL,\n provider TEXT,\n failed INTEGER DEFAULT 0,\n ts REAL,\n muni TEXT -- municipalité officielle (clés « ville:… »)\n);\n\nCREATE TABLE IF NOT EXISTS poi_cache (\n coord_key TEXT PRIMARY KEY, -- \"lat,lng\" arrondi à 4 décimales (~11 m)\n lat REAL,\n lng REAL,\n pois TEXT, -- JSON : [{cat, name, dist_m}] (plus proche/catégorie)\n ts REAL\n);\n\"\"\"\n\n\n_SCHEMA_READY = False # le schéma/migration ne s'exécute qu'UNE fois par process\n\n\ndef _init_schema(con: sqlite3.Connection) -> None:\n \"\"\"Création de schéma + migration — coûteuse (write-lock). À faire une seule\n fois par process : l'exécuter à chaque connexion sérialisait les requêtes du\n web sur un verrou d'écriture (deadlock/starvation sous charge).\"\"\"\n con.executescript(_SCHEMA)\n cols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(listings)\")}\n if \"agency\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN agency TEXT\")\n if \"dup_hidden\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n if \"dup_of\" not in cols: # uid de la fiche visible au profit de laquelle\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_of TEXT\") # celle-ci est masquée\n if \"dauid\" not in cols: # aire de diffusion 2021 (stats de quartier)\n con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")\n if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n gcols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(geocode_cache)\")}\n if \"muni\" not in gcols: # municipalité officielle (entrées « ville:… »)\n con.execute(\"ALTER TABLE geocode_cache ADD COLUMN muni TEXT\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_dupof ON listings(dup_of)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n con.commit()\n\n\ndef refresh_dedup(con: sqlite3.Connection) -> int:\n \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n\n Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée\n si une fiche de plus haute priorité — même n° Centris (external_id), active —\n existe : le flux central/agence principale d'abord, sinon la sous-agence au\n plus petit uid. Les fiches non sous-agence ne sont jamais masquées par\n cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).\n Retourne le nombre total de fiches masquées.\"\"\"\n AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n con.execute(\"UPDATE listings SET dup_hidden=0\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")\n # 3) dédup INTER-SOURCES par adresse : la même propriété publiée sur deux\n # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle\n # conservatrice : même adresse normalisée (civique + rue + ville) + même\n # type + prix identique à ±1 % → on garde la fiche la plus autoritaire.\n try:\n n_addr = dedup_by_address(con)\n if n_addr:\n print(f\"[immo-ka] dédup adresse: {n_addr} doublon(s) inter-sources masqué(s)\")\n except Exception:\n import traceback\n traceback.print_exc()\n n = con.execute(\"SELECT COUNT(*) c FROM listings WHERE dup_hidden=1\").fetchone()[\"c\"]\n con.commit()\n return n\n\n\n# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main)\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\"}\n\n\ndef _source_rank(source: str) -> int:\n \"\"\"Autorité d'une source pour la dédup d'adresse :\n 0 = source primaire (bannière/agence/FSBO), 1 = sous-agence (_ag_),\n 2 = petites annonces (republication probable).\"\"\"\n if source in _PETITES_ANNONCES:\n return 2\n if \"_ag_\" in source:\n return 1\n return 0\n\n\ndef dedup_by_address(con: sqlite3.Connection) -> int:\n \"\"\"Passe de déduplication conservatrice par ADRESSE (inter-sources).\n\n Clé : n° civique(s) + mots significatifs de la rue + ville normalisée +\n type canonique + n° d'app/unité (vide s'il n'y en a pas — deux unités\n différentes d'un même immeuble ne partagent JAMAIS la même clé, et une\n adresse sans unité ne s'apparie pas à une adresse avec unité). Dans une\n clé, seules les fiches au prix identique à ±1 % sont considérées comme\n doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis le plus petit uid. Retourne le nb masqué.\"\"\"\n import re as _re\n from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE\n groups: dict[tuple, list] = {}\n for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):\n civs, words = _addr_parts(r[\"address\"])\n if not civs or not words:\n continue\n a = _norm(r[\"address\"]).split(\",\")[0]\n mapt = _re.search(_APP_RE, a)\n apt = \"\"\n if mapt:\n toks = _re.findall(r\"[a-z0-9]+\", mapt.group(0))\n # dernier token = le n° d'unité (le 1er est le mot-clé app/unité/#)\n apt = toks[-1] if toks else \"\"\n key = (\"-\".join(civs), \" \".join(sorted(set(words))),\n _muni_norm(r[\"city\"]), _norm(r[\"property_type\"]), apt)\n groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))\n hidden = 0\n for rows in groups.values():\n if len(rows) < 2:\n continue\n rows.sort() # par prix croissant\n cluster: list = []\n for row in rows:\n if cluster and row[0] > cluster[0][0] * 1.01:\n hidden += _mask_cluster(con, cluster)\n cluster = []\n cluster.append(row)\n hidden += _mask_cluster(con, cluster)\n return hidden\n\n\ndef _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:\n \"\"\"Masque les doublons d'un groupe (même clé d'adresse, prix ±1 %), puis\n FUSIONNE en « golden record » : les champs vides de la fiche conservée sont\n complétés depuis les doublons masqués (description plus longue, galerie plus\n riche, superficies, année, GPS, téléphone) — le meilleur des deux sources.\"\"\"\n if len(cluster) < 2:\n return 0\n sources = [c[3] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[2] != keep[2]:\n con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n donors.append(c[2])\n n += 1\n try:\n _merge_golden(con, keep[2], donors)\n except Exception:\n pass # la fusion est un bonus — ne jamais casser la dédup\n return n\n\n\n_MERGE_NUM_FIELDS = (\"bedrooms\", \"bathrooms\", \"powder_rooms\", \"area_sqft\",\n \"lot_sqft\", \"year_built\")\n\n\ndef _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:\n \"\"\"Complète les champs vides de `keep_uid` depuis ses doublons masqués.\"\"\"\n if not donor_uids:\n return\n cols = (\"uid, description, images, bedrooms, bathrooms, powder_rooms,\"\n \" area_sqft, lot_sqft, year_built, lat, lng, broker_phone\")\n keep = con.execute(f\"SELECT {cols} FROM listings WHERE uid=?\",\n (keep_uid,)).fetchone()\n if keep is None:\n return\n sets, args = [], []\n kimgs = len(json.loads(keep[\"images\"] or \"[]\"))\n kdesc = len(keep[\"description\"] or \"\")\n best_imgs, best_desc = None, None\n donor_rows = con.execute(\n f\"SELECT {cols} FROM listings WHERE uid IN \"\n f\"({','.join('?' * len(donor_uids))})\", donor_uids).fetchall()\n merged_num: dict = {}\n for d in donor_rows:\n di = json.loads(d[\"images\"] or \"[]\")\n if len(di) > max(kimgs, len(json.loads(best_imgs or \"[]\"))):\n best_imgs = d[\"images\"]\n dd = d[\"description\"] or \"\"\n if len(dd) > max(kdesc, 80, len(best_desc or \"\")):\n best_desc = dd\n for f in _MERGE_NUM_FIELDS:\n if keep[f] is None and merged_num.get(f) is None and d[f] is not None:\n merged_num[f] = d[f]\n # GPS : toujours la PAIRE du même donneur (jamais lat et lng mélangés)\n if (keep[\"lat\"] is None and \"lat\" not in merged_num\n and d[\"lat\"] is not None and d[\"lng\"] is not None):\n merged_num[\"lat\"], merged_num[\"lng\"] = d[\"lat\"], d[\"lng\"]\n if not keep[\"broker_phone\"] and d[\"broker_phone\"] and \"broker_phone\" not in merged_num:\n merged_num[\"broker_phone\"] = d[\"broker_phone\"]\n if best_imgs is not None:\n sets.append(\"images=?\"); args.append(best_imgs)\n if best_desc is not None and kdesc < 80:\n sets.append(\"description=?\"); args.append(best_desc)\n for f, v in merged_num.items():\n sets.append(f\"{f}=?\"); args.append(v)\n if sets:\n args.append(keep_uid)\n con.execute(f\"UPDATE listings SET {', '.join(sets)} WHERE uid=?\", args)\n\n\ndef connect() -> sqlite3.Connection:\n global _SCHEMA_READY\n DB_PATH.parent.mkdir(parents=True, exist_ok=True)\n con = sqlite3.connect(DB_PATH, timeout=60)\n con.row_factory = sqlite3.Row\n # WAL + busy_timeout : accès concurrents (watcher + web) sans « db is locked ».\n con.execute(\"PRAGMA journal_mode=WAL\")\n # 120 s : couvre les longues transactions (refresh_dedup ~70 s) sans que les\n # autres écrivains (géocodage, vraiprix) ne lèvent « database is locked ».\n con.execute(\"PRAGMA busy_timeout=120000\")\n con.execute(\"PRAGMA synchronous=NORMAL\")\n if not _SCHEMA_READY:\n _init_schema(con)\n _SCHEMA_READY = True\n return con\n\n\n# ---------------------------------------------------------------------------\n# Synchronisation d'une source\n# ---------------------------------------------------------------------------\n\ndef _drift_alert(con: sqlite3.Connection, source: str, found: int,\n null_price_rate: float) -> str | None:\n \"\"\"Détecte une dérive du connecteur (chute du volume ou des prix extraits).\"\"\"\n hist = con.execute(\n \"SELECT found, stats FROM sync_log WHERE source=? AND ok=1\"\n \" ORDER BY ts DESC LIMIT ?\", (source, DRIFT_HISTORY)).fetchall()\n if len(hist) < 3:\n return None\n med_found = statistics.median(r[\"found\"] for r in hist)\n if med_found >= DRIFT_MIN_BASE and found <= DRIFT_RATIO * med_found:\n return (f\"dérive: {found} propriété(s) trouvée(s) contre une médiane de \"\n f\"{med_found:.0f} — retraits suspendus, vérifier le connecteur\")\n if found >= DRIFT_MIN_BASE and null_price_rate >= 0.8:\n rates = []\n for r in hist:\n try:\n rates.append(json.loads(r[\"stats\"] or \"{}\")[\"null_price_rate\"])\n except (KeyError, ValueError, TypeError):\n continue\n if rates and statistics.median(rates) <= 0.3:\n return (f\"dérive: {null_price_rate:.0%} des propriétés sans prix \"\n f\"(habituellement {statistics.median(rates):.0%}) — \"\n \"le format de la source a probablement changé\")\n return None\n\n\ndef sync_source(con: sqlite3.Connection, source: str,\n listings: list[PropertyListing]) -> dict:\n \"\"\"Synchronise les propriétés d'une source.\n\n - nouvelle propriété -> insertion\n - propriété modifiée -> mise à jour (comparaison de content_hash)\n - propriété disparue -> miss_count += 1, puis active=0 après MISS_GRACE\n exécutions consécutives (vendue ou retirée)\n - dérive détectée -> alerte consignée, retraits suspendus\n \"\"\"\n now = time.time()\n added = updated = 0\n seen_uids = set()\n\n n = len(listings)\n null_price = sum(1 for l in listings if l.price is None)\n null_addr = sum(1 for l in listings if not l.address)\n null_price_rate = round(null_price / n, 3) if n else 0.0\n\n alert = _drift_alert(con, source, n, null_price_rate)\n\n for lst in listings:\n seen_uids.add(lst.uid)\n h = lst.content_hash()\n row = con.execute(\"SELECT content_hash, price FROM listings WHERE uid=?\",\n (lst.uid,)).fetchone()\n params = dict(\n uid=lst.uid, source=lst.source, external_id=lst.external_id,\n url=lst.url, title=lst.title, address=lst.address,\n sector=lst.sector, city=lst.city, region=lst.region,\n property_type=lst.property_type, price=lst.price,\n price_label=lst.price_label, bedrooms=lst.bedrooms,\n bathrooms=lst.bathrooms, powder_rooms=lst.powder_rooms,\n area_sqft=lst.area_sqft, lot_sqft=lst.lot_sqft,\n year_built=lst.year_built, mls=lst.mls, status=lst.status,\n broker_name=lst.broker_name, broker_phone=lst.broker_phone,\n agency=lst.agency,\n description=lst.description,\n features=json.dumps(lst.features, ensure_ascii=False),\n details=json.dumps(lst.details, ensure_ascii=False),\n images=json.dumps(lst.images, ensure_ascii=False),\n lat=lst.lat, lng=lst.lng, content_hash=h, now=now,\n )\n if row is None:\n con.execute(\n \"\"\"INSERT INTO listings (uid, source, external_id, url, title,\n address, sector, city, region, property_type, price,\n price_label, bedrooms, bathrooms, powder_rooms, area_sqft,\n lot_sqft, year_built, mls, status, broker_name, broker_phone,\n agency, description, features, details, images, lat, lng,\n content_hash, first_seen, last_seen, updated_at,\n miss_count, active)\n VALUES (:uid,:source,:external_id,:url,:title,:address,\n :sector,:city,:region,:property_type,:price,:price_label,\n :bedrooms,:bathrooms,:powder_rooms,:area_sqft,:lot_sqft,\n :year_built,:mls,:status,:broker_name,:broker_phone,\n :agency,:description,:features,:details,:images,:lat,:lng,\n :content_hash,:now,:now,:now,0,1)\"\"\", params)\n if lst.price is not None:\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n added += 1\n elif row[\"content_hash\"] != h:\n # COALESCE : ne jamais écraser par null des coordonnées géocodées ni\n # les année/superficies remplies par enrichissement (rôle d'évaluation,\n # fiche détail) quand la source liste ne les fournit pas\n con.execute(\n \"\"\"UPDATE listings SET url=:url, title=:title,\n address=:address, sector=:sector, city=:city, region=:region,\n property_type=:property_type, price=:price,\n price_label=:price_label, bedrooms=:bedrooms,\n bathrooms=:bathrooms, powder_rooms=:powder_rooms,\n area_sqft=COALESCE(:area_sqft, area_sqft),\n lot_sqft=COALESCE(:lot_sqft, lot_sqft),\n year_built=COALESCE(:year_built, year_built),\n mls=:mls, status=:status,\n broker_name=:broker_name, broker_phone=:broker_phone,\n agency=:agency, description=:description, features=:features,\n details=:details, images=:images,\n lat=COALESCE(:lat, lat), lng=COALESCE(:lng, lng),\n content_hash=:content_hash, last_seen=:now,\n updated_at=:now, miss_count=0, active=1\n WHERE uid=:uid\"\"\", params)\n if lst.price != row[\"price\"]: # baisse/hausse de prix -> historique\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n updated += 1\n else:\n con.execute(\n \"UPDATE listings SET last_seen=?, miss_count=0, active=1 WHERE uid=?\",\n (now, lst.uid))\n\n # Propriétés de cette source qui n'apparaissent plus : délai de grâce,\n # puis désactivation (vendue/retirée). Suspendu si dérive détectée.\n removed = missed = 0\n if not alert:\n for r in con.execute(\n \"SELECT uid, miss_count FROM listings WHERE source=? AND active=1\",\n (source,)).fetchall():\n if r[\"uid\"] in seen_uids:\n continue\n missed += 1\n if r[\"miss_count\"] + 1 >= MISS_GRACE:\n con.execute(\n \"UPDATE listings SET active=0, miss_count=?, updated_at=?\"\n \" WHERE uid=?\", (r[\"miss_count\"] + 1, now, r[\"uid\"]))\n removed += 1\n else:\n con.execute(\"UPDATE listings SET miss_count=miss_count+1 WHERE uid=?\",\n (r[\"uid\"],))\n\n stats = {\n \"null_price_rate\": null_price_rate,\n \"null_address_rate\": round(null_addr / n, 3) if n else 0.0,\n \"missed\": missed,\n }\n if alert:\n stats[\"alert\"] = alert\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok,\"\n \" message, stats) VALUES (?,?,?,?,?,?,1,?,?)\",\n (source, now, n, added, updated, removed, alert or \"ok\",\n json.dumps(stats, ensure_ascii=False)))\n con.commit()\n out = {\"source\": source, \"found\": n, \"added\": added,\n \"updated\": updated, \"removed\": removed}\n if alert:\n out[\"alert\"] = alert\n return out\n\n\ndef log_failure(con: sqlite3.Connection, source: str, message: str) -> None:\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok, message)\"\n \" VALUES (?,?,0,0,0,0,0,?)\", (source, time.time(), message))\n con.commit()\n\n\n# ---------------------------------------------------------------------------\n# Cache des pages détail (« détail si nouveau/modifié »)\n# ---------------------------------------------------------------------------\n\ndef get_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str) -> dict | None:\n \"\"\"Payload détail mis en cache si la clé (hash liste) n'a pas changé.\"\"\"\n row = con.execute(\n \"SELECT key, payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"key\"] == key and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef get_stale_detail(con: sqlite3.Connection, source: str,\n external_id: str) -> dict | None:\n \"\"\"Payload détail SANS vérifier la clé — repli « périmé plutôt que rien »\n quand le budget de re-fetch d'un cycle est épuisé (ex. bump de version de\n clé) : la fiche garde photos/détails existants en attendant son re-parse.\"\"\"\n row = con.execute(\n \"SELECT payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef put_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str, payload: dict) -> None:\n con.execute(\n \"INSERT INTO detail_cache (source, external_id, key, payload, fetched_at)\"\n \" VALUES (?,?,?,?,?)\"\n \" ON CONFLICT(source, external_id) DO UPDATE SET\"\n \" key=excluded.key, payload=excluded.payload, fetched_at=excluded.fetched_at\",\n (source, external_id, key, json.dumps(payload, ensure_ascii=False),\n time.time()))\n con.commit()\n","structuredPatch":[{"oldStart":164,"oldLines":17,"newStart":164,"newLines":24,"lines":[" Retourne le nombre total de fiches masquées.\"\"\""," AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\""," NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"","- con.execute(\"UPDATE listings SET dup_hidden=0\")","+ con.execute(\"UPDATE listings SET dup_hidden=0, dup_of=NULL\")"," # 1) masquer les sous-agences dont le n° Centris est porté par une fiche"," # canonique (non sous-agence) active — semi-jointure, rapide.","+ # dup_of = la fiche canonique (pour la box « Aussi publiée sur… »)."," con.execute(","- f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG}\"","+ f\"UPDATE listings SET dup_hidden=1,\"","+ f\" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"","+ f\" AND d.external_id=listings.external_id AND d.{NOTAG})\"","+ f\" WHERE active=1 AND {AG}\""," f\" AND external_id IN (SELECT external_id FROM listings\""," f\" WHERE active=1 AND {NOTAG})\")"," # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus"," # petit uid par n° Centris."," con.execute(","- f\"UPDATE listings SET dup_hidden=1 WHERE active=1 AND {AG} AND dup_hidden=0\"","+ f\"UPDATE listings SET dup_hidden=1,\"","+ f\" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"","+ f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\"","+ f\" WHERE active=1 AND {AG} AND dup_hidden=0\""," f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\""," f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")"," # 3) dédup INTER-SOURCES par adresse : la même propriété publiée sur deux"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"9d2ba82d-6f37-49a4-9fe6-8b2d3a10435f","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbyLMqTFTAPGjATBpbr","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1149,"cache_read_input_tokens":58938,"cache_creation":{"ephemeral_5m_input_tokens":1149,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"11697680-77ae-4ec4-b992-0890819cb7fe"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbyLMqTFTAPGjATBpbr","type":"message","role":"assistant","content":[{"type":"text","text":"Maintenant la priorité courtier : `fb_marketplace` rejoint les petites annonces, et à rang égal une fiche avec courtier bat une fiche anonyme."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1149,"cache_read_input_tokens":58938,"cache_creation":{"ephemeral_5m_input_tokens":1149,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"69a8ab41-ffe2-4e82-be56-12790d6ff344"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbyLMqTFTAPGjATBpbr","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Au6k2w3Ud6UZcz5Usovti3","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","old_string":"# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main)\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\"}","new_string":"# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main).\n# fb_marketplace : fiches anonymes/republication — jamais préférées à un courtier.\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\", \"fb_marketplace\"}"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1149,"cache_read_input_tokens":58938,"cache_creation":{"ephemeral_5m_input_tokens":1149,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"5be86633-e595-4866-b13d-9f3397b31f8d"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Au6k2w3Ud6UZcz5Usovti3","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/db.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"f711ed9a-b7b6-499d-8ae3-ae144059f701","timestamp":"2026-08-25T14:12:49.294Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","oldString":"# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main)\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\"}","newString":"# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main).\n# fb_marketplace : fiches anonymes/republication — jamais préférées à un courtier.\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\", \"fb_marketplace\"}","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# db.py : persistance SQLite — upsert avec détection de changements,\n# cycle de vie avec délai de grâce (2 syncs), détection de dérive,\n# historique de prix, cache des pages détail.\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport sqlite3\nimport statistics\nimport time\nfrom pathlib import Path\n\nfrom .schema import PropertyListing\n\nDB_PATH = Path(__file__).resolve().parent.parent / \"data\" / \"immoka.db\"\n\n# Nombre d'exécutions consécutives où une propriété doit être absente de la\n# source avant d'être désactivée (délai de grâce contre les ratés ponctuels).\nMISS_GRACE = 2\n\n# Dérive : si une source retourne <= DRIFT_RATIO × sa médiane historique\n# (médiane >= DRIFT_MIN_BASE annonces), on alerte et on suspend les retraits.\nDRIFT_RATIO = 0.25\nDRIFT_MIN_BASE = 8\nDRIFT_HISTORY = 5\n\n_SCHEMA = \"\"\"\nCREATE TABLE IF NOT EXISTS listings (\n uid TEXT PRIMARY KEY,\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n url TEXT,\n title TEXT,\n address TEXT,\n sector TEXT,\n city TEXT,\n region TEXT,\n property_type TEXT,\n price REAL,\n price_label TEXT,\n bedrooms INTEGER,\n bathrooms INTEGER,\n powder_rooms INTEGER,\n area_sqft REAL,\n lot_sqft REAL,\n year_built INTEGER,\n mls TEXT,\n status TEXT DEFAULT 'a-vendre',\n broker_name TEXT,\n broker_phone TEXT,\n agency TEXT,\n description TEXT,\n features TEXT, -- JSON (liste de textes source)\n details TEXT, -- JSON (champs structurés)\n images TEXT, -- JSON\n lat REAL,\n lng REAL,\n geocode_failed INTEGER DEFAULT 0,\n content_hash TEXT,\n first_seen REAL,\n last_seen REAL,\n updated_at REAL,\n miss_count INTEGER DEFAULT 0,\n active INTEGER DEFAULT 1,\n dup_hidden INTEGER DEFAULT 0 -- 1 = doublon de sous-agence masqué (dédup Centris)\n);\nCREATE INDEX IF NOT EXISTS idx_listings_source ON listings(source);\nCREATE INDEX IF NOT EXISTS idx_listings_city ON listings(city);\nCREATE INDEX IF NOT EXISTS idx_listings_type ON listings(property_type);\nCREATE INDEX IF NOT EXISTS idx_listings_active ON listings(active);\nCREATE INDEX IF NOT EXISTS idx_listings_extid ON listings(external_id);\n\nCREATE TABLE IF NOT EXISTS sync_log (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n source TEXT,\n ts REAL,\n found INTEGER,\n added INTEGER,\n updated INTEGER,\n removed INTEGER,\n ok INTEGER,\n message TEXT,\n stats TEXT -- JSON : taux de champs null, missed, alerte…\n);\n\nCREATE TABLE IF NOT EXISTS detail_cache (\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n key TEXT, -- hash du contenu « liste » de l'annonce\n payload TEXT, -- JSON opaque propre au connecteur\n fetched_at REAL,\n PRIMARY KEY (source, external_id)\n);\n\nCREATE TABLE IF NOT EXISTS price_log (\n uid TEXT NOT NULL,\n ts REAL NOT NULL,\n price REAL -- prix observé (baisses/hausses de prix demandé)\n);\nCREATE INDEX IF NOT EXISTS idx_price_log_uid ON price_log(uid);\n\nCREATE TABLE IF NOT EXISTS geocode_cache (\n address TEXT PRIMARY KEY,\n lat REAL,\n lng REAL,\n provider TEXT,\n failed INTEGER DEFAULT 0,\n ts REAL,\n muni TEXT -- municipalité officielle (clés « ville:… »)\n);\n\nCREATE TABLE IF NOT EXISTS poi_cache (\n coord_key TEXT PRIMARY KEY, -- \"lat,lng\" arrondi à 4 décimales (~11 m)\n lat REAL,\n lng REAL,\n pois TEXT, -- JSON : [{cat, name, dist_m}] (plus proche/catégorie)\n ts REAL\n);\n\"\"\"\n\n\n_SCHEMA_READY = False # le schéma/migration ne s'exécute qu'UNE fois par process\n\n\ndef _init_schema(con: sqlite3.Connection) -> None:\n \"\"\"Création de schéma + migration — coûteuse (write-lock). À faire une seule\n fois par process : l'exécuter à chaque connexion sérialisait les requêtes du\n web sur un verrou d'écriture (deadlock/starvation sous charge).\"\"\"\n con.executescript(_SCHEMA)\n cols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(listings)\")}\n if \"agency\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN agency TEXT\")\n if \"dup_hidden\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n if \"dup_of\" not in cols: # uid de la fiche visible au profit de laquelle\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_of TEXT\") # celle-ci est masquée\n if \"dauid\" not in cols: # aire de diffusion 2021 (stats de quartier)\n con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")\n if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n gcols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(geocode_cache)\")}\n if \"muni\" not in gcols: # municipalité officielle (entrées « ville:… »)\n con.execute(\"ALTER TABLE geocode_cache ADD COLUMN muni TEXT\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_dupof ON listings(dup_of)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n con.commit()\n\n\ndef refresh_dedup(con: sqlite3.Connection) -> int:\n \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n\n Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée\n si une fiche de plus haute priorité — même n° Centris (external_id), active —\n existe : le flux central/agence principale d'abord, sinon la sous-agence au\n plus petit uid. Les fiches non sous-agence ne sont jamais masquées par\n cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).\n Retourne le nombre total de fiches masquées.\"\"\"\n AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n con.execute(\"UPDATE listings SET dup_hidden=0, dup_of=NULL\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n # dup_of = la fiche canonique (pour la box « Aussi publiée sur… »).\n con.execute(\n f\"UPDATE listings SET dup_hidden=1,\"\n f\" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{NOTAG})\"\n f\" WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1,\"\n f\" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\"\n f\" WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")\n # 3) dédup INTER-SOURCES par adresse : la même propriété publiée sur deux\n # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle\n # conservatrice : même adresse normalisée (civique + rue + ville) + même\n # type + prix identique à ±1 % → on garde la fiche la plus autoritaire.\n try:\n n_addr = dedup_by_address(con)\n if n_addr:\n print(f\"[immo-ka] dédup adresse: {n_addr} doublon(s) inter-sources masqué(s)\")\n except Exception:\n import traceback\n traceback.print_exc()\n n = con.execute(\"SELECT COUNT(*) c FROM listings WHERE dup_hidden=1\").fetchone()[\"c\"]\n con.commit()\n return n\n\n\n# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main)\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\"}\n\n\ndef _source_rank(source: str) -> int:\n \"\"\"Autorité d'une source pour la dédup d'adresse :\n 0 = source primaire (bannière/agence/FSBO), 1 = sous-agence (_ag_),\n 2 = petites annonces (republication probable).\"\"\"\n if source in _PETITES_ANNONCES:\n return 2\n if \"_ag_\" in source:\n return 1\n return 0\n\n\ndef dedup_by_address(con: sqlite3.Connection) -> int:\n \"\"\"Passe de déduplication conservatrice par ADRESSE (inter-sources).\n\n Clé : n° civique(s) + mots significatifs de la rue + ville normalisée +\n type canonique + n° d'app/unité (vide s'il n'y en a pas — deux unités\n différentes d'un même immeuble ne partagent JAMAIS la même clé, et une\n adresse sans unité ne s'apparie pas à une adresse avec unité). Dans une\n clé, seules les fiches au prix identique à ±1 % sont considérées comme\n doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis le plus petit uid. Retourne le nb masqué.\"\"\"\n import re as _re\n from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE\n groups: dict[tuple, list] = {}\n for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):\n civs, words = _addr_parts(r[\"address\"])\n if not civs or not words:\n continue\n a = _norm(r[\"address\"]).split(\",\")[0]\n mapt = _re.search(_APP_RE, a)\n apt = \"\"\n if mapt:\n toks = _re.findall(r\"[a-z0-9]+\", mapt.group(0))\n # dernier token = le n° d'unité (le 1er est le mot-clé app/unité/#)\n apt = toks[-1] if toks else \"\"\n key = (\"-\".join(civs), \" \".join(sorted(set(words))),\n _muni_norm(r[\"city\"]), _norm(r[\"property_type\"]), apt)\n groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))\n hidden = 0\n for rows in groups.values():\n if len(rows) < 2:\n continue\n rows.sort() # par prix croissant\n cluster: list = []\n for row in rows:\n if cluster and row[0] > cluster[0][0] * 1.01:\n hidden += _mask_cluster(con, cluster)\n cluster = []\n cluster.append(row)\n hidden += _mask_cluster(con, cluster)\n return hidden\n\n\ndef _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:\n \"\"\"Masque les doublons d'un groupe (même clé d'adresse, prix ±1 %), puis\n FUSIONNE en « golden record » : les champs vides de la fiche conservée sont\n complétés depuis les doublons masqués (description plus longue, galerie plus\n riche, superficies, année, GPS, téléphone) — le meilleur des deux sources.\"\"\"\n if len(cluster) < 2:\n return 0\n sources = [c[3] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[2] != keep[2]:\n con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n donors.append(c[2])\n n += 1\n try:\n _merge_golden(con, keep[2], donors)\n except Exception:\n pass # la fusion est un bonus — ne jamais casser la dédup\n return n\n\n\n_MERGE_NUM_FIELDS = (\"bedrooms\", \"bathrooms\", \"powder_rooms\", \"area_sqft\",\n \"lot_sqft\", \"year_built\")\n\n\ndef _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:\n \"\"\"Complète les champs vides de `keep_uid` depuis ses doublons masqués.\"\"\"\n if not donor_uids:\n return\n cols = (\"uid, description, images, bedrooms, bathrooms, powder_rooms,\"\n \" area_sqft, lot_sqft, year_built, lat, lng, broker_phone\")\n keep = con.execute(f\"SELECT {cols} FROM listings WHERE uid=?\",\n (keep_uid,)).fetchone()\n if keep is None:\n return\n sets, args = [], []\n kimgs = len(json.loads(keep[\"images\"] or \"[]\"))\n kdesc = len(keep[\"description\"] or \"\")\n best_imgs, best_desc = None, None\n donor_rows = con.execute(\n f\"SELECT {cols} FROM listings WHERE uid IN \"\n f\"({','.join('?' * len(donor_uids))})\", donor_uids).fetchall()\n merged_num: dict = {}\n for d in donor_rows:\n di = json.loads(d[\"images\"] or \"[]\")\n if len(di) > max(kimgs, len(json.loads(best_imgs or \"[]\"))):\n best_imgs = d[\"images\"]\n dd = d[\"description\"] or \"\"\n if len(dd) > max(kdesc, 80, len(best_desc or \"\")):\n best_desc = dd\n for f in _MERGE_NUM_FIELDS:\n if keep[f] is None and merged_num.get(f) is None and d[f] is not None:\n merged_num[f] = d[f]\n # GPS : toujours la PAIRE du même donneur (jamais lat et lng mélangés)\n if (keep[\"lat\"] is None and \"lat\" not in merged_num\n and d[\"lat\"] is not None and d[\"lng\"] is not None):\n merged_num[\"lat\"], merged_num[\"lng\"] = d[\"lat\"], d[\"lng\"]\n if not keep[\"broker_phone\"] and d[\"broker_phone\"] and \"broker_phone\" not in merged_num:\n merged_num[\"broker_phone\"] = d[\"broker_phone\"]\n if best_imgs is not None:\n sets.append(\"images=?\"); args.append(best_imgs)\n if best_desc is not None and kdesc < 80:\n sets.append(\"description=?\"); args.append(best_desc)\n for f, v in merged_num.items():\n sets.append(f\"{f}=?\"); args.append(v)\n if sets:\n args.append(keep_uid)\n con.execute(f\"UPDATE listings SET {', '.join(sets)} WHERE uid=?\", args)\n\n\ndef connect() -> sqlite3.Connection:\n global _SCHEMA_READY\n DB_PATH.parent.mkdir(parents=True, exist_ok=True)\n con = sqlite3.connect(DB_PATH, timeout=60)\n con.row_factory = sqlite3.Row\n # WAL + busy_timeout : accès concurrents (watcher + web) sans « db is locked ».\n con.execute(\"PRAGMA journal_mode=WAL\")\n # 120 s : couvre les longues transactions (refresh_dedup ~70 s) sans que les\n # autres écrivains (géocodage, vraiprix) ne lèvent « database is locked ».\n con.execute(\"PRAGMA busy_timeout=120000\")\n con.execute(\"PRAGMA synchronous=NORMAL\")\n if not _SCHEMA_READY:\n _init_schema(con)\n _SCHEMA_READY = True\n return con\n\n\n# ---------------------------------------------------------------------------\n# Synchronisation d'une source\n# ---------------------------------------------------------------------------\n\ndef _drift_alert(con: sqlite3.Connection, source: str, found: int,\n null_price_rate: float) -> str | None:\n \"\"\"Détecte une dérive du connecteur (chute du volume ou des prix extraits).\"\"\"\n hist = con.execute(\n \"SELECT found, stats FROM sync_log WHERE source=? AND ok=1\"\n \" ORDER BY ts DESC LIMIT ?\", (source, DRIFT_HISTORY)).fetchall()\n if len(hist) < 3:\n return None\n med_found = statistics.median(r[\"found\"] for r in hist)\n if med_found >= DRIFT_MIN_BASE and found <= DRIFT_RATIO * med_found:\n return (f\"dérive: {found} propriété(s) trouvée(s) contre une médiane de \"\n f\"{med_found:.0f} — retraits suspendus, vérifier le connecteur\")\n if found >= DRIFT_MIN_BASE and null_price_rate >= 0.8:\n rates = []\n for r in hist:\n try:\n rates.append(json.loads(r[\"stats\"] or \"{}\")[\"null_price_rate\"])\n except (KeyError, ValueError, TypeError):\n continue\n if rates and statistics.median(rates) <= 0.3:\n return (f\"dérive: {null_price_rate:.0%} des propriétés sans prix \"\n f\"(habituellement {statistics.median(rates):.0%}) — \"\n \"le format de la source a probablement changé\")\n return None\n\n\ndef sync_source(con: sqlite3.Connection, source: str,\n listings: list[PropertyListing]) -> dict:\n \"\"\"Synchronise les propriétés d'une source.\n\n - nouvelle propriété -> insertion\n - propriété modifiée -> mise à jour (comparaison de content_hash)\n - propriété disparue -> miss_count += 1, puis active=0 après MISS_GRACE\n exécutions consécutives (vendue ou retirée)\n - dérive détectée -> alerte consignée, retraits suspendus\n \"\"\"\n now = time.time()\n added = updated = 0\n seen_uids = set()\n\n n = len(listings)\n null_price = sum(1 for l in listings if l.price is None)\n null_addr = sum(1 for l in listings if not l.address)\n null_price_rate = round(null_price / n, 3) if n else 0.0\n\n alert = _drift_alert(con, source, n, null_price_rate)\n\n for lst in listings:\n seen_uids.add(lst.uid)\n h = lst.content_hash()\n row = con.execute(\"SELECT content_hash, price FROM listings WHERE uid=?\",\n (lst.uid,)).fetchone()\n params = dict(\n uid=lst.uid, source=lst.source, external_id=lst.external_id,\n url=lst.url, title=lst.title, address=lst.address,\n sector=lst.sector, city=lst.city, region=lst.region,\n property_type=lst.property_type, price=lst.price,\n price_label=lst.price_label, bedrooms=lst.bedrooms,\n bathrooms=lst.bathrooms, powder_rooms=lst.powder_rooms,\n area_sqft=lst.area_sqft, lot_sqft=lst.lot_sqft,\n year_built=lst.year_built, mls=lst.mls, status=lst.status,\n broker_name=lst.broker_name, broker_phone=lst.broker_phone,\n agency=lst.agency,\n description=lst.description,\n features=json.dumps(lst.features, ensure_ascii=False),\n details=json.dumps(lst.details, ensure_ascii=False),\n images=json.dumps(lst.images, ensure_ascii=False),\n lat=lst.lat, lng=lst.lng, content_hash=h, now=now,\n )\n if row is None:\n con.execute(\n \"\"\"INSERT INTO listings (uid, source, external_id, url, title,\n address, sector, city, region, property_type, price,\n price_label, bedrooms, bathrooms, powder_rooms, area_sqft,\n lot_sqft, year_built, mls, status, broker_name, broker_phone,\n agency, description, features, details, images, lat, lng,\n content_hash, first_seen, last_seen, updated_at,\n miss_count, active)\n VALUES (:uid,:source,:external_id,:url,:title,:address,\n :sector,:city,:region,:property_type,:price,:price_label,\n :bedrooms,:bathrooms,:powder_rooms,:area_sqft,:lot_sqft,\n :year_built,:mls,:status,:broker_name,:broker_phone,\n :agency,:description,:features,:details,:images,:lat,:lng,\n :content_hash,:now,:now,:now,0,1)\"\"\", params)\n if lst.price is not None:\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n added += 1\n elif row[\"content_hash\"] != h:\n # COALESCE : ne jamais écraser par null des coordonnées géocodées ni\n # les année/superficies remplies par enrichissement (rôle d'évaluation,\n # fiche détail) quand la source liste ne les fournit pas\n con.execute(\n \"\"\"UPDATE listings SET url=:url, title=:title,\n address=:address, sector=:sector, city=:city, region=:region,\n property_type=:property_type, price=:price,\n price_label=:price_label, bedrooms=:bedrooms,\n bathrooms=:bathrooms, powder_rooms=:powder_rooms,\n area_sqft=COALESCE(:area_sqft, area_sqft),\n lot_sqft=COALESCE(:lot_sqft, lot_sqft),\n year_built=COALESCE(:year_built, year_built),\n mls=:mls, status=:status,\n broker_name=:broker_name, broker_phone=:broker_phone,\n agency=:agency, description=:description, features=:features,\n details=:details, images=:images,\n lat=COALESCE(:lat, lat), lng=COALESCE(:lng, lng),\n content_hash=:content_hash, last_seen=:now,\n updated_at=:now, miss_count=0, active=1\n WHERE uid=:uid\"\"\", params)\n if lst.price != row[\"price\"]: # baisse/hausse de prix -> historique\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n updated += 1\n else:\n con.execute(\n \"UPDATE listings SET last_seen=?, miss_count=0, active=1 WHERE uid=?\",\n (now, lst.uid))\n\n # Propriétés de cette source qui n'apparaissent plus : délai de grâce,\n # puis désactivation (vendue/retirée). Suspendu si dérive détectée.\n removed = missed = 0\n if not alert:\n for r in con.execute(\n \"SELECT uid, miss_count FROM listings WHERE source=? AND active=1\",\n (source,)).fetchall():\n if r[\"uid\"] in seen_uids:\n continue\n missed += 1\n if r[\"miss_count\"] + 1 >= MISS_GRACE:\n con.execute(\n \"UPDATE listings SET active=0, miss_count=?, updated_at=?\"\n \" WHERE uid=?\", (r[\"miss_count\"] + 1, now, r[\"uid\"]))\n removed += 1\n else:\n con.execute(\"UPDATE listings SET miss_count=miss_count+1 WHERE uid=?\",\n (r[\"uid\"],))\n\n stats = {\n \"null_price_rate\": null_price_rate,\n \"null_address_rate\": round(null_addr / n, 3) if n else 0.0,\n \"missed\": missed,\n }\n if alert:\n stats[\"alert\"] = alert\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok,\"\n \" message, stats) VALUES (?,?,?,?,?,?,1,?,?)\",\n (source, now, n, added, updated, removed, alert or \"ok\",\n json.dumps(stats, ensure_ascii=False)))\n con.commit()\n out = {\"source\": source, \"found\": n, \"added\": added,\n \"updated\": updated, \"removed\": removed}\n if alert:\n out[\"alert\"] = alert\n return out\n\n\ndef log_failure(con: sqlite3.Connection, source: str, message: str) -> None:\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok, message)\"\n \" VALUES (?,?,0,0,0,0,0,?)\", (source, time.time(), message))\n con.commit()\n\n\n# ---------------------------------------------------------------------------\n# Cache des pages détail (« détail si nouveau/modifié »)\n# ---------------------------------------------------------------------------\n\ndef get_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str) -> dict | None:\n \"\"\"Payload détail mis en cache si la clé (hash liste) n'a pas changé.\"\"\"\n row = con.execute(\n \"SELECT key, payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"key\"] == key and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef get_stale_detail(con: sqlite3.Connection, source: str,\n external_id: str) -> dict | None:\n \"\"\"Payload détail SANS vérifier la clé — repli « périmé plutôt que rien »\n quand le budget de re-fetch d'un cycle est épuisé (ex. bump de version de\n clé) : la fiche garde photos/détails existants en attendant son re-parse.\"\"\"\n row = con.execute(\n \"SELECT payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef put_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str, payload: dict) -> None:\n con.execute(\n \"INSERT INTO detail_cache (source, external_id, key, payload, fetched_at)\"\n \" VALUES (?,?,?,?,?)\"\n \" ON CONFLICT(source, external_id) DO UPDATE SET\"\n \" key=excluded.key, payload=excluded.payload, fetched_at=excluded.fetched_at\",\n (source, external_id, key, json.dumps(payload, ensure_ascii=False),\n time.time()))\n con.commit()\n","structuredPatch":[{"oldStart":201,"oldLines":8,"newStart":201,"newLines":9,"lines":[" "," "," # petites annonces généralistes (republication d'annonces d'ailleurs) : moins","-# autoritaires que la source primaire (courtier / FSBO première main)","-_PETITES_ANNONCES = {\"kijiji\", \"lespac\"}","+# autoritaires que la source primaire (courtier / FSBO première main).","+# fb_marketplace : fiches anonymes/republication — jamais préférées à un courtier.","+_PETITES_ANNONCES = {\"kijiji\", \"lespac\", \"fb_marketplace\"}"," "," "," def _source_rank(source: str) -> int:"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"c925c7b0-b9a2-4c22-af72-3ab09a949f07","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbzBcFszxEn2yZLbj4h","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01LYhvrZg9zeBxFaNRkfZueX","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","old_string":" doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis le plus petit uid. Retourne le nb masqué.\"\"\"","new_string":" doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis à autorité égale celle qui a un COURTIER/agence\n (jamais une fiche anonyme devant un courtier), puis le plus petit uid.\n Retourne le nb masqué.\"\"\""},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":929,"cache_read_input_tokens":60087,"cache_creation":{"ephemeral_5m_input_tokens":929,"ephemeral_1h_input_tokens":0},"output_tokens":20,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"b3f0f934-40c3-4547-8871-a4e29e71740f"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01LYhvrZg9zeBxFaNRkfZueX","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/db.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"531d2cf6-fd29-47c2-83b7-95c511b9df1b","timestamp":"2026-08-25T14:12:57.554Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","oldString":" doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis le plus petit uid. Retourne le nb masqué.\"\"\"","newString":" doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis à autorité égale celle qui a un COURTIER/agence\n (jamais une fiche anonyme devant un courtier), puis le plus petit uid.\n Retourne le nb masqué.\"\"\"","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# db.py : persistance SQLite — upsert avec détection de changements,\n# cycle de vie avec délai de grâce (2 syncs), détection de dérive,\n# historique de prix, cache des pages détail.\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport sqlite3\nimport statistics\nimport time\nfrom pathlib import Path\n\nfrom .schema import PropertyListing\n\nDB_PATH = Path(__file__).resolve().parent.parent / \"data\" / \"immoka.db\"\n\n# Nombre d'exécutions consécutives où une propriété doit être absente de la\n# source avant d'être désactivée (délai de grâce contre les ratés ponctuels).\nMISS_GRACE = 2\n\n# Dérive : si une source retourne <= DRIFT_RATIO × sa médiane historique\n# (médiane >= DRIFT_MIN_BASE annonces), on alerte et on suspend les retraits.\nDRIFT_RATIO = 0.25\nDRIFT_MIN_BASE = 8\nDRIFT_HISTORY = 5\n\n_SCHEMA = \"\"\"\nCREATE TABLE IF NOT EXISTS listings (\n uid TEXT PRIMARY KEY,\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n url TEXT,\n title TEXT,\n address TEXT,\n sector TEXT,\n city TEXT,\n region TEXT,\n property_type TEXT,\n price REAL,\n price_label TEXT,\n bedrooms INTEGER,\n bathrooms INTEGER,\n powder_rooms INTEGER,\n area_sqft REAL,\n lot_sqft REAL,\n year_built INTEGER,\n mls TEXT,\n status TEXT DEFAULT 'a-vendre',\n broker_name TEXT,\n broker_phone TEXT,\n agency TEXT,\n description TEXT,\n features TEXT, -- JSON (liste de textes source)\n details TEXT, -- JSON (champs structurés)\n images TEXT, -- JSON\n lat REAL,\n lng REAL,\n geocode_failed INTEGER DEFAULT 0,\n content_hash TEXT,\n first_seen REAL,\n last_seen REAL,\n updated_at REAL,\n miss_count INTEGER DEFAULT 0,\n active INTEGER DEFAULT 1,\n dup_hidden INTEGER DEFAULT 0 -- 1 = doublon de sous-agence masqué (dédup Centris)\n);\nCREATE INDEX IF NOT EXISTS idx_listings_source ON listings(source);\nCREATE INDEX IF NOT EXISTS idx_listings_city ON listings(city);\nCREATE INDEX IF NOT EXISTS idx_listings_type ON listings(property_type);\nCREATE INDEX IF NOT EXISTS idx_listings_active ON listings(active);\nCREATE INDEX IF NOT EXISTS idx_listings_extid ON listings(external_id);\n\nCREATE TABLE IF NOT EXISTS sync_log (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n source TEXT,\n ts REAL,\n found INTEGER,\n added INTEGER,\n updated INTEGER,\n removed INTEGER,\n ok INTEGER,\n message TEXT,\n stats TEXT -- JSON : taux de champs null, missed, alerte…\n);\n\nCREATE TABLE IF NOT EXISTS detail_cache (\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n key TEXT, -- hash du contenu « liste » de l'annonce\n payload TEXT, -- JSON opaque propre au connecteur\n fetched_at REAL,\n PRIMARY KEY (source, external_id)\n);\n\nCREATE TABLE IF NOT EXISTS price_log (\n uid TEXT NOT NULL,\n ts REAL NOT NULL,\n price REAL -- prix observé (baisses/hausses de prix demandé)\n);\nCREATE INDEX IF NOT EXISTS idx_price_log_uid ON price_log(uid);\n\nCREATE TABLE IF NOT EXISTS geocode_cache (\n address TEXT PRIMARY KEY,\n lat REAL,\n lng REAL,\n provider TEXT,\n failed INTEGER DEFAULT 0,\n ts REAL,\n muni TEXT -- municipalité officielle (clés « ville:… »)\n);\n\nCREATE TABLE IF NOT EXISTS poi_cache (\n coord_key TEXT PRIMARY KEY, -- \"lat,lng\" arrondi à 4 décimales (~11 m)\n lat REAL,\n lng REAL,\n pois TEXT, -- JSON : [{cat, name, dist_m}] (plus proche/catégorie)\n ts REAL\n);\n\"\"\"\n\n\n_SCHEMA_READY = False # le schéma/migration ne s'exécute qu'UNE fois par process\n\n\ndef _init_schema(con: sqlite3.Connection) -> None:\n \"\"\"Création de schéma + migration — coûteuse (write-lock). À faire une seule\n fois par process : l'exécuter à chaque connexion sérialisait les requêtes du\n web sur un verrou d'écriture (deadlock/starvation sous charge).\"\"\"\n con.executescript(_SCHEMA)\n cols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(listings)\")}\n if \"agency\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN agency TEXT\")\n if \"dup_hidden\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n if \"dup_of\" not in cols: # uid de la fiche visible au profit de laquelle\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_of TEXT\") # celle-ci est masquée\n if \"dauid\" not in cols: # aire de diffusion 2021 (stats de quartier)\n con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")\n if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n gcols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(geocode_cache)\")}\n if \"muni\" not in gcols: # municipalité officielle (entrées « ville:… »)\n con.execute(\"ALTER TABLE geocode_cache ADD COLUMN muni TEXT\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_dupof ON listings(dup_of)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n con.commit()\n\n\ndef refresh_dedup(con: sqlite3.Connection) -> int:\n \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n\n Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée\n si une fiche de plus haute priorité — même n° Centris (external_id), active —\n existe : le flux central/agence principale d'abord, sinon la sous-agence au\n plus petit uid. Les fiches non sous-agence ne sont jamais masquées par\n cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).\n Retourne le nombre total de fiches masquées.\"\"\"\n AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n con.execute(\"UPDATE listings SET dup_hidden=0, dup_of=NULL\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n # dup_of = la fiche canonique (pour la box « Aussi publiée sur… »).\n con.execute(\n f\"UPDATE listings SET dup_hidden=1,\"\n f\" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{NOTAG})\"\n f\" WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1,\"\n f\" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\"\n f\" WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")\n # 3) dédup INTER-SOURCES par adresse : la même propriété publiée sur deux\n # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle\n # conservatrice : même adresse normalisée (civique + rue + ville) + même\n # type + prix identique à ±1 % → on garde la fiche la plus autoritaire.\n try:\n n_addr = dedup_by_address(con)\n if n_addr:\n print(f\"[immo-ka] dédup adresse: {n_addr} doublon(s) inter-sources masqué(s)\")\n except Exception:\n import traceback\n traceback.print_exc()\n n = con.execute(\"SELECT COUNT(*) c FROM listings WHERE dup_hidden=1\").fetchone()[\"c\"]\n con.commit()\n return n\n\n\n# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main).\n# fb_marketplace : fiches anonymes/republication — jamais préférées à un courtier.\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\", \"fb_marketplace\"}\n\n\ndef _source_rank(source: str) -> int:\n \"\"\"Autorité d'une source pour la dédup d'adresse :\n 0 = source primaire (bannière/agence/FSBO), 1 = sous-agence (_ag_),\n 2 = petites annonces (republication probable).\"\"\"\n if source in _PETITES_ANNONCES:\n return 2\n if \"_ag_\" in source:\n return 1\n return 0\n\n\ndef dedup_by_address(con: sqlite3.Connection) -> int:\n \"\"\"Passe de déduplication conservatrice par ADRESSE (inter-sources).\n\n Clé : n° civique(s) + mots significatifs de la rue + ville normalisée +\n type canonique + n° d'app/unité (vide s'il n'y en a pas — deux unités\n différentes d'un même immeuble ne partagent JAMAIS la même clé, et une\n adresse sans unité ne s'apparie pas à une adresse avec unité). Dans une\n clé, seules les fiches au prix identique à ±1 % sont considérées comme\n doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis le plus petit uid. Retourne le nb masqué.\"\"\"\n import re as _re\n from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE\n groups: dict[tuple, list] = {}\n for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):\n civs, words = _addr_parts(r[\"address\"])\n if not civs or not words:\n continue\n a = _norm(r[\"address\"]).split(\",\")[0]\n mapt = _re.search(_APP_RE, a)\n apt = \"\"\n if mapt:\n toks = _re.findall(r\"[a-z0-9]+\", mapt.group(0))\n # dernier token = le n° d'unité (le 1er est le mot-clé app/unité/#)\n apt = toks[-1] if toks else \"\"\n key = (\"-\".join(civs), \" \".join(sorted(set(words))),\n _muni_norm(r[\"city\"]), _norm(r[\"property_type\"]), apt)\n groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))\n hidden = 0\n for rows in groups.values():\n if len(rows) < 2:\n continue\n rows.sort() # par prix croissant\n cluster: list = []\n for row in rows:\n if cluster and row[0] > cluster[0][0] * 1.01:\n hidden += _mask_cluster(con, cluster)\n cluster = []\n cluster.append(row)\n hidden += _mask_cluster(con, cluster)\n return hidden\n\n\ndef _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:\n \"\"\"Masque les doublons d'un groupe (même clé d'adresse, prix ±1 %), puis\n FUSIONNE en « golden record » : les champs vides de la fiche conservée sont\n complétés depuis les doublons masqués (description plus longue, galerie plus\n riche, superficies, année, GPS, téléphone) — le meilleur des deux sources.\"\"\"\n if len(cluster) < 2:\n return 0\n sources = [c[3] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[2] != keep[2]:\n con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n donors.append(c[2])\n n += 1\n try:\n _merge_golden(con, keep[2], donors)\n except Exception:\n pass # la fusion est un bonus — ne jamais casser la dédup\n return n\n\n\n_MERGE_NUM_FIELDS = (\"bedrooms\", \"bathrooms\", \"powder_rooms\", \"area_sqft\",\n \"lot_sqft\", \"year_built\")\n\n\ndef _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:\n \"\"\"Complète les champs vides de `keep_uid` depuis ses doublons masqués.\"\"\"\n if not donor_uids:\n return\n cols = (\"uid, description, images, bedrooms, bathrooms, powder_rooms,\"\n \" area_sqft, lot_sqft, year_built, lat, lng, broker_phone\")\n keep = con.execute(f\"SELECT {cols} FROM listings WHERE uid=?\",\n (keep_uid,)).fetchone()\n if keep is None:\n return\n sets, args = [], []\n kimgs = len(json.loads(keep[\"images\"] or \"[]\"))\n kdesc = len(keep[\"description\"] or \"\")\n best_imgs, best_desc = None, None\n donor_rows = con.execute(\n f\"SELECT {cols} FROM listings WHERE uid IN \"\n f\"({','.join('?' * len(donor_uids))})\", donor_uids).fetchall()\n merged_num: dict = {}\n for d in donor_rows:\n di = json.loads(d[\"images\"] or \"[]\")\n if len(di) > max(kimgs, len(json.loads(best_imgs or \"[]\"))):\n best_imgs = d[\"images\"]\n dd = d[\"description\"] or \"\"\n if len(dd) > max(kdesc, 80, len(best_desc or \"\")):\n best_desc = dd\n for f in _MERGE_NUM_FIELDS:\n if keep[f] is None and merged_num.get(f) is None and d[f] is not None:\n merged_num[f] = d[f]\n # GPS : toujours la PAIRE du même donneur (jamais lat et lng mélangés)\n if (keep[\"lat\"] is None and \"lat\" not in merged_num\n and d[\"lat\"] is not None and d[\"lng\"] is not None):\n merged_num[\"lat\"], merged_num[\"lng\"] = d[\"lat\"], d[\"lng\"]\n if not keep[\"broker_phone\"] and d[\"broker_phone\"] and \"broker_phone\" not in merged_num:\n merged_num[\"broker_phone\"] = d[\"broker_phone\"]\n if best_imgs is not None:\n sets.append(\"images=?\"); args.append(best_imgs)\n if best_desc is not None and kdesc < 80:\n sets.append(\"description=?\"); args.append(best_desc)\n for f, v in merged_num.items():\n sets.append(f\"{f}=?\"); args.append(v)\n if sets:\n args.append(keep_uid)\n con.execute(f\"UPDATE listings SET {', '.join(sets)} WHERE uid=?\", args)\n\n\ndef connect() -> sqlite3.Connection:\n global _SCHEMA_READY\n DB_PATH.parent.mkdir(parents=True, exist_ok=True)\n con = sqlite3.connect(DB_PATH, timeout=60)\n con.row_factory = sqlite3.Row\n # WAL + busy_timeout : accès concurrents (watcher + web) sans « db is locked ».\n con.execute(\"PRAGMA journal_mode=WAL\")\n # 120 s : couvre les longues transactions (refresh_dedup ~70 s) sans que les\n # autres écrivains (géocodage, vraiprix) ne lèvent « database is locked ».\n con.execute(\"PRAGMA busy_timeout=120000\")\n con.execute(\"PRAGMA synchronous=NORMAL\")\n if not _SCHEMA_READY:\n _init_schema(con)\n _SCHEMA_READY = True\n return con\n\n\n# ---------------------------------------------------------------------------\n# Synchronisation d'une source\n# ---------------------------------------------------------------------------\n\ndef _drift_alert(con: sqlite3.Connection, source: str, found: int,\n null_price_rate: float) -> str | None:\n \"\"\"Détecte une dérive du connecteur (chute du volume ou des prix extraits).\"\"\"\n hist = con.execute(\n \"SELECT found, stats FROM sync_log WHERE source=? AND ok=1\"\n \" ORDER BY ts DESC LIMIT ?\", (source, DRIFT_HISTORY)).fetchall()\n if len(hist) < 3:\n return None\n med_found = statistics.median(r[\"found\"] for r in hist)\n if med_found >= DRIFT_MIN_BASE and found <= DRIFT_RATIO * med_found:\n return (f\"dérive: {found} propriété(s) trouvée(s) contre une médiane de \"\n f\"{med_found:.0f} — retraits suspendus, vérifier le connecteur\")\n if found >= DRIFT_MIN_BASE and null_price_rate >= 0.8:\n rates = []\n for r in hist:\n try:\n rates.append(json.loads(r[\"stats\"] or \"{}\")[\"null_price_rate\"])\n except (KeyError, ValueError, TypeError):\n continue\n if rates and statistics.median(rates) <= 0.3:\n return (f\"dérive: {null_price_rate:.0%} des propriétés sans prix \"\n f\"(habituellement {statistics.median(rates):.0%}) — \"\n \"le format de la source a probablement changé\")\n return None\n\n\ndef sync_source(con: sqlite3.Connection, source: str,\n listings: list[PropertyListing]) -> dict:\n \"\"\"Synchronise les propriétés d'une source.\n\n - nouvelle propriété -> insertion\n - propriété modifiée -> mise à jour (comparaison de content_hash)\n - propriété disparue -> miss_count += 1, puis active=0 après MISS_GRACE\n exécutions consécutives (vendue ou retirée)\n - dérive détectée -> alerte consignée, retraits suspendus\n \"\"\"\n now = time.time()\n added = updated = 0\n seen_uids = set()\n\n n = len(listings)\n null_price = sum(1 for l in listings if l.price is None)\n null_addr = sum(1 for l in listings if not l.address)\n null_price_rate = round(null_price / n, 3) if n else 0.0\n\n alert = _drift_alert(con, source, n, null_price_rate)\n\n for lst in listings:\n seen_uids.add(lst.uid)\n h = lst.content_hash()\n row = con.execute(\"SELECT content_hash, price FROM listings WHERE uid=?\",\n (lst.uid,)).fetchone()\n params = dict(\n uid=lst.uid, source=lst.source, external_id=lst.external_id,\n url=lst.url, title=lst.title, address=lst.address,\n sector=lst.sector, city=lst.city, region=lst.region,\n property_type=lst.property_type, price=lst.price,\n price_label=lst.price_label, bedrooms=lst.bedrooms,\n bathrooms=lst.bathrooms, powder_rooms=lst.powder_rooms,\n area_sqft=lst.area_sqft, lot_sqft=lst.lot_sqft,\n year_built=lst.year_built, mls=lst.mls, status=lst.status,\n broker_name=lst.broker_name, broker_phone=lst.broker_phone,\n agency=lst.agency,\n description=lst.description,\n features=json.dumps(lst.features, ensure_ascii=False),\n details=json.dumps(lst.details, ensure_ascii=False),\n images=json.dumps(lst.images, ensure_ascii=False),\n lat=lst.lat, lng=lst.lng, content_hash=h, now=now,\n )\n if row is None:\n con.execute(\n \"\"\"INSERT INTO listings (uid, source, external_id, url, title,\n address, sector, city, region, property_type, price,\n price_label, bedrooms, bathrooms, powder_rooms, area_sqft,\n lot_sqft, year_built, mls, status, broker_name, broker_phone,\n agency, description, features, details, images, lat, lng,\n content_hash, first_seen, last_seen, updated_at,\n miss_count, active)\n VALUES (:uid,:source,:external_id,:url,:title,:address,\n :sector,:city,:region,:property_type,:price,:price_label,\n :bedrooms,:bathrooms,:powder_rooms,:area_sqft,:lot_sqft,\n :year_built,:mls,:status,:broker_name,:broker_phone,\n :agency,:description,:features,:details,:images,:lat,:lng,\n :content_hash,:now,:now,:now,0,1)\"\"\", params)\n if lst.price is not None:\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n added += 1\n elif row[\"content_hash\"] != h:\n # COALESCE : ne jamais écraser par null des coordonnées géocodées ni\n # les année/superficies remplies par enrichissement (rôle d'évaluation,\n # fiche détail) quand la source liste ne les fournit pas\n con.execute(\n \"\"\"UPDATE listings SET url=:url, title=:title,\n address=:address, sector=:sector, city=:city, region=:region,\n property_type=:property_type, price=:price,\n price_label=:price_label, bedrooms=:bedrooms,\n bathrooms=:bathrooms, powder_rooms=:powder_rooms,\n area_sqft=COALESCE(:area_sqft, area_sqft),\n lot_sqft=COALESCE(:lot_sqft, lot_sqft),\n year_built=COALESCE(:year_built, year_built),\n mls=:mls, status=:status,\n broker_name=:broker_name, broker_phone=:broker_phone,\n agency=:agency, description=:description, features=:features,\n details=:details, images=:images,\n lat=COALESCE(:lat, lat), lng=COALESCE(:lng, lng),\n content_hash=:content_hash, last_seen=:now,\n updated_at=:now, miss_count=0, active=1\n WHERE uid=:uid\"\"\", params)\n if lst.price != row[\"price\"]: # baisse/hausse de prix -> historique\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n updated += 1\n else:\n con.execute(\n \"UPDATE listings SET last_seen=?, miss_count=0, active=1 WHERE uid=?\",\n (now, lst.uid))\n\n # Propriétés de cette source qui n'apparaissent plus : délai de grâce,\n # puis désactivation (vendue/retirée). Suspendu si dérive détectée.\n removed = missed = 0\n if not alert:\n for r in con.execute(\n \"SELECT uid, miss_count FROM listings WHERE source=? AND active=1\",\n (source,)).fetchall():\n if r[\"uid\"] in seen_uids:\n continue\n missed += 1\n if r[\"miss_count\"] + 1 >= MISS_GRACE:\n con.execute(\n \"UPDATE listings SET active=0, miss_count=?, updated_at=?\"\n \" WHERE uid=?\", (r[\"miss_count\"] + 1, now, r[\"uid\"]))\n removed += 1\n else:\n con.execute(\"UPDATE listings SET miss_count=miss_count+1 WHERE uid=?\",\n (r[\"uid\"],))\n\n stats = {\n \"null_price_rate\": null_price_rate,\n \"null_address_rate\": round(null_addr / n, 3) if n else 0.0,\n \"missed\": missed,\n }\n if alert:\n stats[\"alert\"] = alert\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok,\"\n \" message, stats) VALUES (?,?,?,?,?,?,1,?,?)\",\n (source, now, n, added, updated, removed, alert or \"ok\",\n json.dumps(stats, ensure_ascii=False)))\n con.commit()\n out = {\"source\": source, \"found\": n, \"added\": added,\n \"updated\": updated, \"removed\": removed}\n if alert:\n out[\"alert\"] = alert\n return out\n\n\ndef log_failure(con: sqlite3.Connection, source: str, message: str) -> None:\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok, message)\"\n \" VALUES (?,?,0,0,0,0,0,?)\", (source, time.time(), message))\n con.commit()\n\n\n# ---------------------------------------------------------------------------\n# Cache des pages détail (« détail si nouveau/modifié »)\n# ---------------------------------------------------------------------------\n\ndef get_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str) -> dict | None:\n \"\"\"Payload détail mis en cache si la clé (hash liste) n'a pas changé.\"\"\"\n row = con.execute(\n \"SELECT key, payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"key\"] == key and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef get_stale_detail(con: sqlite3.Connection, source: str,\n external_id: str) -> dict | None:\n \"\"\"Payload détail SANS vérifier la clé — repli « périmé plutôt que rien »\n quand le budget de re-fetch d'un cycle est épuisé (ex. bump de version de\n clé) : la fiche garde photos/détails existants en attendant son re-parse.\"\"\"\n row = con.execute(\n \"SELECT payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef put_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str, payload: dict) -> None:\n con.execute(\n \"INSERT INTO detail_cache (source, external_id, key, payload, fetched_at)\"\n \" VALUES (?,?,?,?,?)\"\n \" ON CONFLICT(source, external_id) DO UPDATE SET\"\n \" key=excluded.key, payload=excluded.payload, fetched_at=excluded.fetched_at\",\n (source, external_id, key, json.dumps(payload, ensure_ascii=False),\n time.time()))\n con.commit()\n","structuredPatch":[{"oldStart":228,"oldLines":7,"newStart":228,"newLines":9,"lines":[" doublons ; si une même source apparaît deux fois dans le groupe (probables"," unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde"," la fiche la plus autoritaire (source primaire > sous-agence _ag_ >","- petites annonces), puis le plus petit uid. Retourne le nb masqué.\"\"\"","+ petites annonces), puis à autorité égale celle qui a un COURTIER/agence","+ (jamais une fiche anonyme devant un courtier), puis le plus petit uid.","+ Retourne le nb masqué.\"\"\""," import re as _re"," from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE"," groups: dict[tuple, list] = {}"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"41939dca-23da-433a-bac6-f0ca34e50d0d","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePbznTznqHtgqWMCbkmq","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01VZMduboNRuCaAEC5Jq4RAy","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","old_string":" for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):","new_string":" for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type,\"\n \" broker_name, agency\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":482,"cache_read_input_tokens":61016,"cache_creation":{"ephemeral_5m_input_tokens":482,"ephemeral_1h_input_tokens":0},"output_tokens":15,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"86da47cf-4a2c-435d-8800-a1f5a13cba6d"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01VZMduboNRuCaAEC5Jq4RAy","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/db.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"7f43a3c1-885d-4021-8ef3-cefc0c392b88","timestamp":"2026-08-25T14:13:04.205Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","oldString":" for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):","newString":" for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type,\"\n \" broker_name, agency\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# db.py : persistance SQLite — upsert avec détection de changements,\n# cycle de vie avec délai de grâce (2 syncs), détection de dérive,\n# historique de prix, cache des pages détail.\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport sqlite3\nimport statistics\nimport time\nfrom pathlib import Path\n\nfrom .schema import PropertyListing\n\nDB_PATH = Path(__file__).resolve().parent.parent / \"data\" / \"immoka.db\"\n\n# Nombre d'exécutions consécutives où une propriété doit être absente de la\n# source avant d'être désactivée (délai de grâce contre les ratés ponctuels).\nMISS_GRACE = 2\n\n# Dérive : si une source retourne <= DRIFT_RATIO × sa médiane historique\n# (médiane >= DRIFT_MIN_BASE annonces), on alerte et on suspend les retraits.\nDRIFT_RATIO = 0.25\nDRIFT_MIN_BASE = 8\nDRIFT_HISTORY = 5\n\n_SCHEMA = \"\"\"\nCREATE TABLE IF NOT EXISTS listings (\n uid TEXT PRIMARY KEY,\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n url TEXT,\n title TEXT,\n address TEXT,\n sector TEXT,\n city TEXT,\n region TEXT,\n property_type TEXT,\n price REAL,\n price_label TEXT,\n bedrooms INTEGER,\n bathrooms INTEGER,\n powder_rooms INTEGER,\n area_sqft REAL,\n lot_sqft REAL,\n year_built INTEGER,\n mls TEXT,\n status TEXT DEFAULT 'a-vendre',\n broker_name TEXT,\n broker_phone TEXT,\n agency TEXT,\n description TEXT,\n features TEXT, -- JSON (liste de textes source)\n details TEXT, -- JSON (champs structurés)\n images TEXT, -- JSON\n lat REAL,\n lng REAL,\n geocode_failed INTEGER DEFAULT 0,\n content_hash TEXT,\n first_seen REAL,\n last_seen REAL,\n updated_at REAL,\n miss_count INTEGER DEFAULT 0,\n active INTEGER DEFAULT 1,\n dup_hidden INTEGER DEFAULT 0 -- 1 = doublon de sous-agence masqué (dédup Centris)\n);\nCREATE INDEX IF NOT EXISTS idx_listings_source ON listings(source);\nCREATE INDEX IF NOT EXISTS idx_listings_city ON listings(city);\nCREATE INDEX IF NOT EXISTS idx_listings_type ON listings(property_type);\nCREATE INDEX IF NOT EXISTS idx_listings_active ON listings(active);\nCREATE INDEX IF NOT EXISTS idx_listings_extid ON listings(external_id);\n\nCREATE TABLE IF NOT EXISTS sync_log (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n source TEXT,\n ts REAL,\n found INTEGER,\n added INTEGER,\n updated INTEGER,\n removed INTEGER,\n ok INTEGER,\n message TEXT,\n stats TEXT -- JSON : taux de champs null, missed, alerte…\n);\n\nCREATE TABLE IF NOT EXISTS detail_cache (\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n key TEXT, -- hash du contenu « liste » de l'annonce\n payload TEXT, -- JSON opaque propre au connecteur\n fetched_at REAL,\n PRIMARY KEY (source, external_id)\n);\n\nCREATE TABLE IF NOT EXISTS price_log (\n uid TEXT NOT NULL,\n ts REAL NOT NULL,\n price REAL -- prix observé (baisses/hausses de prix demandé)\n);\nCREATE INDEX IF NOT EXISTS idx_price_log_uid ON price_log(uid);\n\nCREATE TABLE IF NOT EXISTS geocode_cache (\n address TEXT PRIMARY KEY,\n lat REAL,\n lng REAL,\n provider TEXT,\n failed INTEGER DEFAULT 0,\n ts REAL,\n muni TEXT -- municipalité officielle (clés « ville:… »)\n);\n\nCREATE TABLE IF NOT EXISTS poi_cache (\n coord_key TEXT PRIMARY KEY, -- \"lat,lng\" arrondi à 4 décimales (~11 m)\n lat REAL,\n lng REAL,\n pois TEXT, -- JSON : [{cat, name, dist_m}] (plus proche/catégorie)\n ts REAL\n);\n\"\"\"\n\n\n_SCHEMA_READY = False # le schéma/migration ne s'exécute qu'UNE fois par process\n\n\ndef _init_schema(con: sqlite3.Connection) -> None:\n \"\"\"Création de schéma + migration — coûteuse (write-lock). À faire une seule\n fois par process : l'exécuter à chaque connexion sérialisait les requêtes du\n web sur un verrou d'écriture (deadlock/starvation sous charge).\"\"\"\n con.executescript(_SCHEMA)\n cols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(listings)\")}\n if \"agency\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN agency TEXT\")\n if \"dup_hidden\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n if \"dup_of\" not in cols: # uid de la fiche visible au profit de laquelle\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_of TEXT\") # celle-ci est masquée\n if \"dauid\" not in cols: # aire de diffusion 2021 (stats de quartier)\n con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")\n if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n gcols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(geocode_cache)\")}\n if \"muni\" not in gcols: # municipalité officielle (entrées « ville:… »)\n con.execute(\"ALTER TABLE geocode_cache ADD COLUMN muni TEXT\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_dupof ON listings(dup_of)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n con.commit()\n\n\ndef refresh_dedup(con: sqlite3.Connection) -> int:\n \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n\n Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée\n si une fiche de plus haute priorité — même n° Centris (external_id), active —\n existe : le flux central/agence principale d'abord, sinon la sous-agence au\n plus petit uid. Les fiches non sous-agence ne sont jamais masquées par\n cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).\n Retourne le nombre total de fiches masquées.\"\"\"\n AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n con.execute(\"UPDATE listings SET dup_hidden=0, dup_of=NULL\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n # dup_of = la fiche canonique (pour la box « Aussi publiée sur… »).\n con.execute(\n f\"UPDATE listings SET dup_hidden=1,\"\n f\" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{NOTAG})\"\n f\" WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1,\"\n f\" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\"\n f\" WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")\n # 3) dédup INTER-SOURCES par adresse : la même propriété publiée sur deux\n # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle\n # conservatrice : même adresse normalisée (civique + rue + ville) + même\n # type + prix identique à ±1 % → on garde la fiche la plus autoritaire.\n try:\n n_addr = dedup_by_address(con)\n if n_addr:\n print(f\"[immo-ka] dédup adresse: {n_addr} doublon(s) inter-sources masqué(s)\")\n except Exception:\n import traceback\n traceback.print_exc()\n n = con.execute(\"SELECT COUNT(*) c FROM listings WHERE dup_hidden=1\").fetchone()[\"c\"]\n con.commit()\n return n\n\n\n# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main).\n# fb_marketplace : fiches anonymes/republication — jamais préférées à un courtier.\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\", \"fb_marketplace\"}\n\n\ndef _source_rank(source: str) -> int:\n \"\"\"Autorité d'une source pour la dédup d'adresse :\n 0 = source primaire (bannière/agence/FSBO), 1 = sous-agence (_ag_),\n 2 = petites annonces (republication probable).\"\"\"\n if source in _PETITES_ANNONCES:\n return 2\n if \"_ag_\" in source:\n return 1\n return 0\n\n\ndef dedup_by_address(con: sqlite3.Connection) -> int:\n \"\"\"Passe de déduplication conservatrice par ADRESSE (inter-sources).\n\n Clé : n° civique(s) + mots significatifs de la rue + ville normalisée +\n type canonique + n° d'app/unité (vide s'il n'y en a pas — deux unités\n différentes d'un même immeuble ne partagent JAMAIS la même clé, et une\n adresse sans unité ne s'apparie pas à une adresse avec unité). Dans une\n clé, seules les fiches au prix identique à ±1 % sont considérées comme\n doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis à autorité égale celle qui a un COURTIER/agence\n (jamais une fiche anonyme devant un courtier), puis le plus petit uid.\n Retourne le nb masqué.\"\"\"\n import re as _re\n from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE\n groups: dict[tuple, list] = {}\n for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):\n civs, words = _addr_parts(r[\"address\"])\n if not civs or not words:\n continue\n a = _norm(r[\"address\"]).split(\",\")[0]\n mapt = _re.search(_APP_RE, a)\n apt = \"\"\n if mapt:\n toks = _re.findall(r\"[a-z0-9]+\", mapt.group(0))\n # dernier token = le n° d'unité (le 1er est le mot-clé app/unité/#)\n apt = toks[-1] if toks else \"\"\n key = (\"-\".join(civs), \" \".join(sorted(set(words))),\n _muni_norm(r[\"city\"]), _norm(r[\"property_type\"]), apt)\n groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))\n hidden = 0\n for rows in groups.values():\n if len(rows) < 2:\n continue\n rows.sort() # par prix croissant\n cluster: list = []\n for row in rows:\n if cluster and row[0] > cluster[0][0] * 1.01:\n hidden += _mask_cluster(con, cluster)\n cluster = []\n cluster.append(row)\n hidden += _mask_cluster(con, cluster)\n return hidden\n\n\ndef _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:\n \"\"\"Masque les doublons d'un groupe (même clé d'adresse, prix ±1 %), puis\n FUSIONNE en « golden record » : les champs vides de la fiche conservée sont\n complétés depuis les doublons masqués (description plus longue, galerie plus\n riche, superficies, année, GPS, téléphone) — le meilleur des deux sources.\"\"\"\n if len(cluster) < 2:\n return 0\n sources = [c[3] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[2] != keep[2]:\n con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n donors.append(c[2])\n n += 1\n try:\n _merge_golden(con, keep[2], donors)\n except Exception:\n pass # la fusion est un bonus — ne jamais casser la dédup\n return n\n\n\n_MERGE_NUM_FIELDS = (\"bedrooms\", \"bathrooms\", \"powder_rooms\", \"area_sqft\",\n \"lot_sqft\", \"year_built\")\n\n\ndef _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:\n \"\"\"Complète les champs vides de `keep_uid` depuis ses doublons masqués.\"\"\"\n if not donor_uids:\n return\n cols = (\"uid, description, images, bedrooms, bathrooms, powder_rooms,\"\n \" area_sqft, lot_sqft, year_built, lat, lng, broker_phone\")\n keep = con.execute(f\"SELECT {cols} FROM listings WHERE uid=?\",\n (keep_uid,)).fetchone()\n if keep is None:\n return\n sets, args = [], []\n kimgs = len(json.loads(keep[\"images\"] or \"[]\"))\n kdesc = len(keep[\"description\"] or \"\")\n best_imgs, best_desc = None, None\n donor_rows = con.execute(\n f\"SELECT {cols} FROM listings WHERE uid IN \"\n f\"({','.join('?' * len(donor_uids))})\", donor_uids).fetchall()\n merged_num: dict = {}\n for d in donor_rows:\n di = json.loads(d[\"images\"] or \"[]\")\n if len(di) > max(kimgs, len(json.loads(best_imgs or \"[]\"))):\n best_imgs = d[\"images\"]\n dd = d[\"description\"] or \"\"\n if len(dd) > max(kdesc, 80, len(best_desc or \"\")):\n best_desc = dd\n for f in _MERGE_NUM_FIELDS:\n if keep[f] is None and merged_num.get(f) is None and d[f] is not None:\n merged_num[f] = d[f]\n # GPS : toujours la PAIRE du même donneur (jamais lat et lng mélangés)\n if (keep[\"lat\"] is None and \"lat\" not in merged_num\n and d[\"lat\"] is not None and d[\"lng\"] is not None):\n merged_num[\"lat\"], merged_num[\"lng\"] = d[\"lat\"], d[\"lng\"]\n if not keep[\"broker_phone\"] and d[\"broker_phone\"] and \"broker_phone\" not in merged_num:\n merged_num[\"broker_phone\"] = d[\"broker_phone\"]\n if best_imgs is not None:\n sets.append(\"images=?\"); args.append(best_imgs)\n if best_desc is not None and kdesc < 80:\n sets.append(\"description=?\"); args.append(best_desc)\n for f, v in merged_num.items():\n sets.append(f\"{f}=?\"); args.append(v)\n if sets:\n args.append(keep_uid)\n con.execute(f\"UPDATE listings SET {', '.join(sets)} WHERE uid=?\", args)\n\n\ndef connect() -> sqlite3.Connection:\n global _SCHEMA_READY\n DB_PATH.parent.mkdir(parents=True, exist_ok=True)\n con = sqlite3.connect(DB_PATH, timeout=60)\n con.row_factory = sqlite3.Row\n # WAL + busy_timeout : accès concurrents (watcher + web) sans « db is locked ».\n con.execute(\"PRAGMA journal_mode=WAL\")\n # 120 s : couvre les longues transactions (refresh_dedup ~70 s) sans que les\n # autres écrivains (géocodage, vraiprix) ne lèvent « database is locked ».\n con.execute(\"PRAGMA busy_timeout=120000\")\n con.execute(\"PRAGMA synchronous=NORMAL\")\n if not _SCHEMA_READY:\n _init_schema(con)\n _SCHEMA_READY = True\n return con\n\n\n# ---------------------------------------------------------------------------\n# Synchronisation d'une source\n# ---------------------------------------------------------------------------\n\ndef _drift_alert(con: sqlite3.Connection, source: str, found: int,\n null_price_rate: float) -> str | None:\n \"\"\"Détecte une dérive du connecteur (chute du volume ou des prix extraits).\"\"\"\n hist = con.execute(\n \"SELECT found, stats FROM sync_log WHERE source=? AND ok=1\"\n \" ORDER BY ts DESC LIMIT ?\", (source, DRIFT_HISTORY)).fetchall()\n if len(hist) < 3:\n return None\n med_found = statistics.median(r[\"found\"] for r in hist)\n if med_found >= DRIFT_MIN_BASE and found <= DRIFT_RATIO * med_found:\n return (f\"dérive: {found} propriété(s) trouvée(s) contre une médiane de \"\n f\"{med_found:.0f} — retraits suspendus, vérifier le connecteur\")\n if found >= DRIFT_MIN_BASE and null_price_rate >= 0.8:\n rates = []\n for r in hist:\n try:\n rates.append(json.loads(r[\"stats\"] or \"{}\")[\"null_price_rate\"])\n except (KeyError, ValueError, TypeError):\n continue\n if rates and statistics.median(rates) <= 0.3:\n return (f\"dérive: {null_price_rate:.0%} des propriétés sans prix \"\n f\"(habituellement {statistics.median(rates):.0%}) — \"\n \"le format de la source a probablement changé\")\n return None\n\n\ndef sync_source(con: sqlite3.Connection, source: str,\n listings: list[PropertyListing]) -> dict:\n \"\"\"Synchronise les propriétés d'une source.\n\n - nouvelle propriété -> insertion\n - propriété modifiée -> mise à jour (comparaison de content_hash)\n - propriété disparue -> miss_count += 1, puis active=0 après MISS_GRACE\n exécutions consécutives (vendue ou retirée)\n - dérive détectée -> alerte consignée, retraits suspendus\n \"\"\"\n now = time.time()\n added = updated = 0\n seen_uids = set()\n\n n = len(listings)\n null_price = sum(1 for l in listings if l.price is None)\n null_addr = sum(1 for l in listings if not l.address)\n null_price_rate = round(null_price / n, 3) if n else 0.0\n\n alert = _drift_alert(con, source, n, null_price_rate)\n\n for lst in listings:\n seen_uids.add(lst.uid)\n h = lst.content_hash()\n row = con.execute(\"SELECT content_hash, price FROM listings WHERE uid=?\",\n (lst.uid,)).fetchone()\n params = dict(\n uid=lst.uid, source=lst.source, external_id=lst.external_id,\n url=lst.url, title=lst.title, address=lst.address,\n sector=lst.sector, city=lst.city, region=lst.region,\n property_type=lst.property_type, price=lst.price,\n price_label=lst.price_label, bedrooms=lst.bedrooms,\n bathrooms=lst.bathrooms, powder_rooms=lst.powder_rooms,\n area_sqft=lst.area_sqft, lot_sqft=lst.lot_sqft,\n year_built=lst.year_built, mls=lst.mls, status=lst.status,\n broker_name=lst.broker_name, broker_phone=lst.broker_phone,\n agency=lst.agency,\n description=lst.description,\n features=json.dumps(lst.features, ensure_ascii=False),\n details=json.dumps(lst.details, ensure_ascii=False),\n images=json.dumps(lst.images, ensure_ascii=False),\n lat=lst.lat, lng=lst.lng, content_hash=h, now=now,\n )\n if row is None:\n con.execute(\n \"\"\"INSERT INTO listings (uid, source, external_id, url, title,\n address, sector, city, region, property_type, price,\n price_label, bedrooms, bathrooms, powder_rooms, area_sqft,\n lot_sqft, year_built, mls, status, broker_name, broker_phone,\n agency, description, features, details, images, lat, lng,\n content_hash, first_seen, last_seen, updated_at,\n miss_count, active)\n VALUES (:uid,:source,:external_id,:url,:title,:address,\n :sector,:city,:region,:property_type,:price,:price_label,\n :bedrooms,:bathrooms,:powder_rooms,:area_sqft,:lot_sqft,\n :year_built,:mls,:status,:broker_name,:broker_phone,\n :agency,:description,:features,:details,:images,:lat,:lng,\n :content_hash,:now,:now,:now,0,1)\"\"\", params)\n if lst.price is not None:\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n added += 1\n elif row[\"content_hash\"] != h:\n # COALESCE : ne jamais écraser par null des coordonnées géocodées ni\n # les année/superficies remplies par enrichissement (rôle d'évaluation,\n # fiche détail) quand la source liste ne les fournit pas\n con.execute(\n \"\"\"UPDATE listings SET url=:url, title=:title,\n address=:address, sector=:sector, city=:city, region=:region,\n property_type=:property_type, price=:price,\n price_label=:price_label, bedrooms=:bedrooms,\n bathrooms=:bathrooms, powder_rooms=:powder_rooms,\n area_sqft=COALESCE(:area_sqft, area_sqft),\n lot_sqft=COALESCE(:lot_sqft, lot_sqft),\n year_built=COALESCE(:year_built, year_built),\n mls=:mls, status=:status,\n broker_name=:broker_name, broker_phone=:broker_phone,\n agency=:agency, description=:description, features=:features,\n details=:details, images=:images,\n lat=COALESCE(:lat, lat), lng=COALESCE(:lng, lng),\n content_hash=:content_hash, last_seen=:now,\n updated_at=:now, miss_count=0, active=1\n WHERE uid=:uid\"\"\", params)\n if lst.price != row[\"price\"]: # baisse/hausse de prix -> historique\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n updated += 1\n else:\n con.execute(\n \"UPDATE listings SET last_seen=?, miss_count=0, active=1 WHERE uid=?\",\n (now, lst.uid))\n\n # Propriétés de cette source qui n'apparaissent plus : délai de grâce,\n # puis désactivation (vendue/retirée). Suspendu si dérive détectée.\n removed = missed = 0\n if not alert:\n for r in con.execute(\n \"SELECT uid, miss_count FROM listings WHERE source=? AND active=1\",\n (source,)).fetchall():\n if r[\"uid\"] in seen_uids:\n continue\n missed += 1\n if r[\"miss_count\"] + 1 >= MISS_GRACE:\n con.execute(\n \"UPDATE listings SET active=0, miss_count=?, updated_at=?\"\n \" WHERE uid=?\", (r[\"miss_count\"] + 1, now, r[\"uid\"]))\n removed += 1\n else:\n con.execute(\"UPDATE listings SET miss_count=miss_count+1 WHERE uid=?\",\n (r[\"uid\"],))\n\n stats = {\n \"null_price_rate\": null_price_rate,\n \"null_address_rate\": round(null_addr / n, 3) if n else 0.0,\n \"missed\": missed,\n }\n if alert:\n stats[\"alert\"] = alert\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok,\"\n \" message, stats) VALUES (?,?,?,?,?,?,1,?,?)\",\n (source, now, n, added, updated, removed, alert or \"ok\",\n json.dumps(stats, ensure_ascii=False)))\n con.commit()\n out = {\"source\": source, \"found\": n, \"added\": added,\n \"updated\": updated, \"removed\": removed}\n if alert:\n out[\"alert\"] = alert\n return out\n\n\ndef log_failure(con: sqlite3.Connection, source: str, message: str) -> None:\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok, message)\"\n \" VALUES (?,?,0,0,0,0,0,?)\", (source, time.time(), message))\n con.commit()\n\n\n# ---------------------------------------------------------------------------\n# Cache des pages détail (« détail si nouveau/modifié »)\n# ---------------------------------------------------------------------------\n\ndef get_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str) -> dict | None:\n \"\"\"Payload détail mis en cache si la clé (hash liste) n'a pas changé.\"\"\"\n row = con.execute(\n \"SELECT key, payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"key\"] == key and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef get_stale_detail(con: sqlite3.Connection, source: str,\n external_id: str) -> dict | None:\n \"\"\"Payload détail SANS vérifier la clé — repli « périmé plutôt que rien »\n quand le budget de re-fetch d'un cycle est épuisé (ex. bump de version de\n clé) : la fiche garde photos/détails existants en attendant son re-parse.\"\"\"\n row = con.execute(\n \"SELECT payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef put_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str, payload: dict) -> None:\n con.execute(\n \"INSERT INTO detail_cache (source, external_id, key, payload, fetched_at)\"\n \" VALUES (?,?,?,?,?)\"\n \" ON CONFLICT(source, external_id) DO UPDATE SET\"\n \" key=excluded.key, payload=excluded.payload, fetched_at=excluded.fetched_at\",\n (source, external_id, key, json.dumps(payload, ensure_ascii=False),\n time.time()))\n con.commit()\n","structuredPatch":[{"oldStart":235,"oldLines":7,"newStart":235,"newLines":8,"lines":[" from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE"," groups: dict[tuple, list] = {}"," for r in con.execute(","- \"SELECT uid, source, address, city, price, property_type\"","+ \"SELECT uid, source, address, city, price, property_type,\"","+ \" broker_name, agency\""," \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\""," \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):"," civs, words = _addr_parts(r[\"address\"])"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"69fbeaf3-9f84-4760-9d01-d0d6f288cc0c","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePc1HMKU2W7xchwAz8XM","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01BTFZteaWbiQbfjmBApVQRr","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","old_string":" groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))","new_string":" anonyme = 0 if (r[\"broker_name\"] or r[\"agency\"]) else 1\n groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), anonyme, r[\"uid\"], r[\"source\"]))"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":395,"cache_read_input_tokens":61498,"cache_creation":{"ephemeral_5m_input_tokens":395,"ephemeral_1h_input_tokens":0},"output_tokens":20,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"501418bb-3259-401d-8b09-0359d2bd873d"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01BTFZteaWbiQbfjmBApVQRr","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/db.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"361ae649-4a15-4813-bb26-8b2fe7f138ac","timestamp":"2026-08-25T14:13:12.194Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","oldString":" groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))","newString":" anonyme = 0 if (r[\"broker_name\"] or r[\"agency\"]) else 1\n groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), anonyme, r[\"uid\"], r[\"source\"]))","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# db.py : persistance SQLite — upsert avec détection de changements,\n# cycle de vie avec délai de grâce (2 syncs), détection de dérive,\n# historique de prix, cache des pages détail.\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport sqlite3\nimport statistics\nimport time\nfrom pathlib import Path\n\nfrom .schema import PropertyListing\n\nDB_PATH = Path(__file__).resolve().parent.parent / \"data\" / \"immoka.db\"\n\n# Nombre d'exécutions consécutives où une propriété doit être absente de la\n# source avant d'être désactivée (délai de grâce contre les ratés ponctuels).\nMISS_GRACE = 2\n\n# Dérive : si une source retourne <= DRIFT_RATIO × sa médiane historique\n# (médiane >= DRIFT_MIN_BASE annonces), on alerte et on suspend les retraits.\nDRIFT_RATIO = 0.25\nDRIFT_MIN_BASE = 8\nDRIFT_HISTORY = 5\n\n_SCHEMA = \"\"\"\nCREATE TABLE IF NOT EXISTS listings (\n uid TEXT PRIMARY KEY,\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n url TEXT,\n title TEXT,\n address TEXT,\n sector TEXT,\n city TEXT,\n region TEXT,\n property_type TEXT,\n price REAL,\n price_label TEXT,\n bedrooms INTEGER,\n bathrooms INTEGER,\n powder_rooms INTEGER,\n area_sqft REAL,\n lot_sqft REAL,\n year_built INTEGER,\n mls TEXT,\n status TEXT DEFAULT 'a-vendre',\n broker_name TEXT,\n broker_phone TEXT,\n agency TEXT,\n description TEXT,\n features TEXT, -- JSON (liste de textes source)\n details TEXT, -- JSON (champs structurés)\n images TEXT, -- JSON\n lat REAL,\n lng REAL,\n geocode_failed INTEGER DEFAULT 0,\n content_hash TEXT,\n first_seen REAL,\n last_seen REAL,\n updated_at REAL,\n miss_count INTEGER DEFAULT 0,\n active INTEGER DEFAULT 1,\n dup_hidden INTEGER DEFAULT 0 -- 1 = doublon de sous-agence masqué (dédup Centris)\n);\nCREATE INDEX IF NOT EXISTS idx_listings_source ON listings(source);\nCREATE INDEX IF NOT EXISTS idx_listings_city ON listings(city);\nCREATE INDEX IF NOT EXISTS idx_listings_type ON listings(property_type);\nCREATE INDEX IF NOT EXISTS idx_listings_active ON listings(active);\nCREATE INDEX IF NOT EXISTS idx_listings_extid ON listings(external_id);\n\nCREATE TABLE IF NOT EXISTS sync_log (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n source TEXT,\n ts REAL,\n found INTEGER,\n added INTEGER,\n updated INTEGER,\n removed INTEGER,\n ok INTEGER,\n message TEXT,\n stats TEXT -- JSON : taux de champs null, missed, alerte…\n);\n\nCREATE TABLE IF NOT EXISTS detail_cache (\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n key TEXT, -- hash du contenu « liste » de l'annonce\n payload TEXT, -- JSON opaque propre au connecteur\n fetched_at REAL,\n PRIMARY KEY (source, external_id)\n);\n\nCREATE TABLE IF NOT EXISTS price_log (\n uid TEXT NOT NULL,\n ts REAL NOT NULL,\n price REAL -- prix observé (baisses/hausses de prix demandé)\n);\nCREATE INDEX IF NOT EXISTS idx_price_log_uid ON price_log(uid);\n\nCREATE TABLE IF NOT EXISTS geocode_cache (\n address TEXT PRIMARY KEY,\n lat REAL,\n lng REAL,\n provider TEXT,\n failed INTEGER DEFAULT 0,\n ts REAL,\n muni TEXT -- municipalité officielle (clés « ville:… »)\n);\n\nCREATE TABLE IF NOT EXISTS poi_cache (\n coord_key TEXT PRIMARY KEY, -- \"lat,lng\" arrondi à 4 décimales (~11 m)\n lat REAL,\n lng REAL,\n pois TEXT, -- JSON : [{cat, name, dist_m}] (plus proche/catégorie)\n ts REAL\n);\n\"\"\"\n\n\n_SCHEMA_READY = False # le schéma/migration ne s'exécute qu'UNE fois par process\n\n\ndef _init_schema(con: sqlite3.Connection) -> None:\n \"\"\"Création de schéma + migration — coûteuse (write-lock). À faire une seule\n fois par process : l'exécuter à chaque connexion sérialisait les requêtes du\n web sur un verrou d'écriture (deadlock/starvation sous charge).\"\"\"\n con.executescript(_SCHEMA)\n cols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(listings)\")}\n if \"agency\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN agency TEXT\")\n if \"dup_hidden\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n if \"dup_of\" not in cols: # uid de la fiche visible au profit de laquelle\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_of TEXT\") # celle-ci est masquée\n if \"dauid\" not in cols: # aire de diffusion 2021 (stats de quartier)\n con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")\n if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n gcols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(geocode_cache)\")}\n if \"muni\" not in gcols: # municipalité officielle (entrées « ville:… »)\n con.execute(\"ALTER TABLE geocode_cache ADD COLUMN muni TEXT\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_dupof ON listings(dup_of)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n con.commit()\n\n\ndef refresh_dedup(con: sqlite3.Connection) -> int:\n \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n\n Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée\n si une fiche de plus haute priorité — même n° Centris (external_id), active —\n existe : le flux central/agence principale d'abord, sinon la sous-agence au\n plus petit uid. Les fiches non sous-agence ne sont jamais masquées par\n cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).\n Retourne le nombre total de fiches masquées.\"\"\"\n AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n con.execute(\"UPDATE listings SET dup_hidden=0, dup_of=NULL\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n # dup_of = la fiche canonique (pour la box « Aussi publiée sur… »).\n con.execute(\n f\"UPDATE listings SET dup_hidden=1,\"\n f\" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{NOTAG})\"\n f\" WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1,\"\n f\" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\"\n f\" WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")\n # 3) dédup INTER-SOURCES par adresse : la même propriété publiée sur deux\n # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle\n # conservatrice : même adresse normalisée (civique + rue + ville) + même\n # type + prix identique à ±1 % → on garde la fiche la plus autoritaire.\n try:\n n_addr = dedup_by_address(con)\n if n_addr:\n print(f\"[immo-ka] dédup adresse: {n_addr} doublon(s) inter-sources masqué(s)\")\n except Exception:\n import traceback\n traceback.print_exc()\n n = con.execute(\"SELECT COUNT(*) c FROM listings WHERE dup_hidden=1\").fetchone()[\"c\"]\n con.commit()\n return n\n\n\n# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main).\n# fb_marketplace : fiches anonymes/republication — jamais préférées à un courtier.\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\", \"fb_marketplace\"}\n\n\ndef _source_rank(source: str) -> int:\n \"\"\"Autorité d'une source pour la dédup d'adresse :\n 0 = source primaire (bannière/agence/FSBO), 1 = sous-agence (_ag_),\n 2 = petites annonces (republication probable).\"\"\"\n if source in _PETITES_ANNONCES:\n return 2\n if \"_ag_\" in source:\n return 1\n return 0\n\n\ndef dedup_by_address(con: sqlite3.Connection) -> int:\n \"\"\"Passe de déduplication conservatrice par ADRESSE (inter-sources).\n\n Clé : n° civique(s) + mots significatifs de la rue + ville normalisée +\n type canonique + n° d'app/unité (vide s'il n'y en a pas — deux unités\n différentes d'un même immeuble ne partagent JAMAIS la même clé, et une\n adresse sans unité ne s'apparie pas à une adresse avec unité). Dans une\n clé, seules les fiches au prix identique à ±1 % sont considérées comme\n doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis à autorité égale celle qui a un COURTIER/agence\n (jamais une fiche anonyme devant un courtier), puis le plus petit uid.\n Retourne le nb masqué.\"\"\"\n import re as _re\n from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE\n groups: dict[tuple, list] = {}\n for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type,\"\n \" broker_name, agency\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):\n civs, words = _addr_parts(r[\"address\"])\n if not civs or not words:\n continue\n a = _norm(r[\"address\"]).split(\",\")[0]\n mapt = _re.search(_APP_RE, a)\n apt = \"\"\n if mapt:\n toks = _re.findall(r\"[a-z0-9]+\", mapt.group(0))\n # dernier token = le n° d'unité (le 1er est le mot-clé app/unité/#)\n apt = toks[-1] if toks else \"\"\n key = (\"-\".join(civs), \" \".join(sorted(set(words))),\n _muni_norm(r[\"city\"]), _norm(r[\"property_type\"]), apt)\n groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))\n hidden = 0\n for rows in groups.values():\n if len(rows) < 2:\n continue\n rows.sort() # par prix croissant\n cluster: list = []\n for row in rows:\n if cluster and row[0] > cluster[0][0] * 1.01:\n hidden += _mask_cluster(con, cluster)\n cluster = []\n cluster.append(row)\n hidden += _mask_cluster(con, cluster)\n return hidden\n\n\ndef _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:\n \"\"\"Masque les doublons d'un groupe (même clé d'adresse, prix ±1 %), puis\n FUSIONNE en « golden record » : les champs vides de la fiche conservée sont\n complétés depuis les doublons masqués (description plus longue, galerie plus\n riche, superficies, année, GPS, téléphone) — le meilleur des deux sources.\"\"\"\n if len(cluster) < 2:\n return 0\n sources = [c[3] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[2] != keep[2]:\n con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n donors.append(c[2])\n n += 1\n try:\n _merge_golden(con, keep[2], donors)\n except Exception:\n pass # la fusion est un bonus — ne jamais casser la dédup\n return n\n\n\n_MERGE_NUM_FIELDS = (\"bedrooms\", \"bathrooms\", \"powder_rooms\", \"area_sqft\",\n \"lot_sqft\", \"year_built\")\n\n\ndef _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:\n \"\"\"Complète les champs vides de `keep_uid` depuis ses doublons masqués.\"\"\"\n if not donor_uids:\n return\n cols = (\"uid, description, images, bedrooms, bathrooms, powder_rooms,\"\n \" area_sqft, lot_sqft, year_built, lat, lng, broker_phone\")\n keep = con.execute(f\"SELECT {cols} FROM listings WHERE uid=?\",\n (keep_uid,)).fetchone()\n if keep is None:\n return\n sets, args = [], []\n kimgs = len(json.loads(keep[\"images\"] or \"[]\"))\n kdesc = len(keep[\"description\"] or \"\")\n best_imgs, best_desc = None, None\n donor_rows = con.execute(\n f\"SELECT {cols} FROM listings WHERE uid IN \"\n f\"({','.join('?' * len(donor_uids))})\", donor_uids).fetchall()\n merged_num: dict = {}\n for d in donor_rows:\n di = json.loads(d[\"images\"] or \"[]\")\n if len(di) > max(kimgs, len(json.loads(best_imgs or \"[]\"))):\n best_imgs = d[\"images\"]\n dd = d[\"description\"] or \"\"\n if len(dd) > max(kdesc, 80, len(best_desc or \"\")):\n best_desc = dd\n for f in _MERGE_NUM_FIELDS:\n if keep[f] is None and merged_num.get(f) is None and d[f] is not None:\n merged_num[f] = d[f]\n # GPS : toujours la PAIRE du même donneur (jamais lat et lng mélangés)\n if (keep[\"lat\"] is None and \"lat\" not in merged_num\n and d[\"lat\"] is not None and d[\"lng\"] is not None):\n merged_num[\"lat\"], merged_num[\"lng\"] = d[\"lat\"], d[\"lng\"]\n if not keep[\"broker_phone\"] and d[\"broker_phone\"] and \"broker_phone\" not in merged_num:\n merged_num[\"broker_phone\"] = d[\"broker_phone\"]\n if best_imgs is not None:\n sets.append(\"images=?\"); args.append(best_imgs)\n if best_desc is not None and kdesc < 80:\n sets.append(\"description=?\"); args.append(best_desc)\n for f, v in merged_num.items():\n sets.append(f\"{f}=?\"); args.append(v)\n if sets:\n args.append(keep_uid)\n con.execute(f\"UPDATE listings SET {', '.join(sets)} WHERE uid=?\", args)\n\n\ndef connect() -> sqlite3.Connection:\n global _SCHEMA_READY\n DB_PATH.parent.mkdir(parents=True, exist_ok=True)\n con = sqlite3.connect(DB_PATH, timeout=60)\n con.row_factory = sqlite3.Row\n # WAL + busy_timeout : accès concurrents (watcher + web) sans « db is locked ».\n con.execute(\"PRAGMA journal_mode=WAL\")\n # 120 s : couvre les longues transactions (refresh_dedup ~70 s) sans que les\n # autres écrivains (géocodage, vraiprix) ne lèvent « database is locked ».\n con.execute(\"PRAGMA busy_timeout=120000\")\n con.execute(\"PRAGMA synchronous=NORMAL\")\n if not _SCHEMA_READY:\n _init_schema(con)\n _SCHEMA_READY = True\n return con\n\n\n# ---------------------------------------------------------------------------\n# Synchronisation d'une source\n# ---------------------------------------------------------------------------\n\ndef _drift_alert(con: sqlite3.Connection, source: str, found: int,\n null_price_rate: float) -> str | None:\n \"\"\"Détecte une dérive du connecteur (chute du volume ou des prix extraits).\"\"\"\n hist = con.execute(\n \"SELECT found, stats FROM sync_log WHERE source=? AND ok=1\"\n \" ORDER BY ts DESC LIMIT ?\", (source, DRIFT_HISTORY)).fetchall()\n if len(hist) < 3:\n return None\n med_found = statistics.median(r[\"found\"] for r in hist)\n if med_found >= DRIFT_MIN_BASE and found <= DRIFT_RATIO * med_found:\n return (f\"dérive: {found} propriété(s) trouvée(s) contre une médiane de \"\n f\"{med_found:.0f} — retraits suspendus, vérifier le connecteur\")\n if found >= DRIFT_MIN_BASE and null_price_rate >= 0.8:\n rates = []\n for r in hist:\n try:\n rates.append(json.loads(r[\"stats\"] or \"{}\")[\"null_price_rate\"])\n except (KeyError, ValueError, TypeError):\n continue\n if rates and statistics.median(rates) <= 0.3:\n return (f\"dérive: {null_price_rate:.0%} des propriétés sans prix \"\n f\"(habituellement {statistics.median(rates):.0%}) — \"\n \"le format de la source a probablement changé\")\n return None\n\n\ndef sync_source(con: sqlite3.Connection, source: str,\n listings: list[PropertyListing]) -> dict:\n \"\"\"Synchronise les propriétés d'une source.\n\n - nouvelle propriété -> insertion\n - propriété modifiée -> mise à jour (comparaison de content_hash)\n - propriété disparue -> miss_count += 1, puis active=0 après MISS_GRACE\n exécutions consécutives (vendue ou retirée)\n - dérive détectée -> alerte consignée, retraits suspendus\n \"\"\"\n now = time.time()\n added = updated = 0\n seen_uids = set()\n\n n = len(listings)\n null_price = sum(1 for l in listings if l.price is None)\n null_addr = sum(1 for l in listings if not l.address)\n null_price_rate = round(null_price / n, 3) if n else 0.0\n\n alert = _drift_alert(con, source, n, null_price_rate)\n\n for lst in listings:\n seen_uids.add(lst.uid)\n h = lst.content_hash()\n row = con.execute(\"SELECT content_hash, price FROM listings WHERE uid=?\",\n (lst.uid,)).fetchone()\n params = dict(\n uid=lst.uid, source=lst.source, external_id=lst.external_id,\n url=lst.url, title=lst.title, address=lst.address,\n sector=lst.sector, city=lst.city, region=lst.region,\n property_type=lst.property_type, price=lst.price,\n price_label=lst.price_label, bedrooms=lst.bedrooms,\n bathrooms=lst.bathrooms, powder_rooms=lst.powder_rooms,\n area_sqft=lst.area_sqft, lot_sqft=lst.lot_sqft,\n year_built=lst.year_built, mls=lst.mls, status=lst.status,\n broker_name=lst.broker_name, broker_phone=lst.broker_phone,\n agency=lst.agency,\n description=lst.description,\n features=json.dumps(lst.features, ensure_ascii=False),\n details=json.dumps(lst.details, ensure_ascii=False),\n images=json.dumps(lst.images, ensure_ascii=False),\n lat=lst.lat, lng=lst.lng, content_hash=h, now=now,\n )\n if row is None:\n con.execute(\n \"\"\"INSERT INTO listings (uid, source, external_id, url, title,\n address, sector, city, region, property_type, price,\n price_label, bedrooms, bathrooms, powder_rooms, area_sqft,\n lot_sqft, year_built, mls, status, broker_name, broker_phone,\n agency, description, features, details, images, lat, lng,\n content_hash, first_seen, last_seen, updated_at,\n miss_count, active)\n VALUES (:uid,:source,:external_id,:url,:title,:address,\n :sector,:city,:region,:property_type,:price,:price_label,\n :bedrooms,:bathrooms,:powder_rooms,:area_sqft,:lot_sqft,\n :year_built,:mls,:status,:broker_name,:broker_phone,\n :agency,:description,:features,:details,:images,:lat,:lng,\n :content_hash,:now,:now,:now,0,1)\"\"\", params)\n if lst.price is not None:\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n added += 1\n elif row[\"content_hash\"] != h:\n # COALESCE : ne jamais écraser par null des coordonnées géocodées ni\n # les année/superficies remplies par enrichissement (rôle d'évaluation,\n # fiche détail) quand la source liste ne les fournit pas\n con.execute(\n \"\"\"UPDATE listings SET url=:url, title=:title,\n address=:address, sector=:sector, city=:city, region=:region,\n property_type=:property_type, price=:price,\n price_label=:price_label, bedrooms=:bedrooms,\n bathrooms=:bathrooms, powder_rooms=:powder_rooms,\n area_sqft=COALESCE(:area_sqft, area_sqft),\n lot_sqft=COALESCE(:lot_sqft, lot_sqft),\n year_built=COALESCE(:year_built, year_built),\n mls=:mls, status=:status,\n broker_name=:broker_name, broker_phone=:broker_phone,\n agency=:agency, description=:description, features=:features,\n details=:details, images=:images,\n lat=COALESCE(:lat, lat), lng=COALESCE(:lng, lng),\n content_hash=:content_hash, last_seen=:now,\n updated_at=:now, miss_count=0, active=1\n WHERE uid=:uid\"\"\", params)\n if lst.price != row[\"price\"]: # baisse/hausse de prix -> historique\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n updated += 1\n else:\n con.execute(\n \"UPDATE listings SET last_seen=?, miss_count=0, active=1 WHERE uid=?\",\n (now, lst.uid))\n\n # Propriétés de cette source qui n'apparaissent plus : délai de grâce,\n # puis désactivation (vendue/retirée). Suspendu si dérive détectée.\n removed = missed = 0\n if not alert:\n for r in con.execute(\n \"SELECT uid, miss_count FROM listings WHERE source=? AND active=1\",\n (source,)).fetchall():\n if r[\"uid\"] in seen_uids:\n continue\n missed += 1\n if r[\"miss_count\"] + 1 >= MISS_GRACE:\n con.execute(\n \"UPDATE listings SET active=0, miss_count=?, updated_at=?\"\n \" WHERE uid=?\", (r[\"miss_count\"] + 1, now, r[\"uid\"]))\n removed += 1\n else:\n con.execute(\"UPDATE listings SET miss_count=miss_count+1 WHERE uid=?\",\n (r[\"uid\"],))\n\n stats = {\n \"null_price_rate\": null_price_rate,\n \"null_address_rate\": round(null_addr / n, 3) if n else 0.0,\n \"missed\": missed,\n }\n if alert:\n stats[\"alert\"] = alert\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok,\"\n \" message, stats) VALUES (?,?,?,?,?,?,1,?,?)\",\n (source, now, n, added, updated, removed, alert or \"ok\",\n json.dumps(stats, ensure_ascii=False)))\n con.commit()\n out = {\"source\": source, \"found\": n, \"added\": added,\n \"updated\": updated, \"removed\": removed}\n if alert:\n out[\"alert\"] = alert\n return out\n\n\ndef log_failure(con: sqlite3.Connection, source: str, message: str) -> None:\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok, message)\"\n \" VALUES (?,?,0,0,0,0,0,?)\", (source, time.time(), message))\n con.commit()\n\n\n# ---------------------------------------------------------------------------\n# Cache des pages détail (« détail si nouveau/modifié »)\n# ---------------------------------------------------------------------------\n\ndef get_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str) -> dict | None:\n \"\"\"Payload détail mis en cache si la clé (hash liste) n'a pas changé.\"\"\"\n row = con.execute(\n \"SELECT key, payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"key\"] == key and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef get_stale_detail(con: sqlite3.Connection, source: str,\n external_id: str) -> dict | None:\n \"\"\"Payload détail SANS vérifier la clé — repli « périmé plutôt que rien »\n quand le budget de re-fetch d'un cycle est épuisé (ex. bump de version de\n clé) : la fiche garde photos/détails existants en attendant son re-parse.\"\"\"\n row = con.execute(\n \"SELECT payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef put_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str, payload: dict) -> None:\n con.execute(\n \"INSERT INTO detail_cache (source, external_id, key, payload, fetched_at)\"\n \" VALUES (?,?,?,?,?)\"\n \" ON CONFLICT(source, external_id) DO UPDATE SET\"\n \" key=excluded.key, payload=excluded.payload, fetched_at=excluded.fetched_at\",\n (source, external_id, key, json.dumps(payload, ensure_ascii=False),\n time.time()))\n con.commit()\n","structuredPatch":[{"oldStart":251,"oldLines":8,"newStart":251,"newLines":9,"lines":[" apt = toks[-1] if toks else \"\""," key = (\"-\".join(civs), \" \".join(sorted(set(words))),"," _muni_norm(r[\"city\"]), _norm(r[\"property_type\"]), apt)","+ anonyme = 0 if (r[\"broker_name\"] or r[\"agency\"]) else 1"," groups.setdefault(key, []).append(","- (r[\"price\"], _source_rank(r[\"source\"]), r[\"uid\"], r[\"source\"]))","+ (r[\"price\"], _source_rank(r[\"source\"]), anonyme, r[\"uid\"], r[\"source\"]))"," hidden = 0"," for rows in groups.values():"," if len(rows) < 2:"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"06a52961-80b8-429c-a73e-26d71a3d1c0b","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePc1s8ZhMdwWRx5u5n3i","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Wrt7XgESwwnHCPNnVpRUxJ","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","old_string":" if len(cluster) < 2:\n return 0\n sources = [c[3] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[2] != keep[2]:\n con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n donors.append(c[2])\n n += 1\n try:\n _merge_golden(con, keep[2], donors)","new_string":" if len(cluster) < 2:\n return 0\n sources = [c[4] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2], c[3])) # (autorité, anonyme, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[3] != keep[3]:\n con.execute(\"UPDATE listings SET dup_hidden=1, dup_of=? WHERE uid=?\",\n (keep[3], c[3]))\n donors.append(c[3])\n n += 1\n try:\n _merge_golden(con, keep[3], donors)"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":321,"cache_read_input_tokens":61893,"cache_creation":{"ephemeral_5m_input_tokens":321,"ephemeral_1h_input_tokens":0},"output_tokens":15,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"3593c478-90ca-4239-9dee-85255d920ba1"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Wrt7XgESwwnHCPNnVpRUxJ","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/db.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"39b053f3-af58-444b-9972-af747cabee7d","timestamp":"2026-08-25T14:13:21.441Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/db.py","oldString":" if len(cluster) < 2:\n return 0\n sources = [c[3] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[2] != keep[2]:\n con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n donors.append(c[2])\n n += 1\n try:\n _merge_golden(con, keep[2], donors)","newString":" if len(cluster) < 2:\n return 0\n sources = [c[4] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2], c[3])) # (autorité, anonyme, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[3] != keep[3]:\n con.execute(\"UPDATE listings SET dup_hidden=1, dup_of=? WHERE uid=?\",\n (keep[3], c[3]))\n donors.append(c[3])\n n += 1\n try:\n _merge_golden(con, keep[3], donors)","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# db.py : persistance SQLite — upsert avec détection de changements,\n# cycle de vie avec délai de grâce (2 syncs), détection de dérive,\n# historique de prix, cache des pages détail.\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport sqlite3\nimport statistics\nimport time\nfrom pathlib import Path\n\nfrom .schema import PropertyListing\n\nDB_PATH = Path(__file__).resolve().parent.parent / \"data\" / \"immoka.db\"\n\n# Nombre d'exécutions consécutives où une propriété doit être absente de la\n# source avant d'être désactivée (délai de grâce contre les ratés ponctuels).\nMISS_GRACE = 2\n\n# Dérive : si une source retourne <= DRIFT_RATIO × sa médiane historique\n# (médiane >= DRIFT_MIN_BASE annonces), on alerte et on suspend les retraits.\nDRIFT_RATIO = 0.25\nDRIFT_MIN_BASE = 8\nDRIFT_HISTORY = 5\n\n_SCHEMA = \"\"\"\nCREATE TABLE IF NOT EXISTS listings (\n uid TEXT PRIMARY KEY,\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n url TEXT,\n title TEXT,\n address TEXT,\n sector TEXT,\n city TEXT,\n region TEXT,\n property_type TEXT,\n price REAL,\n price_label TEXT,\n bedrooms INTEGER,\n bathrooms INTEGER,\n powder_rooms INTEGER,\n area_sqft REAL,\n lot_sqft REAL,\n year_built INTEGER,\n mls TEXT,\n status TEXT DEFAULT 'a-vendre',\n broker_name TEXT,\n broker_phone TEXT,\n agency TEXT,\n description TEXT,\n features TEXT, -- JSON (liste de textes source)\n details TEXT, -- JSON (champs structurés)\n images TEXT, -- JSON\n lat REAL,\n lng REAL,\n geocode_failed INTEGER DEFAULT 0,\n content_hash TEXT,\n first_seen REAL,\n last_seen REAL,\n updated_at REAL,\n miss_count INTEGER DEFAULT 0,\n active INTEGER DEFAULT 1,\n dup_hidden INTEGER DEFAULT 0 -- 1 = doublon de sous-agence masqué (dédup Centris)\n);\nCREATE INDEX IF NOT EXISTS idx_listings_source ON listings(source);\nCREATE INDEX IF NOT EXISTS idx_listings_city ON listings(city);\nCREATE INDEX IF NOT EXISTS idx_listings_type ON listings(property_type);\nCREATE INDEX IF NOT EXISTS idx_listings_active ON listings(active);\nCREATE INDEX IF NOT EXISTS idx_listings_extid ON listings(external_id);\n\nCREATE TABLE IF NOT EXISTS sync_log (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n source TEXT,\n ts REAL,\n found INTEGER,\n added INTEGER,\n updated INTEGER,\n removed INTEGER,\n ok INTEGER,\n message TEXT,\n stats TEXT -- JSON : taux de champs null, missed, alerte…\n);\n\nCREATE TABLE IF NOT EXISTS detail_cache (\n source TEXT NOT NULL,\n external_id TEXT NOT NULL,\n key TEXT, -- hash du contenu « liste » de l'annonce\n payload TEXT, -- JSON opaque propre au connecteur\n fetched_at REAL,\n PRIMARY KEY (source, external_id)\n);\n\nCREATE TABLE IF NOT EXISTS price_log (\n uid TEXT NOT NULL,\n ts REAL NOT NULL,\n price REAL -- prix observé (baisses/hausses de prix demandé)\n);\nCREATE INDEX IF NOT EXISTS idx_price_log_uid ON price_log(uid);\n\nCREATE TABLE IF NOT EXISTS geocode_cache (\n address TEXT PRIMARY KEY,\n lat REAL,\n lng REAL,\n provider TEXT,\n failed INTEGER DEFAULT 0,\n ts REAL,\n muni TEXT -- municipalité officielle (clés « ville:… »)\n);\n\nCREATE TABLE IF NOT EXISTS poi_cache (\n coord_key TEXT PRIMARY KEY, -- \"lat,lng\" arrondi à 4 décimales (~11 m)\n lat REAL,\n lng REAL,\n pois TEXT, -- JSON : [{cat, name, dist_m}] (plus proche/catégorie)\n ts REAL\n);\n\"\"\"\n\n\n_SCHEMA_READY = False # le schéma/migration ne s'exécute qu'UNE fois par process\n\n\ndef _init_schema(con: sqlite3.Connection) -> None:\n \"\"\"Création de schéma + migration — coûteuse (write-lock). À faire une seule\n fois par process : l'exécuter à chaque connexion sérialisait les requêtes du\n web sur un verrou d'écriture (deadlock/starvation sous charge).\"\"\"\n con.executescript(_SCHEMA)\n cols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(listings)\")}\n if \"agency\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN agency TEXT\")\n if \"dup_hidden\" not in cols:\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0\")\n if \"dup_of\" not in cols: # uid de la fiche visible au profit de laquelle\n con.execute(\"ALTER TABLE listings ADD COLUMN dup_of TEXT\") # celle-ci est masquée\n if \"dauid\" not in cols: # aire de diffusion 2021 (stats de quartier)\n con.execute(\"ALTER TABLE listings ADD COLUMN dauid TEXT\")\n if \"vraiprix\" not in cols: # estimation Vrai-Prix (JSON) + lien analyse\n con.execute(\"ALTER TABLE listings ADD COLUMN vraiprix TEXT\")\n gcols = {r[\"name\"] for r in con.execute(\"PRAGMA table_info(geocode_cache)\")}\n if \"muni\" not in gcols: # municipalité officielle (entrées « ville:… »)\n con.execute(\"ALTER TABLE geocode_cache ADD COLUMN muni TEXT\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_dupof ON listings(dup_of)\")\n con.execute(\"CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)\")\n con.commit()\n\n\ndef refresh_dedup(con: sqlite3.Connection) -> int:\n \"\"\"Pré-calcule la déduplication de la famille sous-agences (`*_ag_*`) dans la\n colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)\n au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).\n\n Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée\n si une fiche de plus haute priorité — même n° Centris (external_id), active —\n existe : le flux central/agence principale d'abord, sinon la sous-agence au\n plus petit uid. Les fiches non sous-agence ne sont jamais masquées par\n cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons\n INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).\n Retourne le nombre total de fiches masquées.\"\"\"\n AG = \"source LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n NOTAG = \"source NOT LIKE '%\\\\_ag\\\\_%' ESCAPE '\\\\'\"\n con.execute(\"UPDATE listings SET dup_hidden=0, dup_of=NULL\")\n # 1) masquer les sous-agences dont le n° Centris est porté par une fiche\n # canonique (non sous-agence) active — semi-jointure, rapide.\n # dup_of = la fiche canonique (pour la box « Aussi publiée sur… »).\n con.execute(\n f\"UPDATE listings SET dup_hidden=1,\"\n f\" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{NOTAG})\"\n f\" WHERE active=1 AND {AG}\"\n f\" AND external_id IN (SELECT external_id FROM listings\"\n f\" WHERE active=1 AND {NOTAG})\")\n # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus\n # petit uid par n° Centris.\n con.execute(\n f\"UPDATE listings SET dup_hidden=1,\"\n f\" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\"\n f\" WHERE active=1 AND {AG} AND dup_hidden=0\"\n f\" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1\"\n f\" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)\")\n # 3) dédup INTER-SOURCES par adresse : la même propriété publiée sur deux\n # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle\n # conservatrice : même adresse normalisée (civique + rue + ville) + même\n # type + prix identique à ±1 % → on garde la fiche la plus autoritaire.\n try:\n n_addr = dedup_by_address(con)\n if n_addr:\n print(f\"[immo-ka] dédup adresse: {n_addr} doublon(s) inter-sources masqué(s)\")\n except Exception:\n import traceback\n traceback.print_exc()\n n = con.execute(\"SELECT COUNT(*) c FROM listings WHERE dup_hidden=1\").fetchone()[\"c\"]\n con.commit()\n return n\n\n\n# petites annonces généralistes (republication d'annonces d'ailleurs) : moins\n# autoritaires que la source primaire (courtier / FSBO première main).\n# fb_marketplace : fiches anonymes/republication — jamais préférées à un courtier.\n_PETITES_ANNONCES = {\"kijiji\", \"lespac\", \"fb_marketplace\"}\n\n\ndef _source_rank(source: str) -> int:\n \"\"\"Autorité d'une source pour la dédup d'adresse :\n 0 = source primaire (bannière/agence/FSBO), 1 = sous-agence (_ag_),\n 2 = petites annonces (republication probable).\"\"\"\n if source in _PETITES_ANNONCES:\n return 2\n if \"_ag_\" in source:\n return 1\n return 0\n\n\ndef dedup_by_address(con: sqlite3.Connection) -> int:\n \"\"\"Passe de déduplication conservatrice par ADRESSE (inter-sources).\n\n Clé : n° civique(s) + mots significatifs de la rue + ville normalisée +\n type canonique + n° d'app/unité (vide s'il n'y en a pas — deux unités\n différentes d'un même immeuble ne partagent JAMAIS la même clé, et une\n adresse sans unité ne s'apparie pas à une adresse avec unité). Dans une\n clé, seules les fiches au prix identique à ±1 % sont considérées comme\n doublons ; si une même source apparaît deux fois dans le groupe (probables\n unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde\n la fiche la plus autoritaire (source primaire > sous-agence _ag_ >\n petites annonces), puis à autorité égale celle qui a un COURTIER/agence\n (jamais une fiche anonyme devant un courtier), puis le plus petit uid.\n Retourne le nb masqué.\"\"\"\n import re as _re\n from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE\n groups: dict[tuple, list] = {}\n for r in con.execute(\n \"SELECT uid, source, address, city, price, property_type,\"\n \" broker_name, agency\"\n \" FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''\"\n \" AND city<>'' AND price IS NOT NULL AND property_type<>''\"):\n civs, words = _addr_parts(r[\"address\"])\n if not civs or not words:\n continue\n a = _norm(r[\"address\"]).split(\",\")[0]\n mapt = _re.search(_APP_RE, a)\n apt = \"\"\n if mapt:\n toks = _re.findall(r\"[a-z0-9]+\", mapt.group(0))\n # dernier token = le n° d'unité (le 1er est le mot-clé app/unité/#)\n apt = toks[-1] if toks else \"\"\n key = (\"-\".join(civs), \" \".join(sorted(set(words))),\n _muni_norm(r[\"city\"]), _norm(r[\"property_type\"]), apt)\n anonyme = 0 if (r[\"broker_name\"] or r[\"agency\"]) else 1\n groups.setdefault(key, []).append(\n (r[\"price\"], _source_rank(r[\"source\"]), anonyme, r[\"uid\"], r[\"source\"]))\n hidden = 0\n for rows in groups.values():\n if len(rows) < 2:\n continue\n rows.sort() # par prix croissant\n cluster: list = []\n for row in rows:\n if cluster and row[0] > cluster[0][0] * 1.01:\n hidden += _mask_cluster(con, cluster)\n cluster = []\n cluster.append(row)\n hidden += _mask_cluster(con, cluster)\n return hidden\n\n\ndef _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:\n \"\"\"Masque les doublons d'un groupe (même clé d'adresse, prix ±1 %), puis\n FUSIONNE en « golden record » : les champs vides de la fiche conservée sont\n complétés depuis les doublons masqués (description plus longue, galerie plus\n riche, superficies, année, GPS, téléphone) — le meilleur des deux sources.\"\"\"\n if len(cluster) < 2:\n return 0\n sources = [c[3] for c in cluster]\n if len(set(sources)) != len(sources):\n return 0 # même source en double = probables unités distinctes : prudence\n keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)\n n = 0\n donors = []\n for c in cluster:\n if c[2] != keep[2]:\n con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))\n donors.append(c[2])\n n += 1\n try:\n _merge_golden(con, keep[2], donors)\n except Exception:\n pass # la fusion est un bonus — ne jamais casser la dédup\n return n\n\n\n_MERGE_NUM_FIELDS = (\"bedrooms\", \"bathrooms\", \"powder_rooms\", \"area_sqft\",\n \"lot_sqft\", \"year_built\")\n\n\ndef _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:\n \"\"\"Complète les champs vides de `keep_uid` depuis ses doublons masqués.\"\"\"\n if not donor_uids:\n return\n cols = (\"uid, description, images, bedrooms, bathrooms, powder_rooms,\"\n \" area_sqft, lot_sqft, year_built, lat, lng, broker_phone\")\n keep = con.execute(f\"SELECT {cols} FROM listings WHERE uid=?\",\n (keep_uid,)).fetchone()\n if keep is None:\n return\n sets, args = [], []\n kimgs = len(json.loads(keep[\"images\"] or \"[]\"))\n kdesc = len(keep[\"description\"] or \"\")\n best_imgs, best_desc = None, None\n donor_rows = con.execute(\n f\"SELECT {cols} FROM listings WHERE uid IN \"\n f\"({','.join('?' * len(donor_uids))})\", donor_uids).fetchall()\n merged_num: dict = {}\n for d in donor_rows:\n di = json.loads(d[\"images\"] or \"[]\")\n if len(di) > max(kimgs, len(json.loads(best_imgs or \"[]\"))):\n best_imgs = d[\"images\"]\n dd = d[\"description\"] or \"\"\n if len(dd) > max(kdesc, 80, len(best_desc or \"\")):\n best_desc = dd\n for f in _MERGE_NUM_FIELDS:\n if keep[f] is None and merged_num.get(f) is None and d[f] is not None:\n merged_num[f] = d[f]\n # GPS : toujours la PAIRE du même donneur (jamais lat et lng mélangés)\n if (keep[\"lat\"] is None and \"lat\" not in merged_num\n and d[\"lat\"] is not None and d[\"lng\"] is not None):\n merged_num[\"lat\"], merged_num[\"lng\"] = d[\"lat\"], d[\"lng\"]\n if not keep[\"broker_phone\"] and d[\"broker_phone\"] and \"broker_phone\" not in merged_num:\n merged_num[\"broker_phone\"] = d[\"broker_phone\"]\n if best_imgs is not None:\n sets.append(\"images=?\"); args.append(best_imgs)\n if best_desc is not None and kdesc < 80:\n sets.append(\"description=?\"); args.append(best_desc)\n for f, v in merged_num.items():\n sets.append(f\"{f}=?\"); args.append(v)\n if sets:\n args.append(keep_uid)\n con.execute(f\"UPDATE listings SET {', '.join(sets)} WHERE uid=?\", args)\n\n\ndef connect() -> sqlite3.Connection:\n global _SCHEMA_READY\n DB_PATH.parent.mkdir(parents=True, exist_ok=True)\n con = sqlite3.connect(DB_PATH, timeout=60)\n con.row_factory = sqlite3.Row\n # WAL + busy_timeout : accès concurrents (watcher + web) sans « db is locked ».\n con.execute(\"PRAGMA journal_mode=WAL\")\n # 120 s : couvre les longues transactions (refresh_dedup ~70 s) sans que les\n # autres écrivains (géocodage, vraiprix) ne lèvent « database is locked ».\n con.execute(\"PRAGMA busy_timeout=120000\")\n con.execute(\"PRAGMA synchronous=NORMAL\")\n if not _SCHEMA_READY:\n _init_schema(con)\n _SCHEMA_READY = True\n return con\n\n\n# ---------------------------------------------------------------------------\n# Synchronisation d'une source\n# ---------------------------------------------------------------------------\n\ndef _drift_alert(con: sqlite3.Connection, source: str, found: int,\n null_price_rate: float) -> str | None:\n \"\"\"Détecte une dérive du connecteur (chute du volume ou des prix extraits).\"\"\"\n hist = con.execute(\n \"SELECT found, stats FROM sync_log WHERE source=? AND ok=1\"\n \" ORDER BY ts DESC LIMIT ?\", (source, DRIFT_HISTORY)).fetchall()\n if len(hist) < 3:\n return None\n med_found = statistics.median(r[\"found\"] for r in hist)\n if med_found >= DRIFT_MIN_BASE and found <= DRIFT_RATIO * med_found:\n return (f\"dérive: {found} propriété(s) trouvée(s) contre une médiane de \"\n f\"{med_found:.0f} — retraits suspendus, vérifier le connecteur\")\n if found >= DRIFT_MIN_BASE and null_price_rate >= 0.8:\n rates = []\n for r in hist:\n try:\n rates.append(json.loads(r[\"stats\"] or \"{}\")[\"null_price_rate\"])\n except (KeyError, ValueError, TypeError):\n continue\n if rates and statistics.median(rates) <= 0.3:\n return (f\"dérive: {null_price_rate:.0%} des propriétés sans prix \"\n f\"(habituellement {statistics.median(rates):.0%}) — \"\n \"le format de la source a probablement changé\")\n return None\n\n\ndef sync_source(con: sqlite3.Connection, source: str,\n listings: list[PropertyListing]) -> dict:\n \"\"\"Synchronise les propriétés d'une source.\n\n - nouvelle propriété -> insertion\n - propriété modifiée -> mise à jour (comparaison de content_hash)\n - propriété disparue -> miss_count += 1, puis active=0 après MISS_GRACE\n exécutions consécutives (vendue ou retirée)\n - dérive détectée -> alerte consignée, retraits suspendus\n \"\"\"\n now = time.time()\n added = updated = 0\n seen_uids = set()\n\n n = len(listings)\n null_price = sum(1 for l in listings if l.price is None)\n null_addr = sum(1 for l in listings if not l.address)\n null_price_rate = round(null_price / n, 3) if n else 0.0\n\n alert = _drift_alert(con, source, n, null_price_rate)\n\n for lst in listings:\n seen_uids.add(lst.uid)\n h = lst.content_hash()\n row = con.execute(\"SELECT content_hash, price FROM listings WHERE uid=?\",\n (lst.uid,)).fetchone()\n params = dict(\n uid=lst.uid, source=lst.source, external_id=lst.external_id,\n url=lst.url, title=lst.title, address=lst.address,\n sector=lst.sector, city=lst.city, region=lst.region,\n property_type=lst.property_type, price=lst.price,\n price_label=lst.price_label, bedrooms=lst.bedrooms,\n bathrooms=lst.bathrooms, powder_rooms=lst.powder_rooms,\n area_sqft=lst.area_sqft, lot_sqft=lst.lot_sqft,\n year_built=lst.year_built, mls=lst.mls, status=lst.status,\n broker_name=lst.broker_name, broker_phone=lst.broker_phone,\n agency=lst.agency,\n description=lst.description,\n features=json.dumps(lst.features, ensure_ascii=False),\n details=json.dumps(lst.details, ensure_ascii=False),\n images=json.dumps(lst.images, ensure_ascii=False),\n lat=lst.lat, lng=lst.lng, content_hash=h, now=now,\n )\n if row is None:\n con.execute(\n \"\"\"INSERT INTO listings (uid, source, external_id, url, title,\n address, sector, city, region, property_type, price,\n price_label, bedrooms, bathrooms, powder_rooms, area_sqft,\n lot_sqft, year_built, mls, status, broker_name, broker_phone,\n agency, description, features, details, images, lat, lng,\n content_hash, first_seen, last_seen, updated_at,\n miss_count, active)\n VALUES (:uid,:source,:external_id,:url,:title,:address,\n :sector,:city,:region,:property_type,:price,:price_label,\n :bedrooms,:bathrooms,:powder_rooms,:area_sqft,:lot_sqft,\n :year_built,:mls,:status,:broker_name,:broker_phone,\n :agency,:description,:features,:details,:images,:lat,:lng,\n :content_hash,:now,:now,:now,0,1)\"\"\", params)\n if lst.price is not None:\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n added += 1\n elif row[\"content_hash\"] != h:\n # COALESCE : ne jamais écraser par null des coordonnées géocodées ni\n # les année/superficies remplies par enrichissement (rôle d'évaluation,\n # fiche détail) quand la source liste ne les fournit pas\n con.execute(\n \"\"\"UPDATE listings SET url=:url, title=:title,\n address=:address, sector=:sector, city=:city, region=:region,\n property_type=:property_type, price=:price,\n price_label=:price_label, bedrooms=:bedrooms,\n bathrooms=:bathrooms, powder_rooms=:powder_rooms,\n area_sqft=COALESCE(:area_sqft, area_sqft),\n lot_sqft=COALESCE(:lot_sqft, lot_sqft),\n year_built=COALESCE(:year_built, year_built),\n mls=:mls, status=:status,\n broker_name=:broker_name, broker_phone=:broker_phone,\n agency=:agency, description=:description, features=:features,\n details=:details, images=:images,\n lat=COALESCE(:lat, lat), lng=COALESCE(:lng, lng),\n content_hash=:content_hash, last_seen=:now,\n updated_at=:now, miss_count=0, active=1\n WHERE uid=:uid\"\"\", params)\n if lst.price != row[\"price\"]: # baisse/hausse de prix -> historique\n con.execute(\"INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)\",\n (lst.uid, now, lst.price))\n updated += 1\n else:\n con.execute(\n \"UPDATE listings SET last_seen=?, miss_count=0, active=1 WHERE uid=?\",\n (now, lst.uid))\n\n # Propriétés de cette source qui n'apparaissent plus : délai de grâce,\n # puis désactivation (vendue/retirée). Suspendu si dérive détectée.\n removed = missed = 0\n if not alert:\n for r in con.execute(\n \"SELECT uid, miss_count FROM listings WHERE source=? AND active=1\",\n (source,)).fetchall():\n if r[\"uid\"] in seen_uids:\n continue\n missed += 1\n if r[\"miss_count\"] + 1 >= MISS_GRACE:\n con.execute(\n \"UPDATE listings SET active=0, miss_count=?, updated_at=?\"\n \" WHERE uid=?\", (r[\"miss_count\"] + 1, now, r[\"uid\"]))\n removed += 1\n else:\n con.execute(\"UPDATE listings SET miss_count=miss_count+1 WHERE uid=?\",\n (r[\"uid\"],))\n\n stats = {\n \"null_price_rate\": null_price_rate,\n \"null_address_rate\": round(null_addr / n, 3) if n else 0.0,\n \"missed\": missed,\n }\n if alert:\n stats[\"alert\"] = alert\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok,\"\n \" message, stats) VALUES (?,?,?,?,?,?,1,?,?)\",\n (source, now, n, added, updated, removed, alert or \"ok\",\n json.dumps(stats, ensure_ascii=False)))\n con.commit()\n out = {\"source\": source, \"found\": n, \"added\": added,\n \"updated\": updated, \"removed\": removed}\n if alert:\n out[\"alert\"] = alert\n return out\n\n\ndef log_failure(con: sqlite3.Connection, source: str, message: str) -> None:\n con.execute(\n \"INSERT INTO sync_log (source, ts, found, added, updated, removed, ok, message)\"\n \" VALUES (?,?,0,0,0,0,0,?)\", (source, time.time(), message))\n con.commit()\n\n\n# ---------------------------------------------------------------------------\n# Cache des pages détail (« détail si nouveau/modifié »)\n# ---------------------------------------------------------------------------\n\ndef get_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str) -> dict | None:\n \"\"\"Payload détail mis en cache si la clé (hash liste) n'a pas changé.\"\"\"\n row = con.execute(\n \"SELECT key, payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"key\"] == key and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef get_stale_detail(con: sqlite3.Connection, source: str,\n external_id: str) -> dict | None:\n \"\"\"Payload détail SANS vérifier la clé — repli « périmé plutôt que rien »\n quand le budget de re-fetch d'un cycle est épuisé (ex. bump de version de\n clé) : la fiche garde photos/détails existants en attendant son re-parse.\"\"\"\n row = con.execute(\n \"SELECT payload FROM detail_cache WHERE source=? AND external_id=?\",\n (source, external_id)).fetchone()\n if row and row[\"payload\"]:\n try:\n return json.loads(row[\"payload\"])\n except ValueError:\n return None\n return None\n\n\ndef put_cached_detail(con: sqlite3.Connection, source: str,\n external_id: str, key: str, payload: dict) -> None:\n con.execute(\n \"INSERT INTO detail_cache (source, external_id, key, payload, fetched_at)\"\n \" VALUES (?,?,?,?,?)\"\n \" ON CONFLICT(source, external_id) DO UPDATE SET\"\n \" key=excluded.key, payload=excluded.payload, fetched_at=excluded.fetched_at\",\n (source, external_id, key, json.dumps(payload, ensure_ascii=False),\n time.time()))\n con.commit()\n","structuredPatch":[{"oldStart":276,"oldLines":19,"newStart":276,"newLines":20,"lines":[" riche, superficies, année, GPS, téléphone) — le meilleur des deux sources.\"\"\""," if len(cluster) < 2:"," return 0","- sources = [c[3] for c in cluster]","+ sources = [c[4] for c in cluster]"," if len(set(sources)) != len(sources):"," return 0 # même source en double = probables unités distinctes : prudence","- keep = min(cluster, key=lambda c: (c[1], c[2])) # (autorité, uid)","+ keep = min(cluster, key=lambda c: (c[1], c[2], c[3])) # (autorité, anonyme, uid)"," n = 0"," donors = []"," for c in cluster:","- if c[2] != keep[2]:","- con.execute(\"UPDATE listings SET dup_hidden=1 WHERE uid=?\", (c[2],))","- donors.append(c[2])","+ if c[3] != keep[3]:","+ con.execute(\"UPDATE listings SET dup_hidden=1, dup_of=? WHERE uid=?\",","+ (keep[3], c[3]))","+ donors.append(c[3])"," n += 1"," try:","- _merge_golden(con, keep[2], donors)","+ _merge_golden(con, keep[3], donors)"," except Exception:"," pass # la fusion est un bonus — ne jamais casser la dédup"," return n"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"30e6e5c5-a669-4519-aab0-d9151e596306","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePc2Ydc9AnMiSj6sxWif","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":670,"cache_read_input_tokens":62214,"cache_creation":{"ephemeral_5m_input_tokens":670,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"50daeddb-46d5-45df-b795-21501a42b6d5"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePc2Ydc9AnMiSj6sxWif","type":"message","role":"assistant","content":[{"type":"text","text":"db.py fait. Passons à web.py — exposer les doublons dans `get_listing`."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":670,"cache_read_input_tokens":62214,"cache_creation":{"ephemeral_5m_input_tokens":670,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"34f29f56-be91-448c-8fad-61f4a90b7705"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePc2Ydc9AnMiSj6sxWif","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01VswW3XtQ1mYQAWJUApkFFe","name":"Read","input":{"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/web.py","offset":190,"limit":45},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":670,"cache_read_input_tokens":62214,"cache_creation":{"ephemeral_5m_input_tokens":670,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ecff3678-ecf6-4b91-8a7b-bfdde2c01d9b"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01VswW3XtQ1mYQAWJUApkFFe","type":"tool_result","content":"190\t d = inondation.lookup(lat, lng)\n191\t if d is None:\n192\t raise HTTPException(404, \"Base des zones inondables non disponible\")\n193\t return d\n194\t\n195\t\n196\t@app.get(\"/api/listings/{uid}\")\n197\tdef get_listing(uid: str):\n198\t con = db.connect()\n199\t row = con.execute(\"SELECT * FROM listings WHERE uid=?\", (uid,)).fetchone()\n200\t d = None\n201\t if row is not None:\n202\t d = _row_to_dict(row)\n203\t # historique de prix (baisses/hausses du prix demandé)\n204\t d[\"price_history\"] = [dict(r) for r in con.execute(\n205\t \"SELECT ts, price FROM price_log WHERE uid=? ORDER BY ts DESC LIMIT 10\",\n206\t (uid,)).fetchall()]\n207\t # commodités de proximité (cache par immeuble, voir immoka/poi.py)\n208\t if d.get(\"lat\") is not None and d.get(\"lng\") is not None:\n209\t key = f\"{round(d['lat'], 4)},{round(d['lng'], 4)}\"\n210\t poi_row = con.execute(\n211\t \"SELECT pois FROM poi_cache WHERE coord_key=?\", (key,)).fetchone()\n212\t d[\"poi\"] = json.loads(poi_row[\"pois\"]) if poi_row else []\n213\t else:\n214\t d[\"poi\"] = []\n215\t # statistiques de quartier (recensement, proximité, chaleur, criminalité)\n216\t from . import quartier\n217\t dauid = d.get(\"dauid\")\n218\t d[\"quartier\"] = quartier.fiche_quartier(\n219\t d.get(\"lat\"), d.get(\"lng\"), d.get(\"city\") or \"\",\n220\t dauid if dauid and dauid != \"hors-zone\" else None)\n221\t con.close()\n222\t if d is None:\n223\t raise HTTPException(404, \"Propriété introuvable\")\n224\t return d\n225\t\n226\t\n227\t@app.get(\"/api/listings/{uid}/pdf\")\n228\tdef listing_pdf(uid: str):\n229\t \"\"\"Fiche PDF complète de la propriété (immoka/pdffiche.py) — reflète tous\n230\t les blocs de la fiche web : prix + verdict Vrai-Prix, photos, description,\n231\t caractéristiques, pièces, analyses, environnement, quartier, QR.\"\"\"\n232\t from . import pdffiche\n233\t data = pdffiche.fiche_pdf(uid)\n234\t if data is None:"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"11244018-f977-4a90-b69f-06ac67882244","timestamp":"2026-08-25T14:13:28.488Z","tool_use_result":{"type":"text","file":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/web.py","content":" d = inondation.lookup(lat, lng)\n if d is None:\n raise HTTPException(404, \"Base des zones inondables non disponible\")\n return d\n\n\n@app.get(\"/api/listings/{uid}\")\ndef get_listing(uid: str):\n con = db.connect()\n row = con.execute(\"SELECT * FROM listings WHERE uid=?\", (uid,)).fetchone()\n d = None\n if row is not None:\n d = _row_to_dict(row)\n # historique de prix (baisses/hausses du prix demandé)\n d[\"price_history\"] = [dict(r) for r in con.execute(\n \"SELECT ts, price FROM price_log WHERE uid=? ORDER BY ts DESC LIMIT 10\",\n (uid,)).fetchall()]\n # commodités de proximité (cache par immeuble, voir immoka/poi.py)\n if d.get(\"lat\") is not None and d.get(\"lng\") is not None:\n key = f\"{round(d['lat'], 4)},{round(d['lng'], 4)}\"\n poi_row = con.execute(\n \"SELECT pois FROM poi_cache WHERE coord_key=?\", (key,)).fetchone()\n d[\"poi\"] = json.loads(poi_row[\"pois\"]) if poi_row else []\n else:\n d[\"poi\"] = []\n # statistiques de quartier (recensement, proximité, chaleur, criminalité)\n from . import quartier\n dauid = d.get(\"dauid\")\n d[\"quartier\"] = quartier.fiche_quartier(\n d.get(\"lat\"), d.get(\"lng\"), d.get(\"city\") or \"\",\n dauid if dauid and dauid != \"hors-zone\" else None)\n con.close()\n if d is None:\n raise HTTPException(404, \"Propriété introuvable\")\n return d\n\n\n@app.get(\"/api/listings/{uid}/pdf\")\ndef listing_pdf(uid: str):\n \"\"\"Fiche PDF complète de la propriété (immoka/pdffiche.py) — reflète tous\n les blocs de la fiche web : prix + verdict Vrai-Prix, photos, description,\n caractéristiques, pièces, analyses, environnement, quartier, QR.\"\"\"\n from . import pdffiche\n data = pdffiche.fiche_pdf(uid)\n if data is None:","numLines":45,"startLine":190,"totalLines":653}}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"6e888ce9-2276-4a24-a3b8-e21165562f51","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePc34oKB54Zy23yakyNJ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01HFgFjCA8Np3RBGY63YnBJg","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/immoka/web.py","old_string":" # statistiques de quartier (recensement, proximité, chaleur, criminalité)\n from . import quartier","new_string":" # autres publications de la même propriété (doublons masqués par la\n # dédup, rattachés via dup_of) — pour la box « Aussi publiée sur… »\n d[\"duplicates\"] = [dict(r) for r in con.execute(\n \"SELECT uid, source, url, broker_name, agency, price_label\"\n \" FROM listings WHERE dup_of=? AND active=1 ORDER BY source\",\n (uid,)).fetchall()]\n # statistiques de quartier (recensement, proximité, chaleur, criminalité)\n from . import quartier"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1143,"cache_read_input_tokens":62884,"cache_creation":{"ephemeral_5m_input_tokens":1143,"ephemeral_1h_input_tokens":0},"output_tokens":15,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"0f25c957-51ff-4ead-a24c-b5a2226b4439"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01HFgFjCA8Np3RBGY63YnBJg","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/immoka/web.py has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"69b4f118-64b9-46cc-96ee-7660be572d65","timestamp":"2026-08-25T14:13:38.491Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/immoka/web.py","oldString":" # statistiques de quartier (recensement, proximité, chaleur, criminalité)\n from . import quartier","newString":" # autres publications de la même propriété (doublons masqués par la\n # dédup, rattachés via dup_of) — pour la box « Aussi publiée sur… »\n d[\"duplicates\"] = [dict(r) for r in con.execute(\n \"SELECT uid, source, url, broker_name, agency, price_label\"\n \" FROM listings WHERE dup_of=? AND active=1 ORDER BY source\",\n (uid,)).fetchall()]\n # statistiques de quartier (recensement, proximité, chaleur, criminalité)\n from . import quartier","originalFile":"# -----------------------------------------------------------------------------\n# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)\n# Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n# web.py : API FastAPI (JSON) + service du frontend statique (frontend/)\n# -----------------------------------------------------------------------------\nfrom __future__ import annotations\n\nimport json\nimport threading\nimport time\nfrom pathlib import Path\n\nfrom fastapi import BackgroundTasks, Body, FastAPI, HTTPException, Query, Request\nfrom fastapi.middleware.cors import CORSMiddleware\nfrom fastapi.middleware.gzip import GZipMiddleware\nfrom fastapi.responses import FileResponse, RedirectResponse, Response\nfrom fastapi.staticfiles import StaticFiles\n\nfrom . import auth, db, favorites, ingest, seo\nfrom . import stats as kastats\n\nROOT = Path(__file__).resolve().parent.parent\nSOURCES_PATH = ROOT / \"data\" / \"sources.json\"\n# Frontend : build Vite (React) si présent, sinon la page statique de secours.\nFRONTEND_DIST = ROOT / \"frontend\" / \"dist\"\nFRONTEND_DIR = FRONTEND_DIST if FRONTEND_DIST.exists() else ROOT / \"frontend\"\n\napp = FastAPI(title=\"Immo-Ka API\", version=\"0.1\",\n description=\"Agrégateur de maisons à vendre — province de Québec\")\napp.add_middleware(CORSMiddleware, allow_origins=[\"*\"],\n allow_methods=[\"*\"], allow_headers=[\"*\"])\n# le GeoJSON complet pèse ~20 Mo — la compression est vitale pour la carte\napp.add_middleware(GZipMiddleware, minimum_size=1024)\n# connexion Google (compte Groupe-Ka partagé avec Lou-Ka) — voir immoka/auth.py\napp.include_router(auth.router)\n# favoris ♥ — magasin central au hub Groupe KA, voir immoka/favorites.py\napp.include_router(favorites.router)\n# annuaire des déménageurs du Québec — page partagée avec Lou-Ka\nfrom . import demenageurs # noqa: E402\napp.include_router(demenageurs.router)\n# annuaire des inspecteurs en bâtiment du Québec\nfrom . import inspecteurs # noqa: E402\napp.include_router(inspecteurs.router)\n# annuaire des bannières & courtiers (registre OACIQ)\nfrom . import bannieres # noqa: E402\napp.include_router(bannieres.router)\n# moteur hypothécaire — taux réels multibanques + calculateur canadien,\n# voir immoka/mortgage/ (docs/mortgage-engine.md)\nfrom .mortgage import api as mortgage_api # noqa: E402\napp.include_router(mortgage_api.router)\n\n_sync_lock = threading.Lock()\n\n# Déduplication de la famille RE/MAX : le flux central (remax_quebec) et les\n# ~42 connecteurs de sous-agences (remax_ag_*) décrivent les MÊMES inscriptions,\n# identifiées de façon unique par leur numéro Centris (= external_id). On masque\n# donc toute fiche de sous-agence dès qu'une fiche de plus haute priorité existe\n# (le central enrichi d'abord, puis la sous-agence au plus petit uid). Les fiches\n# du central et des autres agences ne sont jamais masquées. → aucun double-comptage,\n# et les sous-agences prennent le relais automatiquement si le central disparaît.\n# Déduplication PRÉ-CALCULÉE : la colonne `dup_hidden` (remplie par\n# db.refresh_dedup après chaque sync) marque les doublons de sous-agences. La\n# lecture est ainsi instantanée (index) au lieu d'un sous-select corrélé par\n# ligne (~300 s sur 75 k lignes). Voir db.refresh_dedup pour la règle.\n# + `published=1` : seuil de qualité minimum (voir immoka/quality.py) — une\n# annonce sans prix plausible, sans ville, sans type de bien ou sans contenu\n# exploitable part en QUARANTAINE (grille, carte, stats, sources) jusqu'à\n# complétion par les prochains cycles. La fiche détail par uid reste accessible.\nDEDUP_CLAUSE = \" AND dup_hidden=0 AND published=1\"\n\n\ndef _row_to_dict(row) -> dict:\n d = dict(row)\n d[\"features\"] = json.loads(d.get(\"features\") or \"[]\")\n d[\"images\"] = json.loads(d.get(\"images\") or \"[]\")\n d[\"details\"] = json.loads(d.get(\"details\") or \"{}\")\n if d.get(\"vraiprix\"):\n try:\n d[\"vraiprix\"] = json.loads(d[\"vraiprix\"]) or None\n except (ValueError, TypeError):\n d[\"vraiprix\"] = None\n # jours sur le marché (depuis la 1re observation par Immo-Ka ; la date\n # d'inscription de la source, si connue, est dans details.listed_at)\n if d.get(\"first_seen\"):\n d[\"days_on_market\"] = max(0, int((time.time() - d[\"first_seen\"]) // 86400))\n return d\n\n\n@app.get(\"/api/listings\")\ndef list_listings(\n city: str | None = None,\n sector: str | None = None,\n region: str | None = None,\n property_type: str | None = None,\n source: str | None = None,\n price_max: float | None = None,\n price_min: float | None = None,\n bedrooms_min: int | None = None,\n bathrooms_min: int | None = None,\n area_min: float | None = None, # superficie habitable minimale (pi²)\n q: str | None = None,\n active: int = 1,\n sort: str = \"price_asc\", # price_asc | price_desc | recent\n limit: int = Query(500, le=2000),\n offset: int = 0,\n):\n con = db.connect()\n sql = \"SELECT * FROM listings WHERE 1=1\"\n args: list = []\n if active in (0, 1):\n sql += \" AND active=?\"; args.append(active)\n if city:\n sql += \" AND city=?\"; args.append(city)\n if sector:\n sql += \" AND sector LIKE ?\"; args.append(f\"%{sector}%\")\n if region:\n sql += \" AND region=?\"; args.append(region)\n if property_type:\n sql += \" AND property_type=?\"; args.append(property_type)\n if source:\n sql += \" AND source=?\"; args.append(source)\n if price_max is not None:\n sql += \" AND price IS NOT NULL AND price<=?\"; args.append(price_max)\n if price_min is not None:\n sql += \" AND price IS NOT NULL AND price>=?\"; args.append(price_min)\n if bedrooms_min is not None:\n sql += \" AND bedrooms IS NOT NULL AND bedrooms>=?\"; args.append(bedrooms_min)\n if bathrooms_min is not None:\n sql += \" AND bathrooms IS NOT NULL AND bathrooms>=?\"; args.append(bathrooms_min)\n if area_min is not None:\n sql += \" AND area_sqft IS NOT NULL AND area_sqft>=?\"; args.append(area_min)\n if q:\n sql += \" AND (title LIKE ? OR address LIKE ? OR city LIKE ? OR mls LIKE ?)\"\n args += [f\"%{q}%\"] * 4\n sql += DEDUP_CLAUSE\n total = con.execute(f\"SELECT COUNT(*) c FROM ({sql})\", args).fetchone()[\"c\"]\n order = {\n \"price_asc\": \" ORDER BY price IS NULL, price ASC\",\n \"price_desc\": \" ORDER BY price IS NULL, price DESC\",\n \"recent\": \" ORDER BY first_seen DESC\",\n }.get(sort, \" ORDER BY price IS NULL, price ASC\")\n sql += order + \" LIMIT ? OFFSET ?\"\n args += [limit, offset]\n rows = [_row_to_dict(r) for r in con.execute(sql, args).fetchall()]\n con.close()\n return {\"total\": total, \"count\": len(rows), \"listings\": rows}\n\n\n@app.get(\"/api/hydro\")\ndef hydro_at(adresse: str, solve: int = 0, uid: str | None = None,\n lat: float | None = None, lng: float | None = None):\n \"\"\"Estimation du coût d'électricité à une adresse (Hydro-Québec).\n Par défaut cache seulement (aucun captcha) ; solve=1 force le calcul.\n uid/lat/lng permettent la lecture cache par annonce et la dérivation du\n code postal (adresses sans CP).\"\"\"\n from . import hydro\n return hydro.estimate(adresse=adresse, uid=uid, lat=lat, lng=lng,\n solve=bool(solve))\n\n\n@app.get(\"/api/commerces\")\ndef commerces_at(lat: float, lng: float):\n \"\"\"Grands commerces + métro/bus les plus proches (Mapbox / OSM).\"\"\"\n from . import commerces\n return commerces.nearby(lat, lng)\n\n\n@app.get(\"/api/air\")\ndef air_at(lat: float, lng: float):\n \"\"\"Qualité de l'air : station RSQAQ la plus proche (MELCCFP).\"\"\"\n from . import air\n d = air.lookup(lat, lng)\n if d is None:\n raise HTTPException(404, \"Base qualité de l'air non disponible\")\n return d\n\n\n@app.get(\"/api/gaz\")\ndef gaz_at(lat: float, lng: float):\n \"\"\"Stations-service à proximité et prix courants (gazquebec.ca).\"\"\"\n from . import gaz\n return gaz.nearby(lat, lng)\n\n\n@app.get(\"/api/inondation\")\ndef inondation_at(lat: float, lng: float):\n \"\"\"Risque d'inondation à l'adresse (BDZI, gouv. du Québec) —\n bloc « Risque d'inondation » de la fiche.\"\"\"\n from . import inondation\n d = inondation.lookup(lat, lng)\n if d is None:\n raise HTTPException(404, \"Base des zones inondables non disponible\")\n return d\n\n\n@app.get(\"/api/listings/{uid}\")\ndef get_listing(uid: str):\n con = db.connect()\n row = con.execute(\"SELECT * FROM listings WHERE uid=?\", (uid,)).fetchone()\n d = None\n if row is not None:\n d = _row_to_dict(row)\n # historique de prix (baisses/hausses du prix demandé)\n d[\"price_history\"] = [dict(r) for r in con.execute(\n \"SELECT ts, price FROM price_log WHERE uid=? ORDER BY ts DESC LIMIT 10\",\n (uid,)).fetchall()]\n # commodités de proximité (cache par immeuble, voir immoka/poi.py)\n if d.get(\"lat\") is not None and d.get(\"lng\") is not None:\n key = f\"{round(d['lat'], 4)},{round(d['lng'], 4)}\"\n poi_row = con.execute(\n \"SELECT pois FROM poi_cache WHERE coord_key=?\", (key,)).fetchone()\n d[\"poi\"] = json.loads(poi_row[\"pois\"]) if poi_row else []\n else:\n d[\"poi\"] = []\n # statistiques de quartier (recensement, proximité, chaleur, criminalité)\n from . import quartier\n dauid = d.get(\"dauid\")\n d[\"quartier\"] = quartier.fiche_quartier(\n d.get(\"lat\"), d.get(\"lng\"), d.get(\"city\") or \"\",\n dauid if dauid and dauid != \"hors-zone\" else None)\n con.close()\n if d is None:\n raise HTTPException(404, \"Propriété introuvable\")\n return d\n\n\n@app.get(\"/api/listings/{uid}/pdf\")\ndef listing_pdf(uid: str):\n \"\"\"Fiche PDF complète de la propriété (immoka/pdffiche.py) — reflète tous\n les blocs de la fiche web : prix + verdict Vrai-Prix, photos, description,\n caractéristiques, pièces, analyses, environnement, quartier, QR.\"\"\"\n from . import pdffiche\n data = pdffiche.fiche_pdf(uid)\n if data is None:\n raise HTTPException(404, \"Propriété introuvable\")\n safe = uid.replace(\":\", \"-\").replace(\"/\", \"-\")\n return Response(\n content=data, media_type=\"application/pdf\",\n headers={\"Content-Disposition\":\n f'attachment; filename=\"immo-ka_fiche_{safe}.pdf\"'})\n\n\n@app.get(\"/api/listings.geojson\")\ndef listings_geojson(\n city: str | None = None,\n sector: str | None = None,\n region: str | None = None,\n property_type: str | None = None,\n source: str | None = None,\n price_max: float | None = None,\n price_min: float | None = None,\n bedrooms_min: int | None = None,\n bathrooms_min: int | None = None,\n area_min: float | None = None,\n q: str | None = None,\n bbox: str | None = None,\n limit: int = Query(3000, le=8000),\n):\n \"\"\"Propriétés géolocalisées (marqueurs de carte, champs allégés).\n\n Ka Maps : `bbox=ouest,sud,est,nord` restreint au rectangle visible\n (index idx_listings_geo) ; `limit` plafonne la réponse ; la collection\n porte `totalGeocoded` (géolocalisées correspondantes) et\n `totalMatching` (avec ou sans coordonnées). Mêmes filtres que\n /api/listings pour que la carte suive exactement la recherche.\n \"\"\"\n con = db.connect()\n sql = (\"SELECT uid, title, address, price, price_label, property_type,\"\n \" bedrooms, bathrooms, source, city, sector, images, lat, lng, vraiprix,\"\n \" json_extract(COALESCE(details,'{}'),'$.cover_thumb') AS cover_thumb\"\n \" FROM listings WHERE active=1 AND lat IS NOT NULL AND lng IS NOT NULL\")\n args: list = []\n if bbox:\n try:\n west, south, east, north = (float(v) for v in bbox.split(\",\"))\n except ValueError:\n raise HTTPException(400, \"bbox attendu : ouest,sud,est,nord\")\n sql += \" AND lat BETWEEN ? AND ? AND lng BETWEEN ? AND ?\"\n args += [south, north, west, east]\n if city:\n sql += \" AND city=?\"; args.append(city)\n if sector:\n sql += \" AND sector LIKE ?\"; args.append(f\"%{sector}%\")\n if region:\n sql += \" AND region=?\"; args.append(region)\n if property_type:\n sql += \" AND property_type=?\"; args.append(property_type)\n if source:\n sql += \" AND source=?\"; args.append(source)\n if price_max is not None:\n sql += \" AND price IS NOT NULL AND price<=?\"; args.append(price_max)\n if price_min is not None:\n sql += \" AND price IS NOT NULL AND price>=?\"; args.append(price_min)\n if bedrooms_min is not None:\n sql += \" AND bedrooms IS NOT NULL AND bedrooms>=?\"; args.append(bedrooms_min)\n if bathrooms_min is not None:\n sql += \" AND bathrooms IS NOT NULL AND bathrooms>=?\"; args.append(bathrooms_min)\n if area_min is not None:\n sql += \" AND area_sqft IS NOT NULL AND area_sqft>=?\"; args.append(area_min)\n if q:\n sql += \" AND (title LIKE ? OR address LIKE ? OR city LIKE ? OR mls LIKE ?)\"\n args += [f\"%{q}%\"] * 4\n sql += DEDUP_CLAUSE\n\n total_geo = con.execute(f\"SELECT COUNT(*) c FROM ({sql})\", args).fetchone()[\"c\"]\n sql_all = sql.replace(\" AND lat IS NOT NULL AND lng IS NOT NULL\", \"\")\n args_all = list(args)\n if bbox:\n sql_all = sql_all.replace(\" AND lat BETWEEN ? AND ? AND lng BETWEEN ? AND ?\", \"\")\n del args_all[0:4]\n total_all = con.execute(f\"SELECT COUNT(*) c FROM ({sql_all})\", args_all).fetchone()[\"c\"]\n\n sql += \" ORDER BY price IS NULL, price ASC LIMIT ?\"\n args.append(limit)\n features = []\n for r in con.execute(sql, args).fetchall():\n images = json.loads(r[\"images\"] or \"[]\")\n try:\n vp_val = (json.loads(r[\"vraiprix\"]) or {}).get(\"value\")\n except (TypeError, ValueError):\n vp_val = None\n features.append({\n \"type\": \"Feature\",\n \"geometry\": {\"type\": \"Point\", \"coordinates\": [r[\"lng\"], r[\"lat\"]]},\n \"properties\": {\n \"uid\": r[\"uid\"],\n \"title\": None if r[\"address\"] else r[\"title\"],\n \"address\": r[\"address\"],\n \"price\": r[\"price\"], \"price_label\": r[\"price_label\"],\n \"property_type\": r[\"property_type\"], \"bedrooms\": r[\"bedrooms\"],\n \"bathrooms\": r[\"bathrooms\"], \"source\": r[\"source\"],\n \"city\": r[\"city\"], \"sector\": r[\"sector\"],\n # miniature légère pour le popup mobile si le connecteur en a une\n \"image\": r[\"cover_thumb\"] or (images[0] if images else None),\n \"vp\": vp_val,\n },\n })\n con.close()\n return {\"type\": \"FeatureCollection\", \"features\": features,\n \"totalGeocoded\": total_geo, \"totalMatching\": total_all}\n\n\n@app.get(\"/api/facets\")\ndef facets(city: str | None = None):\n \"\"\"Valeurs distinctes pour construire les filtres du frontend.\"\"\"\n con = db.connect()\n sector_sql = \"SELECT DISTINCT sector FROM listings WHERE active=1 AND sector<>''\"\n sector_args: list = []\n if city:\n sector_sql += \" AND city=?\"\n sector_args.append(city)\n out = {\n \"cities\": [r[\"city\"] for r in con.execute(\n \"SELECT DISTINCT city FROM listings WHERE active=1 AND city<>'' ORDER BY city\")],\n \"sectors\": [r[\"sector\"] for r in con.execute(\n sector_sql + \" ORDER BY sector\", sector_args)],\n \"property_types\": [r[\"property_type\"] for r in con.execute(\n \"SELECT property_type FROM listings WHERE active=1\"\n \" AND property_type<>''\" + DEDUP_CLAUSE +\n \" GROUP BY property_type ORDER BY COUNT(*) DESC\")],\n \"sources\": [dict(r) for r in con.execute(\n \"SELECT source, COUNT(*) n FROM listings WHERE active=1\"\n + DEDUP_CLAUSE + \" GROUP BY source ORDER BY n DESC\")],\n }\n con.close()\n return out\n\n\n@app.get(\"/api/sources\")\ndef sources():\n registry = json.loads(SOURCES_PATH.read_text(encoding=\"utf-8\"))[\"sources\"]\n con = db.connect()\n counts = {r[\"source\"]: r[\"n\"] for r in con.execute(\n \"SELECT source, COUNT(*) n FROM listings WHERE active=1 GROUP BY source\")}\n last = {r[\"source\"]: r[\"ts\"] for r in con.execute(\n \"SELECT source, MAX(ts) ts FROM sync_log WHERE ok=1 GROUP BY source\")}\n con.close()\n for s in registry:\n s[\"active_listings\"] = counts.get(s[\"id\"], 0)\n s[\"last_sync\"] = last.get(s[\"id\"])\n return {\"sources\": registry}\n\n\n# Rattachement d'une source à sa bannière (franchise) pour le regroupement.\n_FRANCHISES = [\n (\"RE/MAX\", lambda s: s == \"remax_quebec\" or s.startswith(\"remax_ag_\")),\n (\"Via Capitale\", lambda s: s == \"via_capitale\" or s.startswith(\"via_ag_\")),\n (\"Century 21\", lambda s: s == \"century21\" or s.startswith(\"c21_ag_\")),\n (\"Royal LePage\", lambda s: s == \"royal_lepage\"),\n (\"Groupe Sutton\", lambda s: s == \"sutton\"),\n (\"Keller Williams\", lambda s: s.startswith(\"kw_\")),\n (\"DuProprio\", lambda s: s == \"duproprio\"),\n]\n\n\ndef _franchise_of(source: str, source_names: dict) -> str:\n for name, match in _FRANCHISES:\n if match(source):\n return name\n return source_names.get(source, source) # agence indépendante = elle-même\n\n\n@app.get(\"/api/agencies\")\ndef agencies():\n \"\"\"Arbre bannière → sous-agences (bureaux) avec le nombre d'inscriptions.\n\n Alimente la page « Sources » de l'app : chaque bannière est éclatée par\n sous-agence via le champ `agency` (bureau). Dédupliqué (n° Centris).\"\"\"\n con = db.connect()\n registry = json.loads(SOURCES_PATH.read_text(encoding=\"utf-8\"))[\"sources\"]\n source_names = {s[\"id\"]: s[\"name\"] for s in registry}\n rows = con.execute(\n \"SELECT source, COALESCE(NULLIF(agency,''), '') agency, COUNT(*) n\"\n \" FROM listings WHERE active=1\" + DEDUP_CLAUSE +\n \" GROUP BY source, agency\").fetchall()\n con.close()\n tree: dict[str, dict] = {}\n for r in rows:\n fr = _franchise_of(r[\"source\"], source_names)\n node = tree.setdefault(fr, {\"franchise\": fr, \"total\": 0, \"agencies\": {}})\n node[\"total\"] += r[\"n\"]\n # nom de sous-agence : le bureau (agency) sinon le nom de la source\n label = r[\"agency\"] or source_names.get(r[\"source\"], r[\"source\"])\n a = node[\"agencies\"].setdefault(label, {\"name\": label, \"count\": 0,\n \"sources\": set()})\n a[\"count\"] += r[\"n\"]\n a[\"sources\"].add(r[\"source\"])\n out = []\n for node in tree.values():\n ags = sorted(node[\"agencies\"].values(), key=lambda x: -x[\"count\"])\n for a in ags:\n a[\"sources\"] = sorted(a[\"sources\"])\n out.append({\"franchise\": node[\"franchise\"], \"total\": node[\"total\"],\n \"sub_agencies\": len(ags), \"agencies\": ags})\n out.sort(key=lambda x: -x[\"total\"])\n return {\"franchises\": out}\n\n\n@app.get(\"/api/stats\")\ndef stats(syncs_since_h: float | None = None):\n con = db.connect()\n row = con.execute(\n \"\"\"SELECT COUNT(*) total,\n COUNT(DISTINCT source) sources,\n COUNT(DISTINCT city) cities,\n AVG(price) avg_price,\n MIN(price) min_price,\n MAX(price) max_price\n FROM listings WHERE active=1\"\"\" + DEDUP_CLAUSE).fetchone()\n # Fenêtre de synchronisations pour la supervision (moniteur central api-ka) :\n # sans paramètre, comportement historique (20 dernières entrées) ; avec\n # ?syncs_since_h=, toutes les entrées de la fenêtre (borne 4000) —\n # évite les fausses alertes « stale » quand 100+ sources synchronisent\n # plus de 20 fois entre deux sondages.\n log: list[dict] = []\n if syncs_since_h is not None:\n cutoff = time.time() - syncs_since_h * 3600\n log = [dict(r) for r in con.execute(\n \"SELECT * FROM sync_log WHERE ts >= ?\"\n \" ORDER BY ts DESC LIMIT 4000\", (cutoff,))]\n if len(log) < 20:\n log = [dict(r) for r in con.execute(\n \"SELECT * FROM sync_log ORDER BY ts DESC LIMIT 20\")]\n\n # --- écart prix demandé vs estimation Vrai-Prix, par bannière -----------\n registry = json.loads(SOURCES_PATH.read_text(encoding=\"utf-8\"))[\"sources\"]\n source_names = {s[\"id\"]: s[\"name\"] for s in registry}\n deltas: dict[str, list[float]] = {}\n for r in con.execute(\n \"SELECT source, price,\"\n \" CAST(json_extract(vraiprix, '$.value') AS REAL) vp\"\n \" FROM listings WHERE active=1\" + DEDUP_CLAUSE +\n \" AND vraiprix LIKE '%estimation%'\"):\n if not r[\"vp\"] or r[\"vp\"] <= 0:\n continue\n d = (r[\"price\"] - r[\"vp\"]) / r[\"vp\"] * 100.0\n if -80.0 <= d <= 300.0: # coupe les aberrations (terrains, données sales)\n deltas.setdefault(_franchise_of(r[\"source\"], source_names), []).append(d)\n con.close()\n\n def _agg(name: str, ds: list[float]) -> dict:\n ds = sorted(ds)\n n = len(ds)\n med = ds[n // 2] if n % 2 else (ds[n // 2 - 1] + ds[n // 2]) / 2\n return {\n \"banniere\": name, \"n\": n,\n \"median_delta_pct\": round(med, 1),\n \"p25\": round(ds[n // 4], 1), \"p75\": round(ds[(3 * n) // 4], 1),\n \"pct_sur10\": round(100 * sum(1 for d in ds if d > 10) / n, 1),\n \"pct_juste\": round(100 * sum(1 for d in ds if -5 <= d <= 10) / n, 1),\n \"pct_sous5\": round(100 * sum(1 for d in ds if d < -5) / n, 1),\n }\n\n tous = [d for ds in deltas.values() for d in ds]\n vraiprix = {\n \"ensemble\": _agg(\"Toutes bannières\", tous) if tous else None,\n \"bannieres\": sorted(\n (_agg(k, v) for k, v in deltas.items() if len(v) >= 30),\n key=lambda x: -x[\"median_delta_pct\"]),\n }\n # qualité des données : complétude, quarantaine, anomalies (par connecteur)\n from . import quality\n con2 = db.connect()\n try:\n qualite = quality.summary(con2)\n finally:\n con2.close()\n return {**dict(row), \"vraiprix\": vraiprix, \"qualite\": qualite,\n \"recent_syncs\": log}\n\n\n# --- Module Stats commun Groupe KA (voir frontend/src/ka/stats/SPEC.md) ------\n@app.get(\"/api/stats/dashboard\")\ndef stats_dashboard(\n period: str | None = Query(None),\n from_: str | None = Query(None, alias=\"from\"),\n to: str | None = Query(None),\n):\n \"\"\"Tableau de bord analytique (contrat SPEC ka-stats, cache 5 min).\"\"\"\n return kastats.dashboard(period, from_, to)\n\n\n@app.get(\"/api/stats/report\")\ndef stats_report(\n period: str = Query(\"30j\"),\n from_: str | None = Query(None, alias=\"from\"),\n to: str | None = Query(None),\n mode: str = Query(\"complet\"),\n):\n \"\"\"Rapport PDF estampillé Groupe-KA (gabarit commun immoka/kapdf.py).\"\"\"\n from . import kapdf\n dash = kastats.dashboard(period, from_, to)\n site = {\n \"wordmark\": \"Immo·Ka\",\n \"accent\": \"#e23744\",\n \"domain\": \"www.immo-ka.com\",\n \"tagline\": \"Agrégateur de propriétés à vendre — province de Québec\",\n }\n pdf = kapdf.GroupeKAReport(\n site=site, dashboard=dash,\n mode=\"synthese\" if mode == \"synthese\" else \"complet\").build()\n return Response(\n content=pdf, media_type=\"application/pdf\",\n headers={\"Content-Disposition\":\n f'attachment; filename=\"{kapdf.filename(\"immo-ka\", period)}\"'})\n\n\n\n@app.get(\"/api/stats/catalog\")\ndef stats_catalog(\n period: str = Query(\"30j\"),\n from_: str | None = Query(None, alias=\"from\"),\n to: str | None = Query(None),\n):\n \"\"\"v3 — blocs composables pour le constructeur de rapports personnalisés.\"\"\"\n from . import kapdf\n dash = kastats.dashboard(period, from_, to)\n return {\"updated\": dash.get(\"updated\"), \"period\": dash.get(\"period\"),\n \"blocks\": kapdf.catalog(dash)}\n\n\n@app.post(\"/api/stats/report/custom\")\ndef stats_report_custom(spec: dict = Body(...)):\n \"\"\"v3 — rapport PDF personnalisé : {\"title\", \"period\", \"from\", \"to\",\n \"blocks\": [{\"key\": \"series:…\", \"render\": \"bar\"}, …]} (SPEC.md §3bis).\"\"\"\n from . import kapdf\n period = str(spec.get(\"period\") or \"30j\")\n dash = kastats.dashboard(period, str(spec.get(\"from\") or \"\") or None,\n str(spec.get(\"to\") or \"\") or None)\n site = {\n \"wordmark\": \"Immo·Ka\",\n \"accent\": \"#e23744\",\n \"domain\": \"www.immo-ka.com\",\n \"tagline\": \"Agrégateur de propriétés à vendre — province de Québec\",\n }\n known = {b[\"key\"] for b in kapdf.catalog(dash)}\n blocks = [b for b in (spec.get(\"blocks\") or [])\n if isinstance(b, dict) and b.get(\"key\") in known][:40]\n if not blocks:\n raise HTTPException(400, \"Aucun bloc valide dans la composition\")\n pdf = kapdf.GroupeKAReport(\n site=site, dashboard=dash, mode=kapdf.CUSTOM_MODE,\n spec={\"title\": str(spec.get(\"title\") or \"\")[:80], \"blocks\": blocks},\n ).build()\n fname = kapdf.filename(\"immo-ka\", period, kapdf.CUSTOM_MODE)\n return Response(\n content=pdf, media_type=\"application/pdf\",\n headers={\"Content-Disposition\": f'attachment; filename=\"{fname}\"'})\n\n@app.post(\"/api/sync\")\ndef trigger_sync(background: BackgroundTasks, source: str | None = None):\n \"\"\"Déclenche une synchronisation (équivalent d'un webhook entrant).\"\"\"\n def _job():\n with _sync_lock:\n ingest.run([source] if source else None)\n background.add_task(_job)\n return {\"status\": \"démarré\", \"source\": source or \"toutes\"}\n\n\n# --- Référencement : robots, sitemaps, résolution de slugs (voir immoka/seo.py)\n@app.get(\"/robots.txt\")\ndef robots():\n return seo.robots_txt()\n\n\n@app.get(\"/sitemap.xml\")\ndef sitemap():\n return seo.sitemap_index()\n\n\n@app.get(\"/sitemaps/{name}\")\ndef sitemap_part(name: str):\n return seo.sitemap_file(name)\n\n\n@app.get(\"/api/seo/resolve\")\ndef seo_resolve(ville: str | None = None, type: str | None = None):\n \"\"\"Slug d'URL programmatique → valeurs exactes (pages /a-vendre du SPA).\"\"\"\n out = seo.resolve_slugs(ville, type)\n if out is None:\n raise HTTPException(404, \"Slug inconnu\")\n return out\n\n\n# --- Frontend statique -------------------------------------------------------\nif FRONTEND_DIR.exists():\n\n if (FRONTEND_DIR / \"assets\").is_dir():\n app.mount(\"/assets\", StaticFiles(directory=FRONTEND_DIR / \"assets\"), name=\"assets\")\n\n @app.get(\"/doc\", include_in_schema=False)\n def doc_redirect():\n return RedirectResponse(\"/doc/\", status_code=301)\n\n # /doc : documentation statique (index.html + captures + PDF) — montée\n # explicitement pour que le catch-all SPA ne l'intercepte pas.\n if (FRONTEND_DIR / \"doc\").is_dir():\n app.mount(\"/doc\", StaticFiles(directory=FRONTEND_DIR / \"doc\", html=True), name=\"doc\")\n\n @app.get(\"/{full_path:path}\")\n def spa(full_path: str, request: Request):\n target = FRONTEND_DIR / full_path\n if full_path and target.is_file():\n return FileResponse(target)\n # rendu SEO côté serveur : HTML complet par route (meta, JSON-LD,\n # contenu dans #root que React remplace au montage). Ne doit JAMAIS\n # casser l'app → repli sur l'index brut à la moindre erreur.\n try:\n return seo.render_for_path(\"/\" + full_path,\n dict(request.query_params))\n except Exception:\n return FileResponse(FRONTEND_DIR / \"index.html\")\n","structuredPatch":[{"oldStart":212,"oldLines":6,"newStart":212,"newLines":12,"lines":[" d[\"poi\"] = json.loads(poi_row[\"pois\"]) if poi_row else []"," else:"," d[\"poi\"] = []","+ # autres publications de la même propriété (doublons masqués par la","+ # dédup, rattachés via dup_of) — pour la box « Aussi publiée sur… »","+ d[\"duplicates\"] = [dict(r) for r in con.execute(","+ \"SELECT uid, source, url, broker_name, agency, price_label\"","+ \" FROM listings WHERE dup_of=? AND active=1 ORDER BY source\",","+ (uid,)).fetchall()]"," # statistiques de quartier (recensement, proximité, chaleur, criminalité)"," from . import quartier"," dauid = d.get(\"dauid\")"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"bba64dbf-5281-408f-871c-06eeb1388a83","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePc3oKRaWHeS3kMmRpvQ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_017qzP1fGUwqAF77dqxie3tP","name":"TodoWrite","input":{"todos":[{"content":"db.py : priorité courtier + colonne dup_of persistée par les 3 passes de dédup","status":"completed","activeForm":"Modifiant la dédup (priorité courtier + dup_of)"},{"content":"web.py : exposer les doublons dans get_listing","status":"completed","activeForm":"Exposant les doublons dans l'API"},{"content":"Frontend : type + box « Aussi publiée sur… » dans Listing.tsx","status":"in_progress","activeForm":"Ajoutant la box doublons au frontend"},{"content":"refresh_dedup + build + PM2 restart + vérif Charles-Trudel","status":"pending","activeForm":"Recalculant la dédup et vérifiant"},{"content":"Commit + push origin main","status":"pending","activeForm":"Committant et poussant"}]},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":418,"cache_read_input_tokens":64027,"cache_creation":{"ephemeral_5m_input_tokens":418,"ephemeral_1h_input_tokens":0},"output_tokens":25,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"de27864f-4823-4025-9979-df956e79180c"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_017qzP1fGUwqAF77dqxie3tP","type":"tool_result","content":"Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"0b1b9394-0fa4-4cc0-96ed-6b8bdf20dd7c","timestamp":"2026-08-25T14:13:48.755Z","tool_use_result":{"oldTodos":[{"content":"db.py : priorité courtier + colonne dup_of persistée par les 3 passes de dédup","status":"in_progress","activeForm":"Modifiant la dédup (priorité courtier + dup_of)"},{"content":"web.py : exposer les doublons dans get_listing","status":"pending","activeForm":"Exposant les doublons dans l'API"},{"content":"Frontend : type + box « Aussi publiée sur… » dans Listing.tsx","status":"pending","activeForm":"Ajoutant la box doublons au frontend"},{"content":"refresh_dedup + build + PM2 restart + vérif Charles-Trudel","status":"pending","activeForm":"Recalculant la dédup et vérifiant"},{"content":"Commit + push origin main","status":"pending","activeForm":"Committant et poussant"}],"newTodos":[{"content":"db.py : priorité courtier + colonne dup_of persistée par les 3 passes de dédup","status":"completed","activeForm":"Modifiant la dédup (priorité courtier + dup_of)"},{"content":"web.py : exposer les doublons dans get_listing","status":"completed","activeForm":"Exposant les doublons dans l'API"},{"content":"Frontend : type + box « Aussi publiée sur… » dans Listing.tsx","status":"in_progress","activeForm":"Ajoutant la box doublons au frontend"},{"content":"refresh_dedup + build + PM2 restart + vérif Charles-Trudel","status":"pending","activeForm":"Recalculant la dédup et vérifiant"},{"content":"Commit + push origin main","status":"pending","activeForm":"Committant et poussant"}],"verificationNudgeNeeded":false}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePc3oKRaWHeS3kMmRpvQ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_018QCKconWSXP9pqUnUvXLYr","name":"Read","input":{"file_path":"/Users/simon-pierreboucher/apps/immo-ka/frontend/src/api.ts","offset":22,"limit":50},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":418,"cache_read_input_tokens":64027,"cache_creation":{"ephemeral_5m_input_tokens":418,"ephemeral_1h_input_tokens":0},"output_tokens":25,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"3d5b1f56-8664-4f27-9715-d98cad5ca86c"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_018QCKconWSXP9pqUnUvXLYr","type":"tool_result","content":"22\texport interface Listing {\n23\t uid: string;\n24\t source: string;\n25\t external_id: string;\n26\t url: string;\n27\t title: string;\n28\t address: string;\n29\t sector: string;\n30\t city: string;\n31\t region: string;\n32\t property_type: string;\n33\t price: number | null;\n34\t price_label: string;\n35\t bedrooms: number | null;\n36\t bathrooms: number | null;\n37\t powder_rooms: number | null;\n38\t area_sqft: number | null;\n39\t lot_sqft: number | null;\n40\t year_built: number | null;\n41\t mls: string;\n42\t status: string;\n43\t broker_name: string;\n44\t broker_phone: string;\n45\t description: string;\n46\t features: string[];\n47\t details: ListingDetails;\n48\t images: string[];\n49\t lat: number | null;\n50\t lng: number | null;\n51\t price_history?: { ts: number; price: number | null }[];\n52\t poi?: Poi[]; // commodités de proximité (fiche seulement)\n53\t quartier?: Quartier | null; // stats de quartier (fiche seulement)\n54\t vraiprix?: VraiPrix | null; // estimation de valeur marchande (Vrai-Prix)\n55\t first_seen?: number;\n56\t last_seen?: number;\n57\t updated_at?: number;\n58\t active?: number;\n59\t}\n60\t\n61\texport interface Facets {\n62\t cities: string[];\n63\t sectors: string[];\n64\t property_types: string[];\n65\t sources: { source: string; n: number }[];\n66\t}\n67\t\n68\texport interface Source {\n69\t id: string;\n70\t name: string;\n71\t url: string;"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"6cd4636e-0ab3-4a3e-9bcd-5925acf5175f","timestamp":"2026-08-25T14:13:49.068Z","tool_use_result":{"type":"text","file":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/frontend/src/api.ts","content":"export interface Listing {\n uid: string;\n source: string;\n external_id: string;\n url: string;\n title: string;\n address: string;\n sector: string;\n city: string;\n region: string;\n property_type: string;\n price: number | null;\n price_label: string;\n bedrooms: number | null;\n bathrooms: number | null;\n powder_rooms: number | null;\n area_sqft: number | null;\n lot_sqft: number | null;\n year_built: number | null;\n mls: string;\n status: string;\n broker_name: string;\n broker_phone: string;\n description: string;\n features: string[];\n details: ListingDetails;\n images: string[];\n lat: number | null;\n lng: number | null;\n price_history?: { ts: number; price: number | null }[];\n poi?: Poi[]; // commodités de proximité (fiche seulement)\n quartier?: Quartier | null; // stats de quartier (fiche seulement)\n vraiprix?: VraiPrix | null; // estimation de valeur marchande (Vrai-Prix)\n first_seen?: number;\n last_seen?: number;\n updated_at?: number;\n active?: number;\n}\n\nexport interface Facets {\n cities: string[];\n sectors: string[];\n property_types: string[];\n sources: { source: string; n: number }[];\n}\n\nexport interface Source {\n id: string;\n name: string;\n url: string;","numLines":50,"startLine":22,"totalLines":551}}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"eacdc1f6-d7e2-4daa-9c17-ef0a7797ee3a","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePc4bBhYFQDgowRu4iV7","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01CPR5ATr9UCvTHUdcBDyTuv","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/frontend/src/api.ts","old_string":" price_history?: { ts: number; price: number | null }[];","new_string":" price_history?: { ts: number; price: number | null }[];\n duplicates?: DuplicateListing[]; // autres publications de la même propriété"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1218,"cache_read_input_tokens":64445,"cache_creation":{"ephemeral_5m_input_tokens":1218,"ephemeral_1h_input_tokens":0},"output_tokens":17,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"874728a7-3498-46e3-ba2a-172b4797e01c"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01CPR5ATr9UCvTHUdcBDyTuv","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/frontend/src/api.ts has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"f72f7e16-265c-45a6-8029-2f844bf01c38","timestamp":"2026-08-25T14:13:56.558Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/frontend/src/api.ts","oldString":" price_history?: { ts: number; price: number | null }[];","newString":" price_history?: { ts: number; price: number | null }[];\n duplicates?: DuplicateListing[]; // autres publications de la même propriété","originalFile":"// -----------------------------------------------------------------------------\n// Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n// Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n// api.ts : types + client API robuste (timeout, erreurs typées)\n// -----------------------------------------------------------------------------\n\nexport interface Room {\n nom?: string;\n niveau?: string;\n dimensions?: string;\n revetement?: string;\n}\n\n/** details : dictionnaire libre de caractéristiques Centris (libellé → valeur),\n * avec la clé spéciale `pieces` (liste des pièces + dimensions). */\nexport interface ListingDetails {\n pieces?: Room[];\n price_from?: boolean;\n [key: string]: unknown;\n}\n\nexport interface Listing {\n uid: string;\n source: string;\n external_id: string;\n url: string;\n title: string;\n address: string;\n sector: string;\n city: string;\n region: string;\n property_type: string;\n price: number | null;\n price_label: string;\n bedrooms: number | null;\n bathrooms: number | null;\n powder_rooms: number | null;\n area_sqft: number | null;\n lot_sqft: number | null;\n year_built: number | null;\n mls: string;\n status: string;\n broker_name: string;\n broker_phone: string;\n description: string;\n features: string[];\n details: ListingDetails;\n images: string[];\n lat: number | null;\n lng: number | null;\n price_history?: { ts: number; price: number | null }[];\n poi?: Poi[]; // commodités de proximité (fiche seulement)\n quartier?: Quartier | null; // stats de quartier (fiche seulement)\n vraiprix?: VraiPrix | null; // estimation de valeur marchande (Vrai-Prix)\n first_seen?: number;\n last_seen?: number;\n updated_at?: number;\n active?: number;\n}\n\nexport interface Facets {\n cities: string[];\n sectors: string[];\n property_types: string[];\n sources: { source: string; n: number }[];\n}\n\nexport interface Source {\n id: string;\n name: string;\n url: string;\n listing_url?: string;\n coverage?: string;\n type?: string;\n connector?: string | null;\n status: string;\n active_listings: number;\n last_sync: number | null;\n}\n\nexport interface Stats {\n total: number;\n sources: number;\n cities: number;\n avg_price: number | null;\n min_price: number | null;\n max_price: number | null;\n recent_syncs?: {\n source: string; ts: number; found: number; added: number;\n updated: number; removed: number; ok: number; message: string;\n }[];\n vraiprix?: {\n ensemble: VpBanniere | null;\n bannieres: VpBanniere[];\n };\n qualite?: Qualite;\n}\n\n/** Qualité des données (complétude, quarantaine, anomalies) — immoka/quality.py */\nexport interface Qualite {\n actives: number;\n publiees: number;\n quarantaine: number;\n completude_moyenne: number | null;\n anomalies: Record;\n par_source: {\n source: string; n: number; publiees: number;\n completude: number | null; anomalies: number;\n }[];\n}\n\n/** Écart prix demandé vs estimation Vrai-Prix, agrégé par bannière. */\nexport interface VpBanniere {\n banniere: string;\n n: number;\n median_delta_pct: number;\n p25: number;\n p75: number;\n pct_sur10: number;\n pct_juste: number;\n pct_sous5: number;\n}\n\n// --- Noms d'agences (jolis libellés) ----------------------------------------\nconst SOURCE_NAMES: Record = {};\nexport function registerSourceNames(sources: Source[]) {\n for (const s of sources) SOURCE_NAMES[s.id] = s.name;\n}\nexport function sourceName(id: string): string {\n if (SOURCE_NAMES[id]) return SOURCE_NAMES[id];\n // repli lisible pour les sous-agences RE/MAX générées (remax_ag_xxx)\n if (id.startsWith(\"remax_ag_\"))\n return \"RE/MAX \" + id.slice(9).replace(/_/g, \" \").replace(/\\b\\w/g, (c) => c.toUpperCase());\n return id.replace(/_/g, \" \").replace(/\\b\\w/g, (c) => c.toUpperCase());\n}\n\nasync function get(path: string): Promise {\n const ctrl = new AbortController();\n const timer = setTimeout(() => ctrl.abort(), 25000);\n try {\n const res = await fetch(path, { signal: ctrl.signal });\n if (!res.ok) throw new Error(`API ${res.status} — ${path}`);\n return (await res.json()) as T;\n } finally {\n clearTimeout(timer);\n }\n}\n\nexport interface ListingFilters {\n city?: string;\n sector?: string;\n region?: string;\n property_type?: string;\n source?: string;\n price_min?: string;\n price_max?: string;\n bedrooms_min?: string;\n bathrooms_min?: string;\n area_min?: string;\n q?: string;\n sort?: string; // price_asc | price_desc | recent\n}\n\nexport function listingParams(f: ListingFilters): URLSearchParams {\n const params = new URLSearchParams();\n for (const [k, v] of Object.entries(f)) if (v) params.set(k, v);\n return params;\n}\n\nexport function fetchListings(f: ListingFilters, limit = 60, offset = 0) {\n const params = listingParams(f);\n params.set(\"limit\", String(limit));\n params.set(\"offset\", String(offset));\n return get<{ total: number; count: number; listings: Listing[] }>(\n `/api/listings?${params}`);\n}\n\nexport const fetchListing = (uid: string) =>\n get(`/api/listings/${encodeURIComponent(uid)}`);\nexport const fetchFacets = (city?: string) =>\n get(`/api/facets${city ? `?city=${encodeURIComponent(city)}` : \"\"}`);\nexport const fetchSources = () => get<{ sources: Source[] }>(\"/api/sources\");\nexport const fetchStats = () => get(\"/api/stats\");\n\nexport interface SubAgency { name: string; count: number; sources: string[] }\nexport interface Franchise {\n franchise: string;\n total: number;\n sub_agencies: number;\n agencies: SubAgency[];\n}\nexport const fetchAgencies = () =>\n get<{ franchises: Franchise[] }>(\"/api/agencies\");\n\n// --- Formatage --------------------------------------------------------------\nexport const fmtPrice = (p: number | null, label?: string) =>\n p != null\n ? p.toLocaleString(\"fr-CA\", { maximumFractionDigits: 0 }) + \" $\"\n : label || \"Prix sur demande\";\n\nexport const fmtArea = (a: number | null): string | null =>\n a != null ? `${Math.round(a).toLocaleString(\"fr-CA\")} pi²` : null;\n\nexport const fmtDate = (ts: number): string =>\n new Date(ts * 1000).toLocaleDateString(\"fr-CA\", {\n day: \"numeric\", month: \"long\", year: \"numeric\",\n });\n\n// --- Vrai-Prix : estimation de valeur marchande ------------------------------\nexport interface VraiPrix {\n id: string;\n value: number | null;\n low: number | null;\n high: number | null;\n confidence_pct: number | null;\n confidence: string | null; // A | B | C | D\n url: string; // page d'analyse détaillée\n}\n\n// --- Quartier (recensement 2021, proximité StatCan, chaleur INSPQ, crime) ----\nexport interface Poi { cat: string; name: string; dist_m: number }\nexport interface Quartier {\n dauid?: string | null;\n demographie?: {\n population: number | null; densite: number | null; age_median: number | null;\n revenu_median: number | null; pct_locataires: number | null;\n loyer_moyen: number | null; pct_francais: number | null; pct_univ: number | null;\n };\n proximite?: Record;\n defavorisation?: { quintile_materiel: number | null; quintile_social: number | null };\n chaleur?: { classe: number; ecart: number | null };\n crime?:\n | { type: \"points\"; rayon_m: number; douze_mois: number; douze_mois_precedents: number;\n categories?: { nom: string; n: number; n_prec: number }[] }\n | { type: \"igc\"; ville: string; annee: number; indice: number; indice_canada: number | null };\n}\n\n// -----------------------------------------------------------------------------\n// Compte KA ID (SSO hub groupe-ka.com) + favoris « Mon univers Ka »\n// -----------------------------------------------------------------------------\nexport type Socials = Partial>;\n\nexport interface User {\n sub: string;\n email: string;\n name: string;\n picture?: string;\n ka_id?: string;\n provider?: string; // \"ka-id\" | \"google\"\n created_at?: number | null; // epoch (s)\n last_login?: number | null; // epoch (s)\n // profil enrichi par le HUB Groupe KA (source de vérité — groupe-ka.com/compte)\n bio?: string;\n city?: string;\n phone?: string;\n website?: string;\n socials?: Socials;\n public?: boolean;\n role_label?: string;\n job_title?: string;\n company?: string;\n age?: number | null;\n public_url?: string;\n profile_source?: string; // \"groupe-ka\" | \"local\"\n}\n\n/** Profil de session ({user: null} si non connecté ; `enabled` = SSO configuré). */\nexport const fetchMe = () => get<{ user: User | null; enabled: boolean }>(\"/api/auth/me\");\n\nexport const logout = () => fetch(\"/api/auth/logout\", { method: \"POST\" });\n\n/** Item favori tel qu'attendu par le hub (voir immoka/favorites.py). */\nexport interface FavItem {\n item_id: string;\n title: string;\n subtitle: string;\n price_label: string;\n image_url: string;\n url: string;\n}\n\nexport function favItemFromListing(l: Listing): FavItem {\n return {\n item_id: l.uid,\n title: l.title || l.address || l.property_type || \"Propriété\",\n subtitle: [l.city, l.region].filter(Boolean).join(\", \"),\n price_label: l.price_label || fmtPrice(l.price),\n image_url: l.images?.[0] ?? \"\",\n url: `/propriete/${l.uid}`,\n };\n}\n\nexport const fetchFavorites = () =>\n get<{ ids: string[]; items: FavItem[] }>(\"/api/favorites\");\n\nexport async function toggleFavorite(on: boolean, item: FavItem) {\n const res = await fetch(\"/api/favorites/toggle\", {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({ on, item }),\n });\n if (!res.ok) throw new Error(`favoris ${res.status}`);\n return (await res.json()) as { ok: boolean; on: boolean };\n}\n\n// -----------------------------------------------------------------------------\n// Taux hypothécaires (immoka/mortgage) — taux réels observés chez les banques\n// -----------------------------------------------------------------------------\nexport interface MortgageRate {\n provider: string;\n institution: string;\n product_key: string;\n product_name: string | null;\n rate_type: \"fixed\" | \"variable\" | \"adjustable\" | \"other\";\n term_months: number;\n kind: \"posted\" | \"special\";\n rate: number;\n apr: number | null;\n insured_status: \"insured\" | \"insurable\" | \"uninsured\" | \"unknown\";\n purpose: string;\n conditions: string | null;\n source_url: string | null;\n last_checked: number;\n age_minutes: number;\n stale: boolean;\n}\n\nexport interface MortgageBest extends MortgageRate {\n median_rate: number | null;\n institutions_count: number;\n per_institution: MortgageRate[];\n}\n\nexport interface MortgageMarket {\n rate_type: string;\n term_months: number;\n best: number;\n best_provider: string;\n best_institution: string;\n best_kind: string;\n median: number | null;\n spread: number | null;\n institutions_count: number;\n var_7d: number | null;\n var_30d: number | null;\n var_90d: number | null;\n lowest_6m: number | null;\n}\n\nexport interface MortgageIntelligence {\n products: MortgageMarket[];\n prime_rates: { institution: string; rate: number; product_name: string;\n age_minutes: number }[];\n}\n\nexport interface MortgageHistoryRow {\n provider: string; institution: string; product_name: string | null;\n kind: string; rate: number; insured_status: string;\n valid_from: number; valid_to: number | null; last_checked: number;\n source_url: string | null;\n}\n\nexport interface MortgageProviderHealth {\n provider: string; institution: string; source_url: string | null;\n level: \"OK\" | \"WARNING\" | \"ERROR\"; status: string | null;\n age_minutes: number; current_products: number; last_data_at: number | null;\n}\n\nexport interface MortgageRateSource {\n provider: string; institution: string; product_name: string | null;\n kind: string; rate: number; apr?: number | null; insured_status?: string;\n source_url: string | null; last_checked?: number;\n age_minutes: number; stale: boolean;\n}\n\nexport interface MortgageInsurance {\n required: boolean; eligible: boolean; premium: number; premium_rate: number;\n loan_before: number; total_mortgage: number; qc_tax: number;\n ltv: number | null; issues: string[];\n}\n\nexport interface MortgageCalc {\n inputs: {\n price: number; down_payment: number; down_payment_pct: number;\n rate: number; rate_type: string; term_months: number;\n amortization_years: number; frequency: string; compounding: string;\n };\n insurance: MortgageInsurance;\n principal: number;\n payment: number;\n payment_monthly_equivalent: number;\n qualifying: { rate: number; payment: number; note: string };\n term: {\n payment: number; frequency: string; payments_per_year: number;\n payments_in_term: number; annual_cost: number; principal_paid: number;\n interest_paid: number; balance_end_of_term: number; paid_off: boolean;\n };\n stress: { bump: number; rate: number; payment: number }[];\n renewal: {\n balance_at_renewal: number; remaining_amortization_years: number;\n scenarios: { bump: number; rate: number; payment: number }[];\n };\n payoff_years: number;\n rate_source: MortgageRateSource | null;\n annual: { year: number; payment: number; interest: number;\n principal: number; balance: number }[];\n ratios?: { gds: number | null; tds: number | null;\n gds_ok: boolean | null; tds_ok: boolean | null };\n}\n\nexport interface MortgageCalcInput {\n price: number;\n down_payment?: number;\n down_payment_pct?: number;\n amortization_years?: number;\n term_months?: number;\n frequency?: string;\n rate_type?: \"fixed\" | \"variable\";\n rate?: number;\n income?: number;\n property_tax_monthly?: number;\n heating_monthly?: number;\n condo_fees_monthly?: number;\n other_debts_monthly?: number;\n}\n\nasync function post(path: string, body: unknown): Promise {\n const ctrl = new AbortController();\n const timer = setTimeout(() => ctrl.abort(), 25000);\n try {\n const res = await fetch(path, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify(body),\n signal: ctrl.signal,\n });\n if (!res.ok) throw new Error(`API ${res.status} — ${path}`);\n return (await res.json()) as T;\n } finally {\n clearTimeout(timer);\n }\n}\n\nexport const fetchMortgageIntelligence = () =>\n get(\"/api/mortgage/intelligence\");\n\nexport const fetchMortgageBest = (rateType: string, termMonths: number) =>\n get(\n `/api/mortgage/rates/best?rate_type=${rateType}&term_months=${termMonths}`);\n\nexport const fetchMortgageHistory = (\n rateType: string, termMonths: number, days = 365, kind?: string,\n) =>\n get<{ count: number; days: number; history: MortgageHistoryRow[] }>(\n `/api/mortgage/rates/history?rate_type=${rateType}` +\n `&term_months=${termMonths}&days=${days}${kind ? `&kind=${kind}` : \"\"}`);\n\nexport const fetchMortgageProviders = () =>\n get<{ providers: MortgageProviderHealth[]; registered: string[] }>(\n \"/api/mortgage/providers\");\n\nexport const calculateMortgage = (input: MortgageCalcInput) =>\n post(\"/api/mortgage/calculate\", input);\n\n/** 4.19 -> « 4,19 % » */\nexport const fmtRate = (r: number | null | undefined): string =>\n r == null ? \"—\" : `${r.toFixed(2).replace(\".\", \",\")} %`;\n\nexport interface InondationZone {\n type: string; severite: \"eleve\" | \"modere\" | \"present\";\n recurrence: string; distance_m: number; date_rapport: string | null;\n}\n\nexport interface Inondation {\n statut: \"en_zone\" | \"a_proximite\" | \"hors_zone\" | \"non_cartographie\";\n severite: \"eleve\" | \"modere\" | \"present\" | null;\n couvert: boolean;\n zones: InondationZone[];\n}\n\n/** Risque d'inondation BDZI (gouv. du Québec) au point de la propriété. */\nexport const fetchInondation = (lat: number, lng: number) =>\n get(`/api/inondation?lat=${lat}&lng=${lng}`);\n\n/** 250 -> « 250 m », 1240 -> « 1,2 km » */\nexport const fmtDist = (m: number): string =>\n m < 1000 ? `${Math.round(m / 10) * 10} m` : `${(m / 1000).toFixed(1).replace(\".\", \",\")} km`;\n\nexport interface AirMesure {\n moyenne: number; annee: number; n: number; unite: string;\n ref: number | null; ref_nom: string | null;\n}\n\nexport interface AirNearby {\n station: string | null; ville?: string; distance_km?: number;\n mesures: Record;\n}\n\n/** Qualité de l'air : station RSQAQ la plus proche (MELCCFP). */\nexport const fetchAir = (lat: number, lng: number) =>\n get(`/api/air?lat=${lat}&lng=${lng}`);\n\nexport interface GazStation {\n nom: string; adresse: string; dist_m: number;\n regulier: number | null; super: number | null; diesel: number | null;\n moins_chere: boolean;\n}\n\nexport interface GazNearby {\n n: number; rayon_m: number; mediane_regulier: number | null;\n min_regulier: number | null; stations: GazStation[]; maj: string | null;\n}\n\n/** Stations-service à proximité et prix courants (gazquebec.ca). */\nexport const fetchGaz = (lat: number, lng: number) =>\n get(`/api/gaz?lat=${lat}&lng=${lng}`);\n\nexport interface CommerceItem {\n id: string; commerce: string; nom: string; adresse: string;\n dist_m: number; lat: number; lng: number;\n}\n\nexport interface CommercesNearby {\n n: number; commerces: CommerceItem[]; transit?: CommerceItem[];\n}\n\n/** Grands commerces + métro/bus les plus proches (Mapbox / OSM). */\nexport const fetchCommerces = (lat: number, lng: number) =>\n get(`/api/commerces?lat=${lat}&lng=${lng}`);\n\nexport interface HydroEstimate {\n disponible: boolean; raison?: string; adresse?: string;\n cout_annuel?: number; cout_mensuel?: number; kwh_annuel?: number; cache?: boolean; en_attente?: boolean;\n}\n\n/** Coût d'électricité estimé à l'adresse (outil public Hydro-Québec). */\nexport const fetchHydro = (\n adresse: string,\n opts: { uid?: string; lat?: number | null; lng?: number | null } = {},\n solve = false,\n) => {\n const q = new URLSearchParams({ adresse });\n if (opts.uid) q.set(\"uid\", opts.uid);\n if (opts.lat != null) q.set(\"lat\", String(opts.lat));\n if (opts.lng != null) q.set(\"lng\", String(opts.lng));\n if (solve) q.set(\"solve\", \"1\");\n return get(`/api/hydro?${q.toString()}`);\n};\n","structuredPatch":[{"oldStart":49,"oldLines":6,"newStart":49,"newLines":7,"lines":[" lat: number | null;"," lng: number | null;"," price_history?: { ts: number; price: number | null }[];","+ duplicates?: DuplicateListing[]; // autres publications de la même propriété"," poi?: Poi[]; // commodités de proximité (fiche seulement)"," quartier?: Quartier | null; // stats de quartier (fiche seulement)"," vraiprix?: VraiPrix | null; // estimation de valeur marchande (Vrai-Prix)"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"8e86d2ae-37f4-42f7-848d-8e97f31b336c","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePc58iGdFYhH4hR7iGT9","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01WJMeHMyL4sUxttfbdykXKS","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/frontend/src/api.ts","old_string":"export interface Facets {","new_string":"export interface DuplicateListing {\n uid: string;\n source: string;\n url: string;\n broker_name: string;\n agency: string;\n price_label: string;\n}\n\nexport interface Facets {"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":266,"cache_read_input_tokens":65663,"cache_creation":{"ephemeral_5m_input_tokens":266,"ephemeral_1h_input_tokens":0},"output_tokens":17,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"96ddbddd-a6fe-4f85-89a6-88a39f186041"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01WJMeHMyL4sUxttfbdykXKS","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/frontend/src/api.ts has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"cf1796fb-d268-407b-890d-9818e63f2362","timestamp":"2026-08-25T14:14:04.585Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/frontend/src/api.ts","oldString":"export interface Facets {","newString":"export interface DuplicateListing {\n uid: string;\n source: string;\n url: string;\n broker_name: string;\n agency: string;\n price_label: string;\n}\n\nexport interface Facets {","originalFile":"// -----------------------------------------------------------------------------\n// Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n// Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n// api.ts : types + client API robuste (timeout, erreurs typées)\n// -----------------------------------------------------------------------------\n\nexport interface Room {\n nom?: string;\n niveau?: string;\n dimensions?: string;\n revetement?: string;\n}\n\n/** details : dictionnaire libre de caractéristiques Centris (libellé → valeur),\n * avec la clé spéciale `pieces` (liste des pièces + dimensions). */\nexport interface ListingDetails {\n pieces?: Room[];\n price_from?: boolean;\n [key: string]: unknown;\n}\n\nexport interface Listing {\n uid: string;\n source: string;\n external_id: string;\n url: string;\n title: string;\n address: string;\n sector: string;\n city: string;\n region: string;\n property_type: string;\n price: number | null;\n price_label: string;\n bedrooms: number | null;\n bathrooms: number | null;\n powder_rooms: number | null;\n area_sqft: number | null;\n lot_sqft: number | null;\n year_built: number | null;\n mls: string;\n status: string;\n broker_name: string;\n broker_phone: string;\n description: string;\n features: string[];\n details: ListingDetails;\n images: string[];\n lat: number | null;\n lng: number | null;\n price_history?: { ts: number; price: number | null }[];\n duplicates?: DuplicateListing[]; // autres publications de la même propriété\n poi?: Poi[]; // commodités de proximité (fiche seulement)\n quartier?: Quartier | null; // stats de quartier (fiche seulement)\n vraiprix?: VraiPrix | null; // estimation de valeur marchande (Vrai-Prix)\n first_seen?: number;\n last_seen?: number;\n updated_at?: number;\n active?: number;\n}\n\nexport interface Facets {\n cities: string[];\n sectors: string[];\n property_types: string[];\n sources: { source: string; n: number }[];\n}\n\nexport interface Source {\n id: string;\n name: string;\n url: string;\n listing_url?: string;\n coverage?: string;\n type?: string;\n connector?: string | null;\n status: string;\n active_listings: number;\n last_sync: number | null;\n}\n\nexport interface Stats {\n total: number;\n sources: number;\n cities: number;\n avg_price: number | null;\n min_price: number | null;\n max_price: number | null;\n recent_syncs?: {\n source: string; ts: number; found: number; added: number;\n updated: number; removed: number; ok: number; message: string;\n }[];\n vraiprix?: {\n ensemble: VpBanniere | null;\n bannieres: VpBanniere[];\n };\n qualite?: Qualite;\n}\n\n/** Qualité des données (complétude, quarantaine, anomalies) — immoka/quality.py */\nexport interface Qualite {\n actives: number;\n publiees: number;\n quarantaine: number;\n completude_moyenne: number | null;\n anomalies: Record;\n par_source: {\n source: string; n: number; publiees: number;\n completude: number | null; anomalies: number;\n }[];\n}\n\n/** Écart prix demandé vs estimation Vrai-Prix, agrégé par bannière. */\nexport interface VpBanniere {\n banniere: string;\n n: number;\n median_delta_pct: number;\n p25: number;\n p75: number;\n pct_sur10: number;\n pct_juste: number;\n pct_sous5: number;\n}\n\n// --- Noms d'agences (jolis libellés) ----------------------------------------\nconst SOURCE_NAMES: Record = {};\nexport function registerSourceNames(sources: Source[]) {\n for (const s of sources) SOURCE_NAMES[s.id] = s.name;\n}\nexport function sourceName(id: string): string {\n if (SOURCE_NAMES[id]) return SOURCE_NAMES[id];\n // repli lisible pour les sous-agences RE/MAX générées (remax_ag_xxx)\n if (id.startsWith(\"remax_ag_\"))\n return \"RE/MAX \" + id.slice(9).replace(/_/g, \" \").replace(/\\b\\w/g, (c) => c.toUpperCase());\n return id.replace(/_/g, \" \").replace(/\\b\\w/g, (c) => c.toUpperCase());\n}\n\nasync function get(path: string): Promise {\n const ctrl = new AbortController();\n const timer = setTimeout(() => ctrl.abort(), 25000);\n try {\n const res = await fetch(path, { signal: ctrl.signal });\n if (!res.ok) throw new Error(`API ${res.status} — ${path}`);\n return (await res.json()) as T;\n } finally {\n clearTimeout(timer);\n }\n}\n\nexport interface ListingFilters {\n city?: string;\n sector?: string;\n region?: string;\n property_type?: string;\n source?: string;\n price_min?: string;\n price_max?: string;\n bedrooms_min?: string;\n bathrooms_min?: string;\n area_min?: string;\n q?: string;\n sort?: string; // price_asc | price_desc | recent\n}\n\nexport function listingParams(f: ListingFilters): URLSearchParams {\n const params = new URLSearchParams();\n for (const [k, v] of Object.entries(f)) if (v) params.set(k, v);\n return params;\n}\n\nexport function fetchListings(f: ListingFilters, limit = 60, offset = 0) {\n const params = listingParams(f);\n params.set(\"limit\", String(limit));\n params.set(\"offset\", String(offset));\n return get<{ total: number; count: number; listings: Listing[] }>(\n `/api/listings?${params}`);\n}\n\nexport const fetchListing = (uid: string) =>\n get(`/api/listings/${encodeURIComponent(uid)}`);\nexport const fetchFacets = (city?: string) =>\n get(`/api/facets${city ? `?city=${encodeURIComponent(city)}` : \"\"}`);\nexport const fetchSources = () => get<{ sources: Source[] }>(\"/api/sources\");\nexport const fetchStats = () => get(\"/api/stats\");\n\nexport interface SubAgency { name: string; count: number; sources: string[] }\nexport interface Franchise {\n franchise: string;\n total: number;\n sub_agencies: number;\n agencies: SubAgency[];\n}\nexport const fetchAgencies = () =>\n get<{ franchises: Franchise[] }>(\"/api/agencies\");\n\n// --- Formatage --------------------------------------------------------------\nexport const fmtPrice = (p: number | null, label?: string) =>\n p != null\n ? p.toLocaleString(\"fr-CA\", { maximumFractionDigits: 0 }) + \" $\"\n : label || \"Prix sur demande\";\n\nexport const fmtArea = (a: number | null): string | null =>\n a != null ? `${Math.round(a).toLocaleString(\"fr-CA\")} pi²` : null;\n\nexport const fmtDate = (ts: number): string =>\n new Date(ts * 1000).toLocaleDateString(\"fr-CA\", {\n day: \"numeric\", month: \"long\", year: \"numeric\",\n });\n\n// --- Vrai-Prix : estimation de valeur marchande ------------------------------\nexport interface VraiPrix {\n id: string;\n value: number | null;\n low: number | null;\n high: number | null;\n confidence_pct: number | null;\n confidence: string | null; // A | B | C | D\n url: string; // page d'analyse détaillée\n}\n\n// --- Quartier (recensement 2021, proximité StatCan, chaleur INSPQ, crime) ----\nexport interface Poi { cat: string; name: string; dist_m: number }\nexport interface Quartier {\n dauid?: string | null;\n demographie?: {\n population: number | null; densite: number | null; age_median: number | null;\n revenu_median: number | null; pct_locataires: number | null;\n loyer_moyen: number | null; pct_francais: number | null; pct_univ: number | null;\n };\n proximite?: Record;\n defavorisation?: { quintile_materiel: number | null; quintile_social: number | null };\n chaleur?: { classe: number; ecart: number | null };\n crime?:\n | { type: \"points\"; rayon_m: number; douze_mois: number; douze_mois_precedents: number;\n categories?: { nom: string; n: number; n_prec: number }[] }\n | { type: \"igc\"; ville: string; annee: number; indice: number; indice_canada: number | null };\n}\n\n// -----------------------------------------------------------------------------\n// Compte KA ID (SSO hub groupe-ka.com) + favoris « Mon univers Ka »\n// -----------------------------------------------------------------------------\nexport type Socials = Partial>;\n\nexport interface User {\n sub: string;\n email: string;\n name: string;\n picture?: string;\n ka_id?: string;\n provider?: string; // \"ka-id\" | \"google\"\n created_at?: number | null; // epoch (s)\n last_login?: number | null; // epoch (s)\n // profil enrichi par le HUB Groupe KA (source de vérité — groupe-ka.com/compte)\n bio?: string;\n city?: string;\n phone?: string;\n website?: string;\n socials?: Socials;\n public?: boolean;\n role_label?: string;\n job_title?: string;\n company?: string;\n age?: number | null;\n public_url?: string;\n profile_source?: string; // \"groupe-ka\" | \"local\"\n}\n\n/** Profil de session ({user: null} si non connecté ; `enabled` = SSO configuré). */\nexport const fetchMe = () => get<{ user: User | null; enabled: boolean }>(\"/api/auth/me\");\n\nexport const logout = () => fetch(\"/api/auth/logout\", { method: \"POST\" });\n\n/** Item favori tel qu'attendu par le hub (voir immoka/favorites.py). */\nexport interface FavItem {\n item_id: string;\n title: string;\n subtitle: string;\n price_label: string;\n image_url: string;\n url: string;\n}\n\nexport function favItemFromListing(l: Listing): FavItem {\n return {\n item_id: l.uid,\n title: l.title || l.address || l.property_type || \"Propriété\",\n subtitle: [l.city, l.region].filter(Boolean).join(\", \"),\n price_label: l.price_label || fmtPrice(l.price),\n image_url: l.images?.[0] ?? \"\",\n url: `/propriete/${l.uid}`,\n };\n}\n\nexport const fetchFavorites = () =>\n get<{ ids: string[]; items: FavItem[] }>(\"/api/favorites\");\n\nexport async function toggleFavorite(on: boolean, item: FavItem) {\n const res = await fetch(\"/api/favorites/toggle\", {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({ on, item }),\n });\n if (!res.ok) throw new Error(`favoris ${res.status}`);\n return (await res.json()) as { ok: boolean; on: boolean };\n}\n\n// -----------------------------------------------------------------------------\n// Taux hypothécaires (immoka/mortgage) — taux réels observés chez les banques\n// -----------------------------------------------------------------------------\nexport interface MortgageRate {\n provider: string;\n institution: string;\n product_key: string;\n product_name: string | null;\n rate_type: \"fixed\" | \"variable\" | \"adjustable\" | \"other\";\n term_months: number;\n kind: \"posted\" | \"special\";\n rate: number;\n apr: number | null;\n insured_status: \"insured\" | \"insurable\" | \"uninsured\" | \"unknown\";\n purpose: string;\n conditions: string | null;\n source_url: string | null;\n last_checked: number;\n age_minutes: number;\n stale: boolean;\n}\n\nexport interface MortgageBest extends MortgageRate {\n median_rate: number | null;\n institutions_count: number;\n per_institution: MortgageRate[];\n}\n\nexport interface MortgageMarket {\n rate_type: string;\n term_months: number;\n best: number;\n best_provider: string;\n best_institution: string;\n best_kind: string;\n median: number | null;\n spread: number | null;\n institutions_count: number;\n var_7d: number | null;\n var_30d: number | null;\n var_90d: number | null;\n lowest_6m: number | null;\n}\n\nexport interface MortgageIntelligence {\n products: MortgageMarket[];\n prime_rates: { institution: string; rate: number; product_name: string;\n age_minutes: number }[];\n}\n\nexport interface MortgageHistoryRow {\n provider: string; institution: string; product_name: string | null;\n kind: string; rate: number; insured_status: string;\n valid_from: number; valid_to: number | null; last_checked: number;\n source_url: string | null;\n}\n\nexport interface MortgageProviderHealth {\n provider: string; institution: string; source_url: string | null;\n level: \"OK\" | \"WARNING\" | \"ERROR\"; status: string | null;\n age_minutes: number; current_products: number; last_data_at: number | null;\n}\n\nexport interface MortgageRateSource {\n provider: string; institution: string; product_name: string | null;\n kind: string; rate: number; apr?: number | null; insured_status?: string;\n source_url: string | null; last_checked?: number;\n age_minutes: number; stale: boolean;\n}\n\nexport interface MortgageInsurance {\n required: boolean; eligible: boolean; premium: number; premium_rate: number;\n loan_before: number; total_mortgage: number; qc_tax: number;\n ltv: number | null; issues: string[];\n}\n\nexport interface MortgageCalc {\n inputs: {\n price: number; down_payment: number; down_payment_pct: number;\n rate: number; rate_type: string; term_months: number;\n amortization_years: number; frequency: string; compounding: string;\n };\n insurance: MortgageInsurance;\n principal: number;\n payment: number;\n payment_monthly_equivalent: number;\n qualifying: { rate: number; payment: number; note: string };\n term: {\n payment: number; frequency: string; payments_per_year: number;\n payments_in_term: number; annual_cost: number; principal_paid: number;\n interest_paid: number; balance_end_of_term: number; paid_off: boolean;\n };\n stress: { bump: number; rate: number; payment: number }[];\n renewal: {\n balance_at_renewal: number; remaining_amortization_years: number;\n scenarios: { bump: number; rate: number; payment: number }[];\n };\n payoff_years: number;\n rate_source: MortgageRateSource | null;\n annual: { year: number; payment: number; interest: number;\n principal: number; balance: number }[];\n ratios?: { gds: number | null; tds: number | null;\n gds_ok: boolean | null; tds_ok: boolean | null };\n}\n\nexport interface MortgageCalcInput {\n price: number;\n down_payment?: number;\n down_payment_pct?: number;\n amortization_years?: number;\n term_months?: number;\n frequency?: string;\n rate_type?: \"fixed\" | \"variable\";\n rate?: number;\n income?: number;\n property_tax_monthly?: number;\n heating_monthly?: number;\n condo_fees_monthly?: number;\n other_debts_monthly?: number;\n}\n\nasync function post(path: string, body: unknown): Promise {\n const ctrl = new AbortController();\n const timer = setTimeout(() => ctrl.abort(), 25000);\n try {\n const res = await fetch(path, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify(body),\n signal: ctrl.signal,\n });\n if (!res.ok) throw new Error(`API ${res.status} — ${path}`);\n return (await res.json()) as T;\n } finally {\n clearTimeout(timer);\n }\n}\n\nexport const fetchMortgageIntelligence = () =>\n get(\"/api/mortgage/intelligence\");\n\nexport const fetchMortgageBest = (rateType: string, termMonths: number) =>\n get(\n `/api/mortgage/rates/best?rate_type=${rateType}&term_months=${termMonths}`);\n\nexport const fetchMortgageHistory = (\n rateType: string, termMonths: number, days = 365, kind?: string,\n) =>\n get<{ count: number; days: number; history: MortgageHistoryRow[] }>(\n `/api/mortgage/rates/history?rate_type=${rateType}` +\n `&term_months=${termMonths}&days=${days}${kind ? `&kind=${kind}` : \"\"}`);\n\nexport const fetchMortgageProviders = () =>\n get<{ providers: MortgageProviderHealth[]; registered: string[] }>(\n \"/api/mortgage/providers\");\n\nexport const calculateMortgage = (input: MortgageCalcInput) =>\n post(\"/api/mortgage/calculate\", input);\n\n/** 4.19 -> « 4,19 % » */\nexport const fmtRate = (r: number | null | undefined): string =>\n r == null ? \"—\" : `${r.toFixed(2).replace(\".\", \",\")} %`;\n\nexport interface InondationZone {\n type: string; severite: \"eleve\" | \"modere\" | \"present\";\n recurrence: string; distance_m: number; date_rapport: string | null;\n}\n\nexport interface Inondation {\n statut: \"en_zone\" | \"a_proximite\" | \"hors_zone\" | \"non_cartographie\";\n severite: \"eleve\" | \"modere\" | \"present\" | null;\n couvert: boolean;\n zones: InondationZone[];\n}\n\n/** Risque d'inondation BDZI (gouv. du Québec) au point de la propriété. */\nexport const fetchInondation = (lat: number, lng: number) =>\n get(`/api/inondation?lat=${lat}&lng=${lng}`);\n\n/** 250 -> « 250 m », 1240 -> « 1,2 km » */\nexport const fmtDist = (m: number): string =>\n m < 1000 ? `${Math.round(m / 10) * 10} m` : `${(m / 1000).toFixed(1).replace(\".\", \",\")} km`;\n\nexport interface AirMesure {\n moyenne: number; annee: number; n: number; unite: string;\n ref: number | null; ref_nom: string | null;\n}\n\nexport interface AirNearby {\n station: string | null; ville?: string; distance_km?: number;\n mesures: Record;\n}\n\n/** Qualité de l'air : station RSQAQ la plus proche (MELCCFP). */\nexport const fetchAir = (lat: number, lng: number) =>\n get(`/api/air?lat=${lat}&lng=${lng}`);\n\nexport interface GazStation {\n nom: string; adresse: string; dist_m: number;\n regulier: number | null; super: number | null; diesel: number | null;\n moins_chere: boolean;\n}\n\nexport interface GazNearby {\n n: number; rayon_m: number; mediane_regulier: number | null;\n min_regulier: number | null; stations: GazStation[]; maj: string | null;\n}\n\n/** Stations-service à proximité et prix courants (gazquebec.ca). */\nexport const fetchGaz = (lat: number, lng: number) =>\n get(`/api/gaz?lat=${lat}&lng=${lng}`);\n\nexport interface CommerceItem {\n id: string; commerce: string; nom: string; adresse: string;\n dist_m: number; lat: number; lng: number;\n}\n\nexport interface CommercesNearby {\n n: number; commerces: CommerceItem[]; transit?: CommerceItem[];\n}\n\n/** Grands commerces + métro/bus les plus proches (Mapbox / OSM). */\nexport const fetchCommerces = (lat: number, lng: number) =>\n get(`/api/commerces?lat=${lat}&lng=${lng}`);\n\nexport interface HydroEstimate {\n disponible: boolean; raison?: string; adresse?: string;\n cout_annuel?: number; cout_mensuel?: number; kwh_annuel?: number; cache?: boolean; en_attente?: boolean;\n}\n\n/** Coût d'électricité estimé à l'adresse (outil public Hydro-Québec). */\nexport const fetchHydro = (\n adresse: string,\n opts: { uid?: string; lat?: number | null; lng?: number | null } = {},\n solve = false,\n) => {\n const q = new URLSearchParams({ adresse });\n if (opts.uid) q.set(\"uid\", opts.uid);\n if (opts.lat != null) q.set(\"lat\", String(opts.lat));\n if (opts.lng != null) q.set(\"lng\", String(opts.lng));\n if (solve) q.set(\"solve\", \"1\");\n return get(`/api/hydro?${q.toString()}`);\n};\n","structuredPatch":[{"oldStart":59,"oldLines":6,"newStart":59,"newLines":15,"lines":[" active?: number;"," }"," ","+export interface DuplicateListing {","+ uid: string;","+ source: string;","+ url: string;","+ broker_name: string;","+ agency: string;","+ price_label: string;","+}","+"," export interface Facets {"," cities: string[];"," sectors: string[];"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"a453c00e-684a-4d34-a1fa-5b65d7258d94","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePc5ixoHX1nzHCVnYXCT","type":"message","role":"assistant","content":[{"type":"text","text":"Maintenant la box dans Listing.tsx. Je relis la zone du bloc courtier/CTA."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":268,"cache_read_input_tokens":65929,"cache_creation":{"ephemeral_5m_input_tokens":268,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"a0e73140-1764-4b7e-bd15-fcbcd37b7be3"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePc5ixoHX1nzHCVnYXCT","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01SJegwdAUEGZCiZgNbo18e7","name":"Read","input":{"file_path":"/Users/simon-pierreboucher/apps/immo-ka/frontend/src/pages/Listing.tsx","offset":355,"limit":65},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":268,"cache_read_input_tokens":65929,"cache_creation":{"ephemeral_5m_input_tokens":268,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"29b1a794-9b35-4d0d-b866-52c59a1b7ecc"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01SJegwdAUEGZCiZgNbo18e7","type":"tool_result","content":"355\t
\n356\t )}\n357\t
\n358\t );\n359\t })()}\n360\t {l.price != null && (\n361\t (() => {\n362\t const diff = l.price - (l.vraiprix!.value as number);\n363\t const pct = Math.round((diff / (l.vraiprix!.value as number)) * 100);\n364\t const cls = diff > 0 ? \"over\" : \"under\";\n365\t const txt = diff > 0\n366\t ? `Prix demandé ${pct}% au-dessus de l'estimation`\n367\t : `Prix demandé ${Math.abs(pct)}% sous l'estimation`;\n368\t if (Math.abs(pct) > 60) return null; // prix non comparable (loyer, terrain…)\n369\t return Math.abs(pct) >= 1\n370\t ?
{diff > 0 ? \"▲\" : \"▼\"} {txt}
\n371\t :
≈ Prix aligné sur l'estimation
;\n372\t })()\n373\t )}\n374\t \n375\t Voir l'analyse détaillée ↗\n376\t \n377\t
\n378\t )}\n379\t\n380\t {(l.broker_name || l.broker_phone) && (\n381\t
\n382\t
Courtier
\n383\t {l.broker_name &&
{l.broker_name}
}\n384\t {l.broker_phone && {l.broker_phone}}\n385\t
\n386\t )}\n387\t\n388\t \n389\t Voir l'annonce chez {sourceName(l.source)} \n390\t \n391\t \n392\t Télécharger la fiche (PDF) \n393\t \n394\t
\n395\t Agrégé par Immo-Ka — {sourceName(l.source)}{updated ? ` · synchronisé le ${updated}` : \"\"}.\n396\t
\n397\t \n398\t\n399\t\n400\t {l.description && (\n401\t
\n402\t

Description

\n403\t

{l.description}

\n404\t
\n405\t )}\n406\t\n407\t {detEntries.length > 0 && (\n408\t
\n409\t

Caractéristiques

\n410\t
\n411\t {detEntries.map(([k, v]) => (\n412\t
\n413\t {k}\n414\t {/^https?:\\/\\//.test(String(v))\n415\t ? Ouvrir ↗\n416\t : {String(v)}}\n417\t
\n418\t ))}\n419\t
"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"6e59755a-cf03-4b77-8795-ed4f4eeecc2b","timestamp":"2026-08-25T14:14:11.556Z","tool_use_result":{"type":"text","file":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/frontend/src/pages/Listing.tsx","content":"
\n )}\n
\n );\n })()}\n {l.price != null && (\n (() => {\n const diff = l.price - (l.vraiprix!.value as number);\n const pct = Math.round((diff / (l.vraiprix!.value as number)) * 100);\n const cls = diff > 0 ? \"over\" : \"under\";\n const txt = diff > 0\n ? `Prix demandé ${pct}% au-dessus de l'estimation`\n : `Prix demandé ${Math.abs(pct)}% sous l'estimation`;\n if (Math.abs(pct) > 60) return null; // prix non comparable (loyer, terrain…)\n return Math.abs(pct) >= 1\n ?
{diff > 0 ? \"▲\" : \"▼\"} {txt}
\n :
≈ Prix aligné sur l'estimation
;\n })()\n )}\n \n Voir l'analyse détaillée ↗\n \n
\n )}\n\n {(l.broker_name || l.broker_phone) && (\n
\n
Courtier
\n {l.broker_name &&
{l.broker_name}
}\n {l.broker_phone && {l.broker_phone}}\n
\n )}\n\n \n Voir l'annonce chez {sourceName(l.source)} \n \n \n Télécharger la fiche (PDF) \n \n
\n Agrégé par Immo-Ka — {sourceName(l.source)}{updated ? ` · synchronisé le ${updated}` : \"\"}.\n
\n \n\n\n {l.description && (\n
\n

Description

\n

{l.description}

\n
\n )}\n\n {detEntries.length > 0 && (\n
\n

Caractéristiques

\n
\n {detEntries.map(([k, v]) => (\n
\n {k}\n {/^https?:\\/\\//.test(String(v))\n ? Ouvrir ↗\n : {String(v)}}\n
\n ))}\n
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Je vérifie où sont les styles."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1393,"cache_read_input_tokens":66197,"cache_creation":{"ephemeral_5m_input_tokens":1393,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"5d023647-f265-4d5f-b028-767f017ed59f"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePc6EmgRYgMSxscHkZg1","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01K1ue4GA7tZ1LZjUZuAyz47","name":"Grep","input":{"pattern":"\\.broker-name|\\.vp-link|\\.fine","path":"/Users/simon-pierreboucher/apps/immo-ka/frontend/src","output_mode":"files_with_matches"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1393,"cache_read_input_tokens":66197,"cache_creation":{"ephemeral_5m_input_tokens":1393,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"9eec1ddc-3efa-4b47-a3c4-cf6a69830530"}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"257ef212-78a3-4eec-8c63-ef2216a5b085","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01K1ue4GA7tZ1LZjUZuAyz47","type":"tool_result","content":"Found 1 file\nfrontend/src/styles.css"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"a90e6c66-71de-4204-8946-961e3635cf17","timestamp":"2026-08-25T14:14:25.623Z","tool_use_result":{"mode":"files_with_matches","filenames":["frontend/src/styles.css"],"numFiles":1}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePc7H3NyK8vg3vAWN772","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01NFvHaRXXk9YtYevFrsxsNa","name":"Grep","input":{"pattern":"^\\.broker|^\\.fine|^\\.cta","path":"/Users/simon-pierreboucher/apps/immo-ka/frontend/src/styles.css","output_mode":"content","-n":true},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":866,"cache_read_input_tokens":67590,"cache_creation":{"ephemeral_5m_input_tokens":866,"ephemeral_1h_input_tokens":0},"output_tokens":17,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"3b5eade7-2ff9-4270-b696-d3ab2c49d983"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01NFvHaRXXk9YtYevFrsxsNa","type":"tool_result","content":"255:.broker { margin: 16px 0; padding: 14px; border: 1.5px dashed var(--line-strong); border-radius: var(--r-ctl); background: var(--surface-2); }\n256:.broker-k { font-family: var(--font-mono); font-size: 9.5px; text-transform: uppercase; letter-spacing: 0.1em; color: var(--ink-3); }\n257:.broker-name { font-family: var(--font-display); font-weight: 700; font-size: 15px; margin-top: 3px; }\n258:.broker-tel { display: inline-block; margin-top: 6px; color: var(--green-deep); font-weight: 600; border-bottom: 1.5px solid var(--lime); }\n260:.cta { display: block; text-align: center; background: var(--ink); color: var(--lime); font-weight: 700; font-family: var(--font-display); border-radius: var(--r-ctl); padding: 15px; border: 1.5px solid var(--ink); min-height: 48px; box-shadow: 4px 4px 0 rgba(26, 18, 20,0.25); transition: all 0.14s ease; margin-top: 6px; }\n261:.cta:hover { background: var(--lime); color: #fff; }\n262:.cta:active { transform: translate(2px, 2px); box-shadow: none; }\n289:.cta-sticky { position: fixed; 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0 : Math.hypot(p[0].x - p[1].x, p[0].y - p[1].y);\n };\n const center = () => {\n const p = [...pointers.current.values()];\n return p.length < 2\n ? p[0] ?? { x: 0, y: 0 }\n : { x: (p[0].x + p[1].x) / 2, y: (p[0].y + p[1].y) / 2 };\n };\n\n const onDown = (e: React.PointerEvent) => {\n (e.target as HTMLElement).setPointerCapture(e.pointerId);\n pointers.current.set(e.pointerId, { x: e.clientX, y: e.clientY });\n const c = center();\n start.current = { scale: t.scale, x: t.x, y: t.y, dist: dist(), cx: c.x, cy: c.y, t: Date.now() };\n };\n const onMove = (e: React.PointerEvent) => {\n if (!pointers.current.has(e.pointerId)) return;\n pointers.current.set(e.pointerId, { x: e.clientX, y: e.clientY });\n const s = start.current;\n if (pointers.current.size >= 2 && s.dist > 0) {\n // pincement : zoom autour du centre des deux doigts\n const scale = Math.min(4, Math.max(1, (dist() / s.dist) * s.scale));\n const c = center();\n setT({ scale, x: s.x + (c.x - s.cx), y: s.y + (c.y - s.cy) });\n } else if (pointers.current.size === 1 && t.scale > 1) {\n // panoramique une fois zoomé\n const p = pointers.current.get(e.pointerId)!;\n setT({ scale: t.scale, x: s.x + (p.x - s.cx), y: s.y + (p.y - s.cy) });\n }\n };\n const onUp = (e: React.PointerEvent) => {\n const p = pointers.current.get(e.pointerId);\n pointers.current.delete(e.pointerId);\n const s = start.current;\n if (pointers.current.size === 0 && p) {\n const dx = p.x - s.cx, dy = p.y - s.cy, dt = Date.now() - s.t;\n if (t.scale <= 1.05 && Math.abs(dx) > 56 && Math.abs(dx) > Math.abs(dy) * 1.5) {\n onSwipe(dx < 0 ? 1 : -1); // balayage → photo suivante\n } else if (dt < 260 && Math.abs(dx) < 8 && Math.abs(dy) < 8) {\n const now = Date.now();\n if (now - lastTap.current < 320) // double-tap : zoom ×2.4\n setT(t.scale > 1 ? { scale: 1, x: 0, y: 0 } : { scale: 2.4, x: 0, y: 0 });\n lastTap.current = now;\n }\n if (t.scale <= 1.02) setT({ scale: 1, x: 0, y: 0 });\n }\n };\n\n return (\n 1 ? \"grab\" : \"zoom-out\",\n }}\n onClick={(e) => e.stopPropagation()}\n onPointerDown={onDown} onPointerMove={onMove}\n onPointerUp={onUp} onPointerCancel={onUp}\n />\n );\n}\n\n// --- Galerie : balayage natif (scroll-snap) + vignettes + plein écran --------\nfunction Galerie({ images, captions, titre, type }:\n { images: string[]; captions?: string[]; titre: string; type?: string }) {\n const [idx, setIdx] = useState(0);\n const [zoom, setZoom] = useState(false);\n const [dead, setDead] = useState>(new Set());\n const track = useRef(null);\n\n // images qui ne chargent pas : retirées de la galerie à la volée (jamais\n // d'icône d'image cassée) ; légendes gardées alignées\n const alive = images\n .map((u, i) => ({ u, cap: captions && captions.length === images.length ? 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\n
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\n {alive[cur]?.cap && {alive[cur].cap}}\n {cur + 1}/{alive.length}\n {cur > 0 && }\n {cur < alive.length - 1 && }\n
\n {alive.length > 1 && (\n
\n {alive.map(({ u }, i) => (\n \n ))}\n
\n )}\n {zoom && (\n
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\n )}\n \n );\n}\n\n// clés techniques de `details` jamais montrées dans « Caractéristiques »\nconst DETAIL_HIDDEN = new Set([\n \"pieces\", \"price_from\", \"cover_thumb\", \"photo_captions\", \"img_audited\",\n \"needs_image_review\", \"postal_code\", \"region\", \"transaction\",\n \"prix_pi2\", \"prix_m2\", \"listing_origin_url\",\n]);\n\n// icône de chaque tuile « spec » (Icons.tsx)\nconst SPEC_ICONS: Record = {\n \"Type\": \"home\", \"Chambres\": \"bed\", \"Salles de bain\": \"bath\",\n \"Salles d'eau\": \"drop\", \"Superficie\": \"area\", \"Terrain\": \"land\",\n \"Année\": \"calendar\", \"MLS / Centris\": \"tag\",\n};\n\nexport default function ListingPage() {\n const { uid } = useParams<{ uid: string }>();\n const [l, setL] = useState(null);\n const [error, setError] = useState(null);\n\n useEffect(() => {\n fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});\n if (!uid) return;\n setL(null); setError(null);\n fetchListing(uid).then(setL).catch((e) => setError(String(e)));\n window.scrollTo(0, 0);\n }, [uid]);\n\n if (error)\n return (\n
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\n

Propriété introuvable

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{error}

\n Retour aux propriétés\n
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\n
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\n
\n \n
\n\n
\n
\n {l.details?.transaction === \"location\" ? \"Loyer mensuel\" : \"Prix demandé\"}\n
\n
\n
\n {fmtPrice(l.price, l.price_label)}\n {l.details?.transaction === \"location\" && /mois}\n
\n {l.property_type && (\n \n {l.property_type}\n {l.details?.transaction === \"location\" ? \" · location\" : \"\"}\n {l.details?.price_from ? \" · à partir de\" : \"\"}\n \n )}\n
\n {l.price != null && l.area_sqft != null && l.area_sqft > 200 && (\n
{Math.round(l.price / l.area_sqft).toLocaleString(\"fr-CA\")} $ / pi² habitable
\n )}\n

{l.address || l.title}

\n
{[l.sector, l.city, l.region].filter(Boolean).join(\" · \")}
\n\n
\n {specs.map((s) => (\n
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\n ))}\n
\n\n {baisse && (\n
\n Prix passé de {fmtPrice(baisse.de)} à {fmtPrice(baisse.a)}\n
\n )}\n\n {l.vraiprix && l.vraiprix.value != null && (\n
\n
\n Vrai‑Prix\n {l.vraiprix.confidence && (\n \n confiance {l.vraiprix.confidence}\n \n )}\n
\n
Valeur marchande estimée
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{fmtPrice(l.vraiprix.value)}
\n {l.vraiprix.low != null && l.vraiprix.high != null && (() => {\n const lo = l.vraiprix!.low as number, hi = l.vraiprix!.high as number;\n const span = Math.max(1, hi - lo);\n const pos = (v: number) => `${Math.max(2, Math.min(98, ((v - lo) / span) * 100))}%`;\n return (\n
\n
\n \n \n {l.price != null && l.price >= lo * 0.7 && l.price <= hi * 1.3 && (\n \n )}\n
\n
\n {fmtPrice(lo)}\n {fmtPrice(hi)}\n
\n {l.price != null && l.price >= lo * 0.7 && l.price <= hi * 1.3 && (\n
\n estimation\n prix demandé\n
\n )}\n
\n );\n })()}\n {l.price != null && (\n (() => {\n const diff = l.price - (l.vraiprix!.value as number);\n const pct = Math.round((diff / (l.vraiprix!.value as number)) * 100);\n const cls = diff > 0 ? \"over\" : \"under\";\n const txt = diff > 0\n ? `Prix demandé ${pct}% au-dessus de l'estimation`\n : `Prix demandé ${Math.abs(pct)}% sous l'estimation`;\n if (Math.abs(pct) > 60) return null; // prix non comparable (loyer, terrain…)\n return Math.abs(pct) >= 1\n ?
{diff > 0 ? \"▲\" : \"▼\"} {txt}
\n :
≈ Prix aligné sur l'estimation
;\n })()\n )}\n \n Voir l'analyse détaillée ↗\n \n
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\n
Courtier
\n {l.broker_name &&
{l.broker_name}
}\n {l.broker_phone && {l.broker_phone}}\n
\n )}\n\n \n Voir l'annonce chez {sourceName(l.source)} \n \n \n Télécharger la fiche (PDF) \n \n
\n Agrégé par Immo-Ka — {sourceName(l.source)}{updated ? ` · synchronisé le ${updated}` : \"\"}.\n
\n
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\n

Description

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{l.description}

\n
\n )}\n\n {detEntries.length > 0 && (\n
\n

Caractéristiques

\n
\n {detEntries.map(([k, v]) => (\n
\n {k}\n {/^https?:\\/\\//.test(String(v))\n ? Ouvrir ↗\n : {String(v)}}\n
\n ))}\n
\n
\n )}\n\n {rooms.length > 0 && (\n
\n

Pièces

\n
\n \n \n \n {rooms.map((r, i) => (\n \n \n \n \n ))}\n \n
PièceNiveauDimensionsRevêtement
{r.nom || \"—\"}{r.niveau || \"—\"}{r.dimensions || \"—\"}{r.revetement || \"—\"}
\n
\n
\n )}\n\n
\n\n {/* -------- colonne droite (desktop) : inclusions, carte ------------- */}\n
\n {l.features && l.features.length > 0 && (\n
\n

Inclusions

\n
\n {l.features.map((f, i) => {f})}\n
\n
\n )}\n\n {l.lat != null && l.lng != null && (\n
\n

Emplacement

\n Chargement de la carte…
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\n
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\n Les prix et disponibilités sont ceux affichés par la source — chaque fiche renvoie à\n l'annonce originale de l'agence.\n
\n\n
\n {fmtPrice(l.price, l.price_label)}\n \n Voir chez {sourceName(l.source)} ↗\n \n
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color: var(--lime); }\n\n/* ================= Ticker ================= */\n.ticker { background: var(--ink); color: var(--lime); overflow: hidden; font-family: var(--font-mono); font-size: 11.5px; letter-spacing: 0.1em; text-transform: uppercase; padding: 7px 0; white-space: nowrap; border-bottom: 1px solid rgba(226, 55, 68, 0.25); }\n.ticker-track { display: inline-flex; gap: 0; animation: ticker 48s linear infinite; will-change: transform; }\n.ticker span { padding: 0 26px; position: relative; }\n.ticker span::after { content: \"◆\"; position: absolute; right: -6px; opacity: 0.5; font-size: 8px; top: 3px; }\n@keyframes ticker { from { transform: translateX(0); } to { transform: translateX(-50%); } }\n@media (prefers-reduced-motion: reduce) { .ticker-track { animation: none; } * { transition-duration: 0.01ms !important; } }\n\n/* ================= Hero ================= */\n.hero { padding: 58px 0 22px; }\n@media (max-width: 640px) { .hero { padding: 34px 0 14px; } }\n.hero h1 { font-size: clamp(38px, 6.4vw, 78px); font-weight: 700; line-height: 0.98; text-transform: uppercase; letter-spacing: -0.035em; max-width: 940px; margin-top: 14px; }\n.hero h1 .outline { color: transparent; -webkit-text-stroke: 2px var(--ink); }\n.hero h1 .hl { background: var(--lime); color: #fff; padding: 0 10px; border-radius: 8px; display: inline-block; transform: rotate(-1deg); }\n.hero p.lede { color: var(--ink-2); font-size: 16.5px; max-width: 680px; margin: 20px 0 0; }\n.stat-row { display: flex; flex-wrap: wrap; gap: 10px; margin-top: 26px; }\n.stat-chip { background: var(--surface); border: 1.5px solid var(--ink); border-radius: 999px; padding: 8px 16px; font-family: var(--font-mono); font-size: 12px; color: var(--ink-2); display: flex; gap: 8px; align-items: center; box-shadow: 3px 3px 0 rgba(26, 18, 20, 0.12); }\n.stat-chip b { color: var(--ink); font-weight: 700; }\n.stat-chip .pulse { width: 8px; height: 8px; border-radius: 50%; background: var(--green); box-shadow: 0 0 0 4px var(--lime-soft); animation: pulse 2.4s ease infinite; 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color: #fff; }\n.pill-x { font-size: 10px; opacity: 0.65; }\n.pill-clear { background: var(--surface); border-color: var(--danger); color: var(--danger); }\n.pill-clear:hover { background: var(--danger); color: #fff; }\n.link-btn { background: none; border: none; padding: 0; color: var(--green); font: inherit; text-decoration: underline; cursor: pointer; }\n\n.btn { border: 1.5px solid var(--ink); border-radius: var(--r-ctl); padding: 11px 20px; font-weight: 700; font-size: 14px; cursor: pointer; min-height: 44px; transition: transform 0.12s ease, box-shadow 0.12s ease, background 0.15s ease; font-family: var(--font-display); letter-spacing: 0.01em; }\n.btn:active { transform: translate(2px, 2px); box-shadow: none !important; }\n.btn-primary { background: var(--ink); color: var(--lime); box-shadow: 4px 4px 0 rgba(26, 18, 20,0.25); }\n.btn-primary:hover { background: var(--green-deep); }\n.btn-ghost { background: transparent; color: var(--ink); }\n.btn-ghost:hover { background: var(--lime); color: #fff; box-shadow: 4px 4px 0 rgba(26, 18, 20,0.2); }\n\n/* ================= Chips ================= */\n.chips { display: flex; gap: 8px; margin: 16px 0 4px; overflow-x: auto; padding-bottom: 6px; scrollbar-width: none; }\n.chips::-webkit-scrollbar { display: none; }\n.chip { border: 1.5px solid var(--ink); background: var(--surface); color: var(--ink); border-radius: 999px; padding: 8px 18px; font-size: 13.5px; font-weight: 600; cursor: pointer; font-family: var(--font-display); white-space: nowrap; min-height: 40px; transition: all 0.13s ease; }\n.chip:hover { background: var(--lime-soft); transform: translateY(-1px); }\n.chip.on { background: var(--ink); color: var(--lime); box-shadow: 3px 3px 0 rgba(26, 18, 20,0.2); }\n\n/* ================= Results ================= */\n.results-head { display: flex; align-items: baseline; gap: 14px; margin: 28px 0 18px; flex-wrap: wrap; }\n.results-head h2 { font-size: 22px; text-transform: uppercase; letter-spacing: -0.02em; }\n.results-head > span { font-family: var(--font-mono); color: var(--ink-3); font-size: 12px; letter-spacing: 0.06em; }\n.results-tools { display: flex; align-items: center; gap: 12px; margin-left: auto; }\n.sort-ctl select { border: 1.5px solid var(--line-strong); background: var(--surface); border-radius: var(--r-ctl); padding: 7px 28px 7px 12px; font-family: var(--font-mono); font-size: 12px; color: var(--ink); cursor: pointer; appearance: none; -webkit-appearance: none; background-image: url(\"data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='10' height='6'%3E%3Cpath d='M0 0l5 6 5-6z' fill='%23141814'/%3E%3C/svg%3E\"); background-repeat: no-repeat; background-position: right 10px center; }\n.view-toggle { display: inline-flex; border: 1.5px solid var(--line-strong); border-radius: var(--r-ctl); overflow: hidden; background: var(--surface); box-shadow: var(--shadow-flat); }\n.view-toggle button { border: 0; background: transparent; padding: 7px 14px; cursor: pointer; font-family: var(--font-mono); font-size: 12px; color: var(--ink-2); }\n.view-toggle button + button { border-left: 1.5px solid var(--line-strong); }\n.view-toggle button.on { background: var(--ink); color: var(--lime); }\n\n.grid { display: grid; grid-template-columns: repeat(auto-fill, minmax(290px, 1fr)); gap: 22px; padding-bottom: 20px; }\n@media (max-width: 640px) { .grid { grid-template-columns: 1fr; gap: 16px; } }\n.more-wrap { display: flex; justify-content: center; padding: 8px 0 70px; }\n\n.card { background: var(--surface); border: 1.5px solid var(--line-strong); border-radius: var(--r-card); overflow: hidden; display: flex; flex-direction: column; box-shadow: var(--shadow-flat); transition: transform 0.16s ease, box-shadow 0.16s ease; }\n.card:hover { transform: translate(-3px, -3px); box-shadow: var(--shadow-off); }\n.card:focus-visible { outline: 3px solid var(--lime); outline-offset: 2px; }\n.card-img { position: relative; aspect-ratio: 16/10.5; background: repeating-linear-gradient(45deg, #eceae3 0 12px, #f3f1ea 12px 24px); overflow: hidden; }\n.card-img img { width: 100%; height: 100%; object-fit: cover; transition: transform 0.4s ease; }\n.card:hover .card-img img { transform: scale(1.05); }\n.card-img .noimg { display: flex; align-items: center; justify-content: center; height: 100%; color: var(--ink-3); font-size: 34px; }\n.badge { position: absolute; top: 12px; left: 12px; border-radius: 6px; padding: 4px 10px; font-family: var(--font-mono); font-size: 11.5px; font-weight: 700; letter-spacing: 0.04em; background: rgba(255, 255, 255, 0.95); color: var(--ink); border: 1px solid var(--ink); }\n.badge.type { background: var(--ink); color: var(--lime); border-color: var(--ink); }\n.badge.right { left: auto; right: 12px; background: rgba(255,255,255,0.92); border-color: transparent; }\n.card-body { padding: 16px 18px; display: flex; flex-direction: column; gap: 6px; flex: 1; }\n.card-price { font-family: var(--font-display); font-weight: 700; font-size: 21px; letter-spacing: -0.02em; }\n.card-title { font-weight: 600; font-size: 14.5px; color: var(--ink); overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }\n.card-meta { color: var(--ink-3); font-size: 12.5px; display: flex; gap: 7px; flex-wrap: wrap; align-items: center; font-family: var(--font-mono); }\n.card-meta .sep { width: 4px; height: 4px; background: var(--lime); border: 1px solid var(--ink); border-radius: 1px; transform: rotate(45deg); }\n.card-specs { display: flex; gap: 12px; font-size: 12.5px; color: var(--ink-2); font-family: var(--font-mono); }\n.card-foot { margin-top: auto; padding-top: 11px; border-top: 1.5px dashed var(--line); display: flex; justify-content: space-between; align-items: center; gap: 8px; }\n.source-tag { font-family: var(--font-mono); font-size: 10px; font-weight: 700; text-transform: uppercase; letter-spacing: 0.08em; color: var(--green-deep); background: var(--lime-soft); border: 1px solid var(--green); border-radius: 4px; padding: 3px 8px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; max-width: 62%; }\n.avail { font-size: 11px; color: var(--ink-3); font-weight: 500; text-align: right; font-family: var(--font-mono); }\n\n/* ================= Skeletons ================= */\n@keyframes shimmer { 0% { background-position: -400px 0; } 100% { background-position: 400px 0; } }\n.skel { border-radius: var(--r-card); border: 1.5px solid var(--line); overflow: hidden; background: var(--surface); }\n.skel .sk-img, .skel .sk-line { background: linear-gradient(90deg, #eeece5 25%, #f7f5ef 50%, #eeece5 75%); background-size: 800px 100%; animation: shimmer 1.4s infinite linear; }\n.skel .sk-img { aspect-ratio: 16/10.5; }\n.skel .sk-line { height: 14px; border-radius: 4px; margin: 12px 16px; }\n.skel .sk-line.short { width: 45%; }\n\n/* ================= Empty / error ================= */\n.notice { text-align: center; padding: 72px 24px; color: var(--ink-2); }\n.notice .big { font-size: 44px; margin-bottom: 10px; }\n.notice h2 { text-transform: uppercase; }\n\n/* ================= Detail page ================= */\n.detail { padding: 30px 0 90px; }\n.crumbs { font-family: var(--font-mono); font-size: 11.5px; letter-spacing: 0.06em; text-transform: uppercase; color: var(--ink-3); margin-bottom: 20px; display: flex; gap: 8px; align-items: center; flex-wrap: wrap; }\n.crumbs a { border-bottom: 1.5px solid transparent; }\n.crumbs a:hover { color: var(--green); border-color: var(--green); }\n\n/* Ordre DOM = ordre visuel sur TOUS les breakpoints (standard Groupe Ka\n « Ordre des sections — pages détail »). Interdit : `order` / `column-reverse`\n / `display:contents` pour réordonner — un bloc sans `order` retombe à\n order:0 et passe devant la galerie sur mobile (bug corrigé sur Lou-Ka).\n Mobile : colonnes empilées ; desktop : grid 2 colonnes (fiche | annexes). */\n.fiche { display: flex; flex-direction: column; gap: 22px; }\n.f-col { display: flex; flex-direction: column; gap: 22px; min-width: 0; }\n@media (min-width: 900px) {\n .fiche { display: grid; grid-template-columns: 1.6fr 1fr; gap: 30px; align-items: start; }\n .f-col { gap: 26px; }\n .f-col:last-child { position: sticky; top: 88px; }\n}\n.f-bloc { min-width: 0; }\n.f-bloc h2 { font-size: 21px; letter-spacing: -0.02em; margin-bottom: 12px; border-left: 4px solid var(--lime); padding-left: 10px; }\n.f-bloc:empty { display: none; }\n\n/* galerie */\n.carousel { position: relative; border-radius: var(--r-card); overflow: hidden; border: 1.5px solid var(--line-strong); background: var(--surface-2); box-shadow: var(--shadow-off-soft); }\n.carousel-track { display: flex; overflow-x: auto; scroll-snap-type: x mandatory; -webkit-overflow-scrolling: touch; scrollbar-width: none; aspect-ratio: 16/11; }\n.carousel-track::-webkit-scrollbar { display: none; }\n.carousel-track img { flex: 0 0 100%; width: 100%; object-fit: cover; scroll-snap-align: center; cursor: zoom-in; }\n.carousel-empty { display: flex; align-items: center; justify-content: center; aspect-ratio: 16/11; font-size: 48px; }\n.carousel-count { position: absolute; right: 12px; bottom: 12px; z-index: 2; background: rgba(26, 18, 20, 0.82); color: var(--lime); font-family: var(--font-mono); font-size: 12px; font-weight: 700; padding: 4px 10px; border-radius: 999px; }\n.carousel-nav { position: absolute; top: 50%; transform: translateY(-50%); z-index: 2; width: 44px; height: 44px; border-radius: 50%; border: 1.5px solid var(--ink); background: rgba(255, 255, 255, 0.92); font-size: 22px; cursor: pointer; display: flex; align-items: center; justify-content: center; line-height: 1; }\n.carousel-nav.prev { left: 10px; } .carousel-nav.next { right: 10px; }\n@media (max-width: 640px) { .carousel-nav { display: none; } }\n.thumbs { display: grid; grid-template-columns: repeat(auto-fill, minmax(84px, 1fr)); gap: 8px; margin-top: 10px; }\n.thumbs button { border: 2px solid var(--line); border-radius: 8px; overflow: hidden; padding: 0; cursor: pointer; aspect-ratio: 4/3; background: #eceae3; transition: border-color 0.12s ease, transform 0.12s ease; }\n.thumbs button:hover { transform: translateY(-2px); }\n.thumbs button.on { border-color: var(--ink); box-shadow: 3px 3px 0 var(--lime); }\n.thumbs img { width: 100%; height: 100%; object-fit: cover; }\n@media (max-width: 640px) { .thumbs { display: flex; overflow-x: auto; scrollbar-width: none; } .thumbs::-webkit-scrollbar { display: none; } .thumbs button { flex: 0 0 84px; } }\n\n/* lightbox */\n.lightbox { position: fixed; inset: 0; background: rgba(16, 18, 16, 0.94); z-index: 100; display: flex; align-items: center; justify-content: center; cursor: zoom-out; padding: max(16px, env(safe-area-inset-top)) 16px; }\n.lightbox img { max-width: 94vw; max-height: 86vh; border-radius: 6px; border: 2px solid var(--lime); object-fit: contain; }\n.lb-close { position: absolute; top: 18px; right: 22px; background: none; border: none; color: #fff; font-size: 30px; cursor: pointer; }\n.lb-nav { position: absolute; top: 50%; transform: translateY(-50%); background: none; border: none; color: var(--lime); font-size: 52px; cursor: pointer; padding: 0 22px; user-select: none; }\n.lb-nav.prev { left: 6px; } .lb-nav.next { right: 6px; }\n.lb-count { position: absolute; bottom: 24px; color: #c9ccc2; font-family: var(--font-mono); font-size: 13px; }\n\n/* hero panneau (colonne droite) */\n.f-hero { background: var(--surface); border: 1.5px solid var(--ink); border-radius: var(--r-card); box-shadow: var(--shadow-off-soft); padding: 26px; }\n.price-kicker { font-family: var(--font-mono); font-size: 10px; text-transform: uppercase; letter-spacing: 0.14em; color: var(--green); }\n.price-kicker::before { content: \"\"; display: inline-block; width: 16px; height: 2px; background: var(--lime); vertical-align: 3px; margin-right: 7px; }\n.price-row { display: flex; align-items: baseline; gap: 12px; flex-wrap: wrap; }\n.f-hero .price { font-family: var(--font-display); font-size: clamp(30px, 6vw, 40px); font-weight: 700; letter-spacing: -0.03em; }\n.type-chip { display: inline-flex; align-items: center; gap: 5px; padding: 4px 11px; background: var(--lime-soft); color: var(--green-deep); border: 1px solid rgba(179, 32, 43, 0.25); border-radius: 999px; font-size: 12px; font-weight: 600; }\n.price-sub { font-family: var(--font-mono); font-size: 11.5px; color: var(--ink-3); margin-top: 2px; }\n.f-hero h1 { font-size: clamp(20px, 4.5vw, 24px); margin-top: 10px; }\n.f-hero .loc { color: var(--ink-2); font-size: 13.5px; margin-top: 3px; display: flex; align-items: center; gap: 5px; }\n.f-hero .loc .ico { color: var(--lime); }\n\n/* liste de specs — fiche technique premium */\n.spec-list { margin: 18px 0 4px; border-top: 1.5px solid var(--line-strong); }\n.spec-row { display: grid; grid-template-columns: 30px 1fr auto; align-items: center; gap: 11px; padding: 8.5px 0; border-bottom: 1px dashed var(--line); }\n.spec-row:last-child { border-bottom: 1.5px solid var(--line-strong); }\n.spec-badge { display: inline-flex; align-items: center; justify-content: center; width: 30px; height: 30px; border-radius: 9px; background: var(--lime-soft); color: var(--green-deep); }\n.spec-k { font-family: var(--font-mono); font-size: 10.5px; text-transform: uppercase; letter-spacing: 0.08em; color: var(--ink-2); }\n.spec-v { font-family: var(--font-display); font-size: 15.5px; font-weight: 700; text-align: right; }\n.deal-badge { display: inline-flex; align-items: center; gap: 6px; margin: 8px 0 4px; border-radius: 999px; padding: 6px 13px; font-size: 12.5px; font-weight: 600; border: 1.5px solid var(--line-strong); }\n.deal-ok { background: var(--lime-soft); border-color: var(--green); color: var(--green-deep); }\n\n.specs-grid { display: grid; grid-template-columns: repeat(auto-fill, minmax(96px, 1fr)); gap: 8px; margin: 18px 0; }\n.spec { border: 1.5px solid var(--line-strong); border-radius: var(--r-ctl); padding: 9px 11px; background: var(--surface-2); }\n.spec b { display: block; font-family: var(--font-display); font-size: 16px; }\n.spec span { font-family: var(--font-mono); font-size: 9.5px; text-transform: uppercase; letter-spacing: 0.08em; color: var(--ink-3); }\n\n.broker { margin: 16px 0; padding: 14px; border: 1.5px dashed var(--line-strong); border-radius: var(--r-ctl); background: var(--surface-2); }\n.broker-k { font-family: var(--font-mono); font-size: 9.5px; text-transform: uppercase; letter-spacing: 0.1em; color: var(--ink-3); }\n.broker-name { font-family: var(--font-display); font-weight: 700; font-size: 15px; margin-top: 3px; }\n.broker-tel { display: inline-block; margin-top: 6px; color: var(--green-deep); font-weight: 600; border-bottom: 1.5px solid var(--lime); }\n\n.cta { display: block; text-align: center; background: var(--ink); color: var(--lime); font-weight: 700; font-family: var(--font-display); border-radius: var(--r-ctl); padding: 15px; border: 1.5px solid var(--ink); min-height: 48px; box-shadow: 4px 4px 0 rgba(26, 18, 20,0.25); transition: all 0.14s ease; margin-top: 6px; }\n.cta:hover { background: var(--lime); color: #fff; }\n.cta:active { transform: translate(2px, 2px); box-shadow: none; }\n.f-hero .fine { font-size: 11.5px; color: var(--ink-3); margin-top: 14px; text-align: center; font-family: var(--font-mono); letter-spacing: 0.02em; }\n\n.desc-text { color: var(--ink-2); font-size: 14.5px; white-space: pre-line; line-height: 1.6; margin: 0; }\n\n/* tableau caractéristiques */\n.dtable { display: grid; grid-template-columns: repeat(auto-fill, minmax(240px, 1fr)); gap: 0 22px; }\n.drow { display: flex; justify-content: space-between; gap: 12px; padding: 8px 0; border-bottom: 1px solid var(--line); font-size: 13.5px; }\n.drow span { color: var(--ink-3); } .drow b { text-align: right; font-family: var(--font-display); }\n\n/* tableau pièces */\n.rooms-wrap { overflow-x: auto; border: 1.5px solid var(--line-strong); border-radius: var(--r-card); }\ntable.rooms { width: 100%; border-collapse: collapse; font-size: 13.5px; min-width: 460px; }\ntable.rooms th { text-align: left; background: var(--ink); color: var(--paper); padding: 9px 12px; font-family: var(--font-mono); font-size: 10px; text-transform: uppercase; letter-spacing: 0.06em; }\ntable.rooms td { padding: 8px 12px; border-bottom: 1px solid var(--line); }\ntable.rooms tr:last-child td { border-bottom: none; }\ntable.rooms tr:nth-child(even) td { background: var(--surface-2); }\n\n.amenity-row { display: flex; flex-wrap: wrap; gap: 7px; }\n.amenity { background: var(--lime-soft); color: var(--green-deep); font-size: 12px; font-weight: 600; border: 1px solid var(--green); border-radius: 999px; padding: 5px 12px; }\n\n.prix-histo { margin-top: 14px; padding: 10px 14px; border-radius: var(--r-card); border: 1.5px solid var(--line-strong); font-size: 13.5px; background: var(--surface); }\n.prix-histo.down { background: var(--lime-soft); border-color: var(--green); color: var(--green-deep); }\n\n.mini-map { height: 320px; border: 1.5px solid var(--line-strong); border-radius: var(--r-card); overflow: hidden; }\n.mini-map .mapview { border: none; border-radius: 0; box-shadow: none; height: 100%; }\n\n.cta-sticky { position: fixed; left: 0; right: 0; bottom: 0; z-index: 45; display: flex; align-items: center; gap: 12px; background: rgba(247, 241, 239, 0.94); backdrop-filter: blur(12px); border-top: 2px solid var(--ink); padding: 10px 16px calc(10px + env(safe-area-inset-bottom)); }\n.cta-sticky .cta { flex: 1; margin: 0; }\n.cta-sticky-prix { font-family: var(--font-display); font-weight: 700; font-size: 19px; white-space: nowrap; }\n@media (min-width: 900px) { .cta-sticky { display: none; } }\n@media (max-width: 899px) { .detail { padding-bottom: 84px; } }\n.f-foot { margin-top: 26px; }\n.fine { font-size: 12px; color: var(--ink-3); }\n\n/* ================= Sources / Agences ================= */\n.sources { padding: 44px 0 90px; }\n.sources h1 { font-size: clamp(28px, 4vw, 40px); text-transform: uppercase; margin: 10px 0 6px; }\n.sources .sub { color: var(--ink-2); margin-bottom: 30px; max-width: 720px; }\n.src-wrap { overflow-x: auto; border: 1.5px solid var(--ink); border-radius: var(--r-card); box-shadow: var(--shadow-off-soft); background: var(--surface); }\n.src-table { width: 100%; border-collapse: separate; border-spacing: 0; min-width: 760px; }\n.src-table th { text-align: left; font-family: var(--font-mono); font-size: 10px; text-transform: uppercase; letter-spacing: 0.12em; color: var(--ink-3); padding: 14px 18px; border-bottom: 1.5px solid var(--ink); background: var(--surface-2); }\n.src-table td { padding: 13px 18px; border-bottom: 1px solid var(--line); font-size: 14px; vertical-align: top; }\n.src-table tr:last-child td { border-bottom: none; }\n.src-table tr:hover td { background: var(--surface-2); }\n.src-table a { color: var(--green-deep); font-weight: 600; border-bottom: 1.5px solid var(--lime); }\n.pill.ok { background: var(--lime); color: #fff; border: 1px solid var(--ink); border-radius: 4px; padding: 3px 10px; font-family: var(--font-mono); font-size: 10.5px; font-weight: 700; text-transform: uppercase; }\n.pill.todo { background: var(--amber-soft); color: #8a5a12; border: 1px solid var(--amber); border-radius: 4px; padding: 3px 10px; font-family: var(--font-mono); font-size: 10.5px; font-weight: 700; text-transform: uppercase; }\n.count-pill { font-weight: 700; font-family: var(--font-display); font-size: 16px; border-bottom: 1.5px solid var(--lime); }\n\n/* ================= Stats ================= */\n.stats-page { padding: 44px 0 90px; }\n.stats-title { font-size: clamp(30px, 4.6vw, 46px); text-transform: uppercase; margin: 10px 0 6px; }\n.stats-page .sub { color: var(--ink-2); max-width: 660px; margin-bottom: 30px; }\n.tiles { display: grid; grid-template-columns: repeat(auto-fit, minmax(160px, 1fr)); gap: 14px; margin-bottom: 30px; }\n.tile { background: var(--surface); border: 1.5px solid var(--ink); border-radius: var(--r-card); padding: 18px 20px; box-shadow: 3px 3px 0 rgba(26, 18, 20, 0.1); }\n.tile-v { font-family: var(--font-display); font-weight: 700; font-size: clamp(22px, 3vw, 32px); letter-spacing: -0.03em; line-height: 1.05; }\n.tile-k { font-family: var(--font-mono); font-size: 10.5px; text-transform: uppercase; letter-spacing: 0.1em; color: var(--ink-3); margin-top: 6px; }\n.hero-tile { background: var(--ink); color: var(--lime); border-color: var(--ink); }\n.hero-tile .tile-k { color: rgba(226, 55, 68, 0.7); }\n.viz-card { background: var(--surface); border: 1.5px solid var(--ink); border-radius: var(--r-card); box-shadow: var(--shadow-off-soft); padding: 26px 28px 20px; margin-bottom: 22px; min-width: 0; max-width: 100%; overflow-x: auto; }\n/* mobile : une table large ne doit JAMAIS déborder la page (grid blowout) —\n chaque bloc de la page Stats défile horizontalement en interne au besoin */\n.stats-page section, .stats-page > * { min-width: 0; max-width: 100%; }\n@media (max-width: 640px) { .stats-page .viz-card { padding: 18px 14px 14px; } }\n.viz-card h2 { font-size: 19px; text-transform: uppercase; letter-spacing: -0.01em; }\n.viz-sub { font-family: var(--font-mono); font-size: 11px; letter-spacing: 0.06em; text-transform: uppercase; color: var(--ink-3); margin: 4px 0 20px; }\n.viz-grid { display: grid; grid-template-columns: 1fr 1fr; gap: 22px; }\n@media (max-width: 900px) { .viz-grid { grid-template-columns: 1fr; } }\n.hbars { display: flex; flex-direction: column; gap: 7px; }\n.hbar-row { display: grid; grid-template-columns: minmax(96px, 180px) 1fr auto; gap: 12px; align-items: center; min-height: 26px; }\n.hbar-label { font-size: 13px; font-weight: 600; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }\n.hbar-label a { border-bottom: 1.5px solid var(--lime); }\n.hbar-label a:hover { color: var(--green-deep); }\n.hbar-track { background: var(--surface-2); border-radius: 0 4px 4px 0; height: 18px; overflow: hidden; }\n.hbar-fill { display: block; height: 100%; background: var(--green); border-radius: 0 4px 4px 0; min-width: 2px; transition: background 0.12s ease; }\n.hbar-row:hover .hbar-fill { background: var(--ink); box-shadow: inset 0 0 0 2px var(--lime); }\n.hbar-value { font-family: var(--font-mono); font-size: 11.5px; font-weight: 700; white-space: nowrap; }\n.hbar-value em { font-style: normal; font-weight: 500; color: var(--ink-3); }\n.viz-table { margin-top: 4px; }\n.viz-table table { width: 100%; border-collapse: collapse; font-size: 13px; }\n.viz-table th { text-align: left; font-family: var(--font-mono); font-size: 10px; text-transform: uppercase; letter-spacing: 0.08em; color: var(--ink-3); padding: 6px 10px; border-bottom: 1.5px solid var(--ink); }\n.viz-table td { padding: 6px 10px; border-bottom: 1px solid var(--line); }\n.stats-foot { font-family: var(--font-mono); font-size: 11px; color: var(--ink-3); letter-spacing: 0.04em; margin-top: 6px; }\n\n/* ---- Iconographie maison (Icons.tsx) ---- */\n.ico { vertical-align: -3px; flex-shrink: 0; }\n.card-specs span { display: inline-flex; align-items: center; gap: 5px; }\n.card-specs .ico { color: var(--green); }\n.badge.right .ico { vertical-align: -2px; }\n.noimg .ico, .carousel-empty .ico { color: var(--ink-3); }\n.notice .big .ico { color: var(--lime); }\n.amenity .ico { color: var(--green); margin-right: 2px; }\n.q-badge .ico { vertical-align: -3px; margin-right: 2px; }\n.q-bar-label { display: inline-flex; align-items: center; gap: 7px; }\n.q-bar-label .ico { color: var(--green); }\n.mm-ico .ico { vertical-align: -4px; }\n.mv-noimg svg { color: var(--ink-3); }\n.broker-tel .ico { vertical-align: -2.5px; }\n.cta .ico { vertical-align: -2.5px; margin-left: 3px; }\n.prix-histo .ico { vertical-align: -3.5px; }\n.spec { position: relative; }\n.spec-ico { position: absolute; top: 10px; right: 10px; color: var(--lime); opacity: 0.85; }\n\n/* ---- Survalorisation vs Vrai-Prix (jauges divergentes) ---- */\n.vpg-axis { display: grid; grid-template-columns: 220px 1fr 74px 90px; gap: 10px; margin-bottom: 2px; }\n.vpg-axis > div { grid-column: 2; display: flex; justify-content: space-between; font-family: var(--font-mono); font-size: 10px; color: var(--ink-3); }\n.vpg-row { display: grid; grid-template-columns: 220px 1fr 74px 90px; align-items: center; gap: 10px; padding: 7px 0; border-bottom: 1px dashed var(--line); }\n.vpg-row:last-of-type { border-bottom: none; }\n.vpg-name { font-size: 13.5px; font-weight: 600; }\n.vpg-name em { display: block; font-style: normal; font-family: var(--font-mono); font-size: 10px; color: var(--ink-3); }\n.vpg-track { position: relative; height: 18px; background: var(--surface-2); border: 1px solid var(--line); border-radius: 999px; overflow: hidden; }\n.vpg-zero { position: absolute; left: 50%; top: 0; bottom: 0; width: 1.5px; background: var(--line-strong); opacity: 0.5; }\n.vpg-band { position: absolute; top: 3px; bottom: 3px; background: rgba(26, 18, 20, 0.14); border-radius: 999px; }\n.vpg-median { position: absolute; top: 1px; bottom: 1px; width: 4px; margin-left: -2px; border-radius: 2px; }\n.vpg-median.vp-sur { background: var(--lime); }\n.vpg-median.vp-juste { background: #d9a942; }\n.vpg-median.vp-sous { background: #4c8b4f; }\n.vpg-value { font-family: var(--font-display); font-weight: 700; font-size: 15px; text-align: right; }\n.vpg-value.vp-sur { color: var(--green); }\n.vpg-value.vp-juste { color: #a97b1e; }\n.vpg-value.vp-sous { color: #3c7440; }\n.vpg-split { display: flex; height: 10px; border-radius: 999px; overflow: hidden; border: 1px solid var(--line); }\n.vps-sous { background: #7fb283; }\n.vps-juste { background: #d9cfc7; }\n.vps-sur { background: var(--lime); }\n.vpg-sep { border-top: 1.5px solid var(--line-strong); margin: 4px 0; }\n.vpg-legend { display: flex; gap: 16px; margin-top: 10px; font-family: var(--font-mono); font-size: 10.5px; color: var(--ink-2); flex-wrap: wrap; }\n.vpg-legend i { display: inline-block; width: 14px; height: 9px; border-radius: 999px; margin-right: 5px; vertical-align: -1px; }\n@media (max-width: 780px) { .vpg-row { grid-template-columns: 1fr 64px; } .vpg-track { grid-column: 1 / -1; } .vpg-split { grid-column: 1 / -1; } .vpg-axis { display: none; } }\n\n/* ================= Carte (Ka Maps — framework partagé Groupe Ka) =========\n Jetons du design system appliqués au chrome de la carte, mêmes réglages\n que Lou-Ka Maps. */\n.mapview .ka-map, .lmap3d .ka-map {\n --ka-accent: var(--accent);\n --ka-on-accent: var(--on-accent);\n --ka-surface: var(--surface);\n --ka-ink: var(--ink);\n --ka-line: var(--line-strong);\n --ka-radius: var(--r-ctl);\n --ka-shadow: 0 8px 24px rgba(26, 18, 20, 0.14);\n --ka-font: var(--font-body);\n}\n.mapview { position: relative; overflow: hidden; }\n.mapview .ka-map { position: absolute; inset: 0; }\n\n/* mini-carte 3D de la fiche (Emplacement) — bâtiment de l'annonce en cerise */\n.lmap3d {\n position: relative; height: 340px; border: 1.5px solid var(--ink);\n border-radius: var(--r-card); box-shadow: var(--shadow-off-soft);\n overflow: hidden; background: var(--surface-2);\n}\n.lmap3d-skel {\n background: linear-gradient(90deg, #eeece5 25%, #f7f5ef 50%, #eeece5 75%);\n background-size: 800px 100%; animation: shimmer 1.4s infinite linear;\n}\n.lmap3d-legende {\n position: absolute; left: 10px; bottom: 10px; z-index: 5;\n display: inline-flex; align-items: center; gap: 6px;\n padding: 4px 10px; border: 1.5px solid var(--ink);\n border-radius: 999px; background: var(--surface);\n font-size: 10.5px; font-weight: 500; color: var(--ink-2);\n pointer-events: none;\n}\n.lmap3d-legende i {\n width: 10px; height: 10px; border-radius: 3px;\n background: var(--accent); border: 1px solid rgba(26, 18, 20, 0.25);\n}\n@media (max-width: 780px) { .lmap3d { height: 280px; } }\n\n/* ================= Carte ================= */\n.map-split { display: grid; grid-template-columns: minmax(300px, 400px) 1fr; gap: 18px; height: calc(100dvh - 200px); min-height: 420px; }\n.map-list { overflow-y: auto; display: flex; flex-direction: column; gap: 14px; padding-right: 4px; scrollbar-width: thin; }\n.map-list .card { margin: 0; flex: 0 0 auto; }\n/* sync liste ↔ carte : fiche sélectionnée depuis une pastille de la carte */\n.map-card { border-radius: var(--r-card); }\n.map-card-sel .card { border-color: var(--accent); box-shadow: 4px 4px 0 var(--accent-soft), 0 0 0 2px var(--accent); }\n.mapwrap { position: relative; width: 100%; height: 100%; }\n.mapview { width: 100%; height: 100%; border: 1.5px solid var(--line-strong); border-radius: var(--r-card); box-shadow: var(--shadow-off-soft); overflow: hidden; background: var(--surface-2); }\n.mv-brand { position: absolute; top: 10px; left: 10px; z-index: 3; display: flex; align-items: center; gap: 6px; padding: 5px 11px; background: var(--surface); border: 1.5px solid var(--line-strong); border-radius: 999px; box-shadow: var(--shadow-off-soft); font-family: var(--font-mono); font-size: 11px; letter-spacing: 0.04em; color: var(--ink-2); pointer-events: none; }\n.mv-brand b { color: var(--ink); }\n.mv-brand-dot { width: 8px; height: 8px; border-radius: 50%; background: var(--lime); box-shadow: 0 0 0 3px var(--lime-soft); }\n.mv-legend { position: absolute; bottom: 26px; left: 10px; z-index: 3; display: flex; flex-direction: column; gap: 4px; padding: 8px 11px; background: rgba(255, 255, 255, 0.92); border: 1px solid var(--line); border-radius: var(--r-ctl); font-family: var(--font-mono); font-size: 10.5px; color: var(--ink-2); pointer-events: none; }\n.mv-legend span { display: flex; align-items: center; gap: 7px; }\n.mv-lg-pill { display: inline-block; width: 22px; height: 12px; border-radius: 999px; background: #fff; border: 1.5px solid rgba(26, 18, 20, 0.35); }\n.mv-lg-deal { background: var(--lime); border-color: var(--green); }\n.mv-credit { position: absolute; bottom: 8px; right: 8px; z-index: 3; padding: 4px 10px; background: rgba(255, 255, 255, 0.9); border-radius: 999px; font-family: var(--font-mono); font-size: 10px; letter-spacing: 0.04em; color: var(--ink-2); pointer-events: none; }\n.mv-credit b { color: var(--ink); }\n.mini-map .mv-brand, .mini-map .mv-legend { display: none; }\n.mini-map .mapwrap { height: 100%; }\n\n/* ---- carte propriété (fiche) : marqueur pulsant + anneaux piéton ---- */\n.pm-wrap { position: relative; width: 100%; height: 100%; }\n.pm-marker { display: flex; flex-direction: column; align-items: center; }\n.pm-pill { padding: 5px 13px; background: #fff; border: 1.5px solid var(--line-strong); border-radius: 999px; font-family: var(--font-display); font-weight: 700; font-size: 14px; color: var(--ink); box-shadow: var(--shadow-off-soft); white-space: nowrap; margin-bottom: 4px; }\n.pm-pill-deal { background: var(--lime); border-color: var(--green); color: #fff; }\n.pm-dot { width: 14px; height: 14px; border-radius: 50%; background: var(--lime); border: 2.5px solid #fff; box-shadow: 0 1px 4px rgba(26, 18, 20, 0.4); }\n.pm-pulse { position: absolute; bottom: -8px; width: 30px; height: 30px; border-radius: 50%; background: var(--lime); opacity: 0.35; animation: pm-pulse 2s ease-out infinite; }\n@keyframes pm-pulse { 0% { transform: scale(0.5); opacity: 0.45; } 80% { transform: scale(1.9); opacity: 0; } 100% { opacity: 0; } }\n.pm-rings-legend { position: absolute; bottom: 8px; left: 8px; z-index: 3; display: flex; gap: 12px; padding: 4px 10px; background: rgba(255, 255, 255, 0.9); border-radius: 999px; font-family: var(--font-mono); font-size: 10px; color: var(--green); pointer-events: none; }\n.mini-map .pm-wrap .mv-credit { display: block; }\n.map-loading { display: flex; align-items: center; justify-content: center; color: var(--ink-3); font-family: var(--font-mono); font-size: 13px; }\n@media (max-width: 780px) { .map-split { grid-template-columns: 1fr; height: calc(100dvh - 230px); } .map-list { display: none; } .results-tools { width: 100%; justify-content: space-between; } }\n.maplibregl-popup-content { padding: 0; border-radius: var(--r-card); overflow: hidden; border: 1.5px solid var(--line-strong); box-shadow: var(--shadow-off); font-family: var(--font-body); }\n.maplibregl-popup-close-button { font-size: 18px; padding: 2px 8px; color: var(--paper); z-index: 2; text-shadow: 0 0 4px rgba(26, 18, 20, 0.8); }\n.mv-pop img, .mv-noimg { width: 100%; height: 130px; object-fit: cover; }\n.mv-noimg { display: flex; align-items: center; justify-content: center; font-size: 34px; background: var(--surface-2); }\n.mv-pop-body { padding: 10px 12px 12px; }\n.mv-pop-price { font-family: var(--font-display); font-weight: 700; font-size: 18px; }\n.mv-pop-title { font-size: 13px; color: var(--ink-2); margin-top: 2px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }\n.mv-pop-meta { font-family: var(--font-mono); font-size: 11px; color: var(--ink-2); margin-top: 6px; }\n.mv-pop-src { font-family: var(--font-mono); font-size: 10px; color: var(--ink-3); text-transform: uppercase; letter-spacing: 0.06em; margin-top: 2px; }\n.mv-pop-cta { display: block; margin-top: 10px; padding: 8px 10px; text-align: center; background: var(--ink); color: #fff; border-radius: var(--r-ctl); font-weight: 600; font-size: 13px; }\n.mv-pop-cta:hover { background: var(--green-deep); }\n.mv-pop-deal { display: inline-block; margin-left: 6px; padding: 2px 8px; vertical-align: 3px; background: var(--lime); color: #fff; border-radius: 999px; font-family: var(--font-mono); font-size: 9.5px; text-transform: uppercase; letter-spacing: 0.05em; }\n.maplibregl-ctrl-attrib { font-size: 10px; }\n\n/* ================= Menu mobile ================= */\n.menu-btn { display: none; position: relative; z-index: 60; width: 44px; height: 44px; margin-left: auto; border: 1.5px solid var(--ink); border-radius: var(--r-ctl); background: var(--surface); cursor: pointer; padding: 0; flex-direction: column; align-items: center; justify-content: center; gap: 5px; box-shadow: 3px 3px 0 rgba(26, 18, 20, 0.15); transition: box-shadow 0.15s ease, transform 0.15s ease; }\n.menu-btn:active { transform: translate(2px, 2px); box-shadow: 1px 1px 0 rgba(26, 18, 20,0.15); }\n.menu-btn span { display: block; width: 18px; height: 2px; background: var(--ink); border-radius: 2px; transition: transform 0.25s ease, opacity 0.2s ease; }\n.menu-btn.open span:nth-child(1) { transform: translateY(7px) rotate(45deg); }\n.menu-btn.open span:nth-child(2) { opacity: 0; }\n.menu-btn.open span:nth-child(3) { transform: translateY(-7px) rotate(-45deg); }\n.mobile-menu { display: none; position: absolute; left: 0; right: 0; top: 100%; background: var(--paper); border-bottom: 2px solid var(--ink); box-shadow: 0 18px 30px rgba(26, 18, 20, 0.18); padding: 8px 16px calc(16px + env(safe-area-inset-bottom)); max-height: 0; overflow: hidden; opacity: 0; transition: max-height 0.3s ease, opacity 0.22s ease; }\n.mobile-menu.open { max-height: 480px; opacity: 1; }\n.mm-link { display: flex; align-items: center; gap: 12px; padding: 15px 10px; min-height: 52px; font-family: var(--font-display); font-weight: 700; font-size: 19px; letter-spacing: -0.02em; border-bottom: 1.5px dashed var(--line); opacity: 0; transform: translateY(-8px); transition: opacity 0.25s ease, transform 0.25s ease; }\n.mobile-menu.open .mm-link { opacity: 1; transform: translateY(0); }\n.mm-link.active { color: var(--green); }\n.mm-ico { width: 26px; text-align: center; font-size: 17px; }\n.mm-arrow { margin-left: auto; opacity: 0.25; }\n.mm-link:active { background: var(--lime-soft); border-radius: var(--r-ctl); }\n.mm-foot { padding: 12px 10px 4px; font-family: var(--font-mono); font-size: 10.5px; color: var(--ink-3); letter-spacing: 0.04em; }\n.mm-backdrop { position: fixed; inset: 0; z-index: var(--z-overlay, 800); background: rgba(26, 18, 20, 0.35); backdrop-filter: blur(2px); }\n@media (max-width: 760px) { .menu-btn { display: flex; } .nav { display: none; } .mobile-menu { display: block; } }\n\n/* ================= Footer =================\n Remplacé par le footer commun Groupe KA (ka/KaFooter.tsx — styles .ka-footer\n dans ka/tokens.css). */\n\n/* ================= Mobile : feuille de filtres + FAB ================= */\n.sheet-head { display: none; }\n.sheet-apply { display: none; }\n.sheet-backdrop { display: none; }\n.fab { display: none; }\n@media (max-width: 640px) {\n .header-inner { height: 56px; }\n .brand { font-size: 21px; }\n .hero h1 { font-size: clamp(30px, 9.4vw, 44px); }\n .hero p.lede { font-size: 15px; }\n .stat-row { flex-wrap: nowrap; overflow-x: auto; scrollbar-width: none; padding-bottom: 6px; margin-right: -16px; padding-right: 16px; }\n .stat-row::-webkit-scrollbar { display: none; }\n .stat-chip { flex: 0 0 auto; white-space: nowrap; }\n .filterbar { display: none; }\n .filterbar.open .f-primary { flex-direction: column; }\n .filterbar.open .f-ctl select { max-width: none; width: 100%; }\n .filterbar.open .f-more { display: none; }\n .filterbar.open { display: flex; flex-direction: column; gap: 12px; position: fixed; left: 0; right: 0; bottom: 0; z-index: 95; margin: 0; border-radius: 20px 20px 0 0; border-width: 2px 0 0 0; max-height: 82dvh; overflow-y: auto; -webkit-overflow-scrolling: touch; padding: 16px 18px calc(18px + env(safe-area-inset-bottom)); box-shadow: 0 -16px 48px rgba(16, 18, 16, 0.35); animation: sheet-up 0.22s ease; }\n @keyframes sheet-up { from { transform: translateY(30%); opacity: 0.4; } to { transform: none; opacity: 1; } }\n .filterbar.open .sheet-head { display: flex; justify-content: space-between; align-items: center; font-family: var(--font-display); font-weight: 700; font-size: 17px; text-transform: uppercase; position: sticky; top: -16px; background: var(--surface); padding: 6px 0 8px; border-bottom: 1.5px solid var(--line); margin-bottom: 2px; z-index: 1; }\n .sheet-close { border: 1.5px solid var(--ink); background: var(--surface); border-radius: 50%; width: 36px; height: 36px; font-size: 15px; cursor: pointer; line-height: 1; }\n .filterbar.open .sheet-apply { display: block; width: 100%; }\n .sheet-backdrop { display: block; position: fixed; inset: 0; z-index: 90; background: rgba(16, 18, 16, 0.45); backdrop-filter: blur(2px); }\n .fab { display: flex; align-items: center; gap: 6px; position: fixed; left: 50%; transform: translateX(-50%); bottom: calc(18px + env(safe-area-inset-bottom)); z-index: 80; background: var(--ink); color: var(--lime); border: 1.5px solid var(--ink); border-radius: 999px; padding: 13px 24px; font-family: var(--font-display); font-weight: 700; font-size: 15px; cursor: pointer; box-shadow: 0 8px 24px rgba(16, 18, 16, 0.35), 4px 4px 0 rgba(26, 18, 20, 0.25); }\n .fab:active { transform: translateX(-50%) scale(0.97); }\n .results-head { margin-top: 20px; }\n .chips { margin-right: -16px; padding-right: 16px; }\n .notice { padding: 48px 16px; }\n}\n@media (max-width: 900px) { .f-search input, .f-native, .f-ctl select { font-size: 16px; } }\n\n/* --- Sources : bannières → sous-agences -------------------------------- */\n.franchise-list { display: flex; flex-direction: column; gap: 10px; margin: 18px 0; }\n.franchise { border: 2px solid var(--ink); background: var(--surface); box-shadow: var(--shadow-off-soft); }\n.franchise-head {\n width: 100%; display: flex; align-items: center; gap: 12px; padding: 14px 16px;\n background: none; border: 0; cursor: pointer; font-family: var(--font-display);\n font-size: 16px; font-weight: 600; color: var(--ink); text-align: left;\n}\n.franchise-head:hover { background: var(--surface-2); }\n.fh-caret { color: var(--green); width: 14px; }\n.fh-name { flex: 1; }\n.fh-sub { font-size: 12px; font-weight: 500; color: var(--ink-3); font-family: var(--font-mono); }\n.fh-count {\n font-family: var(--font-mono); font-weight: 700; background: var(--ink);\n color: var(--lime); padding: 3px 10px; min-width: 64px; text-align: right;\n}\n.subagency-list { list-style: none; margin: 0; padding: 0 16px 10px 40px; border-top: 1px solid var(--line); }\n.subagency-list li {\n display: flex; align-items: center; justify-content: space-between; gap: 12px;\n padding: 8px 0; border-bottom: 1px dotted var(--line); font-size: 14px;\n}\n.subagency-list li:last-child { border-bottom: 0; }\n.sa-name { color: var(--ink-2); }\n\n/* --- Pagination (accueil) ---------------------------------------------- */\n.pager { display: flex; flex-wrap: wrap; align-items: center; justify-content: center;\n gap: 6px; margin: 32px 0 8px; }\n.pager-btn {\n font-family: var(--font-mono); font-size: 14px; min-width: 40px; padding: 8px 12px;\n border: 2px solid var(--ink); background: var(--surface); color: var(--ink);\n cursor: pointer; box-shadow: var(--shadow-off-soft);\n}\n.pager-btn:hover:not(:disabled) { background: var(--lime-soft); }\n.pager-btn.on { background: var(--ink); color: var(--lime); font-weight: 700; }\n.pager-btn:disabled { opacity: .4; cursor: not-allowed; box-shadow: none; }\n.pager-gap { padding: 0 4px; color: var(--ink-3); }\n.pager-info { width: 100%; text-align: center; margin-top: 8px; font-size: 12px;\n color: var(--ink-3); font-family: var(--font-mono); }\n\n\n\n/* --- Le quartier (census / proximité / chaleur / crime) — porté de Lou-Ka --- */\n/* --- Section « Le quartier » (fiche) --------------------------------------- */\n.quartier { margin-top: 34px; }\n.quartier h2 { font-size: 24px; letter-spacing: -0.02em; }\n.q-sub { color: var(--ink-3); font-size: 13px; margin: 4px 0 16px; }\n.q-grid {\n display: grid; grid-template-columns: repeat(3, 1fr); gap: 10px;\n}\n.q-grid { grid-template-columns: repeat(2, 1fr); }\n.q-cell {\n background: var(--surface); border: 1.5px solid var(--line-strong);\n border-radius: var(--r-card); padding: 12px 14px; box-shadow: var(--shadow-flat);\n}\n.q-val { font-family: var(--font-display); font-weight: 700; font-size: 19px; letter-spacing: -0.02em; }\n.q-label { font-family: var(--font-mono); font-size: 10.5px; color: var(--ink-3);\n text-transform: uppercase; letter-spacing: 0.06em; margin-top: 3px; }\n.q-prox { margin-top: 18px; display: flex; flex-direction: column; gap: 8px; }\n.q-bar { display: flex; align-items: center; gap: 10px; font-size: 13px; }\n.q-bar-label { flex: 0 0 150px; color: var(--ink-2); }\n.q-bar-label { flex-basis: 120px; font-size: 12px; }\n.q-bar-track {\n flex: 1; height: 10px; background: var(--surface-2);\n border: 1px solid var(--line-strong); border-radius: 999px; overflow: hidden;\n}\n.q-bar-fill { display: block; height: 100%; background: var(--green); border-radius: 999px; }\n.q-bar-num { flex: 0 0 30px; text-align: right; font-family: var(--font-mono);\n font-size: 11.5px; font-weight: 700; }\n.q-badges { display: flex; flex-wrap: wrap; gap: 8px; margin-top: 16px; }\n.q-badge {\n display: inline-flex; align-items: center; gap: 6px;\n border: 1.5px solid var(--line-strong); border-radius: 999px;\n padding: 7px 13px; font-size: 12.5px; background: var(--surface);\n}\n.q-badge.cool { background: var(--lime-soft); border-color: var(--green); color: var(--green-deep); }\n.q-badge.hot { background: var(--amber-soft); border-color: var(--amber); color: #8a5a12; }\n.quartier .fine { margin-top: 10px; }\n.q-cell { padding: 9px 11px; }\n.q-val { font-size: 16px; }\n.q-bar { gap: 8px; font-size: 12px; }\n.q-bar-track { height: 8px; }\n.q-badge-sub { display: block; font-size: 10.5px; color: var(--ink-3); font-weight: 400; margin-left: 4px; }\n\n/* --- Vrai-Prix : estimation de valeur ---------------------------------- */\n.vraiprix { border: 2px solid var(--ink); background: var(--surface-2);\n box-shadow: var(--shadow-off-soft); padding: 14px; margin: 14px 0; }\n.vp-head { display: flex; align-items: center; justify-content: space-between; gap: 8px; }\n.vp-logo { font-family: var(--font-display); font-weight: 700; color: var(--green-deep);\n letter-spacing: -.3px; }\n.vp-conf { font-family: var(--font-mono); font-size: 11px; padding: 2px 7px; border: 1px solid var(--ink); }\n.vp-conf-A { background: var(--lime); color: #fff; } .vp-conf-B { background: var(--lime-soft); }\n.vp-conf-C { background: var(--amber-soft); } .vp-conf-D { background: #f0d9d9; }\n.vp-k { font-size: 11px; color: var(--ink-3); text-transform: uppercase;\n letter-spacing: .5px; margin-top: 8px; }\n.vp-value { font-family: var(--font-display); font-size: 26px; font-weight: 700;\n letter-spacing: -1px; color: var(--ink); }\n.vp-range { font-size: 12px; color: var(--ink-2); font-family: var(--font-mono); }\n/* jauge Vrai-Prix : fourchette P10–P90 + marqueurs estimation / prix demandé */\n.vp-gauge { margin-top: 10px; }\n.vp-gauge-track { position: relative; height: 14px; border-radius: 999px; background: var(--surface); border: 1px solid var(--line-strong); overflow: hidden; }\n.vp-gauge-band { position: absolute; inset: 3px 6%; background: linear-gradient(90deg, var(--lime-soft), rgba(226, 55, 68, 0.35), var(--lime-soft)); border-radius: 999px; }\n.vp-gauge-est { position: absolute; top: 0; bottom: 0; width: 4px; margin-left: -2px; background: var(--lime); border-radius: 2px; }\n.vp-gauge-ask { position: absolute; top: 2px; bottom: 2px; width: 4px; margin-left: -2px; background: var(--ink); border-radius: 2px; }\n.vp-gauge-ends { display: flex; justify-content: space-between; font-family: var(--font-mono); font-size: 10px; color: var(--ink-3); margin-top: 4px; }\n.vp-gauge-legend { display: flex; gap: 14px; font-family: var(--font-mono); font-size: 10px; color: var(--ink-2); margin-top: 5px; }\n.vp-dot-est, .vp-dot-ask { display: inline-block; width: 9px; height: 9px; border-radius: 3px; margin-right: 4px; vertical-align: -1px; }\n.vp-dot-est { background: var(--lime); }\n.vp-dot-ask { background: var(--ink); }\n.vp-delta { font-size: 13px; margin-top: 8px; padding: 6px 8px; border-radius: var(--r-ctl); }\n.vp-over { background: #f6e2e2; color: #8a2b2b; }\n.vp-under { background: #e2f0e6; color: #1c5c41; }\n.vp-fair { background: var(--surface); color: var(--ink-2); }\n.vp-link { display: block; text-align: center; margin-top: 10px; font-weight: 700;\n font-size: 13px; padding: 8px; background: var(--green-deep); color: #fff;\n text-decoration: none; }\n.vp-link:hover { background: var(--green); }\n\n/* =============================================================================\n Harmonisation Groupe KA — header (badge + compte KA ID), pages Profil,\n Contact et légales. Le socle vient de ka/tokens.css.\n============================================================================= */\n\n/* ---- Header : badge « Un service Groupe KA » + zone compte ---- */\n.header-inner .gk-badge { flex: none; }\n@media (max-width: 900px) { .header-inner .gk-badge { display: none; } }\n.header-acct { display: flex; align-items: center; gap: 10px; flex: none; }\n.ka-auth { display: flex; align-items: center; gap: 10px; }\n.ka-login {\n display: inline-flex; align-items: center; gap: 6px; min-height: 40px;\n padding: 8px 15px; border: 1.5px solid var(--ink); border-radius: 999px;\n background: var(--surface); color: var(--ink); cursor: pointer;\n font-family: var(--font-display); font-weight: 600; font-size: 13.5px;\n box-shadow: 3px 3px 0 rgba(20, 24, 20, 0.15);\n transition: transform 0.13s ease, box-shadow 0.13s ease, background 0.15s ease;\n}\n.ka-login b { background: var(--ink); color: var(--accent); border-radius: 5px; padding: 0 6px 1px; transform: rotate(-2deg); transition: transform 0.15s ease; }\n.ka-login:hover { transform: translate(-1px, -1px); box-shadow: 4px 4px 0 rgba(20, 24, 20, 0.2); }\n.ka-login:hover b { transform: rotate(0); }\n.ka-login:active { transform: translate(2px, 2px); box-shadow: none; }\n.ka-signup { font-family: var(--font-mono); font-size: 11px; color: var(--ink-2); text-decoration: underline; text-underline-offset: 3px; white-space: nowrap; }\n.ka-signup:hover { color: var(--accent-deep); }\n@media (max-width: 1100px) { .header-acct .ka-signup { display: none; } }\n.ka-acct {\n display: inline-flex; align-items: center; gap: 8px; min-height: 40px;\n padding: 6px 14px; border: 1.5px solid var(--ink); border-radius: 999px;\n background: var(--surface); font-family: var(--font-display);\n font-weight: 600; font-size: 13.5px; color: var(--ink);\n max-width: 160px; overflow: hidden; white-space: nowrap; text-overflow: ellipsis;\n}\n.ka-acct:hover, .ka-acct.active { background: var(--ink); color: var(--accent); }\n.ka-acct-pic { width: 24px; height: 24px; border-radius: 50%; flex: none; border: 1px solid var(--line); }\n@media (max-width: 760px) {\n .header-acct { margin-left: auto; }\n .menu-btn { margin-left: 0; }\n .ka-login { min-height: 44px; }\n}\n@media (max-width: 380px) { .header-acct { display: none; } } /* → menu mobile */\n\n/* ---- Menu mobile : compte + badge groupe ---- */\n.mm-auth { display: flex; align-items: center; gap: 14px; flex-wrap: wrap; padding: 15px 10px; border-bottom: 1.5px dashed var(--line); }\n.mm-auth .ka-login { min-height: 44px; }\n.mm-foot p { margin: 10px 0 0; }\n\n/* ---- Générique : lede (Profil / Contact) ---- */\n.lede { color: var(--ink-2); font-size: 15.5px; max-width: 640px; }\n\n/* ================= Page Profil (KA ID) ================= */\n.profil { padding: 44px 0 90px; }\n.profil h1 { font-size: clamp(28px, 4.6vw, 44px); margin: 10px 0 24px; letter-spacing: -0.03em; }\n.profil .lede { margin-bottom: 22px; }\n.profil .notice { padding: 60px 0; }\n\n/* Carte de membre — encre + cerise */\n.pc {\n position: relative; overflow: hidden; max-width: 460px;\n background: var(--ink); color: var(--paper);\n border: 1.5px solid var(--ink); border-radius: var(--r-card);\n box-shadow: var(--shadow-off-soft); padding: 22px 26px 0;\n}\n.pc-watermark {\n position: absolute; right: -18px; bottom: 14px; font-family: var(--font-display);\n font-weight: 700; font-size: 150px; line-height: 1; letter-spacing: -0.06em;\n color: rgba(245, 243, 238, 0.05); pointer-events: none; user-select: none;\n}\n.pc-head { display: flex; align-items: baseline; justify-content: space-between; gap: 12px; flex-wrap: wrap; }\n.pc-brand { font-family: var(--font-display); font-weight: 700; font-size: 24px; letter-spacing: -0.03em; }\n.pc-ka { display: inline-block; background: var(--accent); color: var(--on-accent); border-radius: 6px; padding: 0 7px 2px; margin-left: 3px; transform: rotate(-2deg); }\n.pc-label { font-family: var(--font-mono); font-size: 9.5px; font-weight: 700; text-transform: uppercase; letter-spacing: 0.16em; color: rgba(245, 243, 238, 0.5); }\n.pc-id-block { margin: 26px 0 22px; display: flex; flex-direction: column; gap: 4px; }\n.pc-id-label { font-family: var(--font-mono); font-size: 10px; font-weight: 700; text-transform: uppercase; letter-spacing: 0.2em; color: var(--accent); }\n.pc-id { font-family: var(--font-mono); font-weight: 700; font-size: clamp(17px, 4.4vw, 22px); letter-spacing: 0.04em; word-break: break-all; }\n.pc-foot { display: flex; align-items: flex-end; justify-content: space-between; gap: 14px; padding-bottom: 18px; }\n.pc-holder { display: flex; flex-direction: column; gap: 3px; min-width: 0; }\n.pc-holder-name { font-family: var(--font-display); font-weight: 600; font-size: 15px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }\n.pc-role-badge { align-self: flex-start; font-family: var(--font-mono); font-size: 9.5px; font-weight: 700; text-transform: uppercase; letter-spacing: 0.1em; background: var(--accent); color: var(--on-accent); border-radius: 999px; padding: 2px 9px; }\n.pc-holder-since { font-family: var(--font-mono); font-size: 10.5px; color: rgba(245, 243, 238, 0.5); letter-spacing: 0.06em; }\n.pc-avatar { width: 52px; height: 52px; border-radius: 50%; border: 2px solid var(--accent); flex: none; object-fit: cover; }\n.pc-strip { display: flex; align-items: flex-end; gap: 5px; margin: 0 -26px; padding: 9px 18px; background: rgba(226, 55, 68, 0.14); border-top: 1px solid rgba(226, 55, 68, 0.4); overflow: hidden; }\n.pc-strip i { display: block; width: 3px; border-radius: 1px; background: var(--accent); opacity: 0.75; }\n.pc-strip i:nth-child(3n) { height: 14px; opacity: 0.4; }\n.pc-strip i:nth-child(3n+1) { height: 9px; }\n.pc-strip i:nth-child(3n+2) { height: 17px; opacity: 0.95; }\n.pc-copy { margin-top: 16px; }\n.pc-copy.ok { background: var(--ink); color: var(--accent); }\n\n.profil-grid {\n display: grid; grid-template-columns: repeat(auto-fill, minmax(220px, 1fr));\n gap: 12px; margin-top: 28px; max-width: 720px;\n}\n.pg-item { background: var(--surface); border: 1.5px solid var(--line-strong); border-radius: var(--r-ctl); padding: 12px 14px; display: flex; flex-direction: column; gap: 4px; min-width: 0; }\n.pg-label { font-family: var(--font-mono); font-size: 10px; font-weight: 700; text-transform: uppercase; letter-spacing: 0.12em; color: var(--ink-3); }\n.pg-value { font-weight: 600; font-size: 14.5px; word-break: break-word; }\n.pg-value.mono { font-family: var(--font-mono); color: var(--accent-deep); }\n.profil-note { max-width: 640px; color: var(--ink-2); font-size: 13.5px; margin-top: 22px; }\n.profil-note a { text-decoration: underline; text-underline-offset: 3px; }\n.profil-actions { display: flex; gap: 10px; flex-wrap: wrap; margin-top: 26px; }\n\n/* Profil hub Groupe KA (lecture seule) */\n.hub-profile { margin-top: 34px; padding-top: 24px; border-top: 1.5px solid var(--line-strong); max-width: 720px; display: flex; flex-direction: column; gap: 14px; }\n.hub-profile h3 { font-size: 18px; }\n.hub-profile .hub-bio { color: var(--ink-2); font-size: 14px; margin: 0; max-width: 560px; }\n.hub-profile .pub-meta { display: flex; gap: 8px; flex-wrap: wrap; }\n.hub-profile .stat-chip { display: inline-flex; align-items: center; gap: 6px; }\n.hub-profile a.stat-chip:hover { background: var(--accent-soft); }\n.hub-hint { color: var(--ink-3); font-size: 12.5px; margin: 0; }\n\n/* ================= Pages légales ================= */\n.legal { padding: 48px 0 80px; max-width: 780px; }\n.legal h1 { font-size: clamp(28px, 4.6vw, 44px); margin: 8px 0 6px; }\n.legal .legal-meta { color: var(--ink-3); font-family: var(--font-mono); font-size: 12px; margin: 0 0 26px; }\n.legal h2 { font-size: 20px; margin: 30px 0 8px; border-left: 4px solid var(--accent); padding-left: 10px; }\n.legal p, .legal li { color: var(--ink-2); font-size: 14.5px; }\n.legal ul { padding-left: 20px; display: flex; flex-direction: column; gap: 6px; }\n.legal a { text-decoration: underline; text-underline-offset: 3px; }\n.legal b { color: var(--ink); }\n\n/* ================= Page Contact (écosystème Groupe KA) ================= */\n.contact { padding: 48px 0 90px; }\n.contact h1 { font-size: clamp(30px, 5vw, 52px); margin: 12px 0 14px; text-transform: uppercase; letter-spacing: -0.03em; }\n.contact-cards { display: grid; grid-template-columns: repeat(auto-fit, minmax(230px, 1fr)); gap: 14px; margin: 28px 0 6px; max-width: 900px; }\n.contact-card {\n display: flex; flex-direction: column; gap: 8px; min-height: var(--touch, 44px);\n background: var(--surface); border: 1.5px solid var(--ink);\n border-radius: var(--r-card); padding: 18px 20px;\n box-shadow: var(--shadow-off-soft);\n transition: transform 0.15s ease, box-shadow 0.15s ease;\n}\n.contact-card:hover { transform: translate(-2px, -2px); box-shadow: var(--shadow-off); }\n.contact-role { font-family: var(--font-mono); font-size: 10.5px; font-weight: 700; text-transform: uppercase; letter-spacing: 0.1em; color: var(--green); }\n.contact-mail { font-family: var(--font-display); font-weight: 700; font-size: clamp(14px, 2vw, 17px); word-break: break-all; border-bottom: 2px solid var(--accent); align-self: flex-start; }\n.contact-disclaimer { max-width: 720px; margin: 24px 0 0; padding: 14px 16px; border-left: 3px solid var(--accent); background: var(--accent-soft); color: var(--ink-2); font-size: 13.5px; }\n.contact-disclaimer b { color: var(--ink); }\n.contact-hub { display: flex; gap: 12px; flex-wrap: wrap; margin-top: 26px; }\n.contact-sites { margin-top: 46px; }\n.contact-sites h2 { font-size: 21px; text-transform: uppercase; margin-bottom: 14px; }\n.contact-sites ul { list-style: none; margin: 0; padding: 0; display: grid; grid-template-columns: repeat(auto-fill, minmax(230px, 1fr)); gap: 10px; }\n.contact-sites a { display: flex; flex-direction: column; gap: 3px; min-height: var(--touch, 44px); background: var(--surface); border: 1.5px solid var(--line-strong); border-radius: var(--r-ctl); padding: 12px 14px; transition: transform 0.14s ease, box-shadow 0.14s ease; }\n.contact-sites a:hover { transform: translate(-2px, -2px); box-shadow: 4px 4px 0 var(--ink); }\n.contact-sites b { font-family: var(--font-display); font-size: 15px; }\n.contact-sites span { font-size: 12px; color: var(--ink-3); }\n@media (max-width: 480px) {\n .header-inner { gap: 10px; }\n .ka-login { font-size: 12px; padding: 6px 10px; gap: 4px; min-height: 44px; }\n}\n\n/* Bulle KA Agent : sur mobile, remontée au-dessus de la barre CTA collante des\n fiches (sinon elle chevauche le bouton « Voir chez … »). */\n@media (max-width: 899px) {\n .kaa-btn {\n bottom: calc(88px + env(safe-area-inset-bottom, 0px)) !important;\n }\n}\n\n/* Footer commun KA : zones tactiles ≥ 44 px pour les petits liens (Ka2, Ka4…)\n — padding compensé par une marge négative : aucun changement visuel. */\n.ka-footer .sites a, .ka-footer .legal a, .ka-footer .contacts a {\n display: inline-block; padding: 12px 8px; margin: -12px -8px;\n}\n\n/* ================= Qualité des annonces / images ================= */\n/* Image de secours par TYPE DE BIEN (jamais d'icône d'image cassée) */\n.type-fallback {\n display: flex; flex-direction: column; align-items: center; justify-content: center;\n gap: 9px; width: 100%; height: 100%; min-height: 120px;\n background:\n radial-gradient(circle at 78% 18%, rgba(226, 55, 68, 0.14), transparent 52%),\n repeating-linear-gradient(45deg, #f3ece9 0 14px, #f7f1ef 14px 28px);\n color: var(--accent-deep);\n}\n.type-fallback .ico { opacity: 0.75; }\n.type-fallback span {\n font-family: var(--font-mono); font-size: 10.5px; font-weight: 700;\n text-transform: uppercase; letter-spacing: 0.12em; color: var(--ink-3);\n}\n.carousel-empty .type-fallback { aspect-ratio: 16/11; }\n\n/* légende de photo (étiquette de pièce de la source) */\n.carousel-caption {\n position: absolute; left: 12px; bottom: 12px; z-index: 2; max-width: 60%;\n background: rgba(26, 18, 20, 0.82); color: #f5f3ee;\n font-family: var(--font-mono); font-size: 11px; font-weight: 600;\n padding: 4px 10px; border-radius: 999px;\n overflow: hidden; text-overflow: ellipsis; white-space: nowrap;\n}\n\n/* mention loyer mensuel (transaction = location) */\n.per-month { font-size: 0.55em; font-weight: 600; color: var(--ink-3); letter-spacing: 0; }\n\n/* lightbox : l'image zoomable ne doit pas déclencher le scroll de la page */\n.lightbox img { user-select: none; -webkit-user-drag: none; }\n\n/* ---- Stats : qualité des données ---- */\n.q-table-wrap { overflow-x: auto; }\n.q-table { width: 100%; border-collapse: collapse; font-size: 13px; min-width: 520px; }\n.q-table th { text-align: left; font-family: var(--font-mono); font-size: 10px; text-transform: uppercase; letter-spacing: 0.08em; color: var(--ink-3); padding: 6px 10px; border-bottom: 1.5px solid var(--ink); }\n.q-table td { padding: 6px 10px; border-bottom: 1px solid var(--line); }\n.q-table .num { text-align: right; font-family: var(--font-mono); }\n.q-meter { display: inline-block; width: 74px; height: 9px; background: var(--surface-2); border: 1px solid var(--line-strong); border-radius: 999px; overflow: hidden; vertical-align: -1px; margin-right: 7px; }\n.q-meter i { display: block; height: 100%; background: var(--green); }\n\n\n/* ---- Criminalité détaillée SPVM (bloc quartier) ---- */\n.q-crime { width: 100%; }\n.q-crime-cats { list-style: none; margin: 8px 0 0; padding: 0; }\n.q-crime-cats li { display: flex; align-items: center; gap: 8px;\n padding: 3px 0; font-size: 12.5px; }\n.q-crime-nom { flex: 0 0 46%; color: var(--ink-2, #555); overflow: hidden;\n text-overflow: ellipsis; white-space: nowrap; }\n.q-crime-barre { flex: 1 1 auto; height: 10px; background: var(--surface-2, #f0ede8);\n border-radius: 5px; overflow: hidden; }\n.q-crime-barre i { display: block; height: 100%; border-radius: 5px;\n background: var(--accent, #e23744); opacity: 0.55; }\n.q-crime-n { flex: 0 0 52px; text-align: right; font-weight: 600;\n color: var(--ink, #222); white-space: nowrap; }\n.q-crime-n small { font-weight: 400; color: var(--ink-3, #888); }\n.q-crime-src { margin-top: 8px; }\n\n\n/* ---- Risque d'inondation (fiche) — BDZI gouv. du Québec ---- */\n.f-zi .zi-head { display: flex; align-items: center; gap: 10px; }\n.zi-badge { display: inline-block; padding: 3px 10px; border-radius: 999px;\n font-size: 12.5px; font-weight: 700; }\n.zi-eleve { background: #fde8e8; color: #a12622; }\n.zi-modere { background: #fdf3e0; color: #8a5a00; }\n.zi-present { background: #fdf3e0; color: #8a5a00; }\n.zi-ok { background: #e7f4ea; color: #1e6b34; }\n.zi-nc { background: var(--surface-2, #f0ede8); color: var(--ink-3, #888); }\n.zi-liste { margin: 8px 0 0; padding: 0; list-style: none; font-size: 13px; }\n.zi-liste li { padding: 4px 0; border-top: 1px solid var(--line, #e6e4df); }\n\n\n/* ---- tuiles KPI + tableau compacts (partagés air/essence) ---- */\n.rdl-kpis { display: flex; flex-wrap: wrap; gap: 10px; margin: 2px 0 12px; }\n.rdl-kpi { flex: 1 1 90px; min-width: 90px; background: var(--surface-2, #f7f5f1);\n border-radius: 10px; padding: 10px 12px; }\n.rdl-kpi-v { display: block; font-size: 20px; font-weight: 700;\n letter-spacing: -0.02em; color: var(--ink, #222); }\n.rdl-kpi-l { display: block; font-size: 11px; line-height: 1.35;\n color: var(--ink-3, #888); margin-top: 2px; }\n.rdl-table { width: 100%; border-collapse: collapse; font-size: 13px; }\n.rdl-table td { padding: 5px 8px 5px 0; border-top: 1px solid var(--line, #e6e4df);\n vertical-align: top; }\n.rdl-table .rdl-addr { max-width: 46%; }\n.rdl-table .rdl-prix { font-weight: 600; white-space: nowrap; }\n.rdl-table .rdl-date { white-space: nowrap; color: var(--ink-2, #555); }\n.rdl-table .rdl-dist { color: var(--ink-3, #888); white-space: nowrap; text-align: right; }\n.rdl-cap { caption-side: top; text-align: left; font-size: 13px; font-weight: 700;\n color: var(--ink, #222); padding: 6px 0; }\n\n/* ---- Qualité de l'air (RSQAQ) + Essence à proximité ---- */\n.air-liste { list-style: none; margin: 10px 0 0; padding: 0; }\n.air-liste li { display: flex; align-items: center; gap: 8px;\n padding: 4px 0; font-size: 12.5px; }\n.air-nom { flex: 0 0 44%; color: var(--ink-2); overflow: hidden;\n text-overflow: ellipsis; white-space: nowrap; }\n.air-barre { flex: 1 1 auto; height: 10px; background: var(--surface-2, #f0ede8);\n border-radius: 5px; overflow: hidden; }\n.air-barre i { display: block; height: 100%; border-radius: 5px;\n background: #4d9e64; }\n.air-barre i.air-sur { background: #c96a1f; }\n.air-val { flex: 0 0 34%; text-align: right; font-weight: 600;\n color: var(--ink); white-space: nowrap; overflow: hidden;\n text-overflow: ellipsis; }\n.air-val small { font-weight: 400; color: var(--ink-3); }\n.air-val .air-ref { display: block; font-size: 10px; }\n.gaz-head th { text-align: left; font-size: 11px; color: var(--ink-3);\n font-weight: 600; padding: 2px 8px 2px 0; }\n.gaz-best { display: inline-block; margin-left: 6px; padding: 1px 7px;\n border-radius: 999px; background: #e7f4ea; color: #1e6b34;\n font-size: 10.5px; font-weight: 700; }\n.gaz-adr { display: block; font-size: 11px; color: var(--ink-3); }\n\n\n/* ---- Commerces et transport (fiche) ---- */\n.cm-grille { list-style: none; margin: 6px 0 0; padding: 0;\n display: grid; grid-template-columns: 1fr 1fr; gap: 4px 18px; }\n@media (max-width: 560px) { .cm-grille { grid-template-columns: 1fr; } }\n.cm-item { display: flex; align-items: center; gap: 9px; padding: 5px 0;\n border-bottom: 1px solid var(--line, #eeece7); min-width: 0; }\n.cm-ico { flex: 0 0 28px; }\n.cm-txt { flex: 1 1 auto; min-width: 0; display: flex; flex-direction: column; }\n.cm-nom { font-size: 13px; font-weight: 600; color: var(--ink, #222);\n white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }\n.cm-poi { font-size: 11px; color: var(--ink-3, #8a877f);\n white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }\n.cm-dist { flex: 0 0 auto; font-size: 13px; font-weight: 700;\n color: var(--ink-2, #4c4a45); white-space: nowrap; }\n\n\n/* ---- Coût d'électricité (Hydro-Québec) ---- */\n.hydro-intro { margin: 2px 0 12px; color: var(--ink-2, #4c4a45); }\n.hydro-btn { appearance: none; border: 0; border-radius: 10px; cursor: pointer;\n background: var(--accent, #2b7a3b); color: #fff; font-weight: 700;\n font-size: 14px; padding: 11px 18px; }\n.hydro-btn:disabled { opacity: 0.6; cursor: progress; }\n.hydro-montant { font-size: 26px; font-weight: 800; letter-spacing: -0.02em;\n color: var(--navy, #1c1b18); display: flex; align-items: baseline;\n gap: 10px; flex-wrap: wrap; }\n.hydro-montant small { font-size: 14px; font-weight: 500; color: var(--ink-3); }\n.hydro-an { font-size: 14px; font-weight: 600; color: var(--ink-2, #4c4a45); }\n.hydro-vide { color: var(--ink-3, #8a877f); }\n\n\n/* ============================================================================\n PASSE DE DESIGN — « éditorial sharp » appliqué à toute la fiche\n Blocs = cartes encre (bordure 1,5 px + ombre décalée douce), titres à\n marqueur accent + filet, tuiles KPI blanches à ombre dure, tableaux zébrés,\n barres en dégradé, pastilles unifiées (mono, point d'état, liseré).\n Aucune propriété `order` (règle Groupe Ka : ordre DOM = ordre visuel).\n ========================================================================== */\n\n/* --- Blocs de la fiche : cartes posées sur le papier --- */\n.f-bloc:not(.f-galerie):not(.f-hero),\n.quartier {\n background: var(--surface);\n border: 1.5px solid var(--ink);\n border-radius: var(--r-card);\n padding: 18px 20px 16px;\n box-shadow: var(--shadow-off-soft);\n}\n@media (max-width: 640px) {\n .f-bloc:not(.f-galerie):not(.f-hero),\n .quartier { padding: 15px 15px 13px; }\n}\n/* blocs pleine largeur sous la grille : respiration entre les cartes */\n.detail > .f-bloc { margin-top: 22px; }\n\n/* --- Titres de section : carré accent + filet éditorial --- */\n.f-bloc h2, .quartier h2 {\n display: flex; align-items: center; gap: 10px;\n font-size: 19px; letter-spacing: -0.015em; margin-bottom: 14px;\n border-left: 0; padding-left: 0;\n}\n.f-bloc h2::before, .quartier h2::before {\n content: \"\"; flex: 0 0 9px; width: 9px; height: 9px;\n background: var(--accent); border: 1.5px solid var(--ink);\n box-shadow: 2px 2px 0 var(--ink);\n}\n.f-bloc h2::after, .quartier h2::after {\n content: \"\"; flex: 1 1 auto; height: 1.5px; min-width: 20px;\n background: var(--line);\n}\n\n/* --- Tuiles KPI : blanches, bord encre, ombre dure accent --- */\n.rdl-kpi {\n background: var(--surface);\n border: 1.5px solid var(--ink);\n border-radius: var(--r-ctl);\n box-shadow: 3px 3px 0 var(--accent-soft);\n}\n.rdl-kpi-v { font-family: var(--font-display); }\n.q-cell { box-shadow: 3px 3px 0 rgba(20, 24, 20, 0.1); border-radius: var(--r-ctl); }\n.q-val { font-size: 20px; }\n\n/* --- Tableaux : en-têtes mono, zébrure, survol accent --- */\n.rdl-table td { padding: 7px 8px 7px 0; }\n.rdl-table tbody tr:nth-child(even) td,\n.rdl-table > tr:nth-child(even) td { background: var(--surface-2); }\n.rdl-table tr:hover td { background: var(--accent-soft); }\n.gaz-head th {\n font-family: var(--font-mono); font-size: 10px; font-weight: 700;\n text-transform: uppercase; letter-spacing: 0.08em;\n border-bottom: 1.5px solid var(--ink);\n}\n.rdl-cap { font-family: var(--font-display); }\ntable.rooms tbody tr:hover td { background: var(--accent-soft); }\n\n/* --- Barres : pistes bordées + remplissage en dégradé --- */\n.q-bar-track, .q-crime-barre, .air-barre {\n background: var(--surface-2);\n border: 1px solid var(--line);\n height: 12px;\n}\n.q-bar-fill {\n background: linear-gradient(90deg, var(--accent), var(--accent-deep));\n}\n.q-crime-barre i {\n background: linear-gradient(90deg, #f0808a, var(--accent));\n opacity: 0.9;\n}\n.air-barre i { background: linear-gradient(90deg, #6fbc85, #2e7d4a); }\n.air-barre i.air-sur { background: linear-gradient(90deg, #e08a48, #c96a1f); }\n\n/* --- Pastilles d'état unifiées (zi-badge & cie) : mono + point d'état --- */\n.zi-badge {\n display: inline-flex; align-items: center; gap: 6px;\n font-family: var(--font-mono); font-size: 10.5px; font-weight: 700;\n text-transform: uppercase; letter-spacing: 0.06em;\n padding: 4px 10px; border: 1.5px solid currentColor;\n}\n.zi-badge::before {\n content: \"\"; width: 6px; height: 6px; border-radius: 50%;\n background: currentColor;\n}\n.gaz-best { border: 1px solid currentColor; }\n\n/* --- Listes riches (zones d'inondation) : mini-cartes à liseré accent --- */\n.zi-liste { display: flex; flex-direction: column; gap: 8px; }\n.zi-liste li {\n border: 1px solid var(--line); border-left: 3px solid var(--accent);\n border-top: 1px solid var(--line);\n border-radius: var(--r-ctl); padding: 9px 12px;\n background: var(--surface-2);\n}\n\n/* --- Inclusions : icône et libellé alignés sur une seule ligne --- */\n.amenity { display: inline-flex; align-items: center; gap: 6px; }\n\n/* --- Notes de bas de bloc : filet pointillé --- */\n.f-bloc .fine, .quartier .fine {\n margin-top: 12px; padding-top: 9px;\n border-top: 1px dashed var(--line);\n}\n\n/* --- CTA secondaire : téléchargement de la fiche PDF --- */\n.cta-pdf {\n background: var(--surface); color: var(--ink);\n box-shadow: 4px 4px 0 rgba(26, 18, 20, 0.12);\n margin-top: 10px;\n}\n.cta-pdf:hover { background: var(--ink); color: var(--paper); }\n\n/* ================= Financement (fiche) + page Taux hypothécaires ========= */\n.f-mtg .mtg-intro { color: var(--ink-2); font-size: 14px; margin: 4px 0 14px; }\n.f-mtg .mtg-intro a { color: var(--lime); font-weight: 600; }\n\n.mtg-form {\n display: grid; gap: 10px;\n grid-template-columns: repeat(auto-fill, minmax(150px, 1fr));\n}\n.mtg-form label { display: flex; flex-direction: column; gap: 3px; min-width: 0; }\n.mtg-form label > span {\n font-family: var(--font-mono); font-size: 9.5px; font-weight: 700;\n text-transform: uppercase; letter-spacing: 0.1em; color: var(--ink-3);\n}\n.mtg-form input, .mtg-form select {\n border: 1.5px solid var(--ink); border-radius: 9px; background: var(--surface);\n padding: 9px 10px; font-size: 14.5px; font-family: inherit; color: var(--ink);\n min-height: 42px; min-width: 0;\n}\n.mtg-form input:focus, .mtg-form select:focus {\n outline: none; box-shadow: 3px 3px 0 var(--lime);\n}\n\n.mtg-err { color: var(--accent-deep); font-size: 13.5px; margin: 12px 0 0; }\n\n.mtg-resultat {\n display: grid; gap: 10px; margin-top: 16px;\n grid-template-columns: repeat(auto-fit, minmax(180px, 1fr));\n}\n.mtg-kpi {\n border: 1.5px solid var(--line-strong); border-radius: var(--r-card);\n background: var(--surface-2); padding: 12px 14px;\n display: flex; flex-direction: column; gap: 2px; min-width: 0;\n}\n.mtg-kpi-k {\n font-family: var(--font-mono); font-size: 9.5px; font-weight: 700;\n text-transform: uppercase; letter-spacing: 0.12em; color: var(--ink-3);\n}\n.mtg-kpi-v {\n font-family: var(--font-display); font-weight: 700; font-size: 22px;\n letter-spacing: -0.02em;\n}\n.mtg-kpi-sub { font-size: 12px; color: var(--ink-3); }\n.mtg-kpi:first-child { background: var(--ink); border-color: var(--ink); }\n.mtg-kpi:first-child .mtg-kpi-v { color: var(--lime); }\n.mtg-kpi:first-child .mtg-kpi-k, .mtg-kpi:first-child .mtg-kpi-sub { color: rgba(255,255,255,0.75); }\n\n.mtg-source { margin-top: 10px; }\n\n.mtg-schl {\n margin-top: 14px; border: 1.5px dashed var(--line-strong);\n border-radius: var(--r-card); padding: 12px 14px; font-size: 13.5px;\n background: var(--surface);\n}\n.mtg-schl ul { margin: 8px 0 0; padding-left: 18px; display: grid; gap: 3px; }\n.mtg-schl-no { border-color: var(--accent-deep); }\n.mtg-issue { margin: 8px 0 0; color: var(--accent-deep); font-size: 13px; }\n\n.mtg-detail {\n margin-top: 10px; border: 1.5px solid var(--line-strong);\n border-radius: var(--r-card); background: var(--surface);\n}\n.mtg-detail > summary {\n cursor: pointer; padding: 11px 14px; font-weight: 700; font-size: 14px;\n list-style: none; display: flex; align-items: center; gap: 8px;\n}\n.mtg-detail > summary::before { content: \"+\"; font-family: var(--font-mono); color: var(--lime); font-weight: 700; }\n.mtg-detail[open] > summary::before { content: \"−\"; }\n.mtg-detail > summary::-webkit-details-marker { display: none; }\n.mtg-detail > *:not(summary) { margin: 0 14px 12px; }\n.mtg-detail .fine { border-top: none; padding-top: 0; }\n.mtg-total { border-top: 2px solid var(--ink); }\n.mtg-comp td, .mtg-comp th { white-space: nowrap; }\n.mtg-stale { color: var(--accent-deep); }\n\n.mtg-chart svg { width: 100%; height: auto; display: block; }\n.mtg-grid { stroke: var(--line); stroke-width: 1; }\n.mtg-tick { font-family: var(--font-mono); font-size: 10px; fill: var(--ink-3); }\n.mtg-line { fill: none; stroke: var(--lime); stroke-width: 2.5; stroke-linejoin: round; }\n.mtg-dot { fill: var(--ink); stroke: var(--lime); stroke-width: 2.5; }\n\n/* ---- page /taux-hypothecaires ---- */\n.taux-page { padding-bottom: 40px; }\n.taux-head { margin: 28px 0 6px; max-width: 760px; }\n.taux-head h1 { font-family: var(--font-display); font-size: clamp(28px, 5vw, 40px); letter-spacing: -0.03em; }\n.taux-head p { color: var(--ink-2); font-size: 15px; margin: 12px 0 0; }\n.taux-page > .f-bloc { margin-top: 22px; }\n\n.taux-grid {\n display: grid; gap: 10px;\n grid-template-columns: repeat(auto-fill, minmax(170px, 1fr));\n}\n.taux-card {\n border: 1.5px solid var(--ink); border-radius: var(--r-card);\n background: var(--surface); padding: 12px 14px; text-align: left;\n cursor: pointer; display: flex; flex-direction: column; gap: 2px;\n transition: box-shadow 0.15s ease; font-family: inherit; min-width: 0;\n}\n.taux-card:hover { box-shadow: 3px 3px 0 var(--lime); }\n.taux-card.on { background: var(--ink); color: var(--paper); }\n.taux-card.on .taux-card-v { color: var(--lime); }\n.taux-card-k {\n font-family: var(--font-mono); font-size: 9.5px; font-weight: 700;\n text-transform: uppercase; letter-spacing: 0.12em; color: var(--ink-3);\n}\n.taux-card.on .taux-card-k, .taux-card.on .taux-card-sub { color: rgba(255,255,255,0.7); }\n.taux-card-v { font-family: var(--font-display); font-weight: 700; font-size: 24px; }\n.taux-card-sub { font-size: 11.5px; color: var(--ink-3); }\n\n.taux-filtres { display: flex; gap: 10px; margin-bottom: 14px; flex-wrap: wrap; }\n.taux-filtres label { display: flex; flex-direction: column; gap: 3px; }\n.taux-filtres label > span {\n font-family: var(--font-mono); font-size: 9.5px; font-weight: 700;\n text-transform: uppercase; letter-spacing: 0.1em; color: var(--ink-3);\n}\n.taux-filtres select {\n border: 1.5px solid var(--ink); border-radius: 9px; background: var(--surface);\n padding: 9px 12px; font-size: 14.5px; font-family: inherit; min-height: 42px;\n}\n.taux-best td { background: var(--lime-soft); }\n.taux-badge {\n font-family: var(--font-mono); font-size: 9px; font-weight: 700;\n text-transform: uppercase; letter-spacing: 0.1em; background: var(--ink);\n color: var(--lime); border-radius: 999px; padding: 2px 8px; margin-left: 8px;\n}\n.taux-sante { display: flex; flex-wrap: wrap; gap: 8px; }\n.taux-src {\n border: 1.5px solid var(--line-strong); border-radius: 999px;\n padding: 6px 12px; font-size: 12.5px; font-weight: 600;\n display: inline-flex; align-items: center; gap: 7px;\n}\n.taux-src::before { content: \"\"; width: 8px; height: 8px; border-radius: 50%; }\n.taux-src-ok::before { background: var(--green, #2f9e44); }\n.taux-src-warning::before { background: #e8a000; }\n.taux-src-error::before { background: var(--accent-deep); }\n","structuredPatch":[{"oldStart":294,"oldLines":6,"newStart":294,"newLines":16,"lines":[" .f-foot { margin-top: 26px; }"," .fine { font-size: 12px; color: var(--ink-3); }"," ","+/* Box « Aussi publiée sur… » : autres publications de la même propriété */","+.dups-note { font-size: 13px; color: var(--ink-3); margin: 4px 0 10px; }","+.dups-list { display: flex; flex-direction: column; gap: 8px; }","+.dup-item { display: flex; align-items: center; gap: 10px; flex-wrap: wrap; padding: 11px 13px; border: 1.5px solid var(--line-strong); border-radius: var(--r-ctl); 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Je lance le build Vite et le recalcul de la dédup en parallèle."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":690,"cache_read_input_tokens":71648,"cache_creation":{"ephemeral_5m_input_tokens":690,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"b0381458-53a4-4ca4-a04f-047395f3dea4"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcAKv71UgLvLpYLEczi","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_013cwhFK5ryPnYsnwwpRU1Ju","name":"TodoWrite","input":{"todos":[{"content":"db.py : priorité courtier + colonne dup_of persistée par les 3 passes de dédup","status":"completed","activeForm":"Modifiant la dédup (priorité courtier + dup_of)"},{"content":"web.py : exposer les doublons dans get_listing","status":"completed","activeForm":"Exposant les doublons dans l'API"},{"content":"Frontend : type + box « Aussi publiée sur… » dans Listing.tsx","status":"completed","activeForm":"Ajoutant la box doublons au frontend"},{"content":"refresh_dedup + build + PM2 restart + vérif Charles-Trudel","status":"in_progress","activeForm":"Recalculant la dédup et vérifiant"},{"content":"Commit + push origin main","status":"pending","activeForm":"Committant et poussant"}]},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":690,"cache_read_input_tokens":71648,"cache_creation":{"ephemeral_5m_input_tokens":690,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"264c23c5-57ca-4068-8240-4c5a6cbb118d"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013cwhFK5ryPnYsnwwpRU1Ju","type":"tool_result","content":"Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"157a5f0c-4fc7-4cc0-9917-c03ab48e33f7","timestamp":"2026-08-25T14:15:17.115Z","tool_use_result":{"oldTodos":[{"content":"db.py : priorité courtier + colonne dup_of persistée par les 3 passes de dédup","status":"completed","activeForm":"Modifiant la dédup (priorité courtier + dup_of)"},{"content":"web.py : exposer les doublons dans get_listing","status":"completed","activeForm":"Exposant les doublons dans l'API"},{"content":"Frontend : type + box « Aussi publiée sur… » dans Listing.tsx","status":"in_progress","activeForm":"Ajoutant la box doublons au frontend"},{"content":"refresh_dedup + build + PM2 restart + vérif Charles-Trudel","status":"pending","activeForm":"Recalculant la dédup et vérifiant"},{"content":"Commit + push origin main","status":"pending","activeForm":"Committant et poussant"}],"newTodos":[{"content":"db.py : priorité courtier + colonne dup_of persistée par les 3 passes de dédup","status":"completed","activeForm":"Modifiant la dédup (priorité courtier + dup_of)"},{"content":"web.py : exposer les doublons dans get_listing","status":"completed","activeForm":"Exposant les doublons dans l'API"},{"content":"Frontend : type + box « Aussi publiée sur… » dans Listing.tsx","status":"completed","activeForm":"Ajoutant la box doublons au frontend"},{"content":"refresh_dedup + build + PM2 restart + vérif Charles-Trudel","status":"in_progress","activeForm":"Recalculant la dédup et vérifiant"},{"content":"Commit + push origin main","status":"pending","activeForm":"Committant et poussant"}],"verificationNudgeNeeded":false}}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcAKv71UgLvLpYLEczi","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01NuGAUKWPsry9nt38XMYHsM","name":"Bash","input":{"command":"cd /Users/simon-pierreboucher/apps/immo-ka/frontend && npm run build 2>&1 | tail -6","description":"Build Vite frontend","timeout":240000},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":690,"cache_read_input_tokens":71648,"cache_creation":{"ephemeral_5m_input_tokens":690,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"362201e9-172d-4aaf-8389-6699378ebeeb"}} {"type":"claude","event":{"type":"system","subtype":"task_started","task_id":"b6ep2iza3","tool_use_id":"toolu_01NuGAUKWPsry9nt38XMYHsM","description":"Build Vite frontend","task_type":"local_bash","uuid":"4f198cac-8a2d-47e6-84f3-c715864591dc","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"system","subtype":"task_notification","task_id":"b6ep2iza3","tool_use_id":"toolu_01NuGAUKWPsry9nt38XMYHsM","status":"completed","output_file":"","summary":"Build Vite frontend","uuid":"ad7144f1-f50c-497b-892c-41c52d727ac8","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01NuGAUKWPsry9nt38XMYHsM","type":"tool_result","content":"(!) 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Consider:\n- Using dynamic import() to code-split the application\n- Use build.rollupOptions.output.manualChunks to improve chunking: https://rollupjs.org/configuration-options/#output-manualchunks\n- Adjust chunk size limit for this warning via build.chunkSizeWarningLimit.\n✓ built in 2.30s","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"22779dd7-0df5-4434-ba0c-463dded0aa14","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcBR8AYzdpowxQC7To2","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":974,"cache_read_input_tokens":72338,"cache_creation":{"ephemeral_5m_input_tokens":974,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"48b18889-158c-4f2f-9780-597d0a0658c0"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcBR8AYzdpowxQC7To2","type":"message","role":"assistant","content":[{"type":"text","text":"Build OK. Je recalcule la dédup (migration `dup_of` incluse)."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":974,"cache_read_input_tokens":72338,"cache_creation":{"ephemeral_5m_input_tokens":974,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"23222e80-3edf-41a0-bed8-514e7c12ad15"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcBR8AYzdpowxQC7To2","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Xm1CjhaquujuD2BzSHg7VH","name":"Bash","input":{"command":"cd /Users/simon-pierreboucher/apps/immo-ka && python3 -c \"\nfrom immoka import db\ncon = db.connect()\nn = db.refresh_dedup(con)\nprint('masquées:', n)\nrow = con.execute(\\\"SELECT uid, source, broker_name, agency FROM listings WHERE address LIKE '3 Ch. Charles-Trudel%' AND active=1 AND dup_hidden=0\\\").fetchall()\nfor r in row: print('visible:', dict(r))\ndups = con.execute(\\\"SELECT uid, source, dup_of FROM listings WHERE address LIKE '3 Ch. Charles-Trudel%' AND dup_hidden=1\\\").fetchall()\nfor r in dups: print('doublon:', dict(r))\ncon.close()\n\" 2>&1 | tail -15","description":"Run refresh_dedup and check Charles-Trudel case","timeout":300000},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":974,"cache_read_input_tokens":72338,"cache_creation":{"ephemeral_5m_input_tokens":974,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"938135f3-e015-41b7-879c-20751ac7681f"}} {"type":"claude","event":{"type":"system","subtype":"task_notification","task_id":"blusct3c7","tool_use_id":"toolu_01Xm1CjhaquujuD2BzSHg7VH","status":"completed","output_file":"","summary":"Run refresh_dedup and check Charles-Trudel case","uuid":"fda0d906-e1eb-4877-bf10-953466b95e37","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"system","subtype":"task_started","task_id":"blusct3c7","tool_use_id":"toolu_01Xm1CjhaquujuD2BzSHg7VH","description":"Run refresh_dedup and check Charles-Trudel case","task_type":"local_bash","uuid":"fbbc083c-2f25-43f2-9875-17fe3e9d46c4","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Xm1CjhaquujuD2BzSHg7VH","type":"tool_result","content":"[immo-ka] dédup adresse: 2197 doublon(s) inter-sources masqué(s)\nmasquées: 51988\nvisible: {'uid': 'via_capitale:23663023', 'source': 'via_capitale', 'broker_name': 'Via Capitale', 'agency': 'Via Capitale'}\ndoublon: {'uid': 'realtor_ag_ca:23663023', 'source': 'realtor_ag_ca', 'dup_of': 'via_capitale:23663023'}","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"4c7ab10c-39d6-4215-8ef8-d2ae39e91c92","timestamp":"2026-08-25T14:15:34.278Z","tool_use_result":{"stdout":"[immo-ka] dédup adresse: 2197 doublon(s) inter-sources masqué(s)\nmasquées: 51988\nvisible: {'uid': 'via_capitale:23663023', 'source': 'via_capitale', 'broker_name': 'Via Capitale', 'agency': 'Via Capitale'}\ndoublon: {'uid': 'realtor_ag_ca:23663023', 'source': 'realtor_ag_ca', 'dup_of': 'via_capitale:23663023'}","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"e2e16c4d-fc48-47e0-900c-35814053f5d9","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcCLNC8c17uJyr5hdQa","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":633,"cache_read_input_tokens":73312,"cache_creation":{"ephemeral_5m_input_tokens":633,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"8da0d8ea-98a8-489e-8136-bb3ec3a52323"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcCLNC8c17uJyr5hdQa","type":"message","role":"assistant","content":[{"type":"text","text":"La fiche Via Capitale (courtier) est maintenant la version visible. Je vérifie où est passée la fiche FB Marketplace."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":633,"cache_read_input_tokens":73312,"cache_creation":{"ephemeral_5m_input_tokens":633,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"1043e54d-ba82-4da1-b444-c6c5e78603c9"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcCLNC8c17uJyr5hdQa","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01MsJwzgusb3LMyxGvjb3Mrq","name":"Bash","input":{"command":"sqlite3 data/immoka.db \"SELECT uid, source, address, active, dup_hidden, dup_of FROM listings WHERE address LIKE '%Charles-Trudel%'\" && sqlite3 data/immoka.db \"SELECT COUNT(*) FROM listings WHERE dup_hidden=1 AND dup_of IS NOT NULL; SELECT COUNT(*) FROM listings WHERE dup_hidden=1 AND dup_of IS NULL\"","description":"Check FB Marketplace duplicate and dup_of coverage"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":633,"cache_read_input_tokens":73312,"cache_creation":{"ephemeral_5m_input_tokens":633,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ff4fa100-d76e-46a3-be08-52fe1f364276"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01MsJwzgusb3LMyxGvjb3Mrq","type":"tool_result","content":"realtor_ag_ca:23663023|realtor_ag_ca|3 Ch. Charles-Trudel|1|1|via_capitale:23663023\nvia_capitale:23663023|via_capitale|3 Ch. Charles-Trudel|1|0|\nfb_marketplace:1034708775856596|fb_marketplace|3 Chemin Charles-Trudel|1|1|via_capitale:23663023\n51988\n0","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"97224de2-24fd-49df-8148-22db5bb542e4","timestamp":"2026-08-25T14:15:43.884Z","tool_use_result":{"stdout":"realtor_ag_ca:23663023|realtor_ag_ca|3 Ch. Charles-Trudel|1|1|via_capitale:23663023\nvia_capitale:23663023|via_capitale|3 Ch. Charles-Trudel|1|0|\nfb_marketplace:1034708775856596|fb_marketplace|3 Chemin Charles-Trudel|1|1|via_capitale:23663023\n51988\n0","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"a6ca05b1-d5e5-4a7e-b99b-9ee048fc1b38","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcD3e9D3PgzhpBNsMQ1","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":553,"cache_read_input_tokens":73945,"cache_creation":{"ephemeral_5m_input_tokens":553,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"b48e24d9-b3e3-413c-87cb-128fa1d81e37"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcD3e9D3PgzhpBNsMQ1","type":"message","role":"assistant","content":[{"type":"text","text":"Parfait : les 51 988 doublons ont tous leur `dup_of`, et Charles-Trudel a maintenant la version courtier visible avec 2 doublons rattachés. Redémarrage PM2 + vérification API et site."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":553,"cache_read_input_tokens":73945,"cache_creation":{"ephemeral_5m_input_tokens":553,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"9729844a-4da0-480b-b2d6-32bc1e741cd3"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcD3e9D3PgzhpBNsMQ1","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01NmnQuj1Y53v7ajzMLxBdxC","name":"Bash","input":{"command":"pm2 restart immo-ka-web immo-ka-sync --update-env >/dev/null 2>&1; sleep 3; curl -s \"http://localhost:8096/api/listings/via_capitale:23663023\" | python3 -c \"\nimport json,sys\nd=json.load(sys.stdin)\nprint('broker:', d.get('broker_name'), '|', d.get('agency'))\nfor x in d.get('duplicates', []): print('dup:', x['source'], x['url'][:60], '| courtier:', x.get('broker_name') or '-')\n\"","description":"Restart PM2 and check duplicates in API","timeout":60000},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":553,"cache_read_input_tokens":73945,"cache_creation":{"ephemeral_5m_input_tokens":553,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"033fc821-8a8e-4428-936f-da07a555c304"}} {"type":"claude","event":{"type":"system","subtype":"task_notification","task_id":"bvnmyacvq","tool_use_id":"toolu_01NmnQuj1Y53v7ajzMLxBdxC","status":"completed","output_file":"","summary":"Restart PM2 and check duplicates in 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Laberge","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"2e88bc3e-2f71-4df5-b916-239473c450cf","timestamp":"2026-08-25T14:15:57.111Z","tool_use_result":{"stdout":"broker: Via Capitale | Via Capitale\ndup: fb_marketplace https://www.facebook.com/marketplace/item/1034708775856596/ | courtier: -\ndup: realtor_ag_ca https://www.realtor.ca/real-estate/30184584/3-ch-charles-tru | courtier: Simon Laberge","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"816d7888-2966-4526-a1a8-803267fe32b1","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcE2ePbEYL7H9Q7YCTx","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":577,"cache_read_input_tokens":74498,"cache_creation":{"ephemeral_5m_input_tokens":577,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"67226669-4de1-4eb8-b032-b6efefa34477"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcE2ePbEYL7H9Q7YCTx","type":"message","role":"assistant","content":[{"type":"text","text":"L'API expose bien les 2 doublons. Vérification du rendu de la box dans le navigateur (Playwright)."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":577,"cache_read_input_tokens":74498,"cache_creation":{"ephemeral_5m_input_tokens":577,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"0ba16db4-2cab-4dce-8555-d4e452e4db95"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcE2ePbEYL7H9Q7YCTx","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01XSjn4535KjoFZsmd8omxrf","name":"Bash","input":{"command":"cd /Users/simon-pierreboucher/apps/immo-ka/frontend && node -e \"\nconst { chromium } = require('playwright');\n(async () => {\n const b = await chromium.launch();\n const p = await b.newPage();\n await p.goto('http://localhost:8096/propriete/via_capitale%3A23663023/x', { waitUntil: 'networkidle' });\n const box = await p.locator('#publications').count();\n if (box) {\n console.log('BOX OK —', await p.locator('#publications h2').innerText());\n console.log(await p.locator('#publications .dup-item').allInnerTexts());\n } else console.log('BOX ABSENTE');\n await b.close();\n})();\n\" 2>&1 | tail -5","description":"Verify duplicates box renders in browser","timeout":90000},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":577,"cache_read_input_tokens":74498,"cache_creation":{"ephemeral_5m_input_tokens":577,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"1eba7a3b-021c-4180-944e-b2793901aa3a"}} {"type":"claude","event":{"type":"system","subtype":"task_started","task_id":"b9nu2iqom","tool_use_id":"toolu_01XSjn4535KjoFZsmd8omxrf","description":"Verify duplicates box renders in browser","task_type":"local_bash","uuid":"8734a230-e9bb-4ee9-ac7a-d22b20e2cf85","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"system","subtype":"task_notification","task_id":"b9nu2iqom","tool_use_id":"toolu_01XSjn4535KjoFZsmd8omxrf","status":"completed","output_file":"","summary":"Verify duplicates box renders in browser","uuid":"2c89d998-43f3-4079-bd33-f189e3708d25","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01XSjn4535KjoFZsmd8omxrf","type":"tool_result","content":"BOX OK — Aussi publiée sur\n[\n \"Fb Marketplace\\nVoir l'annonce\",\n \"Realtor Ag Ca\\nSimon Laberge\\nVoir l'annonce\"\n]","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"ded9b5d3-aea1-4adb-bfc3-62b2845616da","timestamp":"2026-08-25T14:16:34.733Z","tool_use_result":{"stdout":"BOX OK — Aussi publiée sur\n[\n \"Fb Marketplace\\nVoir l'annonce\",\n \"Realtor Ag Ca\\nSimon Laberge\\nVoir l'annonce\"\n]","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"3eec10fb-6c62-40b4-a3d1-2634276dccc0","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcGoWSqMJ6KbSXPEFP7","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":602,"cache_read_input_tokens":75075,"cache_creation":{"ephemeral_5m_input_tokens":602,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"0403a029-f438-4d07-aa34-d28409bb27c0"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcGoWSqMJ6KbSXPEFP7","type":"message","role":"assistant","content":[{"type":"text","text":"La box s'affiche, mais les noms de sources tombent sur le repli (« Fb Marketplace », « Realtor Ag Ca ») — je regarde comment `sourceName` est alimenté sur la fiche."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":602,"cache_read_input_tokens":75075,"cache_creation":{"ephemeral_5m_input_tokens":602,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"2c18a311-4551-4e2f-8030-832e3f54e0e6"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcGoWSqMJ6KbSXPEFP7","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01RAjS1yTLFTvsL5U9KHNaeX","name":"Grep","input":{"pattern":"registerSourceNames|sourceName|SOURCE_NAMES","path":"/Users/simon-pierreboucher/apps/immo-ka/frontend/src","output_mode":"content","-n":true},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":602,"cache_read_input_tokens":75075,"cache_creation":{"ephemeral_5m_input_tokens":602,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"3bb77fc8-44dc-40aa-b9c4-758df44b055a"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01RAjS1yTLFTvsL5U9KHNaeX","type":"tool_result","content":"src/pages/Listing.tsx:12: registerSourceNames, sourceName,\nsrc/pages/Listing.tsx:205: fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});\nsrc/pages/Listing.tsx:389: Voir l'annonce chez {sourceName(l.source)} \nsrc/pages/Listing.tsx:395: Agrégé par Immo-Ka — {sourceName(l.source)}{updated ? ` · synchronisé le ${updated}` : \"\"}.\nsrc/pages/Listing.tsx:410: {sourceName(d.source)}\nsrc/pages/Listing.tsx:523: Voir chez {sourceName(l.source)} ↗\nsrc/pages/Home.tsx:11: registerSourceNames, sourceName,\nsrc/pages/Home.tsx:99: fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});\nsrc/pages/Home.tsx:163: if (source) pills.push({ label: sourceName(source), clear: () => setSource(\"\") });\nsrc/pages/Home.tsx:290: \nsrc/pages/Category.tsx:11: Listing, fetchListings, fetchSources, fmtPrice, registerSourceNames,\nsrc/pages/Category.tsx:30: fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});\nsrc/App.tsx:10:import { fetchFacets, fetchSources, fetchStats, registerSourceNames, sourceName } from \"./api\";\nsrc/App.tsx:32: registerSourceNames(src.sources);\nsrc/App.tsx:38: parts.push(`${sourceName(s.source)} · ${s.n}`);\nsrc/components/ListingCard.tsx:7:import { Listing, fmtArea, fmtPrice, sourceName } from \"../api\";\nsrc/components/ListingCard.tsx:51: {sourceName(l.source)}\nsrc/components/MapView.tsx:31:import { ListingFilters, sourceName } from \"../api\";\nsrc/components/MapView.tsx:70:
{sourceName(extra.source ?? \"\")}
\nsrc/api.ts:135:const SOURCE_NAMES: Record = {};\nsrc/api.ts:136:export function registerSourceNames(sources: Source[]) {\nsrc/api.ts:137: for (const s of sources) SOURCE_NAMES[s.id] = s.name;\nsrc/api.ts:139:export function sourceName(id: string): string {\nsrc/api.ts:140: if (SOURCE_NAMES[id]) return SOURCE_NAMES[id];"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"144ee484-348e-46e5-8389-8970ee6520af","timestamp":"2026-08-25T14:16:43.636Z","tool_use_result":{"mode":"content","numFiles":0,"filenames":[],"content":"src/pages/Listing.tsx:12: registerSourceNames, sourceName,\nsrc/pages/Listing.tsx:205: fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});\nsrc/pages/Listing.tsx:389: Voir l'annonce chez {sourceName(l.source)} \nsrc/pages/Listing.tsx:395: Agrégé par Immo-Ka — {sourceName(l.source)}{updated ? ` · synchronisé le ${updated}` : \"\"}.\nsrc/pages/Listing.tsx:410: {sourceName(d.source)}\nsrc/pages/Listing.tsx:523: Voir chez {sourceName(l.source)} ↗\nsrc/pages/Home.tsx:11: registerSourceNames, sourceName,\nsrc/pages/Home.tsx:99: fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});\nsrc/pages/Home.tsx:163: if (source) pills.push({ label: sourceName(source), clear: () => setSource(\"\") });\nsrc/pages/Home.tsx:290: \nsrc/pages/Category.tsx:11: Listing, fetchListings, fetchSources, fmtPrice, registerSourceNames,\nsrc/pages/Category.tsx:30: fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});\nsrc/App.tsx:10:import { fetchFacets, fetchSources, fetchStats, registerSourceNames, sourceName } from \"./api\";\nsrc/App.tsx:32: registerSourceNames(src.sources);\nsrc/App.tsx:38: parts.push(`${sourceName(s.source)} · ${s.n}`);\nsrc/components/ListingCard.tsx:7:import { Listing, fmtArea, fmtPrice, sourceName } from \"../api\";\nsrc/components/ListingCard.tsx:51: {sourceName(l.source)}\nsrc/components/MapView.tsx:31:import { ListingFilters, sourceName } from \"../api\";\nsrc/components/MapView.tsx:70:
{sourceName(extra.source ?? \"\")}
\nsrc/api.ts:135:const SOURCE_NAMES: Record = {};\nsrc/api.ts:136:export function registerSourceNames(sources: Source[]) {\nsrc/api.ts:137: for (const s of sources) SOURCE_NAMES[s.id] = s.name;\nsrc/api.ts:139:export function sourceName(id: string): string {\nsrc/api.ts:140: if (SOURCE_NAMES[id]) return SOURCE_NAMES[id];","numLines":24}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"d07b559b-3e20-4744-968d-20a24dbc43df","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcHTQzb7LNLzxiDqm8E","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1708,"cache_read_input_tokens":75677,"cache_creation":{"ephemeral_5m_input_tokens":1708,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"3065fd64-f374-4b12-a020-c919a94eb5ed"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcHTQzb7LNLzxiDqm8E","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_0172uNN55LMUeRMRyA2Uy3JF","name":"Bash","input":{"command":"curl -s http://localhost:8096/api/sources | python3 -c \"\nimport json,sys\nd=json.load(sys.stdin)['sources']\nfor s in d:\n if s['id'] in ('fb_marketplace','realtor_ag_ca','via_capitale'): print(s['id'],'→',s['name'])\nprint('total:',len(d))\"","description":"Check source names in /api/sources"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1708,"cache_read_input_tokens":75677,"cache_creation":{"ephemeral_5m_input_tokens":1708,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"78baa74b-1a1b-4464-ac4e-38dd76ed2403"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0172uNN55LMUeRMRyA2Uy3JF","type":"tool_result","content":"via_capitale → Via Capitale\nfb_marketplace → Facebook Marketplace\nrealtor_ag_ca → Realtor.ca (MLS Québec)\ntotal: 80","is_error":false}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"27eae80a-e077-44d3-a94d-2083f812beb7","timestamp":"2026-08-25T14:16:56.262Z","tool_use_result":{"stdout":"via_capitale → Via Capitale\nfb_marketplace → Facebook Marketplace\nrealtor_ag_ca → Realtor.ca (MLS Québec)\ntotal: 80","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"61dacb45-9ff6-4c18-b20d-b532013f3ec6","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcJPBXLciWyEtSAQexa","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":512,"cache_read_input_tokens":77385,"cache_creation":{"ephemeral_5m_input_tokens":512,"ephemeral_1h_input_tokens":0},"output_tokens":6,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"1f39e606-994d-4d6c-b081-e6e25de08529"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcJPBXLciWyEtSAQexa","type":"message","role":"assistant","content":[{"type":"text","text":"Les noms existent dans l'API — c'est une course : `registerSourceNames` ne déclenche pas de re-render. Je corrige avec un tick d'état."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":512,"cache_read_input_tokens":77385,"cache_creation":{"ephemeral_5m_input_tokens":512,"ephemeral_1h_input_tokens":0},"output_tokens":6,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"65fd8827-aec8-46d1-ba56-3eef18d456c1"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcJPBXLciWyEtSAQexa","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Hbz7Mieeu8HAMqgL5pVpkg","name":"Read","input":{"file_path":"/Users/simon-pierreboucher/apps/immo-ka/frontend/src/pages/Listing.tsx","offset":190,"limit":30},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":512,"cache_read_input_tokens":77385,"cache_creation":{"ephemeral_5m_input_tokens":512,"ephemeral_1h_input_tokens":0},"output_tokens":6,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"37322a35-a3f0-4ae1-a61e-e933faacf569"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Hbz7Mieeu8HAMqgL5pVpkg","type":"tool_result","content":"190\t]);\n191\t\n192\t// icône de chaque tuile « spec » (Icons.tsx)\n193\tconst SPEC_ICONS: Record = {\n194\t \"Type\": \"home\", \"Chambres\": \"bed\", \"Salles de bain\": \"bath\",\n195\t \"Salles d'eau\": \"drop\", \"Superficie\": \"area\", \"Terrain\": \"land\",\n196\t \"Année\": \"calendar\", \"MLS / Centris\": \"tag\",\n197\t};\n198\t\n199\texport default function ListingPage() {\n200\t const { uid } = useParams<{ uid: string }>();\n201\t const [l, setL] = useState(null);\n202\t const [error, setError] = useState(null);\n203\t\n204\t useEffect(() => {\n205\t fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});\n206\t if (!uid) return;\n207\t setL(null); setError(null);\n208\t fetchListing(uid).then(setL).catch((e) => setError(String(e)));\n209\t window.scrollTo(0, 0);\n210\t }, [uid]);\n211\t\n212\t if (error)\n213\t return (\n214\t
\n215\t
\n216\t

Propriété introuvable

\n217\t

{error}

\n218\t Retour aux propriétés\n219\t
"}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"d781ce00-8190-49a8-aab3-dcb114610759","timestamp":"2026-08-25T14:17:05.259Z","tool_use_result":{"type":"text","file":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/frontend/src/pages/Listing.tsx","content":"]);\n\n// icône de chaque tuile « spec » (Icons.tsx)\nconst SPEC_ICONS: Record = {\n \"Type\": \"home\", \"Chambres\": \"bed\", \"Salles de bain\": \"bath\",\n \"Salles d'eau\": \"drop\", \"Superficie\": \"area\", \"Terrain\": \"land\",\n \"Année\": \"calendar\", \"MLS / Centris\": \"tag\",\n};\n\nexport default function ListingPage() {\n const { uid } = useParams<{ uid: string }>();\n const [l, setL] = useState(null);\n const [error, setError] = useState(null);\n\n useEffect(() => {\n fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});\n if (!uid) return;\n setL(null); setError(null);\n fetchListing(uid).then(setL).catch((e) => setError(String(e)));\n window.scrollTo(0, 0);\n }, [uid]);\n\n if (error)\n return (\n
\n
\n

Propriété introuvable

\n

{error}

\n Retour aux propriétés\n
","numLines":30,"startLine":190,"totalLines":529}}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"4866f961-6710-4102-8231-76fc9fbfe852","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcK3ZbfqFT1xS21yZVP","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01KpieqBLjpwqPMJTMnCQRD1","name":"Edit","input":{"replace_all":false,"file_path":"/Users/simon-pierreboucher/apps/immo-ka/frontend/src/pages/Listing.tsx","old_string":" const [l, setL] = useState(null);\n const [error, setError] = useState(null);\n\n useEffect(() => {\n fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});\n if (!uid) return;","new_string":" const [l, setL] = useState(null);\n const [error, setError] = useState(null);\n // re-render quand les noms de sources arrivent (sinon repli Title Case)\n const [, setSrcTick] = useState(0);\n\n useEffect(() => {\n fetchSources().then((r) => { registerSourceNames(r.sources); setSrcTick(1); }).catch(() => {});\n if (!uid) return;"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":806,"cache_read_input_tokens":77897,"cache_creation":{"ephemeral_5m_input_tokens":806,"ephemeral_1h_input_tokens":0},"output_tokens":15,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"6391a8c8-3ce7-441e-b653-00e2215b3a87"}} {"type":"claude","event":{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01KpieqBLjpwqPMJTMnCQRD1","type":"tool_result","content":"The file /Users/simon-pierreboucher/apps/immo-ka/frontend/src/pages/Listing.tsx has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"b5333ad5-530f-4f0e-8c1e-349be08accf6","timestamp":"2026-08-25T14:17:13.624Z","tool_use_result":{"filePath":"/Users/simon-pierreboucher/apps/immo-ka/frontend/src/pages/Listing.tsx","oldString":" const [l, setL] = useState(null);\n const [error, setError] = useState(null);\n\n useEffect(() => {\n fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});\n if (!uid) return;","newString":" const [l, setL] = useState(null);\n const [error, setError] = useState(null);\n // re-render quand les noms de sources arrivent (sinon repli Title Case)\n const [, setSrcTick] = useState(0);\n\n useEffect(() => {\n fetchSources().then((r) => { registerSourceNames(r.sources); setSrcTick(1); }).catch(() => {});\n if (!uid) return;","originalFile":"// -----------------------------------------------------------------------------\n// Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)\n// Auteur : Simon-Pierre Boucher — contact@spboucher.ai\n// pages/Listing.tsx : fiche complète d'une propriété\n// galerie + lightbox · specs · caractéristiques (details) · pièces ·\n// inclusions · description · historique de prix · courtier · mini-carte\n// -----------------------------------------------------------------------------\nimport { Suspense, lazy, useEffect, useRef, useState } from \"react\";\nimport { Link, useParams } from \"react-router-dom\";\nimport {\n Listing, Room, fetchListing, fetchSources, fmtArea, fmtDate, fmtPrice,\n registerSourceNames, sourceName,\n} from \"../api\";\n\nconst PropertyMap = lazy(() => import(\"../components/PropertyMap\"));\nimport Financement from \"../components/Financement\";\nimport QuartierBlock from \"../components/QuartierBlock\";\nimport RisqueInondation from \"../components/RisqueInondation\";\nimport QualiteAir from \"../components/QualiteAir\";\nimport EssenceProche from \"../components/EssenceProche\";\nimport HydroEstimation from \"../components/HydroEstimation\";\nimport CommercesProches from \"../components/CommercesProches\";\nimport { Ico } from \"../components/Icons\";\nimport { TypeFallback } from \"../components/PropertyImg\";\n\n// --- Lightbox : pincement pour zoomer + panoramique + balayage entre photos ---\nfunction ZoomImg({ src, onSwipe }: { src: string; onSwipe: (dir: 1 | -1) => void }) {\n const [t, setT] = useState({ scale: 1, x: 0, y: 0 });\n const pointers = useRef(new Map());\n const start = useRef({ scale: 1, x: 0, y: 0, dist: 0, cx: 0, cy: 0, t: 0 });\n const lastTap = useRef(0);\n\n // repartir à zéro quand on change de photo\n useEffect(() => { setT({ scale: 1, x: 0, y: 0 }); }, [src]);\n\n const dist = () => {\n const p = [...pointers.current.values()];\n return p.length < 2 ? 0 : Math.hypot(p[0].x - p[1].x, p[0].y - p[1].y);\n };\n const center = () => {\n const p = [...pointers.current.values()];\n return p.length < 2\n ? p[0] ?? { x: 0, y: 0 }\n : { x: (p[0].x + p[1].x) / 2, y: (p[0].y + p[1].y) / 2 };\n };\n\n const onDown = (e: React.PointerEvent) => {\n (e.target as HTMLElement).setPointerCapture(e.pointerId);\n pointers.current.set(e.pointerId, { x: e.clientX, y: e.clientY });\n const c = center();\n start.current = { scale: t.scale, x: t.x, y: t.y, dist: dist(), cx: c.x, cy: c.y, t: Date.now() };\n };\n const onMove = (e: React.PointerEvent) => {\n if (!pointers.current.has(e.pointerId)) return;\n pointers.current.set(e.pointerId, { x: e.clientX, y: e.clientY });\n const s = start.current;\n if (pointers.current.size >= 2 && s.dist > 0) {\n // pincement : zoom autour du centre des deux doigts\n const scale = Math.min(4, Math.max(1, (dist() / s.dist) * s.scale));\n const c = center();\n setT({ scale, x: s.x + (c.x - s.cx), y: s.y + (c.y - s.cy) });\n } else if (pointers.current.size === 1 && t.scale > 1) {\n // panoramique une fois zoomé\n const p = pointers.current.get(e.pointerId)!;\n setT({ scale: t.scale, x: s.x + (p.x - s.cx), y: s.y + (p.y - s.cy) });\n }\n };\n const onUp = (e: React.PointerEvent) => {\n const p = pointers.current.get(e.pointerId);\n pointers.current.delete(e.pointerId);\n const s = start.current;\n if (pointers.current.size === 0 && p) {\n const dx = p.x - s.cx, dy = p.y - s.cy, dt = Date.now() - s.t;\n if (t.scale <= 1.05 && Math.abs(dx) > 56 && Math.abs(dx) > Math.abs(dy) * 1.5) {\n onSwipe(dx < 0 ? 1 : -1); // balayage → photo suivante\n } else if (dt < 260 && Math.abs(dx) < 8 && Math.abs(dy) < 8) {\n const now = Date.now();\n if (now - lastTap.current < 320) // double-tap : zoom ×2.4\n setT(t.scale > 1 ? { scale: 1, x: 0, y: 0 } : { scale: 2.4, x: 0, y: 0 });\n lastTap.current = now;\n }\n if (t.scale <= 1.02) setT({ scale: 1, x: 0, y: 0 });\n }\n };\n\n return (\n 1 ? \"grab\" : \"zoom-out\",\n }}\n onClick={(e) => e.stopPropagation()}\n onPointerDown={onDown} onPointerMove={onMove}\n onPointerUp={onUp} onPointerCancel={onUp}\n />\n );\n}\n\n// --- Galerie : balayage natif (scroll-snap) + vignettes + plein écran --------\nfunction Galerie({ images, captions, titre, type }:\n { images: string[]; captions?: string[]; titre: string; type?: string }) {\n const [idx, setIdx] = useState(0);\n const [zoom, setZoom] = useState(false);\n const [dead, setDead] = useState>(new Set());\n const track = useRef(null);\n\n // images qui ne chargent pas : retirées de la galerie à la volée (jamais\n // d'icône d'image cassée) ; légendes gardées alignées\n const alive = images\n .map((u, i) => ({ u, cap: captions && captions.length === images.length ? captions[i] : \"\" }))\n .filter(({ u }) => !dead.has(u));\n const markDead = (u: string) => setDead((d) => new Set(d).add(u));\n\n const onScroll = () => {\n const el = track.current;\n if (el) setIdx(Math.round(el.scrollLeft / el.clientWidth));\n };\n const goto = (i: number) =>\n track.current?.scrollTo({ left: i * track.current.clientWidth, behavior: \"smooth\" });\n\n useEffect(() => {\n if (!zoom) return;\n const onKey = (e: KeyboardEvent) => {\n if (e.key === \"Escape\") setZoom(false);\n if (e.key === \"ArrowLeft\") setIdx((i) => Math.max(0, i - 1));\n if (e.key === \"ArrowRight\") setIdx((i) => Math.min(alive.length - 1, i + 1));\n };\n window.addEventListener(\"keydown\", onKey);\n // figer l'arrière-plan pendant le plein écran (mobile)\n document.body.style.overflow = \"hidden\";\n return () => {\n window.removeEventListener(\"keydown\", onKey);\n document.body.style.overflow = \"\";\n };\n }, [zoom, alive.length]);\n\n if (alive.length === 0)\n return
;\n\n const cur = Math.min(idx, alive.length - 1);\n const swipe = (dir: 1 | -1) =>\n setIdx((i) => Math.min(alive.length - 1, Math.max(0, i + dir)));\n\n return (\n <>\n
\n
\n {alive.map(({ u }, i) => (\n {`${titre} markDead(u)} onClick={() => setZoom(true)} />\n ))}\n
\n {alive[cur]?.cap && {alive[cur].cap}}\n {cur + 1}/{alive.length}\n {cur > 0 && }\n {cur < alive.length - 1 && }\n
\n {alive.length > 1 && (\n
\n {alive.map(({ u }, i) => (\n \n ))}\n
\n )}\n {zoom && (\n
setZoom(false)} role=\"dialog\" aria-label=\"Photo agrandie\">\n \n {cur > 0 && }\n \n {cur < alive.length - 1 && }\n \n {alive[cur]?.cap ? `${alive[cur].cap} · ` : \"\"}{cur + 1} / {alive.length}\n \n
\n )}\n \n );\n}\n\n// clés techniques de `details` jamais montrées dans « Caractéristiques »\nconst DETAIL_HIDDEN = new Set([\n \"pieces\", \"price_from\", \"cover_thumb\", \"photo_captions\", \"img_audited\",\n \"needs_image_review\", \"postal_code\", \"region\", \"transaction\",\n \"prix_pi2\", \"prix_m2\", \"listing_origin_url\",\n]);\n\n// icône de chaque tuile « spec » (Icons.tsx)\nconst SPEC_ICONS: Record = {\n \"Type\": \"home\", \"Chambres\": \"bed\", \"Salles de bain\": \"bath\",\n \"Salles d'eau\": \"drop\", \"Superficie\": \"area\", \"Terrain\": \"land\",\n \"Année\": \"calendar\", \"MLS / Centris\": \"tag\",\n};\n\nexport default function ListingPage() {\n const { uid } = useParams<{ uid: string }>();\n const [l, setL] = useState(null);\n const [error, setError] = useState(null);\n\n useEffect(() => {\n fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});\n if (!uid) return;\n setL(null); setError(null);\n fetchListing(uid).then(setL).catch((e) => setError(String(e)));\n window.scrollTo(0, 0);\n }, [uid]);\n\n if (error)\n return (\n
\n
\n

Propriété introuvable

\n

{error}

\n Retour aux propriétés\n
\n );\n\n if (!l)\n return (\n
\n
\n
\n
\n
\n
\n );\n\n const specs: { k: string; v: string }[] = [];\n if (l.property_type) specs.push({ k: \"Type\", v: l.property_type });\n if (l.bedrooms != null) specs.push({ k: \"Chambres\", v: String(l.bedrooms) });\n if (l.bathrooms != null) specs.push({ k: \"Salles de bain\", v: String(l.bathrooms) });\n if (l.powder_rooms != null) specs.push({ k: \"Salles d'eau\", v: String(l.powder_rooms) });\n if (l.area_sqft != null) specs.push({ k: \"Superficie\", v: fmtArea(l.area_sqft)! });\n if (l.lot_sqft != null) specs.push({ k: \"Terrain\", v: fmtArea(l.lot_sqft)! });\n if (l.year_built != null) specs.push({ k: \"Année\", v: String(l.year_built) });\n if (l.mls) specs.push({ k: \"MLS / Centris\", v: l.mls });\n\n const rooms: Room[] = Array.isArray(l.details?.pieces) ? (l.details!.pieces as Room[]) : [];\n const detEntries = Object.entries(l.details ?? {})\n .filter(([k, v]) => !DETAIL_HIDDEN.has(k) && (typeof v === \"string\" || typeof v === \"number\") && String(v).trim());\n\n // taxes annuelles publiées (Centris) → mensualisées pour le coût réel\n const taxesAnnuelles = [\"Taxes municipales\", \"Taxes scolaires\"]\n .map((k) => {\n const v = l.details?.[k];\n const n = parseInt(String(v ?? \"\").replace(/[^\\d]/g, \"\"), 10);\n return Number.isFinite(n) && n > 0 && n < 200_000 ? n : 0;\n })\n .reduce((a, b) => a + b, 0);\n const estVente = l.details?.transaction !== \"location\";\n\n const hist = (l.price_history ?? []).filter((h) => h.price != null);\n const baisse = hist.length >= 2 && hist[0].price !== hist[1].price\n ? { de: hist[1].price!, a: hist[0].price! } : null;\n const updated = l.updated_at ? fmtDate(l.updated_at) : null;\n\n return (\n
\n \n\n
\n {/* -------- colonne gauche : galerie, prix/synthèse, description, ------\n -------- caractéristiques, pièces — ordre du DOM = ordre visuel ---- */}\n
\n
\n \n
\n\n
\n
\n {l.details?.transaction === \"location\" ? \"Loyer mensuel\" : \"Prix demandé\"}\n
\n
\n
\n {fmtPrice(l.price, l.price_label)}\n {l.details?.transaction === \"location\" && /mois}\n
\n {l.property_type && (\n \n {l.property_type}\n {l.details?.transaction === \"location\" ? \" · location\" : \"\"}\n {l.details?.price_from ? \" · à partir de\" : \"\"}\n \n )}\n
\n {l.price != null && l.area_sqft != null && l.area_sqft > 200 && (\n
{Math.round(l.price / l.area_sqft).toLocaleString(\"fr-CA\")} $ / pi² habitable
\n )}\n

{l.address || l.title}

\n
{[l.sector, l.city, l.region].filter(Boolean).join(\" · \")}
\n\n
\n {specs.map((s) => (\n
\n \n {s.k}\n {s.v}\n
\n ))}\n
\n\n {baisse && (\n
\n Prix passé de {fmtPrice(baisse.de)} à {fmtPrice(baisse.a)}\n
\n )}\n\n {l.vraiprix && l.vraiprix.value != null && (\n
\n
\n Vrai‑Prix\n {l.vraiprix.confidence && (\n \n confiance {l.vraiprix.confidence}\n \n )}\n
\n
Valeur marchande estimée
\n
{fmtPrice(l.vraiprix.value)}
\n {l.vraiprix.low != null && l.vraiprix.high != null && (() => {\n const lo = l.vraiprix!.low as number, hi = l.vraiprix!.high as number;\n const span = Math.max(1, hi - lo);\n const pos = (v: number) => `${Math.max(2, Math.min(98, ((v - lo) / span) * 100))}%`;\n return (\n
\n
\n \n \n {l.price != null && l.price >= lo * 0.7 && l.price <= hi * 1.3 && (\n \n )}\n
\n
\n {fmtPrice(lo)}\n {fmtPrice(hi)}\n
\n {l.price != null && l.price >= lo * 0.7 && l.price <= hi * 1.3 && (\n
\n estimation\n prix demandé\n
\n )}\n
\n );\n })()}\n {l.price != null && (\n (() => {\n const diff = l.price - (l.vraiprix!.value as number);\n const pct = Math.round((diff / (l.vraiprix!.value as number)) * 100);\n const cls = diff > 0 ? \"over\" : \"under\";\n const txt = diff > 0\n ? `Prix demandé ${pct}% au-dessus de l'estimation`\n : `Prix demandé ${Math.abs(pct)}% sous l'estimation`;\n if (Math.abs(pct) > 60) return null; // prix non comparable (loyer, terrain…)\n return Math.abs(pct) >= 1\n ?
{diff > 0 ? \"▲\" : \"▼\"} {txt}
\n :
≈ Prix aligné sur l'estimation
;\n })()\n )}\n \n Voir l'analyse détaillée ↗\n \n
\n )}\n\n {(l.broker_name || l.broker_phone) && (\n
\n
Courtier
\n {l.broker_name &&
{l.broker_name}
}\n {l.broker_phone && {l.broker_phone}}\n
\n )}\n\n \n Voir l'annonce chez {sourceName(l.source)} \n \n \n Télécharger la fiche (PDF) \n \n
\n Agrégé par Immo-Ka — {sourceName(l.source)}{updated ? ` · synchronisé le ${updated}` : \"\"}.\n
\n
\n\n {l.duplicates && l.duplicates.length > 0 && (\n
\n

Aussi publiée sur

\n

\n Cette propriété a été repérée sur {l.duplicates.length}{\" \"}\n autre{l.duplicates.length > 1 ? \"s\" : \"\"} plateforme{l.duplicates.length > 1 ? \"s\" : \"\"} —\n Immo-Ka affiche la version la plus complète.\n

\n \n
\n )}\n\n\n {l.description && (\n
\n

Description

\n

{l.description}

\n
\n )}\n\n {detEntries.length > 0 && (\n
\n

Caractéristiques

\n
\n {detEntries.map(([k, v]) => (\n
\n {k}\n {/^https?:\\/\\//.test(String(v))\n ? Ouvrir ↗\n : {String(v)}}\n
\n ))}\n
\n
\n )}\n\n {rooms.length > 0 && (\n
\n

Pièces

\n
\n \n \n \n {rooms.map((r, i) => (\n \n \n \n \n ))}\n \n
PièceNiveauDimensionsRevêtement
{r.nom || \"—\"}{r.niveau || \"—\"}{r.dimensions || \"—\"}{r.revetement || \"—\"}
\n
\n
\n )}\n\n
\n\n {/* -------- colonne droite (desktop) : inclusions, carte ------------- */}\n
\n {l.features && l.features.length > 0 && (\n
\n

Inclusions

\n
\n {l.features.map((f, i) => {f})}\n
\n
\n )}\n\n {l.lat != null && l.lng != null && (\n
\n

Emplacement

\n Chargement de la carte…
}>\n \n \n
\n )}\n
\n
\n\n {/* financement : taux hypothécaires réels + calculateur canadien */}\n {estVente && (\n 0 ? Math.round(taxesAnnuelles / 12) : null}\n />\n )}\n\n {/* quartier : pleine largeur, APRÈS les infos de propriété (ordre mobile correct) */}\n \n\n \n\n \n\n \n\n \n\n {l.quartier && }\n\n
\n Les prix et disponibilités sont ceux affichés par la source — chaque fiche renvoie à\n l'annonce originale de l'agence.\n
\n\n
\n {fmtPrice(l.price, l.price_label)}\n \n Voir chez {sourceName(l.source)} ↗\n \n
\n \n );\n}\n","structuredPatch":[{"oldStart":200,"oldLines":9,"newStart":200,"newLines":11,"lines":[" const { uid } = useParams<{ uid: string }>();"," const [l, setL] = useState(null);"," const [error, setError] = useState(null);","+ // re-render quand les noms de sources arrivent (sinon repli Title Case)","+ const [, setSrcTick] = useState(0);"," "," useEffect(() => {","- fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});","+ fetchSources().then((r) => { registerSourceNames(r.sources); setSrcTick(1); }).catch(() => {});"," if (!uid) return;"," setL(null); setError(null);"," fetchListing(uid).then(setL).catch((e) => setError(String(e)));"]}],"userModified":false,"replaceAll":false}}} {"type":"claude","event":{"type":"system","subtype":"status","status":"requesting","uuid":"4492fec2-b85b-47d8-b291-e849584804ef","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91"}} {"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcKfBj5671DcoCqbvVi","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01PSXYDZ2qdpqJjfQeFo93uu","name":"Bash","input":{"command":"npm run build 2>&1 | tail -2 && node -e \"\nconst { chromium } = require('playwright');\n(async () => {\n const b = await chromium.launch();\n const p = await b.newPage();\n await p.goto('http://localhost:8096/propriete/via_capitale%3A23663023/x', { waitUntil: 'networkidle' });\n console.log((await p.locator('#publications .dup-item').allInnerTexts()).map(t => t.replace(/\\n/g,' | ')));\n await b.close();\n})();\n\" 2>&1 | tail -3","description":"Rebuild and re-verify duplicates box source 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{"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcakpEGtHAKT6B8L3pZ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01SNkRHYC3SgwvFUNX6XA7fP","name":"Bash","input":{"command":"curl -s \"http://localhost:8096/api/listings/remax_quebec:15192567\" | python3 -c \"\nimport json,sys\nd=json.load(sys.stdin)\nprint(d['address'], '|', d['city'], '|', d['price_label'], '|', d['broker_name'], '/', d['agency'])\nfor x in d.get('duplicates', []): print(' dup:', x['source'], '→', x['url'])\"","description":"Check duplicates of the RE/MAX example 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{"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcbZ45DmuNejnUzZUF8","type":"message","role":"assistant","content":[{"type":"text","text":"Bel exemple concret :\n\n**https://www.immo-ka.com/propriete/remax_quebec%3A15192567/3289-rue-bossuet-montreal**\n\n- **3289 Rue Bossuet, Montréal** — 339 900 $ — courtier **RE/MAX Québec (RE/MAX Crystal inc.)**\n- La fiche visible est celle du courtier, et la box « Aussi publiée sur » liste ses 2 doublons :\n - **Facebook Marketplace** → facebook.com/marketplace/item/4531198097125503\n - **RE/MAX Crystal** (site d'agence) → remaxcrystal.com/…/3289-rue-bossuet\n\nAvant le changement d'aujourd'hui, c'est la version FB anonyme qui aurait pu gagner la dédup ; maintenant le courtier passe devant et la republication FB est reléguée dans la 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facebook.com/marketplace/item/4531198097125503\n - **RE/MAX Crystal** (site d'agence) → remaxcrystal.com/…/3289-rue-bossuet\n\nAvant le changement d'aujourd'hui, c'est la version FB anonyme qui aurait pu gagner la dédup ; maintenant le courtier passe devant et la republication FB est reléguée dans la 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{"type":"claude","event":{"type":"assistant","message":{"model":"claude-fable-5","id":"msg_011CePcjj8XGF2MNmK8bEjqW","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_012sbFeBzjSv44MXKaXUDxmH","name":"Bash","input":{"command":"sqlite3 data/immoka.db \"\nSELECT 'actives totales', COUNT(*) FROM listings WHERE active=1;\nSELECT 'uniques visibles (dédup + publiées)', COUNT(*) FROM listings WHERE active=1 AND dup_hidden=0 AND published=1;\nSELECT 'masquées comme doublons', COUNT(*) FROM listings WHERE active=1 AND dup_hidden=1;\nSELECT 'quarantaine qualité', COUNT(*) FROM listings WHERE active=1 AND dup_hidden=0 AND published=0;\"","description":"Count unique visible listings vs 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Le détail :\n\n| | |\n|---|---|\n| Fiches actives totales (toutes sources) | 134 317 |\n| − masquées comme doublons (dédup) | 51 987 |\n| − en quarantaine qualité (incomplètes) | 13 091 |\n| **= uniques publiées** | **69 239** |\n\nDonc en gros 39 % du contenu brut est de la duplication inter-sources (sous-agences Centris, republications FB/Kijiji/LesPAC, sites d'agences) — et chaque doublon masqué est maintenant rattaché à sa fiche visible via `dup_of`, ce qui alimente la box « Aussi publiée sur »."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":388,"cache_read_input_tokens":85668,"cache_creation":{"ephemeral_5m_input_tokens":388,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"global"},"context_management":null},"parent_tool_use_id":null,"session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","uuid":"7d3aa7ff-969b-4c39-ade6-00a8105a986f"}} {"type":"claude","event":{"type":"result","subtype":"success","is_error":false,"api_error_status":null,"duration_ms":19460,"duration_api_ms":19213,"num_turns":2,"result":"Exact — **69 239 annonces uniques visibles** sur le site. Le détail :\n\n| | |\n|---|---|\n| Fiches actives totales (toutes sources) | 134 317 |\n| − masquées comme doublons (dédup) | 51 987 |\n| − en quarantaine qualité (incomplètes) | 13 091 |\n| **= uniques publiées** | **69 239** |\n\nDonc en gros 39 % du contenu brut est de la duplication inter-sources (sous-agences Centris, republications FB/Kijiji/LesPAC, sites d'agences) — et chaque doublon masqué est maintenant rattaché à sa fiche visible via `dup_of`, ce qui alimente la box « Aussi publiée sur ».","stop_reason":"end_turn","session_id":"4c9543da-fa95-4658-8db4-70aa0feada91","total_cost_usd":0.0627525,"usage":{"input_tokens":4,"cache_creation_input_tokens":714,"cache_read_input_tokens":171010,"output_tokens":584,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":714},"inference_geo":"","iterations":[{"input_tokens":2,"output_tokens":251,"cache_read_input_tokens":85668,"cache_creation_input_tokens":388,"cache_creation":{"ephemeral_5m_input_tokens":388,"ephemeral_1h_input_tokens":0},"type":"message"}],"speed":"standard"},"modelUsage":{"claude-fable-5":{"inputTokens":4,"outputTokens":584,"cacheReadInputTokens":171010,"cacheCreationInputTokens":714,"webSearchRequests":0,"costUSD":0.0627525,"contextWindow":200000,"maxOutputTokens":32000}},"permission_denials":[],"terminal_reason":"completed","fast_mode_state":"off","uuid":"2318f014-24f7-4cfc-a1bd-8b3aab4e108a"}} {"type":"status","state":"idle"}