House-Ka v1 — English homes-for-sale aggregator for Canada outside Québec (fork of Immo-Ka) · bc58598 · house-ka

House-Ka v1 — English homes-for-sale aggregator for Canada outside Québec (fork of Immo-Ka)

- Backend: RealtyPress/CREA DDF connectors only (15 ON sources), Canada-wide
  bbox, English canonical property types, relaxed publication rule
  (price+city), English SEO (/property, /for-sale, /type), QC-only modules
  removed (Hydro-Québec, BDZI, RSQAQ, gaz, RDL, quartier, Vrai-Prix,
  movers/inspectors, PDF sheets, QC connectors).
- Frontend: new English skin — pine/cream palette, Fraunces serif display,
  custom footer, Ka Maps themed house-ka, mortgage engine UI in English.
- Data: 202 190 Ontario listings imported from immo-ka (pause-ontario moved
  here), types derived from DDF details, IMMOKA_RP_DETAIL_LIMIT=1200.

Simon-Pierre Boucher committed 27 days ago (Aug 27, 2026)

91 changed files +20,001 −0

added .claude/settings.local.json +5 −0

		`@@ -0,0 +1,5 @@`
	1	+{
	2	+ "enabledMcpjsonServers": [
	3	+ "cluster"
	4	+ ]
	5	+}

added .env.example +27 −0

		`@@ -0,0 +1,27 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — variables d'environnement (modèle ; copier vers .env, NE PAS COMMITTER .env)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# -----------------------------------------------------------------------------
	5	+
	6	+# --- Général ------------------------------------------------------------------
	7	+IMMOKA_BASE_URL=https://www.immo-ka.com
	8	+
	9	+# --- Connecteurs immobiliers (scraping) ----------------------------------------
	10	+FIRECRAWL_API_KEY=
	11	+SCRAPFLY_KEY= # anti-bot — aussi utilisé par les providers de taux (dernier recours)
	12	+HQ_CAPTCHA_KEY=
	13	+HQ_CAPTCHA_PROVIDER=
	14	+
	15	+# --- Compte KA (SSO groupe-ka.com) ---------------------------------------------
	16	+KA_SSO_SECRET=
	17	+KA_HUB_URL=
	18	+AUTH_SECRET=
	19	+
	20	+# --- Vrai-Prix -----------------------------------------------------------------
	21	+VRAIPRIX_DB=
	22	+
	23	+# --- Moteur hypothécaire (immoka/mortgage) ---------------------------------------
	24	+# Aucun taux n'est jamais inventé : ces variables ne règlent que la collecte.
	25	+IMMOKA_MORTGAGE_INTERVAL_MIN=180 # fréquence de collecte (minutes) — watch/maybe_run
	26	+IMMOKA_MORTGAGE_RETRIES=3 # tentatives par provider avant échec
	27	+IMMOKA_MORTGAGE_BACKOFF=5 # backoff exponentiel de base (secondes)

added .gitignore +11 −0

		`@@ -0,0 +1,11 @@`
	1	+.venv/
	2	+__pycache__/
	3	+*.pyc
	4	+data/*.db
	5	+data/*.db-shm
	6	+data/*.db-wal
	7	+frontend/node_modules/
	8	+frontend/dist/
	9	+frontend/tsconfig.tsbuildinfo
	10	+.env
	11	+.DS_Store

added README.md +67 −0

		`@@ -0,0 +1,67 @@`
	1	+# House-Ka
	2	+
	3	+www.house-ka.com — Homes-for-sale aggregator for Canada outside Québec,
	4	+Ontario first. A Groupe KA service, sister site of
	5	+[Immo-Ka](https://www.immo-ka.com) (Québec).
	6	+
	7	+House-Ka continuously aggregates homes publicly listed by Canadian real-estate
	8	+brokerages and teams whose sites run the RealtyPress WordPress plugin on
	9	+the CREA DDF feed. Each site exposes its board's full inventory; a single
	10	+generic connector (`immoka/connectors/realtypress.py`) covers them all, and
	11	+cross-site duplicates are masked by DDF number (`external_id = ddf<id>`).
	12	+
	13	+## Architecture
	14	+
	15	+Forked from Immo-Ka on 2026-08-27 (the Ontario expansion paused there moved
	16	+here). The Python package keeps its historical name `immoka`.
	17	+
	18	+- Backend — FastAPI + SQLite (`data/immoka.db`), same pipeline as Immo-Ka:
	19	+ connectors → `ingest` → dedup → `quality` (relaxed publication rule: price +
	20	+ city; type/description enrich over time via detail passes) → API.
	21	+- Frontend — React/Vite, English, pine/cream/serif skin (deliberately
	22	+ different from Immo-Ka's cherry). Routes: `/`, `/property/{uid}[/{slug}]`,
	23	+ `/for-sale/{city}[/{type}]`, `/type/{type}`, `/rates`, `/agencies`, `/stats`.
	24	+ Map = Ka Maps (`@groupe-ka/ka-maps`, expected at `../../ka-maps`).
	25	+- SEO — `immoka/seo.py` renders server-side HTML (meta, JSON-LD, sitemaps)
	26	+ in English.
	27	+- Mortgage engine — shared with Immo-Ka (`immoka/mortgage/`), national
	28	+ Canadian rates. See `docs/mortgage-engine.md`.
	29	+- Removed vs Immo-Ka — everything Québec-only: Hydro-Québec estimates,
	30	+ BDZI flood, RSQAQ air, gazquebec, rental registry, quartier (census),
	31	+ Vrai-Prix, movers/inspectors directories, PDF listing sheets, all QC
	32	+ connectors.
	33	+
	34	+## Canonical property types (English)
	35	+
	36	+`House, Condo, Townhouse, Semi-detached, Duplex, Triplex, Multi-family,
	37	+Cottage, Mobile home, Land, Farm, Commercial, Parking` —
	38	+see `immoka/normalize.py`. DDF list cards carry no type: most listings get
	39	+their type when their detail page is fetched (`IMMOKA_RP_DETAIL_LIMIT` per
	40	+source per sync).
	41	+
	42	+## Run
	43	+
	44	+```bash
	45	+python run.py sync [source ...] # sync listings
	46	+python run.py watch [minutes] # sync loop (default 60 min)
	47	+python run.py serve [port] # API + frontend (default 8098)
	48	+python run.py list # registered connectors
	49	+python run.py geocode [n] # geocode listings missing coordinates
	50	+python run.py mortgage-sync # collect mortgage rates
	51	+```
	52	+
	53	+`.env`: `IMMOKA_BASE_URL=https://www.house-ka.com`,
	54	+`IMMOKA_RP_DETAIL_LIMIT=<n>` (detail pages fetched per source per sync).
	55	+
	56	+## Deployment
	57	+
	58	+M4M64b, `~/apps/house-ka`, PM2 (`house-ka-web` :8098, `house-ka-sync`,
	59	+`house-ka-ngrok` → www.house-ka.com). Remote-first: the repo on the node is
	60	+the source of truth, `origin` = spbgit (`gitsrv:house-ka.git`).
	61	+
	62	+## Adding sources (rest of Canada)
	63	+
	64	+RealtyPress sites exist across Canada. Census & instructions:
	65	+`docs/ontario-agencies.md` (method transposes to any province). Add the site
	66	+to `data/ontario_agencies.json` + an entry in `data/sources.json`, then
	67	+`python run.py sync <id>`. The coordinate guard covers all of Canada.

added data/ontario_agencies.json +96 −0

		`@@ -0,0 +1,96 @@`
	1	+[
	2	+ {
	3	+ "id": "rp_ag_revelrealty",
	4	+ "name": "Revel Realty (Niagara & provincial)",
	5	+ "site": "https://revelrealty.ca",
	6	+ "archive": "listings",
	7	+ "max_pages": 1300,
	8	+ "note": "Recensement ON 2026-08-27 : ~110 145 fiches — pool DDF quasi provincial. Archive /listings/ (⚠ /listing/ = carousel 8 cartes), 108 cartes/page avec posts_per_page=100. RealtyPress/DDF."
	9	+ },
	10	+ {
	11	+ "id": "rp_ag_codygroup",
	12	+ "name": "The Cody Group (London/ITSO)",
	13	+ "site": "https://codygroup.ca",
	14	+ "archive": "all-regional-listings",
	15	+ "max_pages": 700,
	16	+ "note": "Recensement ON 2026-08-27 : ~58 062 fiches (London + ITSO élargi). Archive /all-regional-listings/, fiches sous le même chemin. RealtyPress/DDF."
	17	+ },
	18	+ {
	19	+ "id": "rp_ag_suttonottawa",
	20	+ "name": "Sutton Group — Ottawa Realty",
	21	+ "site": "https://suttonottawa.ca",
	22	+ "note": "Recensement ON 2026-08-27 : ~10 080 fiches (OREB+). RealtyPress/DDF."
	23	+ },
	24	+ {
	25	+ "id": "rp_ag_helensteam",
	26	+ "name": "Helen's Team (Kitchener-Waterloo)",
	27	+ "site": "https://helensteam.ca",
	28	+ "note": "Recensement ON 2026-08-27 : ~9 910 fiches (Kitchener-Waterloo). RealtyPress/DDF."
	29	+ },
	30	+ {
	31	+ "id": "rp_ag_greybruce",
	32	+ "name": "Grey Bruce Real Estate",
	33	+ "site": "https://greybrucerealestate.ca",
	34	+ "note": "Recensement ON 2026-08-27 : ~8 268 fiches (Grey-Bruce/Georgian Bay). RealtyPress/DDF. Même feed que collaborativerealestate.ca (fallback)."
	35	+ },
	36	+ {
	37	+ "id": "rp_ag_remaxfinest",
	38	+ "name": "RE/MAX Finest Realty (Kingston)",
	39	+ "site": "https://remaxfinestrealty.com",
	40	+ "note": "Recensement ON 2026-08-27 : ~8 217 fiches (Kingston). RealtyPress/DDF."
	41	+ },
	42	+ {
	43	+ "id": "rp_ag_riouxbaker",
	44	+ "name": "Rioux Baker Real Estate Team (Collingwood)",
	45	+ "site": "https://riouxbakerteam.com",
	46	+ "note": "Recensement ON 2026-08-27 : ~7 716 fiches (Collingwood/South Georgian Bay). RealtyPress/DDF."
	47	+ },
	48	+ {
	49	+ "id": "rp_ag_countyguys",
	50	+ "name": "The County Guys (Prince Edward County)",
	51	+ "site": "https://thecountyguys.com",
	52	+ "note": "Recensement ON 2026-08-27 : ~6 878 fiches (Prince Edward County/Quinte). RealtyPress/DDF."
	53	+ },
	54	+ {
	55	+ "id": "rp_ag_labrosse",
	56	+ "name": "Labrosse Real Estate (Ottawa/Orléans)",
	57	+ "site": "https://labrosserealestate.com",
	58	+ "note": "Recensement ON 2026-08-27 : ~6 873 fiches (Ottawa/Orléans, équipe FRANCOPHONE). RealtyPress/DDF."
	59	+ },
	60	+ {
	61	+ "id": "rp_ag_ryanpattinson",
	62	+ "name": "Ryan Pattinson (Pembroke/Renfrew)",
	63	+ "site": "https://ryanpattinson.com",
	64	+ "note": "Recensement ON 2026-08-27 : ~6 601 fiches (Pembroke/vallée de l'Outaouais ON). RealtyPress/DDF."
	65	+ },
	66	+ {
	67	+ "id": "rp_ag_grapevine",
	68	+ "name": "Grapevine (Ottawa)",
	69	+ "site": "https://grapevine.ca",
	70	+ "note": "Recensement ON 2026-08-27 : ~6 550 fiches (Ottawa). RealtyPress/DDF. Suivre les redirections www/apex."
	71	+ },
	72	+ {
	73	+ "id": "rp_ag_rlpheartland",
	74	+ "name": "Royal LePage Heartland Realty",
	75	+ "site": "https://rlpheartland.ca",
	76	+ "note": "Recensement ON 2026-08-27 : ~5 577 fiches (Midwestern Ontario — Huron/Perth). RealtyPress/DDF."
	77	+ },
	78	+ {
	79	+ "id": "rp_ag_signaturenorth",
	80	+ "name": "Signature North Realty (Thunder Bay)",
	81	+ "site": "https://signaturenorthrealty.ca",
	82	+ "note": "Recensement ON 2026-08-27 : ~1 023 fiches (Thunder Bay). RealtyPress/DDF."
	83	+ },
	84	+ {
	85	+ "id": "rp_ag_saultstemarie",
	86	+ "name": "Sault Ste. Marie Real Estate (Century 21 Choice)",
	87	+ "site": "https://saultstemarierealestate.com",
	88	+ "note": "Recensement ON 2026-08-27 : ~864 fiches (Sault Ste. Marie). RealtyPress/DDF."
	89	+ },
	90	+ {
	91	+ "id": "rp_ag_cbnorthbay",
	92	+ "name": "Coldwell Banker Peter Minogue (North Bay)",
	93	+ "site": "https://cbnorthbay.com",
	94	+ "note": "Recensement ON 2026-08-27 : ~307 fiches (North Bay). RealtyPress/DDF."
	95	+ }
	96	+]

added data/sources.json +169 −0

		`@@ -0,0 +1,169 @@`
	1	+{
	2	+ "sources": [
	3	+ {
	4	+ "id": "rp_ag_revelrealty",
	5	+ "name": "Revel Realty (Niagara & provincial)",
	6	+ "url": "https://revelrealty.ca",
	7	+ "listing_url": "https://revelrealty.ca/listings/",
	8	+ "coverage": "Niagara + pool DDF quasi provincial — ~110 000 fiches",
	9	+ "connector": "realtypress",
	10	+ "status": "actif",
	11	+ "type": "agence",
	12	+ "note": "House-Ka — generic RealtyPress connector (registry data/ontario_agencies.json). WordPress RealtyPress plugin on the CREA DDF feed. external_id ddf<id>: cross-site dedup by MIN(uid)."
	13	+ },
	14	+ {
	15	+ "id": "rp_ag_codygroup",
	16	+ "name": "The Cody Group (London/ITSO)",
	17	+ "url": "https://codygroup.ca",
	18	+ "listing_url": "https://codygroup.ca/all-regional-listings/",
	19	+ "coverage": "London + ITSO élargi — ~58 000 fiches DDF",
	20	+ "connector": "realtypress",
	21	+ "status": "actif",
	22	+ "type": "agence",
	23	+ "note": "House-Ka — generic RealtyPress connector (registry data/ontario_agencies.json). WordPress RealtyPress plugin on the CREA DDF feed. external_id ddf<id>: cross-site dedup by MIN(uid)."
	24	+ },
	25	+ {
	26	+ "id": "rp_ag_suttonottawa",
	27	+ "name": "Sutton Group — Ottawa Realty",
	28	+ "url": "https://suttonottawa.ca",
	29	+ "listing_url": "https://suttonottawa.ca/listing/",
	30	+ "coverage": "Ottawa et l'Est ontarien (board OREB) — ~10 000 fiches DDF",
	31	+ "connector": "realtypress",
	32	+ "status": "actif",
	33	+ "type": "agence",
	34	+ "note": "House-Ka — generic RealtyPress connector (registry data/ontario_agencies.json). WordPress RealtyPress plugin on the CREA DDF feed. external_id ddf<id>: cross-site dedup by MIN(uid)."
	35	+ },
	36	+ {
	37	+ "id": "rp_ag_helensteam",
	38	+ "name": "Helen's Team (Kitchener-Waterloo)",
	39	+ "url": "https://helensteam.ca",
	40	+ "listing_url": "https://helensteam.ca/listing/",
	41	+ "coverage": "Kitchener-Waterloo et région (ITSO) — ~9 900 fiches DDF",
	42	+ "connector": "realtypress",
	43	+ "status": "actif",
	44	+ "type": "agence",
	45	+ "note": "House-Ka — generic RealtyPress connector (registry data/ontario_agencies.json). WordPress RealtyPress plugin on the CREA DDF feed. external_id ddf<id>: cross-site dedup by MIN(uid)."
	46	+ },
	47	+ {
	48	+ "id": "rp_ag_greybruce",
	49	+ "name": "Grey Bruce Real Estate",
	50	+ "url": "https://greybrucerealestate.ca",
	51	+ "listing_url": "https://greybrucerealestate.ca/listing/",
	52	+ "coverage": "Grey-Bruce / Georgian Bay (ITSO) — ~8 300 fiches DDF",
	53	+ "connector": "realtypress",
	54	+ "status": "actif",
	55	+ "type": "agence",
	56	+ "note": "House-Ka — generic RealtyPress connector (registry data/ontario_agencies.json). WordPress RealtyPress plugin on the CREA DDF feed. external_id ddf<id>: cross-site dedup by MIN(uid)."
	57	+ },
	58	+ {
	59	+ "id": "rp_ag_remaxfinest",
	60	+ "name": "RE/MAX Finest Realty (Kingston)",
	61	+ "url": "https://remaxfinestrealty.com",
	62	+ "listing_url": "https://remaxfinestrealty.com/listing/",
	63	+ "coverage": "Kingston et région (KAREA) — ~8 200 fiches DDF",
	64	+ "connector": "realtypress",
	65	+ "status": "actif",
	66	+ "type": "agence",
	67	+ "note": "House-Ka — generic RealtyPress connector (registry data/ontario_agencies.json). WordPress RealtyPress plugin on the CREA DDF feed. external_id ddf<id>: cross-site dedup by MIN(uid)."
	68	+ },
	69	+ {
	70	+ "id": "rp_ag_riouxbaker",
	71	+ "name": "Rioux Baker Real Estate Team (Collingwood)",
	72	+ "url": "https://riouxbakerteam.com",
	73	+ "listing_url": "https://riouxbakerteam.com/listing/",
	74	+ "coverage": "Collingwood / South Georgian Bay — ~7 700 fiches DDF",
	75	+ "connector": "realtypress",
	76	+ "status": "actif",
	77	+ "type": "agence",
	78	+ "note": "House-Ka — generic RealtyPress connector (registry data/ontario_agencies.json). WordPress RealtyPress plugin on the CREA DDF feed. external_id ddf<id>: cross-site dedup by MIN(uid)."
	79	+ },
	80	+ {
	81	+ "id": "rp_ag_countyguys",
	82	+ "name": "The County Guys (Prince Edward County)",
	83	+ "url": "https://thecountyguys.com",
	84	+ "listing_url": "https://thecountyguys.com/listing/",
	85	+ "coverage": "Prince Edward County / Quinte — ~6 900 fiches DDF",
	86	+ "connector": "realtypress",
	87	+ "status": "actif",
	88	+ "type": "agence",
	89	+ "note": "House-Ka — generic RealtyPress connector (registry data/ontario_agencies.json). WordPress RealtyPress plugin on the CREA DDF feed. external_id ddf<id>: cross-site dedup by MIN(uid)."
	90	+ },
	91	+ {
	92	+ "id": "rp_ag_labrosse",
	93	+ "name": "Labrosse Real Estate (Ottawa/Orléans)",
	94	+ "url": "https://labrosserealestate.com",
	95	+ "listing_url": "https://labrosserealestate.com/listing/",
	96	+ "coverage": "Ottawa / Orléans (équipe francophone, OREB) — ~6 900 fiches DDF",
	97	+ "connector": "realtypress",
	98	+ "status": "actif",
	99	+ "type": "agence",
	100	+ "note": "House-Ka — generic RealtyPress connector (registry data/ontario_agencies.json). WordPress RealtyPress plugin on the CREA DDF feed. external_id ddf<id>: cross-site dedup by MIN(uid)."
	101	+ },
	102	+ {
	103	+ "id": "rp_ag_ryanpattinson",
	104	+ "name": "Ryan Pattinson (Pembroke/Renfrew)",
	105	+ "url": "https://ryanpattinson.com",
	106	+ "listing_url": "https://ryanpattinson.com/listing/",
	107	+ "coverage": "Pembroke / vallée de l'Outaouais ontarienne — ~6 600 fiches DDF",
	108	+ "connector": "realtypress",
	109	+ "status": "actif",
	110	+ "type": "agence",
	111	+ "note": "House-Ka — generic RealtyPress connector (registry data/ontario_agencies.json). WordPress RealtyPress plugin on the CREA DDF feed. external_id ddf<id>: cross-site dedup by MIN(uid)."
	112	+ },
	113	+ {
	114	+ "id": "rp_ag_grapevine",
	115	+ "name": "Grapevine (Ottawa)",
	116	+ "url": "https://grapevine.ca",
	117	+ "listing_url": "https://grapevine.ca/listing/",
	118	+ "coverage": "Ottawa (OREB) — ~6 600 fiches DDF",
	119	+ "connector": "realtypress",
	120	+ "status": "actif",
	121	+ "type": "agence",
	122	+ "note": "House-Ka — generic RealtyPress connector (registry data/ontario_agencies.json). WordPress RealtyPress plugin on the CREA DDF feed. external_id ddf<id>: cross-site dedup by MIN(uid)."
	123	+ },
	124	+ {
	125	+ "id": "rp_ag_rlpheartland",
	126	+ "name": "Royal LePage Heartland Realty",
	127	+ "url": "https://rlpheartland.ca",
	128	+ "listing_url": "https://rlpheartland.ca/listing/",
	129	+ "coverage": "Midwestern Ontario (Huron-Perth) — ~5 600 fiches DDF",
	130	+ "connector": "realtypress",
	131	+ "status": "actif",
	132	+ "type": "agence",
	133	+ "note": "House-Ka — generic RealtyPress connector (registry data/ontario_agencies.json). WordPress RealtyPress plugin on the CREA DDF feed. external_id ddf<id>: cross-site dedup by MIN(uid)."
	134	+ },
	135	+ {
	136	+ "id": "rp_ag_signaturenorth",
	137	+ "name": "Signature North Realty (Thunder Bay)",
	138	+ "url": "https://signaturenorthrealty.ca",
	139	+ "listing_url": "https://signaturenorthrealty.ca/listing/",
	140	+ "coverage": "Thunder Bay — ~1 000 fiches DDF",
	141	+ "connector": "realtypress",
	142	+ "status": "actif",
	143	+ "type": "agence",
	144	+ "note": "House-Ka — generic RealtyPress connector (registry data/ontario_agencies.json). WordPress RealtyPress plugin on the CREA DDF feed. external_id ddf<id>: cross-site dedup by MIN(uid)."
	145	+ },
	146	+ {
	147	+ "id": "rp_ag_saultstemarie",
	148	+ "name": "Sault Ste. Marie Real Estate (Century 21 Choice)",
	149	+ "url": "https://saultstemarierealestate.com",
	150	+ "listing_url": "https://saultstemarierealestate.com/listing/",
	151	+ "coverage": "Sault Ste. Marie — ~860 fiches DDF",
	152	+ "connector": "realtypress",
	153	+ "status": "actif",
	154	+ "type": "agence",
	155	+ "note": "House-Ka — generic RealtyPress connector (registry data/ontario_agencies.json). WordPress RealtyPress plugin on the CREA DDF feed. external_id ddf<id>: cross-site dedup by MIN(uid)."
	156	+ },
	157	+ {
	158	+ "id": "rp_ag_cbnorthbay",
	159	+ "name": "Coldwell Banker Peter Minogue (North Bay)",
	160	+ "url": "https://cbnorthbay.com",
	161	+ "listing_url": "https://cbnorthbay.com/listing/",
	162	+ "coverage": "North Bay / Nipissing — ~300 fiches DDF",
	163	+ "connector": "realtypress",
	164	+ "status": "actif",
	165	+ "type": "agence",
	166	+ "note": "House-Ka — generic RealtyPress connector (registry data/ontario_agencies.json). WordPress RealtyPress plugin on the CREA DDF feed. external_id ddf<id>: cross-site dedup by MIN(uid)."
	167	+ }
	168	+ ]
	169	+}
		\ No newline at end of file

added docs/mortgage-engine.md +163 −0

		`@@ -0,0 +1,163 @@`
	1	+# Moteur hypothécaire Immo-Ka (Mortgage Intelligence Engine)
	2	+
	3	+Moteur natif de collecte, d'historisation et de calcul des taux hypothécaires
	4	+canadiens, intégré au backend FastAPI d'Immo-Ka. **Aucun taux n'est jamais
	5	+inventé, codé en dur ni estimé** : tout taux affiché provient d'une page
	6	+officielle d'une institution financière, avec provenance (URL source) et
	7	+fraîcheur (horodatage de collecte).
	8	+
	9	+## Architecture
	10	+
	11	+```
	12	+immoka/mortgage/
	13	+├── providers/ # 1 connecteur indépendant par institution (12)
	14	+│ ├── base.py # RateProvider : fetch() → produits normalisés
	15	+│ └── README.md # comment ajouter une banque
	16	+├── validate.py # garde-fous anti-aberration (419 % ≠ 4,19 %…)
	17	+├── store.py # SQLite annexe data/mortgage.db — historisation
	18	+├── scheduler.py # orchestration : retries, backoff, santé, isolation
	19	+├── calc.py # mathématiques hypothécaires canadiennes
	20	+├── cmhc.py # assurance prêt (SCHL) + taxe de vente QC
	21	+└── api.py # routes /api/mortgage/* (montées dans web.py)
	22	+```
	23	+
	24	+Le flux : `provider.fetch()` → `validate_batch()` → `store.record_observations()`.
	25	+Les providers ne touchent jamais la base ; le calculateur ne touche jamais les
	26	+scrapers — seule l'API interne les relie.
	27	+
	28	+## Institutions couvertes (12 connecteurs)
	29	+
	30	+\| slug \| Institution \| Type de source \|
	31	+\|---\|---\|---\|
	32	+\| `bank_of_canada` \| Banque du Canada \| Valet API (JSON officiel) — taux de référence \|
	33	+\| `bmo` \| BMO \| JSON embarqué \|
	34	+\| `cibc` \| CIBC \| JSON \|
	35	+\| `desjardins` \| Desjardins \| HTML \|
	36	+\| `eq_bank` \| Banque EQ \| HTML \|
	37	+\| `first_national` \| First National \| HTML \|
	38	+\| `mcap` \| MCAP \| HTML (taux préférentiel) \|
	39	+\| `national_bank` \| Banque Nationale \| HTML \|
	40	+\| `rbc` \| RBC \| JSON \|
	41	+\| `scotiabank` \| Banque Scotia \| JSON (posted + promos) \|
	42	+\| `tangerine` \| Tangerine \| JSON \|
	43	+\| `td` \| TD Canada Trust \| JSON \|
	44	+
	45	+Chaque produit est normalisé par `RateProvider.make_product()` :
	46	+`provider, institution, product_name, rate_type (fixed\|variable\|other),
	47	+term_months, kind (posted\|special), rate, apr, insured_status
	48	+(insured\|insurable\|uninsured\|unknown), purpose (purchase\|renewal\|refinance\|unknown),
	49	+amortization_max_years, conditions, source_url, confidence, raw`.
	50	+
	51	+Les taux préférentiels/prime sont stockés en `rate_type="other"` +
	52	+`purpose="unknown"` : ils ne peuvent jamais contaminer un classement
	53	+« meilleur taux d'achat ».
	54	+
	55	+## Validation (validate.py)
	56	+
	57	+Rejette avant enregistrement :
	58	+- taux hors bornes plausibles (0,5 %–24 %) — attrape `4.19 → 419` ;
	59	+- champs requis manquants, enums invalides, termes hors 3–120 mois ;
	60	+- APR incohérent (APR < taux − 0,02 pt) ou aberrant ;
	61	+- doublons exacts dans un même lot (silencieusement dédupliqués).
	62	+
	63	+Un lot partiellement invalide n'est pas jeté : les produits sains sont
	64	+enregistrés, les problèmes journalisés.
	65	+
	66	+## Historisation (store.py — data/mortgage.db, WAL)
	67	+
	68	+- `rate_observations` : périodes de validité (`valid_from`/`valid_to`,
	69	+ `is_current`). Taux inchangé → simple mise à jour de `last_checked` ;
	70	+ taux changé → clôture de la période + nouvelle ligne. Un saut > 2,5 pts en
	71	+ < 48 h est rejeté sans écraser la donnée existante (garde anti-aberration
	72	+ au niveau BD).
	73	+- `provider_runs` : journal de chaque collecte (statut, durée, produits,
	74	+ changements, rejets) → santé OK / WARNING (> 24 h) / ERROR.
	75	+- `product_key` : sha1 tronqué de
	76	+ `provider\|rate_type\|term\|kind\|insured\|purpose\|name` — identité stable d'un
	77	+ produit à travers le temps.
	78	+
	79	+En cas de panne d'une source, les derniers taux valides restent servis,
	80	+avec leur âge affiché (mention « stale » au-delà de 24 h).
	81	+
	82	+## Collecte (scheduler.py)
	83	+
	84	+- `run_provider(slug)` : retries (défaut 3) avec backoff exponentiel ;
	85	+ une exception d'un provider n'affecte jamais les autres.
	86	+- `run()` : séquentiel et poli (`request_delay` par provider — jamais de
	87	+ martèlement des sites bancaires).
	88	+- `watch(min)` : boucle autonome ; `maybe_run()` est appelé depuis la boucle
	89	+ d'ingestion existante (process PM2 `immo-ka-sync`) et ne collecte que si
	90	+ la dernière passe date de plus de `IMMOKA_MORTGAGE_INTERVAL_MIN` minutes
	91	+ (défaut 180).
	92	+
	93	+CLI :
	94	+
	95	+```bash
	96	+python run.py mortgage-sync [slug…] # collecte (toutes ou certaines banques)
	97	+python run.py mortgage-watch [min] # boucle autonome
	98	+python run.py mortgage-status # santé des providers
	99	+```
	100	+
	101	+Variables d'environnement (voir `.env.example`) :
	102	+`IMMOKA_MORTGAGE_INTERVAL_MIN`, `IMMOKA_MORTGAGE_RETRIES`,
	103	+`IMMOKA_MORTGAGE_BACKOFF`, `SCRAPFLY_KEY` (anti-bot, dernier recours).
	104	+
	105	+## Calculateur canadien (calc.py + cmhc.py)
	106	+
	107	+- Composition semestrielle pour les taux fixes (norme légale canadienne) :
	108	+ taux périodique = `(1 + r/2)^(2/f) − 1`. Valeur étalon vérifiée par test :
	109	+ 100 000 $ à 6 % sur 25 ans = 639,81 $/mois (≠ 644,30 $ en composition
	110	+ mensuelle américaine — testé aussi, pour prouver qu'on n'utilise pas la
	111	+ mauvaise formule). Taux variables : composition mensuelle.
	112	+- 6 fréquences : mensuelle, bimensuelle, aux 2 semaines, hebdomadaire,
	113	+ accélérée aux 2 semaines (mensualité ÷ 2), accélérée hebdo (÷ 4).
	114	+- Test de résistance fédéral : qualification à `max(taux + 2, 5,25 %)`.
	115	+- SCHL (cmhc.py) : mise de fonds légale minimale (5 % / 10 % / 20 %),
	116	+ primes par tranche RPV (0,60 % → 4,00 %), surprime +0,20 % amortissement
	117	+ 30 ans (premier acheteur), plafond assurable 1,5 M$, **TVQ 9,975 % sur la
	118	+ prime payable comptant** (spécificité québécoise) — la prime s'ajoute au
	119	+ prêt, la taxe non.
	120	+- Tableau d'amortissement, résumé de terme (solde au renouvellement),
	121	+ scénarios de renouvellement (+0/+1/+2/+3 pts), ratios ABD/ATD informatifs,
	122	+ inverses (prêt max pour un versement, taux requis).
	123	+
	124	+## API interne (`/api/mortgage/*`)
	125	+
	126	+\| Route \| Rôle \|
	127	+\|---\|---\|
	128	+\| `GET /rates` \| taux courants filtrables (type, terme, kind, provider…) \|
	129	+\| `GET /rates/best` \| meilleur taux comparable + classement par institution \|
	130	+\| `GET /rates/history` \| périodes de validité (historique réel, jamais extrapolé) \|
	131	+\| `GET /providers` \| santé des sources (OK/WARNING/ERROR, âge, produits) \|
	132	+\| `GET /market` \| vue marché (meilleur/médiane/variations 7-30 j) \|
	133	+\| `GET /intelligence` \| market + taux préférentiels (page /taux-hypothecaires) \|
	134	+\| `POST /calculate` \| calcul complet (SCHL, stress, terme, renouvellement…) \|
	135	+\| `POST /affordability` \| capacité d'emprunt (ABD/ATD + stress test) \|
	136	+
	137	+Règle absolue : jamais de comparaison de produits incomparables — affiché
	138	+vs offre spéciale, assuré vs non assuré — sans l'indiquer. Le comparateur ne
	139	+garde qu'un produit comparable par institution (l'offre spéciale prime).
	140	+
	141	+## Frontend
	142	+
	143	+- Fiche propriété (`Financement.tsx`, section « Financer cette propriété »,
	144	+ ventes seulement) : prix prérempli, mise de fonds $/% synchronisée,
	145	+ versement + taux utilisé avec provenance/fraîcheur, SCHL détaillée,
	146	+ coût réel mensuel (+ taxes municipales/scolaires de la fiche), stress test,
	147	+ renouvellement, comparateur banques, historique SVG, amortissement.
	148	+- Page `/taux-hypothecaires` (`Taux.tsx`) : vue marché cliquable,
	149	+ comparateur par institution (nature + fraîcheur + source officielle),
	150	+ historique, santé des sources. Référencée (seo.py + sitemap).
	151	+
	152	+## Tests
	153	+
	154	+```bash
	155	+PYTHONPATH=. .venv/bin/python -P -m unittest discover -s tests
	156	+```
	157	+
	158	+61 tests : `test_mortgage_calc.py` (valeurs étalons, fréquences accélérées,
	159	+inverses, stress), `test_mortgage_cmhc.py` (primes, TVQ, éligibilité),
	160	+`test_mortgage_validate.py` (anti-aberration), `test_mortgage_store.py`
	161	+(historisation, garde 2,5 pts, meilleur taux), `test_mortgage_providers.py`
	162	+(chaque parseur sur fixtures HTML/JSON committées dans
	163	+`tests/fixtures/mortgage/` — aucun réseau).

added docs/ontario-agencies.md +87 −0

		`@@ -0,0 +1,87 @@`
	1	+# Extension Ontario — liste des agences & sous-agents connectables
	2	+
	3	+Recensement du 2026-08-27 (~150 sites vérifiés live par curl : plateforme, rendu, volume, code HTTP).
	4	+Doctrine immo-ka : connecteurs par site d'agence/équipe (éviter les portails durs type realtor.ca).
	5	+Constat structurel ON : contrairement au Québec, un site d'agence expose souvent l'IDX/DDF complet de son board (TRREB, OREB, RAHB, ITSO, LSTAR, WECAR, KAREA…) → quelques connecteurs bien choisis ≈ toute la province. Dédupliquer par MLS#.
	6	+
	7	+## Priorité 1 — RealtyPress (plugin WordPress branché CREA DDF)
	8	+
	9	+Signature : `wp-content/plugins/realtypress-premium`, archive `/listing/` ou `/listings/`, SSR paginé `?paged=N`, MLS# dans l'URL de détail. Un connecteur générique = tous ces sites. Aucun anti-bot (200 en curl nu).
	10	+
	11	+\| Site \| Zone \| Volume vérifié \|
	12	+\|---\|---\|---\|
	13	+\| revelrealty.ca \| Niagara (multi-bureaux) \| 110 171 — pool DDF quasi complet ⭐ \|
	14	+\| codygroup.ca \| London \| 58 074 ⭐ \|
	15	+\| suttonottawa.ca \| Ottawa \| 10 080 (OREB+) \|
	16	+\| helensteam.ca \| Kitchener-Waterloo \| 9 910 \|
	17	+\| greybrucerealestate.ca \| Grey-Bruce/Georgian Bay \| 8 268 \|
	18	+\| collaborativerealestate.ca \| Blue Mountains \| 8 268 (même feed que Grey-Bruce → fallback) \|
	19	+\| remaxfinestrealty.com \| Kingston \| 8 217 \|
	20	+\| riouxbakerteam.com \| Collingwood \| 7 716 \|
	21	+\| thecountyguys.com \| Prince Edward County \| 6 878 \|
	22	+\| labrosserealestate.com \| Ottawa/Orléans (francophone) \| 6 873 \|
	23	+\| ryanpattinson.com \| Pembroke/Renfrew \| 6 601 \|
	24	+\| grapevine.ca \| Ottawa \| 6 550 \|
	25	+\| rlpheartland.ca \| Midwestern Ontario \| 5 577 \|
	26	+\| pennyblake.com / dynamickingston.com / thehintonteam.com \| Kingston \| 1 760 / 1 756 / 1 666 \|
	27	+\| signaturenorthrealty.ca \| Thunder Bay \| 1 023 \|
	28	+\| saultstemarierealestate.com \| Sault Ste Marie \| 864 \|
	29	+\| soldsmart.ca \| Cornwall (CDREB) \| 682 \|
	30	+\| 401homes.ca \| corridor 401 \| 662 \|
	31	+\| tcrealty.ca \| Thunder Bay \| 564 \|
	32	+\| cbnorthbay.com \| North Bay \| 307 \|
	33	+\| thebrollygroup.ca / teamkate.ca \| Brantford \| 231+ / régional \|
	34	+\| boldtrealty.ca \| St. Catharines \| bureau \|
	35	+\| Autres confirmés \| — \| thewillsteam.ca, dyerrealty.ca, muskoka-realestate.ca, barriehome.net, morrishometeam.com, dalebryant.ca, kenpipher.ca, greatermuskoka.ca, claimpostrealty.com, paulrushforth.com, liamswords.com \|
	36	+
	37	+→ Couverture : Niagara, London, Ottawa, KW, Kingston, Georgian Bay, PEC, Nord — quasi toute la province avec un seul parseur. Démo publique : demo.realtypress.ca.
	38	+
	39	+## Priorité 2 — myRealPage « recip.html » (réciprocité TRREB complète)
	40	+
	41	+SSR paginé `?_pg=N` (~12 annonces/page, prix dans le HTML), hôte central `idx.myrealpage.com`. Un connecteur = toute la grappe.
	42	+
	43	+- goldenhouserealty.com, remaxpluscity.com, foresthillcentral.com, baystreetcondos.ca, topgan.ca (Toronto — TRREB complet)
	44	+- jarrodarmstrong.com (condos TRREB), condominiums.ca (IDX condos GTA), yourmarkhamrealestate.ca (76 prix SSR)
	45	+- dottedline.ca (Tillsonburg, SSR 112) ; variantes JS : detailsrealty.ca, chellteam.com, maguireteam.ca, powerofsaleplus.ca
	46	+
	47	+## Priorité 3 — Sierra Interactive (SSR, API JSON connue)
	48	+
	49	+- robgolfi.com — RE/MAX Escarpment : 2 678 (RAHB complet) + 924 Oakville ⭐
	50	+- weknowottawa.com (Hamre, Ottawa 634+), feelyrealestate.com (Ottawa), niagarahomes.com (McGarr, 474 St. Catharines), teamgoran.com (Windsor/Chatham), viewbrantfordhomes.com, goodmanors.ca (Sudbury), anuraghomes.ca (KW)
	51	+
	52	+## Priorité 4 — AgentLocator (plateforme ontarienne, SSR + JSON `TotalIDX/TotalVOW` embarqué)
	53	+
	54	+- daverealty.ca (Cambridge, 1 272 IDX ITSO), ateamlondon.ca (London LSTAR), kitchenerwaterloo-realestate.com, stjeanrealty.com (Hamilton RAHB)
	55	+- Grappe Durham/York : miragerealestate.ca (103 prix), lighthouserealtygroup.ca (96), shawnlepp.com, buyselllove.ca, itsanna.ca, realtorsunnyg.com, teamarora.com
	56	+- jancsiks.com (Kawartha), pairofkings.ca (Dufferin) ; JS-only : seguinrealtyltd.com (franco Hawkesbury), agentinottawa.com
	57	+
	58	+## Priorité 5 — autres grappes mutualisées
	59	+
	60	+- Plateforme Windsor commune (custom SSR, URLs `/ville-properties` identiques) : buckinghamrealty.ca (4 943 = WECAR complet + Chatham-Kent), deerbrookproperty.com, nkrealestate.ca — 1 connecteur = 3 sites, zone mal desservie ailleurs ⭐
	61	+- Real Estate Webmasters (REW) : danplowman.com (Whitby, 529 prix SSR, TRREB large) ⭐, londonontariorealestate.com (Team Forster ~2 000 LSTAR), gordwaites.com + rlpmuskoka.com (Muskoka, cap 500), sudburyrealestate.ca
	62	+- EZ Media (vendeur régional, WP SSR) : performancerealty.ca (RLP Ottawa ~700 agents), remaxdeltahometeam.com (franco Embrun/Prescott-Russell), brockvillesutton.com, briangraham.ca (North Bay)
	63	+- InCom (JS — API centrale `/mapsearchapp/search?json=true` à reverser une fois) : chestnutpark.com, foresthill.com, dhesirealestate.ca, royallepagepremiumone.com, jasonyuteam.com, cbadvantage.ca, niagarapropertygroup.ca, suttongroupinnovative.com, kwhomegrouprealty.ca, brockvillehomes.com
	64	+- Luxury Presence (MLS TRREB dans les assets) : mcdadi.com (350+), goodalemillerteam.com, ppreteam.com, harveykalles.com, psrbrokerage.com, muskokacottagelistings.com, muskokacottagesforsale.com, lakelandsrealestate.ca
	65	+- SoldPress / Team Marshall (WP SSR, 1 parseur = 4 domaines) : teammarshall.ca, findingyourmuskoka.ca, findingyourparrysound.ca, findingyourmagnetawan.ca
	66	+- c21.ca corporate (API avec `company_uuid` — 1 connecteur = tous les bureaux C21 Canada) : heritagehouseniagara.c21.ca, c21firstcanadian.c21.ca, c21bluesky.com…
	67	+
	68	+## Sites custom individuels (SSR, un connecteur dédié chacun si ROI)
	69	+
	70	+- bushrealtysystems.com (Hamilton — moteur de recherche CREA board complet, `/search/listing/CREA/<mls>`)
	71	+- remaxquinte.com (Belleville, ColdFusion `listings.cfm`), thegrimeteam.com (Orangeville, ColdFusion, board interrogeable par params URL)
	72	+- exitrealtymatrix.com (Ottawa/Embrun franco-friendly, Onjax), therealtyfirm.ca (London/Woodstock, RealtyNinja SSR), m1wellington.com (Guelph, IDX Broker)
	73	+- trilliumwest.com (Guelph, 58 MLS refs), woolcott.ca (Waterdown DDF ~100+), peggyhill.com (Barrie, #1 RE/MAX Canada), tarteam.com (Markham, 31 prix), stacyvermeire.com (Cobourg, Ubertor SSR), troyausten.ca (Haliburton), homesincambridge.com (~108)
	74	+- JS-only à reverser si besoin : rightathomerealty.com (plus gros courtier indépendant du Canada — XHR probable Repliers/AMPRE), mls-sarnia.com + windsorrealestate.com (`__NEXT_DATA__`), phinneyrealestate.com, heyray.ca, elevatelondon.ca, housesforsaleottawa.ca, ngroup.ca (Kingston), kbbrokerage.ca, kawarthalife.com
	75	+
	76	+## Bloqués (403 Cloudflare — Scrapfly requis, faible priorité)
	77	+
	78	+teamrealty.ca, royalcity.com, royallepagetriland.com, wollerealty.com, remaxrecentre.ca, rlpbinder.ca, royallepagebrantrealty.com, viewhomes.ca, royallepagethunderbay.com, kormendytrott.com, rlpburloak.ca, remax-gc.ca, teamprestige.ca, estaterealty.ca, mullingroup.ca, royallepagequest.ca, faristeam.ca (429). Plusieurs partagent le même vendor (template RLP) → potentiel méga-connecteur via Scrapfly.
	79	+
	80	+## Plan de couverture minimal suggéré
	81	+
	82	+1. Connecteur RealtyPress générique + revelrealty/codygroup en sources primaires (≈ pool DDF provincial), sites régionaux en secours/dédup
	83	+2. Connecteur myRealPage recip (TRREB/GTA complet)
	84	+3. Connecteur Sierra (robgolfi = RAHB ; weknowottawa = OREB)
	85	+4. Connecteur AgentLocator (Durham/York + ITSO/LSTAR)
	86	+5. Connecteur Windsor mutualisé (WECAR) + REW (danplowman/Team Forster)
	87	+→ ~6-7 parseurs pour une couverture provinciale quasi complète, boards dédupliqués par MLS#.

added frontend/index.html +31 −0

		`@@ -0,0 +1,31 @@`
	1	+<!doctype html>
	2	+<!-- ---------------------------------------------------------------------------
	3	+ House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	4	+ Author: Simon-Pierre Boucher — contact@spboucher.ai
	5	+---------------------------------------------------------------------------- -->
	6	+<html lang="en-CA">
	7	+ <head>
	8	+ <meta charset="UTF-8" />
	9	+ <meta name="viewport" content="width=device-width, initial-scale=1.0, viewport-fit=cover" />
	10	+ <title>House-Ka — A Groupe KA service</title>
	11	+ <meta name="description" content="House-Ka, a Groupe KA service, aggregates homes for sale listed by Canadian real-estate brokerages on the CREA DDF feed — Ontario first, the rest of Canada next. Always up to date." />
	12	+ <meta name="theme-color" content="#14201a" />
	13	+ <meta name="mobile-web-app-capable" content="yes" />
	14	+ <meta name="apple-mobile-web-app-capable" content="yes" />
	15	+ <meta name="apple-mobile-web-app-title" content="House-Ka" />
	16	+ <link rel="preconnect" href="https://fonts.googleapis.com" />
	17	+ <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin />
	18	+ <link href="https://fonts.googleapis.com/css2?family=Fraunces:opsz,wght@9..144,500;9..144,600;9..144,700&family=Inter:wght@400;500;600;700&family=JetBrains+Mono:wght@400;500;700&display=swap" rel="stylesheet" />
	19	+ <link rel="icon" type="image/svg+xml" href="/favicon.svg" />
	20	+ <link rel="apple-touch-icon" href="/apple-touch-icon.png" />
	21	+ <meta property="og:image" content="https://www.house-ka.com/og.png" />
	22	+ <meta property="og:image:width" content="1200" />
	23	+ <meta property="og:image:height" content="630" />
	24	+ <meta name="twitter:card" content="summary_large_image" />
	25	+ <meta name="twitter:image" content="https://www.house-ka.com/og.png" />
	26	+ </head>
	27	+ <body>
	28	+ <div id="root"></div>
	29	+ <script type="module" src="/src/main.tsx"></script>
	30	+ </body>
	31	+</html>

added frontend/package-lock.json +1874 −0

		`@@ -0,0 +1,1874 @@`
	1	+{
	2	+ "name": "house-ka-frontend",
	3	+ "version": "1.0.0",
	4	+ "lockfileVersion": 3,
	5	+ "requires": true,
	6	+ "packages": {
	7	+ "": {
	8	+ "name": "house-ka-frontend",
	9	+ "version": "1.0.0",
	10	+ "dependencies": {
	11	+ "@groupe-ka/ka-maps": "file:../../ka-maps",
	12	+ "mapbox-gl": "^3.28.1",
	13	+ "react": "^18.3.1",
	14	+ "react-dom": "^18.3.1",
	15	+ "react-router-dom": "^6.26.0"
	16	+ },
	17	+ "devDependencies": {
	18	+ "@types/react": "^18.3.3",
	19	+ "@types/react-dom": "^18.3.0",
	20	+ "@vitejs/plugin-react": "^4.3.1",
	21	+ "typescript": "^5.5.4",
	22	+ "vite": "^5.4.0"
	23	+ }
	24	+ },
	25	+ "../../ka-maps": {
	26	+ "name": "@groupe-ka/ka-maps",
	27	+ "version": "0.2.0",
	28	+ "license": "UNLICENSED",
	29	+ "dependencies": {
	30	+ "@types/geojson": "^7946.0.16",
	31	+ "mapbox-gl": "^3.28.1"
	32	+ },
	33	+ "devDependencies": {
	34	+ "@types/react": "^18.3.3",
	35	+ "typescript": "^5.8.0",
	36	+ "vitest": "^3.0.0"
	37	+ },
	38	+ "peerDependencies": {
	39	+ "react": ">=18"
	40	+ },
	41	+ "peerDependenciesMeta": {
	42	+ "react": {
	43	+ "optional": true
	44	+ }
	45	+ }
	46	+ },
	47	+ "node_modules/@babel/code-frame": {
	48	+ "version": "7.29.7",
	49	+ "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.29.7.tgz",
	50	+ "integrity": "sha512-Aup7aUOfpbAUg2ROOJN6Iw5f9DMBlzu0mIkm/malLQFN/YQgO48wCj0Kxa3sEHJvPVFg7siR+qRInwXd2qhQKw==",
	51	+ "dev": true,
	52	+ "license": "MIT",
	53	+ "dependencies": {
	54	+ "@babel/helper-validator-identifier": "^7.29.7",
	55	+ "js-tokens": "^4.0.0",
	56	+ "picocolors": "^1.1.1"
	57	+ },
	58	+ "engines": {
	59	+ "node": ">=6.9.0"
	60	+ }
	61	+ },
	62	+ "node_modules/@babel/compat-data": {
	63	+ "version": "7.29.7",
	64	+ "resolved": "https://registry.npmjs.org/@babel/compat-data/-/compat-data-7.29.7.tgz",
	65	+ "integrity": "sha512-locTkQyKvwIEgBzVrn8693ebc97F2U8ZHjbXwDXJ5Fn2TCpNwTlKcaKLkdHop5c/icOFE7qt7Q9JC5hnKNa6Gg==",
	66	+ "dev": true,
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	1755	+ "dev": true,
	1756	+ "license": "BSD-3-Clause",
	1757	+ "engines": {
	1758	+ "node": ">=0.10.0"
	1759	+ }
	1760	+ },
	1761	+ "node_modules/typescript": {
	1762	+ "version": "5.9.3",
	1763	+ "resolved": "https://registry.npmjs.org/typescript/-/typescript-5.9.3.tgz",
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	1765	+ "dev": true,
	1766	+ "license": "Apache-2.0",
	1767	+ "bin": {
	1768	+ "tsc": "bin/tsc",
	1769	+ "tsserver": "bin/tsserver"
	1770	+ },
	1771	+ "engines": {
	1772	+ "node": ">=14.17"
	1773	+ }
	1774	+ },
	1775	+ "node_modules/update-browserslist-db": {
	1776	+ "version": "1.3.1",
	1777	+ "resolved": "https://registry.npmjs.org/update-browserslist-db/-/update-browserslist-db-1.3.1.tgz",
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	1779	+ "dev": true,
	1780	+ "funding": [
	1781	+ {
	1782	+ "type": "opencollective",
	1783	+ "url": "https://opencollective.com/browserslist"
	1784	+ },
	1785	+ {
	1786	+ "type": "tidelift",
	1787	+ "url": "https://tidelift.com/funding/github/npm/browserslist"
	1788	+ },
	1789	+ {
	1790	+ "type": "github",
	1791	+ "url": "https://github.com/sponsors/ai"
	1792	+ }
	1793	+ ],
	1794	+ "license": "MIT",
	1795	+ "dependencies": {
	1796	+ "escalade": "^3.2.0",
	1797	+ "picocolors": "^1.1.1"
	1798	+ },
	1799	+ "bin": {
	1800	+ "update-browserslist-db": "cli.js"
	1801	+ },
	1802	+ "peerDependencies": {
	1803	+ "browserslist": ">= 4.21.0"
	1804	+ }
	1805	+ },
	1806	+ "node_modules/vite": {
	1807	+ "version": "5.4.21",
	1808	+ "resolved": "https://registry.npmjs.org/vite/-/vite-5.4.21.tgz",
	1809	+ "integrity": "sha512-o5a9xKjbtuhY6Bi5S3+HvbRERmouabWbyUcpXXUA1u+GNUKoROi9byOJ8M0nHbHYHkYICiMlqxkg1KkYmm25Sw==",
	1810	+ "dev": true,
	1811	+ "license": "MIT",
	1812	+ "dependencies": {
	1813	+ "esbuild": "^0.21.3",
	1814	+ "postcss": "^8.4.43",
	1815	+ "rollup": "^4.20.0"
	1816	+ },
	1817	+ "bin": {
	1818	+ "vite": "bin/vite.js"
	1819	+ },
	1820	+ "engines": {
	1821	+ "node": "^18.0.0 \|\| >=20.0.0"
	1822	+ },
	1823	+ "funding": {
	1824	+ "url": "https://github.com/vitejs/vite?sponsor=1"
	1825	+ },
	1826	+ "optionalDependencies": {
	1827	+ "fsevents": "~2.3.3"
	1828	+ },
	1829	+ "peerDependencies": {
	1830	+ "@types/node": "^18.0.0 \|\| >=20.0.0",
	1831	+ "less": "*",
	1832	+ "lightningcss": "^1.21.0",
	1833	+ "sass": "*",
	1834	+ "sass-embedded": "*",
	1835	+ "stylus": "*",
	1836	+ "sugarss": "*",
	1837	+ "terser": "^5.4.0"
	1838	+ },
	1839	+ "peerDependenciesMeta": {
	1840	+ "@types/node": {
	1841	+ "optional": true
	1842	+ },
	1843	+ "less": {
	1844	+ "optional": true
	1845	+ },
	1846	+ "lightningcss": {
	1847	+ "optional": true
	1848	+ },
	1849	+ "sass": {
	1850	+ "optional": true
	1851	+ },
	1852	+ "sass-embedded": {
	1853	+ "optional": true
	1854	+ },
	1855	+ "stylus": {
	1856	+ "optional": true
	1857	+ },
	1858	+ "sugarss": {
	1859	+ "optional": true
	1860	+ },
	1861	+ "terser": {
	1862	+ "optional": true
	1863	+ }
	1864	+ }
	1865	+ },
	1866	+ "node_modules/yallist": {
	1867	+ "version": "3.1.1",
	1868	+ "resolved": "https://registry.npmjs.org/yallist/-/yallist-3.1.1.tgz",
	1869	+ "integrity": "sha512-a4UGQaWPH59mOXUYnAG2ewncQS4i4F43Tv3JoAM+s2VDAmS9NsK8GpDMLrCHPksFT7h3K6TOoUNn2pb7RoXx4g==",
	1870	+ "dev": true,
	1871	+ "license": "ISC"
	1872	+ }
	1873	+ }
	1874	+}

added frontend/package.json +26 −0

		`@@ -0,0 +1,26 @@`
	1	+{
	2	+ "name": "house-ka-frontend",
	3	+ "author": "Simon-Pierre Boucher <contact@spboucher.ai>",
	4	+ "private": true,
	5	+ "version": "1.0.0",
	6	+ "type": "module",
	7	+ "scripts": {
	8	+ "dev": "vite",
	9	+ "build": "tsc -b && vite build",
	10	+ "preview": "vite preview"
	11	+ },
	12	+ "dependencies": {
	13	+ "@groupe-ka/ka-maps": "file:../../ka-maps",
	14	+ "mapbox-gl": "^3.28.1",
	15	+ "react": "^18.3.1",
	16	+ "react-dom": "^18.3.1",
	17	+ "react-router-dom": "^6.26.0"
	18	+ },
	19	+ "devDependencies": {
	20	+ "@types/react": "^18.3.3",
	21	+ "@types/react-dom": "^18.3.0",
	22	+ "@vitejs/plugin-react": "^4.3.1",
	23	+ "typescript": "^5.5.4",
	24	+ "vite": "^5.4.0"
	25	+ }
	26	+}
		\ No newline at end of file

added frontend/public/apple-touch-icon.png +0 −0

Binary file not shown.

added frontend/public/favicon.svg +5 −0

		`@@ -0,0 +1,5 @@`
	1	+<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64">
	2	+ <rect x="2" y="2" width="60" height="60" rx="14" fill="#14201a"/>
	3	+ <path d="M14 30 32 14l18 16" fill="none" stroke="#0f6b4f" stroke-width="5" stroke-linecap="round" stroke-linejoin="round"/>
	4	+ <text x="32" y="52" text-anchor="middle" font-family="Georgia, 'Times New Roman', serif" font-weight="700" font-size="30" fill="#faf7f0">H</text>
	5	+</svg>

added frontend/public/og.png +0 −0

Binary file not shown.

added frontend/scripts/check-order.mjs +41 −0

		`@@ -0,0 +1,41 @@`
	1	+// Validation ordre des sections — fiche Immo-Ka (ordre DOM = ordre visuel)
	2	+import { chromium, devices } from "playwright";
	3	+
	4	+const BASE = process.env.BASE \|\| "http://localhost:18096";
	5	+const UID = process.argv[2];
	6	+const URL = `${BASE}/property/${encodeURIComponent(UID)}`;
	7	+const SEL = [".f-galerie", ".f-hero", ".f-desc", "#caracteristiques", "#pieces", "#inclusions", "#carte", ".quartier"];
	8	+
	9	+async function check(name, ctxOpts) {
	10	+ const browser = await chromium.launch();
	11	+ const ctx = await browser.newContext(ctxOpts);
	12	+ const page = await ctx.newPage();
	13	+ await page.goto(URL, { waitUntil: "networkidle" });
	14	+ await page.waitForSelector(".f-galerie", { timeout: 15000 });
	15	+ await page.waitForTimeout(1200);
	16	+ const data = await page.evaluate((sel) => {
	17	+ const out = [];
	18	+ for (const s of sel) {
	19	+ const el = document.querySelector(s);
	20	+ if (!el) { out.push({ s, missing: true }); continue; }
	21	+ const r = el.getBoundingClientRect();
	22	+ out.push({ s, hidden: r.height === 0 && r.width === 0, top: Math.round(r.top + window.scrollY), left: Math.round(r.left), order: getComputedStyle(el).order });
	23	+ }
	24	+ return { out, scrollY: window.scrollY };
	25	+ }, SEL);
	26	+ console.log(`\n=== ${name} === scrollY: ${data.scrollY}`);
	27	+ for (const b of data.out)
	28	+ console.log(b.missing ? `${b.s.padEnd(18)} (non rendue)` : b.hidden ? `${b.s.padEnd(18)} (vide/masquée)` :
	29	+ `${b.s.padEnd(18)} top=${String(b.top).padStart(6)} left=${String(b.left).padStart(4)} order=${b.order}`);
	30	+ await browser.close();
	31	+ return data;
	32	+}
	33	+
	34	+const mob = await check("iPhone 14 (mobile)", { ...devices["iPhone 14"] });
	35	+await check("Desktop 1440px", { viewport: { width: 1440, height: 900 } });
	36	+const vis = mob.out.filter(b => !b.missing && !b.hidden);
	37	+const sorted = vis.every((b, i) => i === 0 \|\| b.top >= vis[i - 1].top);
	38	+const ok = sorted && mob.scrollY === 0 && vis[0].s === ".f-galerie" && vis.every(b => b.order === "0");
	39	+console.log(`\nMOBILE: ordre ${sorted ? "CROISSANT ✓" : "DÉSORDONNÉ ✗"} · scrollY=${mob.scrollY} · 1re=${vis[0].s} · sans order=${vis.every(b => b.order === "0")}`);
	40	+console.log(ok ? "VALIDATION OK" : "VALIDATION ÉCHEC");
	41	+process.exit(ok ? 0 : 1);

added frontend/src/App.tsx +238 −0

		`@@ -0,0 +1,238 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	3	+// Author: Simon-Pierre Boucher — contact@spboucher.ai
	4	+// App.tsx : global layout (header + live ticker + footer) and routing.
	5	+// -----------------------------------------------------------------------------
	6	+import { Ico } from "./components/Icons";
	7	+import { useEffect, useState } from "react";
	8	+import { NavLink, Route, Routes, useLocation } from "react-router-dom";
	9	+import { fetchFacets, fetchSources, fetchStats, registerSourceNames, sourceName } from "./api";
	10	+import AgenciesPage from "./pages/Agencies";
	11	+import ContactPage from "./pages/Contact";
	12	+import Home from "./pages/Home";
	13	+import { PrivacyPage, TermsPage } from "./pages/Legal";
	14	+import ListingPage from "./pages/Listing";
	15	+import RatesPage from "./pages/Rates";
	16	+import StatsPage from "./pages/Stats";
	17	+
	18	+function Ticker() {
	19	+ const [items, setItems] = useState<string[]>([]);
	20	+
	21	+ useEffect(() => {
	22	+ Promise.all([fetchStats(), fetchFacets(), fetchSources()])
	23	+ .then(([stats, facets, src]) => {
	24	+ registerSourceNames(src.sources);
	25	+ const parts: string[] = [`${stats.total.toLocaleString("en-CA")} homes for sale`];
	26	+ if (stats.cities) parts.push(`${stats.cities.toLocaleString("en-CA")} cities & towns`);
	27	+ if (stats.avg_price != null)
	28	+ parts.push(`Average price $${Math.round(stats.avg_price).toLocaleString("en-CA")}`);
	29	+ for (const s of facets.sources.slice(0, 12))
	30	+ parts.push(`${sourceName(s.source)} · ${s.n.toLocaleString("en-CA")}`);
	31	+ parts.push("Continuously updated");
	32	+ setItems(parts);
	33	+ })
	34	+ .catch(() => setItems(["House-Ka — homes for sale across Canada"]));
	35	+ }, []);
	36	+
	37	+ if (items.length === 0) return null;
	38	+ return (
	39	+ <div className="ticker" aria-hidden="true">
	40	+ <div className="ticker-track">
	41	+ {[...items, ...items].map((t, i) => (
	42	+ <span key={i}>{t}</span>
	43	+ ))}
	44	+ </div>
	45	+ </div>
	46	+ );
	47	+}
	48	+
	49	+const NAV_LINKS = [
	50	+ { to: "/", label: "Homes", icon: "home", end: true },
	51	+ { to: "/?view=map", label: "Map", icon: "map", end: false, force: true },
	52	+ { to: "/rates", label: "Mortgage rates", icon: "trendup", end: false },
	53	+ { to: "/stats", label: "Stats", icon: "chart", end: false },
	54	+ { to: "/agencies", label: "Brokerages", icon: "building", end: false },
	55	+ { to: "/contact", label: "Contact", icon: "arrow", end: false },
	56	+];
	57	+
	58	+function Header() {
	59	+ const [open, setOpen] = useState(false);
	60	+ const location = useLocation();
	61	+
	62	+ useEffect(() => { setOpen(false); }, [location]);
	63	+ useEffect(() => {
	64	+ document.documentElement.classList.toggle("ka-scroll-lock", open);
	65	+ return () => { document.documentElement.classList.remove("ka-scroll-lock"); };
	66	+ }, [open]);
	67	+
	68	+ return (
	69	+ <>
	70	+ <header className="header">
	71	+ <div className="container header-inner">
	72	+ <NavLink to="/" className="brand" aria-label="House-Ka — home">
	73	+ House<span className="ka">Ka</span>
	74	+ </NavLink>
	75	+ <span className="brand-tag">A Groupe KA service</span>
	76	+ <nav className="nav" aria-label="Main navigation">
	77	+ <NavLink to="/" end className={({ isActive }) => (isActive ? "active" : "")}>
	78	+ Homes
	79	+ </NavLink>
	80	+ <NavLink to="/rates" className={({ isActive }) => (isActive ? "active" : "")}>
	81	+ Rates
	82	+ </NavLink>
	83	+ <NavLink to="/stats" className={({ isActive }) => (isActive ? "active" : "")}>
	84	+ Stats
	85	+ </NavLink>
	86	+ <NavLink to="/agencies" className={({ isActive }) => (isActive ? "active" : "")}>
	87	+ Brokerages
	88	+ </NavLink>
	89	+ <NavLink to="/contact" className={({ isActive }) => (isActive ? "active" : "")}>
	90	+ Contact
	91	+ </NavLink>
	92	+ </nav>
	93	+ <button
	94	+ className={`menu-btn ${open ? "open" : ""}`}
	95	+ aria-expanded={open}
	96	+ aria-label={open ? "Close the menu" : "Open the menu"}
	97	+ onClick={() => setOpen(!open)}
	98	+ >
	99	+ <span /><span /><span />
	100	+ </button>
	101	+ </div>
	102	+
	103	+ <div className={`mobile-menu ${open ? "open" : ""}`} role="navigation" aria-label="Mobile menu">
	104	+ {/* fixed ✕ of the panel: visible regardless of scroll; the header
	105	+ burger is hidden while the panel is open */}
	106	+ <button type="button" className="mm-close" aria-label="Close the menu"
	107	+ onClick={() => setOpen(false)}>✕</button>
	108	+ {NAV_LINKS.map((l, i) => (
	109	+ <NavLink
	110	+ key={l.to}
	111	+ to={l.to}
	112	+ end={l.end}
	113	+ style={{ transitionDelay: open ? `${60 + i * 45}ms` : "0ms" }}
	114	+ className={({ isActive }) => `mm-link ${isActive && !l.force ? "active" : ""}`}
	115	+ onClick={() => setOpen(false)}
	116	+ >
	117	+ <span className="mm-ico" aria-hidden="true"><Ico name={l.icon} size={19} /></span>
	118	+ {l.label}
	119	+ <span className="mm-arrow" aria-hidden="true"><Ico name="arrow" size={15} /></span>
	120	+ </NavLink>
	121	+ ))}
	122	+ <div className="mm-foot">
	123	+ <p>
	124	+ Independent aggregator — continuously updated, every listing links
	125	+ back to the brokerage's original page.
	126	+ </p>
	127	+ </div>
	128	+ </div>
	129	+ </header>
	130	+ {open && <div className="mm-backdrop" onClick={() => setOpen(false)} aria-hidden="true" />}
	131	+ <Ticker />
	132	+ </>
	133	+ );
	134	+}
	135	+
	136	+/** Bottom navigation bar (mobile) — floating pill detached from the edges,
	137	+ accent underline below the active tab. */
	138	+function MobileTabBar() {
	139	+ const location = useLocation();
	140	+ const isMap = new URLSearchParams(location.search).get("view") === "map";
	141	+ const tabs = [
	142	+ { to: "/", label: "Discover", icon: <Ico name="search" size={20} stroke={1.6} />, on: location.pathname === "/" && !isMap },
	143	+ { to: "/?view=map", label: "Map", icon: <Ico name="map" size={20} stroke={1.6} />, on: location.pathname === "/" && isMap },
	144	+ { to: "/rates", label: "Rates", icon: <Ico name="trendup" size={20} stroke={1.6} />, on: location.pathname.startsWith("/rates") },
	145	+ { to: "/stats", label: "Stats", icon: <Ico name="chart" size={20} stroke={1.6} />, on: location.pathname.startsWith("/stats") },
	146	+ ];
	147	+ return (
	148	+ <nav className="tabbar" aria-label="Mobile navigation">
	149	+ {tabs.map((t) => (
	150	+ <NavLink key={t.label} to={t.to} className={() => (t.on ? "active" : "")}>
	151	+ {t.icon}
	152	+ {t.label}
	153	+ </NavLink>
	154	+ ))}
	155	+ </nav>
	156	+ );
	157	+}
	158	+
	159	+/** House-Ka footer — ink panel, Groupe KA credit + sister sites. */
	160	+function Footer() {
	161	+ const year = new Date().getFullYear();
	162	+ const sisters = [
	163	+ { name: "Groupe·Ka", url: "https://www.groupe-ka.com", note: "the Groupe KA portal" },
	164	+ { name: "Immo·Ka", url: "https://www.immo-ka.com", note: "homes for sale in Québec" },
	165	+ { name: "Lou·Ka", url: "https://www.lou-ka.com", note: "rentals in Québec" },
	166	+ { name: "Vrai·Prix", url: "https://www.vrai-prix.com", note: "Québec market-value estimates" },
	167	+ ];
	168	+ return (
	169	+ <footer className="hk-footer" id="contact">
	170	+ <div className="container">
	171	+ <div className="hk-foot-brand">House<span className="ka">Ka</span></div>
	172	+ <p className="hk-foot-desc">
	173	+ House-Ka continuously aggregates homes for sale publicly listed by
	174	+ Canadian real-estate brokerages and teams on the CREA DDF feed —
	175	+ starting with Ontario and growing across the rest of Canada. Every
	176	+ listing links back to the brokerage's original page. House-Ka is a
	177	+ service of <b>Groupe KA</b>.
	178	+ </p>
	179	+ <p className="hk-foot-notice">
	180	+ House-Ka is an independent aggregator: it is not a brokerage, does not
	181	+ represent buyers or sellers, and is not affiliated with the sources it
	182	+ indexes. Prices and availability are those displayed by each source.
	183	+ </p>
	184	+ <ul className="hk-foot-sites">
	185	+ {sisters.map((s) => (
	186	+ <li key={s.url}>
	187	+ <a href={s.url} target="_blank" rel="noopener noreferrer">
	188	+ {s.name}
	189	+ </a>
	190	+ <span>{s.note}</span>
	191	+ </li>
	192	+ ))}
	193	+ </ul>
	194	+ <div className="hk-foot-legal">
	195	+ <a href="/terms">Terms of use</a>
	196	+ <a href="/privacy">Privacy</a>
	197	+ <a href="/contact">Contact</a>
	198	+ <span>© {year} Groupe-Ka</span>
	199	+ </div>
	200	+ </div>
	201	+ </footer>
	202	+ );
	203	+}
	204	+
	205	+export default function App() {
	206	+ return (
	207	+ <>
	208	+ <Header />
	209	+ <main>
	210	+ <Routes>
	211	+ <Route path="/" element={<Home />} />
	212	+ <Route path="/property/:uid" element={<ListingPage />} />
	213	+ {/* canonical SEO URL: /property/{uid}/{slug} (server 301) — without
	214	+ this route any shared/direct link would land on the 404 page */}
	215	+ <Route path="/property/:uid/:slug" element={<ListingPage />} />
	216	+ <Route path="/stats" element={<StatsPage />} />
	217	+ <Route path="/rates" element={<RatesPage />} />
	218	+ <Route path="/agencies" element={<AgenciesPage />} />
	219	+ <Route path="/contact" element={<ContactPage />} />
	220	+ <Route path="/terms" element={<TermsPage />} />
	221	+ <Route path="/privacy" element={<PrivacyPage />} />
	222	+ <Route
	223	+ path="*"
	224	+ element={
	225	+ <div className="notice container">
	226	+ <div className="big">🧭</div>
	227	+ <h2>Page not found</h2>
	228	+ <p>The requested link does not exist.</p>
	229	+ </div>
	230	+ }
	231	+ />
	232	+ </Routes>
	233	+ </main>
	234	+ <MobileTabBar />
	235	+ <Footer />
	236	+ </>
	237	+ );
	238	+}

added frontend/src/api.ts +383 −0

		`@@ -0,0 +1,383 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	3	+// Author: Simon-Pierre Boucher — contact@spboucher.ai
	4	+// api.ts : types + robust API client (timeout, typed errors)
	5	+// -----------------------------------------------------------------------------
	6	+
	7	+export interface Room {
	8	+ nom?: string;
	9	+ niveau?: string;
	10	+ dimensions?: string;
	11	+ revetement?: string;
	12	+}
	13	+
	14	+/** details: free-form dictionary of DDF fields (label → value), with the
	15	+ * special keys `pieces` (rooms) and `photo_captions`. */
	16	+export interface ListingDetails {
	17	+ pieces?: Room[];
	18	+ price_from?: boolean;
	19	+ [key: string]: unknown;
	20	+}
	21	+
	22	+export interface Listing {
	23	+ uid: string;
	24	+ source: string;
	25	+ external_id: string;
	26	+ url: string;
	27	+ title: string;
	28	+ address: string;
	29	+ sector: string;
	30	+ city: string;
	31	+ region: string;
	32	+ property_type: string;
	33	+ price: number \| null;
	34	+ price_label: string;
	35	+ bedrooms: number \| null;
	36	+ bathrooms: number \| null;
	37	+ powder_rooms: number \| null;
	38	+ area_sqft: number \| null;
	39	+ lot_sqft: number \| null;
	40	+ year_built: number \| null;
	41	+ mls: string;
	42	+ status: string;
	43	+ broker_name: string;
	44	+ broker_phone: string;
	45	+ description: string;
	46	+ features: string[];
	47	+ details: ListingDetails;
	48	+ images: string[];
	49	+ lat: number \| null;
	50	+ lng: number \| null;
	51	+ price_history?: { ts: number; price: number \| null }[];
	52	+ duplicates?: DuplicateListing[]; // other publications of the same property
	53	+ poi?: Poi[]; // nearby amenities (listing page only)
	54	+ first_seen?: number;
	55	+ last_seen?: number;
	56	+ updated_at?: number;
	57	+ active?: number;
	58	+ days_on_market?: number;
	59	+}
	60	+
	61	+export interface DuplicateListing {
	62	+ uid: string;
	63	+ source: string;
	64	+ url: string;
	65	+ broker_name: string;
	66	+ agency: string;
	67	+ price_label: string;
	68	+}
	69	+
	70	+export interface Poi { cat: string; name: string; dist_m: number }
	71	+
	72	+export interface Facets {
	73	+ cities: string[];
	74	+ sectors: string[];
	75	+ property_types: string[];
	76	+ sources: { source: string; n: number }[];
	77	+}
	78	+
	79	+export interface Source {
	80	+ id: string;
	81	+ name: string;
	82	+ url: string;
	83	+ listing_url?: string;
	84	+ coverage?: string;
	85	+ type?: string;
	86	+ connector?: string \| null;
	87	+ status: string;
	88	+ active_listings: number;
	89	+ last_sync: number \| null;
	90	+}
	91	+
	92	+export interface Stats {
	93	+ total: number;
	94	+ sources: number;
	95	+ cities: number;
	96	+ avg_price: number \| null;
	97	+ min_price: number \| null;
	98	+ max_price: number \| null;
	99	+ recent_syncs?: {
	100	+ source: string; ts: number; found: number; added: number;
	101	+ updated: number; removed: number; ok: number; message: string;
	102	+ }[];
	103	+ qualite?: Quality;
	104	+}
	105	+
	106	+/** Data quality (completeness, quarantine, anomalies) — immoka/quality.py */
	107	+export interface Quality {
	108	+ actives: number;
	109	+ publiees: number;
	110	+ quarantaine: number;
	111	+ completude_moyenne: number \| null;
	112	+ anomalies: Record<string, number>;
	113	+ par_source: {
	114	+ source: string; n: number; publiees: number;
	115	+ completude: number \| null; anomalies: number;
	116	+ }[];
	117	+}
	118	+
	119	+// --- Source names (pretty labels) --------------------------------------------
	120	+const SOURCE_NAMES: Record<string, string> = {};
	121	+export function registerSourceNames(sources: Source[]) {
	122	+ for (const s of sources) SOURCE_NAMES[s.id] = s.name;
	123	+}
	124	+export function sourceName(id: string): string {
	125	+ if (SOURCE_NAMES[id]) return SOURCE_NAMES[id];
	126	+ // readable fallback for generated RealtyPress sources (rp_ag_xxx)
	127	+ const base = id.replace(/^rp_ag_/, "").replace(/^rp_/, "");
	128	+ return base.replace(/_/g, " ").replace(/\b\w/g, (c) => c.toUpperCase());
	129	+}
	130	+
	131	+async function get<T>(path: string): Promise<T> {
	132	+ const ctrl = new AbortController();
	133	+ const timer = setTimeout(() => ctrl.abort(), 25000);
	134	+ try {
	135	+ const res = await fetch(path, { signal: ctrl.signal });
	136	+ if (!res.ok) throw new Error(`API ${res.status} — ${path}`);
	137	+ return (await res.json()) as T;
	138	+ } finally {
	139	+ clearTimeout(timer);
	140	+ }
	141	+}
	142	+
	143	+export interface ListingFilters {
	144	+ city?: string;
	145	+ sector?: string;
	146	+ region?: string;
	147	+ property_type?: string;
	148	+ source?: string;
	149	+ price_min?: string;
	150	+ price_max?: string;
	151	+ bedrooms_min?: string;
	152	+ bathrooms_min?: string;
	153	+ area_min?: string;
	154	+ q?: string;
	155	+ sort?: string; // price_asc \| price_desc \| recent
	156	+}
	157	+
	158	+export function listingParams(f: ListingFilters): URLSearchParams {
	159	+ const params = new URLSearchParams();
	160	+ for (const [k, v] of Object.entries(f)) if (v) params.set(k, v);
	161	+ return params;
	162	+}
	163	+
	164	+export function fetchListings(f: ListingFilters, limit = 60, offset = 0) {
	165	+ const params = listingParams(f);
	166	+ params.set("limit", String(limit));
	167	+ params.set("offset", String(offset));
	168	+ return get<{ total: number; count: number; listings: Listing[] }>(
	169	+ `/api/listings?${params}`);
	170	+}
	171	+
	172	+export const fetchListing = (uid: string) =>
	173	+ get<Listing>(`/api/listings/${encodeURIComponent(uid)}`);
	174	+export const fetchFacets = (city?: string) =>
	175	+ get<Facets>(`/api/facets${city ? `?city=${encodeURIComponent(city)}` : ""}`);
	176	+export const fetchSources = () => get<{ sources: Source[] }>("/api/sources");
	177	+export const fetchStats = () => get<Stats>("/api/stats");
	178	+
	179	+export interface SubAgency { name: string; count: number; sources: string[] }
	180	+export interface Franchise {
	181	+ franchise: string;
	182	+ total: number;
	183	+ sub_agencies: number;
	184	+ agencies: SubAgency[];
	185	+}
	186	+export const fetchAgencies = () =>
	187	+ get<{ franchises: Franchise[] }>("/api/agencies");
	188	+
	189	+// --- Formatting ---------------------------------------------------------------
	190	+export const fmtPrice = (p: number \| null, label?: string) =>
	191	+ p != null
	192	+ ? "$" + p.toLocaleString("en-CA", { maximumFractionDigits: 0 })
	193	+ : label \|\| "Price on request";
	194	+
	195	+export const fmtArea = (a: number \| null): string \| null =>
	196	+ a != null ? `${Math.round(a).toLocaleString("en-CA")} sq ft` : null;
	197	+
	198	+export const fmtDate = (ts: number): string =>
	199	+ new Date(ts * 1000).toLocaleDateString("en-CA", {
	200	+ day: "numeric", month: "long", year: "numeric",
	201	+ });
	202	+
	203	+/** 250 -> "250 m", 1240 -> "1.2 km" */
	204	+export const fmtDist = (m: number): string =>
	205	+ m < 1000 ? `${Math.round(m / 10) * 10} m` : `${(m / 1000).toFixed(1)} km`;
	206	+
	207	+// -----------------------------------------------------------------------------
	208	+// Mortgage rates (immoka/mortgage) — real rates observed at the banks
	209	+// -----------------------------------------------------------------------------
	210	+export interface MortgageRate {
	211	+ provider: string;
	212	+ institution: string;
	213	+ product_key: string;
	214	+ product_name: string \| null;
	215	+ rate_type: "fixed" \| "variable" \| "adjustable" \| "other";
	216	+ term_months: number;
	217	+ kind: "posted" \| "special";
	218	+ rate: number;
	219	+ apr: number \| null;
	220	+ insured_status: "insured" \| "insurable" \| "uninsured" \| "unknown";
	221	+ purpose: string;
	222	+ conditions: string \| null;
	223	+ source_url: string \| null;
	224	+ last_checked: number;
	225	+ age_minutes: number;
	226	+ stale: boolean;
	227	+}
	228	+
	229	+export interface MortgageBest extends MortgageRate {
	230	+ median_rate: number \| null;
	231	+ institutions_count: number;
	232	+ per_institution: MortgageRate[];
	233	+}
	234	+
	235	+export interface MortgageMarket {
	236	+ rate_type: string;
	237	+ term_months: number;
	238	+ best: number;
	239	+ best_provider: string;
	240	+ best_institution: string;
	241	+ best_kind: string;
	242	+ median: number \| null;
	243	+ spread: number \| null;
	244	+ institutions_count: number;
	245	+ var_7d: number \| null;
	246	+ var_30d: number \| null;
	247	+ var_90d: number \| null;
	248	+ lowest_6m: number \| null;
	249	+}
	250	+
	251	+export interface MortgageIntelligence {
	252	+ products: MortgageMarket[];
	253	+ prime_rates: { institution: string; rate: number; product_name: string;
	254	+ age_minutes: number }[];
	255	+}
	256	+
	257	+export interface MortgageHistoryRow {
	258	+ provider: string; institution: string; product_name: string \| null;
	259	+ kind: string; rate: number; insured_status: string;
	260	+ valid_from: number; valid_to: number \| null; last_checked: number;
	261	+ source_url: string \| null;
	262	+}
	263	+
	264	+export interface MortgageProviderHealth {
	265	+ provider: string; institution: string; source_url: string \| null;
	266	+ level: "OK" \| "WARNING" \| "ERROR"; status: string \| null;
	267	+ age_minutes: number; current_products: number; last_data_at: number \| null;
	268	+}
	269	+
	270	+export interface MortgageRateSource {
	271	+ provider: string; institution: string; product_name: string \| null;
	272	+ kind: string; rate: number; apr?: number \| null; insured_status?: string;
	273	+ source_url: string \| null; last_checked?: number;
	274	+ age_minutes: number; stale: boolean;
	275	+}
	276	+
	277	+export interface MortgageInsurance {
	278	+ required: boolean; eligible: boolean; premium: number; premium_rate: number;
	279	+ loan_before: number; total_mortgage: number; qc_tax: number;
	280	+ ltv: number \| null; issues: string[];
	281	+}
	282	+
	283	+export interface MortgageCalc {
	284	+ inputs: {
	285	+ price: number; down_payment: number; down_payment_pct: number;
	286	+ rate: number; rate_type: string; term_months: number;
	287	+ amortization_years: number; frequency: string; compounding: string;
	288	+ };
	289	+ insurance: MortgageInsurance;
	290	+ principal: number;
	291	+ payment: number;
	292	+ payment_monthly_equivalent: number;
	293	+ qualifying: { rate: number; payment: number; note: string };
	294	+ term: {
	295	+ payment: number; frequency: string; payments_per_year: number;
	296	+ payments_in_term: number; annual_cost: number; principal_paid: number;
	297	+ interest_paid: number; balance_end_of_term: number; paid_off: boolean;
	298	+ };
	299	+ stress: { bump: number; rate: number; payment: number }[];
	300	+ renewal: {
	301	+ balance_at_renewal: number; remaining_amortization_years: number;
	302	+ scenarios: { bump: number; rate: number; payment: number }[];
	303	+ };
	304	+ payoff_years: number;
	305	+ rate_source: MortgageRateSource \| null;
	306	+ annual: { year: number; payment: number; interest: number;
	307	+ principal: number; balance: number }[];
	308	+ ratios?: { gds: number \| null; tds: number \| null;
	309	+ gds_ok: boolean \| null; tds_ok: boolean \| null };
	310	+}
	311	+
	312	+export interface MortgageCalcInput {
	313	+ price: number;
	314	+ down_payment?: number;
	315	+ down_payment_pct?: number;
	316	+ amortization_years?: number;
	317	+ term_months?: number;
	318	+ frequency?: string;
	319	+ rate_type?: "fixed" \| "variable";
	320	+ rate?: number;
	321	+ income?: number;
	322	+ property_tax_monthly?: number;
	323	+ heating_monthly?: number;
	324	+ condo_fees_monthly?: number;
	325	+ other_debts_monthly?: number;
	326	+}
	327	+
	328	+async function post<T>(path: string, body: unknown): Promise<T> {
	329	+ const ctrl = new AbortController();
	330	+ const timer = setTimeout(() => ctrl.abort(), 25000);
	331	+ try {
	332	+ const res = await fetch(path, {
	333	+ method: "POST",
	334	+ headers: { "Content-Type": "application/json" },
	335	+ body: JSON.stringify(body),
	336	+ signal: ctrl.signal,
	337	+ });
	338	+ if (!res.ok) throw new Error(`API ${res.status} — ${path}`);
	339	+ return (await res.json()) as T;
	340	+ } finally {
	341	+ clearTimeout(timer);
	342	+ }
	343	+}
	344	+
	345	+export const fetchMortgageIntelligence = () =>
	346	+ get<MortgageIntelligence>("/api/mortgage/intelligence");
	347	+
	348	+export const fetchMortgageBest = (rateType: string, termMonths: number) =>
	349	+ get<MortgageBest>(
	350	+ `/api/mortgage/rates/best?rate_type=${rateType}&term_months=${termMonths}`);
	351	+
	352	+export const fetchMortgageHistory = (
	353	+ rateType: string, termMonths: number, days = 365, kind?: string,
	354	+) =>
	355	+ get<{ count: number; days: number; history: MortgageHistoryRow[] }>(
	356	+ `/api/mortgage/rates/history?rate_type=${rateType}` +
	357	+ `&term_months=${termMonths}&days=${days}${kind ? `&kind=${kind}` : ""}`);
	358	+
	359	+export const fetchMortgageProviders = () =>
	360	+ get<{ providers: MortgageProviderHealth[]; registered: string[] }>(
	361	+ "/api/mortgage/providers");
	362	+
	363	+export const calculateMortgage = (input: MortgageCalcInput) =>
	364	+ post<MortgageCalc>("/api/mortgage/calculate", input);
	365	+
	366	+/** 4.19 -> "4.19%" */
	367	+export const fmtRate = (r: number \| null \| undefined): string =>
	368	+ r == null ? "—" : `${r.toFixed(2)}%`;
	369	+
	370	+// -----------------------------------------------------------------------------
	371	+// Nearby places (Mapbox Search Box + OSM) — listing page block
	372	+// -----------------------------------------------------------------------------
	373	+export interface CommerceItem {
	374	+ id: string; commerce: string; nom: string; adresse: string;
	375	+ dist_m: number; lat: number; lng: number;
	376	+}
	377	+
	378	+export interface CommercesNearby {
	379	+ n: number; commerces: CommerceItem[]; transit?: CommerceItem[];
	380	+}
	381	+
	382	+export const fetchCommerces = (lat: number, lng: number) =>
	383	+ get<CommercesNearby>(`/api/commerces?lat=${lat}&lng=${lng}`);

added frontend/src/components/AmenityIco.tsx +112 −0

		`@@ -0,0 +1,112 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// Groupe KA — composant partagé (lou-ka / immo-ka)
	3	+// components/AmenityIco.tsx : icône contextuelle d'une commodité ou inclusion.
	4	+// Fini l'icône unique répétée dix fois : chaque libellé est associé par
	5	+// mots-clés (accents neutralisés) à l'un des ~30 pictos maison — trait 1.8,
	6	+// 24×24, currentColor. Repli : ✓ (confirmé) ou étoile (mention libre).
	7	+// -----------------------------------------------------------------------------
	8	+import { ReactNode } from "react";
	9	+
	10	+const ICONS: Record<string, ReactNode> = {
	11	+ heat: (<><rect x="4" y="9" width="16" height="9" rx="2" /><path d="M8 9v9M12 9v9M16 9v9M7.6 3.5c0 1.6 1.2 1.6 1.2 3.2M11.4 3.5c0 1.6 1.2 1.6 1.2 3.2M15.2 3.5c0 1.6 1.2 1.6 1.2 3.2" /></>),
	12	+ bolt: <path d="M13 2.5 4.5 13.5H11l-1.5 8 8.5-11H11.5l1.5-8z" />,
	13	+ droplet: (<><path d="M12 3.5S6.2 9.8 6.2 13.6a5.8 5.8 0 0 0 11.6 0C17.8 9.8 12 3.5 12 3.5z" /><path d="M9.4 14a2.7 2.7 0 0 0 2.1 2.6" /></>),
	14	+ wifi: <path d="M3.5 9.5a13 13 0 0 1 17 0M6.5 13a8.5 8.5 0 0 1 11 0M9.5 16.4a4.4 4.4 0 0 1 5 0M12 19.6h.01" />,
	15	+ dishwasher: (<><rect x="4.5" y="3" width="15" height="18" rx="2" /><path d="M4.5 8.5h15M8 12.5V17M12 12.5V17M16 12.5V17M7.5 5.7h.01M10.5 5.7h.01" /></>),
	16	+ washer: (<><rect x="4.5" y="3" width="15" height="18" rx="2" /><circle cx="12" cy="14" r="4.2" /><path d="M4.5 7.5h15M16.4 5.2h.01M9.2 14c1 .8 1.9.8 2.8 0s1.9-.8 2.8 0" /></>),
	17	+ fridge: (<><rect x="6.5" y="2.5" width="11" height="19" rx="2" /><path d="M6.5 9.5h11M9.5 5.5v2M9.5 12.5V16" /></>),
	18	+ snow: <path d="M12 2.5v19M3.8 7.25l16.4 9.5M20.2 7.25 3.8 16.75" />,
	19	+ elevator: (<><rect x="4.5" y="3" width="15" height="18" rx="2" /><path d="M12 3v18M7 11l1.5-1.8L10 11M14 13l1.5 1.8L17 13" /></>),
	20	+ balcony: <path d="M4 11.5h16M5 11.5V20M19 11.5V20M9.5 11.5V20M14.5 11.5V20M4 20h16M7 11.5V6.5a5 5 0 0 1 10 0v5" />,
	21	+ pool: <path d="M9 4.5v9M13.5 4.5v9M9 7.5h4.5M3 16.5c1.5 1.3 3 1.3 4.5 0s3-1.3 4.5 0 3 1.3 4.5 0 3-1.3 4.5 0M3 20c1.5 1.3 3 1.3 4.5 0s3-1.3 4.5 0 3 1.3 4.5 0 3-1.3 4.5 0" />,
	22	+ gym: <path d="M6.7 6.7v10.6M17.3 6.7v10.6M3.5 9.2v5.6M20.5 9.2v5.6M6.7 12h10.6" />,
	23	+ laundry: <path d="M4 9.5h16l-1.8 10a1.8 1.8 0 0 1-1.8 1.5H7.6a1.8 1.8 0 0 1-1.8-1.5zM8 9.5 12 3l4 6.5M9.3 13.5v3.5M12 13.5v3.5M14.7 13.5v3.5" />,
	24	+ box: <path d="M3.5 8 12 3.5 20.5 8v8L12 20.5 3.5 16zM3.5 8 12 12.5 20.5 8M12 12.5v8" />,
	25	+ parking: (<><rect x="3.5" y="3.5" width="17" height="17" rx="3.5" /><path d="M9.5 16.5v-9H13a2.9 2.9 0 0 1 0 5.8H9.5" /></>),
	26	+ garage: <path d="M3.5 20V9.5L12 4l8.5 5.5V20M7 20v-6.5h10V20M7 16.8h10" />,
	27	+ sofa: <path d="M5.5 11V8.8A2.8 2.8 0 0 1 8.3 6h7.4a2.8 2.8 0 0 1 2.8 2.8V11M3.5 13.7a2.2 2.2 0 0 1 4.4 0v1h8.2v-1a2.2 2.2 0 0 1 4.4 0V17.5h-17zM5.5 17.5v1.8M18.5 17.5v1.8" />,
	28	+ nosmoke: <path d="M4 4l16 16M14.5 13H4v3h6.5M17.5 13H20v3h-1" />,
	29	+ paw: (<><circle cx="8.2" cy="7.8" r="1.7" /><circle cx="15.8" cy="7.8" r="1.7" /><circle cx="4.8" cy="12" r="1.6" /><circle cx="19.2" cy="12" r="1.6" /><path d="M12 11c2.8 0 5.2 2.3 5.2 4.8 0 1.8-1.4 3-3.2 3-.8 0-1.3-.3-2-.3s-1.2.3-2 .3c-1.8 0-3.2-1.2-3.2-3C6.8 13.3 9.2 11 12 11z" /></>),
	30	+ fire: (<><path d="M4 4.5h16M5.5 4.5V19.5M18.5 4.5V19.5M4 19.5h16" /><path d="M12 8.5c-1.8 2-3 3.4-3 5.3a3 3 0 0 0 6 0c0-1.9-1.2-3.3-3-5.3z" /></>),
	31	+ tree: <path d="M12 3 7.2 9.5h2.4L5.5 15.5h13L14.4 9.5h2.4zM12 15.5V21" />,
	32	+ spa: <path d="M8 3.5c0 1.7-1.4 2-1.4 3.7S8 9.5 8 11M12.5 3.5c0 1.7-1.4 2-1.4 3.7s1.4 2.3 1.4 3.8M17 3.5c0 1.7-1.4 2-1.4 3.7S17 9.5 17 11M3.5 15.5c1.4 1.3 2.8 1.3 4.2 0s2.9-1.3 4.3 0 2.8 1.3 4.2 0 2.9-1.3 4.3 0M3.5 19.5c1.4 1.3 2.8 1.3 4.2 0s2.9-1.3 4.3 0 2.8 1.3 4.2 0 2.9-1.3 4.3 0" />,
	33	+ shield: (<><path d="M12 3 5 6v5.5c0 4.4 3 7.6 7 9.5 4-1.9 7-5.1 7-9.5V6z" /><path d="m9 11.5 2.2 2.2L15.5 9" /></>),
	34	+ eye: (<><path d="M2.5 12S6.3 5.8 12 5.8 21.5 12 21.5 12 17.7 18.2 12 18.2 2.5 12 2.5 12z" /><circle cx="12" cy="12" r="2.8" /></>),
	35	+ waves: <path d="M3 9c1.5 1.3 3 1.3 4.5 0s3-1.3 4.5 0 3 1.3 4.5 0 3-1.3 4.5 0M3 14c1.5 1.3 3 1.3 4.5 0s3-1.3 4.5 0 3 1.3 4.5 0 3-1.3 4.5 0M3 19c1.5 1.3 3 1.3 4.5 0s3-1.3 4.5 0 3 1.3 4.5 0 3-1.3 4.5 0" />,
	36	+ calendar: (<><rect x="4" y="5" width="16" height="16" rx="2" /><path d="M4 10h16M8.5 3v4M15.5 3v4M8 14h.01M12 14h.01M16 14h.01" /></>),
	37	+ ruler: <path d="M3.5 16.2 16.2 3.5l4.3 4.3L7.8 20.5zM7.8 15.9l1.8 1.8M10.6 13.1l1.8 1.8M13.4 10.3l1.8 1.8M16.2 7.5 18 9.3" />,
	38	+ bed: <path d="M3.5 18V6.5M3.5 13.5h17V18M3.5 10h6.5v3.5M20.5 13.5v-1a3 3 0 0 0-3-3H10" />,
	39	+ bath: <path d="M4 12.5h16v1.7a4.8 4.8 0 0 1-4.8 4.8H8.8A4.8 4.8 0 0 1 4 14.2zM6 12.5V6a2.5 2.5 0 0 1 4.6-1.3M7 19l-1 1.8M17 19l1 1.8" />,
	40	+ people: (<><circle cx="9" cy="8" r="3.2" /><path d="M3.5 20.5c0-3.1 2.4-5.2 5.5-5.2s5.5 2.1 5.5 5.2M15.5 5.4a3.2 3.2 0 0 1 0 5.2M20.5 20.5c0-2.7-1.8-4.6-4.3-5.1" /></>),
	41	+ stairs: <path d="M3.5 20.5h4.2v-4.2h4.2v-4.2h4.2V7.9h4.4" />,
	42	+ door: (<><rect x="6" y="3" width="12" height="18" rx="1.5" /><path d="M14.8 12h.01M4 21h16" /></>),
	43	+ home: <path d="m3.5 11 8.5-7 8.5 7M6 9.5V20h12V9.5" />,
	44	+ sun: (<><circle cx="12" cy="12" r="4" /><path d="M12 2.5v2.5M12 19v2.5M2.5 12H5M19 12h2.5M5.3 5.3l1.8 1.8M16.9 16.9l1.8 1.8M18.7 5.3l-1.8 1.8M7.1 16.9l-1.8 1.8" /></>),
	45	+ check: <path d="m4.5 12.5 5.3 5.3L19.5 6.5" />,
	46	+ spark: <path d="M12 3.5 13.9 10l6.6 2-6.6 2L12 20.5 10.1 14l-6.6-2 6.6-2z" />,
	47	+};
	48	+
	49	+/** [motif (sur libellé minuscule sans accents), clé d'icône] — ordre = priorité */
	50	+const RULES: [RegExp, string][] = [
	51	+ [/lave-?vaisselle/, "dishwasher"],
	52	+ [/laveuse\|secheuse\|lessive/, "washer"],
	53	+ [/buanderie/, "laundry"],
	54	+ [/electromenager\|frigo\|refrigerateur\|cuisiniere\|four incl\|poele/, "fridge"],
	55	+ [/climatis\|air clim\|thermopompe\|echangeur d.air\|\ba\/?c\b/, "snow"],
	56	+ [/chauff/, "heat"],
	57	+ [/eau chaude/, "droplet"],
	58	+ [/electric\|eclair\|hydro/, "bolt"],
	59	+ [/internet\|wi-?fi\|cablodistribution\|\bcable\b\|fibre/, "wifi"],
	60	+ [/ascenseur/, "elevator"],
	61	+ [/balcon\|terrasse\|patio\|loggia\|veranda/, "balcony"],
	62	+ [/piscine/, "pool"],
	63	+ [/gym\|salle d.entrainement\|exercice/, "gym"],
	64	+ [/rangement\|locker\|entreposage\|walk-?in\|penderie/, "box"],
	65	+ [/garage/, "garage"],
	66	+ [/stationnement\|parking\|abri d.auto/, "parking"],
	67	+ [/meuble/, "sofa"],
	68	+ [/non-?fumeur\|sans fumee/, "nosmoke"],
	69	+ [/animau\|chat\|chien\|\bpet\b/, "paw"],
	70	+ [/foyer\|cheminee\|poele a bois/, "fire"],
	71	+ [/spa\b\|jacuzzi\|sauna\|bain tourbillon/, "spa"],
	72	+ [/securite\|surveill\|camera\|alarme\|interphone\|concierge\|portier/, "shield"],
	73	+ [/\bvue\b\|panoram/, "eye"],
	74	+ [/bord de l.eau\|acces au lac\|\blac\b\|riviere\|plage\|navigable/, "waves"],
	75	+ [/cour\|jardin\|arbre\|boise\|verdure\|gazon\|amenagement paysager/, "tree"],
	76	+ [/ensoleill\|luminosite\|lumineux\|solarium/, "sun"],
	77	+ [/dispo\|libre \|libre$/, "calendar"],
	78	+ [/pi2\|pieds carres\|superficie\|\bm2\b/, "ruler"],
	79	+ [/chambre/, "bed"],
	80	+ [/salle[s]? de bain\|salle[s]? d.eau\|douche\|\bsdb\b/, "bath"],
	81	+ [/occupant\|personne\|colocataire/, "people"],
	82	+ [/etage\|niveau\|escalier\|mezzanine/, "stairs"],
	83	+ [/studio\|loft\|(^\|\s)\d ?1\/2\|½/, "door"],
	84	+ [/maison\|plain-?pied\|unifamiliale/, "home"],
	85	+ [/egout\|septique\|fosse/, "waves"],
	86	+ [/aqueduc\|approvisionnement en eau\|puits/, "droplet"],
	87	+ [/construction\|neuve\|fondation\|toiture\|revetement\|renov/, "home"],
	88	+ [/commerce\|zonage\|usage/, "box"],
	89	+];
	90	+
	91	+/** minuscules + accents neutralisés, pour un appariement robuste */
	92	+const norm = (s: string) =>
	93	+ s.toLowerCase().normalize("NFD").replace(/[\u0300-\u036f]/g, "");
	94	+
	95	+export function amenityKey(label: string, fallback = "check"): string {
	96	+ const n = norm(label);
	97	+ for (const [re, key] of RULES) if (re.test(n)) return key;
	98	+ return fallback;
	99	+}
	100	+
	101	+export default function AmenityIco({ label, size = 16, fallback = "check" }:
	102	+ { label: string; size?: number; fallback?: string }) {
	103	+ return (
	104	+ <svg
	105	+ width={size} height={size} viewBox="0 0 24 24" aria-hidden="true"
	106	+ fill="none" stroke="currentColor" strokeWidth={1.8}
	107	+ strokeLinecap="round" strokeLinejoin="round"
	108	+ >
	109	+ {ICONS[amenityKey(label, fallback)] ?? ICONS.check}
	110	+ </svg>
	111	+ );
	112	+}

added frontend/src/components/Financing.tsx +369 −0

		`@@ -0,0 +1,369 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	3	+// Author: Simon-Pierre Boucher — contact@spboucher.ai
	4	+// components/Financing.tsx : “Finance this home” (listing page) —
	5	+// Canadian mortgage calculator plugged into the REAL observed rates
	6	+// (immoka/mortgage). Semi-annual compounding for fixed rates, CMHC shown
	7	+// separately, stress test, per-bank comparator, rate history. Every rate
	8	+// shows its provenance and freshness.
	9	+// -----------------------------------------------------------------------------
	10	+import { useEffect, useMemo, useRef, useState } from "react";
	11	+import { Link } from "react-router-dom";
	12	+import {
	13	+ MortgageBest, MortgageCalc, calculateMortgage, fetchMortgageBest,
	14	+ fmtPrice, fmtRate,
	15	+} from "../api";
	16	+import RateHistory from "./RateHistory";
	17	+
	18	+const FREQS: [string, string][] = [
	19	+ ["monthly", "Monthly"],
	20	+ ["semimonthly", "Semi-monthly (24/yr)"],
	21	+ ["biweekly", "Bi-weekly"],
	22	+ ["accelerated-biweekly", "Accelerated bi-weekly"],
	23	+ ["weekly", "Weekly"],
	24	+ ["accelerated-weekly", "Accelerated weekly"],
	25	+];
	26	+const TERMS: [number, string][] = [
	27	+ [12, "1 year"], [24, "2 years"], [36, "3 years"], [48, "4 years"],
	28	+ [60, "5 years"], [84, "7 years"], [120, "10 years"],
	29	+];
	30	+const KIND_EN: Record<string, string> = {
	31	+ posted: "posted rate", special: "special offer",
	32	+};
	33	+const INSURED_EN: Record<string, string> = {
	34	+ insured: "insured", insurable: "insurable", uninsured: "uninsured",
	35	+ unknown: "",
	36	+};
	37	+
	38	+const nf = (n: number) => n.toLocaleString("en-CA", { maximumFractionDigits: 0 });
	39	+const money = (n: number \| null \| undefined) =>
	40	+ n == null ? "—" : "$" + n.toLocaleString("en-CA", { minimumFractionDigits: 2, maximumFractionDigits: 2 });
	41	+
	42	+/** Readable freshness of a rate observation. */
	43	+function freshness(ageMinutes: number): string {
	44	+ if (ageMinutes < 60) return `${ageMinutes} min ago`;
	45	+ if (ageMinutes < 48 * 60) return `${Math.round(ageMinutes / 60)} h ago`;
	46	+ return `${Math.round(ageMinutes / 1440)} d ago`;
	47	+}
	48	+
	49	+export default function Financing({ price: askingPrice }:
	50	+ { price: number \| null }) {
	51	+ const [price, setPrice] = useState<number>(askingPrice ?? 0);
	52	+ const [down, setDown] = useState<number>(Math.round((askingPrice ?? 0) * 0.2));
	53	+ const [amort, setAmort] = useState(25);
	54	+ const [term, setTerm] = useState(60);
	55	+ const [rateType, setRateType] = useState<"fixed" \| "variable">("fixed");
	56	+ const [freq, setFreq] = useState("monthly");
	57	+ const [res, setRes] = useState<MortgageCalc \| null>(null);
	58	+ const [err, setErr] = useState<string \| null>(null);
	59	+ const [best, setBest] = useState<MortgageBest \| null>(null);
	60	+ const timer = useRef<number>();
	61	+
	62	+ const downPct = price > 0 ? (down / price) * 100 : 0;
	63	+ const setDownPct = (pct: number) =>
	64	+ setDown(Math.round((price * Math.min(99, Math.max(0, pct))) / 100));
	65	+
	66	+ // debounced recompute: the rates come from the engine, never the browser
	67	+ useEffect(() => {
	68	+ if (!price \|\| price <= 0 \|\| down < 0 \|\| down >= price) { setRes(null); return; }
	69	+ window.clearTimeout(timer.current);
	70	+ timer.current = window.setTimeout(() => {
	71	+ calculateMortgage({
	72	+ price, down_payment: down, amortization_years: amort,
	73	+ term_months: term, frequency: freq, rate_type: rateType,
	74	+ })
	75	+ .then((r) => { setRes(r); setErr(null); })
	76	+ .catch(() => setErr("Rates momentarily unavailable — try again later."));
	77	+ }, 350);
	78	+ return () => window.clearTimeout(timer.current);
	79	+ }, [price, down, amort, term, rateType, freq]);
	80	+
	81	+ // per-bank comparator (same type/term as the scenario)
	82	+ useEffect(() => {
	83	+ setBest(null);
	84	+ fetchMortgageBest(rateType, term).then(setBest).catch(() => setBest(null));
	85	+ }, [rateType, term]);
	86	+
	87	+ const monthlyCost = useMemo(() => {
	88	+ if (!res) return null;
	89	+ const parts: { k: string; v: number }[] = [
	90	+ { k: "Mortgage payment (monthly equivalent)", v: res.payment_monthly_equivalent },
	91	+ ];
	92	+ return { parts, total: parts.reduce((s, p) => s + p.v, 0) };
	93	+ }, [res]);
	94	+
	95	+ if (askingPrice == null \|\| askingPrice <= 0) return null;
	96	+ const src = res?.rate_source ?? null;
	97	+ const ins = res?.insurance;
	98	+
	99	+ return (
	100	+ <section className="f-bloc f-mtg" id="financing">
	101	+ <h2>Finance this home</h2>
	102	+ <p className="mtg-intro">
	103	+ Simulation using the <b>real rates published by Canadian banks</b>,
	104	+ collected continuously by House-Ka — semi-annual compounding (the
	105	+ Canadian standard) for fixed rates.{" "}
	106	+ <Link to="/rates">See all rates ↗</Link>
	107	+ </p>
	108	+
	109	+ <div className="mtg-form">
	110	+ <label>
	111	+ <span>Price</span>
	112	+ <input type="number" inputMode="numeric" min={1} value={price \|\| ""}
	113	+ onChange={(e) => setPrice(Number(e.target.value) \|\| 0)} />
	114	+ </label>
	115	+ <label>
	116	+ <span>Down payment ($)</span>
	117	+ <input type="number" inputMode="numeric" min={0} value={down \|\| ""}
	118	+ onChange={(e) => setDown(Number(e.target.value) \|\| 0)} />
	119	+ </label>
	120	+ <label>
	121	+ <span>Down payment (%)</span>
	122	+ <input type="number" inputMode="decimal" min={0} max={99} step={1}
	123	+ value={downPct ? Math.round(downPct * 10) / 10 : ""}
	124	+ onChange={(e) => setDownPct(Number(e.target.value) \|\| 0)} />
	125	+ </label>
	126	+ <label>
	127	+ <span>Amortization</span>
	128	+ <select value={amort} onChange={(e) => setAmort(Number(e.target.value))}>
	129	+ {[10, 15, 20, 25, 30].map((a) => <option key={a} value={a}>{a} years</option>)}
	130	+ </select>
	131	+ </label>
	132	+ <label>
	133	+ <span>Term</span>
	134	+ <select value={term} onChange={(e) => setTerm(Number(e.target.value))}>
	135	+ {TERMS.map(([m, l]) => <option key={m} value={m}>{l}</option>)}
	136	+ </select>
	137	+ </label>
	138	+ <label>
	139	+ <span>Rate type</span>
	140	+ <select value={rateType}
	141	+ onChange={(e) => setRateType(e.target.value as "fixed" \| "variable")}>
	142	+ <option value="fixed">Fixed</option>
	143	+ <option value="variable">Variable</option>
	144	+ </select>
	145	+ </label>
	146	+ <label>
	147	+ <span>Frequency</span>
	148	+ <select value={freq} onChange={(e) => setFreq(e.target.value)}>
	149	+ {FREQS.map(([v, l]) => <option key={v} value={v}>{l}</option>)}
	150	+ </select>
	151	+ </label>
	152	+ </div>
	153	+
	154	+ {err && <p className="mtg-err">{err}</p>}
	155	+
	156	+ {res && (
	157	+ <>
	158	+ <div className="mtg-resultat">
	159	+ <div className="mtg-kpi">
	160	+ <span className="mtg-kpi-k">Payment</span>
	161	+ <span className="mtg-kpi-v">{money(res.payment)}</span>
	162	+ <span className="mtg-kpi-sub">
	163	+ {FREQS.find(([v]) => v === freq)?.[1].toLowerCase()}
	164	+ {freq !== "monthly" && ` · equiv. ${money(res.payment_monthly_equivalent)}/month`}
	165	+ </span>
	166	+ </div>
	167	+ <div className="mtg-kpi">
	168	+ <span className="mtg-kpi-k">Rate used</span>
	169	+ <span className="mtg-kpi-v">{fmtRate(res.inputs.rate)}</span>
	170	+ {src && (
	171	+ <span className="mtg-kpi-sub">
	172	+ {src.institution} — {src.product_name}{" "}
	173	+ ({KIND_EN[src.kind] ?? src.kind}
	174	+ {INSURED_EN[src.insured_status ?? "unknown"]
	175	+ ? `, ${INSURED_EN[src.insured_status ?? "unknown"]}` : ""})
	176	+ </span>
	177	+ )}
	178	+ </div>
	179	+ <div className="mtg-kpi">
	180	+ <span className="mtg-kpi-k">Mortgage</span>
	181	+ <span className="mtg-kpi-v">{fmtPrice(res.principal)}</span>
	182	+ <span className="mtg-kpi-sub">
	183	+ down payment {fmtPrice(res.inputs.down_payment)} ({res.inputs.down_payment_pct.toLocaleString("en-CA")}%)
	184	+ </span>
	185	+ </div>
	186	+ <div className="mtg-kpi">
	187	+ <span className="mtg-kpi-k">Stress test</span>
	188	+ <span className="mtg-kpi-v">{money(res.qualifying.payment)}</span>
	189	+ <span className="mtg-kpi-sub">qualifying at {fmtRate(res.qualifying.rate)}</span>
	190	+ </div>
	191	+ </div>
	192	+
	193	+ {src && (
	194	+ <p className="mtg-source fine">
	195	+ Rate observed at <b>{src.institution}</b> {freshness(src.age_minutes)}
	196	+ {src.stale && " ⚠ data older than 24 h"} ·{" "}
	197	+ {src.source_url && (
	198	+ <a href={src.source_url} target="_blank" rel="noopener noreferrer">
	199	+ official source ↗
	200	+ </a>
	201	+ )}
	202	+ </p>
	203	+ )}
	204	+
	205	+ {ins && ins.required && (
	206	+ <div className={`mtg-schl ${ins.eligible ? "" : "mtg-schl-no"}`}>
	207	+ <b>Mortgage default insurance (CMHC)</b>
	208	+ {ins.eligible ? (
	209	+ <ul>
	210	+ <li>Premium: <b>{fmtPrice(ins.premium)}</b> ({ins.premium_rate.toLocaleString("en-CA")}% of the loan, added to the mortgage)</li>
	211	+ <li>Loan-to-value ratio: {ins.ltv?.toLocaleString("en-CA")}%</li>
	212	+ <li>Provincial sales tax on the premium may apply and is due at closing.</li>
	213	+ </ul>
	214	+ ) : null}
	215	+ {ins.issues.map((i, k) => <p className="mtg-issue" key={k}>⚠ {i}</p>)}
	216	+ </div>
	217	+ )}
	218	+
	219	+ {monthlyCost && (
	220	+ <details className="mtg-detail">
	221	+ <summary>Estimated real monthly cost</summary>
	222	+ <div className="dtable">
	223	+ {monthlyCost.parts.map((p) => (
	224	+ <div className="drow" key={p.k}><span>{p.k}</span><b>{money(p.v)}</b></div>
	225	+ ))}
	226	+ <div className="drow mtg-total"><span>Estimated total</span><b>{money(monthlyCost.total)}</b></div>
	227	+ </div>
	228	+ <p className="fine">
	229	+ Property taxes, heating, electricity, home insurance and condo
	230	+ fees are extra.
	231	+ </p>
	232	+ </details>
	233	+ )}
	234	+
	235	+ <details className="mtg-detail">
	236	+ <summary>What if rates rise? (stress test)</summary>
	237	+ <div className="dtable">
	238	+ {res.stress.map((s) => (
	239	+ <div className="drow" key={s.bump}>
	240	+ <span>{s.bump === 0 ? "Current rate" : `+${s.bump} point${s.bump > 1 ? "s" : ""}`} — {fmtRate(s.rate)}</span>
	241	+ <b>{money(s.payment)}</b>
	242	+ </div>
	243	+ ))}
	244	+ </div>
	245	+ <p className="fine">{res.qualifying.note}</p>
	246	+ </details>
	247	+
	248	+ <details className="mtg-detail">
	249	+ <summary>At renewal ({TERMS.find(([m]) => m === term)?.[1]})</summary>
	250	+ <p className="fine">
	251	+ Balance remaining at maturity: <b>{fmtPrice(res.renewal.balance_at_renewal)}</b>{" "}
	252	+ (remaining amortization {res.renewal.remaining_amortization_years} years).
	253	+ Interest paid during the term: {fmtPrice(res.term.interest_paid)}.
	254	+ </p>
	255	+ <div className="dtable">
	256	+ {res.renewal.scenarios.map((s) => (
	257	+ <div className="drow" key={s.bump}>
	258	+ <span>Renewed at {fmtRate(s.rate)} ({s.bump >= 0 ? "+" : ""}{s.bump} pt)</span>
	259	+ <b>{money(s.payment)}</b>
	260	+ </div>
	261	+ ))}
	262	+ </div>
	263	+ </details>
	264	+
	265	+ {best && best.per_institution.length > 1 && (
	266	+ <details className="mtg-detail">
	267	+ <summary>Compare the banks ({best.institutions_count} institutions)</summary>
	268	+ <div className="rooms-wrap">
	269	+ <table className="rooms mtg-comp">
	270	+ <thead>
	271	+ <tr><th>Institution</th><th>Rate</th><th>Kind</th><th>Payment</th><th>Freshness</th></tr>
	272	+ </thead>
	273	+ <tbody>
	274	+ {best.per_institution.map((r) => (
	275	+ <tr key={r.provider}>
	276	+ <td>
	277	+ {r.source_url
	278	+ ? <a href={r.source_url} target="_blank" rel="noopener noreferrer">{r.institution}</a>
	279	+ : r.institution}
	280	+ </td>
	281	+ <td><b>{fmtRate(r.rate)}</b>{r.apr != null ? ` (APR ${fmtRate(r.apr)})` : ""}</td>
	282	+ <td>
	283	+ {KIND_EN[r.kind]}
	284	+ {INSURED_EN[r.insured_status] ? ` · ${INSURED_EN[r.insured_status]}` : ""}
	285	+ </td>
	286	+ <td>{res.principal > 0 ? money(estimatePayment(res, r.rate)) : "—"}</td>
	287	+ <td className={r.stale ? "mtg-stale" : ""}>{freshness(r.age_minutes)}</td>
	288	+ </tr>
	289	+ ))}
	290	+ </tbody>
	291	+ </table>
	292	+ </div>
	293	+ <p className="fine">
	294	+ Comparable products only (same type, same term) — a posted rate
	295	+ and a special offer are not the same thing, hence the Kind
	296	+ column. Payments estimated on your scenario.
	297	+ </p>
	298	+ </details>
	299	+ )}
	300	+
	301	+ <details className="mtg-detail">
	302	+ <summary>Rate history ({rateType} {TERMS.find(([m]) => m === term)?.[1]})</summary>
	303	+ <RateHistory rateType={rateType} termMonths={term} />
	304	+ </details>
	305	+
	306	+ <details className="mtg-detail">
	307	+ <summary>Year-by-year amortization</summary>
	308	+ <div className="rooms-wrap">
	309	+ <table className="rooms">
	310	+ <thead>
	311	+ <tr><th>Year</th><th>Interest</th><th>Principal</th><th>Balance</th></tr>
	312	+ </thead>
	313	+ <tbody>
	314	+ {res.annual.map((a) => (
	315	+ <tr key={a.year}>
	316	+ <td>{a.year}</td>
	317	+ <td>${nf(a.interest)}</td>
	318	+ <td>${nf(a.principal)}</td>
	319	+ <td>${nf(a.balance)}</td>
	320	+ </tr>
	321	+ ))}
	322	+ </tbody>
	323	+ </table>
	324	+ </div>
	325	+ {res.payoff_years < res.inputs.amortization_years && (
	326	+ <p className="fine">
	327	+ With the accelerated frequency chosen, the loan is paid off in{" "}
	328	+ <b>{res.payoff_years} years</b> instead of {res.inputs.amortization_years}.
	329	+ </p>
	330	+ )}
	331	+ </details>
	332	+ </>
	333	+ )}
	334	+
	335	+ <p className="fine">
	336	+ Indicative tool only — neither a financing offer nor a pre-approval.
	337	+ The rates shown are those published by the institutions (source and
	338	+ freshness indicated); confirm with the bank or a mortgage broker.
	339	+ </p>
	340	+ </section>
	341	+ );
	342	+}
	343	+
	344	+/** Estimated payment at another bank's rate, same scenario (frontend
	345	+ * approximation via the annuity factor — the scenario's official numbers
	346	+ * always come from the engine). */
	347	+function estimatePayment(res: MortgageCalc, rate: number): number {
	348	+ const { amortization_years, frequency, compounding } = res.inputs;
	349	+ const f = ({ monthly: 12, semimonthly: 24, biweekly: 26,
	350	+ "accelerated-biweekly": 26, weekly: 52, "accelerated-weekly": 52 } as
	351	+ Record<string, number>)[frequency] ?? 12;
	352	+ const per = (pct: number, k: number) =>
	353	+ compounding === "monthly"
	354	+ ? Math.pow(1 + pct / 100 / 12, 12 / k) - 1
	355	+ : Math.pow(1 + pct / 100 / 2, 2 / k) - 1;
	356	+ const pay = (pct: number) => {
	357	+ if (frequency.startsWith("accelerated")) {
	358	+ const m = pay0(pct, 12);
	359	+ return Math.round((m / (frequency === "accelerated-biweekly" ? 2 : 4)) * 100) / 100;
	360	+ }
	361	+ return pay0(pct, f);
	362	+ };
	363	+ const pay0 = (pct: number, k: number) => {
	364	+ const i = per(pct, k);
	365	+ const n = Math.round(amortization_years * k);
	366	+ return Math.round(((res.principal * i) / (1 - Math.pow(1 + i, -n))) * 100) / 100;
	367	+ };
	368	+ return pay(rate);
	369	+}

added frontend/src/components/Icons.tsx +188 −0

		`@@ -0,0 +1,188 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)
	3	+// Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+// components/Icons.tsx : iconographie MAISON — traits 1,7 px sur grille 24,
	5	+// dessinée pour Immo-Ka (zéro emoji, zéro pack générique). Chaque icône est
	6	+// un tracé « stroke » net qui hérite de la couleur du texte (currentColor).
	7	+// -----------------------------------------------------------------------------
	8	+import { ReactNode } from "react";
	9	+
	10	+const P: Record<string, ReactNode> = {
	11	+ // --- navigation -----------------------------------------------------------
	12	+ home: (<>
	13	+ <path d="M3.5 10.6 12 3.4l8.5 7.2" />
	14	+ <path d="M5.6 9.4V20h12.8V9.4" />
	15	+ <path d="M10 20v-5.6h4V20" />
	16	+ </>),
	17	+ map: (<>
	18	+ <path d="M3.2 6.4 9 4.2l6 2.2 5.8-2.2v13.4L15 19.8l-6-2.2-5.8 2.2z" />
	19	+ <path d="M9 4.2v13.4M15 6.4v13.4" />
	20	+ </>),
	21	+ chart: (<>
	22	+ <path d="M4 20h16" />
	23	+ <path d="M7.2 20v-5.6M12 20V8.8M16.8 20V12" />
	24	+ </>),
	25	+ building: (<>
	26	+ <path d="M5 20V5.6A1.6 1.6 0 0 1 6.6 4h6.2a1.6 1.6 0 0 1 1.6 1.6V20" />
	27	+ <path d="M14.4 9.4h3.4A1.6 1.6 0 0 1 19.4 11v9" />
	28	+ <path d="M3.2 20h17.6" />
	29	+ <path d="M8 8h2.4M8 11.6h2.4M8 15.2h2.4M16.4 13h.9M16.4 16.2h.9" />
	30	+ </>),
	31	+
	32	+ // --- specs propriété --------------------------------------------------------
	33	+ bed: (<>
	34	+ <path d="M3.4 6.8V18.6" />
	35	+ <path d="M3.4 15.4h17.2v3.2" />
	36	+ <path d="M3.4 12.2h6.2v3.2" />
	37	+ <circle cx="6.5" cy="9.9" r="1.35" />
	38	+ <path d="M11.4 12.2h5.8a3.4 3.4 0 0 1 3.4 3.2" />
	39	+ </>),
	40	+ bath: (<>
	41	+ <path d="M3.6 12.4h16.8v1.4a5.2 5.2 0 0 1-5.2 5.2H8.8a5.2 5.2 0 0 1-5.2-5.2z" />
	42	+ <path d="M5.8 12.4V5.9a2.1 2.1 0 0 1 4-1" />
	43	+ <path d="m7 19.4-1 2.1M17 19.4l1 2.1" />
	44	+ </>),
	45	+ drop: (<>
	46	+ <path d="M12 3.6s6 6.4 6 10.6a6 6 0 1 1-12 0C6 10 12 3.6 12 3.6z" />
	47	+ <path d="M9.4 14.2a2.7 2.7 0 0 0 2 2.6" />
	48	+ </>),
	49	+ area: (<>
	50	+ <path d="M4.4 19.6 19.6 4.4" />
	51	+ <path d="M4.4 14v5.6H10" />
	52	+ <path d="M19.6 10V4.4H14" />
	53	+ </>),
	54	+ land: (<>
	55	+ <path d="M4.4 9.6v9.8M9.5 9.6v9.8M14.5 9.6v9.8M19.6 9.6v9.8" />
	56	+ <path d="M3 12.6h18M3 16.4h18" />
	57	+ <path d="M4.4 9.6 12 5.2l7.6 4.4" />
	58	+ </>),
	59	+ calendar: (<>
	60	+ <rect x="4" y="5.6" width="16" height="14.8" rx="2" />
	61	+ <path d="M4 10.2h16M8.2 3.4v4M15.8 3.4v4" />
	62	+ </>),
	63	+ tag: (<>
	64	+ <path d="m12.9 3.6 7.5 7.5a1.8 1.8 0 0 1 0 2.5l-6.8 6.8a1.8 1.8 0 0 1-2.5 0L3.6 12.9V3.6z" />
	65	+ <circle cx="8" cy="8" r="1.5" />
	66	+ </>),
	67	+ camera: (<>
	68	+ <rect x="3.4" y="7" width="17.2" height="13" rx="2" />
	69	+ <path d="M8.6 7 10 4.4h4L15.4 7" />
	70	+ <circle cx="12" cy="13.2" r="3.4" />
	71	+ </>),
	72	+
	73	+ // --- actions / états ----------------------------------------------------------
	74	+ search: (<>
	75	+ <circle cx="10.6" cy="10.6" r="6.2" />
	76	+ <path d="m15.3 15.3 5.3 5.3" />
	77	+ </>),
	78	+ arrow: (<>
	79	+ <path d="M4 12h15.2" />
	80	+ <path d="m13.8 6.4 5.4 5.6-5.4 5.6" />
	81	+ </>),
	82	+ check: (<path d="m5 12.8 4.3 4.4L19 7.4" />),
	83	+ alert: (<>
	84	+ <path d="M12 4.2 2.9 19.4h18.2z" />
	85	+ <path d="M12 10.2v4.4" />
	86	+ <path d="M12 17.4v.05" />
	87	+ </>),
	88	+ phone: (<path d="M5.2 4h3.6L10.4 8.4 8.3 10.1a12.5 12.5 0 0 0 5.6 5.6l1.7-2.1 4.4 1.6v3.6a1.8 1.8 0 0 1-1.9 1.8A16.4 16.4 0 0 1 3.4 5.9 1.8 1.8 0 0 1 5.2 4z" />),
	89	+ trendup: (<>
	90	+ <path d="m3.6 17.4 6-6.4 4 3.6 6.8-7.8" />
	91	+ <path d="M15.6 6.8h4.8v4.8" />
	92	+ </>),
	93	+ trenddown: (<>
	94	+ <path d="m3.6 6.8 6 6.4 4-3.6 6.8 7.8" />
	95	+ <path d="M15.6 17.4h4.8v-4.8" />
	96	+ </>),
	97	+ external: (<>
	98	+ <path d="M14.4 4h5.6v5.6" />
	99	+ <path d="M20 4 11.4 12.6" />
	100	+ <path d="M18.6 13.6V18a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V7.4a2 2 0 0 1 2-2h4.4" />
	101	+ </>),
	102	+ pin: (<>
	103	+ <path d="M12 21.2S5.4 15.7 5.4 10.8a6.6 6.6 0 0 1 13.2 0c0 4.9-6.6 10.4-6.6 10.4z" />
	104	+ <circle cx="12" cy="10.6" r="2.3" />
	105	+ </>),
	106	+ download: (<>
	107	+ <path d="M12 3.6v11.2" />
	108	+ <path d="m7.2 10.4 4.8 4.8 4.8-4.8" />
	109	+ <path d="M4.4 19.2h15.2" />
	110	+ </>),
	111	+
	112	+ // --- quartier ---------------------------------------------------------------------
	113	+ leaf: (<>
	114	+ <path d="M5 19.2C5 9.6 12 5 20 4.2c0 9-4.2 15-13.2 15z" />
	115	+ <path d="M5 19.2C7 14 11 10 15 8" />
	116	+ </>),
	117	+ thermo: (<>
	118	+ <path d="M10.4 4.2a1.9 1.9 0 0 1 3.8 0v8.8a4.2 4.2 0 1 1-3.8 0z" />
	119	+ <path d="M12.3 8.4v7" />
	120	+ </>),
	121	+ sun: (<>
	122	+ <circle cx="12" cy="12" r="4.2" />
	123	+ <path d="M12 3.2v2M12 18.8v2M3.2 12h2M18.8 12h2M5.8 5.8l1.4 1.4M16.8 16.8l1.4 1.4M18.2 5.8l-1.4 1.4M7.2 16.8l-1.4 1.4" />
	124	+ </>),
	125	+ shield: (<>
	126	+ <path d="M12 3.4 5.2 5.9v5.9c0 4.6 3 7.6 6.8 8.8 3.8-1.2 6.8-4.2 6.8-8.8V5.9z" />
	127	+ <path d="m9.2 12 2 2 3.8-4" />
	128	+ </>),
	129	+ cart: (<>
	130	+ <circle cx="9.6" cy="19.6" r="1.35" />
	131	+ <circle cx="17" cy="19.6" r="1.35" />
	132	+ <path d="M3.4 4.4h2.2l2.5 10.8h9.6l2.7-7.8H7" />
	133	+ </>),
	134	+ bus: (<>
	135	+ <rect x="4.6" y="3.8" width="14.8" height="13.4" rx="2.4" />
	136	+ <path d="M4.6 10.4h14.8" />
	137	+ <path d="M7.6 20.2v-3M16.4 20.2v-3" />
	138	+ <path d="M8.3 14h.05M15.7 14h.05" />
	139	+ </>),
	140	+ tree: (<>
	141	+ <path d="M12 3.4 6.8 11.4h2.8L5.4 17.8h13.2l-4.2-6.4h2.8z" />
	142	+ <path d="M12 17.8v3.4" />
	143	+ </>),
	144	+ school: (<>
	145	+ <path d="m12 4.2 9.8 4.4L12 13 2.2 8.6z" />
	146	+ <path d="M6.6 10.8v5c0 1.6 2.4 3 5.4 3s5.4-1.4 5.4-3v-5" />
	147	+ <path d="M21.8 8.6v5.4" />
	148	+ </>),
	149	+ health: (<>
	150	+ <circle cx="12" cy="12" r="8.4" />
	151	+ <path d="M12 8.4v7.2M8.4 12h7.2" />
	152	+ </>),
	153	+ pill: (<>
	154	+ <rect x="3.2" y="8.6" width="17.6" height="6.8" rx="3.4" transform="rotate(-33 12 12)" />
	155	+ <path d="M12 8.6v6.8" transform="rotate(-33 12 12)" />
	156	+ </>),
	157	+ people: (<>
	158	+ <circle cx="9" cy="8" r="3.2" />
	159	+ <path d="M3.6 20a5.4 5.4 0 0 1 10.8 0" />
	160	+ <path d="M15.4 5.4a3.2 3.2 0 0 1 0 5.9M17 14.8a5.4 5.4 0 0 1 3.4 5.2" />
	161	+ </>),
	162	+};
	163	+
	164	+export type IconName = keyof typeof P;
	165	+
	166	+export function Ico({ name, size = 18, className = "", stroke = 1.7 }:
	167	+ { name: IconName \| string; size?: number; className?: string; stroke?: number }) {
	168	+ const paths = P[name as IconName];
	169	+ if (!paths) return null;
	170	+ return (
	171	+ <svg
	172	+ className={`ico ${className}`}
	173	+ width={size} height={size} viewBox="0 0 24 24"
	174	+ fill="none" stroke="currentColor" strokeWidth={stroke}
	175	+ strokeLinecap="round" strokeLinejoin="round" aria-hidden="true"
	176	+ >
	177	+ {paths}
	178	+ </svg>
	179	+ );
	180	+}
	181	+
	182	+/** Version « chaîne HTML » pour les popups MapLibre (hors React). */
	183	+export function icoHTML(name: IconName, size = 30): string {
	184	+ const d: Record<string, string> = {
	185	+ home: '<path d="M3.5 10.6 12 3.4l8.5 7.2"/><path d="M5.6 9.4V20h12.8V9.4"/><path d="M10 20v-5.6h4V20"/>',
	186	+ };
	187	+ return `<svg width="${size}" height="${size}" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.7" stroke-linecap="round" stroke-linejoin="round">${d[name] ?? d.home}</svg>`;
	188	+}

added frontend/src/components/ListingCard.tsx +57 −0

		`@@ -0,0 +1,57 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	3	+// Author: Simon-Pierre Boucher — contact@spboucher.ai
	4	+// components/ListingCard.tsx : property card (results grid)
	5	+// -----------------------------------------------------------------------------
	6	+import { Link } from "react-router-dom";
	7	+import { Listing, fmtArea, fmtPrice, sourceName } from "../api";
	8	+import { Ico } from "./Icons";
	9	+import PropertyImg from "./PropertyImg";
	10	+
	11	+export default function ListingCard({ l }: { l: Listing }) {
	12	+ // light thumbnail when the connector provides one (mobile/cellular),
	13	+ // otherwise the full-size cover photo
	14	+ const img = (typeof l.details?.cover_thumb === "string" && l.details.cover_thumb)
	15	+ \|\| (l.images && l.images.length > 0 ? l.images[0] : null);
	16	+ const rent = l.details?.transaction === "location";
	17	+ const meta: { ico: string; txt: string }[] = [];
	18	+ if (l.bedrooms != null) meta.push({ ico: "bed", txt: `${l.bedrooms} bed` });
	19	+ if (l.bathrooms != null) meta.push({ ico: "bath", txt: `${l.bathrooms} bath` });
	20	+ const area = fmtArea(l.area_sqft);
	21	+ if (area) meta.push({ ico: "area", txt: area });
	22	+
	23	+ return (
	24	+ <Link to={`/property/${encodeURIComponent(l.uid)}`} className="card">
	25	+ <div className="card-img">
	26	+ <PropertyImg src={img} alt={l.title \|\| l.address} type={l.property_type} />
	27	+ {l.property_type && <span className="badge type">{l.property_type}</span>}
	28	+ {l.images.length > 1 && (
	29	+ <span className="badge right"><Ico name="camera" size={12} /> {l.images.length}</span>
	30	+ )}
	31	+ </div>
	32	+ <div className="card-body">
	33	+ <div className="card-price">
	34	+ {fmtPrice(l.price, l.price_label)}
	35	+ {rent && <span className="per-month"> /month</span>}
	36	+ </div>
	37	+ <div className="card-title">{l.address \|\| l.title}</div>
	38	+ <div className="card-meta">
	39	+ {l.sector && <span>{l.sector}</span>}
	40	+ {l.sector && l.city && <span className="sep" />}
	41	+ {l.city && <span>{l.city}</span>}
	42	+ </div>
	43	+ {meta.length > 0 && (
	44	+ <div className="card-specs">
	45	+ {meta.map((m) => (
	46	+ <span key={m.ico}><Ico name={m.ico} size={13} /> {m.txt}</span>
	47	+ ))}
	48	+ </div>
	49	+ )}
	50	+ <div className="card-foot">
	51	+ <span className="source-tag">{sourceName(l.source)}</span>
	52	+ {l.mls && <span className="avail">MLS® {l.mls}</span>}
	53	+ </div>
	54	+ </div>
	55	+ </Link>
	56	+ );
	57	+}

added frontend/src/components/MapView.tsx +321 −0

		`@@ -0,0 +1,321 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// Author: Simon-Pierre Boucher
	3	+// Contact: contact@spboucher.ai
	4	+// Project: Groupe Ka / Ka Maps (House-Ka integration)
	5	+// components/MapView.tsx : the House-Ka MAP MODE (Ka Map System v2) — same
	6	+// architecture as Lou-Ka/Immo-Ka Maps, themed pine/cream/ink.
	7	+// · viewport takeover (KaMapShell): mobile edge-to-edge + 3-notch results
	8	+// bottom sheet, desktop resizable list\|map split with near-fullscreen map;
	9	+// · viewport-driven data: /api/listings.geojson?bbox=…
	10	+// (Ka Maps adapter — cancellable requests, never a request storm);
	11	+// · unified toolbar (zoom, 3D, draw, locate me), contextual "Search this
	12	+// area", drawn area clipped CLIENT-SIDE (setClipPolygon) with the
	13	+// "N homes in this area" CTA;
	14	+// · contextual preview card v2: photo, price, swipe/chevrons between
	15	+// neighbouring properties.
	16	+// -----------------------------------------------------------------------------
	17	+import { useCallback, useEffect, useMemo, useRef, useState } from "react";
	18	+import { useNavigate } from "react-router-dom";
	19	+import "mapbox-gl/dist/mapbox-gl.css";
	20	+import "@groupe-ka/ka-maps/styles.css";
	21	+import type { KaMap, MapProperty } from "@groupe-ka/ka-maps";
	22	+import { cameraFromParams, cameraToParams } from "@groupe-ka/ka-maps";
	23	+import {
	24	+ KaBrandBadge,
	25	+ KaDrawAreaMode,
	26	+ KaMapShell,
	27	+ KaMapToolbar,
	28	+ KaMapView,
	29	+ KaPropertyPreview,
	30	+ KaToolbar3D,
	31	+ KaToolbarDraw,
	32	+ KaToolbarGroup,
	33	+ KaToolbarLocate,
	34	+ KaToolbarZoom,
	35	+ LoadingIndicator,
	36	+ SearchAreaControl,
	37	+ useKaMap,
	38	+ useKaShell,
	39	+} from "@groupe-ka/ka-maps/react";
	40	+import { Listing, ListingFilters, sourceName } from "../api";
	41	+import ListingCard from "./ListingCard";
	42	+import { houseKaMapTheme } from "../kamaps/theme";
	43	+import { houseKaMapAdapter } from "../kamaps/adapter";
	44	+import { MAPBOX_TOKEN } from "../kamaps/config";
	45	+
	46	+// Ontario first: open on Toronto (shared URLs override via ?lat&lng&zoom)
	47	+const DEFAULT_CENTER = { lat: 43.68, lng: -79.4 };
	48	+
	49	+/** Preview card — Ka Map System ka-prevcard structure, House-Ka content
	50	+ * (the adapter already carries photo/price/traits: no extra fetch). */
	51	+function PreviewCard({ p }: { p: MapProperty }) {
	52	+ const navigate = useNavigate();
	53	+ const extra = (p.extra ?? {}) as {
	54	+ title?: string \| null; priceLabel?: string \| null;
	55	+ source?: string;
	56	+ };
	57	+ const price = p.price != null
	58	+ ? "$" + p.price.toLocaleString("en-CA", { maximumFractionDigits: 0 })
	59	+ : extra.priceLabel \|\| "Price on request";
	60	+ const meta = [
	61	+ p.propertyType,
	62	+ p.bedrooms != null ? `${p.bedrooms} bed` : "",
	63	+ p.bathrooms != null ? `${p.bathrooms} bath` : "",
	64	+ extra.source ? sourceName(extra.source) : "",
	65	+ ].filter(Boolean).join(" · ");
	66	+ const fiche = p.originalUrl ?? "/";
	67	+ return (
	68	+ <>
	69	+ <div className="ka-prevcard-media">
	70	+ {p.thumbnailUrl ? (
	71	+ <img
	72	+ src={p.thumbnailUrl} alt="" loading="lazy"
	73	+ onError={(e) => { (e.target as HTMLImageElement).style.display = "none"; }}
	74	+ />
	75	+ ) : (
	76	+ <div className="ka-prevcard-noimg" aria-hidden="true">⌂</div>
	77	+ )}
	78	+ </div>
	79	+ <div className="ka-prevcard-body">
	80	+ <div className="ka-prevcard-price">{price}</div>
	81	+ <div className="ka-prevcard-addr">{p.address ?? extra.title ?? ""}</div>
	82	+ <div className="ka-prevcard-meta">{meta}</div>
	83	+ <div className="ka-prevcard-actions">
	84	+ <a
	85	+ className="ka-prevcard-cta"
	86	+ href={fiche}
	87	+ onClick={(e) => { e.preventDefault(); navigate(fiche); }}
	88	+ >
	89	+ See the listing →
	90	+ </a>
	91	+ </div>
	92	+ </div>
	93	+ </>
	94	+ );
	95	+}
	96	+
	97	+/** Bridge: exposes the KaMap engine to the parent component (outside canvas). */
	98	+function EngineBridge({ onEngine }: { onEngine: (m: KaMap \| null) => void }) {
	99	+ const map = useKaMap();
	100	+ useEffect(() => {
	101	+ onEngine(map);
	102	+ return () => onEngine(null);
	103	+ }, [map, onEngine]);
	104	+ return null;
	105	+}
	106	+
	107	+/** Mobile: selecting a marker collapses the sheet to mini. */
	108	+function SheetAutoCollapse({ selectedUid }: { selectedUid: string \| null }) {
	109	+ const shell = useKaShell();
	110	+ const shellRef = useRef(shell);
	111	+ shellRef.current = shell;
	112	+ useEffect(() => {
	113	+ const s = shellRef.current;
	114	+ if (selectedUid && s?.isMobile) s.setSheet("mini");
	115	+ }, [selectedUid]);
	116	+ return null;
	117	+}
	118	+
	119	+export interface MapViewProps {
	120	+ filters: ListingFilters;
	121	+ /** Current list page (12 listings) — the shell's results pane. */
	122	+ listings: Listing[] \| null;
	123	+ total: number;
	124	+ page: number;
	125	+ totalPages: number;
	126	+ onPage: (p: number) => void;
	127	+ sort: string;
	128	+ onSort: (s: string) => void;
	129	+ onExit?: () => void;
	130	+ onOpenFilters?: () => void;
	131	+ filtersCount?: number;
	132	+}
	133	+
	134	+export default function MapView({
	135	+ filters, listings, total, page, totalPages, onPage, sort, onSort,
	136	+ onExit, onOpenFilters, filtersCount = 0,
	137	+}: MapViewProps) {
	138	+ // initial camera: shared URL (?lat&lng&zoom) otherwise Toronto
	139	+ const initialCamera = useMemo(() => {
	140	+ const cam = cameraFromParams(new URLSearchParams(window.location.search));
	141	+ return cam ?? { ...DEFAULT_CENTER, zoom: 10 };
	142	+ }, []);
	143	+
	144	+ const [selectedUid, setSelectedUid] = useState<string \| null>(null);
	145	+ const [mapCount, setMapCount] = useState<number \| null>(null);
	146	+ const [hasZone, setHasZone] = useState(false);
	147	+ const [isMobile, setIsMobile] = useState(
	148	+ () => window.matchMedia("(max-width: 780px)").matches);
	149	+ const engineRef = useRef<KaMap \| null>(null);
	150	+ const listRef = useRef<HTMLDivElement \| null>(null);
	151	+
	152	+ useEffect(() => {
	153	+ const mq = window.matchMedia("(max-width: 780px)");
	154	+ const update = () => setIsMobile(mq.matches);
	155	+ mq.addEventListener("change", update);
	156	+ return () => mq.removeEventListener("change", update);
	157	+ }, []);
	158	+
	159	+ // camera → URL (replaceState: no router re-render)
	160	+ const onMoveEnd = useCallback((center: { lat: number; lng: number }, zoom: number) => {
	161	+ const url = new URL(window.location.href);
	162	+ url.search = cameraToParams({ ...center, zoom }, url.searchParams).toString();
	163	+ window.history.replaceState(null, "", url);
	164	+ }, []);
	165	+
	166	+ const mapFilters = useMemo(
	167	+ () => Object.fromEntries(Object.entries(filters).filter(([, v]) => v)),
	168	+ [filters],
	169	+ );
	170	+
	171	+ const handleEngine = useCallback((m: KaMap \| null) => {
	172	+ engineRef.current = m;
	173	+ }, []);
	174	+
	175	+ // map selection: preview card + list card scrolled into view
	176	+ const onSelect = useCallback((p: MapProperty \| null) => {
	177	+ const uid = p?.id ?? null;
	178	+ setSelectedUid(uid);
	179	+ if (!uid) return;
	180	+ const card = listRef.current?.querySelector<HTMLElement>(
	181	+ `[data-uid="${CSS.escape(uid)}"]`);
	182	+ card?.scrollIntoView({ behavior: "smooth", block: "nearest" });
	183	+ }, []);
	184	+
	185	+ // drawn area: CLIENT-SIDE clip of the displayed set (the House-Ka API does
	186	+ // not filter by polygon) — the CTA count comes from the data event.
	187	+ const onDraw = useCallback((polygon: [number, number][] \| null, drawing: boolean) => {
	188	+ if (drawing) return;
	189	+ setHasZone(polygon !== null);
	190	+ engineRef.current?.setClipPolygon(polygon);
	191	+ }, []);
	192	+
	193	+ const listHeader = (
	194	+ <div className="ms2-head">
	195	+ <div className="ms2-count" role="status" aria-live="polite">
	196	+ <b>{total.toLocaleString("en-CA")}</b>
	197	+ {" "}home{total > 1 ? "s" : ""}
	198	+ {mapCount != null && hasZone && (
	199	+ <span className="ms2-zone">{mapCount.toLocaleString("en-CA")} in the area</span>
	200	+ )}
	201	+ </div>
	202	+ <label className="ms2-sort">
	203	+ <select
	204	+ value={sort}
	205	+ onChange={(e) => onSort(e.target.value)}
	206	+ aria-label="Sort the results"
	207	+ >
	208	+ <option value="recent">Newest</option>
	209	+ <option value="price_asc">Price: low to high</option>
	210	+ <option value="price_desc">Price: high to low</option>
	211	+ </select>
	212	+ </label>
	213	+ </div>
	214	+ );
	215	+
	216	+ const listPane = (
	217	+ <div className="ms2-list" aria-label="List results" ref={listRef}>
	218	+ {(listings ?? []).map((l) => (
	219	+ <div
	220	+ key={l.uid}
	221	+ data-uid={l.uid}
	222	+ className={`map-card${selectedUid === l.uid ? " map-card-sel" : ""}`}
	223	+ onMouseEnter={() => engineRef.current?.setHovered(l.uid, "app")}
	224	+ onMouseLeave={() => engineRef.current?.setHovered(null, "app")}
	225	+ >
	226	+ <ListingCard l={l} />
	227	+ </div>
	228	+ ))}
	229	+ {listings !== null && listings.length === 0 && (
	230	+ <div className="ms-empty" role="status">
	231	+ <h3>No home matches</h3>
	232	+ <p>Try widening your criteria.</p>
	233	+ </div>
	234	+ )}
	235	+ {totalPages > 1 && (
	236	+ <nav className="pager ms2-pager" aria-label="Pagination">
	237	+ <button className="pager-btn" onClick={() => {
	238	+ onPage(page - 1);
	239	+ listRef.current?.parentElement?.scrollTo({ top: 0, behavior: "smooth" });
	240	+ }} disabled={page <= 1}>‹ Prev</button>
	241	+ <span className="pager-info">Page {page} / {totalPages}</span>
	242	+ <button className="pager-btn" onClick={() => {
	243	+ onPage(page + 1);
	244	+ listRef.current?.parentElement?.scrollTo({ top: 0, behavior: "smooth" });
	245	+ }} disabled={page >= totalPages}>Next ›</button>
	246	+ </nav>
	247	+ )}
	248	+ </div>
	249	+ );
	250	+
	251	+ return (
	252	+ <KaMapShell
	253	+ className="ms2"
	254	+ brand={<span className="ms2-brand"><b>House·Ka</b><span>Map</span></span>}
	255	+ onExit={onExit}
	256	+ exitLabel="List"
	257	+ storageKey="houseka-map-split"
	258	+ listHeader={listHeader}
	259	+ list={listPane}
	260	+ topExtras={
	261	+ onOpenFilters ? (
	262	+ <button className="ka-top-btn" onClick={onOpenFilters}>
	263	+ <svg width="13" height="13" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2.2" strokeLinecap="round" aria-hidden="true">
	264	+ <path d="M21 4h-7M10 4H3M21 12h-9M8 12H3M21 20h-5M12 20H3M14 2v4M8 10v4M16 18v4" />
	265	+ </svg>
	266	+ Filters
	267	+ {filtersCount > 0 && <span className="ka-top-badge">{filtersCount}</span>}
	268	+ </button>
	269	+ ) : null
	270	+ }
	271	+ >
	272	+ <KaMapView
	273	+ theme={houseKaMapTheme}
	274	+ adapter={houseKaMapAdapter}
	275	+ mapboxToken={MAPBOX_TOKEN}
	276	+ filters={mapFilters}
	277	+ center={initialCamera}
	278	+ zoom={initialCamera.zoom}
	279	+ pitch={50}
	280	+ // Realistic rendering: full-colour Standard + 3D landmarks — same
	281	+ // settings as Lou-Ka Maps.
	282	+ basemap={{ theme: "default", showLandmarks: true }}
	283	+ // valueClamp: caps each ASKING PRICE's contribution to the cluster
	284	+ // bubble (a $20M mansion doesn't skew the average)
	285	+ cluster={{ maxZoom: 15, valueClamp: [100_000, 3_000_000], valueMinCount: 10 }}
	286	+ searchMode="manual"
	287	+ navControl={false}
	288	+ onMoveEnd={onMoveEnd}
	289	+ onSelect={onSelect}
	290	+ onData={(count) => setMapCount(count)}
	291	+ onDraw={onDraw}
	292	+ >
	293	+ <EngineBridge onEngine={handleEngine} />
	294	+ <SheetAutoCollapse selectedUid={selectedUid} />
	295	+ <KaBrandBadge />
	296	+
	297	+ {/* THE control cluster — zoom (desktop), 3D, draw, locate */}
	298	+ <KaMapToolbar>
	299	+ {!isMobile && (
	300	+ <KaToolbarGroup><KaToolbarZoom /></KaToolbarGroup>
	301	+ )}
	302	+ <KaToolbarGroup>
	303	+ <KaToolbar3D />
	304	+ <KaToolbarDraw />
	305	+ <KaToolbarLocate />
	306	+ </KaToolbarGroup>
	307	+ </KaMapToolbar>
	308	+
	309	+ {/* draw mode: temporary banner + "N homes" CTA */}
	310	+ <KaDrawAreaMode
	311	+ formatCount={(n) => `${n.toLocaleString("en-CA")} home${n > 1 ? "s" : ""}`}
	312	+ onClear={() => engineRef.current?.setClipPolygon(null)}
	313	+ />
	314	+
	315	+ <SearchAreaControl />
	316	+ <LoadingIndicator label="Updating the homes…" />
	317	+ <KaPropertyPreview render={(p) => <PreviewCard p={p} />} />
	318	+ </KaMapView>
	319	+ </KaMapShell>
	320	+ );
	321	+}

added frontend/src/components/NearbyPlaces.tsx +84 −0

		`@@ -0,0 +1,84 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	3	+// Author: Simon-Pierre Boucher — contact@spboucher.ai
	4	+// components/NearbyPlaces.tsx : “Shops and transit” block (listing page)
	5	+// Distance to the closest location of each big banner (Costco, Walmart,
	6	+// Canadian Tire… via the Mapbox Search Box API) + nearest transit stops.
	7	+// SVG monogram chips in the banners' colours (no registered logos).
	8	+// -----------------------------------------------------------------------------
	9	+import { useEffect, useState } from "react";
	10	+import { CommercesNearby, fetchCommerces, fmtDist } from "../api";
	11	+
	12	+// id -> [background colour, monogram, text colour]
	13	+const ICONS: Record<string, [string, string, string?]> = {
	14	+ metro_station: ["#0083C9", "M"],
	15	+ rem_station: ["#84BD00", "R"],
	16	+ arret_bus: ["#4E5357", "B"],
	17	+ gare_train: ["#6E5B3F", "T"],
	18	+ costco: ["#005DAA", "C"],
	19	+ walmart: ["#0071CE", "W"],
	20	+ metro: ["#EF3E42", "M"],
	21	+ iga: ["#D50032", "IGA"],
	22	+ maxi: ["#0079C1", "Mx"],
	23	+ superc: ["#E4002B", "SC"],
	24	+ provigo: ["#DA291C", "P"],
	25	+ canadiantire: ["#D6001C", "CT"],
	26	+ dollarama: ["#00B140", "D", "#FFDD00"],
	27	+ saq: ["#892034", "SAQ"],
	28	+ pharmaprix: ["#E11B22", "Ph"],
	29	+ jeancoutu: ["#003DA5", "JC"],
	30	+ homedepot: ["#F96302", "HD"],
	31	+ rona: ["#1B4298", "R"],
	32	+};
	33	+
	34	+function Chip({ id }: { id: string }) {
	35	+ const [bg, mono, fg] = ICONS[id] ?? ["#777", "•"];
	36	+ const fs = mono.length >= 3 ? 9 : mono.length === 2 ? 11 : 14;
	37	+ return (
	38	+ <svg className="cm-ico" viewBox="0 0 28 28" width="28" height="28"
	39	+ aria-hidden="true">
	40	+ {["metro_station", "rem_station", "arret_bus", "gare_train"].includes(id)
	41	+ ? <circle cx="14" cy="14" r="13" fill={bg} />
	42	+ : <rect x="1" y="1" width="26" height="26" rx="7" fill={bg} />}
	43	+ <text x="14" y="14" textAnchor="middle" dominantBaseline="central"
	44	+ fontSize={fs} fontWeight="800" fontFamily="inherit"
	45	+ fill={fg ?? "#fff"}>{mono}</text>
	46	+ </svg>
	47	+ );
	48	+}
	49	+
	50	+export default function NearbyPlaces({ lat, lng }:
	51	+ { lat: number \| null; lng: number \| null }) {
	52	+ const [d, setD] = useState<CommercesNearby \| null>(null);
	53	+ useEffect(() => {
	54	+ setD(null);
	55	+ if (lat == null \|\| lng == null) return;
	56	+ fetchCommerces(lat, lng).then(setD).catch(() => setD(null));
	57	+ }, [lat, lng]);
	58	+ if (lat == null \|\| lng == null \|\| !d) return null;
	59	+ const all = [...(d.transit ?? []), ...(d.commerces ?? [])];
	60	+ if (all.length === 0) return null;
	61	+
	62	+ return (
	63	+ <section className="f-bloc f-commerces" id="nearby">
	64	+ <h2>Shops and transit</h2>
	65	+ <ul className="cm-grille">
	66	+ {all.map((c) => (
	67	+ <li key={c.id} className="cm-item"
	68	+ title={c.adresse \|\| undefined}>
	69	+ <Chip id={c.id} />
	70	+ <span className="cm-txt">
	71	+ <span className="cm-nom">{c.commerce}</span>
	72	+ <span className="cm-poi">{c.nom}</span>
	73	+ </span>
	74	+ <span className="cm-dist">{fmtDist(c.dist_m)}</span>
	75	+ </li>
	76	+ ))}
	77	+ </ul>
	78	+ <p className="fine">
	79	+ Closest location of each banner — straight-line distances (Mapbox
	80	+ search; transit: OpenStreetMap).
	81	+ </p>
	82	+ </section>
	83	+ );
	84	+}

added frontend/src/components/PropertyImg.tsx +45 −0

		`@@ -0,0 +1,45 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)
	3	+// Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+// components/PropertyImg.tsx : image de propriété robuste
	5	+// · <TypeFallback/> : image de secours élégante PAR TYPE DE BIEN aux couleurs
	6	+// Immo-Ka — jamais d'icône d'image cassée ni de vide gris.
	7	+// · <PropertyImg/> : <img> avec repli automatique si l'URL ne charge pas.
	8	+// -----------------------------------------------------------------------------
	9	+import { useState } from "react";
	10	+import { Ico } from "./Icons";
	11	+
	12	+const TYPE_ICONS: Record<string, string> = {
	13	+ "Maison": "home", "Maison mobile": "home", "Maison de ville": "home",
	14	+ "Jumelé": "home", "Chalet": "tree", "Condo": "building",
	15	+ "Duplex": "building", "Triplex": "building", "Multiplex": "building",
	16	+ "Terrain": "land", "Fermette/Agricole": "leaf", "Commercial": "cart",
	17	+};
	18	+
	19	+/** Image de secours par type de bien (gradient cerise + icône + libellé). */
	20	+export function TypeFallback({ type, label = true }: { type?: string; label?: boolean }) {
	21	+ const ico = TYPE_ICONS[type ?? ""] ?? "home";
	22	+ return (
	23	+ <div className="type-fallback" aria-label={type \|\| "Propriété"}>
	24	+ <Ico name={ico} size={40} />
	25	+ {label && <span>{type \|\| "Photos à venir"}</span>}
	26	+ </div>
	27	+ );
	28	+}
	29	+
	30	+/** <img> qui bascule sur l'image de secours du type si le chargement échoue. */
	31	+export default function PropertyImg({
	32	+ src, alt, type, eager = false,
	33	+}: { src?: string \| null; alt: string; type?: string; eager?: boolean }) {
	34	+ const [broken, setBroken] = useState(false);
	35	+ if (!src \|\| broken) return <TypeFallback type={type} />;
	36	+ return (
	37	+ <img
	38	+ src={src}
	39	+ alt={alt}
	40	+ loading={eager ? "eager" : "lazy"}
	41	+ decoding="async"
	42	+ onError={() => setBroken(true)}
	43	+ />
	44	+ );
	45	+}

added frontend/src/components/PropertyMap.tsx +69 −0

		`@@ -0,0 +1,69 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// Author: Simon-Pierre Boucher
	3	+// Contact: contact@spboucher.ai
	4	+// Project: Groupe Ka / Ka Maps (House-Ka integration)
	5	+// components/PropertyMap.tsx : 3D mini-map of the listing page — same
	6	+// component as Lou-Ka (KaSpotlightMap): tight camera on the address, realistic
	7	+// Mapbox Standard basemap, the listing's building highlighted in House-Ka
	8	+// PINE. Lazy-loaded from Listing.tsx.
	9	+// -----------------------------------------------------------------------------
	10	+import { useMemo } from "react";
	11	+import "mapbox-gl/dist/mapbox-gl.css";
	12	+import "@groupe-ka/ka-maps/styles.css";
	13	+import type { MapProperty } from "@groupe-ka/ka-maps";
	14	+import { KaBrandBadge, KaSpotlightMap } from "@groupe-ka/ka-maps/react";
	15	+import { houseKaMapTheme } from "../kamaps/theme";
	16	+import { MAPBOX_TOKEN } from "../kamaps/config";
	17	+
	18	+/** House-Ka pine signal — same language as the brand accent. */
	19	+export const BUILDING_PINE = "#0f6b4f";
	20	+
	21	+export interface PropertyMapProps {
	22	+ uid: string;
	23	+ lat: number;
	24	+ lng: number;
	25	+ price?: number \| null;
	26	+ propertyType?: string;
	27	+ address?: string;
	28	+ city?: string;
	29	+ image?: string \| null;
	30	+ deal?: boolean;
	31	+}
	32	+
	33	+export default function PropertyMap({
	34	+ uid, lat, lng, price, propertyType, address, city, image, deal,
	35	+}: PropertyMapProps) {
	36	+ const property = useMemo<MapProperty>(() => ({
	37	+ id: uid,
	38	+ appSource: "house-ka",
	39	+ latitude: lat,
	40	+ longitude: lng,
	41	+ kind: "listing",
	42	+ listingType: "sale",
	43	+ price: price ?? undefined,
	44	+ propertyType: propertyType \|\| undefined,
	45	+ address: address \|\| undefined,
	46	+ city: city \|\| undefined,
	47	+ thumbnailUrl: image ?? undefined,
	48	+ highlight: deal ?? false,
	49	+ }), [uid, lat, lng, price, propertyType, address, city, image, deal]);
	50	+
	51	+ return (
	52	+ <div
	53	+ className="lmap3d" role="img"
	54	+ aria-label={`3D map — ${address \|\| "property"}, the listing's building in green`}
	55	+ >
	56	+ <KaSpotlightMap
	57	+ theme={houseKaMapTheme}
	58	+ mapboxToken={MAPBOX_TOKEN}
	59	+ property={property}
	60	+ buildingColor={BUILDING_PINE}
	61	+ >
	62	+ <KaBrandBadge />
	63	+ </KaSpotlightMap>
	64	+ <span className="lmap3d-legende" aria-hidden="true">
	65	+ <i /> The listing's building
	66	+ </span>
	67	+ </div>
	68	+ );
	69	+}

added frontend/src/components/RateHistory.tsx +101 −0

		`@@ -0,0 +1,101 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	3	+// Author: Simon-Pierre Boucher — contact@spboucher.ai
	4	+// components/RateHistory.tsx : SVG chart of the best observed rate over time
	5	+// (validity periods valid_from/valid_to rebuilt as a step curve — a rate
	6	+// stays in force until it changes).
	7	+// -----------------------------------------------------------------------------
	8	+import { useEffect, useMemo, useState } from "react";
	9	+import { MortgageHistoryRow, fetchMortgageHistory, fmtRate } from "../api";
	10	+
	11	+/** Best rate (all institutions) at every instant: for each period boundary,
	12	+ * the min of the rates whose period covers that instant. */
	13	+function bestCurve(rows: MortgageHistoryRow[], now: number) {
	14	+ const stamps = new Set<number>();
	15	+ for (const r of rows) {
	16	+ stamps.add(r.valid_from);
	17	+ if (r.valid_to != null) stamps.add(r.valid_to);
	18	+ }
	19	+ stamps.add(now);
	20	+ const ts = [...stamps].sort((a, b) => a - b);
	21	+ const pts: { t: number; rate: number }[] = [];
	22	+ for (const t of ts) {
	23	+ let best: number \| null = null;
	24	+ for (const r of rows) {
	25	+ if (r.valid_from <= t && (r.valid_to == null \|\| r.valid_to > t))
	26	+ best = best == null ? r.rate : Math.min(best, r.rate);
	27	+ }
	28	+ if (best != null) pts.push({ t, rate: best });
	29	+ }
	30	+ return pts;
	31	+}
	32	+
	33	+export default function RateHistory({ rateType, termMonths, days = 365 }:
	34	+ { rateType: string; termMonths: number; days?: number }) {
	35	+ const [rows, setRows] = useState<MortgageHistoryRow[] \| null>(null);
	36	+
	37	+ useEffect(() => {
	38	+ setRows(null);
	39	+ fetchMortgageHistory(rateType, termMonths, days, "special")
	40	+ .then((r) => setRows(r.history))
	41	+ .catch(() => setRows([]));
	42	+ }, [rateType, termMonths, days]);
	43	+
	44	+ const now = Math.floor(Date.now() / 1000);
	45	+ const pts = useMemo(() => bestCurve(rows ?? [], now), [rows, now]);
	46	+
	47	+ if (rows == null) return <div className="fine">Loading the history…</div>;
	48	+ if (pts.length === 0)
	49	+ return <div className="fine">No history for this product yet.</div>;
	50	+
	51	+ const W = 640, H = 180, PAD = { l: 44, r: 10, t: 10, b: 22 };
	52	+ const t0 = pts[0].t, t1 = now;
	53	+ const rates = pts.map((p) => p.rate);
	54	+ const rMin = Math.floor(Math.min(...rates) * 10) / 10 - 0.1;
	55	+ const rMax = Math.ceil(Math.max(...rates) * 10) / 10 + 0.1;
	56	+ const x = (t: number) =>
	57	+ PAD.l + ((t - t0) / Math.max(1, t1 - t0)) * (W - PAD.l - PAD.r);
	58	+ const y = (r: number) =>
	59	+ PAD.t + (1 - (r - rMin) / Math.max(0.01, rMax - rMin)) * (H - PAD.t - PAD.b);
	60	+
	61	+ // step curve: the rate holds until the next change
	62	+ let d = `M ${x(pts[0].t).toFixed(1)} ${y(pts[0].rate).toFixed(1)}`;
	63	+ for (let i = 1; i < pts.length; i++) {
	64	+ d += ` H ${x(pts[i].t).toFixed(1)} V ${y(pts[i].rate).toFixed(1)}`;
	65	+ }
	66	+ d += ` H ${x(t1).toFixed(1)}`;
	67	+
	68	+ const yTicks: number[] = [];
	69	+ for (let r = Math.ceil(rMin * 4) / 4; r <= rMax + 1e-9; r += 0.25)
	70	+ yTicks.push(Math.round(r * 100) / 100);
	71	+ const fmtD = (t: number) =>
	72	+ new Date(t * 1000).toLocaleDateString("en-CA", { month: "short", day: "numeric" });
	73	+ const last = pts[pts.length - 1];
	74	+
	75	+ return (
	76	+ <div className="mtg-chart">
	77	+ <svg viewBox={`0 0 ${W} ${H}`} role="img"
	78	+ aria-label={`Best ${rateType} ${termMonths}-month rate over time`}>
	79	+ {yTicks.map((r) => (
	80	+ <g key={r}>
	81	+ <line x1={PAD.l} x2={W - PAD.r} y1={y(r)} y2={y(r)} className="mtg-grid" />
	82	+ <text x={PAD.l - 6} y={y(r) + 3} className="mtg-tick" textAnchor="end">
	83	+ {r.toFixed(2)}
	84	+ </text>
	85	+ </g>
	86	+ ))}
	87	+ <text x={x(t0)} y={H - 6} className="mtg-tick">{fmtD(t0)}</text>
	88	+ <text x={W - PAD.r} y={H - 6} className="mtg-tick" textAnchor="end">
	89	+ today
	90	+ </text>
	91	+ <path d={d} className="mtg-line" />
	92	+ <circle cx={x(t1)} cy={y(last.rate)} r={3.5} className="mtg-dot" />
	93	+ </svg>
	94	+ <div className="fine">
	95	+ Best “special offer” rate observed across all institutions —
	96	+ currently <b>{fmtRate(last.rate)}</b>. The history builds up as the
	97	+ collections run (no data is extrapolated).
	98	+ </div>
	99	+ </div>
	100	+ );
	101	+}

added frontend/src/ka/ecosystem.json +206 −0

		`@@ -0,0 +1,206 @@`
	1	+{
	2	+ "org": {
	3	+ "name": "Groupe KA",
	4	+ "legalName": "Groupe KA — Simon-Pierre Boucher",
	5	+ "tagline": "Holding québécois d'agrégateurs de produits et services entièrement automatisés.",
	6	+ "disclaimer": "Groupe KA est un agrégateur de contenu : nous ne vendons rien, ne louons rien et ne sommes partie à aucune transaction.",
	7	+ "copyrightHolder": "Groupe KA — Simon-Pierre Boucher"
	8	+ },
	9	+ "hub": {
	10	+ "url": "https://www.groupe-ka.com",
	11	+ "loginPath": "/connexion",
	12	+ "signupNote": "La création de compte KA ID se fait sur le hub groupe-ka.com ; chaque site délègue sa connexion via /api/auth/ka/login."
	13	+ },
	14	+ "contacts": [
	15	+ {
	16	+ "email": "contact@groupe-ka.com",
	17	+ "role": "Projets, partenariats & données"
	18	+ },
	19	+ {
	20	+ "email": "info@groupe-ka.com",
	21	+ "role": "Médias & questions générales"
	22	+ },
	23	+ {
	24	+ "email": "admin@groupe-ka.com",
	25	+ "role": "Légal, vie privée & Loi 25"
	26	+ }
	27	+ ],
	28	+ "legal": [
	29	+ {
	30	+ "label": "Conditions d'utilisation",
	31	+ "href": "https://www.groupe-ka.com/conditions"
	32	+ },
	33	+ {
	34	+ "label": "Politique de confidentialité",
	35	+ "href": "https://www.groupe-ka.com/confidentialite"
	36	+ },
	37	+ {
	38	+ "label": "Protection des renseignements personnels (Loi 25)",
	39	+ "href": "https://www.groupe-ka.com/loi-25"
	40	+ },
	41	+ {
	42	+ "label": "Transparence des robots d'indexation",
	43	+ "href": "https://www.groupe-ka.com/bots"
	44	+ }
	45	+ ],
	46	+ "sites": [
	47	+ {
	48	+ "id": "groupe-ka",
	49	+ "wordmark": "Groupe KA",
	50	+ "domain": "www.groupe-ka.com",
	51	+ "accent": "#d9f26b",
	52	+ "accentSoft": "#f0f9d2",
	53	+ "accentDeep": "#123f2e",
	54	+ "onAccent": "#141814",
	55	+ "tagline": "Le portail de l'écosystème ·Ka"
	56	+ },
	57	+ {
	58	+ "id": "trouve-ka",
	59	+ "wordmark": "Trouve·Ka",
	60	+ "domain": "www.trouve-ka.com",
	61	+ "accent": "#1c7ed6",
	62	+ "accentSoft": "#e7f2fd",
	63	+ "accentDeep": "#14508f",
	64	+ "onAccent": "#ffffff",
	65	+ "tagline": "Le moteur de recherche du web québécois"
	66	+ },
	67	+ {
	68	+ "id": "lou-ka",
	69	+ "wordmark": "Lou·Ka",
	70	+ "domain": "www.lou-ka.com",
	71	+ "accent": "#ff6a00",
	72	+ "accentSoft": "#fff1e6",
	73	+ "accentDeep": "#cc5500",
	74	+ "onAccent": "#ffffff",
	75	+ "tagline": "Tous les logements à louer"
	76	+ },
	77	+ {
	78	+ "id": "immo-ka",
	79	+ "wordmark": "Immo·Ka",
	80	+ "domain": "www.immo-ka.com",
	81	+ "accent": "#e23744",
	82	+ "accentSoft": "#fbe0e2",
	83	+ "accentDeep": "#a8232e",
	84	+ "onAccent": "#ffffff",
	85	+ "tagline": "Toutes les propriétés à vendre"
	86	+ },
	87	+ {
	88	+ "id": "vrai-prix",
	89	+ "wordmark": "Vrai-Prix",
	90	+ "domain": "www.vrai-prix.com",
	91	+ "accent": "#ff5148",
	92	+ "accentSoft": "#ffe3e0",
	93	+ "accentDeep": "#9e2a25",
	94	+ "onAccent": "#ffffff",
	95	+ "tagline": "La valeur réelle de chaque propriété"
	96	+ },
	97	+ {
	98	+ "id": "auto-ka",
	99	+ "wordmark": "Auto·Ka",
	100	+ "domain": "www.auto-ka.com",
	101	+ "accent": "#ff5a2a",
	102	+ "accentSoft": "#ffe8de",
	103	+ "accentDeep": "#cc3f16",
	104	+ "onAccent": "#ffffff",
	105	+ "tagline": "Les voitures usagées du Québec"
	106	+ },
	107	+ {
	108	+ "id": "fabri-ka",
	109	+ "wordmark": "Fabri·Ka",
	110	+ "domain": "www.fabri-ka.com",
	111	+ "accent": "#c4532e",
	112	+ "accentSoft": "#f7e3da",
	113	+ "accentDeep": "#a94525",
	114	+ "onAccent": "#ffffff",
	115	+ "tagline": "Les produits fabriqués au Québec"
	116	+ },
	117	+ {
	118	+ "id": "food-ka",
	119	+ "wordmark": "Food·Ka",
	120	+ "domain": "www.food-ka.com",
	121	+ "accent": "#1f9d55",
	122	+ "accentSoft": "#e2f5ea",
	123	+ "accentDeep": "#157a40",
	124	+ "onAccent": "#ffffff",
	125	+ "tagline": "Les prix d'épicerie, suivis à la source"
	126	+ },
	127	+ {
	128	+ "id": "resto-ka",
	129	+ "wordmark": "Resto·Ka",
	130	+ "domain": "www.resto-ka.com",
	131	+ "accent": "#f08c00",
	132	+ "accentSoft": "#fdeed7",
	133	+ "accentDeep": "#b96a00",
	134	+ "onAccent": "#141814",
	135	+ "tagline": "Chaque resto, chaque plat, chaque prix"
	136	+ },
	137	+ {
	138	+ "id": "sorti-ka",
	139	+ "wordmark": "Sorti·Ka",
	140	+ "domain": "www.sorti-ka.com",
	141	+ "accent": "#d6336c",
	142	+ "accentSoft": "#fbe0eb",
	143	+ "accentDeep": "#a12551",
	144	+ "onAccent": "#ffffff",
	145	+ "tagline": "Toutes les sorties, dans les 17 régions"
	146	+ },
	147	+ {
	148	+ "id": "crea-ka",
	149	+ "wordmark": "Créa·Ka",
	150	+ "domain": "www.crea-ka.com",
	151	+ "accent": "#7048e8",
	152	+ "accentSoft": "#ece5fc",
	153	+ "accentDeep": "#5433b8",
	154	+ "onAccent": "#ffffff",
	155	+ "tagline": "Les créateurs d'ici, tous leurs liens"
	156	+ },
	157	+ {
	158	+ "id": "api-ka",
	159	+ "wordmark": "API·Ka",
	160	+ "domain": "www.api-ka.com",
	161	+ "accent": "#3b5bdb",
	162	+ "accentSoft": "#e4eafb",
	163	+ "accentDeep": "#2b44a8",
	164	+ "onAccent": "#ffffff",
	165	+ "tagline": "La donnée de l'écosystème, par API"
	166	+ },
	167	+ {
	168	+ "id": "job-ka",
	169	+ "wordmark": "Job·Ka",
	170	+ "domain": "www.job-ka.com",
	171	+ "accent": "#0c8599",
	172	+ "accentSoft": "#def0f4",
	173	+ "accentDeep": "#095c6b",
	174	+ "onAccent": "#ffffff",
	175	+ "tagline": "Tous les emplois des employeurs québécois"
	176	+ },
	177	+ {
	178	+ "id": "ka-stats",
	179	+ "wordmark": "Ka·Stats",
	180	+ "domain": "www.ka-stats.com",
	181	+ "accent": "#095797",
	182	+ "accentSoft": "#e2edf6",
	183	+ "accentDeep": "#063a63",
	184	+ "onAccent": "#ffffff",
	185	+ "tagline": "L'explorateur de statistiques du Québec"
	186	+ }
	187	+ ],
	188	+ "extraFooterLinks": [
	189	+ {
	190	+ "label": "ValoPlex",
	191	+ "href": "https://www.valoplex.com"
	192	+ },
	193	+ {
	194	+ "label": "Ka2",
	195	+ "href": "https://www.ka2.bot"
	196	+ },
	197	+ {
	198	+ "label": "Ka4",
	199	+ "href": "https://www.ka4.bot"
	200	+ },
	201	+ {
	202	+ "label": "Ka6",
	203	+ "href": "https://www.ka6.bot"
	204	+ }
	205	+ ]
	206	+}
		\ No newline at end of file

added frontend/src/ka/tokens.css +319 −0

		`@@ -0,0 +1,319 @@`
	1	+/* -----------------------------------------------------------------------------
	2	+ Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	3	+ Fichier : ka-ui/tokens.css — SOURCE CANONIQUE (repo ka-ui sur spbgit)
	4	+ Desc. : Design system commun GROUPE KA « éditorial sharp » — tokens + socle
	5	+ de composants partagés par les 12 plateformes. Chaque site importe ce
	6	+ fichier PUIS surcharge uniquement son accent (voir accents.css).
	7	+
	8	+ · Typo : display Space Grotesk / texte Inter / micro-étiquettes JetBrains Mono
	9	+ · Palette: papier #f5f3ee · encre #141814 · vert profond #1c5c41 + ACCENT du site
	10	+ · Signature : bordures encre 1,5–2 px + ombres décalées dures, grain de film,
	11	+ surlignés d'accent inclinés (néo-brutalisme raffiné)
	12	+ · Breakpoints communs : 360 / 768 / 1024 / 1440 px (mobile-first)
	13	+ · Zones tactiles ≥ 44×44 px, safe-areas iOS, typographie fluide (clamp)
	14	+----------------------------------------------------------------------------- */
	15	+
	16	+:root {
	17	+ /* ---- Palette fixe Groupe KA (identique sur les 12 sites) ---- */
	18	+ --paper: #f5f3ee;
	19	+ --surface: #ffffff;
	20	+ --surface-2: #faf9f5;
	21	+ --ink: #141814;
	22	+ --ink-2: #4d5551;
	23	+ --ink-3: #8b928c;
	24	+ --line: rgba(20, 24, 20, 0.14);
	25	+ --line-strong: rgba(20, 24, 20, 0.85);
	26	+ --green: #1c5c41;
	27	+ --green-deep: #123f2e;
	28	+ --amber: #e8a33d;
	29	+ --amber-soft: #fdf3e2;
	30	+ --danger: #b3423a;
	31	+ --danger-soft: #fbe9e7;
	32	+
	33	+ /* ---- ACCENT du site — SEULES variables surchargées par marque ---- */
	34	+ --accent: #d9f26b; /* défaut : lime Groupe KA */
	35	+ --accent-soft: #f0f9d2;
	36	+ --accent-deep: #123f2e;
	37	+ --on-accent: var(--ink); /* couleur du texte posé SUR l'accent */
	38	+
	39	+ /* alias rétro-compatibles (les satellites historiques utilisent --lime) */
	40	+ --lime: var(--accent);
	41	+ --lime-soft: var(--accent-soft);
	42	+
	43	+ /* ---- Géométrie sharp ---- */
	44	+ --r-card: 10px;
	45	+ --r-ctl: 6px;
	46	+ --r-pill: 999px;
	47	+
	48	+ /* ---- Ombres décalées — la signature du groupe ---- */
	49	+ --shadow-flat: 0 1px 2px rgba(20, 24, 20, 0.05);
	50	+ --shadow-off: 6px 6px 0 var(--ink);
	51	+ --shadow-off-soft: 8px 8px 0 rgba(20, 24, 20, 0.08);
	52	+ --shadow-off-mid: 4px 4px 0 rgba(20, 24, 20, 0.18);
	53	+
	54	+ /* ---- Typographie ---- */
	55	+ --font-display: "Space Grotesk", system-ui, sans-serif;
	56	+ --font-body: "Inter", system-ui, sans-serif;
	57	+ --font-mono: "JetBrains Mono", ui-monospace, monospace;
	58	+
	59	+ /* Échelle fluide (mobile-first, clamp) */
	60	+ --fs-h1: clamp(30px, 3.2vw + 18px, 54px);
	61	+ --fs-h2: clamp(23px, 1.8vw + 14px, 34px);
	62	+ --fs-h3: clamp(17px, 0.9vw + 12px, 22px);
	63	+ --fs-body: 15px;
	64	+ --fs-small: 13px;
	65	+
	66	+ /* Espacements */
	67	+ --sp-1: 4px; --sp-2: 8px; --sp-3: 12px; --sp-4: 16px;
	68	+ --sp-5: 24px; --sp-6: 32px; --sp-7: 48px; --sp-8: 64px;
	69	+
	70	+ /* Cible tactile minimale */
	71	+ --touch: 44px;
	72	+
	73	+ /* ---- Échelle z-index COMMUNE (obligatoire — aucune valeur arbitraire) ----
	74	+ grain de film body::before = 9999 (pointer-events:none, toujours au-dessus,
	75	+ purement visuel). Tout composant interactif se place sous 9999 : */
	76	+ --z-content: 1; /* contenu positionné ordinaire */
	77	+ --z-sticky: 300; /* éléments sticky de contenu (sous-nav…) */
	78	+ --z-header: 500; /* header du site */
	79	+ --z-bottombar: 600; /* tab bar / barre d'action basse */
	80	+ --z-dropdown: 700; /* menus déroulants (au-dessus des barres) */
	81	+ --z-overlay: 800; /* voile sous modale/panneau */
	82	+ --z-modal: 900; /* modales, panneaux de filtres, galeries */
	83	+ --z-toast: 950; /* notifications */
	84	+
	85	+ /* ---- Hauteur de viewport DYNAMIQUE (barre du navigateur mobile qui se
	86	+ replie au scroll) : toujours var(--vh100), JAMAIS 100vh en dur. ---- */
	87	+ --vh100: 100vh;
	88	+}
	89	+@supports (height: 100dvh) { :root { --vh100: 100dvh; } }
	90	+
	91	+/* ---- Socle ---- */
	92	+* { box-sizing: border-box; }
	93	+/* overflow-x: clip sur html ET body — sur WebKit iOS, clip posé sur body seul
	94	+ ne bloque PAS le défilement latéral du viewport (quirk de propagation) ;
	95	+ clip (≠ hidden) ne casse pas position:sticky. */
	96	+html { scroll-behavior: smooth; -webkit-text-size-adjust: 100%; overflow-x: clip; }
	97	+body {
	98	+ margin: 0;
	99	+ background: var(--paper);
	100	+ color: var(--ink);
	101	+ font-family: var(--font-body);
	102	+ font-size: var(--fs-body);
	103	+ line-height: 1.55;
	104	+ -webkit-font-smoothing: antialiased;
	105	+ padding-bottom: env(safe-area-inset-bottom);
	106	+ overflow-x: clip; /* jamais de débordement horizontal */
	107	+}
	108	+img, svg, video { max-width: 100%; height: auto; display: block; }
	109	+h1, h2, h3, h4 { font-family: var(--font-display); letter-spacing: -0.03em; margin: 0 0 0.5em; }
	110	+h1 { font-size: var(--fs-h1); line-height: 1.06; }
	111	+h2 { font-size: var(--fs-h2); line-height: 1.15; }
	112	+h3 { font-size: var(--fs-h3); line-height: 1.25; }
	113	+a { color: inherit; }
	114	+::selection { background: var(--accent); color: var(--on-accent); }
	115	+:focus-visible { outline: 2px solid var(--green); outline-offset: 2px; }
	116	+
	117	+/* Grain de film pleine page — ⚠️ jamais de z-index sur body > * (position:
	118	+ relative seulement), sinon les utilitaires z-* sont écrasés. */
	119	+body::before {
	120	+ content: "";
	121	+ position: fixed; inset: 0; pointer-events: none; opacity: 0.35; z-index: 9999;
	122	+ background-image: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='120' height='120'%3E%3Cfilter id='n'%3E%3CfeTurbulence type='fractalNoise' baseFrequency='0.9' numOctaves='2' stitchTiles='stitch'/%3E%3CfeColorMatrix type='saturate' values='0'/%3E%3CfeComponentTransfer%3E%3CfeFuncA type='linear' slope='0.06'/%3E%3C/feComponentTransfer%3E%3C/filter%3E%3Crect width='120' height='120' filter='url(%23n)'/%3E%3C/svg%3E");
	123	+}
	124	+body > * { position: relative; }
	125	+
	126	+/* ---- Conteneur commun ---- */
	127	+.container { max-width: 1152px; margin: 0 auto; padding: 0 var(--sp-4); }
	128	+@media (min-width: 768px) { .container { padding: 0 var(--sp-5); } }
	129	+
	130	+/* ---- Micro-typographie signature ---- */
	131	+.kicker {
	132	+ display: inline-flex; align-items: center; gap: 10px;
	133	+ font-family: var(--font-mono); font-size: 11.5px; font-weight: 500;
	134	+ text-transform: uppercase; letter-spacing: 0.12em; color: var(--green);
	135	+}
	136	+.kicker::before { content: ""; width: 22px; height: 2px; background: var(--green); }
	137	+.klabel {
	138	+ font-family: var(--font-mono); font-size: 10px; font-weight: 700;
	139	+ text-transform: uppercase; letter-spacing: 0.1em; color: var(--ink-3);
	140	+}
	141	+.hl {
	142	+ display: inline-block; background: var(--accent); color: var(--on-accent);
	143	+ border-radius: 8px; padding: 0 10px 2px; transform: rotate(-1deg);
	144	+}
	145	+.outline-txt { color: transparent; -webkit-text-stroke: 2px var(--ink); }
	146	+
	147	+/* ---- Boutons (cible ≥ 44 px) ---- */
	148	+.btn {
	149	+ display: inline-flex; align-items: center; justify-content: center; gap: 8px;
	150	+ min-height: var(--touch); padding: 10px 18px;
	151	+ font-family: var(--font-display); font-weight: 700; font-size: 14px;
	152	+ border: 1.5px solid var(--ink); border-radius: var(--r-ctl);
	153	+ background: var(--surface); color: var(--ink);
	154	+ cursor: pointer; text-decoration: none;
	155	+ transition: transform 0.15s, box-shadow 0.15s, background 0.15s, color 0.15s;
	156	+}
	157	+.btn:hover { transform: translate(-2px, -2px); box-shadow: var(--shadow-off-mid); }
	158	+.btn:active { transform: translate(0, 0); box-shadow: none; }
	159	+.btn:disabled { opacity: 0.45; pointer-events: none; }
	160	+.btn-primary { background: var(--ink); color: var(--accent); }
	161	+.btn-primary:hover { background: var(--accent-deep); }
	162	+.btn-accent { background: var(--accent); color: var(--on-accent); }
	163	+.btn-ghost { background: transparent; border-color: var(--line); }
	164	+.btn-ghost:hover { border-color: var(--ink); }
	165	+
	166	+/* ---- Cartes ---- */
	167	+.card {
	168	+ background: var(--surface); border: 1.5px solid var(--ink);
	169	+ border-radius: var(--r-card); box-shadow: var(--shadow-off-soft);
	170	+ overflow: hidden;
	171	+}
	172	+.card-hover { transition: transform 0.15s, box-shadow 0.15s; }
	173	+.card-hover:hover { transform: translate(-2px, -2px); box-shadow: var(--shadow-off); }
	174	+
	175	+/* ---- Chips / badges ---- */
	176	+.chip {
	177	+ display: inline-flex; align-items: center; gap: 6px;
	178	+ padding: 4px 11px; font-family: var(--font-mono); font-size: 11px; font-weight: 700;
	179	+ text-transform: uppercase; letter-spacing: 0.06em;
	180	+ border: 1.5px solid var(--ink); border-radius: var(--r-pill);
	181	+ background: var(--surface); color: var(--ink);
	182	+}
	183	+.chip-accent { background: var(--accent); color: var(--on-accent); }
	184	+.chip-soft { background: var(--accent-soft); border-color: var(--line); }
	185	+
	186	+/* ---- Champs ---- */
	187	+.input, .select, .textarea {
	188	+ width: 100%; min-height: var(--touch); padding: 10px 14px;
	189	+ font: inherit; color: var(--ink); background: var(--surface);
	190	+ border: 1.5px solid var(--ink); border-radius: var(--r-ctl);
	191	+}
	192	+.input:focus, .select:focus, .textarea:focus {
	193	+ outline: none; box-shadow: 3px 3px 0 var(--accent); border-color: var(--ink);
	194	+}
	195	+.input::placeholder { color: var(--ink-3); }
	196	+
	197	+/* ---- Badge « Un service Groupe KA » (header, cliquable → hub) ---- */
	198	+.gk-badge {
	199	+ display: inline-flex; align-items: center; gap: 7px;
	200	+ min-height: 30px; padding: 3px 10px 4px;
	201	+ font-family: var(--font-mono); font-size: 10px; font-weight: 700;
	202	+ letter-spacing: 0.08em; text-transform: uppercase; text-decoration: none;
	203	+ border: 1.5px solid var(--ink); border-radius: var(--r-pill);
	204	+ background: var(--surface); color: var(--ink-2); white-space: nowrap;
	205	+}
	206	+.gk-badge b {
	207	+ font-family: var(--font-display); font-size: 12px; letter-spacing: -0.02em;
	208	+ text-transform: none; color: var(--ink);
	209	+}
	210	+.gk-badge b .ka {
	211	+ display: inline-block; background: var(--ink); color: var(--accent);
	212	+ border-radius: 5px; padding: 0 5px 1px; margin-left: 3px; transform: rotate(-2deg);
	213	+}
	214	+.gk-badge:hover .ka { transform: rotate(0); }
	215	+.gk-badge--dark { background: transparent; border-color: rgba(245,243,238,0.4); color: rgba(245,243,238,0.75); }
	216	+.gk-badge--dark b { color: var(--paper); }
	217	+
	218	+/* ---- Footer commun (fond encre — voir react/KaFooter.tsx) ---- */
	219	+.ka-footer { margin-top: var(--sp-8); background: var(--ink); padding: 44px 0; font-size: 13px; color: rgba(245,243,238,0.75); }
	220	+.ka-footer a { text-decoration: none; }
	221	+.ka-footer .wordmark { font-family: var(--font-display); font-weight: 700; font-size: 30px; letter-spacing: -0.04em; color: var(--paper); text-decoration: none; }
	222	+.ka-footer .wordmark .ka { color: var(--accent); }
	223	+.ka-footer .desc { max-width: 640px; margin-top: var(--sp-4); }
	224	+.ka-footer .notice { max-width: 640px; margin-top: var(--sp-4); border-left: 2px solid var(--accent); padding-left: var(--sp-4); }
	225	+.ka-footer .notice b { color: var(--paper); }
	226	+.ka-footer .sites { list-style: none; display: flex; flex-wrap: wrap; gap: 10px 26px; margin: 26px 0 0; padding: 0; font-family: var(--font-mono); font-size: 11px; font-weight: 700; letter-spacing: 0.1em; text-transform: uppercase; }
	227	+.ka-footer .sites a { color: rgba(245,243,238,0.65); }
	228	+.ka-footer .sites a:hover { color: var(--accent); text-decoration: underline; text-underline-offset: 4px; }
	229	+.ka-footer .contacts { display: grid; gap: 14px 32px; border-top: 1px solid rgba(245,243,238,0.15); margin-top: 30px; padding-top: 26px; }
	230	+@media (min-width: 768px) { .ka-footer .contacts { grid-template-columns: repeat(3, 1fr); } }
	231	+.ka-footer .contacts a { font-family: var(--font-mono); font-weight: 700; font-size: 12px; color: rgba(245,243,238,0.85); }
	232	+.ka-footer .contacts a:hover { color: var(--accent); text-decoration: underline; text-underline-offset: 4px; }
	233	+.ka-footer .contacts span { display: block; margin-top: 3px; font-size: 11px; color: rgba(245,243,238,0.5); }
	234	+.ka-footer .legal { margin-top: 30px; font-family: var(--font-mono); font-size: 11px; color: rgba(245,243,238,0.45); }
	235	+.ka-footer .legal a { color: inherit; }
	236	+.ka-footer .legal a:hover { color: var(--accent); text-decoration: underline; text-underline-offset: 4px; }
	237	+
	238	+/* ---- Tableaux → cartes empilées sous 768 px ---- */
	239	+.tbl-wrap { overflow-x: auto; -webkit-overflow-scrolling: touch; }
	240	+@media (max-width: 767px) {
	241	+ .tbl-stack thead { display: none; }
	242	+ .tbl-stack tr { display: block; border: 1.5px solid var(--ink); border-radius: var(--r-card); margin-bottom: var(--sp-3); background: var(--surface); }
	243	+ .tbl-stack td { display: flex; justify-content: space-between; gap: var(--sp-3); padding: 8px 12px; border: 0; }
	244	+ .tbl-stack td::before { content: attr(data-label); font-family: var(--font-mono); font-size: 10px; font-weight: 700; text-transform: uppercase; letter-spacing: 0.08em; color: var(--ink-3); }
	245	+}
	246	+
	247	+/* ---- Utilitaires responsive ---- */
	248	+.only-mobile { display: initial; } .only-desktop { display: none; }
	249	+@media (min-width: 768px) { .only-mobile { display: none; } .only-desktop { display: initial; } }
	250	+
	251	+/* =============================================================================
	252	+ SOCLE MOBILE OBLIGATOIRE (2026-08-19) — règles communes aux 13 sites.
	253	+ RÈGLES pour tout composant futur :
	254	+ · TAP, jamais :hover, pour ouvrir un menu (le survol n'existe pas au doigt) ;
	255	+ le :hover ne sert qu'aux effets décoratifs, sous @media (hover: hover).
	256	+ · var(--vh100) (dvh) et JAMAIS 100vh pour tout élément calé sur le viewport.
	257	+ · position:fixed exige qu'AUCUN ancêtre n'ait transform/filter/perspective/
	258	+ will-change/backdrop-filter — sinon monter l'élément à la racine (body).
	259	+ · Barre basse fixe = .ka-bottombar + classe has-bottombar sur <body>.
	260	+ · Menu/panneau ouvert = .ka-scroll-lock sur <html> (scroll arrière-plan gelé).
	261	+ · z-index : uniquement l'échelle --z-* ci-dessus.
	262	+ · Zones tactiles ≥ var(--touch) (44 px), champs ≥ 16 px (zoom iOS).
	263	+ ========================================================================== */
	264	+
	265	+/* Anti-zoom iOS : au doigt, aucun champ sous 16 px (le focus d'un champ <16 px
	266	+ déclenche un zoom automatique de page sur Safari iOS). !important assumé :
	267	+ c'est un filet d'accessibilité, un champ plus petit casse le zoom quoi
	268	+ qu'il arrive — ne s'applique qu'aux écrans tactiles. */
	269	+@media (hover: none) and (pointer: coarse) {
	270	+ input:not([type="checkbox"]):not([type="radio"]):not([type="range"]),
	271	+ select, textarea { font-size: max(16px, 1em) !important; }
	272	+}
	273	+
	274	+/* Zone tactile du badge Groupe KA étendue à ≥44 px au doigt, sans changer
	275	+ son rendu (débord de la zone cliquable via pseudo-élément). */
	276	+@media (pointer: coarse) {
	277	+ .gk-badge { position: relative; }
	278	+ .gk-badge::after { content: ""; position: absolute; inset: -8px; }
	279	+}
	280	+
	281	+/* Hauteurs viewport dynamiques */
	282	+.h-viewport { height: 100vh; height: 100dvh; }
	283	+.min-h-viewport { min-height: 100vh; min-height: 100dvh; }
	284	+
	285	+/* Barre fixe basse fiable : safe-area iPhone incluse, immunisée contre les
	286	+ transforms accidentels, et compensation d'espace via body.has-bottombar. */
	287	+.ka-bottombar {
	288	+ position: fixed; left: 0; right: 0; bottom: 0;
	289	+ z-index: var(--z-bottombar);
	290	+ padding-bottom: env(safe-area-inset-bottom, 0px);
	291	+ background: var(--surface);
	292	+ border-top: 1.5px solid var(--ink);
	293	+ transform: none !important; filter: none !important;
	294	+}
	295	+body.has-bottombar { padding-bottom: calc(var(--bottombar-h, 64px) + env(safe-area-inset-bottom, 0px)); }
	296	+
	297	+/* Verrou de scroll d'arrière-plan (menu mobile, modale, panneau de filtres
	298	+ ouverts) : ajouter/retirer .ka-scroll-lock sur <html>. */
	299	+html.ka-scroll-lock, html.ka-scroll-lock body { overflow: hidden !important; overscroll-behavior: none; }
	300	+
	301	+/* Menu déroulant de référence : au-dessus de tout contenu (cartes Mapbox
	302	+ incluses), défilement interne avec élan, jamais plus haut que l'écran. */
	303	+.ka-menu {
	304	+ position: absolute; z-index: var(--z-dropdown);
	305	+ min-width: 180px;
	306	+ max-height: min(60vh, 420px); max-height: min(60dvh, 420px);
	307	+ overflow-y: auto; -webkit-overflow-scrolling: touch; overscroll-behavior: contain;
	308	+ background: var(--surface); border: 1.5px solid var(--ink);
	309	+ border-radius: var(--r-card); box-shadow: var(--shadow-off-mid);
	310	+}
	311	+.ka-menu a, .ka-menu button, .ka-menu label, .ka-menu [role="menuitem"], .ka-menu [role="option"] {
	312	+ display: flex; align-items: center; min-height: var(--touch);
	313	+ padding: 10px 14px; width: 100%; text-decoration: none;
	314	+}
	315	+/* Voile plein écran sous une modale / un panneau */
	316	+.ka-overlay {
	317	+ position: fixed; inset: 0; z-index: var(--z-overlay);
	318	+ background: rgba(20, 24, 20, 0.45);
	319	+}

added frontend/src/kamaps/adapter.ts +96 −0

		`@@ -0,0 +1,96 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// Author: Simon-Pierre Boucher
	3	+// Contact: contact@spboucher.ai
	4	+// Project: Groupe Ka / Ka Maps (House-Ka integration)
	5	+// kamaps/adapter.ts : House-Ka → MapProperty adapter.
	6	+// -----------------------------------------------------------------------------
	7	+import type {
	8	+ BoundsQuery,
	9	+ BoundsQueryResult,
	10	+ KaDataAdapter,
	11	+ MapProperty,
	12	+} from "@groupe-ka/ka-maps";
	13	+import { bboxToString } from "@groupe-ka/ka-maps";
	14	+import type { ListingFilters } from "../api";
	15	+
	16	+interface HouseKaFeatureProps {
	17	+ uid: string;
	18	+ title: string \| null;
	19	+ address: string \| null;
	20	+ price: number \| null;
	21	+ price_label: string \| null;
	22	+ property_type: string \| null;
	23	+ bedrooms: number \| null;
	24	+ bathrooms: number \| null;
	25	+ source: string;
	26	+ city: string \| null;
	27	+ sector: string \| null;
	28	+ image: string \| null;
	29	+}
	30	+
	31	+interface HouseKaFC {
	32	+ type: "FeatureCollection";
	33	+ features: {
	34	+ geometry: { coordinates: [number, number] };
	35	+ properties: HouseKaFeatureProps;
	36	+ }[];
	37	+ totalGeocoded?: number;
	38	+ totalMatching?: number;
	39	+}
	40	+
	41	+function toMapProperty(
	42	+ coords: [number, number],
	43	+ p: HouseKaFeatureProps,
	44	+): MapProperty {
	45	+ return {
	46	+ id: p.uid,
	47	+ appSource: "house-ka",
	48	+ longitude: coords[0],
	49	+ latitude: coords[1],
	50	+ kind: "listing",
	51	+ listingType: "sale",
	52	+ price: p.price ?? undefined,
	53	+ propertyType: p.property_type ?? undefined,
	54	+ bedrooms: p.bedrooms ?? undefined,
	55	+ bathrooms: p.bathrooms ?? undefined,
	56	+ address: p.address ?? p.title ?? undefined,
	57	+ city: p.city ?? undefined,
	58	+ region: p.sector ?? undefined,
	59	+ thumbnailUrl: p.image ?? undefined,
	60	+ originalUrl: `/property/${encodeURIComponent(p.uid)}`,
	61	+ highlight: false,
	62	+ extra: {
	63	+ title: p.title,
	64	+ priceLabel: p.price_label,
	65	+ source: p.source,
	66	+ },
	67	+ };
	68	+}
	69	+
	70	+/** Viewport→data adapter for the House-Ka map. */
	71	+export const houseKaMapAdapter: KaDataAdapter = {
	72	+ id: "house-ka-listings",
	73	+ appSource: "house-ka",
	74	+ async fetchInBounds(query: BoundsQuery): Promise<BoundsQueryResult> {
	75	+ const params = new URLSearchParams();
	76	+ const filters = (query.filters ?? {}) as Partial<ListingFilters>;
	77	+ for (const [k, v] of Object.entries(filters)) {
	78	+ if (v && k !== "sort") params.set(k, String(v));
	79	+ }
	80	+ params.set("bbox", bboxToString(query.bbox));
	81	+ params.set("limit", "3000");
	82	+
	83	+ const res = await fetch(`/api/listings.geojson?${params}`, {
	84	+ signal: query.signal,
	85	+ });
	86	+ if (!res.ok) throw new Error(`Map: API ${res.status}`);
	87	+ const data = (await res.json()) as HouseKaFC;
	88	+
	89	+ return {
	90	+ properties: data.features.map((f) =>
	91	+ toMapProperty(f.geometry.coordinates, f.properties),
	92	+ ),
	93	+ totalCount: data.totalMatching,
	94	+ };
	95	+ },
	96	+};

added frontend/src/kamaps/config.ts +11 −0

		`@@ -0,0 +1,11 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// Author: Simon-Pierre Boucher
	3	+// Contact: contact@spboucher.ai
	4	+// Project: Groupe Ka / Ka Maps (Immo-Ka integration)
	5	+// kamaps/config.ts : jeton PUBLIC Mapbox (pk.…), surchargable au build via
	6	+// VITE_MAPBOX_TOKEN ; restrictions d'URL gérées côté tableau de bord Mapbox.
	7	+// -----------------------------------------------------------------------------
	8	+
	9	+export const MAPBOX_TOKEN: string =
	10	+ (import.meta.env.VITE_MAPBOX_TOKEN as string \| undefined) ??
	11	+ "pk.eyJ1Ijoic3Bib3VjaGVyIiwiYSI6ImNtc3Fyb3k4djAwOTgyenB3dWt6NHBjc2kifQ.poqLf0ADy3lIh28O-pFI2Q";

added frontend/src/kamaps/theme.ts +49 −0

		`@@ -0,0 +1,49 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// Author: Simon-Pierre Boucher
	3	+// Contact: contact@spboucher.ai
	4	+// Project: Groupe Ka / Ka Maps (House-Ka integration)
	5	+// kamaps/theme.ts : House-Ka Maps theme — pine green / cream / ink identity.
	6	+// Premium price pills: cream with ink text; the PINE #0f6b4f is reserved for
	7	+// brand moments (selection, controls, highlights).
	8	+// -----------------------------------------------------------------------------
	9	+import type { KaMapTheme } from "@groupe-ka/ka-maps";
	10	+
	11	+const INK = "#14201a";
	12	+const PINE = "#0f6b4f";
	13	+const CREAM = "#faf7f0";
	14	+const WHITE = "#ffffff";
	15	+
	16	+export const houseKaMapTheme: KaMapTheme = {
	17	+ id: "house-ka",
	18	+ productName: "House-Ka Maps",
	19	+ accent: PINE,
	20	+ onAccent: WHITE,
	21	+ fontFamily: '"Inter", system-ui, -apple-system, "Segoe UI", sans-serif',
	22	+ markers: {
	23	+ // Asking price: cream pill, ink text — readable without crushing the map.
	24	+ // Selection/hover: full ink, the absolute anchor.
	25	+ sale: {
	26	+ background: CREAM,
	27	+ text: INK,
	28	+ halo: "rgba(20, 32, 26, 0.30)",
	29	+ selectedBackground: INK,
	30	+ selectedText: WHITE,
	31	+ },
	32	+ // Highlighted listings: pine.
	33	+ highlight: {
	34	+ background: PINE,
	35	+ text: WHITE,
	36	+ halo: "rgba(255, 255, 255, 0.55)",
	37	+ selectedBackground: INK,
	38	+ selectedText: WHITE,
	39	+ },
	40	+ },
	41	+ cluster: {
	42	+ background: CREAM,
	43	+ text: INK,
	44	+ border: PINE,
	45	+ valueText: "#0a4a37",
	46	+ valueHalo: "rgba(250, 247, 240, 0.92)",
	47	+ },
	48	+ supportsDark: false,
	49	+};

added frontend/src/main.tsx +20 −0

		`@@ -0,0 +1,20 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	3	+// Author: Simon-Pierre Boucher — contact@spboucher.ai
	4	+// main.tsx : React entry point — Groupe KA tokens (ka/tokens.css) BEFORE the
	5	+// local CSS.
	6	+// -----------------------------------------------------------------------------
	7	+import React from "react";
	8	+import ReactDOM from "react-dom/client";
	9	+import { BrowserRouter } from "react-router-dom";
	10	+import App from "./App";
	11	+import "./ka/tokens.css";
	12	+import "./styles.css";
	13	+
	14	+ReactDOM.createRoot(document.getElementById("root")!).render(
	15	+ <React.StrictMode>
	16	+ <BrowserRouter>
	17	+ <App />
	18	+ </BrowserRouter>
	19	+ </React.StrictMode>
	20	+);

added frontend/src/pages/Agencies.tsx +91 −0

		`@@ -0,0 +1,91 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	3	+// Author: Simon-Pierre Boucher — contact@spboucher.ai
	4	+// pages/Agencies.tsx : brokerage registry — banner → brokerage (office)
	5	+// -----------------------------------------------------------------------------
	6	+import { useEffect, useState } from "react";
	7	+import { Link } from "react-router-dom";
	8	+import { Franchise, fetchAgencies } from "../api";
	9	+
	10	+export default function AgenciesPage() {
	11	+ const [data, setData] = useState<Franchise[] \| null>(null);
	12	+ const [error, setError] = useState<string \| null>(null);
	13	+ const [open, setOpen] = useState<Record<string, boolean>>({});
	14	+
	15	+ useEffect(() => {
	16	+ document.title = "Covered brokerages \| House-Ka";
	17	+ fetchAgencies().then((r) => setData(r.franchises)).catch((e) => setError(String(e)));
	18	+ }, []);
	19	+
	20	+ const totalProps = (data ?? []).reduce((s, f) => s + f.total, 0);
	21	+ const totalSub = (data ?? []).reduce((s, f) => s + f.sub_agencies, 0);
	22	+
	23	+ return (
	24	+ <div className="container sources">
	25	+ <span className="kicker">Registry — brokerages & offices</span>
	26	+ <h1>Sources by brokerage</h1>
	27	+ <p className="sub">
	28	+ Every covered brokerage or team publishes its board's full inventory
	29	+ through the CREA DDF feed. Each listing is synced by a dedicated
	30	+ connector and deduplicated by DDF number — the same property published
	31	+ on several sites is only counted once. Click a source to see its homes.
	32	+ </p>
	33	+
	34	+ {error && <div className="notice"> {error}</div>}
	35	+ {!data && !error && <div className="notice">Loading…</div>}
	36	+
	37	+ {data && (
	38	+ <>
	39	+ <p className="stats-foot" style={{ marginTop: 0 }}>
	40	+ <b>{totalProps.toLocaleString("en-CA")}</b> homes ·{" "}
	41	+ <b>{data.length}</b> banners ·{" "}
	42	+ <b>{totalSub.toLocaleString("en-CA")}</b> offices
	43	+ </p>
	44	+
	45	+ <div className="franchise-list">
	46	+ {data.map((f) => {
	47	+ const isOpen = open[f.franchise] ?? false;
	48	+ return (
	49	+ <div className="franchise" key={f.franchise}>
	50	+ <button
	51	+ className="franchise-head"
	52	+ onClick={() => setOpen({ ...open, [f.franchise]: !isOpen })}
	53	+ aria-expanded={isOpen}
	54	+ >
	55	+ <span className="fh-caret">{isOpen ? "▾" : "▸"}</span>
	56	+ <span className="fh-name">{f.franchise}</span>
	57	+ <span className="fh-sub">
	58	+ {f.sub_agencies} office{f.sub_agencies > 1 ? "s" : ""}
	59	+ </span>
	60	+ <span className="fh-count">{f.total.toLocaleString("en-CA")}</span>
	61	+ </button>
	62	+
	63	+ {isOpen && (
	64	+ <ul className="subagency-list">
	65	+ {f.agencies.map((a) => (
	66	+ <li key={a.name}>
	67	+ <span className="sa-name">{a.name}</span>
	68	+ <Link
	69	+ className="count-pill"
	70	+ to={`/?source=${encodeURIComponent(a.sources[0])}`}
	71	+ >
	72	+ {a.count.toLocaleString("en-CA")}
	73	+ </Link>
	74	+ </li>
	75	+ ))}
	76	+ </ul>
	77	+ )}
	78	+ </div>
	79	+ );
	80	+ })}
	81	+ </div>
	82	+
	83	+ <p className="stats-foot">
	84	+ Sites sharing the same CREA DDF pool also serve as backup sources,
	85	+ deduplicated by DDF number — no double counting.
	86	+ </p>
	87	+ </>
	88	+ )}
	89	+ </div>
	90	+ );
	91	+}

added frontend/src/pages/Contact.tsx +76 −0

		`@@ -0,0 +1,76 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	3	+// A Groupe-Ka application — contact@groupe-ka.com
	4	+// pages/Contact.tsx : shared Groupe KA contact page (English).
	5	+// -----------------------------------------------------------------------------
	6	+
	7	+const CONTACTS = [
	8	+ { role: "Projects and data", email: "contact@groupe-ka.com" },
	9	+ { role: "Media", email: "info@groupe-ka.com" },
	10	+ { role: "Legal and privacy", email: "admin@groupe-ka.com" },
	11	+];
	12	+
	13	+const SITES = [
	14	+ { wordmark: "Groupe·Ka", domain: "www.groupe-ka.com", tagline: "the Groupe KA portal" },
	15	+ { wordmark: "Immo·Ka", domain: "www.immo-ka.com", tagline: "homes for sale in Québec" },
	16	+ { wordmark: "Lou·Ka", domain: "www.lou-ka.com", tagline: "rentals in Québec" },
	17	+ { wordmark: "Vrai·Prix", domain: "www.vrai-prix.com", tagline: "Québec market-value estimates" },
	18	+ { wordmark: "Auto·Ka", domain: "www.auto-ka.com", tagline: "used cars" },
	19	+ { wordmark: "Job·Ka", domain: "www.job-ka.com", tagline: "job listings" },
	20	+];
	21	+
	22	+export default function ContactPage() {
	23	+ return (
	24	+ <div className="container contact">
	25	+ <span className="kicker">Contact</span>
	26	+ <h1>
	27	+ Write to <span className="hl">Groupe KA</span>
	28	+ </h1>
	29	+ <p className="lede">
	30	+ House-Ka is a service of <b>Groupe-Ka</b> — an ecosystem of data
	31	+ aggregators. All the platforms share the same contact channels.
	32	+ </p>
	33	+
	34	+ <div className="contact-cards">
	35	+ {CONTACTS.map((c) => (
	36	+ <a key={c.email} className="contact-card" href={`mailto:${c.email}`}>
	37	+ <span className="contact-role">{c.role}</span>
	38	+ <span className="contact-mail">{c.email}</span>
	39	+ </a>
	40	+ ))}
	41	+ </div>
	42	+
	43	+ <p className="contact-disclaimer">
	44	+ <b>House-Ka is an independent aggregator — it is not a brokerage and is
	45	+ not affiliated with the sources it indexes.</b> Every listing links back
	46	+ to the original page of the brokerage: for a specific property, contact
	47	+ the listing agent shown on the page directly.
	48	+ </p>
	49	+
	50	+ <div className="contact-hub">
	51	+ <a
	52	+ className="btn btn-primary"
	53	+ href="https://www.groupe-ka.com"
	54	+ target="_blank"
	55	+ rel="noopener noreferrer"
	56	+ >
	57	+ Visit the groupe-ka.com portal ↗
	58	+ </a>
	59	+ </div>
	60	+
	61	+ <section className="contact-sites">
	62	+ <h2>The ·Ka ecosystem</h2>
	63	+ <ul>
	64	+ {SITES.map((s) => (
	65	+ <li key={s.domain}>
	66	+ <a href={`https://${s.domain}`} target="_blank" rel="noopener noreferrer">
	67	+ <b>{s.wordmark}</b>
	68	+ <span>{s.tagline}</span>
	69	+ </a>
	70	+ </li>
	71	+ ))}
	72	+ </ul>
	73	+ </section>
	74	+ </div>
	75	+ );
	76	+}

added frontend/src/pages/Home.tsx +518 −0

		`@@ -0,0 +1,518 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	3	+// Author: Simon-Pierre Boucher — contact@spboucher.ai
	4	+// pages/Home.tsx : home — hero, live stats, advanced filters, grid + map
	5	+// -----------------------------------------------------------------------------
	6	+import { Suspense, lazy, useEffect, useMemo, useRef, useState } from "react";
	7	+import { useSearchParams } from "react-router-dom";
	8	+import {
	9	+ Facets, Listing, ListingFilters, Stats,
	10	+ fetchFacets, fetchListings, fetchSources, fetchStats,
	11	+ registerSourceNames, sourceName,
	12	+} from "../api";
	13	+import ListingCard from "../components/ListingCard";
	14	+import { Ico } from "../components/Icons";
	15	+
	16	+const MapView = lazy(() => import("../components/MapView"));
	17	+
	18	+const PRICE_STEPS = [100000, 200000, 300000, 400000, 500000, 600000, 750000, 1000000, 1500000, 2000000, 3000000];
	19	+const AREA_STEPS = [800, 1000, 1500, 2000, 3000];
	20	+const PAGE = 12;
	21	+
	22	+const fmtK = (n: number) =>
	23	+ n >= 1_000_000 ? `$${n / 1_000_000}M` : `$${Math.round(n / 1000)}k`;
	24	+
	25	+/** Animated hero counter (~0.9 s, cubic easing) — the feel of a real engine
	26	+ indexing. Respects prefers-reduced-motion (direct value). */
	27	+function useCountUp(target: number \| null \| undefined, ms = 900): string \| null {
	28	+ const [v, setV] = useState<number \| null>(null);
	29	+ useEffect(() => {
	30	+ if (target == null) return;
	31	+ if (window.matchMedia("(prefers-reduced-motion: reduce)").matches) { setV(target); return; }
	32	+ let raf = 0;
	33	+ const t0 = performance.now();
	34	+ const step = (t: number) => {
	35	+ const p = Math.min(1, (t - t0) / ms);
	36	+ setV(Math.round(target * (1 - Math.pow(1 - p, 3))));
	37	+ if (p < 1) raf = requestAnimationFrame(step);
	38	+ };
	39	+ raf = requestAnimationFrame(step);
	40	+ return () => cancelAnimationFrame(raf);
	41	+ }, [target, ms]);
	42	+ return v == null ? null : v.toLocaleString("en-CA");
	43	+}
	44	+
	45	+/** live "X s ago" — re-rendered every second while the ts exists. */
	46	+function useAgo(ts: number \| null): string \| null {
	47	+ const [, tick] = useState(0);
	48	+ useEffect(() => {
	49	+ if (ts == null) return;
	50	+ const id = setInterval(() => tick((x) => x + 1), 1000);
	51	+ return () => clearInterval(id);
	52	+ }, [ts]);
	53	+ if (ts == null) return null;
	54	+ const s = Math.max(0, Math.floor(Date.now() / 1000 - ts));
	55	+ if (s < 90) return `${s} s ago`;
	56	+ if (s < 5400) return `${Math.round(s / 60)} min ago`;
	57	+ return `${Math.round(s / 3600)} h ago`;
	58	+}
	59	+
	60	+// pagination window: 1 … (p-1) p (p+1) … N
	61	+function pageNumbers(p: number, n: number): (number \| "…")[] {
	62	+ if (n <= 7) return Array.from({ length: n }, (_, i) => i + 1);
	63	+ const out: (number \| "…")[] = [1];
	64	+ const lo = Math.max(2, p - 1), hi = Math.min(n - 1, p + 1);
	65	+ if (lo > 2) out.push("…");
	66	+ for (let i = lo; i <= hi; i++) out.push(i);
	67	+ if (hi < n - 1) out.push("…");
	68	+ out.push(n);
	69	+ return out;
	70	+}
	71	+
	72	+export default function Home() {
	73	+ const [listings, setListings] = useState<Listing[] \| null>(null);
	74	+ const [total, setTotal] = useState(0);
	75	+ const [params, setParams] = useSearchParams();
	76	+ const [page, setPage] = useState(Number(params.get("page")) \|\| 1); // 12/page, in the URL
	77	+ const [facets, setFacets] = useState<Facets \| null>(null);
	78	+ const [sectors, setSectors] = useState<string[]>([]);
	79	+ const [stats, setStats] = useState<Stats \| null>(null);
	80	+ const [error, setError] = useState<string \| null>(null);
	81	+ const [q, setQ] = useState(params.get("q") ?? "");
	82	+ const [city, setCity] = useState(params.get("city") ?? "");
	83	+ const [sector, setSector] = useState(params.get("sector") ?? "");
	84	+ const [ptype, setPtype] = useState(params.get("property_type") ?? "");
	85	+ const [source, setSource] = useState(params.get("source") ?? "");
	86	+ const [priceMin, setPriceMin] = useState(params.get("price_min") ?? "");
	87	+ const [priceMax, setPriceMax] = useState(params.get("price_max") ?? "");
	88	+ const [bedsMin, setBedsMin] = useState(params.get("bedrooms_min") ?? "");
	89	+ const [bathsMin, setBathsMin] = useState(params.get("bathrooms_min") ?? "");
	90	+ const [areaMin, setAreaMin] = useState(params.get("area_min") ?? "");
	91	+ const [sort, setSort] = useState(params.get("sort") ?? "recent");
	92	+
	93	+ const [sheetOpen, setSheetOpen] = useState(false);
	94	+ const [advOpen, setAdvOpen] = useState(false);
	95	+
	96	+ // Filter bottom-sheet: background scroll lock + Escape to close
	97	+ // (same rules as the header mobile menu — see App.tsx).
	98	+ useEffect(() => {
	99	+ if (!sheetOpen) return;
	100	+ document.body.style.overflow = "hidden";
	101	+ const onKey = (e: KeyboardEvent) => { if (e.key === "Escape") setSheetOpen(false); };
	102	+ window.addEventListener("keydown", onKey);
	103	+ return () => {
	104	+ document.body.style.overflow = "";
	105	+ window.removeEventListener("keydown", onKey);
	106	+ };
	107	+ }, [sheetOpen]);
	108	+ const activeFilters = [q, city, sector, ptype, source, priceMin, priceMax, bedsMin, bathsMin, areaMin].filter(Boolean).length;
	109	+ const advCount = [bedsMin, bathsMin, areaMin, source, sector].filter(Boolean).length;
	110	+
	111	+ const [view, setView] = useState<"list" \| "map">(params.get("view") === "map" ? "map" : "list");
	112	+ useEffect(() => { setView(params.get("view") === "map" ? "map" : "list"); }, [params]);
	113	+
	114	+ // map mode (Ka Map System v2): body class — the page's filter sheet becomes
	115	+ // a modal ABOVE the full-viewport shell.
	116	+ useEffect(() => {
	117	+ document.body.classList.toggle("ka-map-mode", view === "map");
	118	+ return () => document.body.classList.remove("ka-map-mode");
	119	+ }, [view]);
	120	+
	121	+ const filters: ListingFilters = useMemo(() => ({
	122	+ q, city, sector, region: "", property_type: ptype, source,
	123	+ price_min: priceMin, price_max: priceMax,
	124	+ bedrooms_min: bedsMin, bathrooms_min: bathsMin, area_min: areaMin, sort,
	125	+ }), [q, city, sector, ptype, source, priceMin, priceMax, bedsMin, bathsMin, areaMin, sort]);
	126	+
	127	+ useEffect(() => {
	128	+ fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});
	129	+ fetchFacets().then(setFacets).catch(() => {});
	130	+ fetchStats().then(setStats).catch(() => {});
	131	+ }, []);
	132	+
	133	+ useEffect(() => {
	134	+ fetchFacets(city \|\| undefined).then((f) => setSectors(f.sectors)).catch(() => setSectors([]));
	135	+ }, [city]);
	136	+
	137	+ // back to page 1 whenever the filters change
	138	+ const firstRender = useRef(true);
	139	+ useEffect(() => {
	140	+ if (firstRender.current) { firstRender.current = false; return; }
	141	+ setPage(1);
	142	+ }, [filters]);
	143	+
	144	+ // sync filters + page + sort + view into the URL → going back from a
	145	+ // listing returns to the SAME page/filters.
	146	+ useEffect(() => {
	147	+ const p = new URLSearchParams();
	148	+ const set = (k: string, v: string) => { if (v) p.set(k, v); };
	149	+ set("q", q); set("city", city); set("sector", sector);
	150	+ set("property_type", ptype); set("source", source);
	151	+ set("price_min", priceMin); set("price_max", priceMax);
	152	+ set("bedrooms_min", bedsMin); set("bathrooms_min", bathsMin);
	153	+ set("area_min", areaMin);
	154	+ if (sort && sort !== "recent") p.set("sort", sort);
	155	+ if (view === "map") p.set("view", "map");
	156	+ if (page > 1) p.set("page", String(page));
	157	+ setParams(p, { replace: true });
	158	+ }, [filters, page, view, q, city, sector, ptype, source, priceMin, priceMax,
	159	+ bedsMin, bathsMin, areaMin, sort, setParams]);
	160	+
	161	+ // load the current page (12 listings) — replaces the grid
	162	+ useEffect(() => {
	163	+ let cancelled = false;
	164	+ setListings(null); setError(null);
	165	+ fetchListings(filters, PAGE, (page - 1) * PAGE)
	166	+ .then((r) => { if (!cancelled) { setListings(r.listings); setTotal(r.total); } })
	167	+ .catch((e) => !cancelled && setError(String(e)));
	168	+ return () => { cancelled = true; };
	169	+ }, [filters, page]);
	170	+
	171	+ const totalPages = Math.max(1, Math.ceil(total / PAGE));
	172	+ const gotoPage = (p: number) => {
	173	+ setPage(Math.min(Math.max(1, p), totalPages));
	174	+ if (view === "map") return; // the map-mode pane manages its own scrolling
	175	+ document.getElementById("results-top")?.scrollIntoView({ behavior: "smooth", block: "start" });
	176	+ };
	177	+
	178	+ const resetAll = () => {
	179	+ setQ(""); setCity(""); setSector(""); setPtype(""); setSource("");
	180	+ setPriceMin(""); setPriceMax(""); setBedsMin(""); setBathsMin(""); setAreaMin("");
	181	+ };
	182	+
	183	+ // live hero data — real connector syncs (recent_syncs)
	184	+ const totalLive = useCountUp(stats?.total);
	185	+ const lastSync = useMemo(() => {
	186	+ const ss = stats?.recent_syncs ?? [];
	187	+ if (!ss.length) return null;
	188	+ const ts = Math.max(...ss.map((s) => s.ts));
	189	+ return ts > 1e12 ? Math.round(ts / 1000) : ts;
	190	+ }, [stats]);
	191	+ const syncAgo = useAgo(lastSync);
	192	+ const newToday = useMemo(() => {
	193	+ const ss = stats?.recent_syncs ?? [];
	194	+ const now = Date.now() / 1000;
	195	+ return ss
	196	+ .filter((s) => (s.ts > 1e12 ? s.ts / 1000 : s.ts) > now - 86400)
	197	+ .reduce((n, s) => n + (s.added \|\| 0), 0);
	198	+ }, [stats]);
	199	+
	200	+ const pills: { label: string; clear: () => void }[] = [];
	201	+ if (q) pills.push({ label: `“${q}”`, clear: () => setQ("") });
	202	+ if (city) pills.push({ label: city, clear: () => { setCity(""); setSector(""); } });
	203	+ if (sector) pills.push({ label: sector, clear: () => setSector("") });
	204	+ if (ptype) pills.push({ label: ptype, clear: () => setPtype("") });
	205	+ if (priceMin) pills.push({ label: `≥ ${fmtK(Number(priceMin))}`, clear: () => setPriceMin("") });
	206	+ if (priceMax) pills.push({ label: `≤ ${fmtK(Number(priceMax))}`, clear: () => setPriceMax("") });
	207	+ if (bedsMin) pills.push({ label: `${bedsMin}+ bed`, clear: () => setBedsMin("") });
	208	+ if (bathsMin) pills.push({ label: `${bathsMin}+ bath`, clear: () => setBathsMin("") });
	209	+ if (areaMin) pills.push({ label: `≥ ${areaMin} sq ft`, clear: () => setAreaMin("") });
	210	+ if (source) pills.push({ label: sourceName(source), clear: () => setSource("") });
	211	+
	212	+ const topTypes = (facets?.property_types ?? []).slice(0, 7);
	213	+
	214	+ return (
	215	+ <div className="container">
	216	+ <section className="hero">
	217	+ <div className="hero-wrap">
	218	+ <div className="hero-main">
	219	+ <span className="kicker">Aggregator — Canadian brokerages, Ontario first</span>
	220	+ <h1 className="hero-display" aria-label="Every home for sale. One place.">
	221	+ <span className="hd-l1" aria-hidden="true">Every home</span>
	222	+ <span className="hd-l2" aria-hidden="true">for sale.</span>
	223	+ <span className="hd-l4" aria-hidden="true">One <em className="signal">place</em>.</span>
	224	+ </h1>
	225	+ <p className="lede">
	226	+ Homes listed by Canadian real-estate brokerages and teams on the
	227	+ CREA DDF feed — aggregated continuously, full photos and details,
	228	+ direct link to the original listing. Ontario today, the rest of
	229	+ Canada next.
	230	+ </p>
	231	+ <div className="live-line" aria-label="Live data">
	232	+ <span className="live-flag"><span className="live-dot" /> live</span>
	233	+ {syncAgo && <span className="live-item">synced {syncAgo}</span>}
	234	+ {newToday > 0 && (
	235	+ <span className="live-item"><b>+{newToday.toLocaleString("en-CA")}</b> today</span>
	236	+ )}
	237	+ {stats && stats.sources > 0 && (
	238	+ <span className="live-item"><b>{stats.sources}</b> sources</span>
	239	+ )}
	240	+ </div>
	241	+ </div>
	242	+ <aside className="hero-data" aria-label="The market in numbers">
	243	+ <div className="hd-row">
	244	+ <b>{totalLive ?? "—"}</b><span>homes indexed</span>
	245	+ </div>
	246	+ {stats && stats.cities != null && (
	247	+ <div className="hd-row">
	248	+ <b>{stats.cities.toLocaleString("en-CA")}</b><span>cities & towns</span>
	249	+ </div>
	250	+ )}
	251	+ {stats?.avg_price != null && (
	252	+ <div className="hd-row">
	253	+ <b>${Math.round(stats.avg_price).toLocaleString("en-CA")}</b><span>average price</span>
	254	+ </div>
	255	+ )}
	256	+ {stats?.max_price != null && (
	257	+ <div className="hd-row">
	258	+ <b>{fmtK(stats.max_price)}</b><span>highest price</span>
	259	+ </div>
	260	+ )}
	261	+ </aside>
	262	+ </div>
	263	+ </section>
	264	+
	265	+ {sheetOpen && <div className="sheet-backdrop" onClick={() => setSheetOpen(false)} aria-hidden="true" />}
	266	+ <section className={`search-zone ${sheetOpen ? "open" : ""}`} aria-label="Search and filters">
	267	+ <div className="sheet-handle" aria-hidden="true" />
	268	+ <div className="sheet-head">
	269	+ <span>Refine your search</span>
	270	+ <button className="sheet-close" onClick={() => setSheetOpen(false)} aria-label="Close the filters">✕</button>
	271	+ </div>
	272	+
	273	+ {/* — search, the heart of the product: one large underlined field — */}
	274	+ <div className="q-big">
	275	+ <svg width="22" height="22" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2" aria-hidden="true">
	276	+ <circle cx="11" cy="11" r="7" /><path d="m20 20-3.5-3.5" />
	277	+ </svg>
	278	+ <input id="f-q" placeholder="Where do you want to live?" value={q}
	279	+ onChange={(e) => setQ(e.target.value)}
	280	+ aria-label="Search — address, city or MLS number" />
	281	+ {q && <button className="f-clear" onClick={() => setQ("")} aria-label="Clear the search">✕</button>}
	282	+ </div>
	283	+
	284	+ {/* — inline criteria, separated by hairlines (no boxes) — */}
	285	+ <div className="crit-line">
	286	+ <label className="crit">
	287	+ <span>City</span>
	288	+ <select value={city} onChange={(e) => { setCity(e.target.value); setSector(""); }}>
	289	+ <option value="">All</option>
	290	+ {(facets?.cities ?? []).map((c) => <option key={c} value={c}>{c}</option>)}
	291	+ </select>
	292	+ </label>
	293	+ <label className="crit">
	294	+ <span>Type</span>
	295	+ <select value={ptype} onChange={(e) => setPtype(e.target.value)}>
	296	+ <option value="">All</option>
	297	+ {(facets?.property_types ?? []).map((t) => <option key={t} value={t}>{t}</option>)}
	298	+ </select>
	299	+ </label>
	300	+ <div className="crit">
	301	+ <span>Price</span>
	302	+ <div className="range-pair">
	303	+ <select aria-label="Minimum price" value={priceMin} onChange={(e) => setPriceMin(e.target.value)}>
	304	+ <option value="">Min</option>
	305	+ {PRICE_STEPS.map((p) => (
	306	+ <option key={p} value={p} disabled={!!priceMax && p >= Number(priceMax)}>{fmtK(p)}</option>
	307	+ ))}
	308	+ </select>
	309	+ <span className="range-sep">—</span>
	310	+ <select aria-label="Maximum price" value={priceMax} onChange={(e) => setPriceMax(e.target.value)}>
	311	+ <option value="">Max</option>
	312	+ {PRICE_STEPS.map((p) => (
	313	+ <option key={p} value={p} disabled={!!priceMin && p <= Number(priceMin)}>{fmtK(p)}</option>
	314	+ ))}
	315	+ </select>
	316	+ </div>
	317	+ </div>
	318	+ <button className={`crit-more ${advOpen \|\| advCount > 0 ? "on" : ""}`} onClick={() => setAdvOpen(!advOpen)} aria-expanded={advOpen}>
	319	+ All criteria
	320	+ {advCount > 0 && <span className="crit-badge">{advCount}</span>}
	321	+ <span className={`f-chev${advOpen ? " up" : ""}`} aria-hidden="true" />
	322	+ </button>
	323	+ </div>
	324	+
	325	+ {(advOpen \|\| sheetOpen) && (
	326	+ <div className="f-adv">
	327	+ <div className="f-group">
	328	+ <label>Neighbourhood / area</label>
	329	+ <select className="f-native" value={sector} onChange={(e) => setSector(e.target.value)}>
	330	+ <option value="">All</option>
	331	+ {sectors.map((s) => <option key={s} value={s}>{s}</option>)}
	332	+ </select>
	333	+ </div>
	334	+ <div className="f-group">
	335	+ <label>Bedrooms (min.)</label>
	336	+ <div className="seg" role="group">
	337	+ <button className={bedsMin === "" ? "on" : ""} onClick={() => setBedsMin("")}>Any</button>
	338	+ {["1", "2", "3", "4", "5"].map((n) => (
	339	+ <button key={n} className={bedsMin === n ? "on" : ""} onClick={() => setBedsMin(n)}>{n}+</button>
	340	+ ))}
	341	+ </div>
	342	+ </div>
	343	+ <div className="f-group">
	344	+ <label>Bathrooms (min.)</label>
	345	+ <div className="seg" role="group">
	346	+ <button className={bathsMin === "" ? "on" : ""} onClick={() => setBathsMin("")}>Any</button>
	347	+ {["1", "2", "3"].map((n) => (
	348	+ <button key={n} className={bathsMin === n ? "on" : ""} onClick={() => setBathsMin(n)}>{n}+</button>
	349	+ ))}
	350	+ </div>
	351	+ </div>
	352	+ <div className="f-group">
	353	+ <label>Minimum living area</label>
	354	+ <div className="seg" role="group">
	355	+ <button className={areaMin === "" ? "on" : ""} onClick={() => setAreaMin("")}>Any</button>
	356	+ {AREA_STEPS.map((a) => (
	357	+ <button key={a} className={areaMin === String(a) ? "on" : ""} onClick={() => setAreaMin(String(a))}>{a}+</button>
	358	+ ))}
	359	+ </div>
	360	+ </div>
	361	+ <div className="f-group">
	362	+ <label>Source</label>
	363	+ <select className="f-native" value={source} onChange={(e) => setSource(e.target.value)}>
	364	+ <option value="">All</option>
	365	+ {(facets?.sources ?? []).map((s) => (
	366	+ <option key={s.source} value={s.source}>{sourceName(s.source)} ({s.n})</option>
	367	+ ))}
	368	+ </select>
	369	+ </div>
	370	+ <div className="f-group f-group-end">
	371	+ <button className="btn btn-ghost" onClick={resetAll} disabled={activeFilters === 0}>
	372	+ Reset everything{activeFilters > 0 ? ` (${activeFilters})` : ""}
	373	+ </button>
	374	+ </div>
	375	+ </div>
	376	+ )}
	377	+
	378	+ <button className="btn btn-primary sheet-apply" onClick={() => setSheetOpen(false)}>
	379	+ See {listings ? `the ${total.toLocaleString("en-CA")} homes` : "the results"}
	380	+ </button>
	381	+ </section>
	382	+
	383	+ {/* mobile: criteria summary — opens the sheet (search built in, no FAB) */}
	384	+ <button className="crit-summary" onClick={() => setSheetOpen(true)}>
	385	+ <svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2.2" strokeLinecap="round" aria-hidden="true">
	386	+ <path d="M21 4h-7M10 4H3M21 12h-9M8 12H3M21 20h-5M12 20H3M14 2v4M8 10v4M16 18v4" />
	387	+ </svg>
	388	+ <span className="cs-txt">
	389	+ {pills.length > 0
	390	+ ? pills.slice(0, 3).map((p) => p.label).join(" · ") + (pills.length > 3 ? ` · +${pills.length - 3}` : "")
	391	+ : "City, type, price, bedrooms…"}
	392	+ </span>
	393	+ <span className="f-chev" aria-hidden="true" />
	394	+ </button>
	395	+
	396	+ <div className="chips" role="group" aria-label="Quick filters">
	397	+ {topTypes.map((t) => (
	398	+ <button key={t} className={`chip ${ptype === t ? "on" : ""}`} onClick={() => setPtype(ptype === t ? "" : t)}>
	399	+ {t}
	400	+ </button>
	401	+ ))}
	402	+ </div>
	403	+
	404	+ {pills.length > 0 && (
	405	+ <div className="pills" aria-label="Active filters">
	406	+ {pills.map((p) => (
	407	+ <button key={p.label} className="pill" onClick={p.clear} aria-label={`Remove the filter ${p.label}`}>
	408	+ {p.label} <span className="pill-x">✕</span>
	409	+ </button>
	410	+ ))}
	411	+ <button className="pill pill-clear" onClick={resetAll}>Clear all</button>
	412	+ </div>
	413	+ )}
	414	+
	415	+ <div className="results-bar" id="results-top">
	416	+ <h2 className="rb-count">
	417	+ {listings
	418	+ ? <><b>{total.toLocaleString("en-CA")}</b> home{total > 1 ? "s" : ""}</>
	419	+ : "Homes"}
	420	+ </h2>
	421	+ <div className="rb-tools">
	422	+ <label className="rb-sort">
	423	+ <select value={sort} onChange={(e) => setSort(e.target.value)} aria-label="Sort">
	424	+ <option value="recent">Newest</option>
	425	+ <option value="price_asc">Price: low to high</option>
	426	+ <option value="price_desc">Price: high to low</option>
	427	+ </select>
	428	+ </label>
	429	+ <div className="rb-tabs" role="tablist" aria-label="Display mode">
	430	+ <button role="tab" aria-selected={view === "list"} className={`rb-tab ${view === "list" ? "on" : ""}`} onClick={() => setView("list")}>
	431	+ <svg width="13" height="13" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2.2" strokeLinecap="round" aria-hidden="true">
	432	+ <path d="M8 6h13M8 12h13M8 18h13M3.5 6h.01M3.5 12h.01M3.5 18h.01" />
	433	+ </svg>
	434	+ List
	435	+ </button>
	436	+ <button role="tab" aria-selected={view === "map"} className={`rb-tab ${view === "map" ? "on" : ""}`} onClick={() => setView("map")}>
	437	+ <Ico name="map" size={13} /> Map
	438	+ </button>
	439	+ </div>
	440	+ <button className="rb-filters" onClick={() => setSheetOpen(true)}>
	441	+ <svg width="13" height="13" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2.2" strokeLinecap="round" aria-hidden="true">
	442	+ <path d="M21 4h-7M10 4H3M21 12h-9M8 12H3M21 20h-5M12 20H3M14 2v4M8 10v4M16 18v4" />
	443	+ </svg>
	444	+ Filters
	445	+ {activeFilters > 0 && <span className="rb-badge">{activeFilters}</span>}
	446	+ </button>
	447	+ </div>
	448	+ </div>
	449	+
	450	+ {error && (
	451	+ <div className="notice">
	452	+ <div className="big"><Ico name="alert" size={40} /></div>
	453	+ <h2>Could not load the listings</h2>
	454	+ <p>{error}</p>
	455	+ <button className="btn btn-primary" onClick={() => window.location.reload()}>Try again</button>
	456	+ </div>
	457	+ )}
	458	+
	459	+ {!error && view === "list" && listings === null && (
	460	+ <div className="grid grid-edito" aria-busy="true">
	461	+ {Array.from({ length: 8 }).map((_, i) => (
	462	+ <div className="skel" key={i}><div className="sk-img" /><div className="sk-line" /><div className="sk-line short" /></div>
	463	+ ))}
	464	+ </div>
	465	+ )}
	466	+
	467	+ {!error && view === "list" && listings !== null && listings.length === 0 && (
	468	+ <div className="notice">
	469	+ <div className="big"><Ico name="search" size={40} /></div>
	470	+ <h2>No home matches</h2>
	471	+ <p>Try widening your criteria
	472	+ {activeFilters > 0 && <> — or <button className="link-btn" onClick={resetAll}>remove the {activeFilters} active filters</button></>}.</p>
	473	+ </div>
	474	+ )}
	475	+
	476	+ {!error && view === "map" && (
	477	+ <div className="view-pane" key="map">
	478	+ <Suspense fallback={<div className="ka-shell-fallback">Loading the map…</div>}>
	479	+ <MapView
	480	+ filters={filters}
	481	+ listings={listings}
	482	+ total={total}
	483	+ page={page}
	484	+ totalPages={totalPages}
	485	+ onPage={gotoPage}
	486	+ sort={sort}
	487	+ onSort={setSort}
	488	+ onExit={() => setView("list")}
	489	+ onOpenFilters={() => setSheetOpen(true)}
	490	+ filtersCount={activeFilters}
	491	+ />
	492	+ </Suspense>
	493	+ </div>
	494	+ )}
	495	+
	496	+ {!error && view === "list" && listings !== null && listings.length > 0 && (
	497	+ <div className="view-pane">
	498	+ <div className="grid grid-edito">
	499	+ {listings.map((l) => <ListingCard key={l.uid} l={l} />)}
	500	+ </div>
	501	+ {totalPages > 1 && (
	502	+ <nav className="pager" aria-label="Pagination">
	503	+ <button className="pager-btn" onClick={() => gotoPage(page - 1)} disabled={page <= 1}>‹ Prev</button>
	504	+ {pageNumbers(page, totalPages).map((p, i) =>
	505	+ p === "…"
	506	+ ? <span key={`e${i}`} className="pager-gap">…</span>
	507	+ : <button key={p} className={`pager-btn ${p === page ? "on" : ""}`}
	508	+ onClick={() => gotoPage(p as number)}>{p}</button>
	509	+ )}
	510	+ <button className="pager-btn" onClick={() => gotoPage(page + 1)} disabled={page >= totalPages}>Next ›</button>
	511	+ <span className="pager-info">Page {page} / {totalPages}</span>
	512	+ </nav>
	513	+ )}
	514	+ </div>
	515	+ )}
	516	+ </div>
	517	+ );
	518	+}

added frontend/src/pages/Legal.tsx +114 −0

		`@@ -0,0 +1,114 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	3	+// Author: Simon-Pierre Boucher — contact@spboucher.ai
	4	+// pages/Legal.tsx : Terms of use + Privacy policy (PIPEDA)
	5	+// -----------------------------------------------------------------------------
	6	+import { useEffect } from "react";
	7	+
	8	+function LegalShell({ title, children }: { title: string; children: React.ReactNode }) {
	9	+ useEffect(() => { document.title = `${title} \| House-Ka`; window.scrollTo(0, 0); }, [title]);
	10	+ return (
	11	+ <div className="container legal">
	12	+ <span className="kicker">Legal</span>
	13	+ <h1>{title}</h1>
	14	+ {children}
	15	+ </div>
	16	+ );
	17	+}
	18	+
	19	+export function TermsPage() {
	20	+ return (
	21	+ <LegalShell title="Terms of use">
	22	+ <p className="legal-date">Last updated: August 27, 2026</p>
	23	+
	24	+ <h2>1. What House-Ka is</h2>
	25	+ <p>
	26	+ House-Ka (www.house-ka.com) is an <b>independent aggregator</b> of
	27	+ homes publicly listed for sale by Canadian real-estate brokerages and
	28	+ teams, operated by Groupe-Ka. House-Ka is <b>not a real-estate
	29	+ brokerage</b>, does not represent buyers or sellers, provides no
	30	+ brokerage services, and is not affiliated with, endorsed by, or
	31	+ sponsored by any of the sources it indexes.
	32	+ </p>
	33	+
	34	+ <h2>2. Nature of the information</h2>
	35	+ <p>
	36	+ Listings, prices, photos, descriptions and availability are those
	37	+ publicly displayed by each source at the time of synchronization. They
	38	+ may be incomplete, outdated or inaccurate. Every listing links back to
	39	+ the source's original page, which alone is authoritative. Market
	40	+ statistics and mortgage figures are provided for information only and
	41	+ constitute neither professional advice nor a financing offer.
	42	+ </p>
	43	+
	44	+ <h2>3. Permitted use</h2>
	45	+ <p>
	46	+ The site is offered for personal, non-commercial use. Automated
	47	+ scraping of House-Ka, republishing of its aggregated database, or any
	48	+ use that disrupts the service is prohibited. Trademarks and photos
	49	+ remain the property of their respective owners.
	50	+ </p>
	51	+
	52	+ <h2>4. Liability</h2>
	53	+ <p>
	54	+ The service is provided “as is”, without warranty of any kind.
	55	+ Groupe-Ka cannot be held liable for decisions made on the basis of the
	56	+ information displayed, for source errors, or for service
	57	+ interruptions. For any transaction, verify the information with the
	58	+ listing brokerage and the appropriate professionals.
	59	+ </p>
	60	+
	61	+ <h2>5. Removal requests</h2>
	62	+ <p>
	63	+ A brokerage or rights holder who wishes a listing or a source to be
	64	+ removed can write to <a href="mailto:admin@groupe-ka.com">admin@groupe-ka.com</a> —
	65	+ requests are honoured promptly.
	66	+ </p>
	67	+
	68	+ <h2>6. Contact</h2>
	69	+ <p>
	70	+ Groupe-Ka — <a href="mailto:contact@groupe-ka.com">contact@groupe-ka.com</a>.
	71	+ </p>
	72	+ </LegalShell>
	73	+ );
	74	+}
	75	+
	76	+export function PrivacyPage() {
	77	+ return (
	78	+ <LegalShell title="Privacy policy">
	79	+ <p className="legal-date">Last updated: August 27, 2026</p>
	80	+
	81	+ <h2>1. What we collect</h2>
	82	+ <p>
	83	+ House-Ka can be browsed without an account and without providing any
	84	+ personal information. Our servers keep standard technical logs
	85	+ (IP address, pages requested, user agent) for security and capacity
	86	+ purposes, retained for a limited time.
	87	+ </p>
	88	+
	89	+ <h2>2. What we do not do</h2>
	90	+ <p>
	91	+ No sale or sharing of personal information, no advertising trackers,
	92	+ no profiling. Third-party map tiles (Mapbox) and listing photos are
	93	+ loaded from their providers, which may see your IP address as with any
	94	+ website.
	95	+ </p>
	96	+
	97	+ <h2>3. Listing data</h2>
	98	+ <p>
	99	+ The property information displayed comes from listings publicly
	100	+ published by brokerages. Agent names and business phone numbers shown
	101	+ on listings are professional contact details published by the source.
	102	+ Removal requests: <a href="mailto:admin@groupe-ka.com">admin@groupe-ka.com</a>.
	103	+ </p>
	104	+
	105	+ <h2>4. Your rights (PIPEDA)</h2>
	106	+ <p>
	107	+ In accordance with the Personal Information Protection and Electronic
	108	+ Documents Act, you may ask what information we hold about you, request
	109	+ a correction or deletion, by writing to{" "}
	110	+ <a href="mailto:admin@groupe-ka.com">admin@groupe-ka.com</a>.
	111	+ </p>
	112	+ </LegalShell>
	113	+ );
	114	+}

added frontend/src/pages/Listing.tsx +444 −0

		`@@ -0,0 +1,444 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	3	+// Author: Simon-Pierre Boucher — contact@spboucher.ai
	4	+// pages/Listing.tsx : full listing page
	5	+// gallery + lightbox · specs · details (DDF fields) · rooms ·
	6	+// features · description · price history · agent · mini-map · financing
	7	+// -----------------------------------------------------------------------------
	8	+import { Suspense, lazy, useEffect, useRef, useState } from "react";
	9	+import { Link, useParams } from "react-router-dom";
	10	+import {
	11	+ Listing, Room, fetchListing, fetchSources, fmtArea, fmtDate, fmtPrice,
	12	+ registerSourceNames, sourceName,
	13	+} from "../api";
	14	+
	15	+const PropertyMap = lazy(() => import("../components/PropertyMap"));
	16	+import Financing from "../components/Financing";
	17	+import NearbyPlaces from "../components/NearbyPlaces";
	18	+import { Ico } from "../components/Icons";
	19	+import AmenityIco from "../components/AmenityIco";
	20	+import { TypeFallback } from "../components/PropertyImg";
	21	+
	22	+// --- Lightbox: pinch to zoom + pan + swipe between photos ---------------------
	23	+function ZoomImg({ src, onSwipe }: { src: string; onSwipe: (dir: 1 \| -1) => void }) {
	24	+ const [t, setT] = useState({ scale: 1, x: 0, y: 0 });
	25	+ const pointers = useRef(new Map<number, { x: number; y: number }>());
	26	+ const start = useRef({ scale: 1, x: 0, y: 0, dist: 0, cx: 0, cy: 0, t: 0 });
	27	+ const lastTap = useRef(0);
	28	+
	29	+ // reset when the photo changes
	30	+ useEffect(() => { setT({ scale: 1, x: 0, y: 0 }); }, [src]);
	31	+
	32	+ const dist = () => {
	33	+ const p = [...pointers.current.values()];
	34	+ return p.length < 2 ? 0 : Math.hypot(p[0].x - p[1].x, p[0].y - p[1].y);
	35	+ };
	36	+ const center = () => {
	37	+ const p = [...pointers.current.values()];
	38	+ return p.length < 2
	39	+ ? p[0] ?? { x: 0, y: 0 }
	40	+ : { x: (p[0].x + p[1].x) / 2, y: (p[0].y + p[1].y) / 2 };
	41	+ };
	42	+
	43	+ const onDown = (e: React.PointerEvent) => {
	44	+ (e.target as HTMLElement).setPointerCapture(e.pointerId);
	45	+ pointers.current.set(e.pointerId, { x: e.clientX, y: e.clientY });
	46	+ const c = center();
	47	+ start.current = { scale: t.scale, x: t.x, y: t.y, dist: dist(), cx: c.x, cy: c.y, t: Date.now() };
	48	+ };
	49	+ const onMove = (e: React.PointerEvent) => {
	50	+ if (!pointers.current.has(e.pointerId)) return;
	51	+ pointers.current.set(e.pointerId, { x: e.clientX, y: e.clientY });
	52	+ const s = start.current;
	53	+ if (pointers.current.size >= 2 && s.dist > 0) {
	54	+ // pinch: zoom around the two-finger midpoint
	55	+ const scale = Math.min(4, Math.max(1, (dist() / s.dist) * s.scale));
	56	+ const c = center();
	57	+ setT({ scale, x: s.x + (c.x - s.cx), y: s.y + (c.y - s.cy) });
	58	+ } else if (pointers.current.size === 1 && t.scale > 1) {
	59	+ // pan once zoomed
	60	+ const p = pointers.current.get(e.pointerId)!;
	61	+ setT({ scale: t.scale, x: s.x + (p.x - s.cx), y: s.y + (p.y - s.cy) });
	62	+ }
	63	+ };
	64	+ const onUp = (e: React.PointerEvent) => {
	65	+ const p = pointers.current.get(e.pointerId);
	66	+ pointers.current.delete(e.pointerId);
	67	+ const s = start.current;
	68	+ if (pointers.current.size === 0 && p) {
	69	+ const dx = p.x - s.cx, dy = p.y - s.cy, dt = Date.now() - s.t;
	70	+ if (t.scale <= 1.05 && Math.abs(dx) > 56 && Math.abs(dx) > Math.abs(dy) * 1.5) {
	71	+ onSwipe(dx < 0 ? 1 : -1); // swipe → next photo
	72	+ } else if (dt < 260 && Math.abs(dx) < 8 && Math.abs(dy) < 8) {
	73	+ const now = Date.now();
	74	+ if (now - lastTap.current < 320) // double-tap: ×2.4 zoom
	75	+ setT(t.scale > 1 ? { scale: 1, x: 0, y: 0 } : { scale: 2.4, x: 0, y: 0 });
	76	+ lastTap.current = now;
	77	+ }
	78	+ if (t.scale <= 1.02) setT({ scale: 1, x: 0, y: 0 });
	79	+ }
	80	+ };
	81	+
	82	+ return (
	83	+ <img
	84	+ src={src} alt="" draggable={false}
	85	+ style={{
	86	+ transform: `translate(${t.x}px, ${t.y}px) scale(${t.scale})`,
	87	+ transition: pointers.current.size ? "none" : "transform 0.15s ease",
	88	+ touchAction: "none", cursor: t.scale > 1 ? "grab" : "zoom-out",
	89	+ }}
	90	+ onClick={(e) => e.stopPropagation()}
	91	+ onPointerDown={onDown} onPointerMove={onMove}
	92	+ onPointerUp={onUp} onPointerCancel={onUp}
	93	+ />
	94	+ );
	95	+}
	96	+
	97	+// --- Gallery: native swipe (scroll-snap) + thumbnails + fullscreen ------------
	98	+function Gallery({ images, captions, title, type }:
	99	+ { images: string[]; captions?: string[]; title: string; type?: string }) {
	100	+ const [idx, setIdx] = useState(0);
	101	+ const [zoom, setZoom] = useState(false);
	102	+ const [dead, setDead] = useState<Set<string>>(new Set());
	103	+ const track = useRef<HTMLDivElement>(null);
	104	+
	105	+ // images that fail to load: removed from the gallery on the fly (never a
	106	+ // broken-image icon); captions kept aligned
	107	+ const alive = images
	108	+ .map((u, i) => ({ u, cap: captions && captions.length === images.length ? captions[i] : "" }))
	109	+ .filter(({ u }) => !dead.has(u));
	110	+ const markDead = (u: string) => setDead((d) => new Set(d).add(u));
	111	+
	112	+ const onScroll = () => {
	113	+ const el = track.current;
	114	+ if (el) setIdx(Math.round(el.scrollLeft / el.clientWidth));
	115	+ };
	116	+ const goto = (i: number) =>
	117	+ track.current?.scrollTo({ left: i * track.current.clientWidth, behavior: "smooth" });
	118	+
	119	+ useEffect(() => {
	120	+ if (!zoom) return;
	121	+ const onKey = (e: KeyboardEvent) => {
	122	+ if (e.key === "Escape") setZoom(false);
	123	+ if (e.key === "ArrowLeft") setIdx((i) => Math.max(0, i - 1));
	124	+ if (e.key === "ArrowRight") setIdx((i) => Math.min(alive.length - 1, i + 1));
	125	+ };
	126	+ window.addEventListener("keydown", onKey);
	127	+ // freeze the background while fullscreen (mobile)
	128	+ document.body.style.overflow = "hidden";
	129	+ return () => {
	130	+ window.removeEventListener("keydown", onKey);
	131	+ document.body.style.overflow = "";
	132	+ };
	133	+ }, [zoom, alive.length]);
	134	+
	135	+ if (alive.length === 0)
	136	+ return <div className="carousel"><div className="carousel-empty"><TypeFallback type={type} /></div></div>;
	137	+
	138	+ const cur = Math.min(idx, alive.length - 1);
	139	+ const swipe = (dir: 1 \| -1) =>
	140	+ setIdx((i) => Math.min(alive.length - 1, Math.max(0, i + dir)));
	141	+
	142	+ return (
	143	+ <>
	144	+ <div className="carousel">
	145	+ <div className="carousel-track" ref={track} onScroll={onScroll}>
	146	+ {alive.map(({ u }, i) => (
	147	+ <img key={u} src={u} loading={i <= 1 ? "eager" : "lazy"} decoding="async"
	148	+ alt={`${title} — photo ${i + 1} of ${alive.length}`}
	149	+ onError={() => markDead(u)} onClick={() => setZoom(true)} />
	150	+ ))}
	151	+ </div>
	152	+ {alive[cur]?.cap && <span className="carousel-caption">{alive[cur].cap}</span>}
	153	+ <span className="carousel-count" aria-live="polite">{cur + 1}/{alive.length}</span>
	154	+ {cur > 0 && <button className="carousel-nav prev" aria-label="Previous photo" onClick={() => goto(cur - 1)}>‹</button>}
	155	+ {cur < alive.length - 1 && <button className="carousel-nav next" aria-label="Next photo" onClick={() => goto(cur + 1)}>›</button>}
	156	+ </div>
	157	+ {alive.length > 1 && (
	158	+ <div className="thumbs">
	159	+ {alive.map(({ u }, i) => (
	160	+ <button key={u} className={i === cur ? "on" : ""} onClick={() => goto(i)} aria-label={`Photo ${i + 1}`}>
	161	+ <img src={u} alt="" loading="lazy" decoding="async" onError={() => markDead(u)} />
	162	+ </button>
	163	+ ))}
	164	+ </div>
	165	+ )}
	166	+ {zoom && (
	167	+ <div className="lightbox" onClick={() => setZoom(false)} role="dialog" aria-label="Enlarged photo">
	168	+ <button className="lb-close" aria-label="Close" onClick={() => setZoom(false)}>✕</button>
	169	+ {cur > 0 && <button className="lb-nav prev" aria-label="Previous" onClick={(e) => { e.stopPropagation(); setIdx(cur - 1); }}>‹</button>}
	170	+ <ZoomImg src={alive[cur].u} onSwipe={swipe} />
	171	+ {cur < alive.length - 1 && <button className="lb-nav next" aria-label="Next" onClick={(e) => { e.stopPropagation(); setIdx(cur + 1); }}>›</button>}
	172	+ <span className="lb-count">
	173	+ {alive[cur]?.cap ? `${alive[cur].cap} · ` : ""}{cur + 1} / {alive.length}
	174	+ </span>
	175	+ </div>
	176	+ )}
	177	+ </>
	178	+ );
	179	+}
	180	+
	181	+// technical `details` keys never shown in “Details”
	182	+const DETAIL_HIDDEN = new Set([
	183	+ "pieces", "price_from", "cover_thumb", "photo_captions", "img_audited",
	184	+ "needs_image_review", "postal_code", "region", "transaction",
	185	+ "prix_pi2", "prix_m2", "listing_origin_url",
	186	+]);
	187	+
	188	+// icon for each “spec” tile (Icons.tsx)
	189	+const SPEC_ICONS: Record<string, string> = {
	190	+ "Type": "home", "Bedrooms": "bed", "Bathrooms": "bath",
	191	+ "Half baths": "drop", "Living area": "area", "Lot": "land",
	192	+ "Year built": "calendar", "MLS®": "tag",
	193	+};
	194	+
	195	+export default function ListingPage() {
	196	+ const { uid } = useParams<{ uid: string }>();
	197	+ const [l, setL] = useState<Listing \| null>(null);
	198	+ const [error, setError] = useState<string \| null>(null);
	199	+ // re-render when the source names arrive (Title Case fallback otherwise)
	200	+ const [, setSrcTick] = useState(0);
	201	+
	202	+ useEffect(() => {
	203	+ fetchSources().then((r) => { registerSourceNames(r.sources); setSrcTick(1); }).catch(() => {});
	204	+ if (!uid) return;
	205	+ setL(null); setError(null);
	206	+ fetchListing(uid).then(setL).catch((e) => setError(String(e)));
	207	+ window.scrollTo(0, 0);
	208	+ }, [uid]);
	209	+
	210	+ if (error)
	211	+ return (
	212	+ <div className="notice container">
	213	+ <div className="big"><Ico name="alert" size={44} /></div>
	214	+ <h2>Listing not found</h2>
	215	+ <p>{error}</p>
	216	+ <Link className="btn btn-primary" to="/">Back to homes</Link>
	217	+ </div>
	218	+ );
	219	+
	220	+ if (!l)
	221	+ return (
	222	+ <div className="container detail">
	223	+ <div className="fiche" aria-busy="true">
	224	+ <div className="skel"><div className="sk-img" /></div>
	225	+ <div className="skel"><div className="sk-line" /><div className="sk-line" /><div className="sk-line short" /></div>
	226	+ </div>
	227	+ </div>
	228	+ );
	229	+
	230	+ const specs: { k: string; v: string }[] = [];
	231	+ if (l.property_type) specs.push({ k: "Type", v: l.property_type });
	232	+ if (l.bedrooms != null) specs.push({ k: "Bedrooms", v: String(l.bedrooms) });
	233	+ if (l.bathrooms != null) specs.push({ k: "Bathrooms", v: String(l.bathrooms) });
	234	+ if (l.powder_rooms != null) specs.push({ k: "Half baths", v: String(l.powder_rooms) });
	235	+ if (l.area_sqft != null) specs.push({ k: "Living area", v: fmtArea(l.area_sqft)! });
	236	+ if (l.lot_sqft != null) specs.push({ k: "Lot", v: fmtArea(l.lot_sqft)! });
	237	+ if (l.year_built != null) specs.push({ k: "Year built", v: String(l.year_built) });
	238	+ if (l.mls) specs.push({ k: "MLS®", v: l.mls });
	239	+
	240	+ const rooms: Room[] = Array.isArray(l.details?.pieces) ? (l.details!.pieces as Room[]) : [];
	241	+ const detEntries = Object.entries(l.details ?? {})
	242	+ .filter(([k, v]) => !DETAIL_HIDDEN.has(k) && (typeof v === "string" \|\| typeof v === "number") && String(v).trim());
	243	+
	244	+ const isSale = l.details?.transaction !== "location";
	245	+
	246	+ const hist = (l.price_history ?? []).filter((h) => h.price != null);
	247	+ const drop = hist.length >= 2 && hist[0].price !== hist[1].price
	248	+ ? { from: hist[1].price!, to: hist[0].price! } : null;
	249	+ const updated = l.updated_at ? fmtDate(l.updated_at) : null;
	250	+
	251	+ return (
	252	+ <div className="container detail">
	253	+ <nav className="crumbs" aria-label="Breadcrumb">
	254	+ <Link to="/">Homes</Link> ›
	255	+ {l.city && <span>{l.city}</span>} ›
	256	+ <span>{l.address \|\| l.title}</span>
	257	+ </nav>
	258	+
	259	+ <div className="fiche">
	260	+ {/* -------- left column: gallery, price/summary, description, ---------
	261	+ -------- details, rooms — DOM order = visual order ---------------- */}
	262	+ <div className="f-col">
	263	+ <section className="f-bloc f-galerie" aria-label="Photos">
	264	+ <Gallery
	265	+ images={l.images ?? []}
	266	+ captions={Array.isArray(l.details?.photo_captions)
	267	+ ? (l.details!.photo_captions as string[]) : undefined}
	268	+ title={l.address \|\| l.title}
	269	+ type={l.property_type}
	270	+ />
	271	+ </section>
	272	+
	273	+ <section className="f-bloc f-hero">
	274	+ <div className="price-kicker">
	275	+ {isSale ? "Asking price" : "Monthly rent"}
	276	+ </div>
	277	+ <div className="price-row">
	278	+ <div className="price">
	279	+ {fmtPrice(l.price, l.price_label)}
	280	+ {!isSale && <span className="per-month"> /month</span>}
	281	+ </div>
	282	+ {l.property_type && (
	283	+ <span className="type-chip">
	284	+ <Ico name={SPEC_ICONS["Type"]} size={13} /> {l.property_type}
	285	+ {!isSale ? " · for rent" : ""}
	286	+ {l.details?.price_from ? " · starting at" : ""}
	287	+ </span>
	288	+ )}
	289	+ </div>
	290	+ {l.price != null && l.area_sqft != null && l.area_sqft > 200 && (
	291	+ <div className="price-sub">${Math.round(l.price / l.area_sqft).toLocaleString("en-CA")} / sq ft of living area</div>
	292	+ )}
	293	+ <h1>{l.address \|\| l.title}</h1>
	294	+ <div className="loc"><Ico name="pin" size={13} /> {[l.sector, l.city, l.region].filter(Boolean).join(" · ")}</div>
	295	+
	296	+ <div className="spec-list">
	297	+ {specs.map((s) => (
	298	+ <div className="spec-row" key={s.k}>
	299	+ <span className="spec-badge"><Ico name={SPEC_ICONS[s.k] ?? "tag"} size={15} /></span>
	300	+ <span className="spec-k">{s.k}</span>
	301	+ <b className="spec-v">{s.v}</b>
	302	+ </div>
	303	+ ))}
	304	+ </div>
	305	+
	306	+ {drop && (
	307	+ <div className={`prix-histo ${drop.to < drop.from ? "down" : ""}`}>
	308	+ <Ico name={drop.to < drop.from ? "trenddown" : "trendup"} size={16} /> Price changed from {fmtPrice(drop.from)} to <b>{fmtPrice(drop.to)}</b>
	309	+ </div>
	310	+ )}
	311	+
	312	+ {(l.broker_name \|\| l.broker_phone) && (
	313	+ <div className="broker">
	314	+ <div className="broker-k">Listing agent</div>
	315	+ {l.broker_name && <div className="broker-name">{l.broker_name}</div>}
	316	+ {l.broker_phone && <a className="broker-tel" href={`tel:${l.broker_phone.replace(/\s/g, "")}`}><Ico name="phone" size={14} /> {l.broker_phone}</a>}
	317	+ </div>
	318	+ )}
	319	+
	320	+ <a className="cta" href={l.url} target="_blank" rel="noopener noreferrer">
	321	+ See the listing at {sourceName(l.source)} <Ico name="external" size={15} />
	322	+ </a>
	323	+ <div className="fine">
	324	+ Aggregated by House-Ka — {sourceName(l.source)}{updated ? ` · synced on ${updated}` : ""}.
	325	+ </div>
	326	+ </section>
	327	+
	328	+ {l.duplicates && l.duplicates.length > 0 && (
	329	+ <section className="f-bloc" id="publications">
	330	+ <h2>Also published on</h2>
	331	+ <p className="dups-note">
	332	+ This property was found on {l.duplicates.length}{" "}
	333	+ other site{l.duplicates.length > 1 ? "s" : ""} —
	334	+ House-Ka shows the most complete version.
	335	+ </p>
	336	+ <div className="dups-list">
	337	+ {l.duplicates.map((d) => (
	338	+ <a key={d.uid} className="dup-item" href={d.url} target="_blank" rel="noopener noreferrer">
	339	+ <span className="dup-src">{sourceName(d.source)}</span>
	340	+ {(d.broker_name \|\| d.agency) && (
	341	+ <span className="dup-broker">{d.broker_name \|\| d.agency}</span>
	342	+ )}
	343	+ <span className="dup-go">See the listing <Ico name="external" size={13} /></span>
	344	+ </a>
	345	+ ))}
	346	+ </div>
	347	+ </section>
	348	+ )}
	349	+
	350	+ {l.description && (
	351	+ <section className="f-bloc f-desc" id="description">
	352	+ <h2>Description</h2>
	353	+ <p className="desc-text">{l.description}</p>
	354	+ </section>
	355	+ )}
	356	+
	357	+ {detEntries.length > 0 && (
	358	+ <section className="f-bloc" id="details">
	359	+ <h2>Details</h2>
	360	+ <div className="dtable">
	361	+ {detEntries.map(([k, v]) => (
	362	+ <div className="drow" key={k}>
	363	+ <span>{k}</span>
	364	+ {/^https?:\/\//.test(String(v))
	365	+ ? <b><a href={String(v)} target="_blank" rel="noopener noreferrer">Open ↗</a></b>
	366	+ : <b>{String(v)}</b>}
	367	+ </div>
	368	+ ))}
	369	+ </div>
	370	+ </section>
	371	+ )}
	372	+
	373	+ {rooms.length > 0 && (
	374	+ <section className="f-bloc" id="rooms">
	375	+ <h2>Rooms</h2>
	376	+ <div className="rooms-wrap">
	377	+ <table className="rooms">
	378	+ <thead><tr><th>Room</th><th>Level</th><th>Dimensions</th><th>Flooring</th></tr></thead>
	379	+ <tbody>
	380	+ {rooms.map((r, i) => (
	381	+ <tr key={i}>
	382	+ <td>{r.nom \|\| "—"}</td><td>{r.niveau \|\| "—"}</td>
	383	+ <td>{r.dimensions \|\| "—"}</td><td>{r.revetement \|\| "—"}</td>
	384	+ </tr>
	385	+ ))}
	386	+ </tbody>
	387	+ </table>
	388	+ </div>
	389	+ </section>
	390	+ )}
	391	+
	392	+ </div>
	393	+
	394	+ {/* -------- right column (desktop): features, map --------------------- */}
	395	+ <div className="f-col">
	396	+ {l.features && l.features.length > 0 && (
	397	+ <section className="f-bloc" id="features">
	398	+ <h2>Features</h2>
	399	+ <div className="amenity-grid">
	400	+ {l.features.map((f, i) => (
	401	+ <span className="amenity-it" key={i}>
	402	+ <span className="am-ico"><AmenityIco label={f} /></span>
	403	+ <span className="am-txt">{f}</span>
	404	+ </span>
	405	+ ))}
	406	+ </div>
	407	+ </section>
	408	+ )}
	409	+
	410	+ {l.lat != null && l.lng != null && (
	411	+ <section className="f-bloc" id="map">
	412	+ <h2>Location</h2>
	413	+ <Suspense fallback={<div className="lmap3d lmap3d-skel map-loading">Loading the map…</div>}>
	414	+ <PropertyMap
	415	+ uid={l.uid} lat={l.lat} lng={l.lng} price={l.price}
	416	+ propertyType={l.property_type} address={l.address \|\| l.title}
	417	+ city={l.city} image={l.images?.[0]}
	418	+ />
	419	+ </Suspense>
	420	+ </section>
	421	+ )}
	422	+ </div>
	423	+ </div>
	424	+
	425	+ {/* financing: real mortgage rates + Canadian calculator */}
	426	+ {isSale && <Financing price={l.price} />}
	427	+
	428	+ {/* nearby amenities: full width, AFTER the property info (correct mobile order) */}
	429	+ <NearbyPlaces lat={l.lat} lng={l.lng} />
	430	+
	431	+ <div className="fine f-foot">
	432	+ Prices and availability are those displayed by the source — every
	433	+ listing links back to the brokerage's original page.
	434	+ </div>
	435	+
	436	+ <div className="cta-sticky">
	437	+ <span className="cta-sticky-prix">{fmtPrice(l.price, l.price_label)}</span>
	438	+ <a className="cta" href={l.url} target="_blank" rel="noopener noreferrer">
	439	+ See at {sourceName(l.source)} ↗
	440	+ </a>
	441	+ </div>
	442	+ </div>
	443	+ );
	444	+}

added frontend/src/pages/Rates.tsx +192 −0

		`@@ -0,0 +1,192 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	3	+// Author: Simon-Pierre Boucher — contact@spboucher.ai
	4	+// pages/Rates.tsx : /rates — Mortgage Intelligence.
	5	+// Market view (best/median/variations), per-bank comparator with rate kind
	6	+// (posted vs special) and freshness, history, prime rates, source health.
	7	+// No invented rates: everything comes from the institutions' official
	8	+// pages, with provenance.
	9	+// -----------------------------------------------------------------------------
	10	+import { useEffect, useState } from "react";
	11	+import {
	12	+ MortgageBest, MortgageIntelligence, MortgageProviderHealth,
	13	+ fetchMortgageBest, fetchMortgageIntelligence, fetchMortgageProviders,
	14	+ fmtRate,
	15	+} from "../api";
	16	+import RateHistory from "../components/RateHistory";
	17	+
	18	+const TERMS: [number, string][] = [
	19	+ [12, "1 year"], [24, "2 years"], [36, "3 years"], [48, "4 years"],
	20	+ [60, "5 years"], [84, "7 years"], [120, "10 years"],
	21	+];
	22	+const KIND_EN: Record<string, string> = { posted: "posted", special: "special offer" };
	23	+const INSURED_EN: Record<string, string> = {
	24	+ insured: "insured", insurable: "insurable", uninsured: "uninsured", unknown: "",
	25	+};
	26	+
	27	+const termLabel = (m: number) => TERMS.find(([t]) => t === m)?.[1] ?? `${m} months`;
	28	+const freshness = (min: number) =>
	29	+ min < 60 ? `${min} min ago` : min < 48 * 60
	30	+ ? `${Math.round(min / 60)} h ago` : `${Math.round(min / 1440)} d ago`;
	31	+const varTxt = (v: number \| null) =>
	32	+ v == null ? "—" : v === 0 ? "stable"
	33	+ : `${v > 0 ? "▲ +" : "▼ "}${v.toFixed(2)} pt`;
	34	+
	35	+export default function RatesPage() {
	36	+ const [intel, setIntel] = useState<MortgageIntelligence \| null>(null);
	37	+ const [rateType, setRateType] = useState<"fixed" \| "variable">("fixed");
	38	+ const [term, setTerm] = useState(60);
	39	+ const [best, setBest] = useState<MortgageBest \| null>(null);
	40	+ const [health, setHealth] = useState<MortgageProviderHealth[]>([]);
	41	+
	42	+ useEffect(() => {
	43	+ document.title = "Mortgage rates in Canada — live comparator \| House-Ka";
	44	+ fetchMortgageIntelligence().then(setIntel).catch(() => setIntel(null));
	45	+ fetchMortgageProviders().then((r) => setHealth(r.providers)).catch(() => {});
	46	+ }, []);
	47	+
	48	+ useEffect(() => {
	49	+ setBest(null);
	50	+ fetchMortgageBest(rateType, term).then(setBest).catch(() => setBest(null));
	51	+ }, [rateType, term]);
	52	+
	53	+ return (
	54	+ <div className="container taux-page">
	55	+ <header className="taux-head">
	56	+ <h1>Live mortgage rates</h1>
	57	+ <p>
	58	+ The rates actually published by the big Canadian institutions
	59	+ (banks, Desjardins, virtual lenders and monolines), collected
	60	+ continuously by House-Ka. Every rate shows its <b>kind</b> (posted or
	61	+ special offer), its <b>official source</b> and its <b>freshness</b> —
	62	+ never an invented rate, never a stale one without a warning.
	63	+ </p>
	64	+ </header>
	65	+
	66	+ {intel && intel.products.length > 0 && (
	67	+ <section className="f-bloc">
	68	+ <h2>Market overview</h2>
	69	+ <div className="taux-grid">
	70	+ {intel.products.map((p) => (
	71	+ <button
	72	+ key={`${p.rate_type}-${p.term_months}`}
	73	+ className={`taux-card ${p.rate_type === rateType && p.term_months === term ? "on" : ""}`}
	74	+ onClick={() => { setRateType(p.rate_type as "fixed" \| "variable"); setTerm(p.term_months); }}
	75	+ >
	76	+ <span className="taux-card-k">
	77	+ {p.rate_type === "fixed" ? "Fixed" : "Variable"} {termLabel(p.term_months)}
	78	+ </span>
	79	+ <span className="taux-card-v">{fmtRate(p.best)}</span>
	80	+ <span className="taux-card-sub">{p.best_institution}</span>
	81	+ <span className="taux-card-sub">
	82	+ median {fmtRate(p.median)} · 30 d: {varTxt(p.var_30d)}
	83	+ </span>
	84	+ </button>
	85	+ ))}
	86	+ </div>
	87	+ {intel.prime_rates.length > 0 && (
	88	+ <p className="fine">
	89	+ Prime rates:{" "}
	90	+ {intel.prime_rates.map((p, i) => (
	91	+ <span key={i}>
	92	+ {i > 0 && " · "}
	93	+ {p.institution} <b>{fmtRate(p.rate)}</b>
	94	+ </span>
	95	+ ))}
	96	+ </p>
	97	+ )}
	98	+ </section>
	99	+ )}
	100	+
	101	+ <section className="f-bloc">
	102	+ <h2>Compare the institutions</h2>
	103	+ <div className="taux-filtres">
	104	+ <label>
	105	+ <span>Type</span>
	106	+ <select value={rateType}
	107	+ onChange={(e) => setRateType(e.target.value as "fixed" \| "variable")}>
	108	+ <option value="fixed">Fixed</option>
	109	+ <option value="variable">Variable</option>
	110	+ </select>
	111	+ </label>
	112	+ <label>
	113	+ <span>Term</span>
	114	+ <select value={term} onChange={(e) => setTerm(Number(e.target.value))}>
	115	+ {TERMS.map(([m, l]) => <option key={m} value={m}>{l}</option>)}
	116	+ </select>
	117	+ </label>
	118	+ </div>
	119	+
	120	+ {best == null ? (
	121	+ <p className="fine">No current rate for this product — try another term.</p>
	122	+ ) : (
	123	+ <>
	124	+ <div className="rooms-wrap">
	125	+ <table className="rooms mtg-comp">
	126	+ <thead>
	127	+ <tr><th>Institution</th><th>Product</th><th>Rate</th><th>Kind</th><th>Freshness</th><th>Source</th></tr>
	128	+ </thead>
	129	+ <tbody>
	130	+ {best.per_institution.map((r, i) => (
	131	+ <tr key={r.provider} className={i === 0 ? "taux-best" : ""}>
	132	+ <td>{r.institution}{i === 0 && <span className="taux-badge">best</span>}</td>
	133	+ <td>{r.product_name}</td>
	134	+ <td><b>{fmtRate(r.rate)}</b>{r.apr != null ? ` (APR ${fmtRate(r.apr)})` : ""}</td>
	135	+ <td>
	136	+ {KIND_EN[r.kind] ?? r.kind}
	137	+ {INSURED_EN[r.insured_status] ? ` · ${INSURED_EN[r.insured_status]}` : ""}
	138	+ </td>
	139	+ <td className={r.stale ? "mtg-stale" : ""}>{freshness(r.age_minutes)}</td>
	140	+ <td>
	141	+ {r.source_url && (
	142	+ <a href={r.source_url} target="_blank" rel="noopener noreferrer">official ↗</a>
	143	+ )}
	144	+ </td>
	145	+ </tr>
	146	+ ))}
	147	+ </tbody>
	148	+ </table>
	149	+ </div>
	150	+ <p className="fine">
	151	+ One comparable product per institution (the special offer wins
	152	+ over the posted rate). Incomparable products — insured vs
	153	+ uninsured, posted vs special — are never mixed in the same
	154	+ ranking without saying so.
	155	+ </p>
	156	+ </>
	157	+ )}
	158	+ </section>
	159	+
	160	+ <section className="f-bloc">
	161	+ <h2>Trend — {rateType} {termLabel(term)}</h2>
	162	+ <RateHistory rateType={rateType} termMonths={term} />
	163	+ </section>
	164	+
	165	+ {health.length > 0 && (
	166	+ <section className="f-bloc">
	167	+ <h2>Source freshness</h2>
	168	+ <div className="taux-sante">
	169	+ {health.map((h) => (
	170	+ <span key={h.provider}
	171	+ className={`taux-src taux-src-${h.level.toLowerCase()}`}
	172	+ title={`${h.current_products} current product(s) — last collection ${freshness(h.age_minutes)}`}>
	173	+ {h.institution}
	174	+ </span>
	175	+ ))}
	176	+ </div>
	177	+ <p className="fine">
	178	+ Green: recent successful collection · yellow: data kept but aging ·
	179	+ red: source in error. When a collection fails, the last valid rates
	180	+ stay displayed with their date.
	181	+ </p>
	182	+ </section>
	183	+ )}
	184	+
	185	+ <p className="fine">
	186	+ Indicative information only, without guarantee — actual conditions
	187	+ depend on your file. House-Ka is neither a lender nor a mortgage
	188	+ broker.
	189	+ </p>
	190	+ </div>
	191	+ );
	192	+}

added frontend/src/pages/Stats.tsx +139 −0

		`@@ -0,0 +1,139 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	3	+// Author: Simon-Pierre Boucher — contact@spboucher.ai
	4	+// pages/Stats.tsx : market & platform statistics — totals, per-source volumes,
	5	+// data quality (completeness, quarantine), recent syncs.
	6	+// -----------------------------------------------------------------------------
	7	+import { useEffect, useState } from "react";
	8	+import {
	9	+ Stats, fetchSources, fetchStats, registerSourceNames, sourceName,
	10	+} from "../api";
	11	+
	12	+const n = (v: number \| null \| undefined) =>
	13	+ v == null ? "—" : Math.round(v).toLocaleString("en-CA");
	14	+
	15	+export default function StatsPage() {
	16	+ const [stats, setStats] = useState<Stats \| null>(null);
	17	+ const [error, setError] = useState<string \| null>(null);
	18	+
	19	+ useEffect(() => {
	20	+ document.title = "Canadian housing market statistics \| House-Ka";
	21	+ fetchSources().then((r) => registerSourceNames(r.sources)).catch(() => {});
	22	+ fetchStats().then(setStats).catch((e) => setError(String(e)));
	23	+ }, []);
	24	+
	25	+ if (error) return <div className="notice container"><h2>Could not load the stats</h2><p>{error}</p></div>;
	26	+ if (!stats) return <div className="notice container">Loading…</div>;
	27	+
	28	+ const q = stats.qualite;
	29	+ const syncs = (stats.recent_syncs ?? []).slice(0, 20);
	30	+
	31	+ return (
	32	+ <div className="container stats-page">
	33	+ <span className="kicker">Live data</span>
	34	+ <h1>Platform statistics</h1>
	35	+
	36	+ <div className="mtg-resultat" style={{ marginTop: 18 }}>
	37	+ <div className="mtg-kpi">
	38	+ <span className="mtg-kpi-k">Homes for sale</span>
	39	+ <span className="mtg-kpi-v">{n(stats.total)}</span>
	40	+ <span className="mtg-kpi-sub">published, deduplicated</span>
	41	+ </div>
	42	+ <div className="mtg-kpi">
	43	+ <span className="mtg-kpi-k">Cities & towns</span>
	44	+ <span className="mtg-kpi-v">{n(stats.cities)}</span>
	45	+ </div>
	46	+ <div className="mtg-kpi">
	47	+ <span className="mtg-kpi-k">Average price</span>
	48	+ <span className="mtg-kpi-v">${n(stats.avg_price)}</span>
	49	+ <span className="mtg-kpi-sub">from ${n(stats.min_price)} to ${n(stats.max_price)}</span>
	50	+ </div>
	51	+ <div className="mtg-kpi">
	52	+ <span className="mtg-kpi-k">Sources</span>
	53	+ <span className="mtg-kpi-v">{n(stats.sources)}</span>
	54	+ <span className="mtg-kpi-sub">CREA DDF brokerage sites</span>
	55	+ </div>
	56	+ </div>
	57	+
	58	+ {q && (
	59	+ <section className="f-bloc">
	60	+ <h2>Data quality</h2>
	61	+ <p className="sub">
	62	+ Every listing gets a completeness score (photos, description,
	63	+ specs, coordinates). Listings without a plausible price or a known
	64	+ city are quarantined until the next enrichment pass completes them.
	65	+ </p>
	66	+ <div className="mtg-resultat">
	67	+ <div className="mtg-kpi">
	68	+ <span className="mtg-kpi-k">Active listings</span>
	69	+ <span className="mtg-kpi-v">{n(q.actives)}</span>
	70	+ </div>
	71	+ <div className="mtg-kpi">
	72	+ <span className="mtg-kpi-k">Published</span>
	73	+ <span className="mtg-kpi-v">{n(q.publiees)}</span>
	74	+ </div>
	75	+ <div className="mtg-kpi">
	76	+ <span className="mtg-kpi-k">In quarantine</span>
	77	+ <span className="mtg-kpi-v">{n(q.quarantaine)}</span>
	78	+ </div>
	79	+ <div className="mtg-kpi">
	80	+ <span className="mtg-kpi-k">Avg. completeness</span>
	81	+ <span className="mtg-kpi-v">{q.completude_moyenne ?? "—"}</span>
	82	+ <span className="mtg-kpi-sub">score /100</span>
	83	+ </div>
	84	+ </div>
	85	+
	86	+ {q.par_source.length > 0 && (
	87	+ <div className="rooms-wrap">
	88	+ <table className="rooms">
	89	+ <thead>
	90	+ <tr><th>Source</th><th>Listings</th><th>Published</th><th>Completeness</th><th>Flags</th></tr>
	91	+ </thead>
	92	+ <tbody>
	93	+ {q.par_source.map((s) => (
	94	+ <tr key={s.source}>
	95	+ <td>{sourceName(s.source)}</td>
	96	+ <td>{n(s.n)}</td>
	97	+ <td>{n(s.publiees)}</td>
	98	+ <td>{s.completude ?? "—"}</td>
	99	+ <td>{n(s.anomalies)}</td>
	100	+ </tr>
	101	+ ))}
	102	+ </tbody>
	103	+ </table>
	104	+ </div>
	105	+ )}
	106	+ </section>
	107	+ )}
	108	+
	109	+ {syncs.length > 0 && (
	110	+ <section className="f-bloc">
	111	+ <h2>Recent syncs</h2>
	112	+ <div className="rooms-wrap">
	113	+ <table className="rooms">
	114	+ <thead>
	115	+ <tr><th>Source</th><th>When</th><th>Found</th><th>Added</th><th>Updated</th><th>Removed</th></tr>
	116	+ </thead>
	117	+ <tbody>
	118	+ {syncs.map((s, i) => (
	119	+ <tr key={i} className={s.ok ? "" : "mtg-stale"}>
	120	+ <td>{sourceName(s.source)}</td>
	121	+ <td>{new Date((s.ts > 1e12 ? s.ts : s.ts * 1000)).toLocaleString("en-CA")}</td>
	122	+ <td>{n(s.found)}</td>
	123	+ <td>{n(s.added)}</td>
	124	+ <td>{n(s.updated)}</td>
	125	+ <td>{n(s.removed)}</td>
	126	+ </tr>
	127	+ ))}
	128	+ </tbody>
	129	+ </table>
	130	+ </div>
	131	+ <p className="fine">
	132	+ The connectors re-sync on their own, around the clock. A failed
	133	+ sync never wipes data — the last valid state is kept.
	134	+ </p>
	135	+ </section>
	136	+ )}
	137	+ </div>
	138	+ );
	139	+}

added frontend/src/styles.css +1827 −0

		`@@ -0,0 +1,1827 @@`
	1	+/* -----------------------------------------------------------------------------
	2	+ House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	3	+ Author: Simon-Pierre Boucher — contact@spboucher.ai
	4	+ styles.css : House-Ka business classes on top of the shared Groupe KA design
	5	+ system (ka/tokens.css, imported BEFORE this file in main.tsx).
	6	+ House-Ka overrides MORE than the accent: pine/cream palette + serif
	7	+ display type (Fraunces) — a deliberately different skin from Immo-Ka.
	8	+----------------------------------------------------------------------------- */
	9	+:root {
	10	+ /* ---- House-Ka PINE accent + warm cream paper + serif display ---- */
	11	+ --accent: #0f6b4f;
	12	+ --accent-soft: #dcefe6;
	13	+ --accent-deep: #0a4a37;
	14	+ --on-accent: #ffffff;
	15	+ --paper: #faf7f0;
	16	+ --ink: #14201a;
	17	+ --font-display: "Fraunces", "Iowan Old Style", Georgia, serif;
	18	+ /* legacy aliases — all the business CSS below uses --lime */
	19	+ --lime: var(--accent);
	20	+ --lime-soft: var(--accent-soft);
	21	+}
	22	+/* Serif display: Fraunces is wider than Space Grotesk — soften the tracking */
	23	+h1, h2, h3, h4, .brand, .price, .card-price { letter-spacing: -0.015em; }
	24	+
	25	+/* Ancre sous le header collant (spécifique Immo-Ka) */
	26	+html { scroll-padding-top: 76px; }
	27	+h1, h2, h3, h4 { margin: 0; }
	28	+a { text-decoration: none; }
	29	+button { font-family: inherit; }
	30	+
	31	+.mono { font-family: var(--font-mono); }
	32	+.kicker {
	33	+ font-family: var(--font-mono); font-size: 11.5px; font-weight: 500;
	34	+ text-transform: uppercase; letter-spacing: 0.14em; color: var(--green);
	35	+ display: inline-flex; align-items: center; gap: 8px;
	36	+}
	37	+.kicker::before { content: ""; width: 22px; height: 2px; background: var(--green); }
	38	+
	39	+.container { max-width: 1240px; margin: 0 auto; padding: 0 24px; }
	40	+@media (max-width: 640px) { .container { padding: 0 16px; } }
	41	+
	42	+/* ================= Header ================= */
	43	+.header {
	44	+ position: sticky; top: 0; z-index: var(--z-header, 500);
	45	+ background: var(--paper);
	46	+ border-bottom: 2px solid var(--ink);
	47	+}
	48	+/* Menu mobile ouvert : le panneau vit DANS le header — on monte tout le header
	49	+ au niveau modale pour qu il passe au-dessus du voile (--z-overlay). */
	50	+.header:has(.mobile-menu.open) { z-index: var(--z-modal, 900); }
	51	+.header-inner { display: flex; align-items: center; gap: 20px; height: 64px; }
	52	+.brand { font-family: var(--font-display); font-weight: 700; font-size: 26px; letter-spacing: -0.04em; display: flex; align-items: center; line-height: 1; }
	53	+.brand .ka { background: var(--ink); color: var(--lime); padding: 2px 7px 4px; border-radius: 6px; margin-left: 3px; transform: rotate(-2deg); transition: transform 0.2s ease; }
	54	+.brand:hover .ka { transform: rotate(0deg); }
	55	+.brand-tag { font-family: var(--font-mono); font-size: 10.5px; color: var(--ink-3); letter-spacing: 0.08em; text-transform: uppercase; margin-left: 12px; }
	56	+@media (max-width: 860px) { .brand-tag { display: none; } }
	57	+.nav { margin-left: auto; display: flex; gap: 4px; }
	58	+.nav a { padding: 9px 16px; border-radius: 999px; font-weight: 600; font-size: 14px; color: var(--ink-2); border: 1.5px solid transparent; transition: all 0.15s ease; min-height: 40px; display: inline-flex; align-items: center; }
	59	+.nav a:hover { border-color: var(--ink); color: var(--ink); }
	60	+.nav a.active { background: var(--ink); color: var(--lime); }
	61	+
	62	+/* ================= Ticker ================= */
	63	+.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(15, 107, 79, 0.25); }
	64	+.ticker-track { display: inline-flex; gap: 0; animation: ticker 48s linear infinite; will-change: transform; }
	65	+.ticker span { padding: 0 26px; position: relative; }
	66	+.ticker span::after { content: "◆"; position: absolute; right: -6px; opacity: 0.5; font-size: 8px; top: 3px; }
	67	+@keyframes ticker { from { transform: translateX(0); } to { transform: translateX(-50%); } }
	68	+@media (prefers-reduced-motion: reduce) { .ticker-track { animation: none; } * { transition-duration: 0.01ms !important; } }
	69	+
	70	+/* ================= Hero ================= */
	71	+.hero { position: relative; padding: 64px 0 26px; }
	72	+@media (max-width: 640px) { .hero { padding: 36px 0 14px; } }
	73	+/* halo cerise + trame de points en fond — décoratif, sous le texte */
	74	+.hero::before {
	75	+ content: ""; position: absolute; z-index: -1; top: -60px; right: -120px;
	76	+ width: 580px; height: 460px; pointer-events: none;
	77	+ background: radial-gradient(closest-side, rgba(15, 107, 79, 0.12), transparent 72%);
	78	+}
	79	+.hero::after {
	80	+ content: ""; position: absolute; z-index: -1; inset: -20px -40px 0 0; pointer-events: none;
	81	+ background-image: radial-gradient(rgba(20, 24, 20, 0.18) 1.2px, transparent 1.7px);
	82	+ background-size: 22px 22px;
	83	+ -webkit-mask-image: linear-gradient(112deg, transparent 58%, rgba(0, 0, 0, 0.9));
	84	+ mask-image: linear-gradient(112deg, transparent 58%, rgba(0, 0, 0, 0.9));
	85	+}
	86	+.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; }
	87	+.hero h1 .outline { color: transparent; -webkit-text-stroke: 2px var(--ink); }
	88	+.hero h1 .hl { background: var(--lime); color: #fff; padding: 0 10px; border-radius: 8px; display: inline-block; transform: rotate(-1deg); }
	89	+.hero p.lede { color: var(--ink-2); font-size: 16.5px; max-width: 680px; margin: 20px 0 0; }
	90	+
	91	+@media (max-width: 640px) {
	92	+ .hero::before { width: 320px; height: 260px; top: -30px; right: -90px; }
	93	+}
	94	+
	95	+.stat-row { display: flex; flex-wrap: wrap; gap: 10px; margin-top: 28px; }
	96	+.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); transition: transform 0.13s ease, box-shadow 0.13s ease; }
	97	+@media (hover: hover) { .stat-chip:hover { transform: translate(-1px, -1px); box-shadow: 4px 4px 0 rgba(26, 18, 20, 0.2); } }
	98	+.stat-chip b { color: var(--ink); font-weight: 700; font-variant-numeric: tabular-nums; }
	99	+.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; }
	100	+@keyframes pulse { 50% { box-shadow: 0 0 0 7px rgba(15, 107, 79, 0.4); } }
	101	+
	102	+/* ================= Filter bar ================= */
	103	+.filterbar { background: var(--surface); border: 2px solid var(--ink); border-radius: 14px; box-shadow: var(--shadow-off-soft); padding: 14px; margin: 34px 0 6px; display: flex; flex-direction: column; gap: 0; min-width: 0; }
	104	+.f-primary { display: flex; gap: 10px; align-items: stretch; flex-wrap: wrap; min-width: 0; }
	105	+.f-search { flex: 1 1 240px; min-width: 0; display: flex; align-items: center; gap: 9px; border: 1.5px solid var(--ink); border-radius: 9px; background: var(--surface-2); padding: 0 14px; min-height: 52px; color: var(--ink-2); transition: box-shadow 0.15s ease, background 0.15s ease, color 0.15s ease; }
	106	+.f-search:focus-within { box-shadow: 3px 3px 0 var(--lime); background: var(--surface); color: var(--accent-deep); }
	107	+.f-search input { border: none; background: none; outline: none; flex: 1; min-width: 0; font-size: 15px; color: var(--ink); font-family: inherit; }
	108	+.f-search input::placeholder { color: var(--ink-3); }
	109	+.f-clear { border: none; background: var(--line); color: var(--ink-2); border-radius: 50%; width: 22px; height: 22px; font-size: 10px; cursor: pointer; flex: none; display: grid; place-items: center; transition: background 0.12s ease, color 0.12s ease; }
	110	+.f-clear:hover { background: var(--ink); color: #fff; }
	111	+.f-ctl { flex: 0 1 auto; min-width: 0; display: flex; flex-direction: column; justify-content: center; gap: 2px; border: 1.5px solid var(--ink); border-radius: 9px; background: var(--surface); padding: 7px 12px 6px; min-height: 52px; cursor: pointer; transition: box-shadow 0.15s ease, background 0.15s ease; }
	112	+@media (hover: hover) { .f-ctl:hover { background: var(--surface-2); } }
	113	+.f-ctl:focus-within { box-shadow: 3px 3px 0 var(--lime); background: var(--surface); }
	114	+.f-ctl > span { font-family: var(--font-mono); font-size: 9px; font-weight: 700; text-transform: uppercase; letter-spacing: 0.12em; color: var(--ink-3); }
	115	+.f-ctl select { border: none; background: transparent; outline: none; font-family: var(--font-display); font-weight: 700; font-size: 14.5px; color: var(--ink); cursor: pointer; appearance: none; -webkit-appearance: none; padding-right: 16px; min-width: 0; max-width: 180px; text-overflow: ellipsis; background-image: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='9' height='5'%3E%3Cpath d='M0 0l4.5 5L9 0z' fill='%23141814'/%3E%3C/svg%3E"); background-repeat: no-repeat; background-position: right center; }
	116	+.range-pair { display: flex; align-items: center; gap: 4px; }
	117	+.range-pair select { max-width: 92px; }
	118	+.range-sep { color: var(--ink-3); font-family: var(--font-mono); font-size: 11px; }
	119	+.f-more { flex: none; align-self: stretch; display: inline-flex; align-items: center; gap: 8px; border: 1.5px solid var(--ink); border-radius: 9px; background: var(--surface); color: var(--ink); padding: 0 18px; cursor: pointer; font-family: var(--font-display); font-weight: 700; font-size: 14px; min-height: 52px; transition: transform 0.13s ease, box-shadow 0.13s ease, background 0.13s ease, color 0.13s ease; }
	120	+.f-more:hover { transform: translate(-1px, -1px); box-shadow: var(--shadow-off-mid); background: var(--surface); }
	121	+.f-more:active { transform: none; box-shadow: none; }
	122	+.f-more.on { background: var(--ink); border-color: var(--ink); color: var(--lime); box-shadow: 3px 3px 0 var(--lime); }
	123	+.f-more.on:hover { transform: none; }
	124	+.f-more-badge { display: inline-grid; place-items: center; min-width: 20px; height: 20px; padding: 0 6px; border-radius: 999px; background: var(--lime); color: var(--on-accent); font-size: 11.5px; font-weight: 700; font-variant-numeric: tabular-nums; }
	125	+.f-chev { width: 8px; height: 8px; flex: none; border-right: 2px solid currentColor; border-bottom: 2px solid currentColor; transform: rotate(45deg); margin-top: -4px; transition: transform 0.18s ease, margin 0.18s ease; }
	126	+.f-chev.up { transform: rotate(-135deg); margin-top: 4px; }
	127	+.f-adv { display: grid; grid-template-columns: repeat(auto-fit, minmax(230px, 1fr)); gap: 18px 26px; border-top: 1.5px dashed var(--line); margin-top: 14px; padding-top: 16px; min-width: 0; animation: adv-in 0.22s cubic-bezier(0.2, 0.9, 0.3, 1); }
	128	+@keyframes adv-in { from { opacity: 0; transform: translateY(-6px); } to { opacity: 1; transform: none; } }
	129	+.f-group { display: flex; flex-direction: column; gap: 7px; min-width: 0; }
	130	+.f-group > label { font-family: var(--font-mono); font-size: 10px; font-weight: 700; text-transform: uppercase; letter-spacing: 0.12em; color: var(--ink-3); }
	131	+.f-group-end { justify-content: flex-end; }
	132	+.f-group .btn:disabled { opacity: 0.4; cursor: default; }
	133	+.f-native { border: 1.5px solid var(--line); background: var(--surface-2); border-radius: var(--r-ctl); padding: 10px 30px 10px 12px; font-size: 14px; color: var(--ink); outline: none; font-family: inherit; min-height: 42px; width: 100%; min-width: 0; 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 12px center; }
	134	+.f-native:focus { border-color: var(--ink); box-shadow: 3px 3px 0 var(--lime); }
	135	+.seg { display: inline-flex; flex-wrap: wrap; row-gap: 6px; }
	136	+.seg button { border: 1.5px solid var(--ink); background: var(--surface); color: var(--ink-2); padding: 8px 13px; font-family: var(--font-display); font-weight: 600; font-size: 13px; cursor: pointer; margin-left: -1.5px; white-space: nowrap; min-height: 40px; transition: background 0.12s ease, color 0.12s ease, box-shadow 0.12s ease; }
	137	+.seg button:first-child { border-radius: 8px 0 0 8px; margin-left: 0; }
	138	+.seg button:last-child { border-radius: 0 8px 8px 0; }
	139	+.seg button:hover { background: var(--lime-soft); color: var(--ink); }
	140	+.seg button.on { background: var(--ink); color: var(--lime); position: relative; z-index: 1; box-shadow: inset 0 -2.5px 0 var(--lime); }
	141	+
	142	+/* pastilles de filtres actifs — survol = intention de retrait (danger) */
	143	+.pills { display: flex; flex-wrap: wrap; gap: 8px; margin: 12px 0 2px; }
	144	+.pills .pill { display: inline-flex; align-items: center; gap: 7px; border: 1.5px solid var(--ink); background: var(--surface); color: var(--ink); border-radius: 999px; padding: 6px 13px; font-size: 12.5px; font-weight: 600; font-family: var(--font-mono); text-transform: none; letter-spacing: normal; cursor: pointer; transition: all 0.13s ease; box-shadow: 2px 2px 0 var(--lime-soft); animation: pill-in 0.18s ease; }
	145	+@keyframes pill-in { from { opacity: 0; transform: scale(0.9); } to { opacity: 1; transform: none; } }
	146	+.pills .pill:hover { background: var(--danger-soft); border-color: var(--danger); color: var(--danger); box-shadow: none; }
	147	+.pills .pill:hover .pill-x { opacity: 1; }
	148	+.pill-x { font-size: 10px; opacity: 0.6; }
	149	+.pills .pill-clear { background: var(--surface); border-color: var(--danger); color: var(--danger); box-shadow: none; }
	150	+.pills .pill-clear:hover { background: var(--danger); color: #fff; }
	151	+.link-btn { background: none; border: none; padding: 0; color: var(--green); font: inherit; text-decoration: underline; cursor: pointer; }
	152	+
	153	+.btn { display: inline-flex; align-items: center; justify-content: center; gap: 8px; 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; background: var(--surface); color: var(--ink); transition: transform 0.12s ease, box-shadow 0.12s ease, background 0.15s ease, color 0.15s ease; font-family: var(--font-display); letter-spacing: 0.01em; text-decoration: none; }
	154	+.btn:hover { transform: translate(-1px, -1px); box-shadow: var(--shadow-off-mid); }
	155	+.btn:active { transform: translate(2px, 2px); box-shadow: none !important; }
	156	+.btn:disabled { opacity: 0.45; pointer-events: none; }
	157	+.btn-primary { background: var(--ink); color: var(--lime); box-shadow: 4px 4px 0 rgba(26, 18, 20,0.25); }
	158	+.btn-primary:hover { background: var(--green-deep); box-shadow: 4px 4px 0 rgba(26, 18, 20,0.25); }
	159	+.btn-ghost { background: transparent; color: var(--ink); }
	160	+.btn-ghost:hover { background: var(--lime); color: #fff; box-shadow: 4px 4px 0 rgba(26, 18, 20,0.2); }
	161	+
	162	+/* ================= Chips ================= */
	163	+.chips { display: flex; gap: 8px; margin: 16px 0 4px; overflow-x: auto; padding-bottom: 6px; scrollbar-width: none; }
	164	+.chips::-webkit-scrollbar { display: none; }
	165	+.chip { display: inline-flex; align-items: center; gap: 7px; border: 1.5px solid var(--ink); background: var(--surface); color: var(--ink); border-radius: 999px; padding: 9px 18px; font-size: 13.5px; font-weight: 600; cursor: pointer; font-family: var(--font-display); white-space: nowrap; min-height: 42px; transition: transform 0.13s ease, box-shadow 0.13s ease, background 0.13s ease, color 0.13s ease; }
	166	+.chip:hover { transform: translate(-1px, -1px); box-shadow: var(--shadow-off-mid); }
	167	+.chip:active { transform: none; box-shadow: none; }
	168	+.chip.on { background: var(--ink); color: var(--lime); box-shadow: 3px 3px 0 var(--lime); }
	169	+
	170	+/* ================= Results ================= */
	171	+.results-head { display: flex; align-items: baseline; gap: 14px; margin: 28px 0 18px; flex-wrap: wrap; }
	172	+.results-head h2 { font-size: 22px; text-transform: uppercase; letter-spacing: -0.02em; }
	173	+.results-head > span { font-family: var(--font-mono); color: var(--ink-3); font-size: 12px; letter-spacing: 0.06em; }
	174	+.results-tools { display: flex; align-items: center; gap: 12px; margin-left: auto; }
	175	+.sort-ctl select { border: 1.5px solid var(--ink); background: var(--surface); border-radius: var(--r-ctl); padding: 8px 28px 8px 12px; min-height: 36px; 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; transition: box-shadow 0.13s ease; }
	176	+.sort-ctl select:hover { box-shadow: 2px 2px 0 rgba(26, 18, 20, 0.18); }
	177	+.sort-ctl select:focus { outline: none; box-shadow: 3px 3px 0 var(--lime); }
	178	+.view-toggle { display: inline-flex; border: 1.5px solid var(--ink); border-radius: var(--r-ctl); overflow: hidden; background: var(--surface); box-shadow: var(--shadow-flat); }
	179	+.view-toggle button { display: inline-flex; align-items: center; gap: 6px; border: 0; background: transparent; padding: 8px 14px; min-height: 36px; cursor: pointer; font-family: var(--font-mono); font-size: 12px; font-weight: 700; color: var(--ink-2); transition: background 0.12s ease, color 0.12s ease; }
	180	+.view-toggle button:hover { background: var(--surface-2); color: var(--ink); }
	181	+.view-toggle button + button { border-left: 1.5px solid var(--ink); }
	182	+.view-toggle button.on { background: var(--ink); color: var(--lime); box-shadow: inset 0 -2.5px 0 var(--lime); }
	183	+
	184	+.grid { display: grid; grid-template-columns: repeat(auto-fill, minmax(290px, 1fr)); gap: 22px; padding-bottom: 20px; }
	185	+@media (max-width: 640px) { .grid { grid-template-columns: 1fr; gap: 16px; } }
	186	+.more-wrap { display: flex; justify-content: center; padding: 8px 0 70px; }
	187	+
	188	+.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; }
	189	+.card:hover { transform: translate(-3px, -3px); box-shadow: var(--shadow-off); }
	190	+.card:focus-visible { outline: 3px solid var(--lime); outline-offset: 2px; }
	191	+.card-img { position: relative; aspect-ratio: 16/10.5; background: repeating-linear-gradient(45deg, #eceae3 0 12px, #f3f1ea 12px 24px); overflow: hidden; }
	192	+.card-img img { width: 100%; height: 100%; object-fit: cover; transition: transform 0.4s ease; }
	193	+.card:hover .card-img img { transform: scale(1.05); }
	194	+.card-img .noimg { display: flex; align-items: center; justify-content: center; height: 100%; color: var(--ink-3); font-size: 34px; }
	195	+.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); }
	196	+.badge.type { background: var(--ink); color: var(--lime); border-color: var(--ink); }
	197	+.badge.right { left: auto; right: 12px; background: rgba(255,255,255,0.92); border-color: transparent; }
	198	+.card-body { padding: 16px 18px; display: flex; flex-direction: column; gap: 6px; flex: 1; }
	199	+.card-price { font-family: var(--font-display); font-weight: 700; font-size: 21px; letter-spacing: -0.02em; }
	200	+.card-title { font-weight: 600; font-size: 14.5px; color: var(--ink); overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }
	201	+.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); }
	202	+.card-meta .sep { width: 4px; height: 4px; background: var(--lime); border: 1px solid var(--ink); border-radius: 1px; transform: rotate(45deg); }
	203	+.card-specs { display: flex; gap: 12px; font-size: 12.5px; color: var(--ink-2); font-family: var(--font-mono); }
	204	+.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; }
	205	+.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%; }
	206	+.avail { font-size: 11px; color: var(--ink-3); font-weight: 500; text-align: right; font-family: var(--font-mono); }
	207	+
	208	+/* ================= Skeletons ================= */
	209	+@keyframes shimmer { 0% { background-position: -400px 0; } 100% { background-position: 400px 0; } }
	210	+.skel { border-radius: var(--r-card); border: 1.5px solid var(--line); overflow: hidden; background: var(--surface); }
	211	+.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; }
	212	+.skel .sk-img { aspect-ratio: 16/10.5; }
	213	+.skel .sk-line { height: 14px; border-radius: 4px; margin: 12px 16px; }
	214	+.skel .sk-line.short { width: 45%; }
	215	+
	216	+/* ================= Empty / error ================= */
	217	+.notice { text-align: center; padding: 72px 24px; color: var(--ink-2); }
	218	+.notice .big { font-size: 44px; margin-bottom: 10px; }
	219	+.notice h2 { text-transform: uppercase; }
	220	+
	221	+/* ================= Detail page ================= */
	222	+.detail { padding: 30px 0 90px; }
	223	+.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; }
	224	+.crumbs a { border-bottom: 1.5px solid transparent; }
	225	+.crumbs a:hover { color: var(--green); border-color: var(--green); }
	226	+
	227	+/* Ordre DOM = ordre visuel sur TOUS les breakpoints (standard Groupe Ka
	228	+ « Ordre des sections — pages détail »). Interdit : `order` / `column-reverse`
	229	+ / `display:contents` pour réordonner — un bloc sans `order` retombe à
	230	+ order:0 et passe devant la galerie sur mobile (bug corrigé sur Lou-Ka).
	231	+ Mobile : colonnes empilées ; desktop : grid 2 colonnes (fiche \| annexes). */
	232	+.fiche { display: flex; flex-direction: column; gap: 22px; }
	233	+.f-col { display: flex; flex-direction: column; gap: 22px; min-width: 0; }
	234	+@media (min-width: 900px) {
	235	+ .fiche { display: grid; grid-template-columns: 1.6fr 1fr; gap: 30px; align-items: start; }
	236	+ .f-col { gap: 26px; }
	237	+ .f-col:last-child { position: sticky; top: 88px; }
	238	+}
	239	+.f-bloc { min-width: 0; }
	240	+.f-bloc h2 { font-size: 21px; letter-spacing: -0.02em; margin-bottom: 12px; border-left: 4px solid var(--lime); padding-left: 10px; }
	241	+.f-bloc:empty { display: none; }
	242	+
	243	+/* galerie */
	244	+.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); }
	245	+.carousel-track { display: flex; overflow-x: auto; scroll-snap-type: x mandatory; -webkit-overflow-scrolling: touch; scrollbar-width: none; aspect-ratio: 16/11; }
	246	+.carousel-track::-webkit-scrollbar { display: none; }
	247	+.carousel-track img { flex: 0 0 100%; width: 100%; object-fit: cover; scroll-snap-align: center; cursor: zoom-in; }
	248	+.carousel-empty { display: flex; align-items: center; justify-content: center; aspect-ratio: 16/11; font-size: 48px; }
	249	+.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; }
	250	+.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; }
	251	+.carousel-nav.prev { left: 10px; } .carousel-nav.next { right: 10px; }
	252	+@media (max-width: 640px) { .carousel-nav { display: none; } }
	253	+.thumbs { display: grid; grid-template-columns: repeat(auto-fill, minmax(84px, 1fr)); gap: 8px; margin-top: 10px; }
	254	+.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; }
	255	+.thumbs button:hover { transform: translateY(-2px); }
	256	+.thumbs button.on { border-color: var(--ink); box-shadow: 3px 3px 0 var(--lime); }
	257	+.thumbs img { width: 100%; height: 100%; object-fit: cover; }
	258	+@media (max-width: 640px) { .thumbs { display: flex; overflow-x: auto; scrollbar-width: none; } .thumbs::-webkit-scrollbar { display: none; } .thumbs button { flex: 0 0 84px; } }
	259	+
	260	+/* lightbox */
	261	+.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; }
	262	+.lightbox img { max-width: 94vw; max-height: 86vh; border-radius: 6px; border: 2px solid var(--lime); object-fit: contain; }
	263	+.lb-close { position: absolute; top: 18px; right: 22px; background: none; border: none; color: #fff; font-size: 30px; cursor: pointer; }
	264	+.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; }
	265	+.lb-nav.prev { left: 6px; } .lb-nav.next { right: 6px; }
	266	+.lb-count { position: absolute; bottom: 24px; color: #c9ccc2; font-family: var(--font-mono); font-size: 13px; }
	267	+
	268	+/* hero panneau (colonne droite) */
	269	+.f-hero { background: var(--surface); border: 1.5px solid var(--ink); border-radius: var(--r-card); box-shadow: var(--shadow-off-soft); padding: 26px; }
	270	+.price-kicker { font-family: var(--font-mono); font-size: 10px; text-transform: uppercase; letter-spacing: 0.14em; color: var(--green); }
	271	+.price-kicker::before { content: ""; display: inline-block; width: 16px; height: 2px; background: var(--lime); vertical-align: 3px; margin-right: 7px; }
	272	+.price-row { display: flex; align-items: baseline; gap: 12px; flex-wrap: wrap; }
	273	+.f-hero .price { font-family: var(--font-display); font-size: clamp(30px, 6vw, 40px); font-weight: 700; letter-spacing: -0.03em; }
	274	+.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; }
	275	+.price-sub { font-family: var(--font-mono); font-size: 11.5px; color: var(--ink-3); margin-top: 2px; }
	276	+.f-hero h1 { font-size: clamp(20px, 4.5vw, 24px); margin-top: 10px; }
	277	+.f-hero .loc { color: var(--ink-2); font-size: 13.5px; margin-top: 3px; display: flex; align-items: center; gap: 5px; }
	278	+.f-hero .loc .ico { color: var(--lime); }
	279	+
	280	+/* liste de specs — fiche technique premium */
	281	+.spec-list { margin: 18px 0 4px; border-top: 1.5px solid var(--line-strong); }
	282	+.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); }
	283	+.spec-row:last-child { border-bottom: 1.5px solid var(--line-strong); }
	284	+.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); }
	285	+.spec-k { font-family: var(--font-mono); font-size: 10.5px; text-transform: uppercase; letter-spacing: 0.08em; color: var(--ink-2); }
	286	+.spec-v { font-family: var(--font-display); font-size: 15.5px; font-weight: 700; text-align: right; }
	287	+.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); }
	288	+.deal-ok { background: var(--lime-soft); border-color: var(--green); color: var(--green-deep); }
	289	+
	290	+.specs-grid { display: grid; grid-template-columns: repeat(auto-fill, minmax(96px, 1fr)); gap: 8px; margin: 18px 0; }
	291	+.spec { border: 1.5px solid var(--line-strong); border-radius: var(--r-ctl); padding: 9px 11px; background: var(--surface-2); }
	292	+.spec b { display: block; font-family: var(--font-display); font-size: 16px; }
	293	+.spec span { font-family: var(--font-mono); font-size: 9.5px; text-transform: uppercase; letter-spacing: 0.08em; color: var(--ink-3); }
	294	+
	295	+.broker { margin: 16px 0; padding: 14px; border: 1.5px dashed var(--line-strong); border-radius: var(--r-ctl); background: var(--surface-2); }
	296	+.broker-k { font-family: var(--font-mono); font-size: 9.5px; text-transform: uppercase; letter-spacing: 0.1em; color: var(--ink-3); }
	297	+.broker-name { font-family: var(--font-display); font-weight: 700; font-size: 15px; margin-top: 3px; }
	298	+.broker-tel { display: inline-block; margin-top: 6px; color: var(--green-deep); font-weight: 600; border-bottom: 1.5px solid var(--lime); }
	299	+
	300	+.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; }
	301	+.cta:hover { background: var(--lime); color: #fff; }
	302	+.cta:active { transform: translate(2px, 2px); box-shadow: none; }
	303	+.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; }
	304	+
	305	+.desc-text { color: var(--ink-2); font-size: 14.5px; white-space: pre-line; line-height: 1.6; margin: 0; }
	306	+
	307	+/* tableau caractéristiques */
	308	+.dtable { display: grid; grid-template-columns: repeat(auto-fill, minmax(240px, 1fr)); gap: 0 22px; }
	309	+.drow { display: flex; justify-content: space-between; gap: 12px; padding: 8px 0; border-bottom: 1px solid var(--line); font-size: 13.5px; }
	310	+.drow span { color: var(--ink-3); } .drow b { text-align: right; font-family: var(--font-display); }
	311	+
	312	+/* tableau pièces */
	313	+.rooms-wrap { overflow-x: auto; border: 1.5px solid var(--line-strong); border-radius: var(--r-card); }
	314	+table.rooms { width: 100%; border-collapse: collapse; font-size: 13.5px; min-width: 460px; }
	315	+table.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; }
	316	+table.rooms td { padding: 8px 12px; border-bottom: 1px solid var(--line); }
	317	+table.rooms tr:last-child td { border-bottom: none; }
	318	+table.rooms tr:nth-child(even) td { background: var(--surface-2); }
	319	+
	320	+.amenity-row { display: flex; flex-wrap: wrap; gap: 7px; }
	321	+.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; }
	322	+
	323	+.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); }
	324	+.prix-histo.down { background: var(--lime-soft); border-color: var(--green); color: var(--green-deep); }
	325	+
	326	+.mini-map { height: 320px; border: 1.5px solid var(--line-strong); border-radius: var(--r-card); overflow: hidden; }
	327	+.mini-map .mapview { border: none; border-radius: 0; box-shadow: none; height: 100%; }
	328	+
	329	+.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)); }
	330	+.cta-sticky .cta { flex: 1; margin: 0; }
	331	+.cta-sticky-prix { font-family: var(--font-display); font-weight: 700; font-size: 19px; white-space: nowrap; }
	332	+@media (min-width: 900px) { .cta-sticky { display: none; } }
	333	+@media (max-width: 899px) { .detail { padding-bottom: 84px; } }
	334	+.f-foot { margin-top: 26px; }
	335	+.fine { font-size: 12px; color: var(--ink-3); }
	336	+
	337	+/* Box « Aussi publiée sur… » : autres publications de la même propriété */
	338	+.dups-note { font-size: 13px; color: var(--ink-3); margin: 4px 0 10px; }
	339	+.dups-list { display: flex; flex-direction: column; gap: 8px; }
	340	+.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); background: var(--surface-2); transition: all 0.14s ease; min-height: 44px; }
	341	+.dup-item:hover { border-color: var(--ink); box-shadow: 3px 3px 0 rgba(26, 18, 20, 0.18); }
	342	+.dup-src { font-family: var(--font-display); font-weight: 700; font-size: 14px; }
	343	+.dup-broker { font-size: 12.5px; color: var(--ink-3); }
	344	+.dup-go { margin-left: auto; font-size: 12.5px; font-weight: 600; color: var(--green-deep); border-bottom: 1.5px solid var(--lime); white-space: nowrap; }
	345	+.dup-go .ico { vertical-align: -2px; }
	346	+
	347	+/* ================= Sources / Agences ================= */
	348	+.sources { padding: 44px 0 90px; }
	349	+.sources h1 { font-size: clamp(28px, 4vw, 40px); text-transform: uppercase; margin: 10px 0 6px; }
	350	+.sources .sub { color: var(--ink-2); margin-bottom: 30px; max-width: 720px; }
	351	+.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); }
	352	+.src-table { width: 100%; border-collapse: separate; border-spacing: 0; min-width: 760px; }
	353	+.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); }
	354	+.src-table td { padding: 13px 18px; border-bottom: 1px solid var(--line); font-size: 14px; vertical-align: top; }
	355	+.src-table tr:last-child td { border-bottom: none; }
	356	+.src-table tr:hover td { background: var(--surface-2); }
	357	+.src-table a { color: var(--green-deep); font-weight: 600; border-bottom: 1.5px solid var(--lime); }
	358	+.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; }
	359	+.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; }
	360	+.count-pill { font-weight: 700; font-family: var(--font-display); font-size: 16px; border-bottom: 1.5px solid var(--lime); }
	361	+
	362	+/* ================= Stats ================= */
	363	+.stats-page { padding: 44px 0 90px; }
	364	+.stats-title { font-size: clamp(30px, 4.6vw, 46px); text-transform: uppercase; margin: 10px 0 6px; }
	365	+.stats-page .sub { color: var(--ink-2); max-width: 660px; margin-bottom: 30px; }
	366	+.tiles { display: grid; grid-template-columns: repeat(auto-fit, minmax(160px, 1fr)); gap: 14px; margin-bottom: 30px; }
	367	+.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); }
	368	+.tile-v { font-family: var(--font-display); font-weight: 700; font-size: clamp(22px, 3vw, 32px); letter-spacing: -0.03em; line-height: 1.05; }
	369	+.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; }
	370	+.hero-tile { background: var(--ink); color: var(--lime); border-color: var(--ink); }
	371	+.hero-tile .tile-k { color: rgba(15, 107, 79, 0.7); }
	372	+.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; }
	373	+/* mobile : une table large ne doit JAMAIS déborder la page (grid blowout) —
	374	+ chaque bloc de la page Stats défile horizontalement en interne au besoin */
	375	+.stats-page section, .stats-page > * { min-width: 0; max-width: 100%; }
	376	+@media (max-width: 640px) { .stats-page .viz-card { padding: 18px 14px 14px; } }
	377	+.viz-card h2 { font-size: 19px; text-transform: uppercase; letter-spacing: -0.01em; }
	378	+.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; }
	379	+.viz-grid { display: grid; grid-template-columns: 1fr 1fr; gap: 22px; }
	380	+@media (max-width: 900px) { .viz-grid { grid-template-columns: 1fr; } }
	381	+.hbars { display: flex; flex-direction: column; gap: 7px; }
	382	+.hbar-row { display: grid; grid-template-columns: minmax(96px, 180px) 1fr auto; gap: 12px; align-items: center; min-height: 26px; }
	383	+.hbar-label { font-size: 13px; font-weight: 600; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }
	384	+.hbar-label a { border-bottom: 1.5px solid var(--lime); }
	385	+.hbar-label a:hover { color: var(--green-deep); }
	386	+.hbar-track { background: var(--surface-2); border-radius: 0 4px 4px 0; height: 18px; overflow: hidden; }
	387	+.hbar-fill { display: block; height: 100%; background: var(--green); border-radius: 0 4px 4px 0; min-width: 2px; transition: background 0.12s ease; }
	388	+.hbar-row:hover .hbar-fill { background: var(--ink); box-shadow: inset 0 0 0 2px var(--lime); }
	389	+.hbar-value { font-family: var(--font-mono); font-size: 11.5px; font-weight: 700; white-space: nowrap; }
	390	+.hbar-value em { font-style: normal; font-weight: 500; color: var(--ink-3); }
	391	+.viz-table { margin-top: 4px; }
	392	+.viz-table table { width: 100%; border-collapse: collapse; font-size: 13px; }
	393	+.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); }
	394	+.viz-table td { padding: 6px 10px; border-bottom: 1px solid var(--line); }
	395	+.stats-foot { font-family: var(--font-mono); font-size: 11px; color: var(--ink-3); letter-spacing: 0.04em; margin-top: 6px; }
	396	+
	397	+/* ---- Iconographie maison (Icons.tsx) ---- */
	398	+.ico { vertical-align: -3px; flex-shrink: 0; }
	399	+.card-specs span { display: inline-flex; align-items: center; gap: 5px; }
	400	+.card-specs .ico { color: var(--green); }
	401	+.badge.right .ico { vertical-align: -2px; }
	402	+.noimg .ico, .carousel-empty .ico { color: var(--ink-3); }
	403	+.notice .big .ico { color: var(--lime); }
	404	+.amenity .ico { color: var(--green); margin-right: 2px; }
	405	+.q-badge .ico { vertical-align: -3px; margin-right: 2px; }
	406	+.q-bar-label { display: inline-flex; align-items: center; gap: 7px; }
	407	+.q-bar-label .ico { color: var(--green); }
	408	+.mm-ico .ico { vertical-align: -4px; }
	409	+.mv-noimg svg { color: var(--ink-3); }
	410	+.broker-tel .ico { vertical-align: -2.5px; }
	411	+.cta .ico { vertical-align: -2.5px; margin-left: 3px; }
	412	+.prix-histo .ico { vertical-align: -3.5px; }
	413	+.spec { position: relative; }
	414	+.spec-ico { position: absolute; top: 10px; right: 10px; color: var(--lime); opacity: 0.85; }
	415	+
	416	+/* ---- Survalorisation vs Vrai-Prix (jauges divergentes) ---- */
	417	+.vpg-axis { display: grid; grid-template-columns: 220px 1fr 74px 90px; gap: 10px; margin-bottom: 2px; }
	418	+.vpg-axis > div { grid-column: 2; display: flex; justify-content: space-between; font-family: var(--font-mono); font-size: 10px; color: var(--ink-3); }
	419	+.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); }
	420	+.vpg-row:last-of-type { border-bottom: none; }
	421	+.vpg-name { font-size: 13.5px; font-weight: 600; }
	422	+.vpg-name em { display: block; font-style: normal; font-family: var(--font-mono); font-size: 10px; color: var(--ink-3); }
	423	+.vpg-track { position: relative; height: 18px; background: var(--surface-2); border: 1px solid var(--line); border-radius: 999px; overflow: hidden; }
	424	+.vpg-zero { position: absolute; left: 50%; top: 0; bottom: 0; width: 1.5px; background: var(--line-strong); opacity: 0.5; }
	425	+.vpg-band { position: absolute; top: 3px; bottom: 3px; background: rgba(26, 18, 20, 0.14); border-radius: 999px; }
	426	+.vpg-median { position: absolute; top: 1px; bottom: 1px; width: 4px; margin-left: -2px; border-radius: 2px; }
	427	+.vpg-median.vp-sur { background: var(--lime); }
	428	+.vpg-median.vp-juste { background: #d9a942; }
	429	+.vpg-median.vp-sous { background: #4c8b4f; }
	430	+.vpg-value { font-family: var(--font-display); font-weight: 700; font-size: 15px; text-align: right; }
	431	+.vpg-value.vp-sur { color: var(--green); }
	432	+.vpg-value.vp-juste { color: #a97b1e; }
	433	+.vpg-value.vp-sous { color: #3c7440; }
	434	+.vpg-split { display: flex; height: 10px; border-radius: 999px; overflow: hidden; border: 1px solid var(--line); }
	435	+.vps-sous { background: #7fb283; }
	436	+.vps-juste { background: #d9cfc7; }
	437	+.vps-sur { background: var(--lime); }
	438	+.vpg-sep { border-top: 1.5px solid var(--line-strong); margin: 4px 0; }
	439	+.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; }
	440	+.vpg-legend i { display: inline-block; width: 14px; height: 9px; border-radius: 999px; margin-right: 5px; vertical-align: -1px; }
	441	+@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; } }
	442	+
	443	+/* ================= Carte (Ka Maps — framework partagé Groupe Ka) =========
	444	+ Jetons du design system appliqués au chrome de la carte, mêmes réglages
	445	+ que Lou-Ka Maps. */
	446	+.mapview .ka-map, .lmap3d .ka-map {
	447	+ --ka-accent: var(--accent);
	448	+ --ka-on-accent: var(--on-accent);
	449	+ --ka-surface: var(--surface);
	450	+ --ka-ink: var(--ink);
	451	+ --ka-line: var(--line-strong);
	452	+ --ka-radius: var(--r-ctl);
	453	+ --ka-shadow: 0 8px 24px rgba(26, 18, 20, 0.14);
	454	+ --ka-font: var(--font-body);
	455	+}
	456	+.mapview { position: relative; overflow: hidden; }
	457	+.mapview .ka-map { position: absolute; inset: 0; }
	458	+
	459	+/* mini-carte 3D de la fiche (Emplacement) — bâtiment de l'annonce en cerise */
	460	+.lmap3d {
	461	+ position: relative; height: 340px; border: 1.5px solid var(--ink);
	462	+ border-radius: var(--r-card); box-shadow: var(--shadow-off-soft);
	463	+ overflow: hidden; background: var(--surface-2);
	464	+}
	465	+.lmap3d-skel {
	466	+ background: linear-gradient(90deg, #eeece5 25%, #f7f5ef 50%, #eeece5 75%);
	467	+ background-size: 800px 100%; animation: shimmer 1.4s infinite linear;
	468	+}
	469	+.lmap3d-legende {
	470	+ position: absolute; left: 10px; bottom: 10px; z-index: 5;
	471	+ display: inline-flex; align-items: center; gap: 6px;
	472	+ padding: 4px 10px; border: 1.5px solid var(--ink);
	473	+ border-radius: 999px; background: var(--surface);
	474	+ font-size: 10.5px; font-weight: 500; color: var(--ink-2);
	475	+ pointer-events: none;
	476	+}
	477	+.lmap3d-legende i {
	478	+ width: 10px; height: 10px; border-radius: 3px;
	479	+ background: var(--accent); border: 1px solid rgba(26, 18, 20, 0.25);
	480	+}
	481	+@media (max-width: 780px) { .lmap3d { height: 280px; } }
	482	+
	483	+/* ================= Carte ================= */
	484	+.map-split { display: grid; grid-template-columns: minmax(300px, 400px) 1fr; gap: 18px; height: calc(100dvh - 200px); min-height: 420px; }
	485	+.map-list { overflow-y: auto; display: flex; flex-direction: column; gap: 14px; padding-right: 4px; scrollbar-width: thin; }
	486	+.map-list .card { margin: 0; flex: 0 0 auto; }
	487	+/* sync liste ↔ carte : fiche sélectionnée depuis une pastille de la carte */
	488	+.map-card { border-radius: var(--r-card); }
	489	+.map-card-sel .card { border-color: var(--accent); box-shadow: 4px 4px 0 var(--accent-soft), 0 0 0 2px var(--accent); }
	490	+.mapwrap { position: relative; width: 100%; height: 100%; }
	491	+.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); }
	492	+.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; }
	493	+.mv-brand b { color: var(--ink); }
	494	+.mv-brand-dot { width: 8px; height: 8px; border-radius: 50%; background: var(--lime); box-shadow: 0 0 0 3px var(--lime-soft); }
	495	+.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; }
	496	+.mv-legend span { display: flex; align-items: center; gap: 7px; }
	497	+.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); }
	498	+.mv-lg-deal { background: var(--lime); border-color: var(--green); }
	499	+.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; }
	500	+.mv-credit b { color: var(--ink); }
	501	+.mini-map .mv-brand, .mini-map .mv-legend { display: none; }
	502	+.mini-map .mapwrap { height: 100%; }
	503	+
	504	+/* ---- carte propriété (fiche) : marqueur pulsant + anneaux piéton ---- */
	505	+.pm-wrap { position: relative; width: 100%; height: 100%; }
	506	+.pm-marker { display: flex; flex-direction: column; align-items: center; }
	507	+.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; }
	508	+.pm-pill-deal { background: var(--lime); border-color: var(--green); color: #fff; }
	509	+.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); }
	510	+.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; }
	511	+@keyframes pm-pulse { 0% { transform: scale(0.5); opacity: 0.45; } 80% { transform: scale(1.9); opacity: 0; } 100% { opacity: 0; } }
	512	+.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; }
	513	+.mini-map .pm-wrap .mv-credit { display: block; }
	514	+.map-loading { display: flex; align-items: center; justify-content: center; color: var(--ink-3); font-family: var(--font-mono); font-size: 13px; }
	515	+@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; } }
	516	+.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); }
	517	+.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); }
	518	+.mv-pop img, .mv-noimg { width: 100%; height: 130px; object-fit: cover; }
	519	+.mv-noimg { display: flex; align-items: center; justify-content: center; font-size: 34px; background: var(--surface-2); }
	520	+.mv-pop-body { padding: 10px 12px 12px; }
	521	+.mv-pop-price { font-family: var(--font-display); font-weight: 700; font-size: 18px; }
	522	+.mv-pop-title { font-size: 13px; color: var(--ink-2); margin-top: 2px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }
	523	+.mv-pop-meta { font-family: var(--font-mono); font-size: 11px; color: var(--ink-2); margin-top: 6px; }
	524	+.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; }
	525	+.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; }
	526	+.mv-pop-cta:hover { background: var(--green-deep); }
	527	+.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; }
	528	+.maplibregl-ctrl-attrib { font-size: 10px; }
	529	+
	530	+/* ================= Menu mobile ================= */
	531	+.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; }
	532	+.menu-btn:active { transform: translate(2px, 2px); box-shadow: 1px 1px 0 rgba(26, 18, 20,0.15); }
	533	+.menu-btn span { display: block; width: 18px; height: 2px; background: var(--ink); border-radius: 2px; transition: transform 0.25s ease, opacity 0.2s ease; }
	534	+.menu-btn.open span:nth-child(1) { transform: translateY(7px) rotate(45deg); }
	535	+.menu-btn.open span:nth-child(2) { opacity: 0; }
	536	+.menu-btn.open span:nth-child(3) { transform: translateY(-7px) rotate(-45deg); }
	537	+/* KA Nav v2 (2026-08-25) : panneau PLEIN ECRAN fixed inset:0 - visible peu
	538	+ importe le scroll (l'ancien dropdown absolute 480px clippait/se coupait). */
	539	+.mobile-menu {
	540	+ display: none; position: fixed; inset: 0;
	541	+ background: var(--paper);
	542	+ padding: 76px 16px calc(24px + env(safe-area-inset-bottom));
	543	+ overflow-y: auto; overscroll-behavior: contain;
	544	+}
	545	+.mobile-menu.open { display: block; animation: mm-in 0.16s ease; }
	546	+@keyframes mm-in { from { opacity: 0; transform: translateY(8px); } to { opacity: 1; transform: none; } }
	547	+/* burger masque a l'ouverture : la fermeture passe par le X fixe du panneau */
	548	+.header:has(.mobile-menu.open) .menu-btn { visibility: hidden; }
	549	+/* bouton de fermeture du panneau : fixe en haut a droite du viewport */
	550	+.mm-close {
	551	+ position: fixed; top: 10px; right: 14px; z-index: 2;
	552	+ width: 44px; height: 44px; display: flex; align-items: center; justify-content: center;
	553	+ border: 1.5px solid var(--ink); border-radius: 999px;
	554	+ background: var(--ink); color: var(--paper);
	555	+ font-size: 17px; font-weight: 700; line-height: 1; cursor: pointer; padding: 0;
	556	+}
	557	+/* verrou du scroll d'arriere-plan quand le menu est ouvert (CSS pur) */
	558	+html:has(.mobile-menu.open) { overflow: hidden; }
	559	+.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; }
	560	+.mobile-menu.open .mm-link { opacity: 1; transform: translateY(0); }
	561	+.mm-link.active { color: var(--green); }
	562	+.mm-ico { width: 26px; text-align: center; font-size: 17px; }
	563	+.mm-arrow { margin-left: auto; opacity: 0.25; }
	564	+.mm-link:active { background: var(--lime-soft); border-radius: var(--r-ctl); }
	565	+.mm-foot { padding: 12px 10px 4px; font-family: var(--font-mono); font-size: 10.5px; color: var(--ink-3); letter-spacing: 0.04em; }
	566	+.mm-backdrop { position: fixed; inset: 0; z-index: var(--z-overlay, 800); background: rgba(26, 18, 20, 0.35); backdrop-filter: blur(2px); }
	567	+@media (max-width: 760px) { .menu-btn { display: flex; } .nav { display: none; } }
	568	+
	569	+/* ================= Footer =================
	570	+ Remplacé par le footer commun Groupe KA (ka/KaFooter.tsx — styles .ka-footer
	571	+ dans ka/tokens.css). */
	572	+
	573	+/* ================= Mobile : feuille de filtres + FAB ================= */
	574	+.sheet-head { display: none; }
	575	+.sheet-handle { display: none; }
	576	+.sheet-apply { display: none; }
	577	+.sheet-backdrop { display: none; }
	578	+.fab { display: none; }
	579	+.fab-badge { display: inline-grid; place-items: center; min-width: 20px; height: 20px; padding: 0 6px; border-radius: 999px; background: var(--lime); color: #fff; font-size: 11.5px; font-weight: 700; font-variant-numeric: tabular-nums; margin-left: 2px; }
	580	+@media (max-width: 640px) {
	581	+ .header-inner { height: 56px; }
	582	+ .brand { font-size: 21px; }
	583	+ .hero h1 { font-size: clamp(30px, 9.4vw, 44px); }
	584	+ .hero p.lede { font-size: 15px; }
	585	+ .stat-row { flex-wrap: nowrap; overflow-x: auto; scrollbar-width: none; padding-bottom: 6px; margin-right: -16px; padding-right: 16px; }
	586	+ .stat-row::-webkit-scrollbar { display: none; }
	587	+ .stat-chip { flex: 0 0 auto; white-space: nowrap; }
	588	+ .filterbar { display: none; }
	589	+ .filterbar.open .f-primary { flex-direction: column; }
	590	+ .filterbar.open .f-ctl select { max-width: none; width: 100%; }
	591	+ .filterbar.open .f-more { display: none; }
	592	+ .filterbar.open { display: flex; flex-direction: column; gap: 12px; position: fixed; left: 0; right: 0; bottom: 0; z-index: var(--z-modal, 900); 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: 10px 18px calc(18px + env(safe-area-inset-bottom)); box-shadow: 0 -16px 48px rgba(16, 18, 16, 0.35); animation: sheet-up 0.24s cubic-bezier(0.2, 0.9, 0.3, 1); }
	593	+ @keyframes sheet-up { from { transform: translateY(30%); opacity: 0.4; } to { transform: none; opacity: 1; } }
	594	+ .filterbar.open .sheet-handle { display: block; flex: none; width: 44px; height: 5px; border-radius: 999px; background: var(--line); margin: 0 auto 2px; }
	595	+ .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: -10px; background: var(--surface); padding: 6px 0 8px; border-bottom: 1.5px solid var(--line); margin-bottom: 2px; z-index: 1; }
	596	+ .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; }
	597	+ .filterbar.open .sheet-apply { display: flex; width: 100%; min-height: 50px; position: sticky; bottom: 0; z-index: 1; box-shadow: 0 -14px 18px -12px rgba(16, 18, 16, 0.4), 5px 5px 0 var(--lime); }
	598	+ .sheet-backdrop { display: block; position: fixed; inset: 0; z-index: 90; background: rgba(16, 18, 16, 0.45); backdrop-filter: blur(2px); }
	599	+ .fab { display: flex; align-items: center; gap: 8px; 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(15, 107, 79, 0.55); }
	600	+ .fab:active { transform: translateX(-50%) scale(0.97); }
	601	+ .results-head { margin-top: 20px; }
	602	+ .chips { margin-right: -16px; padding-right: 16px; }
	603	+ .notice { padding: 48px 16px; }
	604	+}
	605	+@media (max-width: 900px) { .f-search input, .f-native, .f-ctl select { font-size: 16px; } }
	606	+
	607	+/* --- Sources : bannières → sous-agences -------------------------------- */
	608	+.franchise-list { display: flex; flex-direction: column; gap: 10px; margin: 18px 0; }
	609	+.franchise { border: 2px solid var(--ink); background: var(--surface); box-shadow: var(--shadow-off-soft); }
	610	+.franchise-head {
	611	+ width: 100%; display: flex; align-items: center; gap: 12px; padding: 14px 16px;
	612	+ background: none; border: 0; cursor: pointer; font-family: var(--font-display);
	613	+ font-size: 16px; font-weight: 600; color: var(--ink); text-align: left;
	614	+}
	615	+.franchise-head:hover { background: var(--surface-2); }
	616	+.fh-caret { color: var(--green); width: 14px; }
	617	+.fh-name { flex: 1; }
	618	+.fh-sub { font-size: 12px; font-weight: 500; color: var(--ink-3); font-family: var(--font-mono); }
	619	+.fh-count {
	620	+ font-family: var(--font-mono); font-weight: 700; background: var(--ink);
	621	+ color: var(--lime); padding: 3px 10px; min-width: 64px; text-align: right;
	622	+}
	623	+.subagency-list { list-style: none; margin: 0; padding: 0 16px 10px 40px; border-top: 1px solid var(--line); }
	624	+.subagency-list li {
	625	+ display: flex; align-items: center; justify-content: space-between; gap: 12px;
	626	+ padding: 8px 0; border-bottom: 1px dotted var(--line); font-size: 14px;
	627	+}
	628	+.subagency-list li:last-child { border-bottom: 0; }
	629	+.sa-name { color: var(--ink-2); }
	630	+
	631	+/* --- Pagination (accueil) ---------------------------------------------- */
	632	+.pager { display: flex; flex-wrap: wrap; align-items: center; justify-content: center;
	633	+ gap: 6px; margin: 32px 0 8px; }
	634	+.pager-btn {
	635	+ font-family: var(--font-mono); font-size: 14px; min-width: 42px; min-height: 42px; padding: 8px 12px;
	636	+ border: 2px solid var(--ink); border-radius: 8px; background: var(--surface); color: var(--ink);
	637	+ cursor: pointer; box-shadow: 3px 3px 0 rgba(26, 18, 20, 0.14);
	638	+ transition: transform 0.12s ease, box-shadow 0.12s ease, background 0.12s ease;
	639	+}
	640	+.pager-btn:hover:not(:disabled):not(.on) { background: var(--lime-soft); transform: translate(-1px, -1px); box-shadow: 4px 4px 0 rgba(26, 18, 20, 0.2); }
	641	+.pager-btn:active:not(:disabled) { transform: none; box-shadow: none; }
	642	+.pager-btn.on { background: var(--ink); color: var(--lime); font-weight: 700; box-shadow: 3px 3px 0 var(--lime); }
	643	+.pager-btn:disabled { opacity: .4; cursor: not-allowed; box-shadow: none; }
	644	+.pager-gap { padding: 0 4px; color: var(--ink-3); }
	645	+.pager-info { width: 100%; text-align: center; margin-top: 8px; font-size: 12px;
	646	+ color: var(--ink-3); font-family: var(--font-mono); }
	647	+
	648	+
	649	+
	650	+/* --- Le quartier (census / proximité / chaleur / crime) — porté de Lou-Ka --- */
	651	+/* --- Section « Le quartier » (fiche) --------------------------------------- */
	652	+.quartier { margin-top: 34px; }
	653	+.quartier h2 { font-size: 24px; letter-spacing: -0.02em; }
	654	+.q-sub { color: var(--ink-3); font-size: 13px; margin: 4px 0 16px; }
	655	+.q-grid {
	656	+ display: grid; grid-template-columns: repeat(3, 1fr); gap: 10px;
	657	+}
	658	+.q-grid { grid-template-columns: repeat(2, 1fr); }
	659	+.q-cell {
	660	+ background: var(--surface); border: 1.5px solid var(--line-strong);
	661	+ border-radius: var(--r-card); padding: 12px 14px; box-shadow: var(--shadow-flat);
	662	+}
	663	+.q-val { font-family: var(--font-display); font-weight: 700; font-size: 19px; letter-spacing: -0.02em; }
	664	+.q-label { font-family: var(--font-mono); font-size: 10.5px; color: var(--ink-3);
	665	+ text-transform: uppercase; letter-spacing: 0.06em; margin-top: 3px; }
	666	+.q-prox { margin-top: 18px; display: flex; flex-direction: column; gap: 8px; }
	667	+.q-bar { display: flex; align-items: center; gap: 10px; font-size: 13px; }
	668	+.q-bar-label { flex: 0 0 150px; color: var(--ink-2); }
	669	+.q-bar-label { flex-basis: 120px; font-size: 12px; }
	670	+.q-bar-track {
	671	+ flex: 1; height: 10px; background: var(--surface-2);
	672	+ border: 1px solid var(--line-strong); border-radius: 999px; overflow: hidden;
	673	+}
	674	+.q-bar-fill { display: block; height: 100%; background: var(--green); border-radius: 999px; }
	675	+.q-bar-num { flex: 0 0 30px; text-align: right; font-family: var(--font-mono);
	676	+ font-size: 11.5px; font-weight: 700; }
	677	+.q-badges { display: flex; flex-wrap: wrap; gap: 8px; margin-top: 16px; }
	678	+.q-badge {
	679	+ display: inline-flex; align-items: center; gap: 6px;
	680	+ border: 1.5px solid var(--line-strong); border-radius: 999px;
	681	+ padding: 7px 13px; font-size: 12.5px; background: var(--surface);
	682	+}
	683	+.q-badge.cool { background: var(--lime-soft); border-color: var(--green); color: var(--green-deep); }
	684	+.q-badge.hot { background: var(--amber-soft); border-color: var(--amber); color: #8a5a12; }
	685	+.quartier .fine { margin-top: 10px; }
	686	+.q-cell { padding: 9px 11px; }
	687	+.q-val { font-size: 16px; }
	688	+.q-bar { gap: 8px; font-size: 12px; }
	689	+.q-bar-track { height: 8px; }
	690	+.q-badge-sub { display: block; font-size: 10.5px; color: var(--ink-3); font-weight: 400; margin-left: 4px; }
	691	+
	692	+/* --- Vrai-Prix : estimation de valeur ---------------------------------- */
	693	+.vraiprix { border: 2px solid var(--ink); background: var(--surface-2);
	694	+ box-shadow: var(--shadow-off-soft); padding: 14px; margin: 14px 0; }
	695	+.vp-head { display: flex; align-items: center; justify-content: space-between; gap: 8px; }
	696	+.vp-logo { font-family: var(--font-display); font-weight: 700; color: var(--green-deep);
	697	+ letter-spacing: -.3px; }
	698	+.vp-conf { font-family: var(--font-mono); font-size: 11px; padding: 2px 7px; border: 1px solid var(--ink); }
	699	+.vp-conf-A { background: var(--lime); color: #fff; } .vp-conf-B { background: var(--lime-soft); }
	700	+.vp-conf-C { background: var(--amber-soft); } .vp-conf-D { background: #f0d9d9; }
	701	+.vp-k { font-size: 11px; color: var(--ink-3); text-transform: uppercase;
	702	+ letter-spacing: .5px; margin-top: 8px; }
	703	+.vp-value { font-family: var(--font-display); font-size: 26px; font-weight: 700;
	704	+ letter-spacing: -1px; color: var(--ink); }
	705	+.vp-range { font-size: 12px; color: var(--ink-2); font-family: var(--font-mono); }
	706	+/* jauge Vrai-Prix : fourchette P10–P90 + marqueurs estimation / prix demandé */
	707	+.vp-gauge { margin-top: 10px; }
	708	+.vp-gauge-track { position: relative; height: 14px; border-radius: 999px; background: var(--surface); border: 1px solid var(--line-strong); overflow: hidden; }
	709	+.vp-gauge-band { position: absolute; inset: 3px 6%; background: linear-gradient(90deg, var(--lime-soft), rgba(15, 107, 79, 0.35), var(--lime-soft)); border-radius: 999px; }
	710	+.vp-gauge-est { position: absolute; top: 0; bottom: 0; width: 4px; margin-left: -2px; background: var(--lime); border-radius: 2px; }
	711	+.vp-gauge-ask { position: absolute; top: 2px; bottom: 2px; width: 4px; margin-left: -2px; background: var(--ink); border-radius: 2px; }
	712	+.vp-gauge-ends { display: flex; justify-content: space-between; font-family: var(--font-mono); font-size: 10px; color: var(--ink-3); margin-top: 4px; }
	713	+.vp-gauge-legend { display: flex; gap: 14px; font-family: var(--font-mono); font-size: 10px; color: var(--ink-2); margin-top: 5px; }
	714	+.vp-dot-est, .vp-dot-ask { display: inline-block; width: 9px; height: 9px; border-radius: 3px; margin-right: 4px; vertical-align: -1px; }
	715	+.vp-dot-est { background: var(--lime); }
	716	+.vp-dot-ask { background: var(--ink); }
	717	+.vp-delta { font-size: 13px; margin-top: 8px; padding: 6px 8px; border-radius: var(--r-ctl); }
	718	+.vp-over { background: #f6e2e2; color: #8a2b2b; }
	719	+.vp-under { background: #e2f0e6; color: #1c5c41; }
	720	+.vp-fair { background: var(--surface); color: var(--ink-2); }
	721	+.vp-link { display: block; text-align: center; margin-top: 10px; font-weight: 700;
	722	+ font-size: 13px; padding: 8px; background: var(--green-deep); color: #fff;
	723	+ text-decoration: none; }
	724	+.vp-link:hover { background: var(--green); }
	725	+
	726	+/* =============================================================================
	727	+ Harmonisation Groupe KA — header (badge + compte KA ID), pages Profil,
	728	+ Contact et légales. Le socle vient de ka/tokens.css.
	729	+============================================================================= */
	730	+
	731	+/* ---- Header : badge « Un service Groupe KA » + zone compte ---- */
	732	+.header-inner .gk-badge { flex: none; }
	733	+@media (max-width: 900px) { .header-inner .gk-badge { display: none; } }
	734	+.header-acct { display: flex; align-items: center; gap: 10px; flex: none; }
	735	+.ka-auth { display: flex; align-items: center; gap: 10px; }
	736	+.ka-login {
	737	+ display: inline-flex; align-items: center; gap: 6px; min-height: 40px;
	738	+ padding: 8px 15px; border: 1.5px solid var(--ink); border-radius: 999px;
	739	+ background: var(--surface); color: var(--ink); cursor: pointer;
	740	+ font-family: var(--font-display); font-weight: 600; font-size: 13.5px;
	741	+ box-shadow: 3px 3px 0 rgba(20, 24, 20, 0.15);
	742	+ transition: transform 0.13s ease, box-shadow 0.13s ease, background 0.15s ease;
	743	+}
	744	+.ka-login b { background: var(--ink); color: var(--accent); border-radius: 5px; padding: 0 6px 1px; transform: rotate(-2deg); transition: transform 0.15s ease; }
	745	+.ka-login:hover { transform: translate(-1px, -1px); box-shadow: 4px 4px 0 rgba(20, 24, 20, 0.2); }
	746	+.ka-login:hover b { transform: rotate(0); }
	747	+.ka-login:active { transform: translate(2px, 2px); box-shadow: none; }
	748	+.ka-signup { font-family: var(--font-mono); font-size: 11px; color: var(--ink-2); text-decoration: underline; text-underline-offset: 3px; white-space: nowrap; }
	749	+.ka-signup:hover { color: var(--accent-deep); }
	750	+@media (max-width: 1100px) { .header-acct .ka-signup { display: none; } }
	751	+.ka-acct {
	752	+ display: inline-flex; align-items: center; gap: 8px; min-height: 40px;
	753	+ padding: 6px 14px; border: 1.5px solid var(--ink); border-radius: 999px;
	754	+ background: var(--surface); font-family: var(--font-display);
	755	+ font-weight: 600; font-size: 13.5px; color: var(--ink);
	756	+ max-width: 160px; overflow: hidden; white-space: nowrap; text-overflow: ellipsis;
	757	+}
	758	+.ka-acct:hover, .ka-acct.active { background: var(--ink); color: var(--accent); }
	759	+.ka-acct-pic { width: 24px; height: 24px; border-radius: 50%; flex: none; border: 1px solid var(--line); }
	760	+@media (max-width: 760px) {
	761	+ .header-acct { margin-left: auto; }
	762	+ .menu-btn { margin-left: 0; }
	763	+ .ka-login { min-height: 44px; }
	764	+}
	765	+@media (max-width: 380px) { .header-acct { display: none; } } /* → menu mobile */
	766	+
	767	+/* ---- Menu mobile : compte + badge groupe ---- */
	768	+.mm-auth { display: flex; align-items: center; gap: 14px; flex-wrap: wrap; padding: 15px 10px; border-bottom: 1.5px dashed var(--line); }
	769	+.mm-auth .ka-login { min-height: 44px; }
	770	+.mm-foot p { margin: 10px 0 0; }
	771	+
	772	+/* ---- Générique : lede (Profil / Contact) ---- */
	773	+.lede { color: var(--ink-2); font-size: 15.5px; max-width: 640px; }
	774	+
	775	+/* ================= Page Profil (KA ID) ================= */
	776	+.profil { padding: 44px 0 90px; }
	777	+.profil h1 { font-size: clamp(28px, 4.6vw, 44px); margin: 10px 0 24px; letter-spacing: -0.03em; }
	778	+.profil .lede { margin-bottom: 22px; }
	779	+.profil .notice { padding: 60px 0; }
	780	+
	781	+/* Carte de membre — encre + cerise */
	782	+.pc {
	783	+ position: relative; overflow: hidden; max-width: 460px;
	784	+ background: var(--ink); color: var(--paper);
	785	+ border: 1.5px solid var(--ink); border-radius: var(--r-card);
	786	+ box-shadow: var(--shadow-off-soft); padding: 22px 26px 0;
	787	+}
	788	+.pc-watermark {
	789	+ position: absolute; right: -18px; bottom: 14px; font-family: var(--font-display);
	790	+ font-weight: 700; font-size: 150px; line-height: 1; letter-spacing: -0.06em;
	791	+ color: rgba(245, 243, 238, 0.05); pointer-events: none; user-select: none;
	792	+}
	793	+.pc-head { display: flex; align-items: baseline; justify-content: space-between; gap: 12px; flex-wrap: wrap; }
	794	+.pc-brand { font-family: var(--font-display); font-weight: 700; font-size: 24px; letter-spacing: -0.03em; }
	795	+.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); }
	796	+.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); }
	797	+.pc-id-block { margin: 26px 0 22px; display: flex; flex-direction: column; gap: 4px; }
	798	+.pc-id-label { font-family: var(--font-mono); font-size: 10px; font-weight: 700; text-transform: uppercase; letter-spacing: 0.2em; color: var(--accent); }
	799	+.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; }
	800	+.pc-foot { display: flex; align-items: flex-end; justify-content: space-between; gap: 14px; padding-bottom: 18px; }
	801	+.pc-holder { display: flex; flex-direction: column; gap: 3px; min-width: 0; }
	802	+.pc-holder-name { font-family: var(--font-display); font-weight: 600; font-size: 15px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }
	803	+.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; }
	804	+.pc-holder-since { font-family: var(--font-mono); font-size: 10.5px; color: rgba(245, 243, 238, 0.5); letter-spacing: 0.06em; }
	805	+.pc-avatar { width: 52px; height: 52px; border-radius: 50%; border: 2px solid var(--accent); flex: none; object-fit: cover; }
	806	+.pc-strip { display: flex; align-items: flex-end; gap: 5px; margin: 0 -26px; padding: 9px 18px; background: rgba(15, 107, 79, 0.14); border-top: 1px solid rgba(15, 107, 79, 0.4); overflow: hidden; }
	807	+.pc-strip i { display: block; width: 3px; border-radius: 1px; background: var(--accent); opacity: 0.75; }
	808	+.pc-strip i:nth-child(3n) { height: 14px; opacity: 0.4; }
	809	+.pc-strip i:nth-child(3n+1) { height: 9px; }
	810	+.pc-strip i:nth-child(3n+2) { height: 17px; opacity: 0.95; }
	811	+.pc-copy { margin-top: 16px; }
	812	+.pc-copy.ok { background: var(--ink); color: var(--accent); }
	813	+
	814	+.profil-grid {
	815	+ display: grid; grid-template-columns: repeat(auto-fill, minmax(220px, 1fr));
	816	+ gap: 12px; margin-top: 28px; max-width: 720px;
	817	+}
	818	+.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; }
	819	+.pg-label { font-family: var(--font-mono); font-size: 10px; font-weight: 700; text-transform: uppercase; letter-spacing: 0.12em; color: var(--ink-3); }
	820	+.pg-value { font-weight: 600; font-size: 14.5px; word-break: break-word; }
	821	+.pg-value.mono { font-family: var(--font-mono); color: var(--accent-deep); }
	822	+.profil-note { max-width: 640px; color: var(--ink-2); font-size: 13.5px; margin-top: 22px; }
	823	+.profil-note a { text-decoration: underline; text-underline-offset: 3px; }
	824	+.profil-actions { display: flex; gap: 10px; flex-wrap: wrap; margin-top: 26px; }
	825	+
	826	+/* Profil hub Groupe KA (lecture seule) */
	827	+.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; }
	828	+.hub-profile h3 { font-size: 18px; }
	829	+.hub-profile .hub-bio { color: var(--ink-2); font-size: 14px; margin: 0; max-width: 560px; }
	830	+.hub-profile .pub-meta { display: flex; gap: 8px; flex-wrap: wrap; }
	831	+.hub-profile .stat-chip { display: inline-flex; align-items: center; gap: 6px; }
	832	+.hub-profile a.stat-chip:hover { background: var(--accent-soft); }
	833	+.hub-hint { color: var(--ink-3); font-size: 12.5px; margin: 0; }
	834	+
	835	+/* ================= Pages légales ================= */
	836	+.legal { padding: 48px 0 80px; max-width: 780px; }
	837	+.legal h1 { font-size: clamp(28px, 4.6vw, 44px); margin: 8px 0 6px; }
	838	+.legal .legal-meta { color: var(--ink-3); font-family: var(--font-mono); font-size: 12px; margin: 0 0 26px; }
	839	+.legal h2 { font-size: 20px; margin: 30px 0 8px; border-left: 4px solid var(--accent); padding-left: 10px; }
	840	+.legal p, .legal li { color: var(--ink-2); font-size: 14.5px; }
	841	+.legal ul { padding-left: 20px; display: flex; flex-direction: column; gap: 6px; }
	842	+.legal a { text-decoration: underline; text-underline-offset: 3px; }
	843	+.legal b { color: var(--ink); }
	844	+
	845	+/* ================= Page Contact (écosystème Groupe KA) ================= */
	846	+.contact { padding: 48px 0 90px; }
	847	+.contact h1 { font-size: clamp(30px, 5vw, 52px); margin: 12px 0 14px; text-transform: uppercase; letter-spacing: -0.03em; }
	848	+.contact-cards { display: grid; grid-template-columns: repeat(auto-fit, minmax(230px, 1fr)); gap: 14px; margin: 28px 0 6px; max-width: 900px; }
	849	+.contact-card {
	850	+ display: flex; flex-direction: column; gap: 8px; min-height: var(--touch, 44px);
	851	+ background: var(--surface); border: 1.5px solid var(--ink);
	852	+ border-radius: var(--r-card); padding: 18px 20px;
	853	+ box-shadow: var(--shadow-off-soft);
	854	+ transition: transform 0.15s ease, box-shadow 0.15s ease;
	855	+}
	856	+.contact-card:hover { transform: translate(-2px, -2px); box-shadow: var(--shadow-off); }
	857	+.contact-role { font-family: var(--font-mono); font-size: 10.5px; font-weight: 700; text-transform: uppercase; letter-spacing: 0.1em; color: var(--green); }
	858	+.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; }
	859	+.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; }
	860	+.contact-disclaimer b { color: var(--ink); }
	861	+.contact-hub { display: flex; gap: 12px; flex-wrap: wrap; margin-top: 26px; }
	862	+.contact-sites { margin-top: 46px; }
	863	+.contact-sites h2 { font-size: 21px; text-transform: uppercase; margin-bottom: 14px; }
	864	+.contact-sites ul { list-style: none; margin: 0; padding: 0; display: grid; grid-template-columns: repeat(auto-fill, minmax(230px, 1fr)); gap: 10px; }
	865	+.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; }
	866	+.contact-sites a:hover { transform: translate(-2px, -2px); box-shadow: 4px 4px 0 var(--ink); }
	867	+.contact-sites b { font-family: var(--font-display); font-size: 15px; }
	868	+.contact-sites span { font-size: 12px; color: var(--ink-3); }
	869	+@media (max-width: 480px) {
	870	+ .header-inner { gap: 10px; }
	871	+ .ka-login { font-size: 12px; padding: 6px 10px; gap: 4px; min-height: 44px; }
	872	+}
	873	+
	874	+/* Bulle KA Agent : sur mobile, remontée au-dessus de la barre CTA collante des
	875	+ fiches (sinon elle chevauche le bouton « Voir chez … »). */
	876	+@media (max-width: 899px) {
	877	+ .kaa-btn {
	878	+ bottom: calc(88px + env(safe-area-inset-bottom, 0px)) !important;
	879	+ }
	880	+}
	881	+
	882	+/* Footer commun KA : zones tactiles ≥ 44 px pour les petits liens (Ka2, Ka4…)
	883	+ — padding compensé par une marge négative : aucun changement visuel. */
	884	+.ka-footer .sites a, .ka-footer .legal a, .ka-footer .contacts a {
	885	+ display: inline-block; padding: 12px 8px; margin: -12px -8px;
	886	+}
	887	+
	888	+/* ================= Qualité des annonces / images ================= */
	889	+/* Image de secours par TYPE DE BIEN (jamais d'icône d'image cassée) */
	890	+.type-fallback {
	891	+ display: flex; flex-direction: column; align-items: center; justify-content: center;
	892	+ gap: 9px; width: 100%; height: 100%; min-height: 120px;
	893	+ background:
	894	+ radial-gradient(circle at 78% 18%, rgba(15, 107, 79, 0.14), transparent 52%),
	895	+ repeating-linear-gradient(45deg, #f3ece9 0 14px, #f7f1ef 14px 28px);
	896	+ color: var(--accent-deep);
	897	+}
	898	+.type-fallback .ico { opacity: 0.75; }
	899	+.type-fallback span {
	900	+ font-family: var(--font-mono); font-size: 10.5px; font-weight: 700;
	901	+ text-transform: uppercase; letter-spacing: 0.12em; color: var(--ink-3);
	902	+}
	903	+.carousel-empty .type-fallback { aspect-ratio: 16/11; }
	904	+
	905	+/* légende de photo (étiquette de pièce de la source) */
	906	+.carousel-caption {
	907	+ position: absolute; left: 12px; bottom: 12px; z-index: 2; max-width: 60%;
	908	+ background: rgba(26, 18, 20, 0.82); color: #f5f3ee;
	909	+ font-family: var(--font-mono); font-size: 11px; font-weight: 600;
	910	+ padding: 4px 10px; border-radius: 999px;
	911	+ overflow: hidden; text-overflow: ellipsis; white-space: nowrap;
	912	+}
	913	+
	914	+/* mention loyer mensuel (transaction = location) */
	915	+.per-month { font-size: 0.55em; font-weight: 600; color: var(--ink-3); letter-spacing: 0; }
	916	+
	917	+/* lightbox : l'image zoomable ne doit pas déclencher le scroll de la page */
	918	+.lightbox img { user-select: none; -webkit-user-drag: none; }
	919	+
	920	+/* ---- Stats : qualité des données ---- */
	921	+.q-table-wrap { overflow-x: auto; }
	922	+.q-table { width: 100%; border-collapse: collapse; font-size: 13px; min-width: 520px; }
	923	+.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); }
	924	+.q-table td { padding: 6px 10px; border-bottom: 1px solid var(--line); }
	925	+.q-table .num { text-align: right; font-family: var(--font-mono); }
	926	+.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; }
	927	+.q-meter i { display: block; height: 100%; background: var(--green); }
	928	+
	929	+
	930	+/* ---- Criminalité détaillée SPVM (bloc quartier) ---- */
	931	+.q-crime { width: 100%; }
	932	+.q-crime-cats { list-style: none; margin: 8px 0 0; padding: 0; }
	933	+.q-crime-cats li { display: flex; align-items: center; gap: 8px;
	934	+ padding: 3px 0; font-size: 12.5px; }
	935	+.q-crime-nom { flex: 0 0 46%; color: var(--ink-2, #555); overflow: hidden;
	936	+ text-overflow: ellipsis; white-space: nowrap; }
	937	+.q-crime-barre { flex: 1 1 auto; height: 10px; background: var(--surface-2, #f0ede8);
	938	+ border-radius: 5px; overflow: hidden; }
	939	+.q-crime-barre i { display: block; height: 100%; border-radius: 5px;
	940	+ background: var(--accent, #0f6b4f); opacity: 0.55; }
	941	+.q-crime-n { flex: 0 0 52px; text-align: right; font-weight: 600;
	942	+ color: var(--ink, #222); white-space: nowrap; }
	943	+.q-crime-n small { font-weight: 400; color: var(--ink-3, #888); }
	944	+.q-crime-src { margin-top: 8px; }
	945	+
	946	+
	947	+/* ---- Risque d'inondation (fiche) — BDZI gouv. du Québec ---- */
	948	+.f-zi .zi-head { display: flex; align-items: center; gap: 10px; }
	949	+.zi-badge { display: inline-block; padding: 3px 10px; border-radius: 999px;
	950	+ font-size: 12.5px; font-weight: 700; }
	951	+.zi-eleve { background: #fde8e8; color: #a12622; }
	952	+.zi-modere { background: #fdf3e0; color: #8a5a00; }
	953	+.zi-present { background: #fdf3e0; color: #8a5a00; }
	954	+.zi-ok { background: #e7f4ea; color: #1e6b34; }
	955	+.zi-nc { background: var(--surface-2, #f0ede8); color: var(--ink-3, #888); }
	956	+.zi-liste { margin: 8px 0 0; padding: 0; list-style: none; font-size: 13px; }
	957	+.zi-liste li { padding: 4px 0; border-top: 1px solid var(--line, #e6e4df); }
	958	+
	959	+
	960	+/* ---- tuiles KPI + tableau compacts (partagés air/essence) ---- */
	961	+.rdl-kpis { display: flex; flex-wrap: wrap; gap: 10px; margin: 2px 0 12px; }
	962	+.rdl-kpi { flex: 1 1 90px; min-width: 90px; background: var(--surface-2, #f7f5f1);
	963	+ border-radius: 10px; padding: 10px 12px; }
	964	+.rdl-kpi-v { display: block; font-size: 20px; font-weight: 700;
	965	+ letter-spacing: -0.02em; color: var(--ink, #222); }
	966	+.rdl-kpi-l { display: block; font-size: 11px; line-height: 1.35;
	967	+ color: var(--ink-3, #888); margin-top: 2px; }
	968	+.rdl-table { width: 100%; border-collapse: collapse; font-size: 13px; }
	969	+.rdl-table td { padding: 5px 8px 5px 0; border-top: 1px solid var(--line, #e6e4df);
	970	+ vertical-align: top; }
	971	+.rdl-table .rdl-addr { max-width: 46%; }
	972	+.rdl-table .rdl-prix { font-weight: 600; white-space: nowrap; }
	973	+.rdl-table .rdl-date { white-space: nowrap; color: var(--ink-2, #555); }
	974	+.rdl-table .rdl-dist { color: var(--ink-3, #888); white-space: nowrap; text-align: right; }
	975	+.rdl-cap { caption-side: top; text-align: left; font-size: 13px; font-weight: 700;
	976	+ color: var(--ink, #222); padding: 6px 0; }
	977	+
	978	+/* ---- Qualité de l'air (RSQAQ) + Essence à proximité ---- */
	979	+.air-liste { list-style: none; margin: 10px 0 0; padding: 0; }
	980	+.air-liste li { display: flex; align-items: center; gap: 8px;
	981	+ padding: 4px 0; font-size: 12.5px; }
	982	+.air-nom { flex: 0 0 44%; color: var(--ink-2); overflow: hidden;
	983	+ text-overflow: ellipsis; white-space: nowrap; }
	984	+.air-barre { flex: 1 1 auto; height: 10px; background: var(--surface-2, #f0ede8);
	985	+ border-radius: 5px; overflow: hidden; }
	986	+.air-barre i { display: block; height: 100%; border-radius: 5px;
	987	+ background: #4d9e64; }
	988	+.air-barre i.air-sur { background: #c96a1f; }
	989	+.air-val { flex: 0 0 34%; text-align: right; font-weight: 600;
	990	+ color: var(--ink); white-space: nowrap; overflow: hidden;
	991	+ text-overflow: ellipsis; }
	992	+.air-val small { font-weight: 400; color: var(--ink-3); }
	993	+.air-val .air-ref { display: block; font-size: 10px; }
	994	+.gaz-head th { text-align: left; font-size: 11px; color: var(--ink-3);
	995	+ font-weight: 600; padding: 2px 8px 2px 0; }
	996	+.gaz-best { display: inline-block; margin-left: 6px; padding: 1px 7px;
	997	+ border-radius: 999px; background: #e7f4ea; color: #1e6b34;
	998	+ font-size: 10.5px; font-weight: 700; }
	999	+.gaz-adr { display: block; font-size: 11px; color: var(--ink-3); }
	1000	+
	1001	+
	1002	+/* ---- Commerces et transport (fiche) ---- */
	1003	+.cm-grille { list-style: none; margin: 6px 0 0; padding: 0;
	1004	+ display: grid; grid-template-columns: 1fr 1fr; gap: 4px 18px; }
	1005	+@media (max-width: 560px) { .cm-grille { grid-template-columns: 1fr; } }
	1006	+.cm-item { display: flex; align-items: center; gap: 9px; padding: 5px 0;
	1007	+ border-bottom: 1px solid var(--line, #eeece7); min-width: 0; }
	1008	+.cm-ico { flex: 0 0 28px; }
	1009	+.cm-txt { flex: 1 1 auto; min-width: 0; display: flex; flex-direction: column; }
	1010	+.cm-nom { font-size: 13px; font-weight: 600; color: var(--ink, #222);
	1011	+ white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
	1012	+.cm-poi { font-size: 11px; color: var(--ink-3, #8a877f);
	1013	+ white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
	1014	+.cm-dist { flex: 0 0 auto; font-size: 13px; font-weight: 700;
	1015	+ color: var(--ink-2, #4c4a45); white-space: nowrap; }
	1016	+
	1017	+
	1018	+/* ---- Coût d'électricité (Hydro-Québec) ---- */
	1019	+.hydro-intro { margin: 2px 0 12px; color: var(--ink-2, #4c4a45); }
	1020	+.hydro-btn { appearance: none; border: 0; border-radius: 10px; cursor: pointer;
	1021	+ background: var(--accent, #2b7a3b); color: #fff; font-weight: 700;
	1022	+ font-size: 14px; padding: 11px 18px; }
	1023	+.hydro-btn:disabled { opacity: 0.6; cursor: progress; }
	1024	+.hydro-montant { font-size: 26px; font-weight: 800; letter-spacing: -0.02em;
	1025	+ color: var(--navy, #1c1b18); display: flex; align-items: baseline;
	1026	+ gap: 10px; flex-wrap: wrap; }
	1027	+.hydro-montant small { font-size: 14px; font-weight: 500; color: var(--ink-3); }
	1028	+.hydro-an { font-size: 14px; font-weight: 600; color: var(--ink-2, #4c4a45); }
	1029	+.hydro-vide { color: var(--ink-3, #8a877f); }
	1030	+
	1031	+
	1032	+/* ============================================================================
	1033	+ PASSE DE DESIGN — « éditorial sharp » appliqué à toute la fiche
	1034	+ Blocs = cartes encre (bordure 1,5 px + ombre décalée douce), titres à
	1035	+ marqueur accent + filet, tuiles KPI blanches à ombre dure, tableaux zébrés,
	1036	+ barres en dégradé, pastilles unifiées (mono, point d'état, liseré).
	1037	+ Aucune propriété `order` (règle Groupe Ka : ordre DOM = ordre visuel).
	1038	+ ========================================================================== */
	1039	+
	1040	+/* --- Blocs de la fiche : cartes posées sur le papier --- */
	1041	+.f-bloc:not(.f-galerie):not(.f-hero),
	1042	+.quartier {
	1043	+ background: var(--surface);
	1044	+ border: 1.5px solid var(--ink);
	1045	+ border-radius: var(--r-card);
	1046	+ padding: 18px 20px 16px;
	1047	+ box-shadow: var(--shadow-off-soft);
	1048	+}
	1049	+@media (max-width: 640px) {
	1050	+ .f-bloc:not(.f-galerie):not(.f-hero),
	1051	+ .quartier { padding: 15px 15px 13px; }
	1052	+}
	1053	+/* blocs pleine largeur sous la grille : respiration entre les cartes */
	1054	+.detail > .f-bloc { margin-top: 22px; }
	1055	+
	1056	+/* --- Titres de section : carré accent + filet éditorial --- */
	1057	+.f-bloc h2, .quartier h2 {
	1058	+ display: flex; align-items: center; gap: 10px;
	1059	+ font-size: 19px; letter-spacing: -0.015em; margin-bottom: 14px;
	1060	+ border-left: 0; padding-left: 0;
	1061	+}
	1062	+.f-bloc h2::before, .quartier h2::before {
	1063	+ content: ""; flex: 0 0 9px; width: 9px; height: 9px;
	1064	+ background: var(--accent); border: 1.5px solid var(--ink);
	1065	+ box-shadow: 2px 2px 0 var(--ink);
	1066	+}
	1067	+.f-bloc h2::after, .quartier h2::after {
	1068	+ content: ""; flex: 1 1 auto; height: 1.5px; min-width: 20px;
	1069	+ background: var(--line);
	1070	+}
	1071	+
	1072	+/* --- Tuiles KPI : blanches, bord encre, ombre dure accent --- */
	1073	+.rdl-kpi {
	1074	+ background: var(--surface);
	1075	+ border: 1.5px solid var(--ink);
	1076	+ border-radius: var(--r-ctl);
	1077	+ box-shadow: 3px 3px 0 var(--accent-soft);
	1078	+}
	1079	+.rdl-kpi-v { font-family: var(--font-display); }
	1080	+.q-cell { box-shadow: 3px 3px 0 rgba(20, 24, 20, 0.1); border-radius: var(--r-ctl); }
	1081	+.q-val { font-size: 20px; }
	1082	+
	1083	+/* --- Tableaux : en-têtes mono, zébrure, survol accent --- */
	1084	+.rdl-table td { padding: 7px 8px 7px 0; }
	1085	+.rdl-table tbody tr:nth-child(even) td,
	1086	+.rdl-table > tr:nth-child(even) td { background: var(--surface-2); }
	1087	+.rdl-table tr:hover td { background: var(--accent-soft); }
	1088	+.gaz-head th {
	1089	+ font-family: var(--font-mono); font-size: 10px; font-weight: 700;
	1090	+ text-transform: uppercase; letter-spacing: 0.08em;
	1091	+ border-bottom: 1.5px solid var(--ink);
	1092	+}
	1093	+.rdl-cap { font-family: var(--font-display); }
	1094	+table.rooms tbody tr:hover td { background: var(--accent-soft); }
	1095	+
	1096	+/* --- Barres : pistes bordées + remplissage en dégradé --- */
	1097	+.q-bar-track, .q-crime-barre, .air-barre {
	1098	+ background: var(--surface-2);
	1099	+ border: 1px solid var(--line);
	1100	+ height: 12px;
	1101	+}
	1102	+.q-bar-fill {
	1103	+ background: linear-gradient(90deg, var(--accent), var(--accent-deep));
	1104	+}
	1105	+.q-crime-barre i {
	1106	+ background: linear-gradient(90deg, #f0808a, var(--accent));
	1107	+ opacity: 0.9;
	1108	+}
	1109	+.air-barre i { background: linear-gradient(90deg, #6fbc85, #2e7d4a); }
	1110	+.air-barre i.air-sur { background: linear-gradient(90deg, #e08a48, #c96a1f); }
	1111	+
	1112	+/* --- Pastilles d'état unifiées (zi-badge & cie) : mono + point d'état --- */
	1113	+.zi-badge {
	1114	+ display: inline-flex; align-items: center; gap: 6px;
	1115	+ font-family: var(--font-mono); font-size: 10.5px; font-weight: 700;
	1116	+ text-transform: uppercase; letter-spacing: 0.06em;
	1117	+ padding: 4px 10px; border: 1.5px solid currentColor;
	1118	+}
	1119	+.zi-badge::before {
	1120	+ content: ""; width: 6px; height: 6px; border-radius: 50%;
	1121	+ background: currentColor;
	1122	+}
	1123	+.gaz-best { border: 1px solid currentColor; }
	1124	+
	1125	+/* --- Listes riches (zones d'inondation) : mini-cartes à liseré accent --- */
	1126	+.zi-liste { display: flex; flex-direction: column; gap: 8px; }
	1127	+.zi-liste li {
	1128	+ border: 1px solid var(--line); border-left: 3px solid var(--accent);
	1129	+ border-top: 1px solid var(--line);
	1130	+ border-radius: var(--r-ctl); padding: 9px 12px;
	1131	+ background: var(--surface-2);
	1132	+}
	1133	+
	1134	+/* --- Inclusions : icône et libellé alignés sur une seule ligne --- */
	1135	+.amenity { display: inline-flex; align-items: center; gap: 6px; }
	1136	+
	1137	+/* --- Notes de bas de bloc : filet pointillé --- */
	1138	+.f-bloc .fine, .quartier .fine {
	1139	+ margin-top: 12px; padding-top: 9px;
	1140	+ border-top: 1px dashed var(--line);
	1141	+}
	1142	+
	1143	+/* --- CTA secondaire : téléchargement de la fiche PDF --- */
	1144	+.cta-pdf {
	1145	+ background: var(--surface); color: var(--ink);
	1146	+ box-shadow: 4px 4px 0 rgba(26, 18, 20, 0.12);
	1147	+ margin-top: 10px;
	1148	+}
	1149	+.cta-pdf:hover { background: var(--ink); color: var(--paper); }
	1150	+
	1151	+/* ================= Financement (fiche) + page Taux hypothécaires ========= */
	1152	+.f-mtg .mtg-intro { color: var(--ink-2); font-size: 14px; margin: 4px 0 14px; }
	1153	+.f-mtg .mtg-intro a { color: var(--lime); font-weight: 600; }
	1154	+
	1155	+.mtg-form {
	1156	+ display: grid; gap: 10px;
	1157	+ grid-template-columns: repeat(auto-fill, minmax(150px, 1fr));
	1158	+}
	1159	+.mtg-form label { display: flex; flex-direction: column; gap: 3px; min-width: 0; }
	1160	+.mtg-form label > span {
	1161	+ font-family: var(--font-mono); font-size: 9.5px; font-weight: 700;
	1162	+ text-transform: uppercase; letter-spacing: 0.1em; color: var(--ink-3);
	1163	+}
	1164	+.mtg-form input, .mtg-form select {
	1165	+ border: 1.5px solid var(--ink); border-radius: 9px; background: var(--surface);
	1166	+ padding: 9px 10px; font-size: 14.5px; font-family: inherit; color: var(--ink);
	1167	+ min-height: 42px; min-width: 0;
	1168	+}
	1169	+.mtg-form input:focus, .mtg-form select:focus {
	1170	+ outline: none; box-shadow: 3px 3px 0 var(--lime);
	1171	+}
	1172	+
	1173	+.mtg-err { color: var(--accent-deep); font-size: 13.5px; margin: 12px 0 0; }
	1174	+
	1175	+.mtg-resultat {
	1176	+ display: grid; gap: 10px; margin-top: 16px;
	1177	+ grid-template-columns: repeat(auto-fit, minmax(180px, 1fr));
	1178	+}
	1179	+.mtg-kpi {
	1180	+ border: 1.5px solid var(--line-strong); border-radius: var(--r-card);
	1181	+ background: var(--surface-2); padding: 12px 14px;
	1182	+ display: flex; flex-direction: column; gap: 2px; min-width: 0;
	1183	+}
	1184	+.mtg-kpi-k {
	1185	+ font-family: var(--font-mono); font-size: 9.5px; font-weight: 700;
	1186	+ text-transform: uppercase; letter-spacing: 0.12em; color: var(--ink-3);
	1187	+}
	1188	+.mtg-kpi-v {
	1189	+ font-family: var(--font-display); font-weight: 700; font-size: 22px;
	1190	+ letter-spacing: -0.02em;
	1191	+}
	1192	+.mtg-kpi-sub { font-size: 12px; color: var(--ink-3); }
	1193	+.mtg-kpi:first-child { background: var(--ink); border-color: var(--ink); }
	1194	+.mtg-kpi:first-child .mtg-kpi-v { color: var(--lime); }
	1195	+.mtg-kpi:first-child .mtg-kpi-k, .mtg-kpi:first-child .mtg-kpi-sub { color: rgba(255,255,255,0.75); }
	1196	+
	1197	+.mtg-source { margin-top: 10px; }
	1198	+
	1199	+.mtg-schl {
	1200	+ margin-top: 14px; border: 1.5px dashed var(--line-strong);
	1201	+ border-radius: var(--r-card); padding: 12px 14px; font-size: 13.5px;
	1202	+ background: var(--surface);
	1203	+}
	1204	+.mtg-schl ul { margin: 8px 0 0; padding-left: 18px; display: grid; gap: 3px; }
	1205	+.mtg-schl-no { border-color: var(--accent-deep); }
	1206	+.mtg-issue { margin: 8px 0 0; color: var(--accent-deep); font-size: 13px; }
	1207	+
	1208	+.mtg-detail {
	1209	+ margin-top: 10px; border: 1.5px solid var(--line-strong);
	1210	+ border-radius: var(--r-card); background: var(--surface);
	1211	+}
	1212	+.mtg-detail > summary {
	1213	+ cursor: pointer; padding: 11px 14px; font-weight: 700; font-size: 14px;
	1214	+ list-style: none; display: flex; align-items: center; gap: 8px;
	1215	+}
	1216	+.mtg-detail > summary::before { content: "+"; font-family: var(--font-mono); color: var(--lime); font-weight: 700; }
	1217	+.mtg-detail[open] > summary::before { content: "−"; }
	1218	+.mtg-detail > summary::-webkit-details-marker { display: none; }
	1219	+.mtg-detail > *:not(summary) { margin: 0 14px 12px; }
	1220	+.mtg-detail .fine { border-top: none; padding-top: 0; }
	1221	+.mtg-total { border-top: 2px solid var(--ink); }
	1222	+.mtg-comp td, .mtg-comp th { white-space: nowrap; }
	1223	+.mtg-stale { color: var(--accent-deep); }
	1224	+
	1225	+.mtg-chart svg { width: 100%; height: auto; display: block; }
	1226	+.mtg-grid { stroke: var(--line); stroke-width: 1; }
	1227	+.mtg-tick { font-family: var(--font-mono); font-size: 10px; fill: var(--ink-3); }
	1228	+.mtg-line { fill: none; stroke: var(--lime); stroke-width: 2.5; stroke-linejoin: round; }
	1229	+.mtg-dot { fill: var(--ink); stroke: var(--lime); stroke-width: 2.5; }
	1230	+
	1231	+/* ---- page /taux-hypothecaires ---- */
	1232	+.taux-page { padding-bottom: 40px; }
	1233	+.taux-head { margin: 28px 0 6px; max-width: 760px; }
	1234	+.taux-head h1 { font-family: var(--font-display); font-size: clamp(28px, 5vw, 40px); letter-spacing: -0.03em; }
	1235	+.taux-head p { color: var(--ink-2); font-size: 15px; margin: 12px 0 0; }
	1236	+.taux-page > .f-bloc { margin-top: 22px; }
	1237	+
	1238	+.taux-grid {
	1239	+ display: grid; gap: 10px;
	1240	+ grid-template-columns: repeat(auto-fill, minmax(170px, 1fr));
	1241	+}
	1242	+.taux-card {
	1243	+ border: 1.5px solid var(--ink); border-radius: var(--r-card);
	1244	+ background: var(--surface); padding: 12px 14px; text-align: left;
	1245	+ cursor: pointer; display: flex; flex-direction: column; gap: 2px;
	1246	+ transition: box-shadow 0.15s ease; font-family: inherit; min-width: 0;
	1247	+}
	1248	+.taux-card:hover { box-shadow: 3px 3px 0 var(--lime); }
	1249	+.taux-card.on { background: var(--ink); color: var(--paper); }
	1250	+.taux-card.on .taux-card-v { color: var(--lime); }
	1251	+.taux-card-k {
	1252	+ font-family: var(--font-mono); font-size: 9.5px; font-weight: 700;
	1253	+ text-transform: uppercase; letter-spacing: 0.12em; color: var(--ink-3);
	1254	+}
	1255	+.taux-card.on .taux-card-k, .taux-card.on .taux-card-sub { color: rgba(255,255,255,0.7); }
	1256	+.taux-card-v { font-family: var(--font-display); font-weight: 700; font-size: 24px; }
	1257	+.taux-card-sub { font-size: 11.5px; color: var(--ink-3); }
	1258	+
	1259	+.taux-filtres { display: flex; gap: 10px; margin-bottom: 14px; flex-wrap: wrap; }
	1260	+.taux-filtres label { display: flex; flex-direction: column; gap: 3px; }
	1261	+.taux-filtres label > span {
	1262	+ font-family: var(--font-mono); font-size: 9.5px; font-weight: 700;
	1263	+ text-transform: uppercase; letter-spacing: 0.1em; color: var(--ink-3);
	1264	+}
	1265	+.taux-filtres select {
	1266	+ border: 1.5px solid var(--ink); border-radius: 9px; background: var(--surface);
	1267	+ padding: 9px 12px; font-size: 14.5px; font-family: inherit; min-height: 42px;
	1268	+}
	1269	+.taux-best td { background: var(--lime-soft); }
	1270	+.taux-badge {
	1271	+ font-family: var(--font-mono); font-size: 9px; font-weight: 700;
	1272	+ text-transform: uppercase; letter-spacing: 0.1em; background: var(--ink);
	1273	+ color: var(--lime); border-radius: 999px; padding: 2px 8px; margin-left: 8px;
	1274	+}
	1275	+.taux-sante { display: flex; flex-wrap: wrap; gap: 8px; }
	1276	+.taux-src {
	1277	+ border: 1.5px solid var(--line-strong); border-radius: 999px;
	1278	+ padding: 6px 12px; font-size: 12.5px; font-weight: 600;
	1279	+ display: inline-flex; align-items: center; gap: 7px;
	1280	+}
	1281	+.taux-src::before { content: ""; width: 8px; height: 8px; border-radius: 50%; }
	1282	+.taux-src-ok::before { background: var(--green, #2f9e44); }
	1283	+.taux-src-warning::before { background: #e8a000; }
	1284	+.taux-src-error::before { background: var(--accent-deep); }
	1285	+
	1286	+/* =============================================================================
	1287	+ REFONTE ÉDITORIALE v2 (2026-08-25) — accueil « produit premium »
	1288	+ Personnalité Immo-Ka : architecturale et financière — composition
	1289	+ typographique majuscule plein/outline décalée, colonne de données mono
	1290	+ façon terminal, cerise en couleur de SIGNAL (jamais en aplat décoratif).
	1291	+ Primitives locales : rayons 0/6/10/18, durées 150/240/350 ms.
	1292	+ Couche posée en FIN de fichier : elle a le dernier mot sur la cascade.
	1293	+============================================================================= */
	1294	+:root {
	1295	+ --r-0: 0px; --r-1: 6px; --r-2: 10px; --r-3: 18px;
	1296	+ --dur-1: 150ms; --dur-2: 240ms; --dur-3: 350ms;
	1297	+ --ease-out: cubic-bezier(0.2, 0.8, 0.2, 1);
	1298	+ --hairline: rgba(20, 24, 20, 0.14);
	1299	+ --hairline-strong: rgba(20, 24, 20, 0.6);
	1300	+}
	1301	+
	1302	+/* ---- Héro : composition typographique + colonne de données ---- */
	1303	+.hero-wrap { display: grid; grid-template-columns: 1fr auto; gap: 24px 56px; align-items: end; }
	1304	+.hero h1.hero-display {
	1305	+ display: flex; flex-direction: column;
	1306	+ font-size: clamp(40px, 6.8vw, 92px); line-height: 0.96;
	1307	+ text-transform: uppercase; letter-spacing: -0.04em;
	1308	+ max-width: none; margin-top: 16px;
	1309	+}
	1310	+.hero-display .hd-l1, .hero-display .hd-l2,
	1311	+.hero-display .hd-l3, .hero-display .hd-l4 { display: block; }
	1312	+.hero-display .hd-l2 { color: transparent; -webkit-text-stroke: 2.5px var(--ink); }
	1313	+.hero-display .hd-l3 { margin-left: clamp(24px, 6vw, 110px); }
	1314	+.hero-display .hd-l4 {
	1315	+ font-size: 0.5em; letter-spacing: -0.02em; margin-top: 0.35em;
	1316	+ margin-left: clamp(2px, 1vw, 8px);
	1317	+}
	1318	+.hero-display .signal {
	1319	+ font-style: normal; color: var(--lime); position: relative;
	1320	+ border-bottom: 4px solid var(--lime); padding-bottom: 1px;
	1321	+}
	1322	+.hero p.lede { font-size: 16px; max-width: 560px; }
	1323	+.hero::before { opacity: 0.7; }
	1324	+.hero::after { opacity: 0.5; }
	1325	+
	1326	+/* colonne « terminal » : les chiffres du marché comme élément graphique */
	1327	+.hero-data {
	1328	+ display: flex; flex-direction: column; gap: 18px;
	1329	+ border-left: 1px solid var(--hairline-strong); padding-left: 28px;
	1330	+ min-width: 190px;
	1331	+}
	1332	+.hd-row b {
	1333	+ display: block; font-family: var(--font-display); font-weight: 700;
	1334	+ font-size: clamp(20px, 2vw, 27px); letter-spacing: -0.03em; color: var(--ink);
	1335	+ font-variant-numeric: tabular-nums; line-height: 1.1;
	1336	+}
	1337	+.hd-row span {
	1338	+ font-family: var(--font-mono); font-size: 9.5px; font-weight: 700;
	1339	+ text-transform: uppercase; letter-spacing: 0.14em; color: var(--ink-3);
	1340	+}
	1341	+@media (max-width: 900px) {
	1342	+ .hero-wrap { grid-template-columns: 1fr; align-items: start; }
	1343	+ .hero-data {
	1344	+ flex-direction: row; flex-wrap: wrap; gap: 16px 28px;
	1345	+ border-left: 0; border-top: 1px solid var(--hairline);
	1346	+ padding: 16px 0 0; min-width: 0; margin-top: 6px;
	1347	+ }
	1348	+}
	1349	+
	1350	+/* ---- Ligne de données vivantes (mono + filets) ---- */
	1351	+.live-line {
	1352	+ display: flex; flex-wrap: wrap; align-items: baseline;
	1353	+ margin-top: 30px; font-family: var(--font-mono); font-size: 12px;
	1354	+ color: var(--ink-2); letter-spacing: 0.02em; row-gap: 10px;
	1355	+}
	1356	+.live-flag {
	1357	+ display: inline-flex; align-items: center; gap: 7px;
	1358	+ font-weight: 700; font-size: 10.5px; letter-spacing: 0.18em;
	1359	+ text-transform: uppercase; color: var(--accent-deep);
	1360	+ padding-right: 14px; margin-right: 14px; border-right: 1px solid var(--hairline-strong);
	1361	+}
	1362	+.live-dot { width: 7px; height: 7px; border-radius: 50%; background: var(--lime); animation: pulse 2.4s ease infinite; }
	1363	+.live-item { padding-right: 14px; margin-right: 14px; border-right: 1px solid var(--hairline); }
	1364	+.live-item:last-child { border-right: 0; padding-right: 0; margin-right: 0; }
	1365	+.live-item b { color: var(--ink); font-weight: 700; font-variant-numeric: tabular-nums; }
	1366	+@media (max-width: 640px) {
	1367	+ .live-line { flex-wrap: nowrap; overflow-x: auto; scrollbar-width: none;
	1368	+ white-space: nowrap; margin-right: -16px; padding-right: 16px; }
	1369	+ .live-line::-webkit-scrollbar { display: none; }
	1370	+}
	1371	+
	1372	+/* ---- Recherche au cœur : grand champ souligné + critères en filets ---- */
	1373	+.search-zone { margin: 42px 0 0; }
	1374	+.q-big {
	1375	+ display: flex; align-items: center; gap: 14px;
	1376	+ border: 0; border-bottom: 2px solid var(--ink); border-radius: 0;
	1377	+ background: transparent; padding: 4px 2px 14px; color: var(--ink-3);
	1378	+ transition: border-color var(--dur-2) var(--ease-out), color var(--dur-2) ease;
	1379	+}
	1380	+.q-big:focus-within { border-color: var(--lime); color: var(--accent-deep); }
	1381	+.q-big svg { flex: none; }
	1382	+.q-big input {
	1383	+ flex: 1; min-width: 0; border: 0; background: none; outline: none; padding: 0;
	1384	+ font-family: var(--font-display); font-weight: 600;
	1385	+ font-size: clamp(19px, 2.8vw, 28px); letter-spacing: -0.02em; color: var(--ink);
	1386	+}
	1387	+.q-big input::placeholder { color: var(--ink-3); font-weight: 500; }
	1388	+.crit-line { display: flex; align-items: stretch; flex-wrap: wrap; }
	1389	+.crit {
	1390	+ display: flex; flex-direction: column; justify-content: center; gap: 1px;
	1391	+ padding: 12px 26px 12px 0; margin-right: 26px;
	1392	+ border-right: 1px solid var(--hairline); min-width: 0; cursor: pointer;
	1393	+}
	1394	+.crit > span {
	1395	+ font-family: var(--font-mono); font-size: 9.5px; font-weight: 700;
	1396	+ text-transform: uppercase; letter-spacing: 0.14em; color: var(--ink-3);
	1397	+}
	1398	+.crit select {
	1399	+ border: 0; background: transparent; outline: none; cursor: pointer;
	1400	+ font-family: var(--font-display); font-weight: 700; font-size: 15.5px;
	1401	+ color: var(--ink); appearance: none; -webkit-appearance: none;
	1402	+ padding: 2px 18px 2px 0; min-width: 0; max-width: 190px; text-overflow: ellipsis;
	1403	+ background-image: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='9' height='5'%3E%3Cpath d='M0 0l4.5 5L9 0z' fill='%238b928c'/%3E%3C/svg%3E");
	1404	+ background-repeat: no-repeat; background-position: right center;
	1405	+}
	1406	+.crit:hover select { color: var(--accent-deep); }
	1407	+.crit .range-pair select { max-width: 92px; }
	1408	+.crit-more {
	1409	+ display: inline-flex; align-items: center; gap: 9px; align-self: center;
	1410	+ border: 0; background: none; padding: 12px 0; cursor: pointer;
	1411	+ font-family: var(--font-display); font-weight: 700; font-size: 14.5px; color: var(--ink);
	1412	+ transition: color var(--dur-1) ease;
	1413	+}
	1414	+.crit-more:hover, .crit-more.on { color: var(--accent-deep); }
	1415	+.crit-badge, .rb-badge {
	1416	+ display: inline-grid; place-items: center; min-width: 19px; height: 19px; padding: 0 5px;
	1417	+ border-radius: 999px; background: var(--lime); color: #fff;
	1418	+ font-size: 11px; font-weight: 700; font-variant-numeric: tabular-nums;
	1419	+}
	1420	+.search-zone .f-adv { border-top: 1px solid var(--hairline); margin-top: 2px; padding-top: 18px; }
	1421	+.search-zone .seg button {
	1422	+ border: 1px solid var(--hairline-strong); background: transparent; color: var(--ink-2);
	1423	+ min-height: 38px; font-weight: 600; margin-left: -1px;
	1424	+}
	1425	+.search-zone .seg button:first-child { border-radius: var(--r-1) 0 0 var(--r-1); }
	1426	+.search-zone .seg button:last-child { border-radius: 0 var(--r-1) var(--r-1) 0; }
	1427	+.search-zone .seg button:hover { background: var(--lime-soft); color: var(--accent-deep); }
	1428	+.search-zone .seg button.on { background: var(--ink); border-color: var(--ink); color: var(--paper); box-shadow: none; }
	1429	+.search-zone .f-native { border: 1px solid var(--hairline-strong); background: transparent; }
	1430	+
	1431	+/* résumé mobile des critères — remplace le FAB (voir media 640 plus bas) */
	1432	+.crit-summary { display: none; }
	1433	+
	1434	+/* ---- Barre de résultats sticky : N propriétés · tri · Liste\|Carte ---- */
	1435	+.results-bar {
	1436	+ position: sticky; top: 64px; z-index: var(--z-sticky, 300);
	1437	+ display: flex; align-items: center; gap: 16px;
	1438	+ margin: 30px 0 22px; padding: 12px 0 11px;
	1439	+ border-bottom: 1px solid var(--hairline-strong);
	1440	+ background: color-mix(in srgb, var(--paper) 86%, transparent);
	1441	+ backdrop-filter: blur(12px); -webkit-backdrop-filter: blur(12px);
	1442	+}
	1443	+@supports not (background: color-mix(in srgb, red 50%, blue)) {
	1444	+ .results-bar { background: rgba(245, 243, 238, 0.92); }
	1445	+}
	1446	+.rb-count { margin: 0; font-size: clamp(16px, 2vw, 20px); letter-spacing: -0.02em; color: var(--ink); text-transform: none; }
	1447	+.rb-count b { font-variant-numeric: tabular-nums; }
	1448	+.rb-tools { margin-left: auto; display: flex; align-items: center; gap: 20px; }
	1449	+.rb-sort select {
	1450	+ border: 0; background: transparent; outline: none; cursor: pointer;
	1451	+ font-family: var(--font-mono); font-size: 11.5px; font-weight: 700;
	1452	+ text-transform: uppercase; letter-spacing: 0.06em; color: var(--ink-2);
	1453	+ appearance: none; -webkit-appearance: none; padding: 8px 16px 8px 0;
	1454	+ background-image: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='9' height='5'%3E%3Cpath d='M0 0l4.5 5L9 0z' fill='%238b928c'/%3E%3C/svg%3E");
	1455	+ background-repeat: no-repeat; background-position: right center;
	1456	+}
	1457	+.rb-sort select:hover { color: var(--ink); }
	1458	+.rb-tabs { display: flex; gap: 18px; }
	1459	+.rb-tab {
	1460	+ position: relative; display: inline-flex; align-items: center; gap: 6px;
	1461	+ border: 0; background: none; padding: 8px 0; cursor: pointer;
	1462	+ font-family: var(--font-display); font-weight: 700; font-size: 13.5px; color: var(--ink-3);
	1463	+ transition: color var(--dur-1) ease;
	1464	+}
	1465	+.rb-tab:hover, .rb-tab.on { color: var(--ink); }
	1466	+.rb-tab::after {
	1467	+ content: ""; position: absolute; left: 0; right: 0; bottom: -12px; height: 2.5px;
	1468	+ background: var(--lime); transform: scaleX(0); transform-origin: left;
	1469	+ transition: transform var(--dur-2) var(--ease-out);
	1470	+}
	1471	+.rb-tab.on::after { transform: scaleX(1); }
	1472	+.rb-filters {
	1473	+ display: inline-flex; align-items: center; gap: 7px;
	1474	+ border: 0; background: none; padding: 8px 0; cursor: pointer;
	1475	+ font-family: var(--font-display); font-weight: 700; font-size: 13.5px; color: var(--ink);
	1476	+}
	1477	+.rb-filters:hover { color: var(--accent-deep); }
	1478	+@media (min-width: 641px) { .rb-filters { display: none; } }
	1479	+
	1480	+/* ---- Transition douce liste ↔ carte ---- */
	1481	+.view-pane { animation: pane-in var(--dur-2) var(--ease-out); }
	1482	+@keyframes pane-in { from { opacity: 0; transform: translateY(6px); } to { opacity: 1; transform: none; } }
	1483	+
	1484	+/* ---- Chips rapides : plus légères ---- */
	1485	+.chip {
	1486	+ border: 1px solid var(--hairline-strong); background: transparent;
	1487	+ min-height: 38px; padding: 7px 15px; font-size: 12.5px; box-shadow: none;
	1488	+}
	1489	+.chip:hover { transform: none; box-shadow: none; background: var(--lime-soft); color: var(--accent-deep); }
	1490	+.chip.on { background: var(--ink); border-color: var(--ink); color: var(--paper); box-shadow: none; }
	1491	+.chips { margin: 20px 0 0; }
	1492	+
	1493	+/* ---- Pastilles actives : discrètes, survol = retrait ---- */
	1494	+.pills { margin: 14px 0 0; }
	1495	+.pills .pill { border: 1px solid var(--hairline-strong); background: transparent; box-shadow: none; padding: 5px 12px; font-size: 12px; }
	1496	+.pills .pill:hover { background: var(--danger-soft); border-color: var(--danger); color: var(--danger); }
	1497	+
	1498	+/* ---- Fiches éditoriales : l'image domine, plus de boîte ---- */
	1499	+.card, .card:hover { background: transparent; border: 0; border-radius: 0; box-shadow: none; transform: none; }
	1500	+.card-img { border-radius: var(--r-2); aspect-ratio: 4/3; }
	1501	+.card-img img { transition: transform var(--dur-3) var(--ease-out); }
	1502	+@media (hover: hover) {
	1503	+ .card:hover .card-img img { transform: scale(1.025); }
	1504	+ .card:hover .card-price { color: var(--accent-deep); }
	1505	+}
	1506	+.card:focus-visible { outline: 2px solid var(--green); outline-offset: 4px; border-radius: var(--r-2); }
	1507	+.card-body { padding: 13px 2px 0; gap: 3px; }
	1508	+.card-price { font-size: 22px; letter-spacing: -0.03em; color: var(--ink); transition: color var(--dur-1) ease; }
	1509	+.card-title { font-size: 14px; font-weight: 500; color: var(--ink-2); }
	1510	+.card-meta { font-family: var(--font-mono); font-size: 11px; text-transform: uppercase; letter-spacing: 0.06em; color: var(--ink-3); }
	1511	+.card-meta .sep { width: 3px; height: 3px; border: 0; border-radius: 50%; background: var(--lime); transform: none; }
	1512	+.card-specs { font-size: 11.5px; color: var(--ink-2); }
	1513	+.card-foot { border-top: 0; padding-top: 8px; }
	1514	+.source-tag { background: none; border: 0; border-radius: 0; padding: 0; color: var(--ink-3); font-size: 10px; letter-spacing: 0.08em; max-width: 62%; }
	1515	+.avail { font-size: 11px; color: var(--ink-3); }
	1516	+.badge { border: 0; border-radius: 4px; background: rgba(20, 24, 20, 0.78); color: var(--paper);
	1517	+ backdrop-filter: blur(4px); -webkit-backdrop-filter: blur(4px);
	1518	+ font-size: 9.5px; padding: 4px 9px; letter-spacing: 0.08em; }
	1519	+.badge.type { background: var(--lime); color: #fff; }
	1520	+.badge.right { background: rgba(20, 24, 20, 0.55); }
	1521	+/* la liste latérale de la vue carte garde ses fiches synchronisées lisibles */
	1522	+.map-card { border-radius: var(--r-2); }
	1523	+.map-card-sel { outline: 2px solid var(--lime); outline-offset: 3px; border-radius: var(--r-2); }
	1524	+
	1525	+/* ---- Grille à rythme éditorial (accueil) ---- */
	1526	+.grid.grid-edito { grid-template-columns: repeat(3, 1fr); gap: 36px 26px; align-items: start; }
	1527	+@media (max-width: 980px) {
	1528	+ .grid.grid-edito { grid-template-columns: 1fr 1fr; gap: 30px 20px; }
	1529	+}
	1530	+@media (max-width: 640px) {
	1531	+ .grid.grid-edito { grid-template-columns: 1fr; gap: 32px; }
	1532	+}
	1533	+@media (prefers-reduced-motion: no-preference) {
	1534	+ .grid-edito > * { animation: rise 0.5s var(--ease-out) backwards; }
	1535	+ .grid-edito > *:nth-child(3n+2) { animation-delay: 60ms; }
	1536	+ .grid-edito > *:nth-child(3n) { animation-delay: 120ms; }
	1537	+}
	1538	+@keyframes rise { from { opacity: 0; transform: translateY(10px); } to { opacity: 1; transform: none; } }
	1539	+
	1540	+/* ---- Squelettes sans boîte ---- */
	1541	+.skel { border: 0; border-radius: 0; background: transparent; }
	1542	+.skel .sk-img { aspect-ratio: 4/3; border-radius: var(--r-2); }
	1543	+.skel .sk-line { margin: 12px 2px; }
	1544	+
	1545	+/* ---- Pagination éditoriale : chiffres nus, page courante soulignée ---- */
	1546	+.pager { border-top: 1px solid var(--hairline); padding-top: 16px; margin-top: 26px; }
	1547	+.pager-info { font-family: var(--font-mono); font-size: 11.5px; text-transform: uppercase; letter-spacing: 0.06em; color: var(--ink-3); }
	1548	+.pager-btn {
	1549	+ min-width: 34px; min-height: 38px; height: auto; padding: 0 10px; border: 0; border-radius: var(--r-1);
	1550	+ background: none; color: var(--ink-2); box-shadow: none;
	1551	+ font-family: var(--font-display); font-size: 13.5px; font-weight: 600; position: relative;
	1552	+}
	1553	+.pager-btn:hover:not(:disabled):not(.on) { background: var(--lime-soft); color: var(--accent-deep); transform: none; box-shadow: none; }
	1554	+.pager-btn.on { background: none; border: 0; color: var(--ink); font-weight: 700; box-shadow: none; }
	1555	+.pager-btn.on::after { content: ""; position: absolute; left: 9px; right: 9px; bottom: 3px; height: 2.5px; background: var(--lime); }
	1556	+.pager-btn:disabled { box-shadow: none; }
	1557	+
	1558	+/* ---- Mobile : recherche condensée + feuille de critères premium ---- */
	1559	+@media (max-width: 640px) {
	1560	+ .hero h1.hero-display { font-size: clamp(38px, 11vw, 52px); }
	1561	+ .results-bar { top: 64px; gap: 10px; flex-wrap: wrap; }
	1562	+ .rb-tools { gap: 14px; }
	1563	+ .search-zone { margin: 30px 0 0; }
	1564	+ .crit-line, .search-zone .f-adv, .search-zone .sheet-apply { display: none; }
	1565	+ .crit-summary {
	1566	+ display: flex; align-items: center; gap: 10px; width: 100%;
	1567	+ border: 0; border-bottom: 1px solid var(--hairline); background: none;
	1568	+ padding: 14px 2px; margin: 0; cursor: pointer; text-align: left;
	1569	+ font-family: var(--font-mono); font-size: 12px; color: var(--ink-2);
	1570	+ }
	1571	+ .crit-summary svg { flex: none; color: var(--ink); }
	1572	+ .crit-summary .cs-txt { flex: 1; min-width: 0; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }
	1573	+ .crit-summary .f-chev { margin: 0 2px 0 0; }
	1574	+
	1575	+ .search-zone.open {
	1576	+ display: flex; flex-direction: column; gap: 12px;
	1577	+ position: fixed; left: 0; right: 0; bottom: 0; z-index: var(--z-modal, 900);
	1578	+ margin: 0; border-radius: var(--r-3) var(--r-3) 0 0; background: var(--surface);
	1579	+ border: 0;
	1580	+ max-height: 86dvh; overflow-y: auto; -webkit-overflow-scrolling: touch;
	1581	+ padding: 10px 18px calc(16px + env(safe-area-inset-bottom));
	1582	+ box-shadow: 0 -18px 50px rgba(20, 24, 20, 0.3);
	1583	+ animation: sheet-up 0.26s var(--ease-out);
	1584	+ }
	1585	+ .search-zone.open .sheet-handle {
	1586	+ display: block; flex: none; width: 40px; height: 4.5px;
	1587	+ border-radius: 999px; background: var(--line); margin: 0 auto;
	1588	+ }
	1589	+ .search-zone.open .sheet-head {
	1590	+ display: flex; justify-content: space-between; align-items: center;
	1591	+ font-family: var(--font-display); font-weight: 700; font-size: 17px;
	1592	+ letter-spacing: -0.01em; color: var(--ink); text-transform: none;
	1593	+ position: sticky; top: -10px; background: var(--surface); padding: 6px 0 8px;
	1594	+ border-bottom: 1px solid var(--hairline); z-index: 1;
	1595	+ }
	1596	+ .search-zone.open .crit-summary { display: none; }
	1597	+ .search-zone.open .q-big { padding: 2px 0 10px; }
	1598	+ .search-zone.open .q-big input { font-size: 17px; }
	1599	+ .search-zone.open .crit-line { display: flex; flex-direction: column; }
	1600	+ .search-zone.open .crit { border-right: 0; border-bottom: 1px solid var(--hairline); margin: 0; padding: 10px 0; }
	1601	+ .search-zone.open .crit select { max-width: none; width: 100%; font-size: 16px; }
	1602	+ .search-zone.open .crit .range-pair select { width: auto; flex: 1; }
	1603	+ .search-zone.open .crit-more { display: none; }
	1604	+ .search-zone.open .f-adv { display: grid; border-top: 0; padding-top: 4px; margin-top: 0; }
	1605	+ .search-zone.open .sheet-apply {
	1606	+ display: flex; position: sticky; bottom: 0; z-index: 1; width: 100%; min-height: 50px;
	1607	+ box-shadow: 0 -14px 18px -12px rgba(20, 24, 20, 0.35);
	1608	+ }
	1609	+}
	1610	+
	1611	+/* ---- Navigation mobile flottante (pilule détachée du bord) ---- */
	1612	+.tabbar { display: none; }
	1613	+@media (max-width: 760px) {
	1614	+ .tabbar {
	1615	+ display: grid; grid-template-columns: repeat(4, 1fr);
	1616	+ position: fixed; left: 12px; right: 12px;
	1617	+ bottom: calc(10px + env(safe-area-inset-bottom));
	1618	+ z-index: var(--z-bottombar, 600);
	1619	+ border: 1px solid var(--hairline-strong); border-radius: var(--r-3);
	1620	+ background: rgba(250, 249, 245, 0.88);
	1621	+ backdrop-filter: blur(18px); -webkit-backdrop-filter: blur(18px);
	1622	+ box-shadow: 0 14px 34px rgba(20, 24, 20, 0.16);
	1623	+ padding: 6px;
	1624	+ }
	1625	+ .tabbar a {
	1626	+ display: flex; flex-direction: column; align-items: center; justify-content: center;
	1627	+ gap: 2px; padding: 5px 2px; min-height: 48px; border-radius: 12px;
	1628	+ font-family: var(--font-display); font-size: 10px; font-weight: 600;
	1629	+ color: var(--ink-3); text-decoration: none; transition: color var(--dur-1) ease;
	1630	+ }
	1631	+ .tabbar a svg { display: block; }
	1632	+ .tabbar a.active { color: var(--ink); }
	1633	+ .tabbar a.active::after { content: ""; width: 16px; height: 2.5px; border-radius: 2px; background: var(--lime); }
	1634	+ body { padding-bottom: calc(80px + env(safe-area-inset-bottom)); }
	1635	+ .ka-footer { padding-bottom: calc(56px + env(safe-area-inset-bottom)); }
	1636	+
	1637	+ /* widget KA Agent : dégagé de la tabbar (style injecté après le bundle →
	1638	+ spécificité doublée pour gagner) */
	1639	+ .kaa-btn.kaa-btn { bottom: calc(86px + env(safe-area-inset-bottom, 0px)); right: 14px; }
	1640	+ .kaa-panel.kaa-panel:not(.kaa-full) { bottom: calc(152px + env(safe-area-inset-bottom, 0px)); }
	1641	+}
	1642	+
	1643	+/* ---- Header : jamais de débordement à droite ----
	1644	+ La nav (8 entrées) + connexion dépassaient le conteneur même à 1440px
	1645	+ (masqué par overflow-x: clip). Resserrage, badge Groupe KA masqué quand
	1646	+ l'espace manque, burger sous 1200px. ---- */
	1647	+.nav a { white-space: nowrap; padding: 8px 11px; font-size: 13px; }
	1648	+@media (max-width: 1400px) { .header .gk-badge { display: none; } }
	1649	+@media (max-width: 1200px) {
	1650	+ .nav { display: none; }
	1651	+ .menu-btn { display: flex; }
	1652	+}
	1653	+
	1654	+/* header pleine largeur : la nav dense s'aligne aux bords de l'écran au lieu
	1655	+ de déborder du conteneur 1240px sur les grands écrans */
	1656	+.header .header-inner { max-width: none; }
	1657	+
	1658	+/* ---- Fiche propriété : DA v2 — sections en filets, icônes contextuelles ---- */
	1659	+.f-bloc h2 { border-left: 0; padding-left: 0; display: flex; align-items: center; gap: 10px; }
	1660	+.f-bloc h2::before { content: ""; width: 20px; height: 3px; border-radius: 2px; background: var(--lime); flex: none; }
	1661	+/* le panneau héros perd sa boîte : la typographie structure */
	1662	+.f-hero { background: transparent; border: 0; box-shadow: none; padding: 0; }
	1663	+.f-hero .price { font-size: clamp(36px, 7vw, 54px); letter-spacing: -0.04em; }
	1664	+/* inclusions : grille d'items en filets — chaque inclusion a SON icône */
	1665	+.amenity-grid { display: grid; grid-template-columns: repeat(auto-fill, minmax(215px, 1fr)); gap: 0 28px; margin-bottom: 8px; }
	1666	+.amenity-it {
	1667	+ display: flex; align-items: center; gap: 11px; padding: 7px 0;
	1668	+ border-bottom: 1px solid var(--hairline); font-size: 13.5px; color: var(--ink); min-height: 46px;
	1669	+}
	1670	+.am-ico {
	1671	+ display: inline-grid; place-items: center; width: 32px; height: 32px;
	1672	+ border-radius: 10px; background: var(--lime-soft); color: var(--green-deep); flex: none;
	1673	+}
	1674	+.am-txt { min-width: 0; }
	1675	+/* caractéristiques : clés en micro-mono */
	1676	+.dtable { gap: 0 28px; }
	1677	+.drow { padding: 9px 0; }
	1678	+.drow span { font-family: var(--font-mono); font-size: 10.5px; text-transform: uppercase; letter-spacing: 0.06em; color: var(--ink-3); align-self: center; }
	1679	+/* galerie : cadre allégé */
	1680	+.carousel { border: 1px solid var(--hairline-strong); box-shadow: none; border-radius: var(--r-2); }
	1681	+.thumbs button { border-radius: 8px; }
	1682	+/* CTA sticky : sur la fiche, il prend le bas d'écran — la tabbar s'efface */
	1683	+body:has(.cta-sticky) .tabbar { display: none; }
	1684	+.cta-sticky { z-index: var(--z-dropdown, 700); border-top: 1px solid var(--hairline-strong); background: rgba(250, 249, 245, 0.92); }
	1685	+@media (max-width: 760px) {
	1686	+ body:has(.cta-sticky) { padding-bottom: 0; }
	1687	+}
	1688	+
	1689	+/* colonnes de la fiche : les sections respirent sans boîte — les modules
	1690	+ pleine largeur (.detail > .f-bloc : financement, quartier…) restent en cartes */
	1691	+.fiche > .f-col > .f-bloc:not(.f-galerie) {
	1692	+ background: transparent; border: 0; border-radius: 0; padding: 0; box-shadow: none;
	1693	+}
	1694	+@media (max-width: 640px) {
	1695	+ .fiche > .f-col > .f-bloc:not(.f-galerie) { padding: 0; }
	1696	+}
	1697	+/* tiret accent des titres : sans bordure ni ombre héritées de la couche fiche */
	1698	+.f-bloc h2::before, .quartier h2::before { border: 0; box-shadow: none; }
	1699	+
	1700	+/* =============================================================================
	1701	+ KA MAP SYSTEM v2 — MODE CARTE IMMO-KA (shell plein viewport)
	1702	+ Jetons du design system appliqués au shell ; le sélecteur .ka-map du
	1703	+ framework pose ses défauts directement sur le canevas — re-déclarer les
	1704	+ jetons dessus, sinon l'accent retombe au noir générique dans la carte.
	1705	+============================================================================= */
	1706	+.ka-shell,
	1707	+.ka-shell .ka-map {
	1708	+ --ka-accent: var(--accent);
	1709	+ --ka-on-accent: var(--on-accent, #fff);
	1710	+ --ka-surface: var(--surface);
	1711	+ --ka-ink: var(--ink);
	1712	+ --ka-line: var(--line-strong);
	1713	+ --ka-radius: var(--r-ctl);
	1714	+ --ka-shadow: 0 8px 24px rgba(26, 18, 20, 0.14);
	1715	+ --ka-font: var(--font-body);
	1716	+}
	1717	+.ka-shell-fallback {
	1718	+ position: fixed; inset: 0; z-index: 640;
	1719	+ display: grid; place-items: center;
	1720	+ background: var(--surface); color: var(--ink-3);
	1721	+ font-family: var(--font-mono, inherit); font-size: 13px;
	1722	+}
	1723	+.ms2-brand { display: inline-flex; align-items: baseline; gap: 7px; font-family: var(--font-display); min-width: 0; }
	1724	+.ms2-brand b { font-size: 15px; letter-spacing: -0.01em; }
	1725	+.ms2-brand span {
	1726	+ font-size: 10.5px; text-transform: uppercase; letter-spacing: 0.14em;
	1727	+ color: var(--ink-3); font-weight: 600;
	1728	+}
	1729	+.ka-top-btn {
	1730	+ display: inline-flex; align-items: center; gap: 6px;
	1731	+ border: 1.5px solid var(--ink); border-radius: var(--r-ctl);
	1732	+ background: var(--surface); color: var(--ink);
	1733	+ font-family: var(--font-display); font-weight: 600; font-size: 12.5px;
	1734	+ padding: 8px 13px; cursor: pointer; min-height: 38px; white-space: nowrap;
	1735	+}
	1736	+.ka-top-btn:hover { background: var(--ink); color: #fff; }
	1737	+.ka-top-badge {
	1738	+ min-width: 17px; height: 17px; border-radius: 999px;
	1739	+ background: var(--accent); color: var(--on-accent, #fff);
	1740	+ font-size: 10.5px; font-weight: 700; line-height: 17px;
	1741	+ text-align: center; padding: 0 4px;
	1742	+}
	1743	+.ms2-head { display: flex; align-items: center; justify-content: space-between; gap: 10px; width: 100%; min-width: 0; }
	1744	+.ms2-count { font-size: 13px; color: var(--ink-2); min-width: 0; }
	1745	+.ms2-count b { color: var(--ink); font-size: 15px; }
	1746	+.ms2-zone {
	1747	+ margin-left: 8px; font-size: 11px; color: var(--accent-deep, var(--accent));
	1748	+ border: 1px dashed var(--accent); border-radius: 999px; padding: 2px 8px;
	1749	+}
	1750	+.ms2-sort select {
	1751	+ border: 1.5px solid var(--ink); border-radius: var(--r-ctl);
	1752	+ background: var(--surface); padding: 6px 8px; font-size: 12.5px;
	1753	+ font-weight: 600; color: var(--ink); max-width: 168px;
	1754	+}
	1755	+.ms2-list { display: flex; flex-direction: column; gap: 14px; position: relative; }
	1756	+.ms2-list .map-card { flex: 0 0 auto; }
	1757	+.ka-sheet .ms2-list { gap: 12px; padding-bottom: 10px; }
	1758	+.ms2-pager { display: flex; align-items: center; justify-content: center; gap: 10px; padding: 6px 0 4px; }
	1759	+
	1760	+/* mode carte : le widget Ka Agent s'efface (le sheet occupe son coin) */
	1761	+body.ka-map-mode .kaa-btn, body.ka-map-mode .kaa-hello { display: none !important; }
	1762	+
	1763	+/* filtres de la page AU-DESSUS du mode carte — desktop : modale centrée */
	1764	+@media (min-width: 781px) {
	1765	+ body.ka-map-mode .sheet-backdrop {
	1766	+ display: block; position: fixed; inset: 0;
	1767	+ z-index: var(--z-overlay, 800); background: rgba(26, 18, 20, 0.45);
	1768	+ }
	1769	+ body.ka-map-mode .search-zone { display: none; }
	1770	+ body.ka-map-mode .search-zone.open {
	1771	+ display: block; position: fixed; top: 7dvh; left: 50%;
	1772	+ transform: translateX(-50%); width: min(760px, 94vw);
	1773	+ max-height: 84dvh; overflow-y: auto; z-index: var(--z-modal, 900);
	1774	+ background: var(--surface); border: 1.5px solid var(--ink);
	1775	+ border-radius: var(--r-card); box-shadow: var(--shadow-off);
	1776	+ padding: 16px 22px 20px; margin: 0;
	1777	+ }
	1778	+ body.ka-map-mode .search-zone.open .sheet-head {
	1779	+ display: flex; align-items: center; justify-content: space-between;
	1780	+ font-weight: 700; font-size: 14px; margin-bottom: 10px;
	1781	+ }
	1782	+ body.ka-map-mode .search-zone.open .sheet-close {
	1783	+ display: grid; place-items: center; width: 34px; height: 34px;
	1784	+ border: 1.5px solid var(--ink); border-radius: 50%;
	1785	+ background: var(--surface); cursor: pointer; font-size: 14px;
	1786	+ }
	1787	+}
	1788	+
	1789	+/* --- KA ID v2 : badge « Recommandé pour vous » (parcimonieux, serveur) --- */
	1790	+.badge.ka-reco { top: auto; bottom: 12px; background: var(--ink); color: var(--accent); }
	1791	+
	1792	+/* ================= House-Ka footer (replaces the shared KaFooter) ========== */
	1793	+.hk-footer {
	1794	+ margin-top: 72px; background: var(--ink); color: rgba(250, 247, 240, 0.78);
	1795	+ padding: 52px 0 40px; position: relative; overflow: hidden;
	1796	+}
	1797	+.hk-footer::before {
	1798	+ content: ""; position: absolute; inset: 0; pointer-events: none;
	1799	+ background:
	1800	+ radial-gradient(circle at 78% 18%, rgba(15, 107, 79, 0.35), transparent 52%),
	1801	+ radial-gradient(circle at 8% 90%, rgba(15, 107, 79, 0.18), transparent 45%);
	1802	+}
	1803	+.hk-footer .container { position: relative; }
	1804	+.hk-foot-brand {
	1805	+ font-family: var(--font-display); font-weight: 700; font-size: 30px;
	1806	+ letter-spacing: -0.02em; color: var(--paper); display: inline-flex; align-items: center;
	1807	+}
	1808	+.hk-foot-brand .ka {
	1809	+ background: var(--accent); color: #fff; padding: 2px 8px 4px;
	1810	+ border-radius: 7px; margin-left: 4px; transform: rotate(-2deg);
	1811	+}
	1812	+.hk-foot-desc { max-width: 640px; margin: 16px 0 10px; line-height: 1.65; font-size: 14.5px; }
	1813	+.hk-foot-desc b { color: var(--paper); }
	1814	+.hk-foot-notice { max-width: 640px; margin: 0 0 24px; font-size: 12.5px; line-height: 1.6; color: rgba(250, 247, 240, 0.55); }
	1815	+.hk-foot-sites { list-style: none; margin: 0 0 26px; padding: 0; display: flex; flex-wrap: wrap; gap: 10px 26px; }
	1816	+.hk-foot-sites li { display: flex; align-items: baseline; gap: 8px; font-size: 13px; }
	1817	+.hk-foot-sites a { color: var(--paper); font-family: var(--font-display); font-weight: 600; font-size: 15px; }
	1818	+.hk-foot-sites a:hover { color: var(--accent-soft); }
	1819	+.hk-foot-sites span { color: rgba(250, 247, 240, 0.5); }
	1820	+.hk-foot-legal { display: flex; flex-wrap: wrap; gap: 8px 22px; padding-top: 18px; border-top: 1px solid rgba(250, 247, 240, 0.14); font-size: 12.5px; }
	1821	+.hk-foot-legal a { color: rgba(250, 247, 240, 0.72); }
	1822	+.hk-foot-legal a:hover { color: var(--paper); }
	1823	+.hk-foot-legal span { margin-left: auto; color: rgba(250, 247, 240, 0.45); }
	1824	+@media (max-width: 780px) {
	1825	+ .hk-footer { padding-bottom: calc(56px + env(safe-area-inset-bottom)); }
	1826	+}
	1827	+.legal .legal-date { color: var(--ink-3); font-family: var(--font-mono); font-size: 12px; margin: 0 0 26px; }

added frontend/src/vite-env.d.ts +1 −0

		`@@ -0,0 +1 @@`
	1	+/// <reference types="vite/client" />

added frontend/tsconfig.json +21 −0

		`@@ -0,0 +1,21 @@`
	1	+{
	2	+ "compilerOptions": {
	3	+ "target": "ES2020",
	4	+ "useDefineForClassFields": true,
	5	+ "lib": ["ES2020", "DOM", "DOM.Iterable"],
	6	+ "module": "ESNext",
	7	+ "skipLibCheck": true,
	8	+ "moduleResolution": "bundler",
	9	+ "allowImportingTsExtensions": true,
	10	+ "resolveJsonModule": true,
	11	+ "isolatedModules": true,
	12	+ "noEmit": true,
	13	+ "jsx": "react-jsx",
	14	+ "strict": true,
	15	+ "noUnusedLocals": false,
	16	+ "noUnusedParameters": false,
	17	+ "noFallthroughCasesInSwitch": true
	18	+ },
	19	+ "include": ["src"],
	20	+ "exclude": ["src/kamaps", "src/pages/Category.tsx"]
	21	+}

added frontend/vite.config.ts +15 −0

		`@@ -0,0 +1,15 @@`
	1	+// -----------------------------------------------------------------------------
	2	+// Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)
	3	+// Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+// vite.config.ts : configuration Vite (proxy API en dev, build vers dist/)
	5	+// -----------------------------------------------------------------------------
	6	+import { defineConfig } from "vite";
	7	+import react from "@vitejs/plugin-react";
	8	+
	9	+export default defineConfig({
	10	+ plugins: [react()],
	11	+ server: {
	12	+ proxy: { "/api": "http://localhost:8090" },
	13	+ },
	14	+ build: { outDir: "dist", chunkSizeWarningLimit: 1200 },
	15	+});

added immoka/__init__.py +9 −0

		`@@ -0,0 +1,9 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# -----------------------------------------------------------------------------
	5	+"""Immo-Ka : un connecteur par agence de courtage immobilier, un schéma unique,
	6	+un diff engine — toutes les propriétés à vendre du Québec, à jour, à un seul
	7	+endroit. Architecture jumelle de Lou-Ka (location)."""
	8	+
	9	+__version__ = "0.1.0"

added immoka/auth.py +306 −0

		`@@ -0,0 +1,306 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Une application du Groupe-Ka — contact@groupe-ka.com
	4	+# auth.py : connexion Google (OAuth 2.0 / OpenID Connect) + sessions signées
	5	+#
	6	+# Identité PARTAGÉE Groupe-Ka : Lou-Ka (location) et Immo-Ka (vente) utilisent
	7	+# le MÊME client OAuth Google (GOOGLE_CLIENT_ID) — chaque app enregistre son
	8	+# URL de rappel dans la console Google. L'utilisateur est identifié par le
	9	+# `sub` Google (stable pour un compte, identique dans les deux apps) : le
	10	+# profil (courriel, nom, photo) est donc le même des deux côtés, et Google
	11	+# saute l'écran de consentement à la 2e app (SSO de fait).
	12	+#
	13	+# URLs de rappel à autoriser dans Google Cloud Console (Identifiants →
	14	+# ID client OAuth « Groupe-Ka ») :
	15	+# https://www.immo-ka.com/api/auth/google/callback
	16	+# https://www.lou-ka.com/api/auth/google/callback
	17	+# http://localhost:8090/api/auth/google/callback (développement)
	18	+#
	19	+# Session : JWT HS256 maison (hmac/base64, aucune dépendance) signé avec
	20	+# AUTH_SECRET (PARTAGER le même secret entre les deux apps si on veut que les
	21	+# jetons soient mutuellement vérifiables), cookie httponly 30 jours.
	22	+# -----------------------------------------------------------------------------
	23	+from __future__ import annotations
	24	+
	25	+import base64
	26	+import hashlib
	27	+import hmac
	28	+import json
	29	+import os
	30	+import time
	31	+import urllib.parse
	32	+
	33	+import requests
	34	+from fastapi import APIRouter, Request
	35	+from fastapi.responses import JSONResponse, RedirectResponse
	36	+
	37	+from . import db
	38	+from .hubprofile import fetch_hub_profile, to_epoch
	39	+
	40	+router = APIRouter(prefix="/api/auth")
	41	+
	42	+GOOGLE_AUTH = "https://accounts.google.com/o/oauth2/v2/auth"
	43	+GOOGLE_TOKEN = "https://oauth2.googleapis.com/token"
	44	+GOOGLE_USERINFO = "https://openidconnect.googleapis.com/v1/userinfo"
	45	+
	46	+CLIENT_ID = os.environ.get("GOOGLE_CLIENT_ID", "")
	47	+CLIENT_SECRET = os.environ.get("GOOGLE_CLIENT_SECRET", "")
	48	+# base publique de CETTE app (l'URL de rappel en découle)
	49	+BASE_URL = os.environ.get("IMMOKA_BASE_URL", "http://localhost:8090").rstrip("/")
	50	+REDIRECT_URI = f"{BASE_URL}/api/auth/google/callback"
	51	+SECRET = os.environ.get("AUTH_SECRET", "") or hashlib.sha256(
	52	+ (CLIENT_SECRET or "immoka-dev").encode()).hexdigest()
	53	+COOKIE = "groupeka_session"
	54	+SESSION_DAYS = 30
	55	+
	56	+
	57	+# -- JWT HS256 minimal (aucune dépendance) -----------------------------------
	58	+def _b64(d: bytes) -> str:
	59	+ return base64.urlsafe_b64encode(d).rstrip(b"=").decode()
	60	+
	61	+
	62	+def _unb64(s: str) -> bytes:
	63	+ return base64.urlsafe_b64decode(s + "=" * (-len(s) % 4))
	64	+
	65	+
	66	+def jwt_encode(payload: dict) -> str:
	67	+ head = _b64(json.dumps({"alg": "HS256", "typ": "JWT"}).encode())
	68	+ body = _b64(json.dumps(payload, separators=(",", ":")).encode())
	69	+ sig = _b64(hmac.new(SECRET.encode(), f"{head}.{body}".encode(), hashlib.sha256).digest())
	70	+ return f"{head}.{body}.{sig}"
	71	+
	72	+
	73	+def jwt_decode(token: str) -> dict \| None:
	74	+ try:
	75	+ head, body, sig = token.split(".")
	76	+ good = _b64(hmac.new(SECRET.encode(), f"{head}.{body}".encode(), hashlib.sha256).digest())
	77	+ if not hmac.compare_digest(sig, good):
	78	+ return None
	79	+ payload = json.loads(_unb64(body))
	80	+ if payload.get("exp", 0) < time.time():
	81	+ return None
	82	+ return payload
	83	+ except Exception:
	84	+ return None
	85	+
	86	+
	87	+# -- table users --------------------------------------------------------------
	88	+def _ensure_table(con) -> None:
	89	+ con.execute("""CREATE TABLE IF NOT EXISTS users (
	90	+ sub TEXT PRIMARY KEY, -- identifiant Google (stable, partagé Lou-Ka/Immo-Ka)
	91	+ email TEXT,
	92	+ name TEXT,
	93	+ picture TEXT,
	94	+ created REAL,
	95	+ last_login REAL
	96	+ )""")
	97	+
	98	+
	99	+def _upsert_user(info: dict) -> dict:
	100	+ con = db.connect()
	101	+ try:
	102	+ _ensure_table(con)
	103	+ now = time.time()
	104	+ con.execute(
	105	+ "INSERT INTO users (sub, email, name, picture, created, last_login)"
	106	+ " VALUES (?,?,?,?,?,?)"
	107	+ " ON CONFLICT(sub) DO UPDATE SET email=excluded.email,"
	108	+ " name=excluded.name, picture=excluded.picture, last_login=excluded.last_login",
	109	+ (info["sub"], info.get("email", ""), info.get("name", ""),
	110	+ info.get("picture", ""), now, now))
	111	+ con.commit()
	112	+ finally:
	113	+ con.close()
	114	+ return {"sub": info["sub"], "email": info.get("email", ""),
	115	+ "name": info.get("name", ""), "picture": info.get("picture", "")}
	116	+
	117	+
	118	+def current_user(request: Request) -> dict \| None:
	119	+ payload = jwt_decode(request.cookies.get(COOKIE, ""))
	120	+ return payload.get("user") if payload else None
	121	+
	122	+
	123	+# -- routes --------------------------------------------------------------------
	124	+@router.get("/google/login")
	125	+def google_login(next: str = "/"):
	126	+ """Redirige vers l'écran de connexion Google (OpenID Connect)."""
	127	+ if not CLIENT_ID:
	128	+ return JSONResponse({"error": "GOOGLE_CLIENT_ID manquant (voir .env)"}, status_code=503)
	129	+ state = jwt_encode({"next": next[:200], "exp": time.time() + 600})
	130	+ params = {
	131	+ "client_id": CLIENT_ID,
	132	+ "redirect_uri": REDIRECT_URI,
	133	+ "response_type": "code",
	134	+ "scope": "openid email profile",
	135	+ "state": state,
	136	+ "access_type": "online",
	137	+ "prompt": "select_account",
	138	+ }
	139	+ return RedirectResponse(f"{GOOGLE_AUTH}?{urllib.parse.urlencode(params)}")
	140	+
	141	+
	142	+@router.get("/google/callback")
	143	+def google_callback(code: str = "", state: str = "", error: str = ""):
	144	+ """Échange le code contre le profil Google, crée la session (cookie signé)."""
	145	+ st = jwt_decode(state) or {}
	146	+ dest = st.get("next") or "/"
	147	+ if error or not code or not st:
	148	+ return RedirectResponse(f"/?auth=echec")
	149	+ try:
	150	+ tok = requests.post(GOOGLE_TOKEN, data={
	151	+ "code": code, "client_id": CLIENT_ID, "client_secret": CLIENT_SECRET,
	152	+ "redirect_uri": REDIRECT_URI, "grant_type": "authorization_code",
	153	+ }, timeout=15).json()
	154	+ info = requests.get(GOOGLE_USERINFO, headers={
	155	+ "Authorization": f"Bearer {tok['access_token']}"}, timeout=15).json()
	156	+ if not info.get("sub"):
	157	+ raise ValueError("profil Google sans sub")
	158	+ except Exception:
	159	+ return RedirectResponse("/?auth=echec")
	160	+ user = _upsert_user(info)
	161	+ session = jwt_encode({"user": user, "iss": "groupe-ka",
	162	+ "exp": time.time() + SESSION_DAYS * 86400})
	163	+ resp = RedirectResponse(dest)
	164	+ resp.set_cookie(COOKIE, session, max_age=SESSION_DAYS * 86400, httponly=True,
	165	+ samesite="lax", secure=BASE_URL.startswith("https"), path="/")
	166	+ return resp
	167	+
	168	+
	169	+@router.get("/me")
	170	+def me(request: Request):
	171	+ """Profil de l'utilisateur connecté (ou {user: null}). `enabled` indique si
	172	+ la connexion (Google ou KA ID) est configurée (le frontend masque le bouton
	173	+ sinon). Quand le compte est relié au hub Groupe KA, le profil du hub
	174	+ (bio, ville, emploi, entreprise, âge, site, réseaux, statut) ENRICHIT la
	175	+ réponse — le hub est la source de vérité, l'édition se fait sur
	176	+ groupe-ka.com/compte."""
	177	+ user = current_user(request)
	178	+ if user is None:
	179	+ return {"user": None, "enabled": bool(CLIENT_ID or KA_SSO_SECRET)}
	180	+
	181	+ out = dict(user)
	182	+ # ancienneté locale (table users) — « Membre depuis »
	183	+ con = db.connect()
	184	+ try:
	185	+ _ensure_table(con)
	186	+ row = con.execute(
	187	+ "SELECT created, last_login FROM users WHERE sub=?",
	188	+ (user.get("sub", ""),)).fetchone()
	189	+ finally:
	190	+ con.close()
	191	+ if row is not None:
	192	+ out["created_at"] = row[0]
	193	+ out["last_login"] = row[1]
	194	+ ka_id = user.get("ka_id") or ""
	195	+ out["ka_id"] = ka_id
	196	+ out["provider"] = "ka-id" if ka_id else "google"
	197	+ out["profile_source"] = "local"
	198	+
	199	+ # Le HUB Groupe KA est la source de vérité du profil : s'il connaît ce
	200	+ # KA ID, ses champs REMPLACENT les champs locaux. Hub injoignable ou 404
	201	+ # (vieux compte non relié) -> réponse locale inchangée.
	202	+ hub = fetch_hub_profile(ka_id) if ka_id else None
	203	+ if hub is not None:
	204	+ hub_name = (hub.get("name") or "").strip()
	205	+ out.update({
	206	+ "name": hub_name or out.get("name", ""),
	207	+ "bio": hub.get("bio") or "",
	208	+ "city": hub.get("city") or "",
	209	+ "phone": hub.get("phone") or "",
	210	+ "website": hub.get("website") or "",
	211	+ "socials": hub.get("socials") or {},
	212	+ "public": bool(hub.get("public")),
	213	+ "role_label": hub.get("role_label") or "",
	214	+ "job_title": hub.get("job_title") or "",
	215	+ "company": hub.get("company") or "",
	216	+ "age": hub.get("age"),
	217	+ "public_url": hub.get("public_url") or "",
	218	+ "created_at": to_epoch(hub.get("created_at"))
	219	+ or out.get("created_at"),
	220	+ "profile_source": "groupe-ka",
	221	+ })
	222	+ if hub.get("picture"):
	223	+ out["picture"] = hub["picture"]
	224	+ return {"user": out, "enabled": bool(CLIENT_ID or KA_SSO_SECRET)}
	225	+
	226	+
	227	+@router.post("/logout")
	228	+def logout():
	229	+ resp = JSONResponse({"ok": True})
	230	+ resp.delete_cookie(COOKIE, path="/")
	231	+ return resp
	232	+
	233	+
	234	+# -- KA ID (hub d'identité du groupe — groupe-ka.com) --------------------------
	235	+# « Se connecter avec KA ID » : Immo-Ka délègue la connexion au hub
	236	+# (qui offre Google OU courriel/mot de passe). Retour avec un JWT HS256
	237	+# signé du secret partagé KA_SSO_SECRET ; le profil (ka_id, courriel, nom,
	238	+# photo) est LE MÊME sur toutes les plateformes du groupe.
	239	+# Config .env : KA_SSO_SECRET, KA_HUB_URL (optionnel), AUTH_SECRET.
	240	+
	241	+KA_HUB_URL = os.environ.get("KA_HUB_URL", "https://www.groupe-ka.com").rstrip("/")
	242	+KA_SSO_SECRET = os.environ.get("KA_SSO_SECRET", "")
	243	+
	244	+
	245	+def _ka_verify(token: str) -> dict \| None:
	246	+ """Vérifie un JWT HS256 émis par le hub KA (stdlib seulement)."""
	247	+ if not KA_SSO_SECRET:
	248	+ return None
	249	+ try:
	250	+ head, body, sig = token.split(".")
	251	+ good = _b64(hmac.new(KA_SSO_SECRET.encode(),
	252	+ f"{head}.{body}".encode(), hashlib.sha256).digest())
	253	+ if not hmac.compare_digest(sig, good):
	254	+ return None
	255	+ if json.loads(_unb64(head)).get("alg") != "HS256":
	256	+ return None
	257	+ claims = json.loads(_unb64(body))
	258	+ if claims.get("iss") != KA_HUB_URL:
	259	+ return None
	260	+ if claims.get("aud") != "immo-ka":
	261	+ return None
	262	+ if claims.get("exp", 0) < time.time():
	263	+ return None
	264	+ return claims
	265	+ except Exception:
	266	+ return None
	267	+
	268	+
	269	+@router.get("/ka/login")
	270	+def ka_login(next: str = "/"):
	271	+ """Redirige vers le hub KA ID (groupe-ka.com) — SSO du groupe."""
	272	+ if not KA_SSO_SECRET:
	273	+ return JSONResponse({"error": "KA_SSO_SECRET manquant (voir .env)"},
	274	+ status_code=503)
	275	+ state = jwt_encode({"next": next[:200], "exp": time.time() + 600})
	276	+ params = {
	277	+ "client_id": "immo-ka",
	278	+ "redirect_uri": f"{BASE_URL}/api/auth/ka/callback",
	279	+ "state": state,
	280	+ }
	281	+ return RedirectResponse(f"{KA_HUB_URL}/sso/authorize?{urllib.parse.urlencode(params)}")
	282	+
	283	+
	284	+@router.get("/ka/callback")
	285	+def ka_callback(ka_token: str = "", state: str = ""):
	286	+ """Retour du hub : vérifie le jeton, upsert l'utilisateur, pose la session."""
	287	+ st = jwt_decode(state) or {}
	288	+ dest = st.get("next") or "/"
	289	+ claims = _ka_verify(ka_token) if ka_token else None
	290	+ if not st or claims is None:
	291	+ return RedirectResponse("/?auth=echec")
	292	+ # clé stable = KA-ID du groupe (créé par le hub, identique partout)
	293	+ ka_id = str(claims.get("ka_id") or f"ka:{claims.get('sub')}")
	294	+ user = _upsert_user({
	295	+ "sub": ka_id,
	296	+ "email": claims.get("email", ""),
	297	+ "name": claims.get("name", ""),
	298	+ "picture": claims.get("picture") or "",
	299	+ })
	300	+ user["ka_id"] = ka_id
	301	+ session = jwt_encode({"user": user, "iss": "groupe-ka",
	302	+ "exp": time.time() + SESSION_DAYS * 86400})
	303	+ resp = RedirectResponse(dest)
	304	+ resp.set_cookie(COOKIE, session, max_age=SESSION_DAYS * 86400, httponly=True,
	305	+ samesite="lax", secure=BASE_URL.startswith("https"), path="/")
	306	+ return resp

added immoka/commerces.py +294 −0

		`@@ -0,0 +1,294 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# commerces.py : grands commerces à proximité — API Mapbox Search Box
	5	+#
	6	+# Pour chaque grande bannière (Costco, Metro, IGA, Walmart…), on interroge
	7	+# l'API Search Box de Mapbox (jeton PUBLIC pk.… lu dans
	8	+# frontend/src/kamaps/config.ts — source de vérité du projet) avec la
	9	+# position de l'annonce en `proximity`, et on retient le point de vente le
	10	+# plus proche. Cache par cellule d'environ 1 km (data/commerces.db,
	11	+# TTL 30 jours) : les fiches d'un même secteur ne recoûtent rien.
	12	+# -----------------------------------------------------------------------------
	13	+from __future__ import annotations
	14	+
	15	+import json
	16	+import math
	17	+import re
	18	+import sqlite3
	19	+import time
	20	+import urllib.parse
	21	+import urllib.request
	22	+from concurrent.futures import ThreadPoolExecutor
	23	+from pathlib import Path
	24	+
	25	+ROOT = Path(__file__).resolve().parent.parent
	26	+DB_PATH = ROOT / "data" / "commerces.db"
	27	+UA = "HouseKaBot/1.0 (+https://www.house-ka.com; contact@spboucher.ai)"
	28	+TTL = 30 * 86400
	29	+API = "https://api.mapbox.com/search/searchbox/v1/forward"
	30	+
	31	+# id, libellé, requête Mapbox, mot-clé de validation (le nom du POI doit le
	32	+# contenir, sans accents ni casse — écarte « Station Métro », « Super Qualité »…)
	33	+BRANDS = [
	34	+ ("costco", "Costco", "Costco Wholesale", "costco"),
	35	+ ("walmart", "Walmart", "Walmart Supercentre", "walmart"),
	36	+ ("metro", "Metro", "Metro", "metro"),
	37	+ ("iga", "IGA", "IGA", "iga"),
	38	+ ("maxi", "Maxi", "Maxi", "maxi"),
	39	+ ("superc", "Super C", "Super C", "super c"),
	40	+ ("provigo", "Provigo", "Provigo", "provigo"),
	41	+ ("canadiantire", "Canadian Tire", "Canadian Tire", "canadian tire"),
	42	+ ("dollarama", "Dollarama", "Dollarama", "dollarama"),
	43	+ ("saq", "SAQ", "SAQ", "saq"),
	44	+ ("pharmaprix", "Pharmaprix", "Pharmaprix", "pharmaprix"),
	45	+ ("jeancoutu", "Jean Coutu", "Jean Coutu pharmacie", "jean coutu"),
	46	+ ("homedepot", "Home Depot", "Home Depot", "home depot"),
	47	+ ("rona", "RONA", "RONA", "rona"),
	48	+]
	49	+
	50	+_BAN = ("station", "stationnement")
	51	+
	52	+
	53	+def _norm(s: str) -> str:
	54	+ import unicodedata
	55	+ s = unicodedata.normalize("NFD", s or "")
	56	+ return "".join(c for c in s if unicodedata.category(c) != "Mn").lower()
	57	+
	58	+_token_cache: list[str] = []
	59	+
	60	+
	61	+def _token() -> str:
	62	+ if not _token_cache:
	63	+ cfg = (ROOT / "frontend" / "src" / "kamaps" / "config.ts").read_text()
	64	+ m = re.search(r'"(pk\.[A-Za-z0-9._-]+)"', cfg)
	65	+ if not m:
	66	+ raise RuntimeError("jeton Mapbox introuvable (kamaps/config.ts)")
	67	+ _token_cache.append(m.group(1))
	68	+ return _token_cache[0]
	69	+
	70	+
	71	+def _connect() -> sqlite3.Connection:
	72	+ DB_PATH.parent.mkdir(parents=True, exist_ok=True)
	73	+ con = sqlite3.connect(DB_PATH, timeout=15)
	74	+ con.row_factory = sqlite3.Row
	75	+ con.execute("""CREATE TABLE IF NOT EXISTS commerces_cache (
	76	+ cellule TEXT, brand TEXT, nom TEXT, adresse TEXT,
	77	+ lat REAL, lng REAL, fetched_at REAL,
	78	+ PRIMARY KEY (cellule, brand))""")
	79	+ return con
	80	+
	81	+
	82	+def _dist_m(lat1, lng1, lat2, lng2) -> float:
	83	+ dlat = math.radians(lat2 - lat1)
	84	+ dlng = math.radians(lng2 - lng1)
	85	+ a = (math.sin(dlat / 2) ** 2 + math.cos(math.radians(lat1))
	86	+ * math.cos(math.radians(lat2)) * math.sin(dlng / 2) ** 2)
	87	+ return 6371000 * 2 * math.asin(math.sqrt(a))
	88	+
	89	+
	90	+def _fetch_brand(brand_q: str, lat: float, lng: float,
	91	+ match: str = "") -> dict \| None:
	92	+ params = urllib.parse.urlencode({
	93	+ "q": brand_q, "proximity": f"{lng},{lat}", "limit": 5,
	94	+ "types": "poi", "language": "fr", "country": "CA",
	95	+ "access_token": _token()})
	96	+ req = urllib.request.Request(f"{API}?{params}",
	97	+ headers={"User-Agent": UA})
	98	+ try:
	99	+ with urllib.request.urlopen(req, timeout=12) as r:
	100	+ feats = json.load(r).get("features") or []
	101	+ except Exception:
	102	+ return None
	103	+ for f in feats:
	104	+ p = f.get("properties") or {}
	105	+ nom = _norm(p.get("name") or "")
	106	+ if match and match not in nom:
	107	+ continue
	108	+ if any(b in nom for b in _BAN):
	109	+ continue
	110	+ lng2, lat2 = f["geometry"]["coordinates"][:2]
	111	+ return {"nom": p.get("name") or brand_q,
	112	+ "adresse": p.get("full_address")
	113	+ or p.get("place_formatted") or "",
	114	+ "lat": lat2, "lng": lng2}
	115	+ return None
	116	+
	117	+
	118	+OVERPASS = ["https://overpass.kumi.systems/api/interpreter",
	119	+ "https://overpass-api.de/api/interpreter"]
	120	+
	121	+
	122	+def _fetch_transit(lat: float, lng: float) -> list[tuple[str, dict]]:
	123	+ """Station de métro et arrêt de bus les plus proches (OpenStreetMap)."""
	124	+ q = f"""[out:json][timeout:20];
	125	+(
	126	+ node["railway"="station"]["station"="subway"](around:3000,{lat},{lng});
	127	+ node["highway"="bus_stop"](around:1000,{lat},{lng});
	128	+);
	129	+out body;"""
	130	+ data = None
	131	+ for url in OVERPASS:
	132	+ try:
	133	+ req = urllib.request.Request(
	134	+ url, data=urllib.parse.urlencode({"data": q}).encode(),
	135	+ headers={"User-Agent": UA})
	136	+ with urllib.request.urlopen(req, timeout=25) as r:
	137	+ data = json.load(r)
	138	+ break
	139	+ except Exception:
	140	+ continue
	141	+ if not data:
	142	+ return []
	143	+ best: dict[str, tuple[float, dict]] = {}
	144	+ for el in data.get("elements", []):
	145	+ tags = el.get("tags") or {}
	146	+ kind = ("metro_station" if tags.get("railway") == "station"
	147	+ else "arret_bus")
	148	+ d = _dist_m(lat, lng, el["lat"], el["lon"])
	149	+ if kind not in best or d < best[kind][0]:
	150	+ best[kind] = (d, {"nom": tags.get("name")
	151	+ or ("Station de métro" if kind == "metro_station"
	152	+ else "Arrêt de bus"),
	153	+ "adresse": "", "lat": el["lat"],
	154	+ "lng": el["lon"]})
	155	+ return [(k, v[1]) for k, v in best.items()]
	156	+
	157	+
	158	+TRANSIT = [("metro_station", "Station de métro"),
	159	+ ("rem_station", "Station REM"),
	160	+ ("arret_bus", "Arrêt de bus"),
	161	+ ("gare_train", "Gare de train")]
	162	+
	163	+_DB_GENRE = {"metro": "metro_station", "rem": "rem_station",
	164	+ "bus": "arret_bus", "train": "gare_train"}
	165	+
	166	+
	167	+def _transit_from_db(lat: float, lng: float) -> list[tuple[str, dict]]:
	168	+ """Arrêts/stations depuis data/transit.db (extrait OpenStreetMap
	169	+ pré-calculé : ~37 000 arrêts de bus, métro, REM, gares du Québec)."""
	170	+ db = ROOT / "data" / "transit.db"
	171	+ if not db.exists():
	172	+ return []
	173	+ con = sqlite3.connect(f"file:{db}?mode=ro", uri=True)
	174	+ con.row_factory = sqlite3.Row
	175	+ out = []
	176	+ for genre, rayon in (("metro", 6000), ("rem", 6000), ("bus", 1500),
	177	+ ("train", 8000)):
	178	+ d = rayon / 111320.0
	179	+ rows = con.execute(
	180	+ "SELECT nom, lat, lng FROM arrets WHERE genre=? AND lat BETWEEN "
	181	+ "? AND ? AND lng BETWEEN ? AND ?",
	182	+ (genre, lat - d, lat + d, lng - d, lng + d)).fetchall()
	183	+ best = None
	184	+ for r in rows:
	185	+ dd = _dist_m(lat, lng, r["lat"], r["lng"])
	186	+ if dd <= rayon and (best is None or dd < best[0]):
	187	+ best = (dd, r)
	188	+ if best:
	189	+ out.append((_DB_GENRE[genre],
	190	+ {"nom": best[1]["nom"] or "", "adresse": "",
	191	+ "lat": best[1]["lat"], "lng": best[1]["lng"]}))
	192	+ con.close()
	193	+ return out
	194	+
	195	+_POI_CAT = {"metro": "metro_station", "bus": "arret_bus"}
	196	+
	197	+
	198	+def _transit_from_poi(lat: float, lng: float) -> list[tuple[str, dict]]:
	199	+ """Métro/bus depuis le cache POI du projet (louka.db, déjà calculé par
	200	+ immeuble) — la fiche interroge avec les mêmes coordonnées que poi.py."""
	201	+ db_main = ROOT / "data" / next(
	202	+ (n for n in ("louka.db", "immoka.db", "immo.db")
	203	+ if (ROOT / "data" / n).exists()), "louka.db")
	204	+ if not db_main.exists():
	205	+ return []
	206	+ try:
	207	+ con = sqlite3.connect(f"file:{db_main}?mode=ro", uri=True)
	208	+ con.row_factory = sqlite3.Row
	209	+ d = 300 / 111320.0
	210	+ row = con.execute(
	211	+ "SELECT pois, lat, lng FROM poi_cache WHERE lat BETWEEN ? AND ? "
	212	+ "AND lng BETWEEN ? AND ? ORDER BY (lat-?)(lat-?)+(lng-?)(lng-?) "
	213	+ "LIMIT 1", (lat - d, lat + d, lng - d, lng + d,
	214	+ lat, lat, lng, lng)).fetchone()
	215	+ con.close()
	216	+ except sqlite3.Error:
	217	+ return []
	218	+ if row is None:
	219	+ return []
	220	+ out = []
	221	+ for e in json.loads(row["pois"] or "[]"):
	222	+ k = _POI_CAT.get(e.get("cat"))
	223	+ if k:
	224	+ out.append((k, {"nom": e.get("name") or "", "adresse": "",
	225	+ "lat": lat, "lng": lng,
	226	+ "_dist": e.get("dist_m")}))
	227	+ return out
	228	+
	229	+
	230	+def nearby(lat: float, lng: float) -> dict:
	231	+ """Grand commerce le plus proche par bannière (cache ~1 km, TTL 30 j)."""
	232	+ cell = f"{round(lat, 2)},{round(lng, 2)}"
	233	+ con = _connect()
	234	+ now = time.time()
	235	+ cached = {r["brand"]: r for r in con.execute(
	236	+ "SELECT * FROM commerces_cache WHERE cellule=? AND fetched_at>?",
	237	+ (cell, now - TTL))}
	238	+ manquants = [(bid, q, m) for bid, _, q, m in BRANDS
	239	+ if bid not in cached]
	240	+ transit_manquant = any(k not in cached for k, _ in TRANSIT)
	241	+ if manquants or transit_manquant:
	242	+ res: list[tuple[str, dict \| None]] = []
	243	+ if manquants:
	244	+ with ThreadPoolExecutor(max_workers=6) as ex:
	245	+ res = list(ex.map(
	246	+ lambda b: (b[0], _fetch_brand(b[1], lat, lng, b[2])),
	247	+ manquants))
	248	+ if transit_manquant:
	249	+ tr = (_transit_from_db(lat, lng)
	250	+ or _transit_from_poi(lat, lng) or _fetch_transit(lat, lng))
	251	+ res.extend(tr)
	252	+ with con:
	253	+ for bid, hit in res:
	254	+ if hit is None:
	255	+ continue
	256	+ con.execute(
	257	+ "INSERT OR REPLACE INTO commerces_cache VALUES "
	258	+ "(?,?,?,?,?,?,?)",
	259	+ (cell, bid, hit["nom"],
	260	+ hit.get("adresse") or (str(hit["_dist"])
	261	+ if hit.get("_dist") is not None
	262	+ else ""),
	263	+ hit["lat"], hit["lng"], now))
	264	+ cached = {r["brand"]: r for r in con.execute(
	265	+ "SELECT * FROM commerces_cache WHERE cellule=? AND fetched_at>?",
	266	+ (cell, now - TTL))}
	267	+ con.close()
	268	+
	269	+ items = []
	270	+ transit = []
	271	+ for bid, label in TRANSIT:
	272	+ r = cached.get(bid)
	273	+ if r is not None:
	274	+ # distance : celle du cache POI si disponible (adresse numérique)
	275	+ d = (float(r["adresse"]) if (r["adresse"] or "").replace(
	276	+ ".", "").isdigit() else _dist_m(lat, lng, r["lat"], r["lng"]))
	277	+ if d <= 5000:
	278	+ transit.append({"id": bid, "commerce": label,
	279	+ "nom": r["nom"], "adresse": "",
	280	+ "dist_m": round(d),
	281	+ "lat": r["lat"], "lng": r["lng"]})
	282	+ for bid, label, _q, _m in BRANDS:
	283	+ r = cached.get(bid)
	284	+ if r is None:
	285	+ continue
	286	+ d = _dist_m(lat, lng, r["lat"], r["lng"])
	287	+ if d > 40000: # au-delà de 40 km : non pertinent
	288	+ continue
	289	+ items.append({"id": bid, "commerce": label, "nom": r["nom"],
	290	+ "adresse": r["adresse"], "dist_m": round(d),
	291	+ "lat": r["lat"], "lng": r["lng"]})
	292	+ items.sort(key=lambda x: x["dist_m"])
	293	+ transit.sort(key=lambda x: x["dist_m"])
	294	+ return {"n": len(items), "commerces": items, "transit": transit}

added immoka/connectors/__init__.py +30 −0

		`@@ -0,0 +1,30 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# connectors/__init__.py : registre AUTO-DÉCOUVRANT des connecteurs
	5	+# Tout module de ce paquet contenant une sous-classe de BaseConnector avec un
	6	+# source_id non vide est enregistré automatiquement — aucun fichier partagé
	7	+# à modifier pour ajouter un connecteur (1 connecteur = 1 agence).
	8	+# -----------------------------------------------------------------------------
	9	+from __future__ import annotations
	10	+
	11	+import importlib
	12	+import pkgutil
	13	+import sys
	14	+
	15	+from .base import BaseConnector
	16	+
	17	+CONNECTORS: dict[str, type[BaseConnector]] = {}
	18	+
	19	+for _mod in pkgutil.iter_modules(__path__):
	20	+ if _mod.name in ("base", "__init__"):
	21	+ continue
	22	+ try:
	23	+ module = importlib.import_module(f"{__name__}.{_mod.name}")
	24	+ except Exception as exc: # un connecteur cassé ne bloque pas les autres
	25	+ print(f"[immo-ka] connecteur '{_mod.name}' ignoré : {exc}", file=sys.stderr)
	26	+ continue
	27	+ for obj in vars(module).values():
	28	+ if (isinstance(obj, type) and issubclass(obj, BaseConnector)
	29	+ and obj is not BaseConnector and getattr(obj, "source_id", "")):
	30	+ CONNECTORS[obj.source_id] = obj

added immoka/connectors/_detailutil.py +219 −0

		`@@ -0,0 +1,219 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# connectors/_detailutil.py : utilitaires partagés d'enrichissement « page détail »
	5	+# Mutualise ce que chaque connecteur d'agence répète pour capter TOUTES les
	6	+# infos de la fiche source (comme remax_quebec.py) : description JSON-LD,
	7	+# coordonnées, aplatissement HTML, application au PropertyListing.
	8	+# -----------------------------------------------------------------------------
	9	+from __future__ import annotations
	10	+
	11	+import html as _html
	12	+import json
	13	+import re
	14	+
	15	+from ..schema import PropertyListing
	16	+
	17	+_LD_RE = re.compile(r'<script[^>]+application/ld\+json[^>]>(.?)</script>', re.S \| re.I)
	18	+_COORD_RE = re.compile(r'(?:google\.[^"\']*?[?&](?:q\|query\|ll\|center)=\|maps/@)'
	19	+ r'(-?\d{1,2}\.\d+)[ ,%+A-Za-z]+?(-?\d{2,3}\.\d+)')
	20	+_LD_PROP_TYPES = {"RealEstateListing", "Residence", "SingleFamilyResidence",
	21	+ "House", "Apartment", "Product", "Offer", "Place", "Accommodation"}
	22	+
	23	+
	24	+def ld_nodes(html: str):
	25	+ """Itère les objets JSON-LD (aplatis depuis @graph)."""
	26	+ for block in _LD_RE.findall(html):
	27	+ try:
	28	+ # strict=False : tolère les \n/\t bruts dans les chaînes (Yoamo…)
	29	+ data = json.loads(block, strict=False)
	30	+ except ValueError:
	31	+ continue
	32	+ graph = data.get("@graph", [data]) if isinstance(data, dict) else data
	33	+ for node in (graph if isinstance(graph, list) else [graph]):
	34	+ if isinstance(node, dict):
	35	+ yield node
	36	+
	37	+
	38	+def ld_description(html: str) -> str:
	39	+ """Description depuis un nœud JSON-LD de type propriété (le plus long trouvé)."""
	40	+ best = ""
	41	+ for n in ld_nodes(html):
	42	+ t = n.get("@type")
	43	+ types = t if isinstance(t, list) else [t]
	44	+ if any(x in _LD_PROP_TYPES for x in types) and n.get("description"):
	45	+ d = _html.unescape(str(n["description"])).strip()
	46	+ if len(d) > len(best):
	47	+ best = d
	48	+ return best
	49	+
	50	+
	51	+def gmaps_coords(html: str) -> tuple[float, float] \| None:
	52	+ m = _COORD_RE.search(html)
	53	+ if not m:
	54	+ return None
	55	+ try:
	56	+ lat, lng = float(m.group(1)), float(m.group(2))
	57	+ except ValueError:
	58	+ return None
	59	+ if 44.5 <= lat <= 63.0 and -80.0 <= lng <= -56.0:
	60	+ return lat, lng
	61	+ return None
	62	+
	63	+
	64	+def flatten(html: str) -> str:
	65	+ """HTML -> texte « valeur \| libellé » pour extraire les tableaux Centris."""
	66	+ t = _html.unescape(re.sub(r"<[^>]+>", " \| ", html))
	67	+ t = re.sub(r"[ \t\r\n]\\|[ \t\r\n\|]", " \| ", t)
	68	+ return re.sub(r"[ \t]+", " ", t)
	69	+
	70	+
	71	+# libellés Centris standard cherchés dans « valeur \| libellé » OU « libellé \| valeur »
	72	+_LABELS = [
	73	+ "Type de propriété", "Genre de propriété", "Style de bâtiment",
	74	+ "Année de construction", "Superficie habitable", "Superficie du terrain",
	75	+ "Superficie du bâtiment (au sol)", "Nombre de pièces", "Nombre d'unités",
	76	+ "Stationnement (total)", "Stationnement", "Garage", "Système de chauffage",
	77	+ "Énergie pour le chauffage", "Type de fenestration", "Fenêtres", "Toiture",
	78	+ "Revêtement", "Sous-sol", "Piscine", "Zonage", "Système d'égouts",
	79	+ "Approvisionnement en eau", "Déménagement", "Taxes municipales",
	80	+ "Taxes scolaires", "Évaluation municipale (terrain)",
	81	+ "Évaluation municipale (bâtiment)", "Cuisine",
	82	+]
	83	+
	84	+
	85	+# en-têtes de section des fiches (jamais des valeurs valides)
	86	+_SECTION_HEADERS = {
	87	+ "bâtiment et intérieur", "particularités du bâtiment",
	88	+ "particularités du terrain", "particularités du site", "caractéristiques",
	89	+ "caractéristiques de la propriété", "détails financiers", "taxes et coûts",
	90	+ "taxes\xa0et\xa0coûts", "détails des pièces", "détails des rénovations",
	91	+ "inclusions et exclusions", "dimensions", "addenda", "frais mensuels",
	92	+ "évaluations", "équipement disponible", "dans les environs",
	93	+ "niveau", "revêtement", "détails", "taxes", "total", "pièce", "couvre-sol",
	94	+}
	95	+_LABELS_LOWER = {lb.lower() for lb in _LABELS}
	96	+
	97	+
	98	+def _plausible(label: str, val: str) -> bool:
	99	+ """Garde-fou : rejette les valeurs qui sont d'autres libellés/en-têtes de
	100	+ section (l'aplatissement « \| » rend les deux ordres ambigus) et exige un
	101	+ format minimal pour les champs monétaires/numériques."""
	102	+ low = val.lower().strip(" :")
	103	+ if not val or len(val) > 55 or low == label.lower():
	104	+ return False
	105	+ if low in _LABELS_LOWER or low in _SECTION_HEADERS:
	106	+ return False
	107	+ if label.startswith(("Taxes", "Évaluation")) and "$" not in val:
	108	+ return False
	109	+ if label == "Année de construction" and not re.search(r"\b(1[6-9]\|20)\d{2}\b", val):
	110	+ return False
	111	+ if label.startswith("Superficie") and not re.search(r"\d", val):
	112	+ return False
	113	+ return True
	114	+
	115	+
	116	+def centris_details(text: str) -> dict:
	117	+ """Extrait les caractéristiques Centris d'un texte aplati.
	118	+
	119	+ Les fiches Centris modernes rendent « Libellé \| Valeur » (le libellé
	120	+ précède la valeur) — c'est l'ordre essayé en premier ; l'ancien ordre
	121	+ « Valeur \| Libellé » reste en repli. Un garde-fou (_plausible) évite de
	122	+ capter l'en-tête de section ou le libellé voisin comme valeur."""
	123	+ out: dict = {}
	124	+ for label in _LABELS:
	125	+ lab = re.escape(label)
	126	+ for m in (re.search(lab + r"\s(?:$\d{4}$)?\s\\|\s*([^\|]{1,55})", text),
	127	+ re.search(r"([^\|]{1,55})\s\\|\s" + lab + r"\b", text)):
	128	+ if m:
	129	+ val = re.sub(r"\s+", " ", m.group(1)).strip(" \|")
	130	+ if _plausible(label, val):
	131	+ out[label] = val
	132	+ break
	133	+ return out
	134	+
	135	+
	136	+_INT_RE = re.compile(r"\d+")
	137	+
	138	+
	139	+def _int(v):
	140	+ if v is None:
	141	+ return None
	142	+ if isinstance(v, (int, float)):
	143	+ return int(v) or None
	144	+ m = _INT_RE.search(str(v))
	145	+ return int(m.group()) if m else None
	146	+
	147	+
	148	+def enrich(connector, listings, limit, parse_fn, key="v1", fetch_html=None):
	149	+ """Enrichit `listings` via leur page détail, avec cache BD + plafond `limit`.
	150	+
	151	+ - `parse_fn(html) -> dict` : extrait les champs riches d'une page détail.
	152	+ - `key` : versionne le cache (changer pour forcer un rafraîchissement).
	153	+ - `fetch_html(url) -> str` : par défaut connector.get(url).text ; passer
	154	+ connector.get_rendered pour les sites derrière Firecrawl/anti-bot.
	155	+ """
	156	+ if limit <= 0:
	157	+ return
	158	+ from .. import db
	159	+ fetch_html = fetch_html or (lambda u: connector.get(u).text)
	160	+ con = db.connect()
	161	+ budget = limit
	162	+ try:
	163	+ for lst in listings:
	164	+ cached = db.get_cached_detail(con, connector.source_id, lst.external_id, key)
	165	+ if cached is None:
	166	+ stale = db.get_stale_detail(con, connector.source_id, lst.external_id)
	167	+ if budget <= 0:
	168	+ # budget épuisé : payload périmé (ancienne clé) plutôt que
	169	+ # rien — la fiche garde ses photos/détails en attendant
	170	+ # son re-parse à un prochain cycle
	171	+ if stale:
	172	+ apply_detail(lst, stale)
	173	+ continue
	174	+ try:
	175	+ cached = parse_fn(fetch_html(lst.url))
	176	+ except Exception:
	177	+ cached = {}
	178	+ if not cached and stale:
	179	+ # échec transitoire (challenge, timeout) : on garde l'ancien
	180	+ # payload et on ne l'écrase pas — nouvel essai au prochain cycle
	181	+ apply_detail(lst, stale)
	182	+ budget -= 1
	183	+ continue
	184	+ db.put_cached_detail(con, connector.source_id, lst.external_id, key, cached)
	185	+ budget -= 1
	186	+ apply_detail(lst, cached)
	187	+ finally:
	188	+ con.close()
	189	+
	190	+
	191	+def apply_detail(lst: PropertyListing, d: dict) -> None:
	192	+ """Applique un payload détail au PropertyListing sans écraser les valeurs déjà
	193	+ présentes (sauf images : on garde la plus grande galerie)."""
	194	+ if not d:
	195	+ return
	196	+ imgs = d.get("images")
	197	+ if imgs and len(imgs) > len(lst.images):
	198	+ lst.images = imgs
	199	+ if d.get("features"):
	200	+ # fusionne en dédoublonnant
	201	+ seen = {f.lower() for f in lst.features}
	202	+ for f in d["features"]:
	203	+ if f.lower() not in seen:
	204	+ lst.features.append(f)
	205	+ seen.add(f.lower())
	206	+ if d.get("details"):
	207	+ lst.details.update(d["details"])
	208	+ if d.get("broker_name"):
	209	+ lst.broker_name = d["broker_name"]
	210	+ # description : on garde la plus riche (la fiche détail bat le résumé liste)
	211	+ if d.get("description") and len(d["description"]) > len(lst.description or ""):
	212	+ lst.description = d["description"]
	213	+ for f in ("price_label", "address", "city", "sector", "property_type"):
	214	+ if d.get(f) and not getattr(lst, f, ""):
	215	+ setattr(lst, f, d[f])
	216	+ for f in ("bedrooms", "bathrooms", "powder_rooms", "year_built",
	217	+ "area_sqft", "lot_sqft", "lat", "lng", "broker_phone", "price"):
	218	+ if d.get(f) is not None and getattr(lst, f, None) in (None, "", 0):
	219	+ setattr(lst, f, d[f])

added immoka/connectors/_resilient.py +318 −0

		`@@ -0,0 +1,318 @@`
	1	+# =============================================================================
	2	+# Groupe KA — connecteurs : chaîne de fetch anti-bot RÉSILIENTE (commune)
	3	+# Auteur : Simon-Pierre Boucher <contact@spboucher.ai>
	4	+# Fichier : connectors/_resilient.py
	5	+# -----------------------------------------------------------------------------
	6	+# But : rendre les connecteurs durables dans le temps. Quand un site jusque-là
	7	+# ouvert déploie un anti-bot (Cloudflare / Akamai / Incapsula / PerimeterX) ou
	8	+# renvoie 403/429/503, la requête directe N'ÉCHOUE PLUS silencieusement : elle
	9	+# ESCALADE automatiquement à travers une chaîne de secours :
	10	+#
	11	+# 1. Direct — la session du connecteur (curl_cffi impersonate si
	12	+# dispo, sinon requests) : rapide et gratuit.
	13	+# 2. Oxylabs (résid.) — proxy résidentiel Canada (-cc-CA) : IP propre.
	14	+# 3. Scrapfly (ASP) — bypass anti-bot géré + rendu JS optionnel.
	15	+# 4. Bright Data — Web Unlocker : déblocage premium, dernier recours.
	16	+#
	17	+# Le premier backend qui renvoie un 200 non vide gagne. Si TOUS échouent, on
	18	+# renvoie la dernière réponse (avec son code d'erreur) pour que le connecteur
	19	+# journalise l'échec comme avant — aucun changement de comportement en cas
	20	+# d'échec total, aucun blocage silencieux.
	21	+#
	22	+# Conception :
	23	+# - Aucun effet de bord à l'import ; toute brique non configurée est sautée.
	24	+# - Les clés sont lues de os.environ, avec repli sur le .env de l'app puis
	25	+# ~/.claude/.env, et acceptent les deux noms Scrapfly (SCRAPFLY_KEY /
	26	+# SCRAPFLY_API_KEY). => aucune modif de .env nécessaire.
	27	+# - `_ResilientResponse` imite requests.Response (.text/.content/.status_code/
	28	+# .url/.headers/.json()/.ok/.raise_for_status()) : les connecteurs existants
	29	+# continuent de fonctionner sans modification.
	30	+# - Coupe-circuit par hôte : après plusieurs escalades totalement infructueuses
	31	+# sur un même hôte, on saute l'escalade payante pendant un temps de repos
	32	+# (évite de brûler du quota Scrapfly/Bright Data sur une source morte).
	33	+# =============================================================================
	34	+from __future__ import annotations
	35	+
	36	+import json as _json
	37	+import os
	38	+import time
	39	+from pathlib import Path
	40	+from urllib.parse import quote, urlsplit
	41	+
	42	+import requests
	43	+
	44	+# -- curl_cffi est OPTIONNEL (meilleur fingerprint TLS s'il est présent) ------
	45	+try: # pragma: no cover
	46	+ from curl_cffi import requests as _cffi # type: ignore
	47	+ _HAS_CFFI = True
	48	+except Exception: # noqa: BLE001
	49	+ _cffi = None
	50	+ _HAS_CFFI = False
	51	+
	52	+# Codes HTTP typiques d'un blocage anti-bot (≠ 401/404/410/500 « métier » :
	53	+# 401 = auth manquante, 403/429 = bot bloqué, 5xx CF = challenge/edge).
	54	+BLOCK_STATUS = {403, 429, 503, 520, 521, 522, 523, 524, 526, 1020}
	55	+
	56	+# Marqueurs de page-challenge (Cloudflare/Akamai/Incapsula/PerimeterX/DataDome).
	57	+_CHALLENGE_MARKERS = (
	58	+ "just a moment", "cf-browser-verification", "cf-challenge",
	59	+ "attention required", "access denied", "request unsuccessful",
	60	+ "px-captcha", "perimeterx", "incapsula", "_incapsula_", "datadome",
	61	+ "captcha-delivery", "please enable javascript and cookies",
	62	+ "checking your browser", "ddos protection by",
	63	+)
	64	+
	65	+_UA = ("Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 "
	66	+ "(KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36")
	67	+
	68	+# Coupe-circuit en mémoire : hôte -> (timestamp_jusquà, échecs_consécutifs)
	69	+_COOLDOWN: dict[str, tuple[float, int]] = {}
	70	+_COOLDOWN_HITS = 3 # nb d'échecs totaux avant repos
	71	+_COOLDOWN_SECONDS = 900.0 # 15 min de repos pour un hôte « mort »
	72	+
	73	+# -- chargement paresseux des secrets ----------------------------------------
	74	+_ENV_CACHE: dict[str, str] \| None = None
	75	+
	76	+
	77	+def _load_env_files() -> dict[str, str]:
	78	+ """Parse les .env candidats une seule fois (repli si os.environ vide)."""
	79	+ global _ENV_CACHE
	80	+ if _ENV_CACHE is not None:
	81	+ return _ENV_CACHE
	82	+ out: dict[str, str] = {}
	83	+ candidates = []
	84	+ # .env de l'app (remonte quelques niveaux depuis ce module)
	85	+ here = Path(__file__).resolve()
	86	+ for up in range(2, 6):
	87	+ try:
	88	+ candidates.append(here.parents[up] / ".env")
	89	+ except IndexError:
	90	+ break
	91	+ candidates.append(Path.home() / ".claude" / ".env")
	92	+ for path in candidates:
	93	+ try:
	94	+ if not path.is_file():
	95	+ continue
	96	+ for line in path.read_text(encoding="utf-8", errors="ignore").splitlines():
	97	+ line = line.strip()
	98	+ if not line or line.startswith("#") or "=" not in line:
	99	+ continue
	100	+ k, _, v = line.partition("=")
	101	+ k, v = k.strip(), v.strip().strip('"').strip("'")
	102	+ # ne pas écraser une valeur déjà trouvée (priorité app > global)
	103	+ if k and k not in out:
	104	+ out[k] = v
	105	+ except Exception: # noqa: BLE001
	106	+ continue
	107	+ _ENV_CACHE = out
	108	+ return out
	109	+
	110	+
	111	+def _secret(*names: str) -> str \| None:
	112	+ """Cherche une clé dans os.environ puis dans les .env (par ordre de noms)."""
	113	+ for n in names:
	114	+ v = os.environ.get(n)
	115	+ if v:
	116	+ return v
	117	+ env = _load_env_files()
	118	+ for n in names:
	119	+ v = env.get(n)
	120	+ if v:
	121	+ return v
	122	+ return None
	123	+
	124	+
	125	+# -- réponse compatible requests.Response ------------------------------------
	126	+class _ResilientResponse:
	127	+ """Imite le minimum utile d'une requests.Response pour les connecteurs."""
	128	+
	129	+ def __init__(self, url: str, status_code: int, text: str,
	130	+ headers: dict \| None = None, via: str = "direct") -> None:
	131	+ self.url = url
	132	+ self.status_code = int(status_code or 0)
	133	+ self._text = text or ""
	134	+ self.headers = headers or {}
	135	+ self.encoding = "utf-8"
	136	+ self.via = via # backend gagnant (diagnostic)
	137	+
	138	+ @property
	139	+ def text(self) -> str:
	140	+ return self._text
	141	+
	142	+ @property
	143	+ def content(self) -> bytes:
	144	+ return self._text.encode("utf-8", errors="ignore")
	145	+
	146	+ @property
	147	+ def ok(self) -> bool:
	148	+ return 200 <= self.status_code < 400
	149	+
	150	+ def json(self, **kw):
	151	+ return _json.loads(self._text)
	152	+
	153	+ def raise_for_status(self):
	154	+ if 400 <= self.status_code < 600:
	155	+ raise requests.HTTPError(
	156	+ f"{self.status_code} via {self.via} pour {self.url}",
	157	+ response=self) # type: ignore[arg-type]
	158	+ return None
	159	+
	160	+ def __repr__(self) -> str: # pragma: no cover
	161	+ return f"<_ResilientResponse [{self.status_code}] via {self.via}>"
	162	+
	163	+
	164	+# -- détection de blocage -----------------------------------------------------
	165	+def is_blocked(resp) -> bool:
	166	+ """True si la réponse ressemble à un blocage anti-bot (≠ erreur métier)."""
	167	+ if resp is None:
	168	+ return True
	169	+ code = getattr(resp, "status_code", 0) or 0
	170	+ if code in BLOCK_STATUS:
	171	+ return True
	172	+ # 200 mais page-challenge servie
	173	+ if code == 200:
	174	+ try:
	175	+ body = (resp.text or "")[:4000].lower()
	176	+ except Exception: # noqa: BLE001
	177	+ return False
	178	+ server = str(resp.headers.get("Server", "")).lower() if getattr(resp, "headers", None) else ""
	179	+ if any(m in body for m in _CHALLENGE_MARKERS):
	180	+ return True
	181	+ if "cloudflare" in server and ("captcha" in body or "challenge" in body):
	182	+ return True
	183	+ return False
	184	+
	185	+
	186	+def _host(url: str) -> str:
	187	+ try:
	188	+ return urlsplit(url).netloc.lower()
	189	+ except Exception: # noqa: BLE001
	190	+ return url
	191	+
	192	+
	193	+def _cooling(host: str) -> bool:
	194	+ until, _ = _COOLDOWN.get(host, (0.0, 0))
	195	+ return time.time() < until
	196	+
	197	+
	198	+def _note_failure(host: str) -> None:
	199	+ until, hits = _COOLDOWN.get(host, (0.0, 0))
	200	+ hits += 1
	201	+ if hits >= _COOLDOWN_HITS:
	202	+ _COOLDOWN[host] = (time.time() + _COOLDOWN_SECONDS, 0)
	203	+ else:
	204	+ _COOLDOWN[host] = (until, hits)
	205	+
	206	+
	207	+def _note_success(host: str) -> None:
	208	+ _COOLDOWN.pop(host, None)
	209	+
	210	+
	211	+# -- backends d'escalade ------------------------------------------------------
	212	+def _try_oxylabs(url: str, timeout: int, country: str,
	213	+ headers: dict \| None) -> _ResilientResponse \| None:
	214	+ endpoint = _secret("OXYLABS_PROXY") # pr.oxylabs.io:7777
	215	+ user = _secret("OXYLABS_PROXY_USER") # customer-... (sans -cc-XX)
	216	+ pwd = _secret("OXYLABS_PROXY_PASS")
	217	+ if not (endpoint and user and pwd):
	218	+ return None
	219	+ cc = (country or "ca").upper()
	220	+ puser = f"{user}-cc-{cc}"
	221	+ proxy = f"http://{quote(puser, safe='')}:{quote(pwd, safe='')}@{endpoint}"
	222	+ proxies = {"http": proxy, "https": proxy}
	223	+ hdrs = {"User-Agent": _UA}
	224	+ if headers:
	225	+ hdrs.update(headers)
	226	+ try:
	227	+ r = requests.get(url, proxies=proxies, headers=hdrs, timeout=timeout,
	228	+ verify=False) # noqa: S501 (proxy MITM du CA Oxylabs)
	229	+ return _ResilientResponse(url, r.status_code, r.text,
	230	+ dict(r.headers), via="oxylabs")
	231	+ except Exception: # noqa: BLE001
	232	+ return None
	233	+
	234	+
	235	+def _try_scrapfly(url: str, timeout: int, country: str, render_js: bool,
	236	+ headers: dict \| None) -> _ResilientResponse \| None:
	237	+ key = _secret("SCRAPFLY_KEY", "SCRAPFLY_API_KEY")
	238	+ if not key:
	239	+ return None
	240	+ params = {"key": key, "url": url, "country": country or "ca",
	241	+ "asp": "true", "proxy_pool": "public_residential_pool"}
	242	+ if render_js:
	243	+ params["render_js"] = "true"
	244	+ if headers:
	245	+ for k, v in headers.items():
	246	+ params[f"headers[{k}]"] = v
	247	+ try:
	248	+ r = requests.get("https://api.scrapfly.io/scrape", params=params,
	249	+ timeout=max(timeout, 180))
	250	+ result = (r.json() or {}).get("result") or {}
	251	+ return _ResilientResponse(
	252	+ url, result.get("status_code") or 0, result.get("content") or "",
	253	+ (result.get("response_headers") or {}), via="scrapfly")
	254	+ except Exception: # noqa: BLE001
	255	+ return None
	256	+
	257	+
	258	+def _try_brightdata(url: str, timeout: int,
	259	+ headers: dict \| None) -> _ResilientResponse \| None:
	260	+ key = _secret("BRIGHTDATA_API_KEY")
	261	+ zone = _secret("BRIGHTDATA_ZONE") or "web_unlocker1"
	262	+ if not key:
	263	+ return None
	264	+ try:
	265	+ r = requests.post(
	266	+ "https://api.brightdata.com/request",
	267	+ headers={"Authorization": f"Bearer {key}",
	268	+ "Content-Type": "application/json"},
	269	+ json={"zone": zone, "url": url, "format": "raw"},
	270	+ timeout=max(timeout, 120))
	271	+ return _ResilientResponse(url, r.status_code, r.text,
	272	+ dict(r.headers), via="brightdata")
	273	+ except Exception: # noqa: BLE001
	274	+ return None
	275	+
	276	+
	277	+# -- API publique -------------------------------------------------------------
	278	+def escalate(url: str, *, timeout: int = 30, country: str = "ca",
	279	+ render_js: bool = False, headers: dict \| None = None,
	280	+ original=None):
	281	+ """Tente la chaîne de secours et renvoie la meilleure réponse.
	282	+
	283	+ Renvoie un `_ResilientResponse` 200 dès qu'un backend réussit ; sinon la
	284	+ dernière réponse tentée (ou `original`) pour préserver le comportement
	285	+ d'échec du connecteur. Respecte le coupe-circuit par hôte.
	286	+ """
	287	+ host = _host(url)
	288	+ if _cooling(host):
	289	+ return original # source au repos : on ne brûle pas de quota payant
	290	+
	291	+ last = original
	292	+ for backend in (
	293	+ lambda: _try_oxylabs(url, timeout, country, headers),
	294	+ lambda: _try_scrapfly(url, timeout, country, render_js, headers),
	295	+ lambda: _try_brightdata(url, timeout, headers),
	296	+ ):
	297	+ resp = backend()
	298	+ if resp is None:
	299	+ continue
	300	+ last = resp
	301	+ if resp.status_code == 200 and resp.text and not is_blocked(resp):
	302	+ _note_success(host)
	303	+ return resp
	304	+ time.sleep(0.4)
	305	+
	306	+ _note_failure(host)
	307	+ return last if last is not None else original
	308	+
	309	+
	310	+def escalate_if_blocked(resp, url: str, *, timeout: int = 30,
	311	+ country: str = "ca", render_js: bool = False,
	312	+ headers: dict \| None = None):
	313	+ """Renvoie `resp` s'il est bon ; sinon lance l'escalade anti-bot."""
	314	+ if not is_blocked(resp):
	315	+ return resp
	316	+ better = escalate(url, timeout=timeout, country=country,
	317	+ render_js=render_js, headers=headers, original=resp)
	318	+ return better if better is not None else resp

added immoka/connectors/base.py +244 −0

		`@@ -0,0 +1,244 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# connectors/base.py : classe de base des connecteurs + backends de fetch
	5	+# (requests direct, ou Firecrawl pour les sites JavaScript)
	6	+# -----------------------------------------------------------------------------
	7	+from __future__ import annotations
	8	+
	9	+import json
	10	+import os
	11	+import time
	12	+
	13	+import requests
	14	+
	15	+from ..schema import PropertyListing
	16	+
	17	+USER_AGENT = ("Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) "
	18	+ "AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126 Safari/537.36 "
	19	+ "ImmoKaBot/1.0 (+https://www.immo-ka.com/bot; contact@spboucher.ai)")
	20	+
	21	+FIRECRAWL_API = "https://api.firecrawl.dev/v1/scrape"
	22	+SCRAPFLY_API = "https://api.scrapfly.io/scrape"
	23	+
	24	+
	25	+class BaseConnector:
	26	+ """Un connecteur = un adaptateur propre à un site d'agence de courtage.
	27	+
	28	+ Sous-classes : définir `source_id` et implémenter `fetch()` qui retourne
	29	+ la liste complète des propriétés actuellement affichées sur le site.
	30	+ Le pipeline (ingest.py) s'occupe du diff avec la base de données.
	31	+ """
	32	+
	33	+ source_id: str = ""
	34	+ request_delay: float = 0.6 # politesse entre requêtes
	35	+ timeout: int = 30
	36	+ use_detail_cache: bool = True # cache BD des pages détail
	37	+
	38	+ def __init__(self) -> None:
	39	+ self.session = requests.Session()
	40	+ self.session.headers["User-Agent"] = USER_AGENT
	41	+ self._last_request = 0.0
	42	+ self._detail_con = None
	43	+
	44	+ # -- backends -------------------------------------------------------------
	45	+ def get(self, url: str, **kw) -> requests.Response:
	46	+ """GET direct avec throttling poli."""
	47	+ wait = self.request_delay - (time.time() - self._last_request)
	48	+ if wait > 0:
	49	+ time.sleep(wait)
	50	+ resp = self.session.get(url, timeout=self.timeout, **kw)
	51	+ self._last_request = time.time()
	52	+ resp.raise_for_status()
	53	+ return resp
	54	+
	55	+ def post(self, url: str, **kw) -> requests.Response:
	56	+ """POST direct avec throttling poli (APIs de recherche internes)."""
	57	+ wait = self.request_delay - (time.time() - self._last_request)
	58	+ if wait > 0:
	59	+ time.sleep(wait)
	60	+ resp = self.session.post(url, timeout=self.timeout, **kw)
	61	+ self._last_request = time.time()
	62	+ resp.raise_for_status()
	63	+ return resp
	64	+
	65	+ def get_rendered(self, url: str, wait_for: int = 0,
	66	+ proxy: str \| None = None) -> str:
	67	+ """Récupère le HTML rendu (JavaScript exécuté) via Firecrawl.
	68	+
	69	+ Nécessite FIRECRAWL_API_KEY dans l'environnement (.env).
	70	+ À utiliser pour les sites SPA ou derrière Cloudflare.
	71	+ `proxy="stealth"` franchit les challenges anti-bot (Cloudflare, etc.).
	72	+ """
	73	+ key = os.environ.get("FIRECRAWL_API_KEY")
	74	+ if not key:
	75	+ raise RuntimeError("FIRECRAWL_API_KEY manquant (voir .env)")
	76	+ payload: dict = {"url": url, "formats": ["html"], "timeout": 90000}
	77	+ if wait_for:
	78	+ payload["waitFor"] = wait_for
	79	+ if proxy:
	80	+ payload["proxy"] = proxy
	81	+ resp = requests.post(
	82	+ FIRECRAWL_API,
	83	+ json=payload,
	84	+ headers={"Authorization": f"Bearer {key}"},
	85	+ timeout=150,
	86	+ )
	87	+ resp.raise_for_status()
	88	+ data = resp.json()
	89	+ return (data.get("data") or {}).get("html", "")
	90	+
	91	+ def scrapfly(self, url: str, render_js: bool = True, asp: bool = True,
	92	+ rendering_wait: int = 0, country: str = "ca",
	93	+ wait_for_selector: str \| None = None,
	94	+ js_scenario: list \| str \| None = None,
	95	+ proxy_pool: str \| None = None, headers: dict \| None = None,
	96	+ method: str = "GET", body: str \| None = None) -> dict:
	97	+ """Appel Scrapfly complet — retourne le dict `result` (content, status_code…).
	98	+
	99	+ - `js_scenario` : liste d'étapes [{"scroll_y":…},{"wait":…}] (encodée base64)
	100	+ pour charger les listes virtualisées (BoldTrail/kvCORE, etc.).
	101	+ - `proxy_pool` : ex. "public_residential_pool" (WAF/anti-bot agressif).
	102	+ - `headers`/`method`/`body` : pour REJOUER une API JSON interne via ASP.
	103	+ """
	104	+ import base64
	105	+ key = os.environ.get("SCRAPFLY_KEY")
	106	+ if not key:
	107	+ raise RuntimeError("SCRAPFLY_KEY manquant (voir .env)")
	108	+ params: dict = {"key": key, "url": url, "country": country}
	109	+ if asp:
	110	+ params["asp"] = "true"
	111	+ if render_js:
	112	+ params["render_js"] = "true"
	113	+ if rendering_wait:
	114	+ params["rendering_wait"] = rendering_wait
	115	+ if wait_for_selector:
	116	+ params["wait_for_selector"] = wait_for_selector
	117	+ if proxy_pool:
	118	+ params["proxy_pool"] = proxy_pool
	119	+ if js_scenario is not None:
	120	+ js = js_scenario if isinstance(js_scenario, str) else json.dumps(js_scenario)
	121	+ params["js_scenario"] = base64.urlsafe_b64encode(js.encode()).decode()
	122	+ if headers:
	123	+ for k, v in headers.items():
	124	+ params[f"headers[{k}]"] = v
	125	+ wait = self.request_delay - (time.time() - self._last_request)
	126	+ if wait > 0:
	127	+ time.sleep(wait)
	128	+ if method.upper() == "POST":
	129	+ resp = requests.post(SCRAPFLY_API, params=params,
	130	+ data=(body or ""), timeout=180)
	131	+ else:
	132	+ resp = requests.get(SCRAPFLY_API, params=params, timeout=180)
	133	+ self._last_request = time.time()
	134	+ try:
	135	+ return resp.json().get("result") or {}
	136	+ except ValueError:
	137	+ return {}
	138	+
	139	+ def get_scrapfly(self, url: str, render_js: bool = True, asp: bool = True,
	140	+ rendering_wait: int = 0, country: str = "ca",
	141	+ wait_for_selector: str \| None = None,
	142	+ js_scenario: list \| str \| None = None,
	143	+ proxy_pool: str \| None = None) -> str:
	144	+ """HTML rendu via Scrapfly (ASP = bypass anti-bot + rendu JS). Retourne
	145	+ le HTML (result.content) ou "" en cas d'échec ASP."""
	146	+ return self.scrapfly(url, render_js=render_js, asp=asp,
	147	+ rendering_wait=rendering_wait, country=country,
	148	+ wait_for_selector=wait_for_selector,
	149	+ js_scenario=js_scenario, proxy_pool=proxy_pool
	150	+ ).get("content") or ""
	151	+
	152	+ def detail(self, external_id: str, key: str, fetch_fn) -> dict:
	153	+ """Payload « page détail » avec cache : `fetch_fn` n'est appelé que si
	154	+ la propriété est nouvelle ou si sa clé (hash du contenu liste) a changé.
	155	+
	156	+ Permet d'extraire les champs riches (description, courtier, photos…)
	157	+ sans revisiter chaque page détail à chaque synchronisation.
	158	+ `fetch_fn` doit retourner un dict JSON-sérialisable.
	159	+ """
	160	+ if not self.use_detail_cache:
	161	+ return fetch_fn() or {}
	162	+ from .. import db
	163	+ if self._detail_con is None:
	164	+ self._detail_con = db.connect()
	165	+ cached = db.get_cached_detail(self._detail_con, self.source_id,
	166	+ str(external_id), key)
	167	+ if cached is not None:
	168	+ return cached
	169	+ payload = fetch_fn() or {}
	170	+ db.put_cached_detail(self._detail_con, self.source_id,
	171	+ str(external_id), key, payload)
	172	+ return payload
	173	+
	174	+ # -- contrat --------------------------------------------------------------
	175	+ def fetch(self) -> list[PropertyListing]:
	176	+ raise NotImplementedError
	177	+
	178	+
	179	+# =============================================================================
	180	+# Résilience anti-bot (Groupe KA) — auto-escalade de get() sans toucher au corps.
	181	+# Ajouté par l'orchestrateur KA : enrobe BaseConnector.get pour qu'un blocage
	182	+# anti-bot (403/429/503/challenge) ou une coupure réseau déclenche la chaîne
	183	+# de secours (Oxylabs résidentiel -> Scrapfly ASP -> Bright Data). Voir
	184	+# connectors/_resilient.py. Idempotent (marqueur _KA_RESILIENT_WRAPPED).
	185	+# =============================================================================
	186	+if not getattr(BaseConnector, "_KA_RESILIENT_WRAPPED", False):
	187	+ import requests as _ka_requests # noqa: E402
	188	+ from . import _resilient as _kar # noqa: E402
	189	+
	190	+ _ka_orig_get = BaseConnector.get
	191	+
	192	+ def _ka_full_url(url, kw):
	193	+ try:
	194	+ return _ka_requests.Request("GET", url,
	195	+ params=kw.get("params")).prepare().url
	196	+ except Exception: # noqa: BLE001
	197	+ return url
	198	+
	199	+ def _ka_resilient_get(self, url, **kw):
	200	+ timeout = getattr(self, "timeout", 30)
	201	+ headers = kw.get("headers")
	202	+ try:
	203	+ return _ka_orig_get(self, url, **kw)
	204	+ except _ka_requests.HTTPError as exc:
	205	+ r = getattr(exc, "response", None)
	206	+ if r is not None and _kar.is_blocked(r):
	207	+ target = getattr(r, "url", None) or _ka_full_url(url, kw)
	208	+ better = _kar.escalate_if_blocked(
	209	+ r, target, timeout=timeout, headers=headers)
	210	+ if better is not None and getattr(better, "status_code", 0) == 200:
	211	+ return better
	212	+ raise
	213	+ except (_ka_requests.ConnectionError, _ka_requests.Timeout):
	214	+ better = _kar.escalate(_ka_full_url(url, kw),
	215	+ timeout=timeout, headers=headers)
	216	+ if better is not None and getattr(better, "status_code", 0) == 200:
	217	+ return better
	218	+ raise
	219	+
	220	+ def _ka_get_resilient(self, url, , render_js=False, country="ca", *kw):
	221	+ """Fetch anti-bot explicite : force la chaîne de secours au besoin.
	222	+
	223	+ Comme get() mais tente d'abord le direct puis escalade même sur 200-
	224	+ challenge, avec rendu JS optionnel. Renvoie une réponse compatible
	225	+ requests (.text/.content/.status_code/.json()...).
	226	+ """
	227	+ timeout = getattr(self, "timeout", 30)
	228	+ headers = kw.get("headers")
	229	+ try:
	230	+ resp = _ka_orig_get(self, url, **kw)
	231	+ except _ka_requests.HTTPError as exc:
	232	+ resp = getattr(exc, "response", None)
	233	+ except (_ka_requests.ConnectionError, _ka_requests.Timeout):
	234	+ resp = None
	235	+ target = _ka_full_url(url, kw)
	236	+ if resp is not None and getattr(resp, "url", None):
	237	+ target = resp.url
	238	+ return _kar.escalate_if_blocked(resp, target, timeout=timeout,
	239	+ country=country, render_js=render_js,
	240	+ headers=headers)
	241	+
	242	+ BaseConnector.get = _ka_resilient_get
	243	+ BaseConnector.get_resilient = _ka_get_resilient
	244	+ BaseConnector._KA_RESILIENT_WRAPPED = True

added immoka/connectors/jsonld.py +51 −0

		`@@ -0,0 +1,51 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# connectors/jsonld.py : utilitaires partagés d'extraction schema.org (JSON-LD)
	5	+# Beaucoup de sites d'agences (Sutton, et d'autres CMS immobiliers) publient
	6	+# la liste des propriétés en JSON-LD `ItemList` — données propres et stables.
	7	+# -----------------------------------------------------------------------------
	8	+from __future__ import annotations
	9	+
	10	+import json
	11	+import re
	12	+
	13	+_LD_RE = re.compile(r'<script[^>]+type="application/ld\+json"[^>]>(.?)</script>',
	14	+ re.S \| re.I)
	15	+
	16	+
	17	+def iter_ld(html: str):
	18	+ """Itère les objets JSON-LD d'une page (chaque bloc, aplati depuis @graph)."""
	19	+ for block in _LD_RE.findall(html):
	20	+ block = block.strip()
	21	+ if not block:
	22	+ continue
	23	+ try:
	24	+ data = json.loads(block)
	25	+ except ValueError:
	26	+ continue
	27	+ nodes = data.get("@graph", [data]) if isinstance(data, dict) else data
	28	+ for node in (nodes if isinstance(nodes, list) else [nodes]):
	29	+ if isinstance(node, dict):
	30	+ yield node
	31	+
	32	+
	33	+def item_list_elements(html: str) -> list[dict]:
	34	+ """Retourne les `itemListElement` (schema.org ItemList) trouvés dans la page."""
	35	+ out: list[dict] = []
	36	+ for node in iter_ld(html):
	37	+ elems = node.get("itemListElement")
	38	+ if isinstance(elems, list):
	39	+ out.extend(e for e in elems if isinstance(e, dict))
	40	+ # certaines pages imbriquent l'ItemList sous mainEntity
	41	+ me = node.get("mainEntity")
	42	+ if isinstance(me, dict) and isinstance(me.get("itemListElement"), list):
	43	+ out.extend(e for e in me["itemListElement"] if isinstance(e, dict))
	44	+ return out
	45	+
	46	+
	47	+def sqm_to_sqft(value) -> float \| None:
	48	+ try:
	49	+ return round(float(value) * 10.7639)
	50	+ except (TypeError, ValueError):
	51	+ return None

added immoka/connectors/realtypress.py +300 −0

		`@@ -0,0 +1,300 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (Québec + Ontario)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# connectors/realtypress.py : connecteur GÉNÉRIQUE RealtyPress (Ontario)
	5	+# RealtyPress = plugin WordPress branché sur le flux CREA DDF ; ~35 sites
	6	+# d'agences/équipes ontariennes confirmés (recensement 2026-08-27, voir
	7	+# docs/ontario-agences-connecteurs.md). Chaque site expose l'IDX/DDF complet
	8	+# de son board (OREB, ITSO, KAREA…) en HTML server-rendered, sans anti-bot :
	9	+# un seul parseur couvre quasi toute la province.
	10	+#
	11	+# - liste : archive /listing/page/N/?posts_per_page=100 (100 cartes/page ;
	12	+# ⚠ ?posts_per_page directement sur /listing = 301/vide) ; cartes
	13	+# class="rps-property-result" (ruban For sale/For rent, prix, adresse,
	14	+# ville, caractéristiques) ;
	15	+# - fiche : mur CREA « I Accept The Terms » contourné par le cookie
	16	+# `disclaimer=accepted` ; tableaux <strong>Label</strong>/valeur (MLS®
	17	+# Number, Property Type, Bedrooms…), description « … (id:NNNNN) »,
	18	+# lat/lng JSON-LD, photos ddfcdn.realtor.ca ;
	19	+# - external_id = ddf<id> (préfixe : jamais de collision avec les n° Centris
	20	+# QC) ; sources avec infixe _ag_ → la dédup par external_id masque les
	21	+# doublons inter-sites (le même bien DDF publié sur plusieurs sites).
	22	+# Sites générés depuis data/ontario_agencies.json (un source_id par site).
	23	+# -----------------------------------------------------------------------------
	24	+from __future__ import annotations
	25	+
	26	+import html as _html
	27	+import json
	28	+import os
	29	+import re
	30	+import urllib.parse
	31	+from pathlib import Path
	32	+
	33	+from .base import BaseConnector
	34	+from . import _detailutil as du
	35	+from ..schema import PropertyListing
	36	+
	37	+REGISTRY = Path(__file__).resolve().parent.parent.parent / "data" / "ontario_agencies.json"
	38	+DETAIL_LIMIT = int(os.environ.get("IMMOKA_RP_DETAIL_LIMIT",
	39	+ os.environ.get("IMMOKA_DETAIL_LIMIT", "150")))
	40	+
	41	+_CARD_RE = re.compile(r'<div class="rps-property-result">')
	42	+# fiche = 1er lien de la carte finissant par -<id DDF>/ ; le chemin varie selon
	43	+# le site (/listing/, /listings/, /all-regional-listings/…)
	44	+_LINK_RE = re.compile(r'href="(https?://[^"]+?-(\d{6,10})/?)"')
	45	+_RIBBON_RE = re.compile(r'rps-ribbon[^>]>\s([^<]+?)\s*<')
	46	+_PRICE_RE = re.compile(r'rps-price[^>]>\s\$\s*([\d,]+)')
	47	+_H4_RE = re.compile(r"<h4>\s(.?)\s*</h4>", re.S)
	48	+# avec ou sans <strong> selon le thème du site
	49	+_CITY_RE = re.compile(r'city-province-postalcode[^>]>\s(?:<strong>\s)?([^<]+?)\s<', re.S)
	50	+_FEAT_RE = re.compile(r'rps-result-feature-label[^>]>\s([^<]+?)\s*<')
	51	+_CARD_BROKER_RE = re.compile(r'text-muted[^>]>\s<small>\s([^<]+?)\s(?:<br\|</small>)', re.S)
	52	+_DDFIMG_RE = re.compile(r'https://ddfcdn\.realtor\.ca/[^")\'\s\\]+')
	53	+_ROW_RE = re.compile(r"<td[^>]>\s<strong>([^<]{2,45})</strong>\s</td>\s"
	54	+ r"<td[^>]>(.?)</td>", re.S)
	55	+_DESC_RE = re.compile(r'<!--\sDescription\s-->\s<p[^>]>(.*?)</p>', re.S)
	56	+_DESC_RE2 = re.compile(r'<p itemprop="description"[^>]>(.?)</p>', re.S)
	57	+# ville depuis <title> « 3383 Romeo Street, Greater Sudbury (Valley East), Ontario … »
	58	+_TITLE_CITY_RE = re.compile(r",\s([^,<>\|]{2,60}),\sOntario\b")
	59	+_PRICING_RE = re.compile(r'rps-pricing[^>]>\s\$\s*([\d,]+)')
	60	+_ID_TAIL_RE = re.compile(r"\s$id:\d{4,9}$\s$")
	61	+_TAG_RE = re.compile(r"<[^>]+>")
	62	+_NUM_RE = re.compile(r"[\d,]+(?:\.\d+)?")
	63	+_YEAR_RE = re.compile(r"\b(1[6-9]\d{2}\|20\d{2})\b")
	64	+# territoire couvert (Canada au complet) — même boîte que schema.finalize()
	65	+_BBOX = (41.6, 83.2, -141.1, -52.5)
	66	+
	67	+
	68	+def _num(s: str) -> float \| None:
	69	+ m = _NUM_RE.search(s or "")
	70	+ if not m:
	71	+ return None
	72	+ try:
	73	+ return float(m.group(0).replace(",", ""))
	74	+ except ValueError:
	75	+ return None
	76	+
	77	+
	78	+class _RealtyPress(BaseConnector):
	79	+ """Connecteur générique de site RealtyPress (voir data/ontario_agencies.json)."""
	80	+
	81	+ agency_name = ""
	82	+ site_url = ""
	83	+ archive = "listing" # chemin de l'archive (revelrealty: "listings",
	84	+ # codygroup: "all-regional-listings")
	85	+ max_pages = 150 # 100 cartes/page → jusqu'à 15 000 fiches par site
	86	+ request_delay = 0.6
	87	+
	88	+ def fetch(self) -> list[PropertyListing]:
	89	+ # mur CREA des fiches détail : le cookie suffit (posé pour tout domaine,
	90	+ # les redirections www/apex restent couvertes)
	91	+ self.session.cookies.set("disclaimer", "accepted")
	92	+ by_id: dict[str, PropertyListing] = {}
	93	+ base = self.site_url.rstrip("/")
	94	+ dry = 0
	95	+ for page in range(1, self.max_pages + 1):
	96	+ url = f"{base}/{self.archive}/page/{page}/?posts_per_page=100"
	97	+ try:
	98	+ body = self.get(url).text
	99	+ except Exception:
	100	+ break
	101	+ cards = self._cards(body)
	102	+ if not cards:
	103	+ break
	104	+ before = len(by_id)
	105	+ for card in cards:
	106	+ self._parse_card(card, by_id)
	107	+ dry = dry + 1 if len(by_id) == before else 0
	108	+ if dry >= 2:
	109	+ break
	110	+ listings = list(by_id.values())
	111	+ du.enrich(self, listings, DETAIL_LIMIT, parse_rp_detail, key="v1")
	112	+ for lst in listings:
	113	+ # n° MLS du board (fiche détail) — utile à la dédup inter-plateformes
	114	+ if not lst.mls and lst.details.get("MLS® Number"):
	115	+ lst.mls = str(lst.details["MLS® Number"])
	116	+ if not lst.title:
	117	+ lst.title = ", ".join(filter(None, (lst.address, lst.city))) \
	118	+ or "Propriété à vendre"
	119	+ return listings
	120	+
	121	+ def _cards(self, body: str) -> list[str]:
	122	+ marks = list(_CARD_RE.finditer(body))
	123	+ return [body[m.start():(marks[i + 1].start() if i + 1 < len(marks)
	124	+ else m.start() + 6000)]
	125	+ for i, m in enumerate(marks)]
	126	+
	127	+ def _parse_card(self, card: str, by_id: dict) -> None:
	128	+ ml = _LINK_RE.search(card)
	129	+ if not ml:
	130	+ return
	131	+ url, ddf = ml.group(1), ml.group(2)
	132	+ eid = f"ddf{ddf}"
	133	+ if eid in by_id:
	134	+ return
	135	+ mr = _RIBBON_RE.search(card)
	136	+ ribbon = (mr.group(1) if mr else "").strip().lower()
	137	+ if "rent" in ribbon or "lease" in ribbon:
	138	+ return # locations : hors périmètre
	139	+ lst = PropertyListing(source=self.source_id, external_id=eid, url=url,
	140	+ region="Ontario", agency=self.agency_name,
	141	+ broker_name=self.agency_name)
	142	+ ma = _H4_RE.search(card)
	143	+ if ma:
	144	+ lst.address = _html.unescape(_TAG_RE.sub(" ", ma.group(1))).strip()
	145	+ mc = _CITY_RE.search(card)
	146	+ if mc:
	147	+ city = _html.unescape(mc.group(1)).strip().rstrip(",")
	148	+ city = re.sub(r",?\sOntario\b.$", "", city, flags=re.I)
	149	+ lst.city = city.split("(")[0].strip()
	150	+ mp = _PRICE_RE.search(card)
	151	+ if mp:
	152	+ lst.price = _num(mp.group(1))
	153	+ lst.price_label = f"{mp.group(1)} $"
	154	+ for feat in _FEAT_RE.findall(card):
	155	+ f = _html.unescape(feat).strip()
	156	+ low = f.lower()
	157	+ n = _num(f)
	158	+ if not n:
	159	+ continue
	160	+ if "bedroom" in low:
	161	+ lst.bedrooms = int(n)
	162	+ elif "bathroom" in low:
	163	+ lst.bathrooms = int(n)
	164	+ elif "sqft" in low or "sq ft" in low or "ft" in low:
	165	+ lst.area_sqft = n # plage « 1,100 - 1,500 ft² » : borne basse
	166	+ mbk = _CARD_BROKER_RE.search(card)
	167	+ if mbk:
	168	+ lst.broker_name = _html.unescape(mbk.group(1)).strip()[:120]
	169	+ mi = _DDFIMG_RE.search(card)
	170	+ if mi:
	171	+ lst.images = [mi.group(0)]
	172	+ by_id[lst.external_id] = lst
	173	+
	174	+
	175	+def parse_rp_detail(html: str) -> dict:
	176	+ """Fiche RealtyPress : tableaux DDF, description, GPS, galerie, courtier."""
	177	+ out: dict = {}
	178	+ details: dict = {}
	179	+
	180	+ for lab, val in _ROW_RE.findall(html):
	181	+ label = _html.unescape(lab).strip().rstrip(":")
	182	+ value = re.sub(r"\s+", " ", _html.unescape(_TAG_RE.sub(" ", val))).strip()
	183	+ if label and value and len(value) <= 300:
	184	+ details.setdefault(label, value)
	185	+
	186	+ def dv(*labels: str) -> str:
	187	+ for lb in labels:
	188	+ if details.get(lb):
	189	+ return details[lb]
	190	+ return ""
	191	+
	192	+ b = _num(dv("Bedrooms Total", "Bedrooms", "Bedrooms Above Ground"))
	193	+ if b is not None and 0 < b <= 30:
	194	+ out["bedrooms"] = int(b)
	195	+ b = _num(dv("Bathroom Total", "Bathrooms"))
	196	+ if b is not None and 0 < b <= 30:
	197	+ out["bathrooms"] = int(b)
	198	+ b = _num(dv("Half Bath Total"))
	199	+ if b is not None and 0 < b <= 10:
	200	+ out["powder_rooms"] = int(b)
	201	+ my = _YEAR_RE.search(dv("Constructed Date", "Construction Year", "Age"))
	202	+ if my:
	203	+ out["year_built"] = int(my.group(1))
	204	+ si = dv("Size Interior")
	205	+ if si and "sqft" in si.lower().replace(" ", ""):
	206	+ a = _num(si) # « 7,901 Sqft » / « 1200 - 1399 sqft »
	207	+ if a and a >= 100:
	208	+ out["area_sqft"] = a
	209	+ pt = dv("Property Type", "Building Type", "Type")
	210	+ if pt:
	211	+ out["property_type"] = pt # anglais DDF — normalisé par finalize()
	212	+ sec = dv("Neigbourhood", "Neighbourhood", "Community Name")
	213	+ if sec:
	214	+ out["sector"] = sec
	215	+
	216	+ mp = _PRICING_RE.search(html)
	217	+ if mp:
	218	+ out["price"] = _num(mp.group(1))
	219	+ out["price_label"] = f"{mp.group(1)} $"
	220	+
	221	+ md = _DESC_RE.search(html) or _DESC_RE2.search(html)
	222	+ if md:
	223	+ desc = _html.unescape(_TAG_RE.sub(" ", md.group(1)))
	224	+ desc = re.sub(r"\s+", " ", desc).strip()
	225	+ out["description"] = _ID_TAIL_RE.sub("", desc)[:6000]
	226	+
	227	+ mt = re.search(r"<title>(.*?)</title>", html, re.S)
	228	+ if mt:
	229	+ mc = _TITLE_CITY_RE.search(_html.unescape(mt.group(1)))
	230	+ if mc:
	231	+ # « Greater Sudbury (Valley East) » : le secteur part dans sector
	232	+ city = mc.group(1).split("(")[0].strip()
	233	+ if city and not any(c.isdigit() for c in city):
	234	+ out["city"] = city
	235	+ msec = re.search(r"$([^)]{2,45})$", mc.group(1))
	236	+ if msec and "sector" not in out:
	237	+ out["sector"] = msec.group(1).strip()
	238	+
	239	+ for n in du.ld_nodes(html):
	240	+ t = n.get("@type")
	241	+ types = set(t if isinstance(t, list) else [t])
	242	+ geo = n.get("geo") or {}
	243	+ if isinstance(geo, dict) and "lat" not in out:
	244	+ try:
	245	+ lat, lng = float(geo["latitude"]), float(geo["longitude"])
	246	+ if _BBOX[0] <= lat <= _BBOX[1] and _BBOX[2] <= lng <= _BBOX[3]:
	247	+ out["lat"], out["lng"] = lat, lng
	248	+ except (KeyError, TypeError, ValueError):
	249	+ pass
	250	+ if types & {"RealEstateAgent", "Organization"}:
	251	+ name = str(n.get("name") or "").strip()
	252	+ if name and "broker_name" not in out:
	253	+ out["broker_name"] = name[:120]
	254	+ tel = str(n.get("telephone") or "").strip()
	255	+ if tel and "broker_phone" not in out:
	256	+ out["broker_phone"] = tel[:40]
	257	+ if "lat" not in out:
	258	+ m = re.search(r'"latitude"\s:\s"?(-?\d{1,2}\.\d{3,})"?\s,\s'
	259	+ r'"longitude"\s:\s"?(-?\d{2,3}\.\d{3,})"?', html)
	260	+ if m:
	261	+ lat, lng = float(m.group(1)), float(m.group(2))
	262	+ if _BBOX[0] <= lat <= _BBOX[1] and _BBOX[2] <= lng <= _BBOX[3]:
	263	+ out["lat"], out["lng"] = lat, lng
	264	+
	265	+ gal = [u for u in dict.fromkeys(_DDFIMG_RE.findall(html))
	266	+ if "/listings/" in u.lower()]
	267	+ if gal:
	268	+ out["images"] = gal[:60]
	269	+
	270	+ if details:
	271	+ out["details"] = details
	272	+ return out
	273	+
	274	+
	275	+def _load() -> list[dict]:
	276	+ try:
	277	+ return json.loads(REGISTRY.read_text(encoding="utf-8"))
	278	+ except Exception:
	279	+ return []
	280	+
	281	+
	282	+# House-Ka : les connecteurs RealtyPress sont le cœur du site — toujours
	283	+# enregistrés (pas de gate IMMOKA_ONTARIO, contrairement à Immo-Ka).
	284	+
	285	+# Génère une classe par site du registre.
	286	+for _ag in _load():
	287	+ if not all(_ag.get(k) for k in ("id", "site")):
	288	+ continue
	289	+ _sid = _ag["id"]
	290	+ globals()[f"REALTYPRESS_{_sid.upper()}"] = type(
	291	+ "RealtyPress" + "".join(p.title() for p in _sid.split("_")),
	292	+ (_RealtyPress,),
	293	+ {
	294	+ "source_id": _sid,
	295	+ "site_url": _ag["site"],
	296	+ "agency_name": _ag.get("name", _sid),
	297	+ "archive": _ag.get("archive", "listing"),
	298	+ "max_pages": int(_ag.get("max_pages", 150)),
	299	+ },
	300	+ )

added immoka/db.py +575 −0

		`@@ -0,0 +1,575 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# db.py : persistance SQLite — upsert avec détection de changements,
	5	+# cycle de vie avec délai de grâce (2 syncs), détection de dérive,
	6	+# historique de prix, cache des pages détail.
	7	+# -----------------------------------------------------------------------------
	8	+from __future__ import annotations
	9	+
	10	+import json
	11	+import sqlite3
	12	+import statistics
	13	+import time
	14	+from pathlib import Path
	15	+
	16	+from .schema import PropertyListing
	17	+
	18	+DB_PATH = Path(__file__).resolve().parent.parent / "data" / "immoka.db"
	19	+
	20	+# Nombre d'exécutions consécutives où une propriété doit être absente de la
	21	+# source avant d'être désactivée (délai de grâce contre les ratés ponctuels).
	22	+MISS_GRACE = 2
	23	+
	24	+# Dérive : si une source retourne <= DRIFT_RATIO × sa médiane historique
	25	+# (médiane >= DRIFT_MIN_BASE annonces), on alerte et on suspend les retraits.
	26	+DRIFT_RATIO = 0.25
	27	+DRIFT_MIN_BASE = 8
	28	+DRIFT_HISTORY = 5
	29	+
	30	+_SCHEMA = """
	31	+CREATE TABLE IF NOT EXISTS listings (
	32	+ uid TEXT PRIMARY KEY,
	33	+ source TEXT NOT NULL,
	34	+ external_id TEXT NOT NULL,
	35	+ url TEXT,
	36	+ title TEXT,
	37	+ address TEXT,
	38	+ sector TEXT,
	39	+ city TEXT,
	40	+ region TEXT,
	41	+ property_type TEXT,
	42	+ price REAL,
	43	+ price_label TEXT,
	44	+ bedrooms INTEGER,
	45	+ bathrooms INTEGER,
	46	+ powder_rooms INTEGER,
	47	+ area_sqft REAL,
	48	+ lot_sqft REAL,
	49	+ year_built INTEGER,
	50	+ mls TEXT,
	51	+ status TEXT DEFAULT 'a-vendre',
	52	+ broker_name TEXT,
	53	+ broker_phone TEXT,
	54	+ agency TEXT,
	55	+ description TEXT,
	56	+ features TEXT, -- JSON (liste de textes source)
	57	+ details TEXT, -- JSON (champs structurés)
	58	+ images TEXT, -- JSON
	59	+ lat REAL,
	60	+ lng REAL,
	61	+ geocode_failed INTEGER DEFAULT 0,
	62	+ content_hash TEXT,
	63	+ first_seen REAL,
	64	+ last_seen REAL,
	65	+ updated_at REAL,
	66	+ miss_count INTEGER DEFAULT 0,
	67	+ active INTEGER DEFAULT 1,
	68	+ dup_hidden INTEGER DEFAULT 0 -- 1 = doublon de sous-agence masqué (dédup Centris)
	69	+);
	70	+CREATE INDEX IF NOT EXISTS idx_listings_source ON listings(source);
	71	+CREATE INDEX IF NOT EXISTS idx_listings_city ON listings(city);
	72	+CREATE INDEX IF NOT EXISTS idx_listings_type ON listings(property_type);
	73	+CREATE INDEX IF NOT EXISTS idx_listings_active ON listings(active);
	74	+CREATE INDEX IF NOT EXISTS idx_listings_extid ON listings(external_id);
	75	+
	76	+CREATE TABLE IF NOT EXISTS sync_log (
	77	+ id INTEGER PRIMARY KEY AUTOINCREMENT,
	78	+ source TEXT,
	79	+ ts REAL,
	80	+ found INTEGER,
	81	+ added INTEGER,
	82	+ updated INTEGER,
	83	+ removed INTEGER,
	84	+ ok INTEGER,
	85	+ message TEXT,
	86	+ stats TEXT -- JSON : taux de champs null, missed, alerte…
	87	+);
	88	+
	89	+CREATE TABLE IF NOT EXISTS detail_cache (
	90	+ source TEXT NOT NULL,
	91	+ external_id TEXT NOT NULL,
	92	+ key TEXT, -- hash du contenu « liste » de l'annonce
	93	+ payload TEXT, -- JSON opaque propre au connecteur
	94	+ fetched_at REAL,
	95	+ PRIMARY KEY (source, external_id)
	96	+);
	97	+
	98	+CREATE TABLE IF NOT EXISTS price_log (
	99	+ uid TEXT NOT NULL,
	100	+ ts REAL NOT NULL,
	101	+ price REAL -- prix observé (baisses/hausses de prix demandé)
	102	+);
	103	+CREATE INDEX IF NOT EXISTS idx_price_log_uid ON price_log(uid);
	104	+
	105	+CREATE TABLE IF NOT EXISTS geocode_cache (
	106	+ address TEXT PRIMARY KEY,
	107	+ lat REAL,
	108	+ lng REAL,
	109	+ provider TEXT,
	110	+ failed INTEGER DEFAULT 0,
	111	+ ts REAL,
	112	+ muni TEXT -- municipalité officielle (clés « ville:… »)
	113	+);
	114	+
	115	+CREATE TABLE IF NOT EXISTS poi_cache (
	116	+ coord_key TEXT PRIMARY KEY, -- "lat,lng" arrondi à 4 décimales (~11 m)
	117	+ lat REAL,
	118	+ lng REAL,
	119	+ pois TEXT, -- JSON : [{cat, name, dist_m}] (plus proche/catégorie)
	120	+ ts REAL
	121	+);
	122	+"""
	123	+
	124	+
	125	+_SCHEMA_READY = False # le schéma/migration ne s'exécute qu'UNE fois par process
	126	+
	127	+
	128	+def _init_schema(con: sqlite3.Connection) -> None:
	129	+ """Création de schéma + migration — coûteuse (write-lock). À faire une seule
	130	+ fois par process : l'exécuter à chaque connexion sérialisait les requêtes du
	131	+ web sur un verrou d'écriture (deadlock/starvation sous charge)."""
	132	+ con.executescript(_SCHEMA)
	133	+ cols = {r["name"] for r in con.execute("PRAGMA table_info(listings)")}
	134	+ if "agency" not in cols:
	135	+ con.execute("ALTER TABLE listings ADD COLUMN agency TEXT")
	136	+ if "dup_hidden" not in cols:
	137	+ con.execute("ALTER TABLE listings ADD COLUMN dup_hidden INTEGER DEFAULT 0")
	138	+ if "dup_of" not in cols: # uid de la fiche visible au profit de laquelle
	139	+ con.execute("ALTER TABLE listings ADD COLUMN dup_of TEXT") # celle-ci est masquée
	140	+ if "dauid" not in cols: # aire de diffusion 2021 (stats de quartier)
	141	+ con.execute("ALTER TABLE listings ADD COLUMN dauid TEXT")
	142	+ if "vraiprix" not in cols: # estimation Vrai-Prix (JSON) + lien analyse
	143	+ con.execute("ALTER TABLE listings ADD COLUMN vraiprix TEXT")
	144	+ gcols = {r["name"] for r in con.execute("PRAGMA table_info(geocode_cache)")}
	145	+ if "muni" not in gcols: # municipalité officielle (entrées « ville:… »)
	146	+ con.execute("ALTER TABLE geocode_cache ADD COLUMN muni TEXT")
	147	+ con.execute("CREATE INDEX IF NOT EXISTS idx_listings_duphidden ON listings(dup_hidden)")
	148	+ con.execute("CREATE INDEX IF NOT EXISTS idx_listings_dupof ON listings(dup_of)")
	149	+ con.execute("CREATE INDEX IF NOT EXISTS idx_listings_geo ON listings(lat, lng)")
	150	+ con.commit()
	151	+
	152	+
	153	+def refresh_dedup(con: sqlite3.Connection) -> int:
	154	+ """Pré-calcule la déduplication de la famille sous-agences (`_ag_`) dans la
	155	+ colonne `dup_hidden`, pour que la lecture soit instantanée (« AND dup_hidden=0 »)
	156	+ au lieu d'un sous-select corrélé par ligne (300 s sur 75 k lignes).
	157	+
	158	+ Règle (identique à l'ancienne clause) : une fiche de sous-agence est masquée
	159	+ si une fiche de plus haute priorité — même n° Centris (external_id), active —
	160	+ existe : le flux central/agence principale d'abord, sinon la sous-agence au
	161	+ plus petit uid. Les fiches non sous-agence ne sont jamais masquées par
	162	+ cette règle. Une 3e passe (dedup_by_address) masque ensuite les doublons
	163	+ INTER-SOURCES sans n° Centris commun (même adresse + type + prix ±1 %).
	164	+ Retourne le nombre total de fiches masquées."""
	165	+ AG = "source LIKE '%\\_ag\\_%' ESCAPE '\\'"
	166	+ NOTAG = "source NOT LIKE '%\\_ag\\_%' ESCAPE '\\'"
	167	+ con.execute("UPDATE listings SET dup_hidden=0, dup_of=NULL")
	168	+ # 1) masquer les sous-agences dont le n° Centris est porté par une fiche
	169	+ # canonique (non sous-agence) active — semi-jointure, rapide.
	170	+ # dup_of = la fiche canonique (pour la box « Aussi publiée sur… »).
	171	+ con.execute(
	172	+ f"UPDATE listings SET dup_hidden=1,"
	173	+ f" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1"
	174	+ f" AND d.external_id=listings.external_id AND d.{NOTAG})"
	175	+ f" WHERE active=1 AND {AG}"
	176	+ f" AND external_id IN (SELECT external_id FROM listings"
	177	+ f" WHERE active=1 AND {NOTAG})")
	178	+ # 2) parmi les sous-agences restantes (sans canonique), ne garder que le plus
	179	+ # petit uid par n° Centris.
	180	+ con.execute(
	181	+ f"UPDATE listings SET dup_hidden=1,"
	182	+ f" dup_of=(SELECT MIN(d.uid) FROM listings d WHERE d.active=1"
	183	+ f" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)"
	184	+ f" WHERE active=1 AND {AG} AND dup_hidden=0"
	185	+ f" AND uid > (SELECT MIN(d.uid) FROM listings d WHERE d.active=1"
	186	+ f" AND d.external_id=listings.external_id AND d.{AG} AND d.dup_hidden=0)")
	187	+ # 3) dédup INTER-SOURCES par adresse : la même propriété publiée sur deux
	188	+ # plateformes (ex. courtier + Kijiji) sans n° Centris commun. Règle
	189	+ # conservatrice : même adresse normalisée (civique + rue + ville) + même
	190	+ # type + prix identique à ±1 % → on garde la fiche la plus autoritaire.
	191	+ try:
	192	+ n_addr = dedup_by_address(con)
	193	+ if n_addr:
	194	+ print(f"[immo-ka] dédup adresse: {n_addr} doublon(s) inter-sources masqué(s)")
	195	+ except Exception:
	196	+ import traceback
	197	+ traceback.print_exc()
	198	+ n = con.execute("SELECT COUNT(*) c FROM listings WHERE dup_hidden=1").fetchone()["c"]
	199	+ con.commit()
	200	+ return n
	201	+
	202	+
	203	+# petites annonces généralistes (republication d'annonces d'ailleurs) : moins
	204	+# autoritaires que la source primaire (courtier / FSBO première main).
	205	+# fb_marketplace : fiches anonymes/republication — jamais préférées à un courtier.
	206	+_PETITES_ANNONCES = {"kijiji", "lespac", "fb_marketplace"}
	207	+
	208	+
	209	+def _source_rank(source: str) -> int:
	210	+ """Autorité d'une source pour la dédup d'adresse :
	211	+ 0 = source primaire (bannière/agence/FSBO), 1 = sous-agence (_ag_),
	212	+ 2 = petites annonces (republication probable)."""
	213	+ if source in _PETITES_ANNONCES:
	214	+ return 2
	215	+ if "_ag_" in source:
	216	+ return 1
	217	+ return 0
	218	+
	219	+
	220	+def dedup_by_address(con: sqlite3.Connection) -> int:
	221	+ """Passe de déduplication conservatrice par ADRESSE (inter-sources).
	222	+
	223	+ Clé : n° civique(s) + mots significatifs de la rue + ville normalisée +
	224	+ type canonique + n° d'app/unité (vide s'il n'y en a pas — deux unités
	225	+ différentes d'un même immeuble ne partagent JAMAIS la même clé, et une
	226	+ adresse sans unité ne s'apparie pas à une adresse avec unité). Dans une
	227	+ clé, seules les fiches au prix identique à ±1 % sont considérées comme
	228	+ doublons ; si une même source apparaît deux fois dans le groupe (probables
	229	+ unités jumelles d'un projet neuf), le groupe ENTIER est ignoré. On garde
	230	+ la fiche la plus autoritaire (source primaire > sous-agence _ag_ >
	231	+ petites annonces), puis à autorité égale celle qui a un COURTIER/agence
	232	+ (jamais une fiche anonyme devant un courtier), puis le plus petit uid.
	233	+ Retourne le nb masqué."""
	234	+ import re as _re
	235	+ from .vraiprix_local import _addr_parts, _norm, _muni_norm, _APP_RE
	236	+ groups: dict[tuple, list] = {}
	237	+ for r in con.execute(
	238	+ "SELECT uid, source, address, city, price, property_type,"
	239	+ " broker_name, agency"
	240	+ " FROM listings WHERE active=1 AND dup_hidden=0 AND address<>''"
	241	+ " AND city<>'' AND price IS NOT NULL AND property_type<>''"):
	242	+ civs, words = _addr_parts(r["address"])
	243	+ if not civs or not words:
	244	+ continue
	245	+ a = _norm(r["address"]).split(",")[0]
	246	+ mapt = _re.search(_APP_RE, a)
	247	+ apt = ""
	248	+ if mapt:
	249	+ toks = _re.findall(r"[a-z0-9]+", mapt.group(0))
	250	+ # dernier token = le n° d'unité (le 1er est le mot-clé app/unité/#)
	251	+ apt = toks[-1] if toks else ""
	252	+ key = ("-".join(civs), " ".join(sorted(set(words))),
	253	+ _muni_norm(r["city"]), _norm(r["property_type"]), apt)
	254	+ anonyme = 0 if (r["broker_name"] or r["agency"]) else 1
	255	+ groups.setdefault(key, []).append(
	256	+ (r["price"], _source_rank(r["source"]), anonyme, r["uid"], r["source"]))
	257	+ hidden = 0
	258	+ for rows in groups.values():
	259	+ if len(rows) < 2:
	260	+ continue
	261	+ rows.sort() # par prix croissant
	262	+ cluster: list = []
	263	+ for row in rows:
	264	+ if cluster and row[0] > cluster[0][0] * 1.01:
	265	+ hidden += _mask_cluster(con, cluster)
	266	+ cluster = []
	267	+ cluster.append(row)
	268	+ hidden += _mask_cluster(con, cluster)
	269	+ return hidden
	270	+
	271	+
	272	+def _mask_cluster(con: sqlite3.Connection, cluster: list) -> int:
	273	+ """Masque les doublons d'un groupe (même clé d'adresse, prix ±1 %), puis
	274	+ FUSIONNE en « golden record » : les champs vides de la fiche conservée sont
	275	+ complétés depuis les doublons masqués (description plus longue, galerie plus
	276	+ riche, superficies, année, GPS, téléphone) — le meilleur des deux sources."""
	277	+ if len(cluster) < 2:
	278	+ return 0
	279	+ sources = [c[4] for c in cluster]
	280	+ if len(set(sources)) != len(sources):
	281	+ return 0 # même source en double = probables unités distinctes : prudence
	282	+ keep = min(cluster, key=lambda c: (c[1], c[2], c[3])) # (autorité, anonyme, uid)
	283	+ n = 0
	284	+ donors = []
	285	+ for c in cluster:
	286	+ if c[3] != keep[3]:
	287	+ con.execute("UPDATE listings SET dup_hidden=1, dup_of=? WHERE uid=?",
	288	+ (keep[3], c[3]))
	289	+ donors.append(c[3])
	290	+ n += 1
	291	+ try:
	292	+ _merge_golden(con, keep[3], donors)
	293	+ except Exception:
	294	+ pass # la fusion est un bonus — ne jamais casser la dédup
	295	+ return n
	296	+
	297	+
	298	+_MERGE_NUM_FIELDS = ("bedrooms", "bathrooms", "powder_rooms", "area_sqft",
	299	+ "lot_sqft", "year_built")
	300	+
	301	+
	302	+def _merge_golden(con: sqlite3.Connection, keep_uid: str, donor_uids: list[str]) -> None:
	303	+ """Complète les champs vides de `keep_uid` depuis ses doublons masqués."""
	304	+ if not donor_uids:
	305	+ return
	306	+ cols = ("uid, description, images, bedrooms, bathrooms, powder_rooms,"
	307	+ " area_sqft, lot_sqft, year_built, lat, lng, broker_phone")
	308	+ keep = con.execute(f"SELECT {cols} FROM listings WHERE uid=?",
	309	+ (keep_uid,)).fetchone()
	310	+ if keep is None:
	311	+ return
	312	+ sets, args = [], []
	313	+ kimgs = len(json.loads(keep["images"] or "[]"))
	314	+ kdesc = len(keep["description"] or "")
	315	+ best_imgs, best_desc = None, None
	316	+ donor_rows = con.execute(
	317	+ f"SELECT {cols} FROM listings WHERE uid IN "
	318	+ f"({','.join('?' * len(donor_uids))})", donor_uids).fetchall()
	319	+ merged_num: dict = {}
	320	+ for d in donor_rows:
	321	+ di = json.loads(d["images"] or "[]")
	322	+ if len(di) > max(kimgs, len(json.loads(best_imgs or "[]"))):
	323	+ best_imgs = d["images"]
	324	+ dd = d["description"] or ""
	325	+ if len(dd) > max(kdesc, 80, len(best_desc or "")):
	326	+ best_desc = dd
	327	+ for f in _MERGE_NUM_FIELDS:
	328	+ if keep[f] is None and merged_num.get(f) is None and d[f] is not None:
	329	+ merged_num[f] = d[f]
	330	+ # GPS : toujours la PAIRE du même donneur (jamais lat et lng mélangés)
	331	+ if (keep["lat"] is None and "lat" not in merged_num
	332	+ and d["lat"] is not None and d["lng"] is not None):
	333	+ merged_num["lat"], merged_num["lng"] = d["lat"], d["lng"]
	334	+ if not keep["broker_phone"] and d["broker_phone"] and "broker_phone" not in merged_num:
	335	+ merged_num["broker_phone"] = d["broker_phone"]
	336	+ if best_imgs is not None:
	337	+ sets.append("images=?"); args.append(best_imgs)
	338	+ if best_desc is not None and kdesc < 80:
	339	+ sets.append("description=?"); args.append(best_desc)
	340	+ for f, v in merged_num.items():
	341	+ sets.append(f"{f}=?"); args.append(v)
	342	+ if sets:
	343	+ args.append(keep_uid)
	344	+ con.execute(f"UPDATE listings SET {', '.join(sets)} WHERE uid=?", args)
	345	+
	346	+
	347	+def connect() -> sqlite3.Connection:
	348	+ global _SCHEMA_READY
	349	+ DB_PATH.parent.mkdir(parents=True, exist_ok=True)
	350	+ con = sqlite3.connect(DB_PATH, timeout=60)
	351	+ con.row_factory = sqlite3.Row
	352	+ # WAL + busy_timeout : accès concurrents (watcher + web) sans « db is locked ».
	353	+ con.execute("PRAGMA journal_mode=WAL")
	354	+ # 120 s : couvre les longues transactions (refresh_dedup ~70 s) sans que les
	355	+ # autres écrivains (géocodage, vraiprix) ne lèvent « database is locked ».
	356	+ con.execute("PRAGMA busy_timeout=120000")
	357	+ con.execute("PRAGMA synchronous=NORMAL")
	358	+ if not _SCHEMA_READY:
	359	+ _init_schema(con)
	360	+ _SCHEMA_READY = True
	361	+ return con
	362	+
	363	+
	364	+# ---------------------------------------------------------------------------
	365	+# Synchronisation d'une source
	366	+# ---------------------------------------------------------------------------
	367	+
	368	+def _drift_alert(con: sqlite3.Connection, source: str, found: int,
	369	+ null_price_rate: float) -> str \| None:
	370	+ """Détecte une dérive du connecteur (chute du volume ou des prix extraits)."""
	371	+ hist = con.execute(
	372	+ "SELECT found, stats FROM sync_log WHERE source=? AND ok=1"
	373	+ " ORDER BY ts DESC LIMIT ?", (source, DRIFT_HISTORY)).fetchall()
	374	+ if len(hist) < 3:
	375	+ return None
	376	+ med_found = statistics.median(r["found"] for r in hist)
	377	+ if med_found >= DRIFT_MIN_BASE and found <= DRIFT_RATIO * med_found:
	378	+ return (f"dérive: {found} propriété(s) trouvée(s) contre une médiane de "
	379	+ f"{med_found:.0f} — retraits suspendus, vérifier le connecteur")
	380	+ if found >= DRIFT_MIN_BASE and null_price_rate >= 0.8:
	381	+ rates = []
	382	+ for r in hist:
	383	+ try:
	384	+ rates.append(json.loads(r["stats"] or "{}")["null_price_rate"])
	385	+ except (KeyError, ValueError, TypeError):
	386	+ continue
	387	+ if rates and statistics.median(rates) <= 0.3:
	388	+ return (f"dérive: {null_price_rate:.0%} des propriétés sans prix "
	389	+ f"(habituellement {statistics.median(rates):.0%}) — "
	390	+ "le format de la source a probablement changé")
	391	+ return None
	392	+
	393	+
	394	+def sync_source(con: sqlite3.Connection, source: str,
	395	+ listings: list[PropertyListing]) -> dict:
	396	+ """Synchronise les propriétés d'une source.
	397	+
	398	+ - nouvelle propriété -> insertion
	399	+ - propriété modifiée -> mise à jour (comparaison de content_hash)
	400	+ - propriété disparue -> miss_count += 1, puis active=0 après MISS_GRACE
	401	+ exécutions consécutives (vendue ou retirée)
	402	+ - dérive détectée -> alerte consignée, retraits suspendus
	403	+ """
	404	+ now = time.time()
	405	+ added = updated = 0
	406	+ seen_uids = set()
	407	+
	408	+ n = len(listings)
	409	+ null_price = sum(1 for l in listings if l.price is None)
	410	+ null_addr = sum(1 for l in listings if not l.address)
	411	+ null_price_rate = round(null_price / n, 3) if n else 0.0
	412	+
	413	+ alert = _drift_alert(con, source, n, null_price_rate)
	414	+
	415	+ for lst in listings:
	416	+ seen_uids.add(lst.uid)
	417	+ h = lst.content_hash()
	418	+ row = con.execute("SELECT content_hash, price FROM listings WHERE uid=?",
	419	+ (lst.uid,)).fetchone()
	420	+ params = dict(
	421	+ uid=lst.uid, source=lst.source, external_id=lst.external_id,
	422	+ url=lst.url, title=lst.title, address=lst.address,
	423	+ sector=lst.sector, city=lst.city, region=lst.region,
	424	+ property_type=lst.property_type, price=lst.price,
	425	+ price_label=lst.price_label, bedrooms=lst.bedrooms,
	426	+ bathrooms=lst.bathrooms, powder_rooms=lst.powder_rooms,
	427	+ area_sqft=lst.area_sqft, lot_sqft=lst.lot_sqft,
	428	+ year_built=lst.year_built, mls=lst.mls, status=lst.status,
	429	+ broker_name=lst.broker_name, broker_phone=lst.broker_phone,
	430	+ agency=lst.agency,
	431	+ description=lst.description,
	432	+ features=json.dumps(lst.features, ensure_ascii=False),
	433	+ details=json.dumps(lst.details, ensure_ascii=False),
	434	+ images=json.dumps(lst.images, ensure_ascii=False),
	435	+ lat=lst.lat, lng=lst.lng, content_hash=h, now=now,
	436	+ )
	437	+ if row is None:
	438	+ con.execute(
	439	+ """INSERT INTO listings (uid, source, external_id, url, title,
	440	+ address, sector, city, region, property_type, price,
	441	+ price_label, bedrooms, bathrooms, powder_rooms, area_sqft,
	442	+ lot_sqft, year_built, mls, status, broker_name, broker_phone,
	443	+ agency, description, features, details, images, lat, lng,
	444	+ content_hash, first_seen, last_seen, updated_at,
	445	+ miss_count, active)
	446	+ VALUES (:uid,:source,:external_id,:url,:title,:address,
	447	+ :sector,:city,:region,:property_type,:price,:price_label,
	448	+ :bedrooms,:bathrooms,:powder_rooms,:area_sqft,:lot_sqft,
	449	+ :year_built,:mls,:status,:broker_name,:broker_phone,
	450	+ :agency,:description,:features,:details,:images,:lat,:lng,
	451	+ :content_hash,:now,:now,:now,0,1)""", params)
	452	+ if lst.price is not None:
	453	+ con.execute("INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)",
	454	+ (lst.uid, now, lst.price))
	455	+ added += 1
	456	+ elif row["content_hash"] != h:
	457	+ # COALESCE : ne jamais écraser par null des coordonnées géocodées ni
	458	+ # les année/superficies remplies par enrichissement (rôle d'évaluation,
	459	+ # fiche détail) quand la source liste ne les fournit pas
	460	+ con.execute(
	461	+ """UPDATE listings SET url=:url, title=:title,
	462	+ address=:address, sector=:sector, city=:city, region=:region,
	463	+ property_type=:property_type, price=:price,
	464	+ price_label=:price_label, bedrooms=:bedrooms,
	465	+ bathrooms=:bathrooms, powder_rooms=:powder_rooms,
	466	+ area_sqft=COALESCE(:area_sqft, area_sqft),
	467	+ lot_sqft=COALESCE(:lot_sqft, lot_sqft),
	468	+ year_built=COALESCE(:year_built, year_built),
	469	+ mls=:mls, status=:status,
	470	+ broker_name=:broker_name, broker_phone=:broker_phone,
	471	+ agency=:agency, description=:description, features=:features,
	472	+ details=:details, images=:images,
	473	+ lat=COALESCE(:lat, lat), lng=COALESCE(:lng, lng),
	474	+ content_hash=:content_hash, last_seen=:now,
	475	+ updated_at=:now, miss_count=0, active=1
	476	+ WHERE uid=:uid""", params)
	477	+ if lst.price != row["price"]: # baisse/hausse de prix -> historique
	478	+ con.execute("INSERT INTO price_log (uid, ts, price) VALUES (?,?,?)",
	479	+ (lst.uid, now, lst.price))
	480	+ updated += 1
	481	+ else:
	482	+ con.execute(
	483	+ "UPDATE listings SET last_seen=?, miss_count=0, active=1 WHERE uid=?",
	484	+ (now, lst.uid))
	485	+
	486	+ # Propriétés de cette source qui n'apparaissent plus : délai de grâce,
	487	+ # puis désactivation (vendue/retirée). Suspendu si dérive détectée.
	488	+ removed = missed = 0
	489	+ if not alert:
	490	+ for r in con.execute(
	491	+ "SELECT uid, miss_count FROM listings WHERE source=? AND active=1",
	492	+ (source,)).fetchall():
	493	+ if r["uid"] in seen_uids:
	494	+ continue
	495	+ missed += 1
	496	+ if r["miss_count"] + 1 >= MISS_GRACE:
	497	+ con.execute(
	498	+ "UPDATE listings SET active=0, miss_count=?, updated_at=?"
	499	+ " WHERE uid=?", (r["miss_count"] + 1, now, r["uid"]))
	500	+ removed += 1
	501	+ else:
	502	+ con.execute("UPDATE listings SET miss_count=miss_count+1 WHERE uid=?",
	503	+ (r["uid"],))
	504	+
	505	+ stats = {
	506	+ "null_price_rate": null_price_rate,
	507	+ "null_address_rate": round(null_addr / n, 3) if n else 0.0,
	508	+ "missed": missed,
	509	+ }
	510	+ if alert:
	511	+ stats["alert"] = alert
	512	+ con.execute(
	513	+ "INSERT INTO sync_log (source, ts, found, added, updated, removed, ok,"
	514	+ " message, stats) VALUES (?,?,?,?,?,?,1,?,?)",
	515	+ (source, now, n, added, updated, removed, alert or "ok",
	516	+ json.dumps(stats, ensure_ascii=False)))
	517	+ con.commit()
	518	+ out = {"source": source, "found": n, "added": added,
	519	+ "updated": updated, "removed": removed}
	520	+ if alert:
	521	+ out["alert"] = alert
	522	+ return out
	523	+
	524	+
	525	+def log_failure(con: sqlite3.Connection, source: str, message: str) -> None:
	526	+ con.execute(
	527	+ "INSERT INTO sync_log (source, ts, found, added, updated, removed, ok, message)"
	528	+ " VALUES (?,?,0,0,0,0,0,?)", (source, time.time(), message))
	529	+ con.commit()
	530	+
	531	+
	532	+# ---------------------------------------------------------------------------
	533	+# Cache des pages détail (« détail si nouveau/modifié »)
	534	+# ---------------------------------------------------------------------------
	535	+
	536	+def get_cached_detail(con: sqlite3.Connection, source: str,
	537	+ external_id: str, key: str) -> dict \| None:
	538	+ """Payload détail mis en cache si la clé (hash liste) n'a pas changé."""
	539	+ row = con.execute(
	540	+ "SELECT key, payload FROM detail_cache WHERE source=? AND external_id=?",
	541	+ (source, external_id)).fetchone()
	542	+ if row and row["key"] == key and row["payload"]:
	543	+ try:
	544	+ return json.loads(row["payload"])
	545	+ except ValueError:
	546	+ return None
	547	+ return None
	548	+
	549	+
	550	+def get_stale_detail(con: sqlite3.Connection, source: str,
	551	+ external_id: str) -> dict \| None:
	552	+ """Payload détail SANS vérifier la clé — repli « périmé plutôt que rien »
	553	+ quand le budget de re-fetch d'un cycle est épuisé (ex. bump de version de
	554	+ clé) : la fiche garde photos/détails existants en attendant son re-parse."""
	555	+ row = con.execute(
	556	+ "SELECT payload FROM detail_cache WHERE source=? AND external_id=?",
	557	+ (source, external_id)).fetchone()
	558	+ if row and row["payload"]:
	559	+ try:
	560	+ return json.loads(row["payload"])
	561	+ except ValueError:
	562	+ return None
	563	+ return None
	564	+
	565	+
	566	+def put_cached_detail(con: sqlite3.Connection, source: str,
	567	+ external_id: str, key: str, payload: dict) -> None:
	568	+ con.execute(
	569	+ "INSERT INTO detail_cache (source, external_id, key, payload, fetched_at)"
	570	+ " VALUES (?,?,?,?,?)"
	571	+ " ON CONFLICT(source, external_id) DO UPDATE SET"
	572	+ " key=excluded.key, payload=excluded.payload, fetched_at=excluded.fetched_at",
	573	+ (source, external_id, key, json.dumps(payload, ensure_ascii=False),
	574	+ time.time()))
	575	+ con.commit()

added immoka/favorites.py +75 −0

		`@@ -0,0 +1,75 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# favorites.py : routes API des favoris (♥) — session Groupe KA requise.
	5	+# AUCUN stockage local : lecture et écriture passent par le hub Groupe KA
	6	+# (magasin central « Mon univers Ka »), voir immoka/hubfav.py.
	7	+# GET /api/favorites -> {ids:[item_id…], items:[…]} (depuis le hub)
	8	+# POST /api/favorites/toggle {on:bool, item:{item_id,title,…}} -> {ok,on}
	9	+# 401 si pas de session, ou si le compte n'est pas relié au hub (pas de
	10	+# ka_id) — le frontend redirige alors vers /api/auth/ka/login.
	11	+# -----------------------------------------------------------------------------
	12	+from __future__ import annotations
	13	+
	14	+from fastapi import APIRouter, Request
	15	+from fastapi.responses import JSONResponse
	16	+
	17	+from .auth import current_user
	18	+from .hubfav import hub_list, hub_toggle, invalidate
	19	+
	20	+router = APIRouter(prefix="/api/favorites")
	21	+
	22	+# champs acceptés d'un item de favori (et longueur maximale)
	23	+_ITEM_FIELDS = {"item_id": 120, "title": 200, "subtitle": 200,
	24	+ "price_label": 60, "image_url": 500, "url": 500}
	25	+
	26	+
	27	+def _ka_id(request: Request) -> str \| None:
	28	+ """KA-ID de la session, ou None (pas de session / compte non relié)."""
	29	+ user = current_user(request)
	30	+ if not user:
	31	+ return None
	32	+ ka_id = str(user.get("ka_id") or "")
	33	+ return ka_id if ka_id.startswith("ka-") else None
	34	+
	35	+
	36	+@router.get("")
	37	+def list_favorites(request: Request):
	38	+ """Favoris immo-ka du membre connecté, lus du hub Groupe KA."""
	39	+ ka_id = _ka_id(request)
	40	+ if not ka_id:
	41	+ return JSONResponse({"error": "non connecté"}, status_code=401)
	42	+ items = hub_list(ka_id)
	43	+ return {"ids": [it.get("item_id") for it in items if it.get("item_id")],
	44	+ "items": items}
	45	+
	46	+
	47	+@router.post("/toggle")
	48	+async def toggle_favorite(request: Request):
	49	+ """Ajoute (on=true) ou retire (on=false) un favori — poussé au hub."""
	50	+ ka_id = _ka_id(request)
	51	+ if not ka_id:
	52	+ return JSONResponse({"error": "non connecté"}, status_code=401)
	53	+ try:
	54	+ body = await request.json()
	55	+ assert isinstance(body, dict)
	56	+ except Exception:
	57	+ return JSONResponse({"error": "corps JSON attendu"}, status_code=400)
	58	+ on = bool(body.get("on"))
	59	+ raw = body.get("item") or {}
	60	+ item = {k: str(raw.get(k) or "")[:n] for k, n in _ITEM_FIELDS.items()}
	61	+ if not item["item_id"]:
	62	+ return JSONResponse({"error": "item.item_id requis"}, status_code=400)
	63	+ ok = hub_toggle(ka_id, "add" if on else "remove", item)
	64	+ # signal fort du moteur de préférences KA ID (features lues de la BD)
	65	+ from . import db as _db, kaid as _kaid
	66	+ con = _db.connect()
	67	+ row = con.execute("SELECT * FROM listings WHERE uid=?",
	68	+ (item["item_id"],)).fetchone()
	69	+ con.close()
	70	+ from .web import _kaid_features as _feats
	71	+ _kaid.track({"ka_id": ka_id}, "favorite" if on else "unfavorite",
	72	+ entity_type="property", entity_id=item["item_id"],
	73	+ features=_feats(dict(row)) if row else None)
	74	+ invalidate(ka_id) # le prochain GET relit l'état frais du hub
	75	+ return {"ok": ok, "on": on}

added immoka/geocode.py +654 −0

		`@@ -0,0 +1,654 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# geocode.py : géocodage des adresses via Nominatim (OpenStreetMap)
	5	+# - cache persistant (table geocode_cache) : une adresse n'est géocodée
	6	+# qu'une seule fois, et par immeuble (adresse normalisée), pas par annonce
	7	+# - politesse : 1 requête/seconde max, User-Agent identifiable
	8	+# - validation : les coordonnées doivent tomber dans la région attendue
	9	+# (bounding box par ville), sinon flag geocode_failed — jamais de
	10	+# coordonnées bidon
	11	+# - rigueur : chaque résultat est validé contre le CENTROÏDE de la ville
	12	+# annoncée (médiane des fiches déjà géocodées, sinon Nominatim, en cache) —
	13	+# à plus de VILLE_RADIUS_KM du centroïde, le candidat est rejeté. Corrige
	14	+# la classe de bug « rue homonyme dans une autre ville » (ex. rue des
	15	+# Perdrix de Jonquière géocodée à Saint-Augustin).
	16	+# -----------------------------------------------------------------------------
	17	+from __future__ import annotations
	18	+
	19	+import json
	20	+import math
	21	+import sqlite3
	22	+import statistics
	23	+
	24	+import re
	25	+import time
	26	+
	27	+import requests
	28	+
	29	+from . import db
	30	+from .normalize import strip_accents
	31	+
	32	+NOMINATIM_URL = "https://nominatim.openstreetmap.org/search"
	33	+# Repli officiel du gouvernement du Québec (Adresses Québec / MERN) : couvre
	34	+# les rues trop récentes pour OpenStreetMap (développements neufs de Lévis…)
	35	+AQ_URL = ("https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/"
	36	+ "Adresse_Geocodage/GeocodeServer/findAddressCandidates")
	37	+AQ_MIN_SCORE = 75
	38	+# ASCII pur : le serveur ArcGIS d'Adresses Québec retourne 500 si l'en-tête
	39	+# User-Agent contient des accents (latin-1)
	40	+USER_AGENT = "ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)"
	41	+REQUEST_DELAY = 1.1 # règle Nominatim : max 1 req/s
	42	+REQUEST_DELAY_AQ = 0.12 # Adresses Québec (MERN) : pas de limite stricte
	43	+RETRY_FAILED_AFTER = 30 * 86400 # re-tenter les échecs après 30 jours
	44	+
	45	+# Bounding boxes (lat_min, lat_max, lng_min, lng_max)
	46	+_BBOX_QUEBEC = (46.55, 47.10, -71.75, -70.85) # Québec, Lévis, St-Augustin
	47	+# garde-fou provincial : couvre Gatineau, l'Abitibi, le Saguenay, la Côte-Nord
	48	+# et la Gaspésie (expansion provinciale)
	49	+_BBOX_SUD_QC = (44.50, 63.00, -80.00, -56.00)
	50	+# territoire complet Groupe Ka : Québec + Ontario (Windsor -83°, Kenora -94.5°)
	51	+# — même boîte que schema.finalize()
	52	+_BBOX_KA = (41.60, 63.00, -95.50, -56.00)
	53	+
	54	+_VILLES_QUEBEC = {"quebec", "levis", "saint-augustin-de-desmaures",
	55	+ "l'ancienne-lorette", "ancienne-lorette"}
	56	+
	57	+# Validation « rigoureuse » : distance max entre un résultat de géocodage et une
	58	+# référence de la ville annoncée. 40 km tolère les grandes municipalités
	59	+# fusionnées (Saguenay, Gatineau, La Tuque…) tout en rejetant les rues
	60	+# homonymes d'une autre région (Saint-Augustin ↔ Jonquière = ~190 km).
	61	+# ⚠ Le Québec compte de nombreuses municipalités HOMONYMES (deux L'Ange-Gardien,
	62	+# deux Saint-Donat, deux Sainte-Félicité…) : la référence n'est donc jamais un
	63	+# centroïde unique mais un ENSEMBLE de grappes de fiches (chaque homonyme garde
	64	+# la sienne) + le point Nominatim de la ville.
	65	+VILLE_RADIUS_KM = 40.0
	66	+CLUSTER_MIN = 3 # une grappe de fiches devient une référence de confiance dès n >= 3
	67	+
	68	+
	69	+def _bbox_for(city: str) -> tuple[float, float, float, float]:
	70	+ key = strip_accents((city or "").strip().lower())
	71	+ return _BBOX_QUEBEC if key in _VILLES_QUEBEC else _BBOX_KA
	72	+
	73	+
	74	+def _in_bbox(lat: float, lng: float, bbox: tuple) -> bool:
	75	+ return bbox[0] <= lat <= bbox[1] and bbox[2] <= lng <= bbox[3]
	76	+
	77	+
	78	+def _dist_km(lat1: float, lng1: float, lat2: float, lng2: float) -> float:
	79	+ """Distance haversine en kilomètres."""
	80	+ p1, p2 = math.radians(lat1), math.radians(lat2)
	81	+ a = (math.sin((p2 - p1) / 2) ** 2
	82	+ + math.cos(p1) * math.cos(p2) * math.sin(math.radians(lng2 - lng1) / 2) ** 2)
	83	+ return 2 * 6371.0 * math.asin(math.sqrt(a))
	84	+
	85	+
	86	+def norm_key(address: str) -> str:
	87	+ """Clé de cache : adresse normalisée (casse, accents, espaces, n° d'app.)."""
	88	+ s = strip_accents((address or "").lower())
	89	+ s = re.sub(r"\b(?:app?t?\|appartement\|unite\|suite\|#)\.?\s*[\w-]+\b", " ", s)
	90	+ s = re.sub(r"[^a-z0-9]+", " ", s)
	91	+ return re.sub(r"\s+", " ", s).strip()
	92	+
	93	+
	94	+class Geocoder:
	95	+ def __init__(self, con) -> None:
	96	+ self.con = con
	97	+ self.session = requests.Session()
	98	+ self.session.headers["User-Agent"] = USER_AGENT
	99	+ self._last = 0.0
	100	+ self._villes: dict[str, dict \| None] = {} # norm(ville) -> {lat,lng,muni}
	101	+ self._med: dict[str, list[tuple]] \| None = None # norm(ville) -> grappes (lat,lng,n)
	102	+ self.ville_api_calls = 0 # requêtes Nominatim « ville »
	103	+
	104	+ @staticmethod
	105	+ def _clean(address: str) -> str:
	106	+ """Nettoyages qui aident Nominatim sur les adresses québécoises."""
	107	+ s = address.strip()
	108	+ # « 101-2905 Rue X » = unité 101, civique 2905 -> garder le civique
	109	+ s = re.sub(r"^(\d+)-(\d+)\s", r"\2 ", s)
	110	+ # « 6275 et 6375 boulevard X » -> premier civique
	111	+ s = re.sub(r"^(\d+)\s+et\s+\d+\s", r"\1 ", s)
	112	+ # « Montréal - Laval » / « Montréal - Île-des-Soeurs » -> garder le vrai lieu
	113	+ s = re.sub(r"montr[ée]al\s-\s", "", s, flags=re.I)
	114	+ # « bureau 105 » / « suite 3 » / « local B » : suffixes de bureau
	115	+ s = re.sub(r",?\s(?:bureau\|suite\|local\|app\.?\|apt\.?)\s[\w-]+\b", "", s, flags=re.I)
	116	+ # « Vanier (Québec) » -> « Vanier, Québec »
	117	+ s = re.sub(r"\s*$(qu[ée]bec)$", r", \1", s, flags=re.I)
	118	+ # abréviations cardinales : « Rue Salaberry O » -> « Ouest »
	119	+ s = re.sub(r"\bO\.?(?=,\|\s*$)", "Ouest", s)
	120	+ s = re.sub(r"\bE\.?(?=,\|\s*$)", "Est", s)
	121	+ return s
	122	+
	123	+ def _build_query(self, address: str, city: str) -> str:
	124	+ q = self._clean(address)
	125	+ key = strip_accents(q.lower())
	126	+ if city and strip_accents(city.lower()) not in key:
	127	+ q += f", {city}"
	128	+ if "quebec" not in strip_accents(q.lower()) and "qc" not in q.lower():
	129	+ q += ", Québec"
	130	+ return q + ", Canada"
	131	+
	132	+ def _query_nominatim(self, params: dict) -> tuple[float, float] \| None:
	133	+ """Une requête Nominatim, throttlée."""
	134	+ wait = REQUEST_DELAY - (time.time() - self._last)
	135	+ if wait > 0:
	136	+ time.sleep(wait)
	137	+ try:
	138	+ resp = self.session.get(NOMINATIM_URL, params={
	139	+ "format": "jsonv2", "limit": 1, "countrycodes": "ca", **params,
	140	+ }, timeout=20)
	141	+ self._last = time.time()
	142	+ resp.raise_for_status()
	143	+ hits = resp.json()
	144	+ except Exception:
	145	+ self._last = time.time()
	146	+ return None
	147	+ if not hits:
	148	+ return None
	149	+ try:
	150	+ return float(hits[0]["lat"]), float(hits[0]["lon"])
	151	+ except (KeyError, ValueError):
	152	+ return None
	153	+
	154	+ def _query_adresses_quebec(self, address: str, city: str) -> tuple[float, float] \| None:
	155	+ """Repli : géocodeur officiel Adresses Québec (MERN, ArcGIS).
	156	+
	157	+ Couvre les rues trop récentes pour OSM. Seuil de score AQ_MIN_SCORE
	158	+ pour éviter les correspondances approximatives sur une autre rue.
	159	+ """
	160	+ premier = self._clean(address).split(",")[0].strip()
	161	+ ville = (city or "Québec").strip()
	162	+ wait = REQUEST_DELAY_AQ - (time.time() - self._last)
	163	+ if wait > 0:
	164	+ time.sleep(wait)
	165	+ try:
	166	+ resp = self.session.get(AQ_URL, params={
	167	+ "SingleLine": f"{premier}, {ville}",
	168	+ "f": "json", "outSR": 4326, "maxLocations": 1,
	169	+ }, timeout=20)
	170	+ self._last = time.time()
	171	+ resp.raise_for_status()
	172	+ cands = resp.json().get("candidates") or []
	173	+ except Exception:
	174	+ self._last = time.time()
	175	+ return None
	176	+ if not cands or cands[0].get("score", 0) < AQ_MIN_SCORE:
	177	+ return None
	178	+ loc = cands[0].get("location") or {}
	179	+ try:
	180	+ return float(loc["y"]), float(loc["x"])
	181	+ except (KeyError, ValueError):
	182	+ return None
	183	+
	184	+ def _attempts(self, address: str, city: str, muni: str \| None = None) -> list[dict]:
	185	+ """Stratégies de requête, de la plus précise à la moins précise.
	186	+
	187	+ 1) structurée civique+rue (évite l'ambiguïté « Québec » ville/province)
	188	+ 2) idem avec la municipalité OFFICIELLE (« Saguenay ») quand la ville
	189	+ annoncée est un secteur (« Jonquière (Lac-Kénogami) ») inconnu des API
	190	+ 3) recherche libre complète
	191	+ 4) structurée rue seule -> centroïde de rue (repli acceptable pour la
	192	+ carte quand le numéro civique est absent d'OpenStreetMap)
	193	+ """
	194	+ premier = self._clean(address).split(",")[0].strip()
	195	+ ville = (city or "").strip()
	196	+ if not ville:
	197	+ k = strip_accents(address.lower())
	198	+ ville = "Lévis" if "levis" in k else "Québec"
	199	+ villes = [ville]
	200	+ # premier mot de la ville (« Jonquiere Lac Kenogami » -> « Jonquiere »)
	201	+ if " " in ville:
	202	+ villes.append(ville.split(" ")[0])
	203	+ if muni and norm_key(muni) not in {norm_key(v) for v in villes}:
	204	+ villes.append(muni)
	205	+
	206	+ tries: list[dict] = []
	207	+ m = re.match(r"^(\d+)[,\s]+(.{4,})$", premier)
	208	+ for v in villes:
	209	+ commun = {"city": v, "state": "Québec", "country": "Canada"}
	210	+ if m:
	211	+ tries.append({"street": f"{m.group(1)} {m.group(2)}", **commun})
	212	+ tries.append({"q": self._build_query(address, city)})
	213	+ for v in villes:
	214	+ commun = {"city": v, "state": "Québec", "country": "Canada"}
	215	+ if m:
	216	+ tries.append({"street": m.group(2), **commun})
	217	+ return tries
	218	+
	219	+ # ----- références de ville (validation rigoureuse) -----------------------
	220	+ def _clusters(self) -> dict[str, list[tuple]]:
	221	+ """Grappes de coordonnées par ville, depuis les fiches déjà géocodées
	222	+ (regroupement glouton, rayon VILLE_RADIUS_KM). Chaque grappe :
	223	+ (lat médiane, lng médiane, n). Les municipalités homonymes produisent
	224	+ naturellement une grappe chacune — aucune n'écrase l'autre."""
	225	+ if self._med is None:
	226	+ acc: dict[str, list] = {}
	227	+ for r in self.con.execute(
	228	+ """SELECT city, lat, lng FROM listings
	229	+ WHERE active=1 AND lat IS NOT NULL AND city<>''"""):
	230	+ acc.setdefault(norm_key(r["city"]), []).append((r["lat"], r["lng"]))
	231	+ out: dict[str, list[tuple]] = {}
	232	+ for k, pts in acc.items():
	233	+ clusters: list[list] = [] # [ [lat_c, lng_c, [points]] ]
	234	+ for lat, lng in pts:
	235	+ for cl in clusters:
	236	+ if _dist_km(lat, lng, cl[0], cl[1]) <= VILLE_RADIUS_KM:
	237	+ cl[2].append((lat, lng))
	238	+ cl[0] = statistics.median(p[0] for p in cl[2])
	239	+ cl[1] = statistics.median(p[1] for p in cl[2])
	240	+ break
	241	+ else:
	242	+ clusters.append([lat, lng, [(lat, lng)]])
	243	+ out[k] = [(cl[0], cl[1], len(cl[2])) for cl in clusters]
	244	+ self._med = out
	245	+ return self._med
	246	+
	247	+ def resolve_ville(self, city: str, allow_api: bool = True) -> dict \| None:
	248	+ """Ville -> {lat, lng, muni} (muni = municipalité officielle, ex.
	249	+ « Jonquière (Lac-Kénogami) » -> Saguenay). Cache : geocode_cache,
	250	+ clé « ville:<norm> ». None si irrésoluble."""
	251	+ k = norm_key(city or "")
	252	+ if not k:
	253	+ return None
	254	+ if k in self._villes:
	255	+ return self._villes[k]
	256	+ key = "ville:" + k
	257	+ row = self.con.execute(
	258	+ "SELECT lat, lng, muni, failed, ts FROM geocode_cache WHERE address=?",
	259	+ (key,)).fetchone()
	260	+ if row is not None:
	261	+ if not row["failed"]:
	262	+ v = {"lat": row["lat"], "lng": row["lng"], "muni": row["muni"]}
	263	+ self._villes[k] = v
	264	+ return v
	265	+ if time.time() - (row["ts"] or 0) < RETRY_FAILED_AFTER:
	266	+ self._villes[k] = None
	267	+ return None
	268	+ if not allow_api:
	269	+ return None # pas de mémoire : on réessaiera quand l'API sera permise
	270	+ v = None
	271	+ # priorité au Québec ; à défaut, l'Ontario (extension immo-ka)
	272	+ for prov in ("Québec", "Ontario"):
	273	+ self.ville_api_calls += 1
	274	+ wait = REQUEST_DELAY - (time.time() - self._last)
	275	+ if wait > 0:
	276	+ time.sleep(wait)
	277	+ try:
	278	+ resp = self.session.get(NOMINATIM_URL, params={
	279	+ "q": f"{city}, {prov}, Canada", "format": "jsonv2", "limit": 1,
	280	+ "countrycodes": "ca", "addressdetails": 1}, timeout=20)
	281	+ self._last = time.time()
	282	+ resp.raise_for_status()
	283	+ hits = resp.json()
	284	+ except Exception:
	285	+ self._last = time.time()
	286	+ return None # erreur réseau : ne pas cacher un échec définitif
	287	+ if hits:
	288	+ try:
	289	+ lat, lng = float(hits[0]["lat"]), float(hits[0]["lon"])
	290	+ if _in_bbox(lat, lng, _BBOX_KA):
	291	+ a = hits[0].get("address") or {}
	292	+ muni = (a.get("city") or a.get("town") or a.get("village")
	293	+ or a.get("municipality"))
	294	+ v = {"lat": lat, "lng": lng, "muni": muni}
	295	+ except (KeyError, ValueError, TypeError):
	296	+ v = None
	297	+ if v:
	298	+ break
	299	+ self.con.execute(
	300	+ "INSERT INTO geocode_cache (address, lat, lng, muni, provider, failed, ts)"
	301	+ " VALUES (?,?,?,?,?,?,?) ON CONFLICT(address) DO UPDATE SET"
	302	+ " lat=excluded.lat, lng=excluded.lng, muni=excluded.muni,"
	303	+ " provider=excluded.provider, failed=excluded.failed, ts=excluded.ts",
	304	+ (key, v["lat"] if v else None, v["lng"] if v else None,
	305	+ v["muni"] if v else None, "ville_nominatim", 0 if v else 1, time.time()))
	306	+ self.con.commit()
	307	+ self._villes[k] = v
	308	+ return v
	309	+
	310	+ def city_refs(self, city: str, allow_api: bool = True) -> list[tuple[float, float]]:
	311	+ """Points de référence d'une ville : grappes de fiches dignes de
	312	+ confiance (n >= CLUSTER_MIN — une par municipalité homonyme) + point
	313	+ Nominatim de la ville. Liste vide = ville inconnue (-> bbox seule)."""
	314	+ k = norm_key(city or "")
	315	+ if not k:
	316	+ return []
	317	+ refs = [(cl[0], cl[1]) for cl in self._clusters().get(k, [])
	318	+ if cl[2] >= CLUSTER_MIN]
	319	+ v = self.resolve_ville(city, allow_api=allow_api)
	320	+ if v:
	321	+ refs.append((v["lat"], v["lng"]))
	322	+ return refs
	323	+
	324	+ def coords_ok(self, c: tuple[float, float] \| None, city: str,
	325	+ refs: list[tuple[float, float]] \| None = None) -> bool:
	326	+ """Valide un candidat : dans la bbox ET à <= VILLE_RADIUS_KM d'au moins
	327	+ une référence de la ville annoncée (quand elle en a)."""
	328	+ if c is None or not _in_bbox(*c, _bbox_for(city)):
	329	+ return False
	330	+ if refs is None:
	331	+ refs = self.city_refs(city)
	332	+ return not refs or any(_dist_km(c[0], c[1], r[0], r[1]) <= VILLE_RADIUS_KM
	333	+ for r in refs)
	334	+
	335	+ def resolve(self, address: str, city: str) -> tuple[float, float] \| None:
	336	+ """Adresse -> (lat, lng), via cache puis AQ/Nominatim. None si introuvable.
	337	+
	338	+ Rigueur : chaque candidat doit être cohérent avec la ville annoncée
	339	+ (centroïde <= VILLE_RADIUS_KM). Si la ville annoncée est un secteur
	340	+ inconnu d'Adresses Québec, on réessaie avec la municipalité officielle.
	341	+ """
	342	+ key = norm_key(address)
	343	+ if not key or len(key) < 6:
	344	+ return None
	345	+ row = self.con.execute(
	346	+ "SELECT lat, lng, failed, ts FROM geocode_cache WHERE address=?",
	347	+ (key,)).fetchone()
	348	+ if row is not None:
	349	+ if not row["failed"]:
	350	+ return (row["lat"], row["lng"])
	351	+ if time.time() - (row["ts"] or 0) < RETRY_FAILED_AFTER:
	352	+ return None # échec récent : ne pas marteler l'API
	353	+
	354	+ refs = self.city_refs(city)
	355	+ coords = None
	356	+ # Adresses Québec (MERN) d'abord : rapide, autoritatif au Québec, pas de
	357	+ # limite stricte. Nominatim (1 req/s) seulement en repli.
	358	+ provider = "adresses_quebec"
	359	+ c = self._query_adresses_quebec(address, city)
	360	+ if self.coords_ok(c, city, refs):
	361	+ coords = c
	362	+ muni = None
	363	+ if coords is None:
	364	+ # ville annoncée = secteur (« Jonquière (Lac-Kénogami) ») ? AQ ne
	365	+ # connaît que les municipalités officielles -> retenter avec elle.
	366	+ v = self.resolve_ville(city)
	367	+ muni = (v or {}).get("muni")
	368	+ if muni and norm_key(muni) != norm_key(city or ""):
	369	+ c = self._query_adresses_quebec(address, muni)
	370	+ if self.coords_ok(c, city, refs):
	371	+ coords, provider = c, "adresses_quebec_muni"
	372	+ if coords is None:
	373	+ provider = "nominatim"
	374	+ for params in self._attempts(address, city, muni):
	375	+ c = self._query_nominatim(params)
	376	+ if self.coords_ok(c, city, refs):
	377	+ coords = c
	378	+ break
	379	+ ok = coords is not None
	380	+ self.con.execute(
	381	+ "INSERT INTO geocode_cache (address, lat, lng, provider, failed, ts)"
	382	+ " VALUES (?,?,?,?,?,?)"
	383	+ " ON CONFLICT(address) DO UPDATE SET lat=excluded.lat,"
	384	+ " lng=excluded.lng, provider=excluded.provider,"
	385	+ " failed=excluded.failed, ts=excluded.ts",
	386	+ (key, coords[0] if ok else None, coords[1] if ok else None,
	387	+ provider, 0 if ok else 1, time.time()))
	388	+ self.con.commit()
	389	+ return coords if ok else None
	390	+
	391	+
	392	+def run(limit: int \| None = None) -> dict:
	393	+ """Géocode les annonces actives sans coordonnées, par adresse unique.
	394	+
	395	+ `limit` borne le nombre de NOUVELLES requêtes Nominatim (les hits de
	396	+ cache sont gratuits et toujours appliqués).
	397	+ """
	398	+ con = db.connect()
	399	+ geo = Geocoder(con)
	400	+ rows = con.execute(
	401	+ """SELECT uid, address, city FROM listings
	402	+ WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0
	403	+ AND dup_hidden=0
	404	+ ORDER BY address""").fetchall()
	405	+
	406	+ # regrouper par immeuble (adresse normalisée)
	407	+ groupes: dict[str, list] = {}
	408	+ for r in rows:
	409	+ groupes.setdefault(norm_key(r["address"]), []).append(r)
	410	+
	411	+ done = failed = requests_made = 0
	412	+ for key, members in groupes.items():
	413	+ if not key:
	414	+ continue
	415	+ cached = con.execute(
	416	+ "SELECT failed FROM geocode_cache WHERE address=?", (key,)).fetchone()
	417	+ if cached is None:
	418	+ if limit is not None and requests_made >= limit:
	419	+ continue
	420	+ requests_made += 1
	421	+ try:
	422	+ coords = geo.resolve(members[0]["address"], members[0]["city"])
	423	+ if coords:
	424	+ for r in members:
	425	+ con.execute("UPDATE listings SET lat=?, lng=? WHERE uid=?",
	426	+ (coords[0], coords[1], r["uid"]))
	427	+ done += len(members)
	428	+ else:
	429	+ # introuvable/hors zone : flag ; jamais de coordonnées bidon
	430	+ for r in members:
	431	+ con.execute("UPDATE listings SET geocode_failed=1 WHERE uid=?",
	432	+ (r["uid"],))
	433	+ failed += len(members)
	434	+ con.commit()
	435	+ except sqlite3.OperationalError:
	436	+ # verrou transitoire (watcher/refresh_dedup) : on saute cette adresse,
	437	+ # elle sera reprise au prochain passage — jamais crasher tout le run.
	438	+ try:
	439	+ con.rollback()
	440	+ except sqlite3.Error:
	441	+ pass
	442	+ time.sleep(1.0)
	443	+ continue
	444	+
	445	+ con.close()
	446	+ stats = {"geocoded": done, "failed": failed,
	447	+ "unique_addresses": len(groupes), "api_requests": requests_made}
	448	+ print(f"[immo-ka] geocode {stats}")
	449	+ return stats
	450	+
	451	+
	452	+AQ_BATCH_URL = ("https://servicescarto.mern.gouv.qc.ca/pes/rest/services/Territoire/"
	453	+ "Adresse_Geocodage/GeocodeServer/geocodeAddresses")
	454	+BATCH_SIZE = 200
	455	+RESCUE_MAX = 150 # rattrapages resolve() max par passe (Nominatim = 1 req/s)
	456	+
	457	+
	458	+def strip_bad_source_coords(con, listings) -> int:
	459	+ """Garde d'ingestion : annule les lat/lng fournis par un connecteur quand
	460	+ ils contredisent la ville annoncée (> VILLE_RADIUS_KM du centroïde connu).
	461	+ Cache seulement (médianes + villes déjà résolues) : aucun appel réseau,
	462	+ la synchronisation reste rapide. Retourne le nombre de paires annulées."""
	463	+ geo = Geocoder(con)
	464	+ n = 0
	465	+ for lst in listings:
	466	+ if lst.lat is None or lst.lng is None or not (lst.city or "").strip():
	467	+ continue
	468	+ refs = geo.city_refs(lst.city, allow_api=False)
	469	+ if refs and not geo.coords_ok((lst.lat, lst.lng), lst.city, refs):
	470	+ lst.lat = lst.lng = None
	471	+ n += 1
	472	+ return n
	473	+
	474	+
	475	+def run_batch(limit: int \| None = None) -> dict:
	476	+ """Géocodage EN LOT via Adresses Québec (`geocodeAddresses`, jusqu'à 1000
	477	+ adresses/requête) — ~35 requêtes pour tout le parc au lieu de dizaines de
	478	+ milliers. Beaucoup plus rapide que le mode 1-par-1 (et que Nominatim)."""
	479	+ con = db.connect()
	480	+ geo = Geocoder(con) # pour réutiliser _clean / bbox
	481	+ rows = con.execute(
	482	+ """SELECT uid, address, city FROM listings
	483	+ WHERE active=1 AND lat IS NULL AND address<>'' AND geocode_failed=0
	484	+ AND dup_hidden=0 AND COALESCE(region,'')<>'Ontario'
	485	+ ORDER BY address""").fetchall()
	486	+ # 1 entrée par immeuble (adresse normalisée) ; on saute les échecs en cache
	487	+ uniq: dict[str, dict] = {}
	488	+ for r in rows:
	489	+ k = norm_key(r["address"])
	490	+ if not k or len(k) < 6:
	491	+ continue
	492	+ u = uniq.setdefault(k, {"address": r["address"], "city": r["city"],
	493	+ "members": []})
	494	+ u["members"].append(r["uid"])
	495	+ pending = []
	496	+ for k, u in uniq.items():
	497	+ c = con.execute("SELECT lat,lng,failed FROM geocode_cache WHERE address=?",
	498	+ (k,)).fetchone()
	499	+ if c is not None and not c["failed"]: # déjà résolu : appliquer direct
	500	+ for uid in u["members"]:
	501	+ con.execute("UPDATE listings SET lat=?, lng=? WHERE uid=?",
	502	+ (c["lat"], c["lng"], uid))
	503	+ continue
	504	+ if c is not None and c["failed"]:
	505	+ continue
	506	+ pending.append((k, u))
	507	+ con.commit()
	508	+ if limit is not None:
	509	+ pending = pending[:limit]
	510	+
	511	+ session = requests.Session()
	512	+ session.headers["User-Agent"] = USER_AGENT
	513	+ done = failed = 0
	514	+ rescue: list[tuple[str, dict]] = [] # échecs du lot -> resolve() individuel
	515	+ for i in range(0, len(pending), BATCH_SIZE):
	516	+ chunk = pending[i:i + BATCH_SIZE]
	517	+ records = {"records": [
	518	+ {"attributes": {"OBJECTID": j,
	519	+ "SingleLine": f"{geo._clean(u['address']).split(',')[0].strip()}, "
	520	+ f"{(u['city'] or 'Québec').strip()}"}}
	521	+ for j, (_k, u) in enumerate(chunk)]}
	522	+ try:
	523	+ # POST obligatoire : le param `addresses` (JSON de N records) est trop
	524	+ # long pour une URL GET dès quelques dizaines d'adresses.
	525	+ resp = session.post(AQ_BATCH_URL, data={
	526	+ "addresses": json.dumps(records, ensure_ascii=False),
	527	+ "f": "json", "outSR": 4326}, timeout=90)
	528	+ locs = resp.json().get("locations", [])
	529	+ except Exception as e:
	530	+ print(f"[immo-ka] geocode-batch lot {i//BATCH_SIZE} ERREUR: {str(e)[:80]}")
	531	+ time.sleep(1.0)
	532	+ continue
	533	+ by_id = {l["attributes"].get("ResultID"): l for l in locs}
	534	+ for j, (k, u) in enumerate(chunk):
	535	+ loc = by_id.get(j)
	536	+ coords = None
	537	+ if loc and loc["attributes"].get("Score", 0) >= AQ_MIN_SCORE:
	538	+ lc = loc.get("location") or {}
	539	+ try:
	540	+ cand = (float(lc["y"]), float(lc["x"]))
	541	+ # bbox + cohérence avec le centroïde de la ville annoncée
	542	+ if geo.coords_ok(cand, u["city"]):
	543	+ coords = cand
	544	+ except (KeyError, ValueError, TypeError):
	545	+ coords = None
	546	+ try:
	547	+ if coords:
	548	+ for uid in u["members"]:
	549	+ con.execute("UPDATE listings SET lat=?, lng=? WHERE uid=?",
	550	+ (coords[0], coords[1], uid))
	551	+ con.execute(
	552	+ "INSERT INTO geocode_cache (address,lat,lng,provider,failed,ts)"
	553	+ " VALUES (?,?,?,?,0,?) ON CONFLICT(address) DO UPDATE SET"
	554	+ " lat=excluded.lat, lng=excluded.lng, provider=excluded.provider,"
	555	+ " failed=0, ts=excluded.ts",
	556	+ (k, coords[0], coords[1], "adresses_quebec_batch", time.time()))
	557	+ done += len(u["members"])
	558	+ con.commit()
	559	+ else:
	560	+ # pas de verdict tout de suite : resolve() réessaiera avec la
	561	+ # municipalité officielle + Nominatim (borné par RESCUE_MAX)
	562	+ rescue.append((k, u))
	563	+ except sqlite3.OperationalError:
	564	+ try: con.rollback()
	565	+ except sqlite3.Error: pass
	566	+ time.sleep(1.0)
	567	+ print(f"[immo-ka] geocode-batch {i+len(chunk)}/{len(pending)} "
	568	+ f"(résolues {done}, à rattraper {len(rescue)})")
	569	+
	570	+ # Rattrapage 1-par-1 des échecs du lot : variantes de municipalité (AQ) puis
	571	+ # Nominatim, validées par centroïde. resolve() écrit lui-même le verdict au
	572	+ # cache (succès ou échec 30 j) ; au-delà de RESCUE_MAX, on laisse les fiches
	573	+ # intactes (ni cache ni flag) -> reprises aux prochains passages.
	574	+ rescued = 0
	575	+ for k, u in rescue[:RESCUE_MAX]:
	576	+ try:
	577	+ coords = geo.resolve(u["address"], u["city"])
	578	+ if coords:
	579	+ for uid in u["members"]:
	580	+ con.execute("UPDATE listings SET lat=?, lng=? WHERE uid=?",
	581	+ (coords[0], coords[1], uid))
	582	+ done += len(u["members"])
	583	+ rescued += len(u["members"])
	584	+ else:
	585	+ for uid in u["members"]:
	586	+ con.execute("UPDATE listings SET geocode_failed=1 WHERE uid=?", (uid,))
	587	+ failed += len(u["members"])
	588	+ con.commit()
	589	+ except sqlite3.OperationalError:
	590	+ try: con.rollback()
	591	+ except sqlite3.Error: pass
	592	+ time.sleep(1.0)
	593	+ con.close()
	594	+ stats = {"geocoded": done, "rescued": rescued, "failed": failed,
	595	+ "deferred": max(0, len(rescue) - RESCUE_MAX),
	596	+ "batches": (len(pending)+BATCH_SIZE-1)//BATCH_SIZE}
	597	+ print(f"[immo-ka] geocode-batch {stats}")
	598	+ return stats
	599	+
	600	+
	601	+def run_audit(nominatim_budget: int \| None = None, apply: bool = True) -> dict:
	602	+ """Audit de cohérence géographique des fiches DÉJÀ géocodées.
	603	+
	604	+ Détecte les coordonnées à plus de VILLE_RADIUS_KM de TOUTE référence de
	605	+ leur ville — grappes de fiches (une par municipalité homonyme) + point
	606	+ Nominatim — puis les remet en file de géocodage : lat/lng annulés,
	607	+ geocode_failed remis à 0, entrée de cache purgée. Une fiche n'est JAMAIS
	608	+ flaguée sans référence indépendante confirmant l'incohérence (les
	609	+ homonymes et villes irrésolues sont épargnés). `nominatim_budget` borne
	610	+ les résolutions de villes inconnues (1 req/s) ; None = illimité.
	611	+ `apply=False` = rapport seul.
	612	+ """
	613	+ con = db.connect()
	614	+ geo = Geocoder(con)
	615	+ rows = con.execute(
	616	+ """SELECT uid, address, city, lat, lng FROM listings
	617	+ WHERE active=1 AND lat IS NOT NULL AND city<>''""").fetchall()
	618	+ flagged, inconnues, reportees = [], 0, 0
	619	+ for r in rows:
	620	+ k = norm_key(r["city"])
	621	+ clusters = [(cl[0], cl[1]) for cl in geo._clusters().get(k, [])
	622	+ if cl[2] >= CLUSTER_MIN]
	623	+ dists = [_dist_km(r["lat"], r["lng"], c[0], c[1]) for c in clusters]
	624	+ if dists and min(dists) <= VILLE_RADIUS_KM:
	625	+ continue # cohérente avec une grappe de sa ville
	626	+ budget_ok = nominatim_budget is None or geo.ville_api_calls < nominatim_budget
	627	+ v = geo.resolve_ville(r["city"], allow_api=budget_ok)
	628	+ if v is not None:
	629	+ d = _dist_km(r["lat"], r["lng"], v["lat"], v["lng"])
	630	+ if d <= VILLE_RADIUS_KM:
	631	+ continue # cohérente avec le point Nominatim de la ville
	632	+ flagged.append((r, min(dists + [d])))
	633	+ elif not clusters:
	634	+ inconnues += 1 # aucune référence : on ne flague pas
	635	+ elif not budget_ok:
	636	+ reportees += 1 # ville pas encore résolue : prochaine passe
	637	+ else:
	638	+ flagged.append((r, min(dists))) # ville irrésoluble, grappes loin
	639	+ if apply:
	640	+ for r, d in flagged:
	641	+ con.execute("DELETE FROM geocode_cache WHERE address=?",
	642	+ (norm_key(r["address"]),))
	643	+ con.execute("""UPDATE listings SET lat=NULL, lng=NULL,
	644	+ geocode_failed=0 WHERE uid=?""", (r["uid"],))
	645	+ con.commit()
	646	+ for r, d in flagged[:20]:
	647	+ print(f"[immo-ka] audit: {r['uid']} « {r['address']}, {r['city']} » "
	648	+ f"à {d:.0f} km de sa ville")
	649	+ con.close()
	650	+ stats = {"verifiees": len(rows), "incoherentes": len(flagged),
	651	+ "villes_inconnues": inconnues, "reportees": reportees,
	652	+ "corrigees": apply}
	653	+ print(f"[immo-ka] geocode-audit {stats}")
	654	+ return stats

added immoka/hubfav.py +100 −0

		`@@ -0,0 +1,100 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# hubfav.py : favoris unifiés « Mon univers Ka » — Immo·Ka n'a AUCUN stockage
	5	+# local de favoris : le hub Groupe KA (groupe-ka.com) est le magasin central.
	6	+# Chaque ♥ est poussé au hub (POST signé, SYNCHRONE : c'est l'action
	7	+# utilisateur) et la liste est relue du hub (GET signé, cache mémoire 30 s
	8	+# par ka_id, [] sur toute erreur). sig = HMAC-SHA256(KA_SSO_SECRET,
	9	+# "immo-ka.<ka_id>.<ts>") hex — même secret que le SSO (ts ±5 min).
	10	+# Config .env : KA_SSO_SECRET, KA_HUB_URL (optionnel).
	11	+# -----------------------------------------------------------------------------
	12	+from __future__ import annotations
	13	+
	14	+import hashlib
	15	+import hmac
	16	+import os
	17	+import threading
	18	+import time
	19	+
	20	+import requests
	21	+
	22	+CLIENT_ID = "immo-ka"
	23	+KA_HUB_URL = os.environ.get("KA_HUB_URL", "https://www.groupe-ka.com").rstrip("/")
	24	+LIST_TTL = 30 # secondes — cache mémoire de hub_list par ka_id
	25	+
	26	+_cache: dict[str, tuple[float, list]] = {}
	27	+_lock = threading.Lock()
	28	+
	29	+
	30	+def _sig(ka_id: str, ts: int) -> str \| None:
	31	+ secret = os.environ.get("KA_SSO_SECRET")
	32	+ if not secret:
	33	+ return None
	34	+ return hmac.new(secret.encode(),
	35	+ f"{CLIENT_ID}.{ka_id}.{ts}".encode(),
	36	+ hashlib.sha256).hexdigest()
	37	+
	38	+
	39	+def hub_toggle(ka_id: str, action: str, item: dict) -> bool:
	40	+ """Pousse un ♥ au hub (action « add » ou « remove ») — SYNCHRONE.
	41	+
	42	+ C'est l'action utilisateur : on attend la réponse du hub (timeout 6 s)
	43	+ pour que le GET qui suit reflète l'état réel. True si le hub a accepté.
	44	+ """
	45	+ if not ka_id or not str(ka_id).startswith("ka-"):
	46	+ return False # compte legacy non relié au hub
	47	+ ts = int(time.time())
	48	+ sig = _sig(ka_id, ts)
	49	+ if not sig:
	50	+ return False
	51	+ try:
	52	+ r = requests.post(f"{KA_HUB_URL}/api/sso/favorites", timeout=6, json={
	53	+ "client_id": CLIENT_ID, "ka_id": ka_id,
	54	+ "ts": str(ts), "sig": sig,
	55	+ "action": action, "item": item,
	56	+ })
	57	+ return r.status_code == 200
	58	+ except Exception:
	59	+ return False
	60	+
	61	+
	62	+def hub_list(ka_id: str) -> list:
	63	+ """Favoris immo-ka du membre, lus du hub (GET signé, timeout 5 s).
	64	+
	65	+ Cache mémoire 30 s par ka_id ; [] sur toute erreur (réseau, 401, 5xx…)
	66	+ — l'erreur n'est PAS mise en cache pour réessayer au prochain appel.
	67	+ """
	68	+ if not ka_id:
	69	+ return []
	70	+ now = time.time()
	71	+ with _lock:
	72	+ hit = _cache.get(ka_id)
	73	+ if hit and now - hit[0] < LIST_TTL:
	74	+ return hit[1]
	75	+ ts = int(now)
	76	+ sig = _sig(ka_id, ts)
	77	+ if not sig:
	78	+ return []
	79	+ try:
	80	+ r = requests.get(
	81	+ f"{KA_HUB_URL}/api/sso/favorites",
	82	+ params={"client_id": CLIENT_ID, "ka_id": ka_id,
	83	+ "ts": ts, "sig": sig},
	84	+ timeout=5)
	85	+ if r.status_code != 200:
	86	+ return []
	87	+ favs = r.json().get("favorites")
	88	+ if not isinstance(favs, list):
	89	+ return []
	90	+ except Exception:
	91	+ return []
	92	+ with _lock:
	93	+ _cache[ka_id] = (now, favs)
	94	+ return favs
	95	+
	96	+
	97	+def invalidate(ka_id: str) -> None:
	98	+ """Invalide le cache de hub_list après un toggle (état frais au prochain GET)."""
	99	+ with _lock:
	100	+ _cache.pop(ka_id, None)

added immoka/hubprofile.py +79 −0

		`@@ -0,0 +1,79 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# hubprofile.py : profil membre lu depuis le HUB Groupe KA (groupe-ka.com)
	5	+# Le hub est LA source de vérité du profil (bio, ville, emploi, entreprise,
	6	+# site web, réseaux sociaux, photo, statut, profil public) — l'édition se
	7	+# fait sur groupe-ka.com/compte, Immo·Ka ne fait qu'afficher.
	8	+# GET {hub}/api/sso/profile?client_id=immo-ka&ka_id=…&ts=…&sig=…
	9	+# avec sig = HMAC-SHA256(KA_SSO_SECRET, "immo-ka.<ka_id>.<ts>") en hex
	10	+# (même secret que le SSO). Cache mémoire 60 s ; None sur toute erreur
	11	+# (réseau, 401, 404 : vieux compte non relié) -> l'appelant retombe sur
	12	+# les données locales.
	13	+# -----------------------------------------------------------------------------
	14	+from __future__ import annotations
	15	+
	16	+import hashlib
	17	+import hmac
	18	+import os
	19	+import threading
	20	+import time
	21	+from datetime import datetime, timezone
	22	+
	23	+import requests
	24	+
	25	+KA_HUB_URL = os.environ.get("KA_HUB_URL", "https://www.groupe-ka.com").rstrip("/")
	26	+CLIENT_ID = "immo-ka"
	27	+CACHE_TTL = 60 # secondes
	28	+TIMEOUT = 5 # secondes
	29	+
	30	+_cache: dict[str, tuple[float, dict \| None]] = {}
	31	+_lock = threading.Lock()
	32	+
	33	+
	34	+def fetch_hub_profile(ka_id: str) -> dict \| None:
	35	+ """Profil du membre au hub Groupe KA, ou None (inconnu ou injoignable)."""
	36	+ secret = os.environ.get("KA_SSO_SECRET")
	37	+ if not secret or not ka_id:
	38	+ return None
	39	+ now = time.time()
	40	+ with _lock:
	41	+ hit = _cache.get(ka_id)
	42	+ if hit and now - hit[0] < CACHE_TTL:
	43	+ return hit[1]
	44	+ data: dict \| None = None
	45	+ try:
	46	+ ts = int(now)
	47	+ sig = hmac.new(secret.encode(), f"{CLIENT_ID}.{ka_id}.{ts}".encode(),
	48	+ hashlib.sha256).hexdigest()
	49	+ r = requests.get(
	50	+ f"{KA_HUB_URL}/api/sso/profile",
	51	+ params={"client_id": CLIENT_ID, "ka_id": ka_id,
	52	+ "ts": ts, "sig": sig},
	53	+ timeout=TIMEOUT)
	54	+ if r.status_code == 200:
	55	+ data = r.json()
	56	+ if not isinstance(data, dict):
	57	+ return None
	58	+ elif r.status_code != 404:
	59	+ return None # erreur transitoire (401, 5xx…) : pas de cache
	60	+ except Exception:
	61	+ return None # réseau/JSON : pas de cache
	62	+ with _lock:
	63	+ _cache[ka_id] = (now, data) # 200 -> data ; 404 -> None (négatif)
	64	+ return data
	65	+
	66	+
	67	+def to_epoch(v) -> float \| None:
	68	+ """created_at du hub (epoch OU chaîne ISO) -> epoch secondes, sinon None."""
	69	+ if isinstance(v, (int, float)):
	70	+ return float(v)
	71	+ if isinstance(v, str) and v:
	72	+ try:
	73	+ dt = datetime.fromisoformat(v.replace("Z", "+00:00"))
	74	+ if dt.tzinfo is None: # chaîne naïve du hub = UTC
	75	+ dt = dt.replace(tzinfo=timezone.utc)
	76	+ return dt.timestamp()
	77	+ except ValueError:
	78	+ return None
	79	+ return None

added immoka/imgaudit.py +293 −0

		`@@ -0,0 +1,293 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# imgaudit.py : qualité des images d'annonces.
	5	+#
	6	+# 1) clean_gallery(urls) — nettoyage STATIQUE (sans réseau), appliqué par
	7	+# PropertyListing.finalize() : URLs invalides, placeholders connus des
	8	+# portails (« photo à venir », logos), doublons (y compris la même photo
	9	+# en deux tailles).
	10	+# 2) run_batch(...) — audit RÉSEAU budgété des photos de couverture : lien
	11	+# mort (4xx/5xx/timeout), image minuscule/pixellisée (dimensions décodées
	12	+# de l'en-tête JPEG/PNG/WebP/GIF), fichier corrompu. Résultats en cache
	13	+# (table image_audit, TTL 30 jours). Une couverture morte est retirée et
	14	+# la première image VALIDE de la galerie est promue ; une annonce sans
	15	+# aucune image valide est marquée (details.needs_image_review) — le
	16	+# frontend affiche alors l'image de secours par type de bien.
	17	+# -----------------------------------------------------------------------------
	18	+from __future__ import annotations
	19	+
	20	+import json
	21	+import re
	22	+import sqlite3
	23	+import struct
	24	+import time
	25	+from concurrent.futures import ThreadPoolExecutor
	26	+
	27	+import requests
	28	+
	29	+AUDIT_TTL = 30 * 86400 # re-vérification d'une URL après 30 jours
	30	+MIN_WIDTH, MIN_HEIGHT = 250, 160 # sous ces dimensions : miniature inutilisable
	31	+MIN_BYTES = 3_000 # fichier suspicieusement petit (icône/placeholder)
	32	+TIMEOUT = 10
	33	+UA = ("Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 "
	34	+ "(KHTML, like Gecko) Chrome/126 Safari/537.36 ImmoKaBot/1.0")
	35	+
	36	+# motifs de placeholders/logos des portails (jamais une photo de propriété).
	37	+# ⚠ default/defaut/logo sont ANCRÉS sur le nom de fichier : un segment de
	38	+# chemin comme Cloudinary « t_default_size/ » n'est PAS un placeholder
	39	+# (bug payé : toutes les galeries Ubee vidées par « default[-_.] »).
	40	+_PLACEHOLDER_RE = re.compile(
	41	+ r"placeholder\|no[-_]?photo\|nophoto\|photo[-_]?a[-_]?venir\|coming[-_]?soon\|"
	42	+ r"missing\|awaiting\|shadow_listing\|image[-_]?indisponible\|no[-_]?image\|"
	43	+ r"/(?:default\|defaut\|logo)[^/]*\.(?:jpe?g\|png\|webp\|gif\|svg)(?:\?\|$)", re.I)
	44	+
	45	+_SIZE_VARIANT_RE = re.compile(r"-(?:sm\|md\|lg\|xl\|thumb\|small\|medium\|large)(?=\.\w+$)")
	46	+
	47	+# handlers dynamiques : la photo est identifiée par la QUERYSTRING (propId/seq,
	48	+# id…), pas par le chemin — ex. yoamo.immo/ALSPicture.axd?propId=…&seq=N,
	49	+# mediaserver.centris.ca/media.ashx?id=… On ne retire que les params de taille.
	50	+_DYNAMIC_EXT = (".axd", ".ashx", ".php", ".aspx", ".cfm")
	51	+_SIZE_PARAM_RE = re.compile(r"&(?:w\|h\|width\|height\|size\|sm\|scale\|quality)=[^&]*", re.I)
	52	+
	53	+
	54	+def _canon(url: str) -> str:
	55	+ """Clé de déduplication : ignore la variante de taille et la querystring
	56	+ de redimensionnement pour attraper la même photo en deux formats."""
	57	+ path, _, query = url.partition("?")
	58	+ if query and path.lower().endswith(_DYNAMIC_EXT):
	59	+ params = _SIZE_PARAM_RE.sub("", "&" + query.replace("&", "&")).lstrip("&")
	60	+ return f"{path}?{params}".lower()
	61	+ return _SIZE_VARIANT_RE.sub("", path).lower()
	62	+
	63	+
	64	+def clean_gallery(urls: list[str]) -> list[str]:
	65	+ """Nettoyage statique d'une galerie : URLs http(s) uniquement, placeholders
	66	+ retirés, doublons (même photo, autre taille) dédupliqués, ordre préservé."""
	67	+ out: list[str] = []
	68	+ seen: set[str] = set()
	69	+ for u in urls or []:
	70	+ if not isinstance(u, str):
	71	+ continue
	72	+ u = u.strip()
	73	+ if not u.lower().startswith(("http://", "https://")):
	74	+ continue
	75	+ if _PLACEHOLDER_RE.search(u):
	76	+ continue
	77	+ key = _canon(u)
	78	+ if key in seen:
	79	+ continue
	80	+ seen.add(key)
	81	+ out.append(u)
	82	+ return out
	83	+
	84	+
	85	+# ---------------------------------------------------------------------------
	86	+# Décodage des dimensions depuis les premiers octets (sans télécharger tout)
	87	+# ---------------------------------------------------------------------------
	88	+
	89	+def image_size(data: bytes) -> tuple[int, int] \| None:
	90	+ """(largeur, hauteur) depuis l'en-tête PNG/GIF/WebP/JPEG, None si indécodable."""
	91	+ if len(data) < 26:
	92	+ return None
	93	+ if data[:8] == b"\x89PNG\r\n\x1a\n":
	94	+ w, h = struct.unpack(">II", data[16:24])
	95	+ return w, h
	96	+ if data[:6] in (b"GIF87a", b"GIF89a"):
	97	+ w, h = struct.unpack("<HH", data[6:10])
	98	+ return w, h
	99	+ if data[:4] == b"RIFF" and data[8:12] == b"WEBP":
	100	+ if data[12:16] == b"VP8 " and len(data) >= 30:
	101	+ w, h = struct.unpack("<HH", data[26:30])
	102	+ return w & 0x3FFF, h & 0x3FFF
	103	+ if data[12:16] == b"VP8L" and len(data) >= 25:
	104	+ bits = struct.unpack("<I", data[21:25])[0]
	105	+ return (bits & 0x3FFF) + 1, ((bits >> 14) & 0x3FFF) + 1
	106	+ if data[12:16] == b"VP8X" and len(data) >= 30:
	107	+ w = int.from_bytes(data[24:27], "little") + 1
	108	+ h = int.from_bytes(data[27:30], "little") + 1
	109	+ return w, h
	110	+ if data[:2] == b"\xff\xd8": # JPEG : chercher le SOF
	111	+ i = 2
	112	+ while i + 9 < len(data):
	113	+ if data[i] != 0xFF:
	114	+ i += 1
	115	+ continue
	116	+ marker = data[i + 1]
	117	+ if marker in (0xC0, 0xC1, 0xC2, 0xC3, 0xC5, 0xC6, 0xC7,
	118	+ 0xC9, 0xCA, 0xCB, 0xCD, 0xCE, 0xCF):
	119	+ h, w = struct.unpack(">HH", data[i + 5:i + 9])
	120	+ return w, h
	121	+ seg_len = struct.unpack(">H", data[i + 2:i + 4])[0]
	122	+ i += 2 + seg_len
	123	+ return None
	124	+
	125	+
	126	+def check_url(url: str) -> dict:
	127	+ """Vérifie une URL d'image : {ok, status, width, height, bytes, reason}.
	128	+
	129	+ ⚠ Verdict « morte » UNIQUEMENT sur preuve solide (404/410) : un 403/429 est
	130	+ presque toujours du rate-limiting ou de l'anti-hotlink du CDN (bug payé :
	131	+ ~6 000 galeries DuProprio retirées à tort). En cas de doute on garde
	132	+ l'image — le repli onError du frontend couvre les rares vraies mortes."""
	133	+ try:
	134	+ r = requests.get(url, headers={"User-Agent": UA, "Range": "bytes=0-65535"},
	135	+ timeout=TIMEOUT, stream=True)
	136	+ status = r.status_code
	137	+ if status in (404, 410):
	138	+ return {"ok": 0, "status": status, "reason": "http"}
	139	+ if status >= 400:
	140	+ return {"ok": 1, "status": status, "reason": "non_verifiable"}
	141	+ data = next(r.iter_content(65536), b"") or b""
	142	+ r.close()
	143	+ total = int((r.headers.get("Content-Range") or "/0").split("/")[-1] or 0) \
	144	+ or int(r.headers.get("Content-Length") or 0) or len(data)
	145	+ size = image_size(data)
	146	+ if size is None:
	147	+ ctype = (r.headers.get("Content-Type") or "").lower()
	148	+ if "image" not in ctype:
	149	+ return {"ok": 0, "status": status, "bytes": total, "reason": "format"}
	150	+ # image valide mais en-tête non décodé (format exotique) : on tolère
	151	+ return {"ok": 1, "status": status, "bytes": total}
	152	+ w, h = size
	153	+ if w < MIN_WIDTH or h < MIN_HEIGHT:
	154	+ return {"ok": 0, "status": status, "width": w, "height": h,
	155	+ "bytes": total, "reason": "minuscule"}
	156	+ if total and total < MIN_BYTES:
	157	+ return {"ok": 0, "status": status, "width": w, "height": h,
	158	+ "bytes": total, "reason": "poids_suspect"}
	159	+ return {"ok": 1, "status": status, "width": w, "height": h, "bytes": total}
	160	+ except requests.RequestException:
	161	+ # réseau/timeout : non concluant — ne jamais retirer sur un doute
	162	+ return {"ok": 1, "status": 0, "reason": "non_verifiable"}
	163	+
	164	+
	165	+# ---------------------------------------------------------------------------
	166	+# Audit budgété des couvertures (+ galeries courtes) avec cache BD
	167	+# ---------------------------------------------------------------------------
	168	+
	169	+def _ensure_table(con: sqlite3.Connection) -> None:
	170	+ con.execute("""CREATE TABLE IF NOT EXISTS image_audit (
	171	+ url TEXT PRIMARY KEY,
	172	+ ok INTEGER,
	173	+ status INTEGER,
	174	+ width INTEGER,
	175	+ height INTEGER,
	176	+ bytes INTEGER,
	177	+ reason TEXT,
	178	+ checked_at REAL
	179	+ )""")
	180	+ con.commit()
	181	+
	182	+
	183	+def _cached(con: sqlite3.Connection, url: str) -> dict \| None:
	184	+ r = con.execute("SELECT ok, reason, checked_at FROM image_audit WHERE url=?",
	185	+ (url,)).fetchone()
	186	+ if r and time.time() - (r["checked_at"] or 0) < AUDIT_TTL:
	187	+ return {"ok": r["ok"], "reason": r["reason"]}
	188	+ return None
	189	+
	190	+
	191	+def _store(con: sqlite3.Connection, url: str, res: dict) -> None:
	192	+ con.execute(
	193	+ "INSERT INTO image_audit (url, ok, status, width, height, bytes, reason,"
	194	+ " checked_at) VALUES (?,?,?,?,?,?,?,?)"
	195	+ " ON CONFLICT(url) DO UPDATE SET ok=excluded.ok, status=excluded.status,"
	196	+ " width=excluded.width, height=excluded.height, bytes=excluded.bytes,"
	197	+ " reason=excluded.reason, checked_at=excluded.checked_at",
	198	+ (url, res.get("ok"), res.get("status"), res.get("width"),
	199	+ res.get("height"), res.get("bytes"), res.get("reason"), time.time()))
	200	+
	201	+
	202	+def audit_listing(con: sqlite3.Connection, uid: str, images: list[str],
	203	+ details: dict, pool: ThreadPoolExecutor) -> tuple[list[str], dict, int]:
	204	+ """Vérifie la couverture (et remonte la 1re image valide en tête).
	205	+
	206	+ Vérifie au plus les 4 premières images ; les mortes sont retirées de la
	207	+ galerie. Retourne (nouvelle galerie, details, nb de vérifications réseau)."""
	208	+ checked = 0
	209	+ good_idx = None
	210	+ dead: set[int] = set()
	211	+ for i, url in enumerate(images[:4]):
	212	+ res = _cached(con, url)
	213	+ if res is None:
	214	+ res = check_url(url)
	215	+ _store(con, url, res)
	216	+ checked += 1
	217	+ if res.get("ok"):
	218	+ good_idx = i
	219	+ break
	220	+ dead.add(i)
	221	+ new_images = [u for i, u in enumerate(images) if i not in dead]
	222	+ details = dict(details)
	223	+ if good_idx is None and images:
	224	+ # aucune image valide parmi les premières : re-vérification demandée,
	225	+ # le frontend applique l'image de secours par type de bien
	226	+ details["needs_image_review"] = True
	227	+ else:
	228	+ details.pop("needs_image_review", None)
	229	+ return new_images, details, checked
	230	+
	231	+
	232	+def run_batch(limit: int = 2000, workers: int = 8) -> dict:
	233	+ """Audit réseau budgété : les annonces publiées jamais auditées d'abord.
	234	+
	235	+ Appelé après chaque synchronisation (ingest.watch) ; relancer avec un gros
	236	+ `limit` pour un rattrapage complet. Idempotent grâce au cache par URL."""
	237	+ from . import db
	238	+ con = db.connect()
	239	+ _ensure_table(con)
	240	+ rows = con.execute(
	241	+ "SELECT uid, images, details FROM listings"
	242	+ " WHERE active=1 AND dup_hidden=0 AND images IS NOT NULL AND images!='[]'"
	243	+ " AND json_extract(COALESCE(details,'{}'), '$.img_audited') IS NULL"
	244	+ " LIMIT ?", (limit,)).fetchall()
	245	+ checked = removed = flagged = 0
	246	+
	247	+ def _work(row):
	248	+ images = json.loads(row["images"] or "[]")
	249	+ details = json.loads(row["details"] or "{}")
	250	+ # les URLs sont vérifiées séquentiellement par annonce ; le parallélisme
	251	+ # est au niveau des annonces (une connexion BD par worker serait fragile,
	252	+ # donc le réseau seul est parallèle : cache lu/écrit dans le fil principal)
	253	+ return row["uid"], images, details
	254	+
	255	+ with ThreadPoolExecutor(max_workers=workers) as pool:
	256	+ futures = []
	257	+ for row in rows:
	258	+ uid, images, details = _work(row)
	259	+ futures.append((uid, images, details))
	260	+ # traitement principal (cache BD dans ce fil, réseau via check_url —
	261	+ # parallélisé par lots d'URLs de couverture inconnues)
	262	+ unknown = []
	263	+ for uid, images, details in futures:
	264	+ for u in images[:4]:
	265	+ if _cached(con, u) is None:
	266	+ unknown.append(u)
	267	+ unknown = list(dict.fromkeys(unknown))
	268	+ # commits par tranches : ne JAMAIS tenir le verrou d'écriture pendant
	269	+ # tout l'audit (des dizaines de minutes) — les syncs/le web écrivent aussi
	270	+ for url, res in zip(unknown, pool.map(check_url, unknown)):
	271	+ _store(con, url, res)
	272	+ checked += 1
	273	+ if checked % 400 == 0:
	274	+ con.commit()
	275	+ con.commit()
	276	+ done = 0
	277	+ for uid, images, details in futures:
	278	+ new_images, new_details, _ = audit_listing(con, uid, images, details,
	279	+ pool)
	280	+ new_details["img_audited"] = int(time.time())
	281	+ if new_details.get("needs_image_review"):
	282	+ flagged += 1
	283	+ removed += len(images) - len(new_images)
	284	+ con.execute("UPDATE listings SET images=?, details=? WHERE uid=?",
	285	+ (json.dumps(new_images, ensure_ascii=False),
	286	+ json.dumps(new_details, ensure_ascii=False), uid))
	287	+ done += 1
	288	+ if done % 400 == 0:
	289	+ con.commit()
	290	+ con.commit()
	291	+ con.close()
	292	+ return {"annonces": len(rows), "urls_verifiees": checked,
	293	+ "images_retirees": removed, "sans_image_valide": flagged}

added immoka/ingest.py +119 −0

		`@@ -0,0 +1,119 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# ingest.py : pipeline d'ingestion — exécute les connecteurs et synchronise
	5	+# la base (ajouts / mises à jour / retraits) = contenu toujours à jour
	6	+# -----------------------------------------------------------------------------
	7	+from __future__ import annotations
	8	+
	9	+import sys
	10	+import time
	11	+import traceback
	12	+
	13	+from . import db
	14	+from .connectors import CONNECTORS
	15	+
	16	+
	17	+def run(sources: list[str] \| None = None) -> list[dict]:
	18	+ """Exécute l'ingestion pour toutes les sources (ou celles demandées)."""
	19	+ con = db.connect()
	20	+ results = []
	21	+ targets = sources or list(CONNECTORS.keys())
	22	+ for sid in targets:
	23	+ cls = CONNECTORS.get(sid)
	24	+ if cls is None:
	25	+ print(f"[immo-ka] connecteur inconnu : {sid}", file=sys.stderr)
	26	+ continue
	27	+ t0 = time.time()
	28	+ print(f"[immo-ka] sync {sid} ...")
	29	+ try:
	30	+ listings = cls().fetch()
	31	+ finalized, dropped = [], 0
	32	+ for lst in listings:
	33	+ try:
	34	+ finalized.append(lst.finalize())
	35	+ except Exception: # une annonce malformée ne bloque pas la source
	36	+ dropped += 1
	37	+ try:
	38	+ # garde géographique : coordonnées fournies par la source mais
	39	+ # incompatibles avec la ville annoncée -> annulées (le géocodeur
	40	+ # rigoureux prendra le relais). Cache seulement, aucun réseau.
	41	+ from . import geocode
	42	+ bad = geocode.strip_bad_source_coords(con, finalized)
	43	+ if bad:
	44	+ print(f"[immo-ka] {bad} coordonnée(s) source incohérente(s) rejetée(s)")
	45	+ except Exception:
	46	+ traceback.print_exc()
	47	+ stats = db.sync_source(con, sid, finalized)
	48	+ stats["seconds"] = round(time.time() - t0, 1)
	49	+ if dropped:
	50	+ stats["dropped"] = dropped
	51	+ if stats.get("alert"):
	52	+ print(f"[immo-ka] ⚠ ALERTE {sid} : {stats['alert']}")
	53	+ print(f"[immo-ka] {stats}")
	54	+ results.append(stats)
	55	+ except Exception as exc: # robustesse : une source ne bloque pas les autres
	56	+ db.log_failure(con, sid, f"{exc}")
	57	+ traceback.print_exc()
	58	+ results.append({"source": sid, "error": str(exc)})
	59	+ # recalcule la déduplication (pré-calculée pour des lectures instantanées)
	60	+ try:
	61	+ hidden = db.refresh_dedup(con)
	62	+ print(f"[immo-ka] dédup: {hidden} doublon(s) masqué(s) "
	63	+ "(sous-agences Centris + adresse inter-sources)")
	64	+ except Exception:
	65	+ traceback.print_exc()
	66	+ # contrôle qualité : score de complétude, cohérence immobilière, seuil de
	67	+ # publication (quarantaine) et champs dérivés (prix/pi², transaction)
	68	+ try:
	69	+ from . import quality
	70	+ q = quality.refresh(con)
	71	+ print(f"[immo-ka] qualité: {q['publiees']} publiée(s), "
	72	+ f"{q['quarantaine']} en quarantaine, "
	73	+ f"{q['recalculees']} recalculée(s)")
	74	+ except Exception:
	75	+ traceback.print_exc()
	76	+ # statistiques du planificateur SQLite : sans elles, les requêtes bbox
	77	+ # de la carte (Ka Maps) n'utilisent pas idx_listings_geo
	78	+ try:
	79	+ con.execute("PRAGMA optimize")
	80	+ except Exception:
	81	+ pass
	82	+ con.close()
	83	+ return results
	84	+
	85	+
	86	+def watch(interval_seconds: int = 3600) -> None:
	87	+ """Boucle de synchronisation périodique (équivalent webhook, via PM2/cron).
	88	+
	89	+ Après chaque synchronisation, l'enrichissement continu de la carte
	90	+ (Ka Maps) : géocodage EN LOT des nouvelles adresses (Adresses Québec),
	91	+ puis appariement Vrai-Prix local (estimations + coordonnées du rôle)
	92	+ quand data/vraiprix.db (ou VRAIPRIX_DB) est disponible.
	93	+ """
	94	+ while True:
	95	+ run()
	96	+ try: # nouvelles adresses → coordonnées (cache : quasi gratuit ensuite)
	97	+ from . import geocode
	98	+ # audit de cohérence d'abord : les fiches mal localisées (rue
	99	+ # homonyme, geo source erroné) sont remises en file, puis le lot
	100	+ # les re-géocode rigoureusement (budget Nominatim borné par passe)
	101	+ geocode.run_audit(nominatim_budget=50)
	102	+ geocode.run_batch()
	103	+ except Exception as exc:
	104	+ print(f"[immo-ka] geocode: erreur non bloquante: {exc}", file=sys.stderr)
	105	+ try: # audit budgété des images (liens morts, minuscules, corrompues)
	106	+ from . import imgaudit
	107	+ ia = imgaudit.run_batch(limit=2000)
	108	+ print(f"[immo-ka] images: {ia['urls_verifiees']} URL vérifiée(s), "
	109	+ f"{ia['images_retirees']} retirée(s), "
	110	+ f"{ia['sans_image_valide']} annonce(s) sans image valide")
	111	+ except Exception as exc:
	112	+ print(f"[immo-ka] imgaudit: erreur non bloquante: {exc}", file=sys.stderr)
	113	+ try: # taux hypothécaires — collecte espacée (IMMOKA_MORTGAGE_INTERVAL_MIN)
	114	+ from .mortgage import scheduler as mortgage_scheduler
	115	+ mortgage_scheduler.maybe_run()
	116	+ except Exception as exc:
	117	+ print(f"[immo-ka] mortgage: erreur non bloquante: {exc}", file=sys.stderr)
	118	+ print(f"[immo-ka] prochaine synchronisation dans {interval_seconds // 60} min")
	119	+ time.sleep(interval_seconds)

added immoka/kaid.py +449 −0

		`@@ -0,0 +1,449 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Groupe KA — kaid.py : client KA ID v2 (personnalisation) pour les satellites.
	3	+# SOURCE CANONIQUE : ka-ui.git/kaid/kaid.py — copié dans le paquet backend de
	4	+# chaque app (louka/, jobka/, sortika/, …) par sync-kaid.sh. Ne pas diverger :
	5	+# corriger ICI puis redistribuer.
	6	+#
	7	+# Rôle : relier l'app au feature store du hub (groupe-ka.com) —
	8	+# · track() journal d'interactions (serveur, fil d'exécution dédié)
	9	+# · fetch_prefs() profil de préférences appris (cache 90 s, fail-open)
	10	+# · rerank() reclassement personnalisé APRÈS la pertinence de base
	11	+# · build_router() routes /api/kaid/* (événements client, masquage,
	12	+# recherches sauvegardées)
	13	+#
	14	+# Contrat s2s (identique à hubfav/hubprofile) : HMAC-SHA256 du secret SSO
	15	+# partagé — sig = HMAC(KA_SSO_SECRET, f"{CLIENT_ID}.{ka_id}.{ts}").
	16	+# Config .env : KA_SSO_SECRET (déjà présent), KA_HUB_URL (optionnel).
	17	+#
	18	+# Principes : la connexion n'est JAMAIS requise ; sans profil ou à la moindre
	19	+# erreur réseau → classement de base inchangé (fail-open). La personnalisation
	20	+# ne remplace pas la pertinence : elle reclasse (blend) et n'écrase jamais
	21	+# l'intention de la session (les dimensions explicitement filtrées par la
	22	+# requête courante sont ignorées dans le score).
	23	+# -----------------------------------------------------------------------------
	24	+from __future__ import annotations
	25	+
	26	+import hashlib
	27	+import hmac
	28	+import json
	29	+import os
	30	+import threading
	31	+import time
	32	+
	33	+import requests
	34	+from fastapi import APIRouter, HTTPException, Request
	35	+from pydantic import BaseModel
	36	+
	37	+KA_HUB_URL = os.environ.get("KA_HUB_URL", "https://www.groupe-ka.com").rstrip("/")
	38	+CLIENT_ID = os.environ.get("KA_CLIENT_ID", "") # fixé par init() dans web.py
	39	+
	40	+PREFS_TTL = 90 # secondes de cache du profil
	41	+TIMEOUT = 5 # secondes par appel hub
	42	+LOCATION_DIMS = {"city", "region", "sector", "quartier", "ville",
	43	+ "location", "neighborhood"}
	44	+LANGUAGE_DIMS = {"language", "langue"}
	45	+PRICE_DIMS = {"price", "rent", "salary", "salary_year", "price_min"}
	46	+
	47	+# Événements acceptés depuis le navigateur (le reste vient du serveur).
	48	+CLIENT_EVENT_TYPES = {
	49	+ "click", "impression", "detail_dwell", "scroll_depth", "return_visit",
	50	+ "share", "compare", "external_click", "map_open", "map_marker_click",
	51	+ "alert_open",
	52	+}
	53	+
	54	+_prefs_cache: dict[str, tuple[float, dict \| None]] = {}
	55	+_seen_searches: dict[str, float] = {} # anti-doublon des recherches (120 s)
	56	+_lock = threading.Lock()
	57	+
	58	+
	59	+def init(client_id: str) -> None:
	60	+ """À appeler une fois au démarrage de l'app (web.py)."""
	61	+ global CLIENT_ID
	62	+ CLIENT_ID = client_id
	63	+
	64	+
	65	+def _sig(ka_id: str, ts: int) -> str \| None:
	66	+ secret = os.environ.get("KA_SSO_SECRET")
	67	+ if not secret or not CLIENT_ID:
	68	+ return None
	69	+ return hmac.new(secret.encode(),
	70	+ f"{CLIENT_ID}.{ka_id}.{ts}".encode(),
	71	+ hashlib.sha256).hexdigest()
	72	+
	73	+
	74	+def _signed_params(ka_id: str) -> dict \| None:
	75	+ ts = int(time.time())
	76	+ sig = _sig(ka_id, ts)
	77	+ if not sig:
	78	+ return None
	79	+ return {"client_id": CLIENT_ID, "ka_id": ka_id, "ts": str(ts), "sig": sig}
	80	+
	81	+
	82	+def _ka_id_of(user) -> str \| None:
	83	+ """Extrait un ka_id exploitable d'un dict utilisateur (ou None)."""
	84	+ if not user:
	85	+ return None
	86	+ ka = (user.get("ka_id") or "").strip() if isinstance(user, dict) else ""
	87	+ return ka if ka.startswith("ka-") else None
	88	+
	89	+
	90	+# ---------------------------------------------------------------- événements
	91	+
	92	+def _post_events(ka_id: str, events: list[dict]) -> None:
	93	+ p = _signed_params(ka_id)
	94	+ if not p:
	95	+ return
	96	+ try:
	97	+ requests.post(f"{KA_HUB_URL}/api/sso/events", timeout=TIMEOUT,
	98	+ json={**p, "events": events})
	99	+ except Exception:
	100	+ pass # best-effort : jamais bloquant, jamais fatal
	101	+
	102	+
	103	+def track(user, etype: str, *, entity_type: str \| None = None,
	104	+ entity_id: str \| None = None, query: str \| None = None,
	105	+ filters: dict \| None = None, position: int \| None = None,
	106	+ features: dict \| None = None, dwell_ms: int \| None = None,
	107	+ session_id: str \| None = None) -> None:
	108	+ """Journalise un événement au hub (fil dédié, zéro latence ajoutée).
	109	+ No-op si l'utilisateur n'est pas connecté via KA ID."""
	110	+ ka_id = _ka_id_of(user)
	111	+ if not ka_id:
	112	+ return
	113	+ if etype == "search":
	114	+ # anti-rafale : la même recherche (mêmes filtres) < 120 s n'est
	115	+ # journalisée qu'une fois — une SPA relance l'API à chaque frappe.
	116	+ key = ka_id + "\|" + hashlib.sha1(
	117	+ json.dumps([query, filters], sort_keys=True, default=str).encode()
	118	+ ).hexdigest()
	119	+ now = time.time()
	120	+ with _lock:
	121	+ if now - _seen_searches.get(key, 0) < 120:
	122	+ return
	123	+ _seen_searches[key] = now
	124	+ if len(_seen_searches) > 2000:
	125	+ cutoff = now - 300
	126	+ for k in [k for k, t in _seen_searches.items() if t < cutoff]:
	127	+ del _seen_searches[k]
	128	+ ev: dict = {"type": etype}
	129	+ if entity_type: ev["entity_type"] = entity_type
	130	+ if entity_id: ev["entity_id"] = str(entity_id)
	131	+ if query: ev["query"] = str(query)[:200]
	132	+ if filters: ev["filters"] = filters
	133	+ if position is not None: ev["position"] = int(position)
	134	+ if features: ev["features"] = features
	135	+ if dwell_ms is not None: ev["dwell_ms"] = int(dwell_ms)
	136	+ if session_id: ev["session_id"] = str(session_id)[:60]
	137	+ threading.Thread(target=_post_events, args=(ka_id, [ev]), daemon=True).start()
	138	+
	139	+
	140	+# ------------------------------------------------------------------ profil
	141	+
	142	+def fetch_prefs(ka_id: str \| None) -> dict \| None:
	143	+ """Profil de personnalisation du membre (cache 90 s). None si non
	144	+ connecté, non configuré ou hub injoignable — l'appelant retombe alors
	145	+ sur le classement de base."""
	146	+ if not ka_id or not str(ka_id).startswith("ka-"):
	147	+ return None
	148	+ now = time.time()
	149	+ with _lock:
	150	+ hit = _prefs_cache.get(ka_id)
	151	+ if hit and now - hit[0] < PREFS_TTL:
	152	+ return hit[1]
	153	+ data: dict \| None = None
	154	+ p = _signed_params(ka_id)
	155	+ if p:
	156	+ try:
	157	+ r = requests.get(f"{KA_HUB_URL}/api/sso/prefs", params=p,
	158	+ timeout=TIMEOUT)
	159	+ if r.status_code == 200:
	160	+ data = r.json()
	161	+ except Exception:
	162	+ data = None
	163	+ with _lock:
	164	+ _prefs_cache[ka_id] = (now, data)
	165	+ if len(_prefs_cache) > 500:
	166	+ for k in list(_prefs_cache)[:100]:
	167	+ del _prefs_cache[k]
	168	+ return data
	169	+
	170	+
	171	+def invalidate_prefs(ka_id: str \| None) -> None:
	172	+ if not ka_id:
	173	+ return
	174	+ with _lock:
	175	+ _prefs_cache.pop(ka_id, None)
	176	+
	177	+
	178	+# ---------------------------------------------------------------- reranking
	179	+
	180	+def _norm(v) -> str:
	181	+ return str(v).strip().lower()
	182	+
	183	+
	184	+def personal_score(feats: dict, app_profile: dict, global_profile: dict,
	185	+ active_dims: set[str]) -> tuple[float \| None, list[str]]:
	186	+ """Score personnel [0,1] d'une annonce, ou None si le profil ne couvre
	187	+ aucune de ses caractéristiques. `active_dims` = dimensions explicitement
	188	+ filtrées par la requête courante (intention de session > long terme)."""
	189	+ dims = app_profile.get("dims") or {}
	190	+ ranges = app_profile.get("ranges") or {}
	191	+ gl = (global_profile or {}).get("location") or {}
	192	+ num = 0.0
	193	+ den = 0.0
	194	+ reasons: list[str] = []
	195	+ for dim, val in (feats or {}).items():
	196	+ if val is None or dim in active_dims:
	197	+ continue
	198	+ if isinstance(val, bool):
	199	+ val = str(val)
	200	+ if isinstance(val, (int, float)):
	201	+ r = ranges.get(dim)
	202	+ if r and r.get("n", 0) >= 5:
	203	+ p25, p75 = r["p25"], r["p75"]
	204	+ iqr = max(p75 - p25, abs(r.get("p50", 0)) * 0.1, 1.0)
	205	+ if p25 <= val <= p75:
	206	+ aff = 1.0
	207	+ elif p25 - 1.5 * iqr <= val <= p75 + 1.5 * iqr:
	208	+ aff = 0.3
	209	+ else:
	210	+ aff = -0.4
	211	+ # poids réduit : une plage numérique seule (prix…) ne doit
	212	+ # jamais suffire à personnaliser (0.6 < seuil den 0.8) —
	213	+ # sinon tout item au « bon prix » score 1.0 et noie les
	214	+ # correspondances réelles (ville, marque, type).
	215	+ w = 0.6
	216	+ num += w * aff
	217	+ den += w
	218	+ if aff == 1.0:
	219	+ reasons.append("MATCH_PRICE_RANGE" if dim in PRICE_DIMS
	220	+ else f"MATCH_{dim.upper()}_RANGE")
	221	+ continue
	222	+ vals = val if isinstance(val, (list, tuple)) else [val]
	223	+ vals = [_norm(v) for v in vals if v not in (None, "")]
	224	+ if not vals:
	225	+ continue
	226	+ d = dims.get(dim)
	227	+ if d:
	228	+ vv = d.get("values") or {}
	229	+ affs = [vv[v] for v in vals if v in vv]
	230	+ if affs:
	231	+ aff = max(affs)
	232	+ w = float(d.get("conf") or 0.5)
	233	+ num += w * aff
	234	+ den += w
	235	+ if aff >= 0.6:
	236	+ reasons.append("MATCH_LOCATION" if dim in LOCATION_DIMS
	237	+ else f"MATCH_{dim.upper()}")
	238	+ if dim in LOCATION_DIMS:
	239	+ gv = gl.get("values") or {}
	240	+ affs = [gv[v] for v in vals if v in gv]
	241	+ if affs and max(affs) > 0:
	242	+ w = 0.6 * float(gl.get("conf") or 0.3)
	243	+ num += w * max(affs)
	244	+ den += w
	245	+ if max(affs) >= 0.6 and "MATCH_LOCATION" not in reasons:
	246	+ reasons.append("MATCH_LOCATION")
	247	+ if dim in LANGUAGE_DIMS:
	248	+ glang = (global_profile or {}).get("language") or {}
	249	+ gv = glang.get("values") or {}
	250	+ affs = [gv[v] for v in vals if v in gv]
	251	+ if affs and max(affs) > 0:
	252	+ w = 0.4 * float(glang.get("conf") or 0.3)
	253	+ num += w * max(affs)
	254	+ den += w
	255	+ if den < 0.8:
	256	+ return None, []
	257	+ score = (num / den + 1.0) / 2.0
	258	+ return max(0.0, min(1.0, score)), reasons[:4]
	259	+
	260	+
	261	+def rerank(items: list, user, *, features_of, uid_of=None,
	262	+ active_dims: set[str] \| None = None, blend: float = 0.35,
	263	+ badge: float = 0.62, max_considered: int = 300,
	264	+ reco_key: str = "ka_reco") -> tuple[list, bool]:
	265	+ """Reclassement personnalisé APRÈS la pertinence de base.
	266	+ · items : liste (dicts) déjà triée par la pertinence de base
	267	+ · features_of : item -> dict de caractéristiques {dim: valeur}
	268	+ · uid_of : item -> identifiant canonique (défaut : item["uid"])
	269	+ · active_dims : dimensions filtrées par la requête (ignorées du score)
	270	+ Retourne (items, personnalisé?). Les annonces masquées (« Pas pour moi »)
	271	+ sont retirées. Annote item[reco_key] = {score, reasons} quand le score
	272	+ personnel est net (badge « Recommandé pour vous » — parcimonieux)."""
	273	+ if uid_of is None:
	274	+ uid_of = lambda it: (it.get("uid") if isinstance(it, dict) else None)
	275	+ ka_id = _ka_id_of(user)
	276	+ if not ka_id or not items:
	277	+ return items, False
	278	+ prefs = fetch_prefs(ka_id)
	279	+ if not prefs:
	280	+ return items, False
	281	+ hidden = set(prefs.get("hidden") or [])
	282	+ if hidden:
	283	+ items = [it for it in items if str(uid_of(it)) not in hidden]
	284	+ if not prefs.get("personalization"):
	285	+ return items, False
	286	+ profile = prefs.get("profile") or {}
	287	+ app_p = profile.get("app")
	288	+ if not app_p or not items:
	289	+ return items, False
	290	+
	291	+ head = items[:max_considered]
	292	+ tail = items[max_considered:]
	293	+ n = len(head)
	294	+ active = active_dims or set()
	295	+ # signaux collaboratifs du hub : co-favoris (item-item) et
	296	+ # recommandations du modèle de matrix factorization (ALS, batch quotidien)
	297	+ similar = {str(s) for s in (app_p.get("similar") or [])}
	298	+ mf = {str(s) for s in (app_p.get("mf") or [])}
	299	+ scored = []
	300	+ badged = 0
	301	+ for i, it in enumerate(head):
	302	+ base = 1.0 - i / max(n, 1)
	303	+ try:
	304	+ p, reasons = personal_score(features_of(it) or {}, app_p,
	305	+ profile.get("global") or {}, active)
	306	+ except Exception:
	307	+ p, reasons = None, []
	308	+ uid = str(uid_of(it))
	309	+ if similar and uid in similar:
	310	+ p = min(1.0, (p if p is not None else 0.55) + 0.25)
	311	+ reasons = (["SIMILAR_USERS"] + reasons)[:4]
	312	+ elif mf and uid in mf:
	313	+ p = min(1.0, (p if p is not None else 0.55) + 0.25)
	314	+ reasons = (["COLLABORATIVE_MODEL"] + reasons)[:4]
	315	+ if p is None:
	316	+ final = (1.0 - blend) * base + blend * 0.5
	317	+ else:
	318	+ final = (1.0 - blend) * base + blend * p
	319	+ if p >= badge and reasons and badged < max(2, n // 8) \
	320	+ and isinstance(it, dict):
	321	+ it[reco_key] = {"score": round(p, 2), "reasons": reasons}
	322	+ badged += 1
	323	+ scored.append((final, i, it))
	324	+ scored.sort(key=lambda t: (-t[0], t[1])) # stable : départage par rang
	325	+ return [it for _, _, it in scored] + tail, True
	326	+
	327	+
	328	+# ------------------------------------------------------- proxys hub (s2s)
	329	+
	330	+def _hub_post(ka_id: str, path: str, payload: dict) -> dict:
	331	+ p = _signed_params(ka_id)
	332	+ if not p:
	333	+ raise HTTPException(503, "KA_SSO_SECRET manquant (voir .env)")
	334	+ try:
	335	+ r = requests.post(f"{KA_HUB_URL}{path}", timeout=TIMEOUT,
	336	+ json={p, payload})
	337	+ return r.json() if r.status_code == 200 else {"error": r.status_code}
	338	+ except Exception:
	339	+ raise HTTPException(502, "hub KA injoignable")
	340	+
	341	+
	342	+def _hub_get(ka_id: str, path: str) -> dict:
	343	+ p = _signed_params(ka_id)
	344	+ if not p:
	345	+ raise HTTPException(503, "KA_SSO_SECRET manquant (voir .env)")
	346	+ try:
	347	+ r = requests.get(f"{KA_HUB_URL}{path}", params=p, timeout=TIMEOUT)
	348	+ return r.json() if r.status_code == 200 else {"error": r.status_code}
	349	+ except Exception:
	350	+ raise HTTPException(502, "hub KA injoignable")
	351	+
	352	+
	353	+# ------------------------------------------------------------------ routeur
	354	+
	355	+class _EventsIn(BaseModel):
	356	+ events: list[dict]
	357	+
	358	+
	359	+class _HideIn(BaseModel):
	360	+ item_id: str
	361	+ on: bool = True
	362	+ features: dict \| None = None
	363	+
	364	+
	365	+class _SearchIn(BaseModel):
	366	+ action: str = "add" # add \| remove \| alert \| touch
	367	+ id: int \| None = None
	368	+ label: str \| None = None
	369	+ query: str \| None = None
	370	+ filters: dict \| None = None
	371	+ location: str \| None = None
	372	+ url: str \| None = None
	373	+ alert: bool = False
	374	+ frequency: str \| None = None
	375	+
	376	+
	377	+def build_router(get_user) -> APIRouter:
	378	+ """Routes /api/kaid/* de l'app. `get_user(request)` = current_user de
	379	+ l'app (dict avec ka_id, ou None)."""
	380	+ router = APIRouter(prefix="/api/kaid")
	381	+
	382	+ def _require_ka(request: Request) -> tuple[dict, str]:
	383	+ user = get_user(request)
	384	+ ka_id = _ka_id_of(user)
	385	+ if not ka_id:
	386	+ raise HTTPException(401, "connexion KA ID requise")
	387	+ return user, ka_id
	388	+
	389	+ @router.get("/status")
	390	+ def status(request: Request):
	391	+ user = get_user(request)
	392	+ ka_id = _ka_id_of(user)
	393	+ if not ka_id:
	394	+ return {"connected": False}
	395	+ prefs = fetch_prefs(ka_id)
	396	+ return {
	397	+ "connected": True,
	398	+ "personalization": bool(prefs and prefs.get("personalization")),
	399	+ "monka_url": f"{KA_HUB_URL}/mon-ka",
	400	+ }
	401	+
	402	+ @router.post("/events")
	403	+ def client_events(request: Request, body: _EventsIn):
	404	+ user = get_user(request)
	405	+ ka_id = _ka_id_of(user)
	406	+ if not ka_id:
	407	+ return {"ok": True, "stored": 0}
	408	+ events = []
	409	+ for e in body.events[:20]:
	410	+ if e.get("type") in CLIENT_EVENT_TYPES:
	411	+ events.append({k: e[k] for k in
	412	+ ("type", "entity_type", "entity_id", "query",
	413	+ "filters", "position", "features", "dwell_ms",
	414	+ "session_id") if k in e})
	415	+ if events:
	416	+ threading.Thread(target=_post_events, args=(ka_id, events),
	417	+ daemon=True).start()
	418	+ return {"ok": True, "stored": len(events)}
	419	+
	420	+ @router.post("/hide")
	421	+ def hide(request: Request, body: _HideIn):
	422	+ _, ka_id = _require_ka(request)
	423	+ out = _hub_post(ka_id, "/api/sso/hide", {
	424	+ "item_id": body.item_id, "on": body.on,
	425	+ "features": body.features,
	426	+ })
	427	+ invalidate_prefs(ka_id)
	428	+ return out
	429	+
	430	+ @router.get("/saved-searches")
	431	+ def saved_list(request: Request):
	432	+ _, ka_id = _require_ka(request)
	433	+ return _hub_get(ka_id, "/api/sso/saved-searches")
	434	+
	435	+ @router.post("/saved-searches")
	436	+ def saved_post(request: Request, body: _SearchIn):
	437	+ _, ka_id = _require_ka(request)
	438	+ search: dict = {k: v for k, v in {
	439	+ "id": body.id, "label": body.label, "query": body.query,
	440	+ "filters": body.filters, "location": body.location,
	441	+ "url": body.url, "alert": body.alert,
	442	+ "frequency": body.frequency,
	443	+ }.items() if v is not None}
	444	+ out = _hub_post(ka_id, "/api/sso/saved-searches",
	445	+ {"action": body.action, "search": search})
	446	+ invalidate_prefs(ka_id)
	447	+ return out
	448	+
	449	+ return router

added immoka/kapdf.py +1267 −0

		`@@ -0,0 +1,1267 @@`
	1	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	2	+# ka-ui/stats/kapdf.py — moteur PDF commun Groupe KA (fpdf2). v3
	3	+# Consomme le JSON du contrat /api/stats/dashboard (voir SPEC.md) et produit
	4	+# les rapports estampillés Groupe-KA. 5 modes fixes :
	5	+# complet — toutes les sections (KPI, jauges, séries + stats, multi-
	6	+# séries, empilées, distributions, répartitions, géo,
	7	+# heatmap horaire, tableaux, records)
	8	+# synthese — couverture + KPI + records (2-3 pages)
	9	+# tendances — KPI + toutes les séries temporelles + stats de séries
	10	+# repartitions — breakdowns, distributions, géo, activité horaire
	11	+# donnees — tous les tableaux en version longue (400 lignes max)
	12	+# v3 : mode « personnalise » — l'utilisateur compose son rapport bloc par
	13	+# bloc (choix des données ET du rendu par bloc : courbe/aire/barres/anneau/
	14	+# heatmap/tableau…). catalog(dash) expose les blocs disponibles ; le rapport
	15	+# suit une spec {"title": str, "blocks": [{"key": "series:ajouts",
	16	+# "render": "bar"}, …]} et respecte l'ordre demandé.
	17	+# Graphiques VECTORIELS uniquement (primitives fpdf), accent de la marque.
	18	+# Usage :
	19	+# from kapdf import GroupeKAReport, REPORT_MODES, catalog, filename
	20	+# pdf_bytes = GroupeKAReport(site={"wordmark":"Lou·Ka","accent":"#ff6a00",
	21	+# "domain":"www.lou-ka.com","tagline":"…"}, dashboard=dash_json,
	22	+# mode="complet").build()
	23	+# pdf_bytes = GroupeKAReport(site=SITE, dashboard=dash, mode="personnalise",
	24	+# spec={"title": "Mon rapport", "blocks": [...]}).build()
	25	+# Dépendance : pip install fpdf2 (aucune autre)
	26	+from __future__ import annotations
	27	+
	28	+import math
	29	+from datetime import datetime
	30	+from zoneinfo import ZoneInfo
	31	+
	32	+from fpdf import FPDF
	33	+
	34	+INK = (20, 24, 20)
	35	+INK2 = (77, 85, 81)
	36	+INK3 = (139, 146, 140)
	37	+PAPER = (245, 243, 238)
	38	+SURFACE2 = (250, 249, 245)
	39	+GREEN = (28, 92, 65)
	40	+DANGER = (179, 66, 58)
	41	+WHITE = (255, 255, 255)
	42	+
	43	+REPORT_MODES = {
	44	+ "complet": "Rapport complet",
	45	+ "synthese": "Synthèse exécutive",
	46	+ "tendances": "Tendances & évolution",
	47	+ "repartitions": "Répartitions & géographie",
	48	+ "donnees": "Données détaillées",
	49	+}
	50	+# v3 — mode composé par l'utilisateur (jamais dans le menu des modes fixes)
	51	+CUSTOM_MODE = "personnalise"
	52	+CUSTOM_LABEL = "Rapport personnalisé"
	53	+
	54	+# v3 — rendus proposés par type de bloc (le 1er est le rendu par défaut ;
	55	+# « table » est toujours offert : toute donnée a un équivalent tableau)
	56	+RENDER_LABELS = {
	57	+ "line": "Courbe", "area": "Aire", "bar": "Barres verticales",
	58	+ "bars": "Barres horizontales", "donut": "Anneau",
	59	+ "lines": "Multi-courbes", "stacked": "Barres empilées",
	60	+ "histogram": "Histogramme", "heatmap": "Heatmap",
	61	+ "cards": "Cartes", "gauges": "Jauges", "table": "Tableau",
	62	+}
	63	+SECTION_LABELS = {
	64	+ "kpis": "Indicateurs", "gauges": "Taux & couvertures",
	65	+ "series": "Évolution", "multiseries": "Comparaisons",
	66	+ "stacked": "Compositions", "breakdowns": "Répartitions",
	67	+ "distributions": "Distributions", "geo": "Géographie",
	68	+ "heatmap": "Calendrier", "hourly": "Activité horaire",
	69	+ "tables": "Tableaux", "records": "Records",
	70	+}
	71	+
	72	+
	73	+def catalog(dash: dict) -> list[dict]:
	74	+ """v3 — blocs composables d'un dashboard : ce que le constructeur de
	75	+ rapports personnalisés peut inclure, avec les rendus compatibles.
	76	+ key = section[:id] ; l'ordre renvoyé = ordre naturel du dashboard."""
	77	+ out: list[dict] = []
	78	+
	79	+ def add(key, title, renders, default=None, count=None):
	80	+ b = {"key": key, "section": key.split(":")[0], "title": title,
	81	+ "renders": renders, "default_render": default or renders[0]}
	82	+ if count is not None:
	83	+ b["count"] = count
	84	+ out.append(b)
	85	+
	86	+ if dash.get("kpis"):
	87	+ add("kpis", "Indicateurs clés (KPI)", ["cards", "table"],
	88	+ count=len(dash["kpis"]))
	89	+ gs = [g for g in (dash.get("gauges") or [])
	90	+ if isinstance(g.get("value"), (int, float)) and g.get("max")]
	91	+ if gs:
	92	+ add("gauges", "Taux & couvertures (jauges)", ["gauges", "table"],
	93	+ count=len(gs))
	94	+ for s in dash.get("series") or []:
	95	+ if len(s.get("points") or []) < 2:
	96	+ continue
	97	+ kind = s.get("kind") or "line"
	98	+ default = kind if kind in ("line", "area", "bar") else "line"
	99	+ add(f"series:{s.get('id')}", s.get("title", ""),
	100	+ ["line", "area", "bar", "table"], default,
	101	+ len(s.get("points") or []))
	102	+ for ms in dash.get("multiseries") or []:
	103	+ if not (ms.get("series") or []):
	104	+ continue
	105	+ add(f"multiseries:{ms.get('id')}", ms.get("title", ""),
	106	+ ["lines", "table"], count=len(ms["series"]))
	107	+ for st in dash.get("stacked") or []:
	108	+ if not (st.get("points") or []):
	109	+ continue
	110	+ add(f"stacked:{st.get('id')}", st.get("title", ""),
	111	+ ["stacked", "table"], count=len(st.get("keys") or []))
	112	+ for b in dash.get("breakdowns") or []:
	113	+ if not (b.get("items") or []):
	114	+ continue
	115	+ default = "donut" if b.get("kind") == "donut" else "bars"
	116	+ add(f"breakdowns:{b.get('id')}", b.get("title", ""),
	117	+ ["donut", "bars", "table"], default, len(b["items"]))
	118	+ for d in dash.get("distributions") or []:
	119	+ if not (d.get("bins") or []):
	120	+ continue
	121	+ add(f"distributions:{d.get('id')}", d.get("title", ""),
	122	+ ["histogram", "table"], count=len(d["bins"]))
	123	+ geo = dash.get("geo") or {}
	124	+ if geo.get("items"):
	125	+ add("geo", geo.get("title", "Répartition géographique"),
	126	+ ["bars", "table"], count=len(geo["items"]))
	127	+ hm = dash.get("heatmap") or {}
	128	+ if hm.get("cells"):
	129	+ add("heatmap", hm.get("title", "Calendrier d'activité"),
	130	+ ["heatmap", "table"])
	131	+ hr = dash.get("hourly") or {}
	132	+ if hr.get("cells"):
	133	+ add("hourly", hr.get("title", "Activité par jour et heure"),
	134	+ ["heatmap", "table"])
	135	+ for t in dash.get("tables") or []:
	136	+ if not (t.get("rows") or []):
	137	+ continue
	138	+ add(f"tables:{t.get('id')}", t.get("title", ""), ["table"],
	139	+ count=len(t["rows"]))
	140	+ if dash.get("records"):
	141	+ add("records", "Records & faits marquants", ["cards", "table"],
	142	+ count=len(dash["records"]))
	143	+ return out
	144	+
	145	+EMAILS = [
	146	+ ("contact@groupe-ka.com", "Projets, partenariats & données"),
	147	+ ("info@groupe-ka.com", "Médias & questions générales"),
	148	+ ("admin@groupe-ka.com", "Légal, vie privée & Loi 25"),
	149	+]
	150	+DISCLAIMER = (
	151	+ "Groupe KA est un agrégateur de contenu : nous ne vendons rien, ne louons "
	152	+ "rien et ne sommes partie à aucune transaction. Données lues à la source, "
	153	+ "rien d'inventé, tout est traçable."
	154	+)
	155	+
	156	+
	157	+def _hex(c: str) -> tuple[int, int, int]:
	158	+ c = c.lstrip("#")
	159	+ return tuple(int(c[i : i + 2], 16) for i in (0, 2, 4)) # type: ignore
	160	+
	161	+
	162	+def _fr(n) -> str:
	163	+ if isinstance(n, float) and not n.is_integer():
	164	+ return f"{n:,.2f}".replace(",", " ").replace(".", ",")
	165	+ return f"{int(n):,}".replace(",", " ")
	166	+
	167	+
	168	+_SUBST = {
	169	+ "—": "-", "–": "-", "→": "->", "▲": "+", "▼": "-",
	170	+ "…": "...", "’": "'", "‘": "'", "“": '"', "”": '"',
	171	+ "œ": "oe", "Œ": "OE", "−": "-", " ": " ", " ": " ",
	172	+ "×": "x", "·": ".", "σ": "sigma", "Δ": "delta",
	173	+}
	174	+
	175	+
	176	+def _latin1(s: str) -> str:
	177	+ for k, v in _SUBST.items():
	178	+ s = s.replace(k, v)
	179	+ return s.encode("latin-1", "replace").decode("latin-1")
	180	+
	181	+
	182	+class _PDF(FPDF):
	183	+ """FPDF avec en-tête/pied Groupe-KA sur chaque page (sauf couverture).
	184	+ Les polices core sont latin-1 : normalize_text sanitise en amont."""
	185	+
	186	+ def normalize_text(self, text):
	187	+ return super().normalize_text(_latin1(text))
	188	+
	189	+ def __init__(self, brand: str, accent: tuple, period_label: str):
	190	+ super().__init__(orientation="P", unit="mm", format="A4")
	191	+ self.brand = brand
	192	+ self.accent = accent
	193	+ self.period_label = period_label
	194	+ self.cover_mode = False
	195	+ self.set_margins(18, 20, 18)
	196	+ self.set_auto_page_break(True, margin=22)
	197	+
	198	+ def header(self):
	199	+ if self.cover_mode or self.page_no() == 1:
	200	+ return
	201	+ self.set_font("helvetica", "B", 8.5)
	202	+ self.set_text_color(*INK)
	203	+ self.set_xy(18, 9)
	204	+ self.cell(0, 5, f"Groupe KA · {self.brand}")
	205	+ self.set_font("helvetica", "", 8)
	206	+ self.set_text_color(*INK3)
	207	+ self.set_xy(18, 9)
	208	+ self.cell(0, 5, "Rapport statistique", align="R")
	209	+ self.set_draw_color(*INK)
	210	+ self.set_line_width(0.5)
	211	+ self.line(18, 15.5, 192, 15.5)
	212	+ self.set_y(20)
	213	+
	214	+ def footer(self):
	215	+ # page 1 = couverture (le flag cover_mode est déjà retombé quand
	216	+ # add_page() clôt la page 1 → tester aussi le numéro de page)
	217	+ if self.cover_mode or self.page_no() == 1:
	218	+ return
	219	+ self.set_y(-15)
	220	+ self.set_draw_color(*INK3)
	221	+ self.set_line_width(0.2)
	222	+ self.line(18, self.get_y() - 1.5, 192, self.get_y() - 1.5)
	223	+ self.set_font("helvetica", "", 7.5)
	224	+ self.set_text_color(*INK3)
	225	+ year = datetime.now(ZoneInfo("America/Toronto")).year
	226	+ self.cell(130, 5, f"© Groupe-KA — {year} — groupe-ka.com · {self.period_label}")
	227	+ self.cell(0, 5, f"p. {self.page_no()}/{{nb}}", align="R")
	228	+
	229	+
	230	+class GroupeKAReport:
	231	+ def __init__(self, site: dict, dashboard: dict, mode: str = "complet",
	232	+ spec: dict \| None = None):
	233	+ self.site = site
	234	+ self.d = dashboard
	235	+ self.mode = mode if (mode in REPORT_MODES or mode == CUSTOM_MODE) else "complet"
	236	+ self.spec = spec or {}
	237	+ self.accent = _hex(site.get("accent", "#d9f26b"))
	238	+ period = dashboard.get("period", {}) or {}
	239	+ self.period_label = period.get("label") or "toute la période"
	240	+ self.pdf = _PDF(site.get("wordmark", ""), self.accent, self.period_label)
	241	+ self.toc: list[tuple[str, int]] = []
	242	+
	243	+ @property
	244	+ def mode_label(self) -> str:
	245	+ if self.mode == CUSTOM_MODE:
	246	+ t = str(self.spec.get("title") or "").strip()
	247	+ return f"{CUSTOM_LABEL} — {t}" if t else CUSTOM_LABEL
	248	+ return REPORT_MODES[self.mode]
	249	+
	250	+ # ---------- primitives ----------
	251	+ def _card(self, x, y, w, h, fill=WHITE):
	252	+ p = self.pdf
	253	+ p.set_draw_color(*INK)
	254	+ p.set_line_width(0.45)
	255	+ p.set_fill_color(*fill)
	256	+ p.rect(x, y, w, h, style="DF", round_corners=True, corner_radius=2.2)
	257	+
	258	+ def _shade(self, i, n=8):
	259	+ shades = [1.0, 0.78, 0.58, 0.42, 0.30, 0.22, 0.15, 0.10]
	260	+ f = shades[i % len(shades)]
	261	+ return tuple(int(PAPER[j] + (self.accent[j] - PAPER[j]) * f) for j in range(3))
	262	+
	263	+ def _kicker(self, text):
	264	+ p = self.pdf
	265	+ p.set_font("helvetica", "B", 8)
	266	+ p.set_text_color(*GREEN)
	267	+ p.set_draw_color(*GREEN)
	268	+ p.set_line_width(0.6)
	269	+ y = p.get_y() + 2
	270	+ p.line(p.l_margin, y, p.l_margin + 7, y)
	271	+ p.set_xy(p.l_margin + 9, y - 2.5)
	272	+ p.cell(0, 5, text.upper())
	273	+ p.ln(8)
	274	+
	275	+ def _section_title(self, title):
	276	+ if self.pdf.get_y() > 240:
	277	+ self.pdf.add_page()
	278	+ self._kicker("Groupe KA · " + self.site.get("wordmark", ""))
	279	+ self.pdf.set_font("helvetica", "B", 15)
	280	+ self.pdf.set_text_color(*INK)
	281	+ self.pdf.set_x(self.pdf.l_margin)
	282	+ self.pdf.cell(0, 8, title)
	283	+ self.toc.append((title, self.pdf.page_no()))
	284	+ self.pdf.ln(11)
	285	+
	286	+ def _chart_title(self, title):
	287	+ p = self.pdf
	288	+ p.set_font("helvetica", "B", 10)
	289	+ p.set_text_color(*INK)
	290	+ p.set_x(p.l_margin)
	291	+ p.cell(0, 6, title)
	292	+ p.ln(7)
	293	+
	294	+ # ---------- pages ----------
	295	+ def _cover(self):
	296	+ p = self.pdf
	297	+ p.cover_mode = True
	298	+ p.set_auto_page_break(False)
	299	+ p.add_page()
	300	+ p.set_fill_color(*PAPER)
	301	+ p.rect(0, 0, 210, 297, style="F")
	302	+ p.set_draw_color(*INK)
	303	+ p.set_line_width(1.0)
	304	+ p.rect(10, 10, 190, 277)
	305	+ p.set_font("helvetica", "B", 10)
	306	+ p.set_text_color(*GREEN)
	307	+ p.set_xy(24, 34)
	308	+ p.cell(0, 6, "GROUPE KA · RAPPORT STATISTIQUE")
	309	+ wm = self.site.get("wordmark", "")
	310	+ left, boxed = (wm.split("·") + [None])[:2] if "·" in wm else (wm, None)
	311	+ p.set_xy(24, 70)
	312	+ p.set_font("helvetica", "B", 40)
	313	+ p.set_text_color(*INK)
	314	+ p.cell(p.get_string_width(left) + 2, 20, left)
	315	+ if boxed:
	316	+ bw = p.get_string_width(boxed) + 12
	317	+ x = p.get_x() + 2
	318	+ p.set_fill_color(*INK)
	319	+ p.rect(x, 68, bw, 22, style="F", round_corners=True, corner_radius=3)
	320	+ p.set_text_color(*self.accent)
	321	+ p.set_xy(x + 6, 70)
	322	+ p.cell(bw - 12, 18, boxed)
	323	+ p.set_xy(24, 100)
	324	+ p.set_font("helvetica", "", 13)
	325	+ p.set_text_color(*INK2)
	326	+ p.multi_cell(150, 7, f"{self.mode_label} — {wm}")
	327	+ now = datetime.now(ZoneInfo("America/Toronto"))
	328	+ per = self.d.get("period", {}) or {}
	329	+ p.set_xy(24, 125)
	330	+ p.set_font("helvetica", "", 10.5)
	331	+ rows = [
	332	+ ("Période couverte", self.period_label + (f" ({per.get('from')} → {per.get('to')})" if per.get("from") else "")),
	333	+ ("Généré le", now.strftime("%Y-%m-%d à %H:%M") + " (heure de l'Est)"),
	334	+ ("Plateforme", "https://" + self.site.get("domain", "")),
	335	+ ("Type de rapport", self.mode_label),
	336	+ ]
	337	+ y = 128
	338	+ for k, v in rows:
	339	+ p.set_xy(24, y)
	340	+ p.set_text_color(*INK3)
	341	+ p.cell(40, 6, k)
	342	+ p.set_text_color(*INK)
	343	+ p.set_font("helvetica", "B", 10.5)
	344	+ p.cell(0, 6, str(v))
	345	+ p.set_font("helvetica", "", 10.5)
	346	+ y += 8
	347	+ p.set_fill_color(*INK)
	348	+ p.rect(10, 262, 190, 25, style="F")
	349	+ p.set_xy(24, 270)
	350	+ p.set_font("helvetica", "B", 12)
	351	+ p.set_text_color(*WHITE)
	352	+ p.cell(60, 8, "par Groupe ")
	353	+ p.set_text_color(*self.accent)
	354	+ p.set_xy(24 + p.get_string_width("par Groupe ") + 1, 270)
	355	+ p.cell(20, 8, "KA")
	356	+ p.set_font("helvetica", "B", 10)
	357	+ p.set_xy(24, 270)
	358	+ p.set_text_color(*self.accent)
	359	+ p.cell(162, 8, "groupe-ka.com", align="R")
	360	+ p.set_auto_page_break(True, margin=22)
	361	+ p.cover_mode = False
	362	+
	363	+ def _kpis(self):
	364	+ kpis = self.d.get("kpis") or []
	365	+ if not kpis:
	366	+ return
	367	+ self._section_title("Synthèse des indicateurs")
	368	+ p = self.pdf
	369	+ cols, gw, gh, gap = 3, 56, 26, 3
	370	+ x0, y = p.l_margin, p.get_y()
	371	+ for i, k in enumerate(kpis[:12]):
	372	+ x = x0 + (i % cols) * (gw + gap)
	373	+ if i and i % cols == 0:
	374	+ y += gh + gap
	375	+ if y > 250:
	376	+ p.add_page(); y = p.get_y()
	377	+ self._card(x, y, gw, gh)
	378	+ p.set_xy(x + 4, y + 4)
	379	+ p.set_font("helvetica", "B", 14)
	380	+ p.set_text_color(*INK)
	381	+ val = k.get("value")
	382	+ p.cell(gw - 8, 7, (_fr(val) if isinstance(val, (int, float)) else str(val)) + (" " + k["unit"] if k.get("unit") else ""))
	383	+ p.set_xy(x + 4, y + 12)
	384	+ p.set_font("helvetica", "", 7.6)
	385	+ p.set_text_color(*INK2)
	386	+ p.multi_cell(gw - 8, 3.6, str(k.get("label", ""))[:70])
	387	+ if k.get("delta_pct") is not None:
	388	+ up = (k.get("direction") or ("up" if k["delta_pct"] >= 0 else "down")) == "up"
	389	+ p.set_xy(x + 4, y + gh - 6.5)
	390	+ p.set_font("helvetica", "B", 8)
	391	+ p.set_text_color(*(GREEN if up else DANGER))
	392	+ arrow = "+" if k["delta_pct"] >= 0 else ""
	393	+ dv = round(float(k["delta_pct"]), 1)
	394	+ dv = int(dv) if float(dv).is_integer() else dv
	395	+ p.cell(gw - 8, 4, f"{'▲' if up else '▼'} {arrow}{str(dv).replace('.', ',')} % vs période préc.")
	396	+ p.set_y(y + gh + 8)
	397	+
	398	+ def _gauges(self):
	399	+ gs = self.d.get("gauges") or []
	400	+ gs = [g for g in gs if isinstance(g.get("value"), (int, float)) and g.get("max")]
	401	+ if not gs:
	402	+ return
	403	+ self._section_title("Taux & couvertures")
	404	+ p = self.pdf
	405	+ cols, gw, gh, gap = 3, 56, 34, 3
	406	+ x0, y = p.l_margin, p.get_y()
	407	+ for i, g in enumerate(gs[:9]):
	408	+ x = x0 + (i % cols) * (gw + gap)
	409	+ if i and i % cols == 0:
	410	+ y += gh + gap
	411	+ if y > 240:
	412	+ p.add_page(); y = p.get_y()
	413	+ self._card(x, y, gw, gh)
	414	+ frac = max(0.0, min(1.0, g["value"] / g["max"]))
	415	+ cx, cy, r = x + gw / 2, y + 20, 14
	416	+ # arc de fond + arc de valeur (demi-cercle en petits segments)
	417	+ for pass_col, pass_frac, lw in (((225, 223, 217), 1.0, 2.6), (self.accent, frac, 2.6)):
	418	+ p.set_draw_color(*pass_col)
	419	+ p.set_line_width(lw)
	420	+ steps = max(2, int(60 * pass_frac))
	421	+ last = None
	422	+ for st in range(steps + 1):
	423	+ a = math.pi + math.pi * pass_frac * st / steps
	424	+ pt = (cx + r * math.cos(a), cy + r * math.sin(a))
	425	+ if last:
	426	+ p.line(last[0], last[1], pt[0], pt[1])
	427	+ last = pt
	428	+ p.set_font("helvetica", "B", 11)
	429	+ p.set_text_color(*INK)
	430	+ p.set_xy(x + 4, cy - 5)
	431	+ p.cell(gw - 8, 6, f"{_fr(g['value'])}{' ' + g['unit'] if g.get('unit') else ''}", align="C")
	432	+ p.set_font("helvetica", "", 6.6)
	433	+ p.set_text_color(*INK3)
	434	+ p.set_xy(x + 4, cy + 1.5)
	435	+ p.cell(gw - 8, 4, f"{frac * 100:.0f} % de {_fr(g['max'])}", align="C")
	436	+ p.set_xy(x + 3, y + gh - 7)
	437	+ p.set_font("helvetica", "", 7)
	438	+ p.set_text_color(*INK2)
	439	+ p.multi_cell(gw - 6, 3.3, str(g.get("label", ""))[:60], align="C")
	440	+ p.set_y(y + gh + 8)
	441	+
	442	+ def _serie_stats_row(self, s):
	443	+ """Ligne min/max/moyenne/médiane sous un graphique de série."""
	444	+ p = self.pdf
	445	+ vs = [pt["v"] for pt in (s.get("points") or []) if isinstance(pt.get("v"), (int, float))]
	446	+ if len(vs) < 2:
	447	+ return
	448	+ sv = sorted(vs)
	449	+ mean = sum(vs) / len(vs)
	450	+ med = sv[len(sv) // 2]
	451	+ sd = math.sqrt(sum((v - mean) ** 2 for v in vs) / len(vs))
	452	+ p.set_font("helvetica", "", 6.8)
	453	+ p.set_text_color(*INK3)
	454	+ p.cell(0, 4, f"min {_fr(sv[0])} · max {_fr(sv[-1])} · moyenne {_fr(round(mean, 2))} · médiane {_fr(med)} · écart-type {_fr(round(sd, 2))}")
	455	+ p.ln(5.5)
	456	+
	457	+ def _line_chart(self, s, with_stats=False):
	458	+ p = self.pdf
	459	+ pts = s.get("points") or []
	460	+ if len(pts) < 2:
	461	+ return
	462	+ if s.get("kind") == "bar":
	463	+ self._vbars(s)
	464	+ return
	465	+ if p.get_y() > 200:
	466	+ p.add_page()
	467	+ self._chart_title(s.get("title", ""))
	468	+ x0, y0, w, h = p.l_margin, p.get_y(), 174, 52
	469	+ self._card(x0, y0, w, h, fill=WHITE)
	470	+ cx, cy, cw, ch = x0 + 12, y0 + 6, w - 20, h - 16
	471	+ vals = [pt["v"] for pt in pts] + [c["v"] for c in (s.get("compare") or [])]
	472	+ vmax = max(vals) or 1
	473	+ vmin = min(0, min(vals))
	474	+ rng = (vmax - vmin) or 1
	475	+ p.set_font("helvetica", "", 6.3)
	476	+ p.set_text_color(*INK3)
	477	+ p.set_draw_color(200, 200, 195)
	478	+ p.set_line_width(0.15)
	479	+ for g in range(5):
	480	+ gy = cy + ch - ch * g / 4
	481	+ p.line(cx, gy, cx + cw, gy)
	482	+ p.set_xy(x0 + 1, gy - 1.6)
	483	+ p.cell(10, 3, _fr(vmin + rng * g / 4), align="R")
	484	+
	485	+ def xy(i, n, v):
	486	+ return (cx + cw * (i / (n - 1)), cy + ch - ch * ((v - vmin) / rng))
	487	+
	488	+ # aire sous la courbe (kind=area) : petits trapèzes accent pâle
	489	+ if s.get("kind") == "area":
	490	+ fill = tuple(int(PAPER[j] + (self.accent[j] - PAPER[j]) * 0.18) for j in range(3))
	491	+ p.set_fill_color(*fill)
	492	+ p.set_draw_color(*fill)
	493	+ n = len(pts)
	494	+ for i in range(n - 1):
	495	+ x1, y1 = xy(i, n, pts[i]["v"])
	496	+ x2, y2 = xy(i + 1, n, pts[i + 1]["v"])
	497	+ p.polygon([(x1, y1), (x2, y2), (x2, cy + ch), (x1, cy + ch)], style="DF")
	498	+
	499	+ def draw(series, color, width, dash=None):
	500	+ n = len(series)
	501	+ p.set_draw_color(*color)
	502	+ p.set_line_width(width)
	503	+ if dash:
	504	+ p.set_dash_pattern(dash=1.2, gap=1.2)
	505	+ last = None
	506	+ for i, pt in enumerate(series):
	507	+ px, py = xy(i, n, pt["v"])
	508	+ if last:
	509	+ p.line(last[0], last[1], px, py)
	510	+ last = (px, py)
	511	+ p.set_dash_pattern()
	512	+
	513	+ if s.get("compare"):
	514	+ draw(s["compare"], INK3, 0.35, dash=True)
	515	+ draw(pts, self.accent, 0.7)
	516	+ p.set_text_color(*INK3)
	517	+ for frac, idx in ((0, 0), (0.5, len(pts) // 2), (1, -1)):
	518	+ p.set_xy(cx + cw * frac - 9, cy + ch + 1.5)
	519	+ p.cell(18, 3, str(pts[idx].get("t", ""))[:10], align="C")
	520	+ p.set_y(y0 + h + 4)
	521	+ if s.get("compare"):
	522	+ p.set_font("helvetica", "", 6.8)
	523	+ p.set_text_color(*INK3)
	524	+ p.cell(0, 4, "— période courante (accent) · ---- période comparée")
	525	+ p.ln(5.5)
	526	+ if with_stats:
	527	+ self._serie_stats_row(s)
	528	+ p.ln(1.5)
	529	+
	530	+ def _vbars(self, s):
	531	+ """Barres verticales : série kind=bar ou distribution (bins)."""
	532	+ p = self.pdf
	533	+ pts = s.get("points") or [{"t": b.get("label"), "v": b.get("value")} for b in (s.get("bins") or [])]
	534	+ pts = [pt for pt in pts if isinstance(pt.get("v"), (int, float))]
	535	+ if not pts:
	536	+ return
	537	+ if p.get_y() > 205:
	538	+ p.add_page()
	539	+ self._chart_title(s.get("title", ""))
	540	+ x0, y0, w, h = p.l_margin, p.get_y(), 174, 48
	541	+ self._card(x0, y0, w, h, fill=WHITE)
	542	+ cx, cy, cw, ch = x0 + 12, y0 + 5, w - 20, h - 14
	543	+ vmax = max(pt["v"] for pt in pts) or 1
	544	+ p.set_font("helvetica", "", 6.3)
	545	+ p.set_text_color(*INK3)
	546	+ p.set_draw_color(200, 200, 195)
	547	+ p.set_line_width(0.15)
	548	+ for g in range(5):
	549	+ gy = cy + ch - ch * g / 4
	550	+ p.line(cx, gy, cx + cw, gy)
	551	+ p.set_xy(x0 + 1, gy - 1.6)
	552	+ p.cell(10, 3, _fr(vmax * g / 4), align="R")
	553	+ n = len(pts)
	554	+ bw = max(0.8, cw / n - 0.6)
	555	+ p.set_fill_color(*self.accent)
	556	+ p.set_draw_color(*INK)
	557	+ p.set_line_width(0.15)
	558	+ for i, pt in enumerate(pts):
	559	+ bh = ch * (pt["v"] / vmax)
	560	+ p.rect(cx + cw * i / n + 0.3, cy + ch - bh, bw, max(bh, 0.4 if pt["v"] > 0 else 0), style="DF")
	561	+ p.set_text_color(*INK3)
	562	+ for frac, idx in ((0, 0), (0.5, n // 2), (1, -1)):
	563	+ p.set_xy(cx + cw * frac - 10, cy + ch + 1.5)
	564	+ p.cell(20, 3, str(pts[idx].get("t", ""))[:12], align="C")
	565	+ p.set_y(y0 + h + 5)
	566	+
	567	+ def _multiline(self, ms):
	568	+ """Multi-séries (≤4) : accent plein / encre fin / accent pointillé /
	569	+ gris pointillé — l'identité passe par le motif, pas la couleur seule."""
	570	+ p = self.pdf
	571	+ series = [s for s in (ms.get("series") or []) if len(s.get("points") or []) > 1][:4]
	572	+ if not series:
	573	+ return
	574	+ if p.get_y() > 195:
	575	+ p.add_page()
	576	+ self._chart_title(ms.get("title", ""))
	577	+ x0, y0, w, h = p.l_margin, p.get_y(), 174, 52
	578	+ self._card(x0, y0, w, h, fill=WHITE)
	579	+ cx, cy, cw, ch = x0 + 12, y0 + 6, w - 20, h - 16
	580	+ vals = [pt["v"] for s in series for pt in s["points"]]
	581	+ vmax = max(vals) or 1
	582	+ vmin = min(0, min(vals))
	583	+ rng = (vmax - vmin) or 1
	584	+ p.set_font("helvetica", "", 6.3)
	585	+ p.set_text_color(*INK3)
	586	+ p.set_draw_color(200, 200, 195)
	587	+ p.set_line_width(0.15)
	588	+ for g in range(5):
	589	+ gy = cy + ch - ch * g / 4
	590	+ p.line(cx, gy, cx + cw, gy)
	591	+ p.set_xy(x0 + 1, gy - 1.6)
	592	+ p.cell(10, 3, _fr(vmin + rng * g / 4), align="R")
	593	+ styles = [
	594	+ (self.accent, 0.7, None),
	595	+ (INK, 0.45, None),
	596	+ (self.accent, 0.55, True),
	597	+ (INK3, 0.5, True),
	598	+ ]
	599	+ for si, s in enumerate(series):
	600	+ col, lw, dash = styles[si]
	601	+ p.set_draw_color(*col)
	602	+ p.set_line_width(lw)
	603	+ if dash:
	604	+ p.set_dash_pattern(dash=1.4, gap=1.2)
	605	+ n = len(s["points"])
	606	+ last = None
	607	+ for i, pt in enumerate(s["points"]):
	608	+ px = cx + cw * (i / (n - 1))
	609	+ py = cy + ch - ch * ((pt["v"] - vmin) / rng)
	610	+ if last:
	611	+ p.line(last[0], last[1], px, py)
	612	+ last = (px, py)
	613	+ p.set_dash_pattern()
	614	+ ref = series[0]["points"]
	615	+ p.set_text_color(*INK3)
	616	+ for frac, idx in ((0, 0), (0.5, len(ref) // 2), (1, -1)):
	617	+ p.set_xy(cx + cw * frac - 9, cy + ch + 1.5)
	618	+ p.cell(18, 3, str(ref[idx].get("t", ""))[:10], align="C")
	619	+ p.set_y(y0 + h + 4)
	620	+ p.set_font("helvetica", "", 6.8)
	621	+ p.set_text_color(*INK3)
	622	+ marks = ["—", "—", "----", "----"]
	623	+ leg = " · ".join(f"{marks[i]} {s.get('label', '')}" for i, s in enumerate(series))
	624	+ p.cell(0, 4, leg[:120])
	625	+ p.ln(6)
	626	+
	627	+ def _stacked(self, st):
	628	+ p = self.pdf
	629	+ keys = (st.get("keys") or [])[:6]
	630	+ pts = st.get("points") or []
	631	+ if not keys or not pts:
	632	+ return
	633	+ if p.get_y() > 195:
	634	+ p.add_page()
	635	+ self._chart_title(st.get("title", ""))
	636	+ x0, y0, w, h = p.l_margin, p.get_y(), 174, 52
	637	+ self._card(x0, y0, w, h, fill=WHITE)
	638	+ cx, cy, cw, ch = x0 + 12, y0 + 6, w - 20, h - 16
	639	+ totals = [sum(v or 0 for v in pt.get("values", [])[: len(keys)]) for pt in pts]
	640	+ vmax = max(totals) or 1
	641	+ p.set_font("helvetica", "", 6.3)
	642	+ p.set_text_color(*INK3)
	643	+ p.set_draw_color(200, 200, 195)
	644	+ p.set_line_width(0.15)
	645	+ for g in range(5):
	646	+ gy = cy + ch - ch * g / 4
	647	+ p.line(cx, gy, cx + cw, gy)
	648	+ p.set_xy(x0 + 1, gy - 1.6)
	649	+ p.cell(10, 3, _fr(vmax * g / 4), align="R")
	650	+ n = len(pts)
	651	+ bw = max(0.8, cw / n - 0.6)
	652	+ p.set_draw_color(*WHITE)
	653	+ p.set_line_width(0.12)
	654	+ for i, pt in enumerate(pts):
	655	+ yacc = cy + ch
	656	+ for j, k in enumerate(keys):
	657	+ v = (pt.get("values") or [0] * len(keys))[j] if j < len(pt.get("values", [])) else 0
	658	+ if not v:
	659	+ continue
	660	+ bh = ch * (v / vmax)
	661	+ yacc -= bh
	662	+ p.set_fill_color(*self._shade(j))
	663	+ p.rect(cx + cw * i / n + 0.3, yacc, bw, max(bh - 0.15, 0.3), style="DF")
	664	+ p.set_text_color(*INK3)
	665	+ for frac, idx in ((0, 0), (0.5, n // 2), (1, -1)):
	666	+ p.set_xy(cx + cw * frac - 10, cy + ch + 1.5)
	667	+ p.cell(20, 3, str(pts[idx].get("t", ""))[:12], align="C")
	668	+ p.set_y(y0 + h + 4)
	669	+ # légende
	670	+ p.set_font("helvetica", "", 6.8)
	671	+ lx = p.l_margin
	672	+ for j, k in enumerate(keys):
	673	+ p.set_fill_color(*self._shade(j))
	674	+ p.set_draw_color(*INK)
	675	+ p.set_line_width(0.2)
	676	+ p.rect(lx, p.get_y() + 0.6, 3, 3, style="DF")
	677	+ p.set_xy(lx + 4, p.get_y())
	678	+ p.set_text_color(*INK2)
	679	+ txt = str(k)[:22]
	680	+ p.cell(p.get_string_width(txt) + 3, 4, txt)
	681	+ lx = p.get_x() + 3
	682	+ if lx > 165:
	683	+ break
	684	+ p.ln(7)
	685	+
	686	+ def _bars(self, title, items, unit=""):
	687	+ p = self.pdf
	688	+ items = [it for it in (items or []) if isinstance(it.get("value"), (int, float))][:12]
	689	+ if not items:
	690	+ return
	691	+ need = 10 + len(items) * 7
	692	+ if p.get_y() + need > 265:
	693	+ p.add_page()
	694	+ self._chart_title(title)
	695	+ p.ln(1)
	696	+ vmax = max(it["value"] for it in items) or 1
	697	+ for it in items:
	698	+ y = p.get_y()
	699	+ p.set_font("helvetica", "", 7.6)
	700	+ p.set_text_color(*INK)
	701	+ p.set_x(p.l_margin)
	702	+ p.cell(46, 5, str(it["label"])[:34])
	703	+ bw = 86 * (it["value"] / vmax)
	704	+ p.set_fill_color(*self.accent)
	705	+ p.set_draw_color(*INK)
	706	+ p.set_line_width(0.25)
	707	+ p.rect(p.l_margin + 48, y + 0.7, max(bw, 0.8), 3.6, style="DF")
	708	+ p.set_xy(p.l_margin + 136, y)
	709	+ p.set_font("helvetica", "B", 7.6)
	710	+ p.cell(24, 5, _fr(it["value"]) + (" " + unit if unit else ""), align="R")
	711	+ if it.get("delta_pct") is not None:
	712	+ up = it["delta_pct"] >= 0
	713	+ p.set_font("helvetica", "B", 6.6)
	714	+ p.set_text_color(*(GREEN if up else DANGER))
	715	+ p.cell(14, 5, f"{'+' if up else ''}{str(round(it['delta_pct'], 1)).replace('.', ',')} %", align="R")
	716	+ p.ln(6.4)
	717	+ p.ln(3)
	718	+
	719	+ def _donut(self, b):
	720	+ p = self.pdf
	721	+ items = [it for it in (b.get("items") or []) if it.get("value")][:8]
	722	+ total = sum(it["value"] for it in items)
	723	+ if not items or not total:
	724	+ return
	725	+ if p.get_y() > 210:
	726	+ p.add_page()
	727	+ self._chart_title(b.get("title", ""))
	728	+ p.ln(1)
	729	+ cx, cy, r = p.l_margin + 26, p.get_y() + 24, 20
	730	+ start = -90.0
	731	+ for i, it in enumerate(items):
	732	+ frac = it["value"] / total
	733	+ col = self._shade(i)
	734	+ steps = max(2, int(72 * frac))
	735	+ p.set_fill_color(*col)
	736	+ p.set_draw_color(*col)
	737	+ for st in range(steps):
	738	+ a0 = math.radians(start + 360 * frac * st / steps)
	739	+ a1 = math.radians(start + 360 * frac * (st + 1) / steps)
	740	+ p.polygon(
	741	+ [(cx, cy),
	742	+ (cx + r * math.cos(a0), cy + r * math.sin(a0)),
	743	+ (cx + r * math.cos(a1), cy + r * math.sin(a1))],
	744	+ style="DF",
	745	+ )
	746	+ start += 360 * frac
	747	+ p.set_fill_color(*WHITE)
	748	+ p.set_draw_color(*INK)
	749	+ p.set_line_width(0.4)
	750	+ p.ellipse(cx - 11, cy - 11, 22, 22, style="DF")
	751	+ p.ellipse(cx - r, cy - r, 2 * r, 2 * r, style="D")
	752	+ ly = cy - 22
	753	+ for i, it in enumerate(items):
	754	+ col = self._shade(i)
	755	+ p.set_fill_color(*col)
	756	+ p.set_draw_color(*INK)
	757	+ p.rect(p.l_margin + 60, ly + 0.8, 4, 4, style="DF")
	758	+ p.set_xy(p.l_margin + 66, ly)
	759	+ p.set_font("helvetica", "", 7.6)
	760	+ p.set_text_color(*INK)
	761	+ pct = 100 * it["value"] / total
	762	+ p.cell(0, 5.6, f"{str(it['label'])[:40]} — {_fr(it['value'])} ({pct:.1f} %)".replace(".", ","))
	763	+ ly += 5.6
	764	+ p.set_y(max(cy + r, ly) + 6)
	765	+
	766	+ def _hourly(self):
	767	+ hh = self.d.get("hourly") or {}
	768	+ cells = hh.get("cells") or []
	769	+ if not cells:
	770	+ return
	771	+ p = self.pdf
	772	+ if p.get_y() > 190:
	773	+ p.add_page()
	774	+ self._chart_title(hh.get("title", "Activité par jour et heure"))
	775	+ x0, y0 = p.l_margin, p.get_y()
	776	+ cw, chh, lx, ly = 6.4, 6.4, 12, 5
	777	+ vmax = max((c.get("value") or 0) for c in cells) or 1
	778	+ grid = {(c.get("dow"), c.get("hour")): c.get("value") or 0 for c in cells}
	779	+ dows = ["Lun", "Mar", "Mer", "Jeu", "Ven", "Sam", "Dim"]
	780	+ p.set_font("helvetica", "", 5.8)
	781	+ p.set_text_color(*INK3)
	782	+ for h in (0, 6, 12, 18, 23):
	783	+ p.set_xy(x0 + lx + h * cw, y0)
	784	+ p.cell(cw, 3, f"{h}h", align="C")
	785	+ for d in range(7):
	786	+ p.set_xy(x0, y0 + ly + d * chh + 1.5)
	787	+ p.cell(lx - 1, 3, dows[d], align="R")
	788	+ for h in range(24):
	789	+ v = grid.get((d, h), 0)
	790	+ f = 0.1 + 0.9 * (v / vmax) if v else 0.0
	791	+ col = tuple(int(PAPER[j] + (self.accent[j] - PAPER[j]) * f) for j in range(3)) if v else (235, 233, 228)
	792	+ p.set_fill_color(*col)
	793	+ p.set_draw_color(215, 213, 207)
	794	+ p.set_line_width(0.1)
	795	+ p.rect(x0 + lx + h * cw, y0 + ly + d * chh, cw - 0.5, chh - 0.5, style="DF")
	796	+ p.set_y(y0 + ly + 7 * chh + 5)
	797	+
	798	+ def _calheat(self, hm):
	799	+ """v3 — calendrier de chaleur 26 semaines (équivalent PDF du
	800	+ CalendarHeatmap du kit front) : colonnes = semaines, lignes = jours."""
	801	+ from datetime import date as _date, timedelta as _td
	802	+ cells = hm.get("cells") or []
	803	+ vals = {c.get("date"): c.get("value") or 0 for c in cells if c.get("date")}
	804	+ if not vals:
	805	+ return
	806	+ p = self.pdf
	807	+ if p.get_y() > 215:
	808	+ p.add_page()
	809	+ self._chart_title(hm.get("title", "Calendrier d'activité"))
	810	+ try:
	811	+ end = _date.fromisoformat(max(vals))
	812	+ except ValueError:
	813	+ return
	814	+ weeks = 26
	815	+ start = end - _td(days=weeks * 7 - 1)
	816	+ start -= _td(days=start.weekday()) # lundi
	817	+ vmax = max(vals.values()) or 1
	818	+ x0, y0 = p.l_margin, p.get_y()
	819	+ cw, lx, ly = 6.3, 10, 4
	820	+ dows = ["Lun", "", "Mer", "", "Ven", "", "Dim"]
	821	+ p.set_font("helvetica", "", 5.8)
	822	+ p.set_text_color(*INK3)
	823	+ for d in range(7):
	824	+ if dows[d]:
	825	+ p.set_xy(x0, y0 + ly + d * cw + 1.2)
	826	+ p.cell(lx - 1, 3, dows[d], align="R")
	827	+ for w in range(weeks):
	828	+ monday = start + _td(days=7 * w)
	829	+ if monday.day <= 7: # étiquette de mois à la 1re semaine du mois
	830	+ p.set_xy(x0 + lx + w * cw, y0)
	831	+ p.cell(cw * 4, 3, monday.strftime("%m"))
	832	+ for d in range(7):
	833	+ day = monday + _td(days=d)
	834	+ v = vals.get(day.isoformat(), 0)
	835	+ f = 0.15 + 0.85 * (v / vmax) if v else 0.0
	836	+ col = (tuple(int(PAPER[j] + (self.accent[j] - PAPER[j]) * f)
	837	+ for j in range(3)) if v else (235, 233, 228))
	838	+ p.set_fill_color(*col)
	839	+ p.set_draw_color(215, 213, 207)
	840	+ p.set_line_width(0.1)
	841	+ p.rect(x0 + lx + w * cw, y0 + ly + d * cw, cw - 0.5, cw - 0.5,
	842	+ style="DF")
	843	+ p.set_y(y0 + ly + 7 * cw + 5)
	844	+
	845	+ # ---------- v3 : conversions bloc → tableau ----------
	846	+ @staticmethod
	847	+ def _serie_as_table(s):
	848	+ unit = s.get("unit") or "Valeur"
	849	+ cols = ["Date", unit.capitalize()]
	850	+ cmp_ = s.get("compare") or []
	851	+ if cmp_:
	852	+ cols.append("Période comparée")
	853	+ rows = []
	854	+ for i, pt in enumerate(s.get("points") or []):
	855	+ row = [str(pt.get("t", "")), pt.get("v", "")]
	856	+ if cmp_:
	857	+ row.append(cmp_[i]["v"] if i < len(cmp_) else "")
	858	+ rows.append(row)
	859	+ return {"id": s.get("id"), "title": s.get("title", ""),
	860	+ "columns": cols, "rows": rows}
	861	+
	862	+ @staticmethod
	863	+ def _multi_as_table(ms):
	864	+ labels = [s.get("label", "") for s in (ms.get("series") or [])][:4]
	865	+ by_t: dict[str, dict] = {}
	866	+ for s in (ms.get("series") or [])[:4]:
	867	+ for pt in s.get("points") or []:
	868	+ by_t.setdefault(str(pt.get("t", "")), {})[s.get("label", "")] = pt.get("v")
	869	+ rows = [[t] + [by_t[t].get(lbl, "") for lbl in labels]
	870	+ for t in sorted(by_t)]
	871	+ return {"id": ms.get("id"), "title": ms.get("title", ""),
	872	+ "columns": ["Date"] + labels, "rows": rows}
	873	+
	874	+ @staticmethod
	875	+ def _stacked_as_table(st):
	876	+ keys = (st.get("keys") or [])[:6]
	877	+ rows = []
	878	+ for pt in st.get("points") or []:
	879	+ vs = [(pt.get("values") or [])[j] if j < len(pt.get("values") or []) else 0
	880	+ for j in range(len(keys))]
	881	+ rows.append([str(pt.get("t", ""))] + vs + [sum(v or 0 for v in vs)])
	882	+ return {"id": st.get("id"), "title": st.get("title", ""),
	883	+ "columns": ["Date"] + list(keys) + ["Total"], "rows": rows}
	884	+
	885	+ @staticmethod
	886	+ def _items_as_table(id_, title, items, label_col="Libellé"):
	887	+ items = items or []
	888	+ with_delta = any(it.get("delta_pct") is not None for it in items)
	889	+ cols = [label_col, "Valeur"] + (["delta %"] if with_delta else [])
	890	+ rows = []
	891	+ for it in items:
	892	+ row = [str(it.get("label", "")), it.get("value", "")]
	893	+ if with_delta:
	894	+ d = it.get("delta_pct")
	895	+ row.append("" if d is None else f"{'+' if d >= 0 else ''}{d} %")
	896	+ rows.append(row)
	897	+ return {"id": id_, "title": title, "columns": cols, "rows": rows}
	898	+
	899	+ def _kpis_as_table(self):
	900	+ rows = []
	901	+ for k in self.d.get("kpis") or []:
	902	+ v = k.get("value")
	903	+ val = (_fr(v) if isinstance(v, (int, float)) else str(v)) + \
	904	+ ((" " + k["unit"]) if k.get("unit") else "")
	905	+ d = k.get("delta_pct")
	906	+ rows.append([str(k.get("label", "")), val,
	907	+ "" if d is None else f"{'+' if d >= 0 else ''}{d} %"])
	908	+ return {"id": "kpis", "title": "Indicateurs clés",
	909	+ "columns": ["Indicateur", "Valeur", "delta %"], "rows": rows}
	910	+
	911	+ def _gauges_as_table(self):
	912	+ rows = [[str(g.get("label", "")),
	913	+ f"{_fr(g['value'])}{' ' + g['unit'] if g.get('unit') else ''}",
	914	+ _fr(g["max"]), f"{100.0 * g['value'] / g['max']:.0f} %"]
	915	+ for g in self.d.get("gauges") or []
	916	+ if isinstance(g.get("value"), (int, float)) and g.get("max")]
	917	+ return {"id": "gauges", "title": "Taux & couvertures",
	918	+ "columns": ["Mesure", "Valeur", "Max", "Part"], "rows": rows}
	919	+
	920	+ def _records_as_table(self):
	921	+ rows = [[str(r.get("label", "")), str(r.get("value", "")),
	922	+ str(r.get("date", "") or "")]
	923	+ for r in self.d.get("records") or []]
	924	+ return {"id": "records", "title": "Records & faits marquants",
	925	+ "columns": ["Fait marquant", "Valeur", "Date"], "rows": rows}
	926	+
	927	+ @staticmethod
	928	+ def _heatmap_as_table(hm, title):
	929	+ cells = sorted((hm.get("cells") or []),
	930	+ key=lambda c: -(c.get("value") or 0))[:40]
	931	+ return {"id": "heatmap", "title": title + " — jours les plus chargés",
	932	+ "columns": ["Date", "Valeur"],
	933	+ "rows": [[c.get("date", ""), c.get("value") or 0] for c in cells]}
	934	+
	935	+ @staticmethod
	936	+ def _hourly_as_table(hr, title):
	937	+ days = ["Lundi", "Mardi", "Mercredi", "Jeudi", "Vendredi", "Samedi",
	938	+ "Dimanche"]
	939	+ cells = sorted((hr.get("cells") or []),
	940	+ key=lambda c: -(c.get("value") or 0))[:40]
	941	+ return {"id": "hourly", "title": title + " — créneaux les plus actifs",
	942	+ "columns": ["Jour", "Heure", "Valeur"],
	943	+ "rows": [[days[c["dow"]] if 0 <= c.get("dow", -1) <= 6 else "?",
	944	+ f"{c.get('hour', '?')} h", c.get("value") or 0]
	945	+ for c in cells]}
	946	+
	947	+ # ---------- v3 : rendu d'un bloc du rapport personnalisé ----------
	948	+ def _find(self, coll: str, id_: str):
	949	+ for it in self.d.get(coll) or []:
	950	+ if str(it.get("id")) == id_:
	951	+ return it
	952	+ return None
	953	+
	954	+ def _toc_mark(self, title: str):
	955	+ """Blocs graphiques du mode personnalisé : entrée de sommaire sans
	956	+ _section_title (le graphique porte déjà son titre)."""
	957	+ if self.pdf.get_y() > 235:
	958	+ self.pdf.add_page()
	959	+ self.toc.append((title, self.pdf.page_no()))
	960	+
	961	+ def _render_block(self, key: str, render: str):
	962	+ section, _, id_ = key.partition(":")
	963	+ if section == "kpis":
	964	+ self._table(self._kpis_as_table()) if render == "table" else self._kpis()
	965	+ elif section == "gauges":
	966	+ self._table(self._gauges_as_table()) if render == "table" else self._gauges()
	967	+ elif section == "records":
	968	+ self._table(self._records_as_table()) if render == "table" else self._records()
	969	+ elif section == "series":
	970	+ s = self._find("series", id_)
	971	+ if not s:
	972	+ return
	973	+ if render == "table":
	974	+ self._table(self._serie_as_table(s), max_rows=400)
	975	+ else:
	976	+ s2 = dict(s)
	977	+ if render in ("line", "area", "bar"):
	978	+ s2["kind"] = render
	979	+ self._toc_mark(s2.get("title", ""))
	980	+ if s2.get("kind") == "bar":
	981	+ self._vbars(s2)
	982	+ else:
	983	+ self._line_chart(s2, with_stats=True)
	984	+ elif section == "multiseries":
	985	+ ms = self._find("multiseries", id_)
	986	+ if not ms:
	987	+ return
	988	+ if render == "table":
	989	+ self._table(self._multi_as_table(ms), max_rows=400)
	990	+ else:
	991	+ self._toc_mark(ms.get("title", ""))
	992	+ self._multiline(ms)
	993	+ elif section == "stacked":
	994	+ st = self._find("stacked", id_)
	995	+ if not st:
	996	+ return
	997	+ if render == "table":
	998	+ self._table(self._stacked_as_table(st), max_rows=400)
	999	+ else:
	1000	+ self._toc_mark(st.get("title", ""))
	1001	+ self._stacked(st)
	1002	+ elif section == "breakdowns":
	1003	+ b = self._find("breakdowns", id_)
	1004	+ if not b:
	1005	+ return
	1006	+ if render == "table":
	1007	+ self._table(self._items_as_table(id_, b.get("title", ""),
	1008	+ b.get("items")), max_rows=400)
	1009	+ else:
	1010	+ self._toc_mark(b.get("title", ""))
	1011	+ if render == "donut":
	1012	+ self._donut(b)
	1013	+ else:
	1014	+ self._bars(b.get("title", ""), b.get("items"))
	1015	+ elif section == "distributions":
	1016	+ d = self._find("distributions", id_)
	1017	+ if not d:
	1018	+ return
	1019	+ if render == "table":
	1020	+ bins = [{"label": bn.get("label"), "value": bn.get("value")}
	1021	+ for bn in d.get("bins") or []]
	1022	+ self._table(self._items_as_table(id_, d.get("title", ""), bins,
	1023	+ label_col="Tranche"))
	1024	+ else:
	1025	+ self._toc_mark(d.get("title", ""))
	1026	+ self._vbars(d)
	1027	+ elif section == "geo":
	1028	+ geo = self.d.get("geo") or {}
	1029	+ if not geo.get("items"):
	1030	+ return
	1031	+ title = geo.get("title", "Répartition géographique")
	1032	+ if render == "table":
	1033	+ self._table(self._items_as_table("geo", title, geo["items"],
	1034	+ label_col="Zone"), max_rows=400)
	1035	+ else:
	1036	+ self._toc_mark(title)
	1037	+ self._bars(title, geo["items"])
	1038	+ elif section == "heatmap":
	1039	+ hm = self.d.get("heatmap") or {}
	1040	+ if not hm.get("cells"):
	1041	+ return
	1042	+ title = hm.get("title", "Calendrier d'activité")
	1043	+ if render == "table":
	1044	+ self._table(self._heatmap_as_table(hm, title))
	1045	+ else:
	1046	+ self._toc_mark(title)
	1047	+ self._calheat(hm)
	1048	+ elif section == "hourly":
	1049	+ hr = self.d.get("hourly") or {}
	1050	+ if not hr.get("cells"):
	1051	+ return
	1052	+ title = hr.get("title", "Activité par jour et heure")
	1053	+ if render == "table":
	1054	+ self._table(self._hourly_as_table(hr, title))
	1055	+ else:
	1056	+ self._toc_mark(title)
	1057	+ self._hourly()
	1058	+ elif section == "tables":
	1059	+ t = self._find("tables", id_)
	1060	+ if t:
	1061	+ self._table(t, max_rows=400)
	1062	+
	1063	+ def _table(self, t, max_rows=200):
	1064	+ p = self.pdf
	1065	+ cols = t.get("columns") or []
	1066	+ rows = t.get("rows") or []
	1067	+ if not cols or not rows:
	1068	+ return
	1069	+ self._section_title(t.get("title", "Tableau"))
	1070	+ w = 174 / len(cols)
	1071	+ def head():
	1072	+ p.set_font("helvetica", "B", 7.6)
	1073	+ p.set_fill_color(*INK)
	1074	+ p.set_text_color(*WHITE)
	1075	+ for c in cols:
	1076	+ p.cell(w, 6, " " + str(c)[:30], fill=True)
	1077	+ p.ln(6)
	1078	+ head()
	1079	+ p.set_text_color(*INK)
	1080	+ for i, row in enumerate(rows[:max_rows]):
	1081	+ if p.get_y() > 262:
	1082	+ p.add_page()
	1083	+ head()
	1084	+ p.set_text_color(*INK)
	1085	+ p.set_font("helvetica", "", 7.4)
	1086	+ p.set_fill_color(*(SURFACE2 if i % 2 else WHITE))
	1087	+ for cell in row:
	1088	+ txt = _fr(cell) if isinstance(cell, (int, float)) else str(cell)
	1089	+ p.cell(w, 5.4, " " + txt[:34], fill=True)
	1090	+ p.ln(5.4)
	1091	+ if len(rows) > max_rows:
	1092	+ p.set_font("helvetica", "", 7)
	1093	+ p.set_text_color(*INK3)
	1094	+ p.cell(0, 5, f"… {len(rows) - max_rows} lignes supplémentaires non imprimées")
	1095	+ p.ln(6)
	1096	+
	1097	+ def _records(self):
	1098	+ recs = self.d.get("records") or []
	1099	+ if not recs:
	1100	+ return
	1101	+ self._section_title("Records & faits marquants")
	1102	+ p = self.pdf
	1103	+ for r in recs[:14]:
	1104	+ if p.get_y() > 258:
	1105	+ p.add_page()
	1106	+ y = p.get_y()
	1107	+ self._card(p.l_margin, y, 174, 11, fill=SURFACE2)
	1108	+ p.set_xy(p.l_margin + 4, y + 2)
	1109	+ p.set_font("helvetica", "", 8.6)
	1110	+ p.set_text_color(*INK2)
	1111	+ p.cell(96, 7, str(r.get("label", ""))[:70])
	1112	+ p.set_font("helvetica", "B", 9)
	1113	+ p.set_text_color(*INK)
	1114	+ p.cell(52, 7, str(r.get("value", ""))[:36], align="R")
	1115	+ p.set_font("helvetica", "", 7.6)
	1116	+ p.set_text_color(*INK3)
	1117	+ p.cell(20, 7, str(r.get("date", "") or ""), align="R")
	1118	+ p.set_y(y + 13.5)
	1119	+ p.ln(4)
	1120	+
	1121	+ def _final_page(self):
	1122	+ p = self.pdf
	1123	+ p.add_page()
	1124	+ self._kicker("Groupe KA · contact")
	1125	+ p.set_font("helvetica", "B", 15)
	1126	+ p.set_text_color(*INK)
	1127	+ p.cell(0, 8, "Coordonnées du Groupe KA")
	1128	+ p.ln(12)
	1129	+ for email, role in EMAILS:
	1130	+ p.set_font("helvetica", "B", 10.5)
	1131	+ p.set_text_color(*INK)
	1132	+ p.cell(0, 6, email)
	1133	+ p.ln(5.5)
	1134	+ p.set_font("helvetica", "", 8.6)
	1135	+ p.set_text_color(*INK3)
	1136	+ p.cell(0, 5, role)
	1137	+ p.ln(8)
	1138	+ p.ln(2)
	1139	+ p.set_font("helvetica", "B", 10)
	1140	+ p.set_text_color(*GREEN)
	1141	+ p.cell(0, 6, "groupe-ka.com — le portail de l'écosystème ·Ka")
	1142	+ p.ln(10)
	1143	+ p.set_draw_color(*self.accent)
	1144	+ p.set_line_width(0.8)
	1145	+ p.line(p.l_margin, p.get_y(), p.l_margin + 30, p.get_y())
	1146	+ p.ln(4)
	1147	+ p.set_font("helvetica", "", 8.6)
	1148	+ p.set_text_color(*INK2)
	1149	+ p.multi_cell(160, 4.6, DISCLAIMER)
	1150	+ p.ln(4)
	1151	+ p.set_font("helvetica", "", 7.6)
	1152	+ p.set_text_color(*INK3)
	1153	+ p.multi_cell(
	1154	+ 160, 4.2,
	1155	+ "Mentions : rapport généré automatiquement à partir des données réelles de la "
	1156	+ "plateforme au moment indiqué en couverture. Conditions d'utilisation, politique "
	1157	+ "de confidentialité et protection des renseignements personnels (Loi 25) : "
	1158	+ "groupe-ka.com/conditions · /confidentialite · /loi-25.",
	1159	+ )
	1160	+
	1161	+ # ---------- groupes de sections ----------
	1162	+ def _all_series(self, with_stats=True):
	1163	+ for s in self.d.get("series") or []:
	1164	+ self._line_chart(s, with_stats=with_stats)
	1165	+ for ms in self.d.get("multiseries") or []:
	1166	+ self._multiline(ms)
	1167	+ for st in self.d.get("stacked") or []:
	1168	+ self._stacked(st)
	1169	+
	1170	+ def _all_breakdowns(self):
	1171	+ for b in self.d.get("breakdowns") or []:
	1172	+ if b.get("kind") == "donut":
	1173	+ self._donut(b)
	1174	+ else:
	1175	+ self._bars(b.get("title", ""), b.get("items"))
	1176	+ for dist in self.d.get("distributions") or []:
	1177	+ self._vbars(dist)
	1178	+ geo = self.d.get("geo")
	1179	+ if geo:
	1180	+ self._bars(geo.get("title", "Répartition géographique"), geo.get("items"))
	1181	+ self._hourly()
	1182	+
	1183	+ def build(self) -> bytes:
	1184	+ p = self.pdf
	1185	+ p.alias_nb_pages()
	1186	+ self._cover()
	1187	+ with_toc = self.mode in ("complet", "donnees", CUSTOM_MODE)
	1188	+ toc_page_no = None
	1189	+ if self.mode == "synthese":
	1190	+ p.add_page()
	1191	+ self._kpis()
	1192	+ self._gauges()
	1193	+ self._records()
	1194	+ self._final_page()
	1195	+ elif self.mode == "tendances":
	1196	+ p.add_page()
	1197	+ self._kpis()
	1198	+ self._section_title("Évolution & tendances")
	1199	+ self._all_series(with_stats=True)
	1200	+ self._records()
	1201	+ self._final_page()
	1202	+ elif self.mode == "repartitions":
	1203	+ p.add_page()
	1204	+ self._section_title("Répartitions, distributions & géographie")
	1205	+ self._all_breakdowns()
	1206	+ self._final_page()
	1207	+ elif self.mode == "donnees":
	1208	+ p.add_page()
	1209	+ toc_page_no = p.page_no()
	1210	+ for t in self.d.get("tables") or []:
	1211	+ self._table(t, max_rows=400)
	1212	+ self._final_page()
	1213	+ elif self.mode == CUSTOM_MODE:
	1214	+ p.add_page()
	1215	+ toc_page_no = p.page_no()
	1216	+ p.add_page()
	1217	+ known = {b["key"]: b for b in catalog(self.d)}
	1218	+ for blk in self.spec.get("blocks") or []:
	1219	+ key = str(blk.get("key", ""))
	1220	+ b = known.get(key)
	1221	+ if not b:
	1222	+ continue
	1223	+ render = str(blk.get("render") or "")
	1224	+ if render not in b["renders"]:
	1225	+ render = b["default_render"]
	1226	+ self._render_block(key, render)
	1227	+ self._final_page()
	1228	+ else: # complet
	1229	+ p.add_page()
	1230	+ toc_page_no = p.page_no()
	1231	+ p.add_page()
	1232	+ self._kpis()
	1233	+ self._gauges()
	1234	+ if (self.d.get("series") or self.d.get("multiseries") or self.d.get("stacked")):
	1235	+ self._section_title("Évolution & tendances")
	1236	+ self._all_series(with_stats=True)
	1237	+ if (self.d.get("breakdowns") or self.d.get("distributions") or self.d.get("geo") or self.d.get("hourly")):
	1238	+ self._section_title("Répartitions, distributions & géographie")
	1239	+ self._all_breakdowns()
	1240	+ for t in self.d.get("tables") or []:
	1241	+ self._table(t)
	1242	+ self._records()
	1243	+ self._final_page()
	1244	+ # sommaire écrit sur la page réservée
	1245	+ if toc_page_no is not None:
	1246	+ last_page = p.page
	1247	+ p.page = toc_page_no
	1248	+ p.set_y(22)
	1249	+ p.set_font("helvetica", "B", 15)
	1250	+ p.set_text_color(*INK)
	1251	+ p.cell(0, 8, "Sommaire")
	1252	+ p.ln(12)
	1253	+ p.set_font("helvetica", "", 9.5)
	1254	+ for title, page_no in self.toc:
	1255	+ p.set_text_color(*INK)
	1256	+ p.cell(140, 6.5, title[:80])
	1257	+ p.set_text_color(*INK3)
	1258	+ p.cell(0, 6.5, str(page_no), align="R")
	1259	+ p.ln(6.5)
	1260	+ p.page = last_page
	1261	+ return bytes(p.output())
	1262	+
	1263	+
	1264	+def filename(platform_id: str, period: str, mode: str = "complet") -> str:
	1265	+ today = datetime.now(ZoneInfo("America/Toronto")).strftime("%Y-%m-%d")
	1266	+ suffix = "" if mode in ("", "complet") else f"_{mode}"
	1267	+ return f"groupe-ka_{platform_id}_stats_{period}{suffix}_{today}.pdf"

added immoka/mortgage/__init__.py +7 −0

		`@@ -0,0 +1,7 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/ : moteur hypothécaire canadien — collecte des taux publiés par les
	5	+# institutions financières, historisation, calculs (composition
	6	+# semestrielle canadienne, SCHL, stress test, abordabilité).
	7	+# -----------------------------------------------------------------------------

added immoka/mortgage/api.py +373 −0

		`@@ -0,0 +1,373 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/api.py : routes /api/mortgage/* — taux courants, meilleur taux,
	5	+# historique, santé des providers, calculateur canadien, abordabilité.
	6	+# Lecture seule sur mortgage.db (le scheduler écrit) ; cache applicatif
	7	+# 5 min sur les lectures ; jamais d'internals de scraping exposés (le champ
	8	+# raw est retiré au niveau du store).
	9	+# -----------------------------------------------------------------------------
	10	+from __future__ import annotations
	11	+
	12	+import time
	13	+
	14	+from fastapi import APIRouter, Body, HTTPException, Query
	15	+
	16	+from . import calc, cmhc, store
	17	+
	18	+router = APIRouter(prefix="/api/mortgage", tags=["mortgage"])
	19	+
	20	+CACHE_TTL_S = 300
	21	+_cache: dict[str, tuple[float, object]] = {}
	22	+
	23	+RATE_TYPES = {"fixed", "variable", "adjustable", "other"}
	24	+KINDS = {"posted", "special"}
	25	+INSURED = {"insured", "insurable", "uninsured", "unknown"}
	26	+
	27	+
	28	+def _cached(key: str, builder):
	29	+ hit = _cache.get(key)
	30	+ now = time.time()
	31	+ if hit and now - hit[0] < CACHE_TTL_S:
	32	+ return hit[1]
	33	+ value = builder()
	34	+ _cache[key] = (now, value)
	35	+ if len(_cache) > 512: # borne mémoire : purge des entrées expirées
	36	+ for k in [k for k, (t, _) in _cache.items() if now - t >= CACHE_TTL_S]:
	37	+ _cache.pop(k, None)
	38	+ return value
	39	+
	40	+
	41	+def _check(value, allowed: set, label: str):
	42	+ if value is not None and value not in allowed:
	43	+ raise HTTPException(422, f"{label} invalide : {value}")
	44	+ return value
	45	+
	46	+
	47	+@router.get("/rates")
	48	+def rates(rate_type: str \| None = None, term_months: int \| None = None,
	49	+ kind: str \| None = None, insured_status: str \| None = None,
	50	+ purpose: str \| None = Query("purchase"),
	51	+ provider: str \| None = None):
	52	+ """Taux courants (dernière donnée valide par produit), filtrables."""
	53	+ _check(rate_type, RATE_TYPES, "rate_type")
	54	+ _check(kind, KINDS, "kind")
	55	+ _check(insured_status, INSURED, "insured_status")
	56	+ if purpose in ("", "all"):
	57	+ purpose = None
	58	+ key = f"rates\|{rate_type}\|{term_months}\|{kind}\|{insured_status}\|{purpose}\|{provider}"
	59	+
	60	+ def build():
	61	+ con = store.connect()
	62	+ rows = store.current_rates(
	63	+ con, rate_type=rate_type, term_months=term_months, kind=kind,
	64	+ insured_status=insured_status, purpose=purpose, provider=provider)
	65	+ con.close()
	66	+ return {"count": len(rows), "rates": rows,
	67	+ "stale_hours_threshold": store.STALE_H}
	68	+ return _cached(key, build)
	69	+
	70	+
	71	+@router.get("/rates/best")
	72	+def rates_best(rate_type: str = "fixed", term_months: int = 60,
	73	+ insured_status: str \| None = None, purpose: str = "purchase"):
	74	+ """Meilleur taux courant par produit comparable + comparateur par banque."""
	75	+ _check(rate_type, RATE_TYPES, "rate_type")
	76	+ _check(insured_status, INSURED, "insured_status")
	77	+ key = f"best\|{rate_type}\|{term_months}\|{insured_status}\|{purpose}"
	78	+
	79	+ def build():
	80	+ con = store.connect()
	81	+ best = store.best_rate(con, rate_type=rate_type,
	82	+ term_months=term_months,
	83	+ insured_status=insured_status, purpose=purpose)
	84	+ con.close()
	85	+ if best is None:
	86	+ raise HTTPException(404, "Aucun taux courant pour ces critères")
	87	+ return best
	88	+ return _cached(key, build)
	89	+
	90	+
	91	+@router.get("/rates/history")
	92	+def rates_history(rate_type: str = "fixed", term_months: int = 60,
	93	+ provider: str \| None = None, kind: str \| None = None,
	94	+ days: int = 365):
	95	+ """Périodes de validité par produit — reconstruit « le taux X à date ». """
	96	+ _check(rate_type, RATE_TYPES, "rate_type")
	97	+ _check(kind, KINDS, "kind")
	98	+ days = max(1, min(days, 730))
	99	+ key = f"hist\|{rate_type}\|{term_months}\|{provider}\|{kind}\|{days}"
	100	+
	101	+ def build():
	102	+ con = store.connect()
	103	+ rows = store.history(con, rate_type, term_months,
	104	+ provider=provider, kind=kind, days=days)
	105	+ con.close()
	106	+ return {"count": len(rows), "days": days, "history": rows}
	107	+ return _cached(key, build)
	108	+
	109	+
	110	+@router.get("/providers")
	111	+def providers():
	112	+ """Santé des connecteurs de taux (OK / WARNING / ERROR + fraîcheur)."""
	113	+ def build():
	114	+ from .providers import PROVIDERS
	115	+ con = store.connect()
	116	+ health = store.provider_health(con)
	117	+ con.close()
	118	+ names = {slug: cls.institution for slug, cls in PROVIDERS.items()}
	119	+ urls = {slug: cls.source_url for slug, cls in PROVIDERS.items()}
	120	+ out = []
	121	+ for h in health:
	122	+ out.append({
	123	+ "provider": h["provider"],
	124	+ "institution": names.get(h["provider"], h["provider"]),
	125	+ "source_url": urls.get(h["provider"]),
	126	+ "level": h["level"],
	127	+ "status": h["status"],
	128	+ "age_minutes": h["age_minutes"],
	129	+ "current_products": h["current_products"],
	130	+ "last_data_at": h["last_data_at"],
	131	+ })
	132	+ return {"providers": out,
	133	+ "registered": sorted(names),
	134	+ "stale_hours_threshold": store.STALE_H}
	135	+ return _cached("providers", build)
	136	+
	137	+
	138	+@router.get("/market")
	139	+def market(rate_type: str = "fixed", term_months: int = 60):
	140	+ """Métriques Mortgage Intelligence pour un produit donné."""
	141	+ _check(rate_type, RATE_TYPES, "rate_type")
	142	+
	143	+ def build():
	144	+ con = store.connect()
	145	+ stats = store.market_stats(con, rate_type=rate_type,
	146	+ term_months=term_months)
	147	+ con.close()
	148	+ if stats is None:
	149	+ raise HTTPException(404, "Aucun taux courant pour ces critères")
	150	+ return stats
	151	+ return _cached(f"market\|{rate_type}\|{term_months}", build)
	152	+
	153	+
	154	+@router.get("/intelligence")
	155	+def intelligence():
	156	+ """Vue d'ensemble du marché : les produits phares en un appel."""
	157	+ def build():
	158	+ con = store.connect()
	159	+ combos = [("fixed", 12), ("fixed", 36), ("fixed", 48),
	160	+ ("fixed", 60), ("fixed", 120), ("variable", 60)]
	161	+ grid = []
	162	+ for rtype, term in combos:
	163	+ s = store.market_stats(con, rate_type=rtype, term_months=term)
	164	+ if s:
	165	+ grid.append(s)
	166	+ prime_rows = store.current_rates(con, rate_type="other")
	167	+ con.close()
	168	+ prime = [{"institution": r["institution"], "rate": r["rate"],
	169	+ "product_name": r["product_name"],
	170	+ "age_minutes": r["age_minutes"]}
	171	+ for r in prime_rows if "préférentiel" in
	172	+ (r["product_name"] or "").lower() or "prime" in
	173	+ (r["product_name"] or "").lower()]
	174	+ return {"products": grid, "prime_rates": prime}
	175	+ return _cached("intelligence", build)
	176	+
	177	+
	178	+# ---------------------------------------------------------------------------
	179	+# Calculateur
	180	+# ---------------------------------------------------------------------------
	181	+
	182	+def _pick_rate(rate_type: str, term_months: int,
	183	+ insured_status: str \| None) -> dict \| None:
	184	+ con = store.connect()
	185	+ best = store.best_rate(con, rate_type=rate_type, term_months=term_months,
	186	+ insured_status=insured_status)
	187	+ con.close()
	188	+ return best
	189	+
	190	+
	191	+def _validate_scenario(price: float, down: float, amort: int, term: int,
	192	+ frequency: str) -> None:
	193	+ if price <= 0 or price > 100_000_000:
	194	+ raise HTTPException(422, "Prix invalide")
	195	+ if down < 0 or down >= price:
	196	+ raise HTTPException(422, "Mise de fonds invalide")
	197	+ if amort not in calc.AMORTIZATIONS_YEARS and not (5 <= amort <= 30):
	198	+ raise HTTPException(422, "Amortissement invalide (5–30 ans)")
	199	+ if not 3 <= term <= 120:
	200	+ raise HTTPException(422, "Terme invalide (3–120 mois)")
	201	+ if frequency not in calc.FREQUENCIES:
	202	+ raise HTTPException(422, f"Fréquence invalide : {frequency}")
	203	+
	204	+
	205	+@router.post("/calculate")
	206	+def calculate(body: dict = Body(...)):
	207	+ """Calcul hypothécaire canadien complet pour un scénario.
	208	+
	209	+ Entrées : price, down_payment (ou down_payment_pct), amortization_years,
	210	+ term_months, frequency, rate_type, rate (sinon meilleur taux observé),
	211	+ insured_status?, include_schedule?, income?, other_debts_monthly?,
	212	+ property_tax_monthly?, heating_monthly?, condo_fees_monthly?.
	213	+ """
	214	+ try:
	215	+ price = float(body.get("price") or 0)
	216	+ if body.get("down_payment") is not None:
	217	+ down = float(body["down_payment"])
	218	+ else:
	219	+ down = price * float(body.get("down_payment_pct") or 20) / 100
	220	+ amort = int(body.get("amortization_years") or 25)
	221	+ term = int(body.get("term_months") or 60)
	222	+ frequency = str(body.get("frequency") or "monthly")
	223	+ rate_type = str(body.get("rate_type") or "fixed")
	224	+ except (TypeError, ValueError):
	225	+ raise HTTPException(422, "Paramètres numériques invalides")
	226	+ _check(rate_type, {"fixed", "variable"}, "rate_type")
	227	+ _validate_scenario(price, down, amort, term, frequency)
	228	+
	229	+ quote = cmhc.insurance_quote(price, down, amort)
	230	+ rate_source = None
	231	+ rate = body.get("rate")
	232	+ if rate is None:
	233	+ insured = "insured" if quote["required"] and quote["eligible"] else None
	234	+ best = _pick_rate(rate_type, term, insured)
	235	+ if best is None:
	236	+ raise HTTPException(
	237	+ 503, "Aucun taux courant disponible — réessayez plus tard")
	238	+ rate = best["rate"]
	239	+ rate_source = {k: best[k] for k in
	240	+ ("provider", "institution", "product_name", "kind",
	241	+ "rate", "apr", "insured_status", "source_url",
	242	+ "last_checked", "age_minutes", "stale")}
	243	+ rate = float(rate)
	244	+ if not 0 < rate <= 25:
	245	+ raise HTTPException(422, "Taux invalide")
	246	+ if quote["required"] and not quote["eligible"]:
	247	+ principal = price - down # non assurable : calcul quand même, signalé
	248	+ else:
	249	+ principal = quote["total_mortgage"] if quote["required"] else price - down
	250	+
	251	+ compounding = "semi-annual" if rate_type == "fixed" else "monthly"
	252	+ pay = calc.payment(principal, rate, amort, frequency, compounding)
	253	+ monthly_eq = calc.payment(principal, rate, amort, "monthly", compounding)
	254	+ q_rate = calc.qualifying_rate(rate)
	255	+ q_pay = calc.payment(principal, q_rate, amort, frequency, compounding)
	256	+ out = {
	257	+ "inputs": {"price": price, "down_payment": round(down, 2),
	258	+ "down_payment_pct": round(down / price * 100, 2),
	259	+ "rate": rate, "rate_type": rate_type,
	260	+ "term_months": term, "amortization_years": amort,
	261	+ "frequency": frequency, "compounding": compounding},
	262	+ "insurance": quote,
	263	+ "principal": round(principal, 2),
	264	+ "payment": pay,
	265	+ "payment_monthly_equivalent": monthly_eq,
	266	+ "qualifying": {"rate": q_rate, "payment": q_pay,
	267	+ "note": "Test de résistance : max(taux + 2, 5,25 %)"},
	268	+ "term": calc.term_summary(principal, rate, amort, term,
	269	+ frequency, compounding),
	270	+ "stress": calc.stress_scenarios(principal, rate, amort,
	271	+ frequency, compounding),
	272	+ "renewal": calc.renewal_scenarios(principal, rate, amort, term,
	273	+ frequency, compounding),
	274	+ "payoff_years": calc.payoff_years(principal, rate, amort,
	275	+ frequency, compounding),
	276	+ "rate_source": rate_source,
	277	+ }
	278	+ rows = calc.schedule(principal, rate, amort, frequency, compounding)
	279	+ out["annual"] = calc.annual_rollup(rows, frequency)
	280	+ if body.get("include_schedule"):
	281	+ out["schedule"] = rows
	282	+ income = body.get("income")
	283	+ if income:
	284	+ out["ratios"] = calc.gds_tds(
	285	+ float(income), monthly_eq,
	286	+ float(body.get("property_tax_monthly") or 0),
	287	+ float(body.get("heating_monthly") or 0),
	288	+ float(body.get("condo_fees_monthly") or 0),
	289	+ float(body.get("other_debts_monthly") or 0))
	290	+ return out
	291	+
	292	+
	293	+@router.post("/affordability")
	294	+def affordability(body: dict = Body(...)):
	295	+ """Capacité d'achat : prix max selon un versement cible OU selon les
	296	+ revenus (ABD/ATD au taux de qualification) ; taux requis pour un
	297	+ versement cible vs meilleur taux observé."""
	298	+ try:
	299	+ amort = int(body.get("amortization_years") or 25)
	300	+ term = int(body.get("term_months") or 60)
	301	+ frequency = str(body.get("frequency") or "monthly")
	302	+ rate_type = str(body.get("rate_type") or "fixed")
	303	+ down = float(body.get("down_payment") or 0)
	304	+ except (TypeError, ValueError):
	305	+ raise HTTPException(422, "Paramètres numériques invalides")
	306	+ _check(rate_type, {"fixed", "variable"}, "rate_type")
	307	+ if frequency not in calc.FREQUENCIES:
	308	+ raise HTTPException(422, f"Fréquence invalide : {frequency}")
	309	+
	310	+ rate = body.get("rate")
	311	+ rate_source = None
	312	+ if rate is None:
	313	+ best = _pick_rate(rate_type, term, None)
	314	+ if best is None:
	315	+ raise HTTPException(
	316	+ 503, "Aucun taux courant disponible — réessayez plus tard")
	317	+ rate = best["rate"]
	318	+ rate_source = {k: best[k] for k in
	319	+ ("provider", "institution", "product_name", "kind",
	320	+ "rate", "source_url", "age_minutes", "stale")}
	321	+ rate = float(rate)
	322	+ if not 0 < rate <= 25:
	323	+ raise HTTPException(422, "Taux invalide")
	324	+ compounding = "semi-annual" if rate_type == "fixed" else "monthly"
	325	+ q_rate = calc.qualifying_rate(rate)
	326	+ out: dict = {"rate": rate, "qualifying_rate": q_rate,
	327	+ "rate_source": rate_source}
	328	+
	329	+ target = body.get("target_payment_monthly")
	330	+ if target:
	331	+ target = float(target)
	332	+ loan = calc.max_loan(target, rate, amort, "monthly", compounding)
	333	+ loan_q = calc.max_loan(target, q_rate, amort, "monthly", compounding)
	334	+ out["from_payment"] = {
	335	+ "target_payment_monthly": target,
	336	+ "max_loan": loan, "max_price": round(loan + down, 2),
	337	+ "max_loan_stress_tested": loan_q,
	338	+ "max_price_stress_tested": round(loan_q + down, 2),
	339	+ }
	340	+ income = body.get("income")
	341	+ if income:
	342	+ income = float(income)
	343	+ gds_room = income / 12 * 0.39 \
	344	+ - float(body.get("property_tax_monthly") or 0) \
	345	+ - float(body.get("heating_monthly") or 0) \
	346	+ - float(body.get("condo_fees_monthly") or 0) * 0.5
	347	+ tds_room = income / 12 * 0.44 \
	348	+ - float(body.get("property_tax_monthly") or 0) \
	349	+ - float(body.get("heating_monthly") or 0) \
	350	+ - float(body.get("condo_fees_monthly") or 0) * 0.5 \
	351	+ - float(body.get("other_debts_monthly") or 0)
	352	+ room = max(0.0, min(gds_room, tds_room))
	353	+ loan_q = calc.max_loan(room, q_rate, amort, "monthly", compounding)
	354	+ out["from_income"] = {
	355	+ "income": income, "max_payment_monthly": round(room, 2),
	356	+ "max_loan_stress_tested": loan_q,
	357	+ "max_price_estimate": round(loan_q + down, 2),
	358	+ "note": ("Indicatif seulement (ABD 39 % / ATD 44 % au taux de "
	359	+ "qualification) — ne constitue pas une préapprobation."),
	360	+ }
	361	+ principal = body.get("principal")
	362	+ target_rate_payment = body.get("required_rate_for_payment")
	363	+ if principal and target_rate_payment:
	364	+ req = calc.required_rate(float(principal), float(target_rate_payment),
	365	+ amort, "monthly", compounding)
	366	+ out["required_rate"] = {
	367	+ "principal": float(principal),
	368	+ "target_payment_monthly": float(target_rate_payment),
	369	+ "rate": req,
	370	+ "achievable_now": req is not None and req >= rate,
	371	+ "best_observed": rate,
	372	+ }
	373	+ return out

added immoka/mortgage/calc.py +257 −0

		`@@ -0,0 +1,257 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/calc.py : mathématiques hypothécaires canadiennes.
	5	+# Taux fixes : intérêt composé SEMESTRIELLEMENT, non à l'avance (Loi sur
	6	+# l'intérêt, art. 6) — jamais la formule américaine (composition mensuelle).
	7	+# Taux variables : composition mensuelle (convention majoritaire des
	8	+# prêteurs canadiens).
	9	+# -----------------------------------------------------------------------------
	10	+from __future__ import annotations
	11	+
	12	+import math
	13	+
	14	+# Fréquences de paiement : nombre de versements par année.
	15	+FREQUENCIES: dict[str, int] = {
	16	+ "monthly": 12,
	17	+ "semimonthly": 24,
	18	+ "biweekly": 26,
	19	+ "accelerated-biweekly": 26,
	20	+ "weekly": 52,
	21	+ "accelerated-weekly": 52,
	22	+}
	23	+
	24	+# Taux de qualification minimal (test de résistance B-20 / ligne directrice
	25	+# du BSIF) : max(taux contractuel + 2 points, plancher).
	26	+STRESS_TEST_FLOOR = 5.25
	27	+STRESS_TEST_BUFFER = 2.0
	28	+
	29	+AMORTIZATIONS_YEARS = [10, 15, 20, 25, 30]
	30	+TERMS_MONTHS = [12, 24, 36, 48, 60, 84, 120]
	31	+
	32	+
	33	+def periodic_rate(annual_pct: float, frequency: str = "monthly",
	34	+ compounding: str = "semi-annual") -> float:
	35	+ """Taux périodique équivalent au taux nominal annuel `annual_pct` (%).
	36	+
	37	+ compounding="semi-annual" : convention canadienne des prêts fixes —
	38	+ i = (1 + r/2)^(2/f) − 1. "monthly" : prêts variables — i = (1+r/12)^(12/f) − 1.
	39	+ """
	40	+ if annual_pct < 0:
	41	+ raise ValueError("taux négatif")
	42	+ f = FREQUENCIES[frequency]
	43	+ r = annual_pct / 100.0
	44	+ if compounding == "monthly":
	45	+ return (1.0 + r / 12.0) ** (12.0 / f) - 1.0
	46	+ return (1.0 + r / 2.0) ** (2.0 / f) - 1.0
	47	+
	48	+
	49	+def payment(principal: float, annual_pct: float, amort_years: float,
	50	+ frequency: str = "monthly",
	51	+ compounding: str = "semi-annual") -> float:
	52	+ """Versement périodique (arrondi au cent).
	53	+
	54	+ Fréquences accélérées : convention canadienne — le versement mensuel
	55	+ divisé par 2 (aux deux semaines) ou par 4 (hebdomadaire), ce qui raccourcit
	56	+ l'amortissement réel.
	57	+ """
	58	+ if principal <= 0:
	59	+ return 0.0
	60	+ if frequency in ("accelerated-biweekly", "accelerated-weekly"):
	61	+ m = payment(principal, annual_pct, amort_years, "monthly", compounding)
	62	+ return round(m / (2 if frequency == "accelerated-biweekly" else 4), 2)
	63	+ i = periodic_rate(annual_pct, frequency, compounding)
	64	+ n = round(amort_years * FREQUENCIES[frequency])
	65	+ if i == 0:
	66	+ return round(principal / n, 2)
	67	+ return round(principal * i / (1.0 - (1.0 + i) ** -n), 2)
	68	+
	69	+
	70	+def schedule(principal: float, annual_pct: float, amort_years: float,
	71	+ frequency: str = "monthly", compounding: str = "semi-annual",
	72	+ pay_amount: float \| None = None,
	73	+ max_periods: int \| None = None) -> list[dict]:
	74	+ """Tableau d'amortissement complet : [{n, payment, interest, principal,
	75	+ balance}]. Le dernier versement est ajusté au solde exact. Les fréquences
	76	+ accélérées s'éteignent avant l'amortissement contractuel (comportement
	77	+ attendu). `max_periods` borne la simulation (ex. durée du terme)."""
	78	+ if principal <= 0:
	79	+ return []
	80	+ i = periodic_rate(annual_pct, frequency, compounding)
	81	+ pmt = pay_amount if pay_amount is not None else payment(
	82	+ principal, annual_pct, amort_years, frequency, compounding)
	83	+ if pmt <= 0:
	84	+ return []
	85	+ hard_cap = round(amort_years * FREQUENCIES[frequency]) + FREQUENCIES[frequency]
	86	+ if frequency.startswith("accelerated"):
	87	+ hard_cap = round(40 * FREQUENCIES[frequency]) # s'éteint plus tôt
	88	+ limit = min(max_periods, hard_cap) if max_periods else hard_cap
	89	+ rows: list[dict] = []
	90	+ bal = round(principal, 2)
	91	+ n = 0
	92	+ while bal > 0.005 and n < limit:
	93	+ n += 1
	94	+ interest = round(bal * i, 2)
	95	+ cap = round(pmt - interest, 2)
	96	+ if cap <= 0 and n > 1:
	97	+ break # paiement insuffisant : ne jamais boucler à l'infini
	98	+ if cap >= bal: # dernier versement ajusté
	99	+ cap = bal
	100	+ row_pay = round(cap + interest, 2)
	101	+ else:
	102	+ row_pay = pmt
	103	+ bal = round(bal - cap, 2)
	104	+ rows.append({"n": n, "payment": row_pay, "interest": interest,
	105	+ "principal": cap, "balance": bal})
	106	+ return rows
	107	+
	108	+
	109	+def annual_rollup(rows: list[dict], frequency: str = "monthly") -> list[dict]:
	110	+ """Agrège un tableau d'amortissement par année de prêt."""
	111	+ f = FREQUENCIES[frequency]
	112	+ out: list[dict] = []
	113	+ for r in rows:
	114	+ year = (r["n"] - 1) // f + 1
	115	+ if not out or out[-1]["year"] != year:
	116	+ out.append({"year": year, "payment": 0.0, "interest": 0.0,
	117	+ "principal": 0.0, "balance": r["balance"]})
	118	+ acc = out[-1]
	119	+ acc["payment"] = round(acc["payment"] + r["payment"], 2)
	120	+ acc["interest"] = round(acc["interest"] + r["interest"], 2)
	121	+ acc["principal"] = round(acc["principal"] + r["principal"], 2)
	122	+ acc["balance"] = r["balance"]
	123	+ return out
	124	+
	125	+
	126	+def term_summary(principal: float, annual_pct: float, amort_years: float,
	127	+ term_months: int, frequency: str = "monthly",
	128	+ compounding: str = "semi-annual") -> dict:
	129	+ """Bilan du terme : versement, nombre de versements, capital payé,
	130	+ intérêts payés, solde à l'échéance du terme."""
	131	+ f = FREQUENCIES[frequency]
	132	+ n_term = round(f * term_months / 12)
	133	+ rows = schedule(principal, annual_pct, amort_years, frequency,
	134	+ compounding, max_periods=n_term)
	135	+ pmt = payment(principal, annual_pct, amort_years, frequency, compounding)
	136	+ interest = round(sum(r["interest"] for r in rows), 2)
	137	+ cap = round(sum(r["principal"] for r in rows), 2)
	138	+ balance = rows[-1]["balance"] if rows else round(principal, 2)
	139	+ payments_per_year = f
	140	+ return {
	141	+ "payment": pmt,
	142	+ "frequency": frequency,
	143	+ "payments_per_year": payments_per_year,
	144	+ "payments_in_term": len(rows),
	145	+ "annual_cost": round(pmt * payments_per_year, 2),
	146	+ "principal_paid": cap,
	147	+ "interest_paid": interest,
	148	+ "balance_end_of_term": balance,
	149	+ "paid_off": balance <= 0.005,
	150	+ }
	151	+
	152	+
	153	+def payoff_years(principal: float, annual_pct: float, amort_years: float,
	154	+ frequency: str, compounding: str = "semi-annual") -> float:
	155	+ """Durée réelle d'extinction (années) — utile pour les fréquences
	156	+ accélérées qui raccourcissent l'amortissement."""
	157	+ rows = schedule(principal, annual_pct, amort_years, frequency, compounding)
	158	+ if not rows or rows[-1]["balance"] > 0.005:
	159	+ return float(amort_years)
	160	+ return round(len(rows) / FREQUENCIES[frequency], 2)
	161	+
	162	+
	163	+def max_loan(target_payment: float, annual_pct: float, amort_years: float,
	164	+ frequency: str = "monthly",
	165	+ compounding: str = "semi-annual") -> float:
	166	+ """Prêt maximal finançable avec un versement donné (calcul inverse)."""
	167	+ if target_payment <= 0:
	168	+ return 0.0
	169	+ if frequency in ("accelerated-biweekly", "accelerated-weekly"):
	170	+ # équivalent : versement mensuel = paiement × 2 ou × 4
	171	+ mult = 2 if frequency == "accelerated-biweekly" else 4
	172	+ return max_loan(target_payment * mult, annual_pct, amort_years,
	173	+ "monthly", compounding)
	174	+ i = periodic_rate(annual_pct, frequency, compounding)
	175	+ n = round(amort_years * FREQUENCIES[frequency])
	176	+ if i == 0:
	177	+ return round(target_payment * n, 2)
	178	+ return round(target_payment * (1.0 - (1.0 + i) ** -n) / i, 2)
	179	+
	180	+
	181	+def required_rate(principal: float, target_payment: float, amort_years: float,
	182	+ frequency: str = "monthly",
	183	+ compounding: str = "semi-annual") -> float \| None:
	184	+ """Taux annuel (%) tel que le versement du prêt = `target_payment`.
	185	+ Bisection sur [0, 25]. None si même 0 % ne suffit pas."""
	186	+ if principal <= 0 or target_payment <= 0:
	187	+ return None
	188	+ if payment(principal, 0.0, amort_years, frequency, compounding) > target_payment:
	189	+ return None
	190	+ lo, hi = 0.0, 25.0
	191	+ if payment(principal, hi, amort_years, frequency, compounding) < target_payment:
	192	+ return hi
	193	+ for _ in range(60):
	194	+ mid = (lo + hi) / 2
	195	+ if payment(principal, mid, amort_years, frequency, compounding) > target_payment:
	196	+ hi = mid
	197	+ else:
	198	+ lo = mid
	199	+ return round(lo, 2)
	200	+
	201	+
	202	+def qualifying_rate(contract_pct: float) -> float:
	203	+ """Taux de qualification du test de résistance canadien."""
	204	+ return round(max(contract_pct + STRESS_TEST_BUFFER, STRESS_TEST_FLOOR), 2)
	205	+
	206	+
	207	+def stress_scenarios(principal: float, annual_pct: float, amort_years: float,
	208	+ frequency: str = "monthly",
	209	+ compounding: str = "semi-annual",
	210	+ bumps: tuple = (0.0, 1.0, 2.0, 3.0)) -> list[dict]:
	211	+ """« Et si les taux montent ? » — versement à +0/+1/+2/+3 points."""
	212	+ return [{
	213	+ "bump": b,
	214	+ "rate": round(annual_pct + b, 2),
	215	+ "payment": payment(principal, annual_pct + b, amort_years,
	216	+ frequency, compounding),
	217	+ } for b in bumps]
	218	+
	219	+
	220	+def renewal_scenarios(principal: float, annual_pct: float, amort_years: float,
	221	+ term_months: int, frequency: str = "monthly",
	222	+ compounding: str = "semi-annual",
	223	+ bumps: tuple = (-1.0, 0.0, 1.0, 2.0)) -> dict:
	224	+ """Scénario de renouvellement : solde restant à la fin du terme, puis
	225	+ versement recalculé sur l'amortissement résiduel à divers taux."""
	226	+ summary = term_summary(principal, annual_pct, amort_years, term_months,
	227	+ frequency, compounding)
	228	+ balance = summary["balance_end_of_term"]
	229	+ remaining_years = max(amort_years - term_months / 12.0, 1.0)
	230	+ rows = []
	231	+ for b in bumps:
	232	+ r = round(annual_pct + b, 2)
	233	+ if r <= 0 or balance <= 0:
	234	+ continue
	235	+ rows.append({"bump": b, "rate": r,
	236	+ "payment": payment(balance, r, remaining_years,
	237	+ frequency, compounding)})
	238	+ return {"balance_at_renewal": balance,
	239	+ "remaining_amortization_years": round(remaining_years, 1),
	240	+ "scenarios": rows}
	241	+
	242	+
	243	+def gds_tds(gross_annual_income: float, mortgage_payment_monthly: float,
	244	+ property_tax_monthly: float = 0.0, heating_monthly: float = 0.0,
	245	+ condo_fees_monthly: float = 0.0,
	246	+ other_debts_monthly: float = 0.0) -> dict:
	247	+ """Ratios ABD/ATD (GDS/TDS). Convention : 50 % des frais de copropriété.
	248	+ Seuils usuels assurés SCHL : ABD ≤ 39 %, ATD ≤ 44 %. Informatif seulement."""
	249	+ if gross_annual_income <= 0:
	250	+ return {"gds": None, "tds": None, "gds_ok": None, "tds_ok": None}
	251	+ monthly_income = gross_annual_income / 12.0
	252	+ housing = (mortgage_payment_monthly + property_tax_monthly +
	253	+ heating_monthly + 0.5 * condo_fees_monthly)
	254	+ gds = round(100.0 * housing / monthly_income, 1)
	255	+ tds = round(100.0 * (housing + other_debts_monthly) / monthly_income, 1)
	256	+ return {"gds": gds, "tds": tds, "gds_ok": gds <= 39.0, "tds_ok": tds <= 44.0,
	257	+ "gds_limit": 39.0, "tds_limit": 44.0}

added immoka/mortgage/cmhc.py +123 −0

		`@@ -0,0 +1,123 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/cmhc.py : assurance prêt hypothécaire (SCHL / Sagen / Canada
	5	+# Guaranty). Règles et barèmes isolés ici pour être mis à jour facilement.
	6	+# Barème standard en vigueur (2026) — primes en % du prêt selon le
	7	+# rapport prêt-valeur (RPV).
	8	+# -----------------------------------------------------------------------------
	9	+from __future__ import annotations
	10	+
	11	+# (RPV maximal, prime en % du prêt)
	12	+PREMIUM_TABLE: list[tuple[float, float]] = [
	13	+ (0.65, 0.0060),
	14	+ (0.75, 0.0170),
	15	+ (0.80, 0.0240),
	16	+ (0.85, 0.0280),
	17	+ (0.90, 0.0310),
	18	+ (0.95, 0.0400),
	19	+]
	20	+
	21	+# Surprime pour amortissement assuré de 30 ans (premier acheteur / neuf,
	22	+# admissible depuis déc. 2024).
	23	+SURCHARGE_30Y = 0.0020
	24	+
	25	+# Prix maximal admissible à l'assurance (porté de 1 M$ à 1,5 M$ en déc. 2024).
	26	+MAX_INSURABLE_PRICE = 1_500_000
	27	+
	28	+# Amortissement maximal assuré (30 ans seulement premier acheteur / neuf).
	29	+MAX_INSURED_AMORTIZATION = 25
	30	+MAX_INSURED_AMORTIZATION_FTHB = 30
	31	+
	32	+# Taxe de vente du Québec sur la prime (payable comptant à la clôture,
	33	+# jamais ajoutée au prêt).
	34	+QC_TAX_ON_PREMIUM = 0.09975
	35	+
	36	+
	37	+def min_down_payment(price: float) -> float:
	38	+ """Mise de fonds minimale légale au Canada.
	39	+ 5 % de la première tranche de 500 000 $, 10 % de l'excédent jusqu'à
	40	+ 1,5 M$ ; 20 % à compter de 1,5 M$."""
	41	+ if price <= 0:
	42	+ return 0.0
	43	+ if price >= MAX_INSURABLE_PRICE:
	44	+ return round(0.20 * price, 2)
	45	+ return round(0.05 * min(price, 500_000) + 0.10 * max(0.0, price - 500_000), 2)
	46	+
	47	+
	48	+def premium_rate(ltv: float, amort_years: int = 25) -> float \| None:
	49	+ """Taux de prime selon le RPV. None si RPV > 95 % (non assurable)."""
	50	+ if ltv <= 0:
	51	+ return 0.0
	52	+ for cap, rate in PREMIUM_TABLE:
	53	+ if ltv <= cap + 1e-9:
	54	+ extra = SURCHARGE_30Y if amort_years > 25 else 0.0
	55	+ return rate + extra
	56	+ return None
	57	+
	58	+
	59	+def insurance_quote(price: float, down_payment: float,
	60	+ amort_years: int = 25) -> dict:
	61	+ """Décomposition complète de l'assurance prêt hypothécaire.
	62	+
	63	+ Retourne : required (bool), eligible (bool), premium, premium_rate,
	64	+ loan_before, total_mortgage, qc_tax (payable comptant), ltv, issues[].
	65	+ Ne devine rien : si le scénario est inadmissible, le dit explicitement.
	66	+ """
	67	+ issues: list[str] = []
	68	+ if price <= 0 or down_payment < 0 or down_payment >= price:
	69	+ return {"required": False, "eligible": False, "premium": 0.0,
	70	+ "premium_rate": 0.0, "loan_before": max(price - down_payment, 0.0),
	71	+ "total_mortgage": max(price - down_payment, 0.0),
	72	+ "qc_tax": 0.0, "ltv": None, "issues": ["paramètres invalides"]}
	73	+ loan = round(price - down_payment, 2)
	74	+ ltv = loan / price
	75	+ required = ltv > 0.80 + 1e-9
	76	+ if not required:
	77	+ return {"required": False, "eligible": True, "premium": 0.0,
	78	+ "premium_rate": 0.0, "loan_before": loan,
	79	+ "total_mortgage": loan, "qc_tax": 0.0,
	80	+ "ltv": round(ltv * 100, 2), "issues": issues}
	81	+ # Prêt assuré : vérifier l'admissibilité.
	82	+ eligible = True
	83	+ if price >= MAX_INSURABLE_PRICE:
	84	+ eligible = False
	85	+ issues.append("prix ≥ 1,5 M$ : assurance non disponible — mise de "
	86	+ "fonds de 20 % requise")
	87	+ if down_payment < min_down_payment(price) - 0.01:
	88	+ eligible = False
	89	+ issues.append("mise de fonds sous le minimum légal "
	90	+ f"({min_down_payment(price):,.0f} $)".replace(",", " "))
	91	+ if amort_years > MAX_INSURED_AMORTIZATION_FTHB:
	92	+ eligible = False
	93	+ issues.append("amortissement > 30 ans impossible pour un prêt assuré")
	94	+ elif amort_years > MAX_INSURED_AMORTIZATION:
	95	+ issues.append("30 ans assuré : réservé premier acheteur ou "
	96	+ "construction neuve (surprime de 0,20 %)")
	97	+ rate = premium_rate(ltv, amort_years) if eligible else None
	98	+ if rate is None and eligible:
	99	+ eligible = False
	100	+ issues.append("rapport prêt-valeur > 95 % : non assurable")
	101	+ premium = round(loan * rate, 2) if (eligible and rate) else 0.0
	102	+ return {
	103	+ "required": True,
	104	+ "eligible": eligible,
	105	+ "premium": premium,
	106	+ "premium_rate": round((rate or 0.0) * 100, 2),
	107	+ "loan_before": loan,
	108	+ "total_mortgage": round(loan + premium, 2),
	109	+ "qc_tax": round(premium * QC_TAX_ON_PREMIUM, 2),
	110	+ "ltv": round(ltv * 100, 2),
	111	+ "issues": issues,
	112	+ }
	113	+
	114	+
	115	+def allowed_amortizations(price: float, down_payment: float) -> list[int]:
	116	+ """Amortissements permis pour un scénario donné (25 ans max si assuré,
	117	+ 30 ans si mise de fonds ≥ 20 % — ou premier acheteur/neuf assuré)."""
	118	+ if price <= 0:
	119	+ return [10, 15, 20, 25, 30]
	120	+ ltv = (price - down_payment) / price
	121	+ if ltv > 0.80:
	122	+ return [10, 15, 20, 25, 30] # 30 = cas particulier (signalé par issues)
	123	+ return [10, 15, 20, 25, 30]

added immoka/mortgage/providers/README.md +85 −0

		`@@ -0,0 +1,85 @@`
	1	+# Providers de taux hypothécaires
	2	+
	3	+Un connecteur indépendant par institution. Auto-découverte : tout module du
	4	+dossier définissant une sous-classe de `RateProvider` avec un `provider_id`
	5	+non vide est enregistré dans `PROVIDERS` automatiquement (aucun registre à
	6	+éditer). La panne d'un provider n'affecte jamais les autres.
	7	+
	8	+Règle absolue : aucun taux inventé. Un produit non confirmé sur la page
	9	+officielle est simplement omis — jamais deviné, jamais de valeur par défaut.
	10	+
	11	+## Ajouter une institution (8 étapes)
	12	+
	13	+1. Créer `<slug>.py` dans ce dossier, avec une sous-classe de
	14	+ `RateProvider` :
	15	+
	16	+ ```python
	17	+ from .base import RateProvider
	18	+
	19	+ class MaBanque(RateProvider):
	20	+ provider_id = "ma_banque" # slug stable (clé BD)
	21	+ institution = "Ma Banque" # nom d'affichage fr-CA
	22	+ source_url = "https://mabanque.ca/taux-hypothecaires"
	23	+
	24	+ def fetch(self) -> list[dict]:
	25	+ html = self.get(self.source_url).text # ou .json()
	26	+ return self.parse(html)
	27	+
	28	+ def parse(self, html: str) -> list[dict]:
	29	+ ... # → [self.make_product(...), ...]
	30	+ ```
	31	+
	32	+ Séparer `fetch()` (réseau) de `parse()` (pur) : les tests appellent
	33	+ `parse()` sur des fixtures, sans réseau.
	34	+
	35	+2. Backend réseau : `self.get(url)` (requests + politesse `request_delay`)
	36	+ d'abord ; `self.get_scrapfly(url, render_js=True)` **en dernier recours
	37	+ seulement** si le site bloque (403/JS requis).
	38	+
	39	+3. Normaliser chaque produit via `self.make_product(...)` :
	40	+ - `rate_type` : `fixed` / `variable` — ou **`other` pour tout taux
	41	+ préférentiel/prime/référence** (avec `purpose="unknown"`), afin qu'il ne
	42	+ tombe jamais dans un classement « meilleur taux d'achat » ;
	43	+ - `kind` : `posted` (affiché) ou `special` (offre spéciale) — ne jamais
	44	+ confondre ;
	45	+ - `insured_status` : `insured` / `insurable` / `uninsured`, ou `unknown`
	46	+ si la page ne le précise pas — ne pas deviner ;
	47	+ - `product_name` en français, explicite (ex. « Fixe fermé 5 ans ») ;
	48	+ - `apr` (TAP) seulement s'il est publié.
	49	+
	50	+4. Aucune écriture BD dans le provider : le scheduler valide
	51	+ (`validate_batch`) puis enregistre (`store.record_observations`). Ne pas
	52	+ filtrer soi-même les aberrations — la validation s'en charge et journalise.
	53	+
	54	+5. Fixture : sauvegarder la réponse réelle (HTML/JSON) dans
	55	+ `tests/fixtures/mortgage/<slug>.<ext>` (anonymisée si besoin, taille
	56	+ raisonnable — garder le bloc utile).
	57	+
	58	+6. Test : ajouter le slug dans `EXPECTED` de
	59	+ `tests/test_mortgage_providers.py` (fixture + nombre exact de produits) ;
	60	+ le test générique vérifie déjà validation propre, `source_url`,
	61	+ `institution` et la règle « préférentiel → other/unknown ». Ajouter un
	62	+ test ciblé sur 1–2 valeurs connues de la fixture.
	63	+
	64	+7. Exécuter :
	65	+
	66	+ ```bash
	67	+ PYTHONPATH=. .venv/bin/python -P -m unittest tests.test_mortgage_providers
	68	+ .venv/bin/python run.py mortgage-sync ma_banque # collecte réelle
	69	+ .venv/bin/python run.py mortgage-status # santé
	70	+ ```
	71	+
	72	+8. Vérifier en BD/API : `GET /api/mortgage/rates?provider=ma_banque` —
	73	+ provenance (`source_url`), fraîcheur et nature correctes. C'est tout :
	74	+ ni web.py, ni le scheduler, ni le frontend n'ont besoin d'être modifiés.
	75	+
	76	+## Pièges connus
	77	+
	78	+- `4.19 % → 419` : toujours vérifier l'échelle ; la validation rejette
	79	+ > 24 %, mais un « 41,9 » passerait — parser au bon endroit.
	80	+- Pages avec plusieurs onglets (assuré/non assuré) : étiqueter
	81	+ `insured_status` correctement plutôt que de tout mélanger.
	82	+- Taux « ouverts » vs « fermés » : les distinguer dans `product_name`
	83	+ (ex. BNC publie « Fixe ouvert 1 an » à 9,65 % — ce n'est pas une erreur).
	84	+- Ne jamais soumettre de formulaire ni simuler une demande de prêt : pages
	85	+ publiques de taux uniquement.

added immoka/mortgage/providers/__init__.py +25 −0

		`@@ -0,0 +1,25 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/providers/ : un connecteur indépendant par institution financière.
	5	+# Auto-découverte : tout module du dossier définissant une sous-classe de
	6	+# RateProvider avec provider_id non vide est enregistré automatiquement
	7	+# (même mécanique que immoka/connectors/).
	8	+# -----------------------------------------------------------------------------
	9	+from __future__ import annotations
	10	+
	11	+import importlib
	12	+import pkgutil
	13	+
	14	+from .base import RateProvider
	15	+
	16	+PROVIDERS: dict[str, type[RateProvider]] = {}
	17	+
	18	+for _mod in pkgutil.iter_modules(__path__):
	19	+ if _mod.name.startswith("_") or _mod.name == "base":
	20	+ continue
	21	+ module = importlib.import_module(f".{_mod.name}", __name__)
	22	+ for obj in vars(module).values():
	23	+ if (isinstance(obj, type) and issubclass(obj, RateProvider)
	24	+ and obj is not RateProvider and obj.provider_id):
	25	+ PROVIDERS[obj.provider_id] = obj

added immoka/mortgage/providers/bank_of_canada.py +77 −0

		`@@ -0,0 +1,77 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/providers/bank_of_canada.py : Banque du Canada — API Valet
	5	+# (officielle, publique, JSON). Séries de référence : taux hypothécaire
	6	+# conventionnel affiché 1/3/5 ans, taux directeur, rendement obligataire
	7	+# 5 ans. purpose="unknown" : séries de RÉFÉRENCE, exclues du comparateur
	8	+# de prêteurs (la BdC ne prête pas aux particuliers).
	9	+# -----------------------------------------------------------------------------
	10	+from __future__ import annotations
	11	+
	12	+from .base import RateProvider
	13	+
	14	+SERIES_URL = ("https://www.bankofcanada.ca/valet/observations/"
	15	+ "V80691333,V80691334,V80691335,V39079,BD.CDN.5YR.DQ.YLD/"
	16	+ "json?recent=10")
	17	+
	18	+# série -> (terme mois, nom de produit)
	19	+MORTGAGE_SERIES = {
	20	+ "V80691333": (12, "Taux hypothécaire conventionnel affiché — 1 an"),
	21	+ "V80691334": (36, "Taux hypothécaire conventionnel affiché — 3 ans"),
	22	+ "V80691335": (60, "Taux hypothécaire conventionnel affiché — 5 ans"),
	23	+}
	24	+CONTEXT_SERIES = {
	25	+ "V39079": "Taux cible du financement à un jour",
	26	+ "BD.CDN.5YR.DQ.YLD": "Rendement obligataire 5 ans — Gouvernement du Canada",
	27	+}
	28	+
	29	+
	30	+class BankOfCanadaProvider(RateProvider):
	31	+ provider_id = "bank_of_canada"
	32	+ institution = "Banque du Canada"
	33	+ source_url = "https://www.bankofcanada.ca/rates/interest-rates/"
	34	+ request_delay = 0.5
	35	+
	36	+ def fetch(self) -> list[dict]:
	37	+ return self.parse(self.get(SERIES_URL).text)
	38	+
	39	+ def parse(self, payload: str) -> list[dict]:
	40	+ import json
	41	+ data = json.loads(payload)
	42	+ observations = data.get("observations") or []
	43	+ # Séries à fréquences mélangées : garder la DERNIÈRE valeur par série.
	44	+ latest: dict[str, tuple[str, float]] = {}
	45	+ for obs in observations:
	46	+ d = obs.get("d", "")
	47	+ for sid, cell in obs.items():
	48	+ if sid == "d" or not isinstance(cell, dict):
	49	+ continue
	50	+ v = cell.get("v")
	51	+ if v in (None, ""):
	52	+ continue
	53	+ try:
	54	+ latest[sid] = (d, float(v))
	55	+ except ValueError:
	56	+ continue
	57	+ out: list[dict] = []
	58	+ for sid, (term, name) in MORTGAGE_SERIES.items():
	59	+ if sid not in latest:
	60	+ continue
	61	+ d, v = latest[sid]
	62	+ out.append(self.make_product(
	63	+ rate=v, rate_type="fixed", term_months=term, kind="posted",
	64	+ product_name=name, purpose="unknown",
	65	+ conditions=f"Série Valet {sid} — observation du {d} "
	66	+ "(moyenne hebdomadaire des taux affichés)",
	67	+ raw={"series": sid, "date": d, "value": v}))
	68	+ for sid, name in CONTEXT_SERIES.items():
	69	+ if sid not in latest:
	70	+ continue
	71	+ d, v = latest[sid]
	72	+ out.append(self.make_product(
	73	+ rate=v, rate_type="other", term_months=12, kind="posted",
	74	+ product_name=name, purpose="unknown",
	75	+ conditions=f"Série Valet {sid} — observation du {d}",
	76	+ raw={"series": sid, "date": d, "value": v}))
	77	+ return out

added immoka/mortgage/providers/base.py +133 −0

		`@@ -0,0 +1,133 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/providers/base.py : classe de base des connecteurs de taux.
	5	+# Contrat : fetch() retourne la liste des produits NORMALISÉS de
	6	+# l'institution (dicts au format de make_product). Aucune écriture BD ici —
	7	+# le scheduler valide puis enregistre. Jamais de taux inventé : un produit
	8	+# non confirmé est simplement omis.
	9	+# -----------------------------------------------------------------------------
	10	+from __future__ import annotations
	11	+
	12	+import os
	13	+import re
	14	+import time
	15	+
	16	+import requests
	17	+
	18	+USER_AGENT = ("Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) "
	19	+ "AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126 Safari/537.36 "
	20	+ "ImmoKaBot/1.0 (+https://www.immo-ka.com/bot; contact@spboucher.ai)")
	21	+
	22	+SCRAPFLY_API = "https://api.scrapfly.io/scrape"
	23	+
	24	+
	25	+class RateProvider:
	26	+ provider_id: str = "" # slug (rbc, td, desjardins…)
	27	+ institution: str = "" # nom d'affichage
	28	+ source_url: str = "" # page officielle des taux (lien public)
	29	+ request_delay: float = 1.0 # politesse
	30	+ timeout: int = 30
	31	+
	32	+ def __init__(self) -> None:
	33	+ self.session = requests.Session()
	34	+ self.session.headers["User-Agent"] = USER_AGENT
	35	+ self._last_request = 0.0
	36	+
	37	+ # -- backends -------------------------------------------------------------
	38	+ def get(self, url: str, **kw) -> requests.Response:
	39	+ wait = self.request_delay - (time.time() - self._last_request)
	40	+ if wait > 0:
	41	+ time.sleep(wait)
	42	+ resp = self.session.get(url, timeout=self.timeout, **kw)
	43	+ self._last_request = time.time()
	44	+ resp.raise_for_status()
	45	+ return resp
	46	+
	47	+ def get_scrapfly(self, url: str, render_js: bool = False,
	48	+ asp: bool = True, country: str = "ca") -> str:
	49	+ """HTML via Scrapfly (anti-bot) — dernier recours seulement."""
	50	+ key = os.environ.get("SCRAPFLY_KEY") or os.environ.get("SCRAPFLY_API_KEY")
	51	+ if not key:
	52	+ raise RuntimeError("SCRAPFLY_KEY manquant (voir .env)")
	53	+ params: dict = {"key": key, "url": url, "country": country}
	54	+ if asp:
	55	+ params["asp"] = "true"
	56	+ if render_js:
	57	+ params["render_js"] = "true"
	58	+ wait = self.request_delay - (time.time() - self._last_request)
	59	+ if wait > 0:
	60	+ time.sleep(wait)
	61	+ resp = requests.get(SCRAPFLY_API, params=params, timeout=180)
	62	+ self._last_request = time.time()
	63	+ try:
	64	+ return (resp.json().get("result") or {}).get("content") or ""
	65	+ except ValueError:
	66	+ return ""
	67	+
	68	+ # -- normalisation --------------------------------------------------------
	69	+ def make_product(self, *, rate: float, rate_type: str, term_months: int,
	70	+ kind: str, product_name: str \| None = None,
	71	+ apr: float \| None = None,
	72	+ insured_status: str = "unknown",
	73	+ purpose: str = "purchase",
	74	+ amortization_max_years: int \| None = None,
	75	+ conditions: str \| None = None,
	76	+ source_url: str \| None = None,
	77	+ confidence: float = 1.0,
	78	+ raw=None) -> dict:
	79	+ """Observation normalisée commune à tous les providers."""
	80	+ return {
	81	+ "provider": self.provider_id,
	82	+ "institution": self.institution,
	83	+ "product_name": product_name,
	84	+ "rate_type": rate_type,
	85	+ "term_months": int(term_months),
	86	+ "kind": kind,
	87	+ "rate": round(float(rate), 4),
	88	+ "apr": round(float(apr), 4) if apr is not None else None,
	89	+ "insured_status": insured_status,
	90	+ "purpose": purpose,
	91	+ "amortization_max_years": amortization_max_years,
	92	+ "conditions": conditions,
	93	+ "source_url": source_url or self.source_url,
	94	+ "confidence": confidence,
	95	+ "raw": raw,
	96	+ }
	97	+
	98	+ # -- contrat --------------------------------------------------------------
	99	+ def fetch(self) -> list[dict]:
	100	+ raise NotImplementedError
	101	+
	102	+ # Point d'entrée pour les tests avec fixtures : si le provider parse un
	103	+ # payload texte, il expose parse(payload) et fetch() = parse(download()).
	104	+ def parse(self, payload: str) -> list[dict]: # pragma: no cover
	105	+ raise NotImplementedError
	106	+
	107	+
	108	+def parse_rate(text: str) -> float \| None:
	109	+ """Extrait un taux en % d'un texte : '4,19 %', '4.19%', ' 4.19 '.
	110	+ Retourne None si introuvable — jamais de valeur devinée."""
	111	+ if text is None:
	112	+ return None
	113	+ m = re.search(r"(\d{1,2}(?:[.,]\d{1,4})?)\s*%?", str(text).strip())
	114	+ if not m:
	115	+ return None
	116	+ try:
	117	+ return float(m.group(1).replace(",", "."))
	118	+ except ValueError:
	119	+ return None
	120	+
	121	+
	122	+def term_to_months(text: str) -> int \| None:
	123	+ """'5 ans', '5 year', '5-year', '6 months', '6 mois' → mois."""
	124	+ if not text:
	125	+ return None
	126	+ t = str(text).lower()
	127	+ m = re.search(r"(\d{1,3})\s(?:-\|\s)?\s(an\|ans\|année\|year\|yr)", t)
	128	+ if m:
	129	+ return int(m.group(1)) * 12
	130	+ m = re.search(r"(\d{1,3})\s(?:-\|\s)?\s(mois\|month)", t)
	131	+ if m:
	132	+ return int(m.group(1))
	133	+ return None

added immoka/mortgage/providers/bmo.py +135 −0

		`@@ -0,0 +1,135 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/providers/bmo.py : BMO — 3 JSON publics public-data (spéciaux,
	5	+# grille affichée EPM, prime). ⚠️ bmo.com filtre l'empreinte TLS (Akamai) :
	6	+# cascade requests → curl_cffi (si dispo) → Scrapfly asp. Les clés Over25
	7	+# sont les variantes amortissement > 25 ans ; 18YearOpen et 12Variable*
	8	+# sont des reliquats hérités (valeurs figées) et sont ignorés.
	9	+# -----------------------------------------------------------------------------
	10	+from __future__ import annotations
	11	+
	12	+import json
	13	+
	14	+from .base import RateProvider
	15	+
	16	+URLS = {
	17	+ "ca-mortgages-special-rates":
	18	+ "https://www.bmo.com/public-data/api/v2.0/bmo-ca-mortgages-rates.json",
	19	+ "epm-mortgage":
	20	+ "https://www.bmo.com/public-data/api/epm/v1.0/bmo-epm-mortgage.json",
	21	+ "epm-prime":
	22	+ "https://www.bmo.com/public-data/api/epm/v1.0/bmo-epm-prime.json",
	23	+}
	24	+PAGE_URL = "https://www.bmo.com/en-ca/main/personal/mortgages/mortgage-rates/"
	25	+
	26	+# clé spéciale -> (rate_type, terme mois, nom, clé APR, amort max, insured)
	27	+SPECIAL_MAP: dict[str, tuple] = {
	28	+ "fixed3YearClosedSpecial":
	29	+ ("fixed", 36, "Fixe fermé 3 ans (offre spéciale)",
	30	+ "fixed3YearClosedSpecialApr", 25, "unknown"),
	31	+ "fixed3YearClosedSpecialOver25":
	32	+ ("fixed", 36, "Fixe fermé 3 ans (offre spéciale, amort. >25 ans)",
	33	+ "fixed3YearClosedSpecialOver25Apr", 30, "uninsured"),
	34	+ "smartFixed5YearClosedSpecial":
	35	+ ("fixed", 60, "Smart Fixed fermé 5 ans (offre spéciale)",
	36	+ "smartFixed5YearClosedSpecialApr", 25, "uninsured"),
	37	+ "smartFixed5YearClosedHighRatioSpecial":
	38	+ ("fixed", 60, "Smart Fixed fermé 5 ans (offre spéciale, ratio élevé)",
	39	+ "smartFixed5YearClosedHighRatioSpecialApr", 25, "insured"),
	40	+ "variable5YearClosedSpecial":
	41	+ ("variable", 60, "Variable fermé 5 ans (offre spéciale)",
	42	+ "variable5YearClosedSpecialApr", 25, "unknown"),
	43	+ "variable5YearClosedSpecialOver25":
	44	+ ("variable", 60, "Variable fermé 5 ans (offre spéciale, amort. >25 ans)",
	45	+ "variable5YearClosedSpecialOver25Apr", 30, "uninsured"),
	46	+}
	47	+
	48	+EPM_SKIP = {"18YearOpen", "12VariableLimited", "12VariableOpen"}
	49	+
	50	+
	51	+def _num(v) -> float \| None:
	52	+ try:
	53	+ return float(str(v).strip())
	54	+ except (TypeError, ValueError):
	55	+ return None
	56	+
	57	+
	58	+class BmoProvider(RateProvider):
	59	+ provider_id = "bmo"
	60	+ institution = "BMO Banque de Montréal"
	61	+ source_url = PAGE_URL
	62	+ request_delay = 1.2
	63	+
	64	+ def _get_json_text(self, url: str) -> str:
	65	+ try:
	66	+ return self.get(url).text
	67	+ except Exception: # noqa: BLE001 — TLS Akamai : on escalade
	68	+ pass
	69	+ try:
	70	+ from curl_cffi import requests as curl_requests
	71	+ resp = curl_requests.get(url, impersonate="chrome",
	72	+ timeout=self.timeout)
	73	+ resp.raise_for_status()
	74	+ return resp.text
	75	+ except ImportError:
	76	+ pass
	77	+ return self.get_scrapfly(url, render_js=False, asp=True)
	78	+
	79	+ def fetch(self) -> list[dict]:
	80	+ docs: dict[str, dict] = {}
	81	+ for key, url in URLS.items():
	82	+ text = self._get_json_text(url)
	83	+ docs[key] = json.loads(text)
	84	+ return self.parse_docs(docs)
	85	+
	86	+ def parse(self, payload: str) -> list[dict]:
	87	+ """Pour les tests fixtures : payload = JSON {clé: {url, payload}}."""
	88	+ data = json.loads(payload)
	89	+ docs: dict[str, dict] = {}
	90	+ for key, entry in data.items():
	91	+ doc = entry.get("payload") if isinstance(entry, dict) and \
	92	+ "payload" in entry else entry
	93	+ if isinstance(doc, str):
	94	+ doc = json.loads(doc)
	95	+ docs[key] = doc
	96	+ return self.parse_docs(docs)
	97	+
	98	+ def parse_docs(self, docs: dict[str, dict]) -> list[dict]:
	99	+ out: list[dict] = []
	100	+ specials = docs.get("ca-mortgages-special-rates") or {}
	101	+ for key, (rtype, term, name, apr_key, amort, insured) in \
	102	+ SPECIAL_MAP.items():
	103	+ rate = _num(specials.get(key))
	104	+ if rate is None or rate <= 0:
	105	+ continue
	106	+ out.append(self.make_product(
	107	+ rate=rate, rate_type=rtype, term_months=term, kind="special",
	108	+ product_name=name, apr=_num(specials.get(apr_key)),
	109	+ insured_status=insured, amortization_max_years=amort,
	110	+ raw={"key": key, "value": specials.get(key)}))
	111	+ epm = docs.get("epm-mortgage") or {}
	112	+ grid = epm.get("mortgageRates") or epm
	113	+ for rtype_key, rtype, prefix in (("fixed", "fixed", "Fixe"),
	114	+ ("variable", "variable", "Variable")):
	115	+ for key, cell in (grid.get(rtype_key) or {}).items():
	116	+ if key in EPM_SKIP or not isinstance(cell, dict):
	117	+ continue
	118	+ rate = _num(cell.get("value"))
	119	+ term = _num(cell.get("term_months"))
	120	+ if rate is None or rate <= 0 or not term:
	121	+ continue
	122	+ label = cell.get("fr") or cell.get("en") or key
	123	+ out.append(self.make_product(
	124	+ rate=rate, rate_type=rtype, term_months=int(term),
	125	+ kind="posted", product_name=f"{prefix} {label}",
	126	+ raw={"key": key, "cell": cell}))
	127	+ prime = docs.get("epm-prime") or {}
	128	+ prime_rate = _num((prime.get("caPrimeRate") or {}).get("value"))
	129	+ if prime_rate and prime_rate > 0:
	130	+ out.append(self.make_product(
	131	+ rate=prime_rate, rate_type="other", term_months=12,
	132	+ kind="posted", product_name="Taux préférentiel BMO",
	133	+ purpose="unknown",
	134	+ raw={"caPrimeRate": prime.get("caPrimeRate")}))
	135	+ return out

added immoka/mortgage/providers/cibc.py +144 −0

		`@@ -0,0 +1,144 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/providers/cibc.py : CIBC — pseudo-JSON JS productRatesLegacy
	5	+# (blocs `var CODE = {...}` avec lignes [terme, ?, colId, valeur, …]).
	6	+# colId 1 = affiché, 18 = spécial, 2 = APR du spécial ; sentinelle
	7	+# -99.999999991 et spécial 0.00 = non publié ; colId 34 = colonne
	8	+# d'identité inconnue, jamais devinée. MICRO/MICROVAR ne portent que
	9	+# l'offre spéciale (leur « affiché » duplique FRCM).
	10	+# -----------------------------------------------------------------------------
	11	+from __future__ import annotations
	12	+
	13	+import re
	14	+
	15	+from .base import RateProvider
	16	+
	17	+BASE_URL = ("https://www.cibconline.cibc.com/ebm-pno/api/v1/json/"
	18	+ "productRatesLegacy?lobId={lob}&sourceProductCode={codes}")
	19	+LOB5_CODES = "FRCM,FOM,CCM,5YRVARCLO,MICRO,MICROVAR,VROM"
	20	+PAGE_URL = "https://www.cibc.com/en/interest-rates/mortgage-rates.html"
	21	+
	22	+COL_POSTED, COL_APR, COL_SPECIAL = 1, 2, 18
	23	+SENTINEL = -99.0
	24	+
	25	+# code -> (rate_type, libellé de base, spécial seulement, libellé du spécial)
	26	+PRODUCTS: dict[str, tuple] = {
	27	+ "FRCM": ("fixed", "Fixe fermé", False, "offre spéciale"),
	28	+ "FOM": ("fixed", "Fixe ouvert", False, "offre spéciale"),
	29	+ "CCM": ("fixed", "Fermé convertible", False, "offre spéciale"),
	30	+ "5YRVARCLO": ("variable", "Variable Flex fermé", False, "offre spéciale"),
	31	+ "VROM": ("variable", "Variable ouvert", False, "offre spéciale"),
	32	+ # MICRO/MICROVAR : l'offre mise en avant sur la page des taux — libellé
	33	+ # distinct pour ne pas entrer en collision avec le spécial FRCM/5YRVARCLO.
	34	+ "MICRO": ("fixed", "Fixe fermé", True, "offre annoncée"),
	35	+ "MICROVAR": ("variable", "Variable Flex fermé", True, "offre annoncée"),
	36	+}
	37	+
	38	+BLOCK_RX = re.compile(r"var\s+(\w+)\s=\s\{(.?)\]\s\}", re.S)
	39	+ROW_RX = re.compile(r"\[([^\[\]]*)\]")
	40	+TERM_RX = re.compile(r"^(\d{1,3})_.*_(Year\|Years\|Month\|Months)_T$")
	41	+
	42	+
	43	+def _cells(row: str) -> list:
	44	+ out = []
	45	+ for cell in row.split(","):
	46	+ c = cell.strip().strip("'\"")
	47	+ out.append(None if c == "null" else c)
	48	+ return out
	49	+
	50	+
	51	+def _term_months(token) -> int \| None:
	52	+ m = TERM_RX.match(str(token or ""))
	53	+ if not m:
	54	+ return None
	55	+ n = int(m.group(1))
	56	+ return n * 12 if m.group(2).startswith("Year") else n
	57	+
	58	+
	59	+def _num(v) -> float \| None:
	60	+ try:
	61	+ return float(str(v).strip())
	62	+ except (TypeError, ValueError):
	63	+ return None
	64	+
	65	+
	66	+def _label(months: int) -> str:
	67	+ if months < 12:
	68	+ return f"{months} mois"
	69	+ years = months // 12
	70	+ return f"{years} an" if years == 1 else f"{years} ans"
	71	+
	72	+
	73	+class CibcProvider(RateProvider):
	74	+ provider_id = "cibc"
	75	+ institution = "CIBC"
	76	+ source_url = PAGE_URL
	77	+ request_delay = 1.2
	78	+
	79	+ def fetch(self) -> list[dict]:
	80	+ text = self.get(BASE_URL.format(lob=5, codes=LOB5_CODES)).text
	81	+ try:
	82	+ text += "\n" + self.get(BASE_URL.format(lob=1, codes="PRIME")).text
	83	+ except Exception: # noqa: BLE001 — prime facultatif
	84	+ pass
	85	+ return self.parse(text)
	86	+
	87	+ def parse(self, payload: str) -> list[dict]:
	88	+ out: list[dict] = []
	89	+ for var_name, body in BLOCK_RX.findall(payload):
	90	+ name = var_name[1:] if var_name[:1] == "p" and \
	91	+ var_name[1:2].isdigit() else var_name
	92	+ if name == "PRIME":
	93	+ out.extend(self._parse_prime(body))
	94	+ continue
	95	+ if name not in PRODUCTS:
	96	+ continue
	97	+ rtype, base_label, special_only, special_label = PRODUCTS[name]
	98	+ # (terme -> {colId: valeur})
	99	+ grid: dict[int, dict[int, float]] = {}
	100	+ for row in ROW_RX.findall(body):
	101	+ cells = _cells(row)
	102	+ if len(cells) < 4:
	103	+ continue
	104	+ term = _term_months(cells[0])
	105	+ col = _num(cells[2])
	106	+ val = _num(cells[3])
	107	+ if term is None or col is None or val is None:
	108	+ continue
	109	+ if val < SENTINEL + 1 or val <= 0:
	110	+ continue # sentinelle -99.999999991 ou 0.00 : non publié
	111	+ grid.setdefault(term, {})[int(col)] = val
	112	+ for term, cols in sorted(grid.items()):
	113	+ posted = cols.get(COL_POSTED)
	114	+ special = cols.get(COL_SPECIAL)
	115	+ if posted and not special_only:
	116	+ out.append(self.make_product(
	117	+ rate=posted, rate_type=rtype, term_months=term,
	118	+ kind="posted",
	119	+ product_name=f"{base_label} {_label(term)}",
	120	+ conditions="Base = taux préférentiel CIBC"
	121	+ if rtype == "variable" and name == "5YRVARCLO"
	122	+ else None,
	123	+ raw={"code": name, "cols": cols}))
	124	+ if special:
	125	+ out.append(self.make_product(
	126	+ rate=special, rate_type=rtype, term_months=term,
	127	+ kind="special", apr=cols.get(COL_APR),
	128	+ product_name=f"{base_label} {_label(term)} "
	129	+ f"({special_label})",
	130	+ raw={"code": name, "cols": cols}))
	131	+ return out
	132	+
	133	+ def _parse_prime(self, body: str) -> list[dict]:
	134	+ for row in ROW_RX.findall(body):
	135	+ cells = _cells(row)
	136	+ if len(cells) < 4:
	137	+ continue
	138	+ rate = _num(cells[3])
	139	+ if rate and rate > 0:
	140	+ return [self.make_product(
	141	+ rate=rate, rate_type="other", term_months=12,
	142	+ kind="posted", product_name="Taux préférentiel CIBC",
	143	+ purpose="unknown", raw={"code": "PRIME", "value": rate})]
	144	+ return []

added immoka/mortgage/providers/desjardins.py +83 −0

		`@@ -0,0 +1,83 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/providers/desjardins.py : Desjardins — JSON server-rendered
	5	+# window.dcomProducts sur la page des taux. Clé = cfPath COMPLET (le même
	6	+# id existe dans les familles « taux-hypothecaires » (affichés) et
	7	+# « taux-hypothecaires-promotionnels » (spéciaux) avec des valeurs
	8	+# différentes — ne jamais confondre).
	9	+# -----------------------------------------------------------------------------
	10	+from __future__ import annotations
	11	+
	12	+import json
	13	+import re
	14	+
	15	+from .base import RateProvider
	16	+
	17	+PAGE_URL = "https://www.desjardins.com/fr/hypotheque/taux-hypothecaires.html"
	18	+
	19	+# id Desjardins -> (rate_type, terme mois, nom, purpose)
	20	+ID_MAP: dict[str, tuple] = {
	21	+ "6000_6M": ("fixed", 6, "Fixe fermé 6 mois"),
	22	+ "6000_1A": ("fixed", 12, "Fixe fermé 1 an"),
	23	+ "6000_2A": ("fixed", 24, "Fixe fermé 2 ans"),
	24	+ "6000_3A": ("fixed", 36, "Fixe fermé 3 ans"),
	25	+ "6000_4A": ("fixed", 48, "Fixe fermé 4 ans"),
	26	+ "6000_5A": ("fixed", 60, "Fixe fermé 5 ans"),
	27	+ "6000_6A": ("fixed", 72, "Fixe fermé 6 ans"),
	28	+ "6000_7A": ("fixed", 84, "Fixe fermé 7 ans"),
	29	+ "6000_10A": ("fixed", 120, "Fixe fermé 10 ans"),
	30	+ "6000_6MO": ("fixed", 6, "Fixe ouvert 6 mois"),
	31	+ "6000_1AO": ("fixed", 12, "Fixe ouvert 1 an"),
	32	+ "6004_5AR": ("variable", 60, "Variable réduit 5 ans"),
	33	+ "tvp": ("variable", 60, "Variable protégé 5 ans"),
	34	+ "tvred": ("variable", 60, "Variable réduit"),
	35	+ "tvreg": ("variable", 60, "Variable régulier"),
	36	+ "tra": ("fixed", 12, "Révisable annuellement"),
	37	+}
	38	+PRIME_ID = "tpcad"
	39	+
	40	+
	41	+class DesjardinsProvider(RateProvider):
	42	+ provider_id = "desjardins"
	43	+ institution = "Desjardins"
	44	+ source_url = PAGE_URL
	45	+ request_delay = 1.5
	46	+
	47	+ def fetch(self) -> list[dict]:
	48	+ return self.parse(self.get(self.source_url).text)
	49	+
	50	+ def parse(self, payload: str) -> list[dict]:
	51	+ m = re.search(r"window\.dcomProducts\s=\s(\{.*?\});", payload, re.S)
	52	+ if not m:
	53	+ raise ValueError("dcomProducts introuvable (structure changée)")
	54	+ products = json.loads(m.group(1))
	55	+ out: list[dict] = []
	56	+ for cf_path, cell in products.items():
	57	+ if "/hypotheque/" not in cf_path or not isinstance(cell, dict):
	58	+ continue
	59	+ pid = cell.get("id") or ""
	60	+ try:
	61	+ rate = float(cell.get("rate"))
	62	+ except (TypeError, ValueError):
	63	+ continue
	64	+ if rate <= 0:
	65	+ continue
	66	+ promo = "taux-hypothecaires-promotionnels" in cf_path
	67	+ if pid == PRIME_ID:
	68	+ out.append(self.make_product(
	69	+ rate=rate, rate_type="other", term_months=12,
	70	+ kind="posted", product_name="Taux préférentiel Desjardins",
	71	+ purpose="unknown", raw={"cfPath": cf_path, "rate": rate}))
	72	+ continue
	73	+ if pid not in ID_MAP:
	74	+ continue # id inconnu : jamais deviné
	75	+ rtype, term, label = ID_MAP[pid]
	76	+ out.append(self.make_product(
	77	+ rate=rate, rate_type=rtype, term_months=term,
	78	+ kind="special" if promo else "posted",
	79	+ product_name=label + (" (promotion)" if promo else ""),
	80	+ conditions="Taux promotionnel Desjardins" if promo
	81	+ else "Taux affiché Desjardins",
	82	+ raw={"cfPath": cf_path, "id": pid, "rate": cell.get("rate")}))
	83	+ return out

added immoka/mortgage/providers/eq_bank.py +94 −0

		`@@ -0,0 +1,94 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/providers/eq_bank.py : Banque EQ / Équitable — dictionnaire JSON
	5	+# global embarqué dans le payload Next.js de la page des taux (marqueur
	6	+# \"rates\":{ échappé). Clés CMS stables ; les clés « Adjustable » sont des
	7	+# ÉCARTS vs prime (jamais interprétées comme des taux).
	8	+# -----------------------------------------------------------------------------
	9	+from __future__ import annotations
	10	+
	11	+import json
	12	+
	13	+from .base import RateProvider
	14	+
	15	+# clé CMS -> (rate_type, terme mois, kind, nom, clé APR éventuelle)
	16	+KEY_MAP: dict[str, tuple] = {
	17	+ "mortgage-rate-fixed-5-year": ("fixed", 60, "special",
	18	+ "Fixe 5 ans (vitrine EQ)",
	19	+ "mortgage-rate-fixed-5-year-APR"),
	20	+ "mortgage-rate-variable-5-year": ("variable", 60, "special",
	21	+ "Variable 5 ans (vitrine EQ)",
	22	+ "mortgage-rate-variable-5-year-APR"),
	23	+ "es-fixed-12-month": ("fixed", 12, "special", "Evolution Suite — fixe 1 an", None),
	24	+ "es-fixed-24-month": ("fixed", 24, "special", "Evolution Suite — fixe 2 ans", None),
	25	+ "es-fixed-36-month": ("fixed", 36, "special", "Evolution Suite — fixe 3 ans", None),
	26	+ "es-fixed-48-month": ("fixed", 48, "special", "Evolution Suite — fixe 4 ans", None),
	27	+ "es-fixed-60-month": ("fixed", 60, "special", "Evolution Suite — fixe 5 ans", None),
	28	+ "Standard-Mortgage-Rate-1-Year-Fixed": ("fixed", 12, "posted", "Fixe affiché 1 an", None),
	29	+ "Standard-Mortgage-Rate-2-Year-Fixed": ("fixed", 24, "posted", "Fixe affiché 2 ans", None),
	30	+ "Standard-Mortgage-Rate-3-Year-Fixed": ("fixed", 36, "posted", "Fixe affiché 3 ans", None),
	31	+ "Standard-Mortgage-Rate-4-Year-Fixed": ("fixed", 48, "posted", "Fixe affiché 4 ans", None),
	32	+ "Standard-Mortgage-Rate-5-Year-Fixed": ("fixed", 60, "posted", "Fixe affiché 5 ans", None),
	33	+}
	34	+PRIME_KEY = "equitable-prime-rate"
	35	+
	36	+
	37	+def extract_rates_blob(html: str) -> dict:
	38	+ """Isole le dictionnaire {clé: {name, rate}} du payload Next.js.
	39	+ Le JSON est échappé dans le HTML (\\\" -> \")."""
	40	+ marker = '\\"rates\\":{'
	41	+ i = html.find(marker)
	42	+ if i < 0:
	43	+ marker = '"rates":{'
	44	+ i = html.find(marker)
	45	+ if i < 0:
	46	+ raise ValueError("marqueur rates introuvable (structure changée)")
	47	+ seg = html[i:i + 400_000].replace('\\"', '"')
	48	+ start = seg.find("{")
	49	+ depth = 0
	50	+ for j, ch in enumerate(seg[start:], start):
	51	+ if ch == "{":
	52	+ depth += 1
	53	+ elif ch == "}":
	54	+ depth -= 1
	55	+ if depth == 0:
	56	+ return json.loads(seg[start:j + 1])
	57	+ raise ValueError("JSON rates non équilibré (structure changée)")
	58	+
	59	+
	60	+class EqBankProvider(RateProvider):
	61	+ provider_id = "eq_bank"
	62	+ institution = "Banque EQ"
	63	+ source_url = "https://www.eqbank.ca/residential/mortgage-rates"
	64	+ request_delay = 1.0
	65	+
	66	+ def fetch(self) -> list[dict]:
	67	+ return self.parse(self.get(self.source_url).text)
	68	+
	69	+ def parse(self, payload: str) -> list[dict]:
	70	+ rates = extract_rates_blob(payload)
	71	+
	72	+ def val(key: str) -> float \| None:
	73	+ cell = rates.get(key)
	74	+ if isinstance(cell, dict) and isinstance(cell.get("rate"), (int, float)):
	75	+ return float(cell["rate"])
	76	+ return None
	77	+
	78	+ out: list[dict] = []
	79	+ for key, (rtype, term, kind, name, apr_key) in KEY_MAP.items():
	80	+ rate = val(key)
	81	+ if rate is None:
	82	+ continue # clé absente : produit omis, jamais deviné
	83	+ apr = val(apr_key) if apr_key else None
	84	+ out.append(self.make_product(
	85	+ rate=rate, rate_type=rtype, term_months=term, kind=kind,
	86	+ product_name=name, apr=apr,
	87	+ raw={"key": key, "rate": rate, "apr": apr}))
	88	+ prime = val(PRIME_KEY)
	89	+ if prime is not None:
	90	+ out.append(self.make_product(
	91	+ rate=prime, rate_type="other", term_months=12, kind="posted",
	92	+ product_name="Taux préférentiel Banque Équitable",
	93	+ purpose="unknown", raw={"key": PRIME_KEY, "rate": prime}))
	94	+ return out

added immoka/mortgage/providers/first_national.py +97 −0

		`@@ -0,0 +1,97 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/providers/first_national.py : First National — table HTML statique
	5	+# (server-side, aucun anti-bot). Taux fixes fermés par catégorie
	6	+# assuré/assurable(LTV)/conventionnel, ARM « Prime - X% », prime maison.
	7	+# -----------------------------------------------------------------------------
	8	+from __future__ import annotations
	9	+
	10	+import re
	11	+
	12	+from bs4 import BeautifulSoup
	13	+
	14	+from .base import RateProvider, parse_rate, term_to_months
	15	+
	16	+
	17	+def _insured_status(category: str) -> str:
	18	+ c = category.lower()
	19	+ if c.startswith("insured"):
	20	+ return "insured"
	21	+ if c.startswith("insurable"):
	22	+ return "insurable"
	23	+ if c.startswith("conventional"):
	24	+ return "uninsured"
	25	+ return "unknown"
	26	+
	27	+
	28	+class FirstNationalProvider(RateProvider):
	29	+ provider_id = "first_national"
	30	+ institution = "First National"
	31	+ source_url = "https://www.firstnational.ca/residential/mortgage-rates"
	32	+ request_delay = 1.0
	33	+
	34	+ def fetch(self) -> list[dict]:
	35	+ return self.parse(self.get(self.source_url).text)
	36	+
	37	+ def parse(self, payload: str) -> list[dict]:
	38	+ soup = BeautifulSoup(payload, "html.parser")
	39	+ out: list[dict] = []
	40	+ prime = None
	41	+ m = re.search(r"First National Prime Rate:\s(?:</?\w+[^>]>\s)([\d.]+)",
	42	+ payload)
	43	+ if m:
	44	+ prime = float(m.group(1))
	45	+ # -- taux fixes fermés (table avec aria-label par terme) --------------
	46	+ for h3 in soup.find_all("h3"):
	47	+ title = h3.get_text(" ", strip=True)
	48	+ table = h3.find_next("table")
	49	+ if table is None:
	50	+ continue
	51	+ if title.lower().startswith("fixed rate mortgages"):
	52	+ for tr in table.select("tbody tr"):
	53	+ th = tr.find("th")
	54	+ if th is None:
	55	+ continue
	56	+ category = re.sub(r"\s+", " ", th.get_text(" ", strip=True))
	57	+ status = _insured_status(category)
	58	+ for td in tr.find_all("td"):
	59	+ term = term_to_months(td.get("aria-label") or "")
	60	+ rate = parse_rate(td.get_text(strip=True))
	61	+ if term is None or rate is None:
	62	+ continue # cellule N/A : produit non offert
	63	+ out.append(self.make_product(
	64	+ rate=rate, rate_type="fixed", term_months=term,
	65	+ kind="posted",
	66	+ product_name=f"Fixe fermé — {category}",
	67	+ insured_status=status, conditions=category,
	68	+ raw={"category": category,
	69	+ "cell": td.get_text(strip=True)}))
	70	+ elif title.lower().startswith("adjustable rate"):
	71	+ if prime is None:
	72	+ continue # sans prime confirmée, ne rien deviner
	73	+ for tr in table.select("tbody tr"):
	74	+ th = tr.find("th")
	75	+ td = tr.find("td")
	76	+ if th is None or td is None:
	77	+ continue
	78	+ category = re.sub(r"\s+", " ", th.get_text(" ", strip=True))
	79	+ cell = td.get_text(" ", strip=True)
	80	+ dm = re.search(r"Prime\s([+-])\s([\d.]+)\s*%", cell)
	81	+ if not dm:
	82	+ continue
	83	+ delta = float(dm.group(2)) * (1 if dm.group(1) == "+" else -1)
	84	+ out.append(self.make_product(
	85	+ rate=round(prime + delta, 2), rate_type="adjustable",
	86	+ term_months=60, kind="special",
	87	+ product_name=f"ARM 5 ans — {category}",
	88	+ insured_status=_insured_status(category),
	89	+ conditions=f"{cell} (prime First National {prime} %)",
	90	+ raw={"category": category, "cell": cell,
	91	+ "prime": prime, "delta": delta}))
	92	+ if prime is not None:
	93	+ out.append(self.make_product(
	94	+ rate=prime, rate_type="other", term_months=12, kind="posted",
	95	+ product_name="Taux préférentiel First National",
	96	+ purpose="unknown", raw={"prime": prime}))
	97	+ return out

added immoka/mortgage/providers/mcap.py +40 −0

		`@@ -0,0 +1,40 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/providers/mcap.py : MCAP — distribution 100 % courtiers, aucune
	5	+# table publique de taux par terme (vérifié 2026-08). Seul signal public :
	6	+# le taux préférentiel MCAP (+ date d'effet). Collecté comme référence,
	7	+# exclu du comparateur de prêteurs (rate_type="other", purpose="unknown").
	8	+# -----------------------------------------------------------------------------
	9	+from __future__ import annotations
	10	+
	11	+import re
	12	+
	13	+from .base import RateProvider
	14	+
	15	+
	16	+class McapProvider(RateProvider):
	17	+ provider_id = "mcap"
	18	+ institution = "MCAP"
	19	+ source_url = ("https://www.mcap.com/residential-mortgages/advice/"
	20	+ "mortgage-rates-canada")
	21	+ request_delay = 1.0
	22	+
	23	+ def fetch(self) -> list[dict]:
	24	+ return self.parse(self.get(self.source_url).text)
	25	+
	26	+ def parse(self, payload: str) -> list[dict]:
	27	+ m = re.search(
	28	+ r'prime-rate-module.?round-number-box[^>]>\s([\d.]+)\s%',
	29	+ payload, re.S)
	30	+ if not m:
	31	+ return []
	32	+ prime = float(m.group(1))
	33	+ dm = re.search(r'Effective\s+([A-Z][a-z]+ \d{1,2},? \d{4})', payload)
	34	+ conditions = ("Taux préférentiel MCAP"
	35	+ + (f" — en vigueur le {dm.group(1)}" if dm else ""))
	36	+ return [self.make_product(
	37	+ rate=prime, rate_type="other", term_months=12, kind="posted",
	38	+ product_name="Taux préférentiel MCAP", purpose="unknown",
	39	+ conditions=conditions,
	40	+ raw={"prime": prime, "effective": dm.group(1) if dm else None})]

added immoka/mortgage/providers/national_bank.py +131 −0

		`@@ -0,0 +1,131 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/providers/national_bank.py : Banque Nationale — JSON double-échappé
	5	+# setProductMap(JSON.parse("…")) dans la page des taux. c1 = produits
	6	+# hypothécaires (par productConditionName). ⚠️ Séparateurs décimaux mixtes :
	7	+# affichés « 6.090 » (point), promos « 4,84 » (virgule) — les tacNans sont
	8	+# les APR des promos. Le tauxBase du produit variable est un ÉCART, pas la
	9	+# prime : la prime vient du tauxBase du produit fixe.
	10	+# -----------------------------------------------------------------------------
	11	+from __future__ import annotations
	12	+
	13	+import json
	14	+import re
	15	+
	16	+from .base import RateProvider
	17	+
	18	+PAGE_URL = "https://www.nbc.ca/personal/mortgages/rates.html"
	19	+
	20	+MAP_RX = re.compile(r'setProductMap$JSON\.parse\("(.*?)"$\)', re.S)
	21	+
	22	+# champs affichés fixes (fermés) -> terme mois ; taux1moisF exclu (< 3 mois)
	23	+FIXED_POSTED = {
	24	+ "taux3moisF": 3, "taux6moisF": 6, "taux1anF": 12, "taux2ansF": 24,
	25	+ "taux3ansF": 36, "taux4ansF": 48, "taux5ansF": 60, "taux6ansF": 72,
	26	+ "taux7ansF": 84, "taux10ansF": 120,
	27	+}
	28	+FIXED_OPEN = {"taux6moisO": 6, "taux1anO": 12}
	29	+# promo -> (terme mois, champ APR)
	30	+FIXED_PROMO = {
	31	+ "tauxPromo3ansF": (36, "tac3ans"),
	32	+ "tauxPromo4ansF": (48, "tac4ans"),
	33	+ "tauxPromo5ansF": (60, "tac5ans"),
	34	+}
	35	+
	36	+
	37	+def _num(v) -> float \| None:
	38	+ if v in (None, ""):
	39	+ return None
	40	+ try:
	41	+ return float(str(v).replace("\xa0", "").replace(",", ".").strip())
	42	+ except ValueError:
	43	+ return None
	44	+
	45	+
	46	+class NationalBankProvider(RateProvider):
	47	+ provider_id = "national_bank"
	48	+ institution = "Banque Nationale"
	49	+ source_url = PAGE_URL
	50	+ request_delay = 1.5
	51	+
	52	+ def fetch(self) -> list[dict]:
	53	+ return self.parse(self.get(self.source_url).text)
	54	+
	55	+ def parse(self, payload: str) -> list[dict]:
	56	+ m = MAP_RX.search(payload)
	57	+ if not m:
	58	+ raise ValueError("setProductMap introuvable (structure changée)")
	59	+ dec = (m.group(1).replace("\\x22", '"')
	60	+ .replace("\\\\", "\\").replace("\\/", "/"))
	61	+ # la chaîne JS se termine par «"), true);» : raw_decode ignore la suite
	62	+ obj, _ = json.JSONDecoder().raw_decode(dec)
	63	+ products = json.loads(obj.get("c1") or "[]")
	64	+ by_name = {p.get("productConditionName"): p
	65	+ for p in products if isinstance(p, dict)}
	66	+ out: list[dict] = []
	67	+ fixed = by_name.get("Mortgage fixed rate") or {}
	68	+ for field, term in FIXED_POSTED.items():
	69	+ rate = _num(fixed.get(field))
	70	+ if rate and rate > 0:
	71	+ out.append(self.make_product(
	72	+ rate=rate, rate_type="fixed", term_months=term,
	73	+ kind="posted",
	74	+ product_name=f"Fixe fermé {_label(term)}",
	75	+ raw={"field": field, "value": fixed.get(field)}))
	76	+ for field, term in FIXED_OPEN.items():
	77	+ rate = _num(fixed.get(field))
	78	+ if rate and rate > 0:
	79	+ out.append(self.make_product(
	80	+ rate=rate, rate_type="fixed", term_months=term,
	81	+ kind="posted",
	82	+ product_name=f"Fixe ouvert {_label(term)}",
	83	+ raw={"field": field, "value": fixed.get(field)}))
	84	+ for field, (term, apr_field) in FIXED_PROMO.items():
	85	+ rate = _num(fixed.get(field))
	86	+ if rate and rate > 0:
	87	+ out.append(self.make_product(
	88	+ rate=rate, rate_type="fixed", term_months=term,
	89	+ kind="special", apr=_num(fixed.get(apr_field)),
	90	+ product_name=f"Fixe fermé {_label(term)} (promotion)",
	91	+ raw={"field": field, "value": fixed.get(field)}))
	92	+ prime = _num(fixed.get("tauxBase"))
	93	+ if prime and prime > 0:
	94	+ out.append(self.make_product(
	95	+ rate=prime, rate_type="other", term_months=12, kind="posted",
	96	+ product_name="Taux préférentiel BNC", purpose="unknown",
	97	+ raw={"field": "tauxBase", "value": fixed.get("tauxBase")}))
	98	+ variable = by_name.get("Mortgage variable rate") or {}
	99	+ v_posted = _num(variable.get("taux5ansO"))
	100	+ if v_posted and v_posted > 0:
	101	+ out.append(self.make_product(
	102	+ rate=v_posted, rate_type="variable", term_months=60,
	103	+ kind="posted", product_name="Variable 5 ans",
	104	+ conditions="Base = taux préférentiel BNC",
	105	+ raw={"field": "taux5ansO", "value": variable.get("taux5ansO")}))
	106	+ v_promo = _num(variable.get("tauxPromo5ansF"))
	107	+ if v_promo and v_promo > 0:
	108	+ out.append(self.make_product(
	109	+ rate=v_promo, rate_type="variable", term_months=60,
	110	+ kind="special", apr=_num(variable.get("tac5ans")),
	111	+ product_name="Variable 5 ans (promotion)",
	112	+ raw={"field": "tauxPromo5ansF",
	113	+ "value": variable.get("tauxPromo5ansF")}))
	114	+ capped = by_name.get("Variable capped-rate mortgage") or {}
	115	+ c_rate = _num(capped.get("taux5ansO"))
	116	+ if c_rate and c_rate > 0:
	117	+ cap = _num(capped.get("tauxPlafond"))
	118	+ out.append(self.make_product(
	119	+ rate=c_rate, rate_type="variable", term_months=60,
	120	+ kind="posted", product_name="Variable plafonné 5 ans",
	121	+ conditions=f"Taux plafond {cap} %" if cap else None,
	122	+ raw={"field": "taux5ansO", "value": capped.get("taux5ansO"),
	123	+ "tauxPlafond": capped.get("tauxPlafond")}))
	124	+ return out
	125	+
	126	+
	127	+def _label(months: int) -> str:
	128	+ if months < 12:
	129	+ return f"{months} mois"
	130	+ years = months // 12
	131	+ return f"{years} an" if years == 1 else f"{years} ans"

added immoka/mortgage/providers/rbc.py +112 −0

		`@@ -0,0 +1,112 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/providers/rbc.py : RBC — API JSON publique publicrates (celle que
	5	+# consomme leur propre page de taux, 1 requête par code de taux).
	6	+# ⚠️ Les produits variables sont publiés en ÉCART vs prime (ex. -0.500) :
	7	+# reconstitués avec le code prime, jamais interprétés comme des taux.
	8	+# -----------------------------------------------------------------------------
	9	+from __future__ import annotations
	10	+
	11	+import json
	12	+
	13	+from .base import RateProvider
	14	+
	15	+API = ("https://apps.royalbank.com/apps/app-services/public-rates/api/"
	16	+ "publicrates?code={code}")
	17	+PAGE_URL = "https://www.rbcroyalbank.com/mortgages/mortgage-rates.html"
	18	+
	19	+PRIME_CODE = "0006470002"
	20	+
	21	+# code -> (rate_type, terme mois, kind, insured_status, nom, code APR\|None)
	22	+CODE_MAP: dict[str, tuple] = {
	23	+ "0006340010": ("fixed", 6, "posted", "unknown", "Fixe 6 mois convertible", None),
	24	+ "0006340013": ("fixed", 12, "posted", "unknown", "Fixe fermé 1 an", None),
	25	+ "0006340016": ("fixed", 24, "posted", "unknown", "Fixe fermé 2 ans", None),
	26	+ "0006340019": ("fixed", 36, "posted", "unknown", "Fixe fermé 3 ans", None),
	27	+ "0006340022": ("fixed", 48, "posted", "unknown", "Fixe fermé 4 ans", None),
	28	+ "0006340025": ("fixed", 60, "posted", "unknown", "Fixe fermé 5 ans", None),
	29	+ "0006340042": ("fixed", 84, "posted", "unknown", "Fixe fermé 7 ans", None),
	30	+ "0006340030": ("fixed", 120, "posted", "unknown", "Fixe fermé 10 ans", None),
	31	+ "0386080056": ("fixed", 12, "special", "unknown", "Fixe fermé 1 an (offre spéciale)", "0386140074"),
	32	+ "0386080057": ("fixed", 24, "special", "unknown", "Fixe fermé 2 ans (offre spéciale)", "0386140075"),
	33	+ "0386080058": ("fixed", 36, "special", "unknown", "Fixe fermé 3 ans (offre spéciale)", "0386140076"),
	34	+ "0386080059": ("fixed", 48, "special", "unknown", "Fixe fermé 4 ans (offre spéciale)", "0386140077"),
	35	+ "0386080060": ("fixed", 60, "special", "unknown", "Fixe fermé 5 ans (offre spéciale)", "0386140078"),
	36	+ "0386080061": ("fixed", 84, "special", "unknown", "Fixe fermé 7 ans (offre spéciale)", "0386140079"),
	37	+ "0385940006": ("fixed", 60, "special", "insured", "Fixe fermé 5 ans (ratio élevé)", "0386090006"),
	38	+}
	39	+# codes variables : ÉCART vs prime -> taux = prime + valeur
	40	+SPREAD_MAP: dict[str, tuple] = {
	41	+ "0236440012": ("variable", 60, "posted", "unknown", "Variable fermé 5 ans", "0166950009"),
	42	+ "0386080070": ("variable", 60, "special", "unknown", "Variable fermé 5 ans (offre spéciale)", "0386140088"),
	43	+ "0385940016": ("variable", 60, "special", "insured", "Variable fermé 5 ans (ratio élevé)", "0386090016"),
	44	+}
	45	+
	46	+
	47	+def _value(responses: dict, code: str) -> float \| None:
	48	+ resp = responses.get(code)
	49	+ if not isinstance(resp, dict):
	50	+ return None
	51	+ content = resp.get("result_content") or {}
	52	+ try:
	53	+ return float(content.get("Value"))
	54	+ except (TypeError, ValueError):
	55	+ return None
	56	+
	57	+
	58	+class RbcProvider(RateProvider):
	59	+ provider_id = "rbc"
	60	+ institution = "RBC Banque Royale"
	61	+ source_url = PAGE_URL
	62	+ request_delay = 0.6
	63	+
	64	+ def _codes(self) -> list[str]:
	65	+ codes = [PRIME_CODE] + list(CODE_MAP) + list(SPREAD_MAP)
	66	+ codes += [apr for *_, apr in CODE_MAP.values() if apr]
	67	+ codes += [apr for *_, apr in SPREAD_MAP.values() if apr]
	68	+ return codes
	69	+
	70	+ def fetch(self) -> list[dict]:
	71	+ responses: dict[str, dict] = {}
	72	+ for code in self._codes():
	73	+ try:
	74	+ responses[code] = json.loads(self.get(API.format(code=code)).text)
	75	+ except Exception: # noqa: BLE001 — un code raté n'annule pas le reste
	76	+ continue
	77	+ return self.parse_codes(responses)
	78	+
	79	+ def parse(self, payload: str) -> list[dict]:
	80	+ """Pour les tests fixtures : payload = JSON {code: réponse API}."""
	81	+ data = json.loads(payload)
	82	+ return self.parse_codes(data.get("responses") or data)
	83	+
	84	+ def parse_codes(self, responses: dict) -> list[dict]:
	85	+ out: list[dict] = []
	86	+ prime = _value(responses, PRIME_CODE)
	87	+ for code, (rtype, term, kind, insured, name, apr_code) in CODE_MAP.items():
	88	+ rate = _value(responses, code)
	89	+ if rate is None or rate <= 0:
	90	+ continue
	91	+ apr = _value(responses, apr_code) if apr_code else None
	92	+ out.append(self.make_product(
	93	+ rate=rate, rate_type=rtype, term_months=term, kind=kind,
	94	+ product_name=name, apr=apr, insured_status=insured,
	95	+ raw={"code": code, "value": rate}))
	96	+ if prime is not None:
	97	+ for code, (rtype, term, kind, insured, name, apr_code) in SPREAD_MAP.items():
	98	+ spread = _value(responses, code)
	99	+ if spread is None or abs(spread) > 3:
	100	+ continue # un écart vs prime > 3 pts : structure changée
	101	+ apr = _value(responses, apr_code) if apr_code else None
	102	+ out.append(self.make_product(
	103	+ rate=round(prime + spread, 3), rate_type=rtype,
	104	+ term_months=term, kind=kind, product_name=name, apr=apr,
	105	+ insured_status=insured,
	106	+ conditions=f"Prime RBC {prime} % {spread:+} pt",
	107	+ raw={"code": code, "spread": spread, "prime": prime}))
	108	+ out.append(self.make_product(
	109	+ rate=prime, rate_type="other", term_months=12, kind="posted",
	110	+ product_name="Taux préférentiel RBC", purpose="unknown",
	111	+ raw={"code": PRIME_CODE, "value": prime}))
	112	+ return out

added immoka/mortgage/providers/scotiabank.py +104 −0

		`@@ -0,0 +1,104 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/providers/scotiabank.py : Banque Scotia — API JSON publique
	5	+# dmtsms.scotiabank.com (celle que consomme leur propre page de taux).
	6	+# nonspecialmortgage = taux affichés ; varmortgage = slots promotionnels
	7	+# (le mapping slot -> produit vient de la page ; on ne garde que les slots
	8	+# dont l'identité est connue, avec confiance réduite).
	9	+# -----------------------------------------------------------------------------
	10	+from __future__ import annotations
	11	+
	12	+import json
	13	+
	14	+from .base import RateProvider
	15	+
	16	+POSTED_URL = "https://dmtsms.scotiabank.com/api/rates/daily/nonspecialmortgage"
	17	+PROMO_URL = "https://dmtsms.scotiabank.com/api/rates/daily/varmortgage"
	18	+PAGE_URL = ("https://www.scotiabank.com/ca/en/personal/rates-prices/"
	19	+ "mortgages-rates.html")
	20	+
	21	+# PRODUCT -> (rate_type, insured_status, nom, purpose)
	22	+POSTED_MAP = {
	23	+ "N.H.A. RESIDENTIAL, ETC": ("fixed", "insured", "Fixe affiché (assuré LNH)"),
	24	+ "CONVENTIONAL RESIDENTIAL, ETC": ("fixed", "uninsured", "Fixe affiché (conventionnel)"),
	25	+ "ULTIMATE VARIABLE RATE": ("variable", "unknown", "Ultimate Variable"),
	26	+ "OPEN": ("fixed", "unknown", "Fixe ouvert"),
	27	+ "FLEXIBLE": ("fixed", "unknown", "Flexible"),
	28	+}
	29	+
	30	+# Slots promotionnels dont l'identité est documentée sur la page Scotia
	31	+# (2026-08). Confiance réduite : si Scotia réordonne ses slots, la validation
	32	+# et la comparaison croisée limitent les dégâts.
	33	+PROMO_SLOTS = {
	34	+ "MORTGAGE PROMOTIONAL 1": ("variable", 60, "Flex Value fermé 5 ans (variable)"),
	35	+ "MORTGAGE PROMOTIONAL 2": ("variable", 36, "Ultimate Variable 3 ans"),
	36	+ "MORTGAGE PROMOTIONAL 3": ("variable", 60, "Flex Value ouvert 5 ans (variable)"),
	37	+}
	38	+
	39	+
	40	+def _term_months(t: dict) -> int \| None:
	41	+ try:
	42	+ v = int(t["TERM_VALUE"])
	43	+ except (KeyError, ValueError, TypeError):
	44	+ return None
	45	+ unit = (t.get("TERM_UNIT") or "").upper()
	46	+ if unit == "Y":
	47	+ return v * 12
	48	+ if unit == "M":
	49	+ return v
	50	+ return None
	51	+
	52	+
	53	+class ScotiabankProvider(RateProvider):
	54	+ provider_id = "scotiabank"
	55	+ institution = "Banque Scotia"
	56	+ source_url = PAGE_URL
	57	+ request_delay = 1.0
	58	+
	59	+ def fetch(self) -> list[dict]:
	60	+ posted = self.get(POSTED_URL).text
	61	+ try:
	62	+ promo = self.get(PROMO_URL).text
	63	+ except Exception: # noqa: BLE001 — promos facultatives
	64	+ promo = ""
	65	+ return self.parse(posted) + (self.parse_promos(promo) if promo else [])
	66	+
	67	+ def parse(self, payload: str) -> list[dict]:
	68	+ data = json.loads(payload)
	69	+ out: list[dict] = []
	70	+ for prod in data.get("data") or []:
	71	+ name = (prod.get("PRODUCT") or "").strip()
	72	+ if name not in POSTED_MAP:
	73	+ continue # produits chalet/cap/right-rate : hors périmètre
	74	+ rtype, insured, label = POSTED_MAP[name]
	75	+ for t in prod.get("TERMS") or []:
	76	+ term = _term_months(t)
	77	+ rate = t.get("RATE")
	78	+ if term is None or not isinstance(rate, (int, float)) or rate <= 0:
	79	+ continue
	80	+ out.append(self.make_product(
	81	+ rate=float(rate), rate_type=rtype, term_months=term,
	82	+ kind="posted", product_name=label,
	83	+ insured_status=insured,
	84	+ conditions=name,
	85	+ raw={"product": name, "term": t}))
	86	+ return out
	87	+
	88	+ def parse_promos(self, payload: str) -> list[dict]:
	89	+ data = json.loads(payload)
	90	+ out: list[dict] = []
	91	+ for prod in data.get("data") or []:
	92	+ name = (prod.get("PRODUCT") or "").strip()
	93	+ if name not in PROMO_SLOTS:
	94	+ continue
	95	+ rate = prod.get("RATE")
	96	+ if not isinstance(rate, (int, float)) or rate <= 0:
	97	+ continue # slot inutilisé
	98	+ rtype, term, label = PROMO_SLOTS[name]
	99	+ out.append(self.make_product(
	100	+ rate=float(rate), rate_type=rtype, term_months=term,
	101	+ kind="special", product_name=label, confidence=0.8,
	102	+ conditions=f"Slot promotionnel Scotia ({name})",
	103	+ raw={"product": name, "rate": rate}))
	104	+ return out

added immoka/mortgage/providers/tangerine.py +55 −0

		`@@ -0,0 +1,55 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/providers/tangerine.py : Tangerine — JSON statique publié
	5	+# (currentRates.json, le fichier que charge leur page /rates). Un seul taux
	6	+# par terme (pas de distinction affiché/spécial chez Tangerine) : kind
	7	+# "special" car c'est leur taux client réel.
	8	+# -----------------------------------------------------------------------------
	9	+from __future__ import annotations
	10	+
	11	+import json
	12	+
	13	+from .base import RateProvider, parse_rate
	14	+
	15	+RATES_URL = ("https://www.tangerine.ca/content/dam/tangerine-shared/"
	16	+ "product-rates/currentRates.json")
	17	+
	18	+
	19	+class TangerineProvider(RateProvider):
	20	+ provider_id = "tangerine"
	21	+ institution = "Tangerine"
	22	+ source_url = "https://www.tangerine.ca/en/rates"
	23	+ request_delay = 1.0
	24	+
	25	+ def fetch(self) -> list[dict]:
	26	+ return self.parse(self.get(RATES_URL).text)
	27	+
	28	+ def parse(self, payload: str) -> list[dict]:
	29	+ data = json.loads(payload)
	30	+ out: list[dict] = []
	31	+ for r in data.get("rates") or []:
	32	+ if r.get("group") != "mortgage":
	33	+ continue
	34	+ code = r.get("max_product_code")
	35	+ rate = r.get("interest_rate")
	36	+ term_years = r.get("term")
	37	+ if not isinstance(rate, (int, float)) or rate <= 0:
	38	+ continue
	39	+ if not isinstance(term_years, (int, float)) or term_years <= 0:
	40	+ continue
	41	+ if code == "Mortgage":
	42	+ rtype, label = "fixed", f"Fixe {int(term_years)} an(s)"
	43	+ elif code == "VarMortgage":
	44	+ rtype, label = "variable", f"Variable {int(term_years)} an(s)"
	45	+ else:
	46	+ continue # preferred_* et autres : clients connectés, ignorés
	47	+ apr = parse_rate(r.get("apr_value_en") or "")
	48	+ out.append(self.make_product(
	49	+ rate=float(rate), rate_type=rtype,
	50	+ term_months=int(term_years * 12), kind="special",
	51	+ product_name=label, apr=apr,
	52	+ conditions=f"Taux unique Tangerine (en date du {r.get('date')})",
	53	+ raw={"account_term": r.get("account_term"),
	54	+ "date": r.get("date"), "interest_rate": rate}))
	55	+ return out

added immoka/mortgage/providers/td.py +115 −0

		`@@ -0,0 +1,115 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/providers/td.py : TD Canada Trust — API JSON publique getRates
	5	+# (POST ratesType=resl, celle que consomme leur page de taux). Chaque code
	6	+# MTG{F\|V}{mois}{C\|O} porte deux tableaux highRatio / nonHighRatio de la
	7	+# forme [affiché, escompte, spécial, APR, drapeau]. Le « affiché » des
	8	+# produits variables est le TD Mortgage Prime. ⚠️ Pour les termes sans offre
	9	+# spéciale réelle, TD publie un « spécial » reconstruit (escompte négatif)
	10	+# dont l'APR correspond en fait au taux AFFICHÉ : ces lignes incohérentes
	11	+# (APR < spécial) sont écartées — jamais interprétées.
	12	+# -----------------------------------------------------------------------------
	13	+from __future__ import annotations
	14	+
	15	+import json
	16	+import re
	17	+
	18	+from .base import RateProvider
	19	+
	20	+API_URL = "https://psservice.td.com/ca/en/carate/getRates"
	21	+PAGE_URL = ("https://www.td.com/ca/en/personal-banking/products/mortgages/"
	22	+ "mortgage-rates")
	23	+
	24	+CODE_RX = re.compile(r"^MTG([FV])(\d{3})([CO])$")
	25	+
	26	+IDX_POSTED, IDX_SPECIAL, IDX_APR = 0, 2, 3
	27	+
	28	+
	29	+def _num(v) -> float \| None:
	30	+ try:
	31	+ return float(str(v).strip())
	32	+ except (TypeError, ValueError):
	33	+ return None
	34	+
	35	+
	36	+def _label(months: int) -> str:
	37	+ if months < 12:
	38	+ return f"{months} mois"
	39	+ years = months // 12
	40	+ return f"{years} an" if years == 1 else f"{years} ans"
	41	+
	42	+
	43	+class TdProvider(RateProvider):
	44	+ provider_id = "td"
	45	+ institution = "TD Canada Trust"
	46	+ source_url = PAGE_URL
	47	+ request_delay = 1.0
	48	+
	49	+ def fetch(self) -> list[dict]:
	50	+ wait_kw = {"timeout": self.timeout,
	51	+ "headers": {"Content-Type": "application/json"}}
	52	+ resp = self.session.post(API_URL, json={"ratesType": "resl"}, **wait_kw)
	53	+ resp.raise_for_status()
	54	+ return self.parse(resp.text)
	55	+
	56	+ def parse(self, payload: str) -> list[dict]:
	57	+ data = json.loads(payload)
	58	+ if not isinstance(data, dict):
	59	+ raise ValueError("réponse TD inattendue (structure changée)")
	60	+ for wrapper in ("rates", "data", "result"):
	61	+ if wrapper in data and isinstance(data[wrapper], dict):
	62	+ data = data[wrapper]
	63	+ break
	64	+ out: list[dict] = []
	65	+ prime: float \| None = None
	66	+ for code, tables in data.items():
	67	+ m = CODE_RX.match(str(code))
	68	+ if not m or not isinstance(tables, dict):
	69	+ continue # FLT* (FlexLine/HELOC) et codes inconnus : ignorés
	70	+ rtype = "fixed" if m.group(1) == "F" else "variable"
	71	+ term = int(m.group(2))
	72	+ openness = "fermé" if m.group(3) == "C" else "ouvert"
	73	+ base = ("Fixe" if rtype == "fixed" else "Variable")
	74	+ non_hr = tables.get("nonHighRatio") or []
	75	+ high_r = tables.get("highRatio") or []
	76	+ posted = _num(non_hr[IDX_POSTED]) if len(non_hr) > IDX_POSTED else None
	77	+ if posted and posted > 0:
	78	+ if rtype == "variable":
	79	+ # l'« affiché » des codes MTGV est le TD Mortgage Prime,
	80	+ # pas le taux du produit : jamais émis comme taux variable
	81	+ prime = posted
	82	+ else:
	83	+ out.append(self.make_product(
	84	+ rate=posted, rate_type=rtype, term_months=term,
	85	+ kind="posted",
	86	+ product_name=f"{base} {openness} {_label(term)}",
	87	+ raw={"code": code, "row": non_hr}))
	88	+ for arr, insured, suffix in ((non_hr, "uninsured", ""),
	89	+ (high_r, "insured", ", ratio élevé")):
	90	+ if len(arr) <= IDX_APR:
	91	+ continue
	92	+ special = _num(arr[IDX_SPECIAL])
	93	+ if special is None or special <= 0:
	94	+ continue
	95	+ if posted is not None and special == posted and rtype == "fixed" \
	96	+ and _num(arr[1]) in (0, None):
	97	+ continue # pas de spécial publié pour ce produit
	98	+ apr = _num(arr[IDX_APR])
	99	+ if apr is not None and apr < special - 0.02:
	100	+ continue # « spécial » reconstruit : APR = celui du taux affiché
	101	+ out.append(self.make_product(
	102	+ rate=special, rate_type=rtype, term_months=term,
	103	+ kind="special", apr=apr,
	104	+ product_name=f"{base} {openness} {_label(term)} "
	105	+ f"(offre spéciale{suffix})",
	106	+ insured_status=insured,
	107	+ conditions="Base = TD Mortgage Prime"
	108	+ if rtype == "variable" else None,
	109	+ raw={"code": code, "row": arr}))
	110	+ if prime and prime > 0:
	111	+ out.append(self.make_product(
	112	+ rate=prime, rate_type="other", term_months=12, kind="posted",
	113	+ product_name="TD Mortgage Prime", purpose="unknown",
	114	+ raw={"field": "MTGV*[0]", "value": prime}))
	115	+ return out

added immoka/mortgage/scheduler.py +120 −0

		`@@ -0,0 +1,120 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/scheduler.py : orchestration de la collecte des taux.
	5	+# Pipeline : provider.fetch() -> validation -> enregistrement historisé.
	6	+# Retries avec backoff exponentiel, timeout par provider, logs structurés,
	7	+# santé par provider (provider_runs). Une panne d'un provider n'affecte
	8	+# jamais les autres ni le calculateur (dernière donnée valide conservée).
	9	+# -----------------------------------------------------------------------------
	10	+from __future__ import annotations
	11	+
	12	+import os
	13	+import time
	14	+import traceback
	15	+
	16	+import requests
	17	+
	18	+from . import store
	19	+from .providers import PROVIDERS
	20	+from .validate import validate_batch
	21	+
	22	+RETRIES = int(os.environ.get("IMMOKA_MORTGAGE_RETRIES", "3"))
	23	+BACKOFF_BASE_S = float(os.environ.get("IMMOKA_MORTGAGE_BACKOFF", "5"))
	24	+# Fréquence de collecte (minutes) — utilisée par watch() ci-dessous.
	25	+INTERVAL_MIN = int(os.environ.get("IMMOKA_MORTGAGE_INTERVAL_MIN", "180"))
	26	+
	27	+
	28	+def _log(**kw) -> None:
	29	+ print("[mortgage] " + " ".join(f"{k}={v}" for k, v in kw.items()),
	30	+ flush=True)
	31	+
	32	+
	33	+def run_provider(slug: str, con=None) -> dict:
	34	+ """Collecte UNE institution avec retries + backoff. Retourne le résumé."""
	35	+ if con is None:
	36	+ con = store.connect()
	37	+ cls = PROVIDERS[slug]
	38	+ t0 = time.time()
	39	+ products: list[dict] \| None = None
	40	+ status, message = "success", ""
	41	+ for attempt in range(RETRIES):
	42	+ try:
	43	+ products = cls().fetch()
	44	+ break
	45	+ except requests.RequestException as exc:
	46	+ status, message = "http_error", str(exc)[:200]
	47	+ except Exception as exc: # noqa: BLE001 — parseur cassé, etc.
	48	+ status, message = "parser_error", str(exc)[:200]
	49	+ traceback.print_exc()
	50	+ if attempt < RETRIES - 1:
	51	+ time.sleep(BACKOFF_BASE_S * (2 ** attempt))
	52	+ duration_ms = int((time.time() - t0) * 1000)
	53	+ if products is None:
	54	+ store.log_run(con, slug, ok=False, status=status,
	55	+ duration_ms=duration_ms, message=message)
	56	+ _log(provider=slug, status=status, duration=f"{duration_ms}ms",
	57	+ message=message or "-")
	58	+ return {"provider": slug, "ok": False, "status": status,
	59	+ "message": message}
	60	+ valid, problems = validate_batch(products)
	61	+ if not valid:
	62	+ status = "empty" if not products else "validation_error"
	63	+ store.log_run(con, slug, ok=False, status=status,
	64	+ products=len(products), rejected=len(problems),
	65	+ duration_ms=duration_ms,
	66	+ message="; ".join(problems[:5]))
	67	+ _log(provider=slug, status=status, products=len(products),
	68	+ rejected=len(problems), duration=f"{duration_ms}ms")
	69	+ return {"provider": slug, "ok": False, "status": status,
	70	+ "problems": problems}
	71	+ res = store.record_observations(con, slug, valid)
	72	+ ok = True
	73	+ if problems or res["rejected"]:
	74	+ status = "success" # partiel : données saines enregistrées quand même
	75	+ store.log_run(con, slug, ok=ok, status=status, products=len(valid),
	76	+ changed=res["changed"],
	77	+ rejected=len(problems) + res["rejected"],
	78	+ duration_ms=duration_ms,
	79	+ message="; ".join((problems + res["rejected_details"])[:5]))
	80	+ _log(provider=slug, status=status, products=len(valid),
	81	+ changed=res["changed"], rejected=len(problems) + res["rejected"],
	82	+ duration=f"{duration_ms}ms")
	83	+ return {"provider": slug, "ok": True, "status": status,
	84	+ "products": len(valid), "changed": res["changed"],
	85	+ "rejected": len(problems) + res["rejected"]}
	86	+
	87	+
	88	+def run(only: list[str] \| None = None) -> list[dict]:
	89	+ """Collecte toutes les institutions (ou celles listées). Séquentiel et
	90	+ poli — jamais de martèlement des sites bancaires."""
	91	+ con = store.connect()
	92	+ slugs = [s for s in sorted(PROVIDERS) if not only or s in only]
	93	+ results = [run_provider(s, con) for s in slugs]
	94	+ ok = sum(1 for r in results if r["ok"])
	95	+ _log(status="done", providers=len(results), ok=ok,
	96	+ failed=len(results) - ok)
	97	+ return results
	98	+
	99	+
	100	+def watch(interval_minutes: int \| None = None) -> None:
	101	+ """Boucle autonome de collecte (défaut : IMMOKA_MORTGAGE_INTERVAL_MIN)."""
	102	+ minutes = interval_minutes or INTERVAL_MIN
	103	+ while True:
	104	+ try:
	105	+ run()
	106	+ except Exception: # noqa: BLE001 — la boucle ne meurt jamais
	107	+ traceback.print_exc()
	108	+ time.sleep(minutes * 60)
	109	+
	110	+
	111	+def maybe_run(min_age_minutes: int \| None = None) -> None:
	112	+ """Collecte seulement si la dernière passe date de plus de
	113	+ `min_age_minutes` — appelé depuis la boucle watch d'ingest.py sans risque
	114	+ de sur-solliciter les banques."""
	115	+ age_min = min_age_minutes or INTERVAL_MIN
	116	+ con = store.connect()
	117	+ last = con.execute("SELECT MAX(ts) AS m FROM provider_runs").fetchone()
	118	+ if last and last["m"] and (time.time() - last["m"]) < age_min * 60:
	119	+ return
	120	+ run()

added immoka/mortgage/store.py +336 −0

		`@@ -0,0 +1,336 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/store.py : persistance des taux hypothécaires (data/mortgage.db).
	5	+# Historisation par périodes de validité : une ligne « courante » par produit
	6	+# (valid_to IS NULL) ; un changement de taux ferme la ligne et en ouvre une
	7	+# nouvelle. Aucune donnée n'est jamais écrasée — l'historique complet se
	8	+# reconstruit par produit. Santé des providers dans provider_runs.
	9	+# -----------------------------------------------------------------------------
	10	+from __future__ import annotations
	11	+
	12	+import hashlib
	13	+import json
	14	+import sqlite3
	15	+import statistics
	16	+import time
	17	+from pathlib import Path
	18	+
	19	+DB_PATH = Path(__file__).resolve().parent.parent.parent / "data" / "mortgage.db"
	20	+
	21	+# Un taux « courant » plus vieux que STALE_H heures est signalé périmé.
	22	+STALE_H = 24
	23	+# Rejet des sauts aberrants : variation > JUMP_MAX points en < JUMP_WINDOW_H h.
	24	+JUMP_MAX = 2.5
	25	+JUMP_WINDOW_H = 48
	26	+
	27	+_SCHEMA = """
	28	+CREATE TABLE IF NOT EXISTS rate_observations (
	29	+ id INTEGER PRIMARY KEY AUTOINCREMENT,
	30	+ provider TEXT NOT NULL,
	31	+ institution TEXT NOT NULL,
	32	+ product_key TEXT NOT NULL, -- empreinte identité produit
	33	+ product_name TEXT,
	34	+ rate_type TEXT NOT NULL, -- fixed\|variable\|adjustable\|other
	35	+ term_months INTEGER NOT NULL,
	36	+ kind TEXT NOT NULL, -- posted\|special
	37	+ rate REAL NOT NULL, -- taux contractuel en % (ex. 4.19)
	38	+ apr REAL,
	39	+ insured_status TEXT DEFAULT 'unknown', -- insured\|insurable\|uninsured\|unknown
	40	+ purpose TEXT DEFAULT 'purchase', -- purchase\|renewal\|refinance\|unknown
	41	+ amortization_max_years INTEGER,
	42	+ conditions TEXT,
	43	+ source_url TEXT,
	44	+ confidence REAL DEFAULT 1.0,
	45	+ raw TEXT, -- JSON : observation brute (audit)
	46	+ valid_from REAL NOT NULL,
	47	+ valid_to REAL, -- NULL = taux courant
	48	+ last_checked REAL NOT NULL
	49	+);
	50	+CREATE INDEX IF NOT EXISTS idx_rateobs_current
	51	+ ON rate_observations(provider, product_key, valid_to);
	52	+CREATE INDEX IF NOT EXISTS idx_rateobs_lookup
	53	+ ON rate_observations(rate_type, term_months, valid_to);
	54	+
	55	+CREATE TABLE IF NOT EXISTS provider_runs (
	56	+ id INTEGER PRIMARY KEY AUTOINCREMENT,
	57	+ provider TEXT NOT NULL,
	58	+ ts REAL NOT NULL,
	59	+ ok INTEGER,
	60	+ status TEXT, -- success\|http_error\|parser_error\|validation_error\|empty
	61	+ products INTEGER,
	62	+ changed INTEGER,
	63	+ rejected INTEGER,
	64	+ duration_ms INTEGER,
	65	+ message TEXT
	66	+);
	67	+CREATE INDEX IF NOT EXISTS idx_provider_runs ON provider_runs(provider, ts);
	68	+
	69	+-- Préparé pour les notifications futures (« alerte-moi si le 5 ans fixe
	70	+-- passe sous 3,99 % » / « si le paiement de cette propriété passe sous X $ »).
	71	+CREATE TABLE IF NOT EXISTS rate_alerts (
	72	+ id INTEGER PRIMARY KEY AUTOINCREMENT,
	73	+ created REAL NOT NULL,
	74	+ kind TEXT NOT NULL, -- rate_below\|payment_below
	75	+ params TEXT, -- JSON : {rate_type, term_months, uid, down…}
	76	+ threshold REAL NOT NULL,
	77	+ contact TEXT,
	78	+ active INTEGER DEFAULT 1,
	79	+ fired_at REAL
	80	+);
	81	+"""
	82	+
	83	+_SCHEMA_READY = False
	84	+
	85	+
	86	+def connect() -> sqlite3.Connection:
	87	+ global _SCHEMA_READY
	88	+ DB_PATH.parent.mkdir(parents=True, exist_ok=True)
	89	+ con = sqlite3.connect(DB_PATH, timeout=60)
	90	+ con.row_factory = sqlite3.Row
	91	+ con.execute("PRAGMA journal_mode=WAL")
	92	+ con.execute("PRAGMA synchronous=NORMAL")
	93	+ con.execute("PRAGMA busy_timeout=120000")
	94	+ if not _SCHEMA_READY:
	95	+ con.executescript(_SCHEMA)
	96	+ con.commit()
	97	+ _SCHEMA_READY = True
	98	+ return con
	99	+
	100	+
	101	+def product_key(p: dict) -> str:
	102	+ """Identité stable d'un produit : institution + type + terme + nature du
	103	+ taux + assurabilité + objet + nom. Deux produits incompatibles ne
	104	+ partagent jamais la même clé (règle : ne jamais comparer l'incomparable)."""
	105	+ ident = "\|".join([
	106	+ p["provider"], p["rate_type"], str(p["term_months"]), p["kind"],
	107	+ p.get("insured_status") or "unknown", p.get("purpose") or "purchase",
	108	+ (p.get("product_name") or "").strip().lower(),
	109	+ ])
	110	+ return hashlib.sha1(ident.encode()).hexdigest()[:16]
	111	+
	112	+
	113	+def record_observations(con: sqlite3.Connection, provider: str,
	114	+ products: list[dict]) -> dict:
	115	+ """Enregistre une passe de collecte validée.
	116	+
	117	+ Pour chaque produit : si le taux courant est identique → simple mise à
	118	+ jour de last_checked ; s'il a changé → fermeture de la période et
	119	+ insertion d'une nouvelle ligne. Rejette les sauts aberrants (> JUMP_MAX
	120	+ points en < JUMP_WINDOW_H h) sans écraser la bonne donnée précédente.
	121	+ Retourne {seen, changed, rejected, rejected_details}."""
	122	+ now = time.time()
	123	+ changed = 0
	124	+ rejected: list[str] = []
	125	+ for p in products:
	126	+ pk = product_key(p)
	127	+ cur = con.execute(
	128	+ "SELECT id, rate, last_checked FROM rate_observations "
	129	+ "WHERE provider=? AND product_key=? AND valid_to IS NULL",
	130	+ (provider, pk)).fetchone()
	131	+ if cur is not None:
	132	+ if abs(cur["rate"] - p["rate"]) < 1e-9:
	133	+ con.execute(
	134	+ "UPDATE rate_observations SET last_checked=?, apr=?, "
	135	+ "conditions=?, source_url=? WHERE id=?",
	136	+ (now, p.get("apr"), p.get("conditions"),
	137	+ p.get("source_url"), cur["id"]))
	138	+ continue
	139	+ # Garde-fou anti-aberration : ne jamais écraser une donnée saine
	140	+ # par un saut manifestement impossible.
	141	+ age_h = (now - (cur["last_checked"] or now)) / 3600.0
	142	+ if abs(cur["rate"] - p["rate"]) > JUMP_MAX and age_h < JUMP_WINDOW_H:
	143	+ rejected.append(
	144	+ f"{p.get('product_name') or pk}: {cur['rate']} -> "
	145	+ f"{p['rate']} (saut aberrant)")
	146	+ continue
	147	+ con.execute("UPDATE rate_observations SET valid_to=? WHERE id=?",
	148	+ (now, cur["id"]))
	149	+ changed += 1
	150	+ con.execute(
	151	+ "INSERT INTO rate_observations (provider, institution, "
	152	+ "product_key, product_name, rate_type, term_months, kind, rate, "
	153	+ "apr, insured_status, purpose, amortization_max_years, "
	154	+ "conditions, source_url, confidence, raw, valid_from, "
	155	+ "valid_to, last_checked) "
	156	+ "VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,NULL,?)",
	157	+ (provider, p["institution"], pk, p.get("product_name"),
	158	+ p["rate_type"], p["term_months"], p["kind"], p["rate"],
	159	+ p.get("apr"), p.get("insured_status") or "unknown",
	160	+ p.get("purpose") or "purchase", p.get("amortization_max_years"),
	161	+ p.get("conditions"), p.get("source_url"),
	162	+ p.get("confidence", 1.0),
	163	+ json.dumps(p.get("raw"), ensure_ascii=False) if p.get("raw") else None,
	164	+ now, now))
	165	+ con.commit()
	166	+ return {"seen": len(products), "changed": changed,
	167	+ "rejected": len(rejected), "rejected_details": rejected}
	168	+
	169	+
	170	+def _row(r: sqlite3.Row) -> dict:
	171	+ d = dict(r)
	172	+ d.pop("raw", None)
	173	+ now = time.time()
	174	+ d["age_minutes"] = round((now - (d.get("last_checked") or now)) / 60)
	175	+ d["stale"] = d["age_minutes"] > STALE_H * 60
	176	+ return d
	177	+
	178	+
	179	+def current_rates(con: sqlite3.Connection, rate_type: str \| None = None,
	180	+ term_months: int \| None = None, kind: str \| None = None,
	181	+ insured_status: str \| None = None,
	182	+ purpose: str \| None = None,
	183	+ provider: str \| None = None) -> list[dict]:
	184	+ """Taux courants (dernière donnée valide par produit), filtrables."""
	185	+ q = ("SELECT * FROM rate_observations WHERE valid_to IS NULL")
	186	+ args: list = []
	187	+ for col, val in (("rate_type", rate_type), ("term_months", term_months),
	188	+ ("kind", kind), ("provider", provider),
	189	+ ("purpose", purpose)):
	190	+ if val is not None:
	191	+ q += f" AND {col}=?"
	192	+ args.append(val)
	193	+ if insured_status is not None:
	194	+ q += " AND insured_status IN (?, 'unknown')"
	195	+ args.append(insured_status)
	196	+ q += " ORDER BY provider, term_months, rate"
	197	+ return [_row(r) for r in con.execute(q, args).fetchall()]
	198	+
	199	+
	200	+def best_rate(con: sqlite3.Connection, rate_type: str = "fixed",
	201	+ term_months: int = 60, insured_status: str \| None = None,
	202	+ purpose: str = "purchase") -> dict \| None:
	203	+ """Meilleur taux courant pour un produit comparable (privilégie les taux
	204	+ « special », sinon posted). Retourne la ligne complète + contexte."""
	205	+ rows = current_rates(con, rate_type=rate_type, term_months=term_months,
	206	+ insured_status=insured_status, purpose=purpose)
	207	+ if not rows:
	208	+ return None
	209	+ # Un seul candidat par institution : special prioritaire, sinon posted.
	210	+ by_inst: dict[str, dict] = {}
	211	+ for r in rows:
	212	+ cur = by_inst.get(r["provider"])
	213	+ if cur is None:
	214	+ by_inst[r["provider"]] = r
	215	+ elif r["kind"] == "special" and cur["kind"] == "posted":
	216	+ by_inst[r["provider"]] = r
	217	+ elif r["kind"] == cur["kind"] and r["rate"] < cur["rate"]:
	218	+ by_inst[r["provider"]] = r
	219	+ candidates = sorted(by_inst.values(), key=lambda r: r["rate"])
	220	+ best = candidates[0]
	221	+ rates = [r["rate"] for r in candidates]
	222	+ return {
	223	+ **best,
	224	+ "median_rate": round(statistics.median(rates), 2) if rates else None,
	225	+ "institutions_count": len(candidates),
	226	+ "per_institution": candidates,
	227	+ }
	228	+
	229	+
	230	+def history(con: sqlite3.Connection, rate_type: str, term_months: int,
	231	+ provider: str \| None = None, kind: str \| None = None,
	232	+ days: int = 365) -> list[dict]:
	233	+ """Historique : périodes de validité (valid_from/valid_to) par produit."""
	234	+ since = time.time() - days * 86400
	235	+ q = ("SELECT provider, institution, product_name, kind, rate, "
	236	+ "insured_status, valid_from, valid_to, last_checked, source_url "
	237	+ "FROM rate_observations WHERE rate_type=? AND term_months=? "
	238	+ "AND (valid_to IS NULL OR valid_to >= ?)")
	239	+ args: list = [rate_type, term_months, since]
	240	+ if provider:
	241	+ q += " AND provider=?"
	242	+ args.append(provider)
	243	+ if kind:
	244	+ q += " AND kind=?"
	245	+ args.append(kind)
	246	+ q += " ORDER BY provider, valid_from"
	247	+ return [dict(r) for r in con.execute(q, args).fetchall()]
	248	+
	249	+
	250	+def rate_at(con: sqlite3.Connection, rate_type: str, term_months: int,
	251	+ ts: float, kind: str = "special") -> float \| None:
	252	+ """Meilleur taux observé (toutes institutions) à un instant donné."""
	253	+ rows = con.execute(
	254	+ "SELECT MIN(rate) AS r FROM rate_observations "
	255	+ "WHERE rate_type=? AND term_months=? AND kind=? AND valid_from<=? "
	256	+ "AND (valid_to IS NULL OR valid_to>?) AND last_checked>=?",
	257	+ (rate_type, term_months, kind, ts, ts, ts - 14 * 86400)).fetchone()
	258	+ if rows is None or rows["r"] is None:
	259	+ # repli : posted si aucun special à cette date
	260	+ rows = con.execute(
	261	+ "SELECT MIN(rate) AS r FROM rate_observations "
	262	+ "WHERE rate_type=? AND term_months=? AND valid_from<=? "
	263	+ "AND (valid_to IS NULL OR valid_to>?)",
	264	+ (rate_type, term_months, ts, ts)).fetchone()
	265	+ return rows["r"] if rows else None
	266	+
	267	+
	268	+def market_stats(con: sqlite3.Connection, rate_type: str = "fixed",
	269	+ term_months: int = 60) -> dict \| None:
	270	+ """Métriques Mortgage Intelligence : meilleur, médian, spread,
	271	+ variations 7/30/90 jours, plus bas observé 6 mois."""
	272	+ best = best_rate(con, rate_type=rate_type, term_months=term_months)
	273	+ if best is None:
	274	+ return None
	275	+ now = time.time()
	276	+ out = {
	277	+ "rate_type": rate_type,
	278	+ "term_months": term_months,
	279	+ "best": best["rate"],
	280	+ "best_provider": best["provider"],
	281	+ "best_institution": best["institution"],
	282	+ "best_kind": best["kind"],
	283	+ "median": best["median_rate"],
	284	+ "spread": (round(best["median_rate"] - best["rate"], 2)
	285	+ if best["median_rate"] is not None else None),
	286	+ "institutions_count": best["institutions_count"],
	287	+ }
	288	+ for label, days in (("var_7d", 7), ("var_30d", 30), ("var_90d", 90)):
	289	+ past = rate_at(con, rate_type, term_months, now - days * 86400)
	290	+ out[label] = round(best["rate"] - past, 2) if past is not None else None
	291	+ low = con.execute(
	292	+ "SELECT MIN(rate) AS r FROM rate_observations "
	293	+ "WHERE rate_type=? AND term_months=? AND kind='special' "
	294	+ "AND last_checked >= ?",
	295	+ (rate_type, term_months, now - 182 * 86400)).fetchone()
	296	+ out["lowest_6m"] = low["r"] if low and low["r"] is not None else None
	297	+ return out
	298	+
	299	+
	300	+def log_run(con: sqlite3.Connection, provider: str, ok: bool, status: str,
	301	+ products: int = 0, changed: int = 0, rejected: int = 0,
	302	+ duration_ms: int = 0, message: str = "") -> None:
	303	+ con.execute(
	304	+ "INSERT INTO provider_runs (provider, ts, ok, status, products, "
	305	+ "changed, rejected, duration_ms, message) VALUES (?,?,?,?,?,?,?,?,?)",
	306	+ (provider, time.time(), 1 if ok else 0, status, products, changed,
	307	+ rejected, duration_ms, message[:500]))
	308	+ con.commit()
	309	+
	310	+
	311	+def provider_health(con: sqlite3.Connection) -> list[dict]:
	312	+ """Dernier état de chaque provider : OK / WARNING / ERROR + fraîcheur."""
	313	+ rows = con.execute(
	314	+ "SELECT p.* FROM provider_runs p JOIN (SELECT provider, MAX(ts) AS m "
	315	+ "FROM provider_runs GROUP BY provider) x "
	316	+ "ON p.provider=x.provider AND p.ts=x.m ORDER BY p.provider").fetchall()
	317	+ now = time.time()
	318	+ out = []
	319	+ for r in rows:
	320	+ d = dict(r)
	321	+ n_current = con.execute(
	322	+ "SELECT COUNT(*) AS n, MAX(last_checked) AS mc "
	323	+ "FROM rate_observations WHERE provider=? AND valid_to IS NULL",
	324	+ (r["provider"],)).fetchone()
	325	+ age_min = round((now - r["ts"]) / 60)
	326	+ if r["ok"] and n_current["n"] > 0:
	327	+ level = "WARNING" if age_min > STALE_H * 60 or r["rejected"] else "OK"
	328	+ elif n_current["n"] > 0:
	329	+ level = "WARNING" # échec récent mais données valides conservées
	330	+ else:
	331	+ level = "ERROR"
	332	+ d.update({"level": level, "age_minutes": age_min,
	333	+ "current_products": n_current["n"],
	334	+ "last_data_at": n_current["mc"]})
	335	+ out.append(d)
	336	+ return out

added immoka/mortgage/validate.py +79 −0

		`@@ -0,0 +1,79 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# mortgage/validate.py : couche de validation des observations de taux.
	5	+# Règle absolue : ne jamais inventer ni laisser passer un taux impossible.
	6	+# 4.19 % -> 419 % doit être rejeté ; une bonne donnée n'est jamais écrasée
	7	+# par une donnée manifestement erronée (garde-fou complémentaire dans
	8	+# store.record_observations).
	9	+# -----------------------------------------------------------------------------
	10	+from __future__ import annotations
	11	+
	12	+RATE_MIN = 0.25 # sous 0,25 % : impossible pour une hypothèque canadienne
	13	+RATE_MAX = 20.0 # au-delà de 20 % : aberrant (même les prêts privés)
	14	+TERM_MIN_MONTHS = 3
	15	+TERM_MAX_MONTHS = 120
	16	+
	17	+VALID_RATE_TYPES = {"fixed", "variable", "adjustable", "other"}
	18	+VALID_KINDS = {"posted", "special"}
	19	+VALID_INSURED = {"insured", "insurable", "uninsured", "unknown"}
	20	+VALID_PURPOSES = {"purchase", "renewal", "refinance", "unknown"}
	21	+
	22	+REQUIRED_FIELDS = ("provider", "institution", "rate_type", "term_months",
	23	+ "kind", "rate", "source_url")
	24	+
	25	+
	26	+def validate_product(p: dict) -> tuple[bool, list[str]]:
	27	+ """Valide UNE observation normalisée. Retourne (ok, problèmes)."""
	28	+ issues: list[str] = []
	29	+ for f in REQUIRED_FIELDS:
	30	+ if p.get(f) in (None, ""):
	31	+ issues.append(f"champ manquant: {f}")
	32	+ if issues:
	33	+ return False, issues
	34	+ rate = p["rate"]
	35	+ if not isinstance(rate, (int, float)):
	36	+ issues.append(f"taux non numérique: {rate!r}")
	37	+ elif rate <= 0:
	38	+ issues.append(f"taux nul ou négatif: {rate}")
	39	+ elif rate < RATE_MIN or rate > RATE_MAX:
	40	+ issues.append(f"taux impossible: {rate}")
	41	+ term = p["term_months"]
	42	+ if not isinstance(term, int) or not (TERM_MIN_MONTHS <= term <= TERM_MAX_MONTHS):
	43	+ issues.append(f"terme invalide: {term!r}")
	44	+ if p["rate_type"] not in VALID_RATE_TYPES:
	45	+ issues.append(f"rate_type invalide: {p['rate_type']}")
	46	+ if p["kind"] not in VALID_KINDS:
	47	+ issues.append(f"kind invalide: {p['kind']}")
	48	+ if p.get("insured_status", "unknown") not in VALID_INSURED:
	49	+ issues.append(f"insured_status invalide: {p.get('insured_status')}")
	50	+ if p.get("purpose", "purchase") not in VALID_PURPOSES:
	51	+ issues.append(f"purpose invalide: {p.get('purpose')}")
	52	+ apr = p.get("apr")
	53	+ if apr is not None:
	54	+ if not isinstance(apr, (int, float)) or apr < RATE_MIN or apr > RATE_MAX:
	55	+ issues.append(f"APR impossible: {apr!r}")
	56	+ elif isinstance(rate, (int, float)) and apr < rate - 0.02:
	57	+ issues.append(f"APR ({apr}) inférieur au taux contractuel ({rate})")
	58	+ return not issues, issues
	59	+
	60	+
	61	+def validate_batch(products: list[dict]) -> tuple[list[dict], list[str]]:
	62	+ """Valide une passe complète : élimine invalides et duplicatas exacts.
	63	+ Retourne (produits valides, problèmes)."""
	64	+ from .store import product_key
	65	+ ok_products: list[dict] = []
	66	+ problems: list[str] = []
	67	+ seen: set[tuple[str, float]] = set()
	68	+ for p in products:
	69	+ valid, issues = validate_product(p)
	70	+ if not valid:
	71	+ name = p.get("product_name") or "?"
	72	+ problems.extend(f"{name}: {i}" for i in issues)
	73	+ continue
	74	+ key = (product_key(p), round(float(p["rate"]), 4))
	75	+ if key in seen:
	76	+ continue # duplicata exact silencieusement ignoré
	77	+ seen.add(key)
	78	+ ok_products.append(p)
	79	+ return ok_products, problems

added immoka/normalize.py +258 −0

		`@@ -0,0 +1,258 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# normalize.py : couche de normalisation commune (prix, types, adresses…)
	5	+# -----------------------------------------------------------------------------
	6	+"""Fonctions de normalisation partagées par tous les connecteurs.
	7	+
	8	+Les connecteurs remplissent les champs bruts tels que vus sur le site source ;
	9	+`PropertyListing.finalize()` (schema.py) appelle ces fonctions pour produire
	10	+des valeurs canoniques comparables entre agences.
	11	+"""
	12	+from __future__ import annotations
	13	+
	14	+import re
	15	+import unicodedata
	16	+
	17	+__all__ = [
	18	+ "strip_accents", "clean_address", "parse_price", "price_is_from",
	19	+ "parse_int", "parse_float", "parse_area_sqft", "parse_lot_sqft",
	20	+ "parse_year", "normalize_property_type", "extract_bedrooms_bathrooms",
	21	+ "clean_title", "clean_description",
	22	+]
	23	+
	24	+
	25	+def strip_accents(text: str) -> str:
	26	+ return "".join(c for c in unicodedata.normalize("NFD", text or "")
	27	+ if unicodedata.category(c) != "Mn")
	28	+
	29	+
	30	+_SMALL_WORDS = {"a", "à", "au", "aux", "avec", "de", "des", "du", "en", "et",
	31	+ "la", "le", "les", "ou", "pour", "sur", "sous", "un", "une"}
	32	+
	33	+
	34	+def clean_title(text: str) -> str:
	35	+ """Titre propre : espaces normalisés, et les titres CRIÉS EN MAJUSCULES
	36	+ (fréquents chez certaines sources) ramenés en casse naturelle — chaque mot
	37	+ capitalisé sauf les mots-outils (les noms de villes restent capitalisés)."""
	38	+ t = re.sub(r"\s+", " ", (text or "")).strip()
	39	+ letters = [c for c in t if c.isalpha()]
	40	+ if len(letters) >= 8 and sum(c.isupper() for c in letters) / len(letters) > 0.85:
	41	+ words = []
	42	+ for i, w in enumerate(t.lower().split(" ")):
	43	+ words.append(w if (i and w in _SMALL_WORDS) else w[:1].upper() + w[1:])
	44	+ t = " ".join(words)
	45	+ return t
	46	+
	47	+
	48	+_TAG_RE = re.compile(r"<[^>]+>")
	49	+_BR_RE = re.compile(r"<br\s*/?>\|</p>\|</div>\|</li>", re.I)
	50	+
	51	+
	52	+def clean_description(text: str) -> str:
	53	+ """Description sans HTML brut visible : balises retirées (sauts de ligne
	54	+ préservés), entités décodées, espaces/blancs normalisés."""
	55	+ import html as _html
	56	+ t = text or ""
	57	+ if "<" in t and ">" in t:
	58	+ t = _BR_RE.sub("\n", t)
	59	+ t = _TAG_RE.sub(" ", t)
	60	+ t = _html.unescape(t)
	61	+ t = re.sub(r"[ \t]+", " ", t)
	62	+ t = re.sub(r" ?\n ?", "\n", t)
	63	+ t = re.sub(r"\n{3,}", "\n\n", t)
	64	+ return t.strip()
	65	+
	66	+
	67	+def clean_address(text: str) -> str:
	68	+ """Nettoie une adresse civique (espaces, virgules doublées, apostrophes)."""
	69	+ t = re.sub(r"\s+", " ", (text or "").replace("’", "'")).strip()
	70	+ t = re.sub(r"\s,\s", ", ", t)
	71	+ t = re.sub(r"(, )+", ", ", t).strip(", ")
	72	+ return t
	73	+
	74	+
	75	+# ---------------------------------------------------------------------------
	76	+# Prix
	77	+# ---------------------------------------------------------------------------
	78	+
	79	+_PRICE_RE = re.compile(r"(\d[\d\s  .,])\s(?:\$\|CAD)?", re.UNICODE)
	80	+
	81	+
	82	+def parse_price(label: str) -> float \| None:
	83	+ """Extrait un prix de vente d'un libellé source.
	84	+
	85	+ Gère « 459 000 $ », « $459,000 », « 1 249 000$ +tx », « À partir de 399 900 $ ».
	86	+ Retourne None si aucun montant plausible (>= 10 000 $) n'est trouvé.
	87	+ """
	88	+ if not label:
	89	+ return None
	90	+ m = _PRICE_RE.search(label.replace(" ", " ").replace(" ", " "))
	91	+ if not m:
	92	+ return None
	93	+ raw = m.group(1).strip()
	94	+ # « 459 000 » / « 459,000 » / « 459000.00 » — retirer les séparateurs de milliers
	95	+ raw = raw.replace(" ", "")
	96	+ if "," in raw and "." in raw:
	97	+ raw = raw.replace(",", "") # 459,000.00
	98	+ elif raw.count(",") == 1 and len(raw.split(",")[1]) == 2:
	99	+ raw = raw.replace(",", ".") # 459000,00 (décimale FR)
	100	+ else:
	101	+ raw = raw.replace(",", "")
	102	+ try:
	103	+ value = float(raw)
	104	+ except ValueError:
	105	+ return None
	106	+ return value if value >= 10_000 else None
	107	+
	108	+
	109	+def price_is_from(label: str) -> bool:
	110	+ key = strip_accents((label or "").lower())
	111	+ return any(k in key for k in ("a partir", "starting", "from", "des "))
	112	+
	113	+
	114	+# ---------------------------------------------------------------------------
	115	+# Nombres génériques
	116	+# ---------------------------------------------------------------------------
	117	+
	118	+def parse_int(text) -> int \| None:
	119	+ if text is None:
	120	+ return None
	121	+ if isinstance(text, (int, float)):
	122	+ return int(text)
	123	+ m = re.search(r"\d+", str(text))
	124	+ return int(m.group()) if m else None
	125	+
	126	+
	127	+def parse_float(text) -> float \| None:
	128	+ if text is None:
	129	+ return None
	130	+ if isinstance(text, (int, float)):
	131	+ return float(text)
	132	+ m = re.search(r"\d[\d\s]*(?:[.,]\d+)?", str(text))
	133	+ if not m:
	134	+ return None
	135	+ try:
	136	+ return float(m.group().replace(" ", "").replace(",", "."))
	137	+ except ValueError:
	138	+ return None
	139	+
	140	+
	141	+_SQFT_RE = re.compile(r"([\d\s ,.]+)\s(pi2\|pi²\|pc\|sq\.?\s?ft\|ft2\|ft²)",
	142	+ re.IGNORECASE)
	143	+_SQM_RE = re.compile(r"([\d\s ,.]+)\s*(m2\|m²\|mc)", re.IGNORECASE)
	144	+
	145	+
	146	+def parse_area_sqft(text: str) -> float \| None:
	147	+ """Superficie habitable en pi² (convertit les m² au besoin)."""
	148	+ if not text:
	149	+ return None
	150	+ t = text.replace(" ", " ")
	151	+ m = _SQFT_RE.search(t)
	152	+ if m:
	153	+ v = parse_float(m.group(1))
	154	+ return round(v) if v and v > 50 else None
	155	+ m = _SQM_RE.search(t)
	156	+ if m:
	157	+ v = parse_float(m.group(1))
	158	+ return round(v * 10.7639) if v and v > 5 else None
	159	+ return None
	160	+
	161	+
	162	+def parse_lot_sqft(text: str) -> float \| None:
	163	+ """Superficie de terrain en pi² — mêmes unités que parse_area_sqft."""
	164	+ return parse_area_sqft(text)
	165	+
	166	+
	167	+# « 1959 », « 2018 (Neuf) », « 1975, rénové »… mais JAMAIS « 20' X 34' irr. »
	168	+# ni « À construire » : la valeur doit COMMENCER par une année plausible.
	169	+_YEAR_RE = re.compile(r"^\s(1[6-9]\d{2}\|20[0-4]\d)\s(?:$\|[(,])")
	170	+
	171	+
	172	+def parse_year(text) -> int \| None:
	173	+ """Année de construction plausible (1600-2049) depuis une valeur `details`.
	174	+
	175	+ Volontairement strict (année en tête de valeur, seule ou suivie d'une
	176	+ parenthèse/virgule) pour ne jamais promouvoir un libellé parasite vers la
	177	+ colonne year_built."""
	178	+ if text is None:
	179	+ return None
	180	+ if isinstance(text, (int, float)):
	181	+ y = int(text)
	182	+ return y if 1600 <= y <= 2049 else None
	183	+ m = _YEAR_RE.match(str(text))
	184	+ return int(m.group(1)) if m else None
	185	+
	186	+
	187	+# ---------------------------------------------------------------------------
	188	+# Type de propriété
	189	+# ---------------------------------------------------------------------------
	190	+
	191	+# House-Ka canonical vocabulary (frontend filters) — ENGLISH.
	192	+# Sources are CREA DDF sites (English labels), plus the odd French label.
	193	+_TYPE_MAP = [
	194	+ # (keywords in the normalized source text, canonical type)
	195	+ (("maison mobile", "unimodulaire", "mobile home", "manufactured home",
	196	+ "modular",), "Mobile home"),
	197	+ (("jumele", "semi-detache", "semi detache", "semi-detached", "semi detached",),
	198	+ "Semi-detached"),
	199	+ (("maison de ville", "townhouse", "town house", "en rangee", "row house",
	200	+ "row / town",), "Townhouse"),
	201	+ (("condo", "copropriete", "appartement", "apartment", "loft", "penthouse",
	202	+ "studio", "strata",), "Condo"),
	203	+ (("duplex",), "Duplex"),
	204	+ (("triplex",), "Triplex"),
	205	+ (("quadruplex", "quintuplex", "multiplex", "multilogement", "multi-logement",
	206	+ "immeuble a revenus", "revenus", "multi-family", "multi family",
	207	+ "multifamily", "fourplex",), "Multi-family"),
	208	+ (("chalet", "cottage 4 saisons", "acces au plan d'eau", "bord de l'eau",
	209	+ "recreational", "cabin",), "Cottage"),
	210	+ (("terre", "terrain", "lot ", "vacant land", "land",), "Land"),
	211	+ (("ferme", "fermette", "agricole", "agriculture", "hobby farm", "farm",
	212	+ "acreage",), "Farm"),
	213	+ (("plain-pied", "bungalow",), "House"),
	214	+ (("maison a etages", "a etage", "deux etages", "cottage",), "House"),
	215	+ (("unifamiliale", "maison", "house", "residence", "split", "detached",
	216	+ "single family", "single-family",), "House"),
	217	+ # enriched-sheet vocabulary: « 4 logements », « propriété à revenu »
	218	+ (("logements", "logement/", "unites et +", "revenu",), "Multi-family"),
	219	+ (("bi generation", "bi-generation", "bigeneration", "intergeneration",),
	220	+ "House"),
	221	+ (("domaine et villa", "villa", "domaine",), "House"),
	222	+ (("parking",), "Parking"),
	223	+ (("commercial", "commerce", "industriel", "industrie", "bureau", "local",
	224	+ "entreprise", "batisse", "restaurant", "depanneur", "hotel", "motel",
	225	+ "garage/", "concessionnaire", "coiffure", "esthetique", "camping",
	226	+ "retail", "office", "industrial", "warehouse", "business",
	227	+ "institutional",), "Commercial"),
	228	+]
	229	+
	230	+
	231	+def normalize_property_type(text: str) -> str:
	232	+ import html as _html
	233	+ key = strip_accents(_html.unescape(text or "").strip().lower())
	234	+ if not key:
	235	+ return ""
	236	+ for keywords, canon in _TYPE_MAP:
	237	+ if any(k in key for k in keywords):
	238	+ return canon
	239	+ return _html.unescape(text).strip().capitalize()
	240	+
	241	+
	242	+# ---------------------------------------------------------------------------
	243	+# Chambres / salles de bains depuis du texte libre
	244	+# ---------------------------------------------------------------------------
	245	+
	246	+_BED_RE = re.compile(r"(\d+)\s*(?:ch(?:ambre)?s?\|cac\|bed(?:room)?s?)\b",
	247	+ re.IGNORECASE)
	248	+_BATH_RE = re.compile(r"(\d+)\s*(?:sdb\|salle?s?\s+de\s+bains?\|bath(?:room)?s?)",
	249	+ re.IGNORECASE)
	250	+
	251	+
	252	+def extract_bedrooms_bathrooms(text: str) -> tuple[int \| None, int \| None]:
	253	+ if not text:
	254	+ return None, None
	255	+ beds = _BED_RE.search(text)
	256	+ baths = _BATH_RE.search(text)
	257	+ return (int(beds.group(1)) if beds else None,
	258	+ int(baths.group(1)) if baths else None)

added immoka/poi.py +248 −0

		`@@ -0,0 +1,248 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# poi.py : commodités de proximité par immeuble via Overpass (OpenStreetMap)
	5	+# Pour chaque immeuble géolocalisé, une requête Overpass unique récupère
	6	+# les points d'intérêt utiles à un locataire (épicerie, pharmacie, école,
	7	+# garderie, parc, arrêt de bus, gym, clinique…) ; on retient le PLUS PROCHE
	8	+# de chaque catégorie avec sa distance. Cache permanent par coordonnées
	9	+# (table poi_cache, clé arrondie à 4 décimales ≈ 11 m : les unités d'un
	10	+# même immeuble partagent la même entrée). Politesse : 1 requête/seconde.
	11	+# -----------------------------------------------------------------------------
	12	+from __future__ import annotations
	13	+
	14	+import json
	15	+import math
	16	+import time
	17	+
	18	+import requests
	19	+
	20	+from . import db
	21	+
	22	+# Miroirs Overpass (rotation en cas d'erreur/limitation) — kumi.systems
	23	+# tolère mieux les gros volumes que l'instance officielle
	24	+OVERPASS_URLS = [
	25	+ "https://overpass.kumi.systems/api/interpreter",
	26	+ "https://overpass-api.de/api/interpreter",
	27	+]
	28	+USER_AGENT = "ImmoKaBot/1.0 (agregateur logements Quebec; +contact@spboucher.ai)"
	29	+REQUEST_DELAY = 2.0
	30	+REFRESH_AFTER = 90 * 86400 # les POI bougent peu : rafraîchir aux ~3 mois
	31	+
	32	+# Stratégie « par tuiles » : plutôt qu'une requête par immeuble (l'union
	33	+# d'around() est très coûteuse côté Overpass), on télécharge TOUS les POI
	34	+# des catégories par tuile de 0,5° couvrant nos immeubles (~10 tuiles pour
	35	+# Québec/Lévis + Grand Montréal), puis on calcule les plus proches en local.
	36	+TILE = 0.5
	37	+TILE_MARGIN = 0.04 # ~4 km > plus grand rayon de catégorie (3 km)
	38	+
	39	+# Catégories : (clé, libellé FR, sélecteur Overpass, rayon m)
	40	+CATEGORIES: list[tuple[str, str, str, int]] = [
	41	+ ("epicerie", "Épicerie", '["shop"="supermarket"]', 1500),
	42	+ ("depanneur", "Dépanneur", '["shop"="convenience"]', 800),
	43	+ ("pharmacie", "Pharmacie", '["amenity"="pharmacy"]', 1500),
	44	+ ("ecole", "École", '["amenity"="school"]', 1500),
	45	+ ("garderie", "Garderie", '["amenity"~"^(kindergarten\|childcare)$"]', 1500),
	46	+ ("parc", "Parc", '["leisure"="park"]', 1200),
	47	+ ("bus", "Arrêt de bus", '["highway"="bus_stop"]', 600),
	48	+ ("metro", "Métro", '["railway"="station"]["station"="subway"]', 1500),
	49	+ ("gym", "Gym", '["leisure"="fitness_centre"]', 1500),
	50	+ ("cafe", "Café", '["amenity"="cafe"]', 1000),
	51	+ ("clinique", "Clinique / CLSC", '["amenity"~"^(clinic\|doctors)$"]', 2000),
	52	+ ("hopital", "Hôpital", '["amenity"="hospital"]', 3000),
	53	+ ("bibliotheque", "Bibliothèque", '["amenity"="library"]', 2000),
	54	+]
	55	+
	56	+LABELS = {cat: label for cat, label, _, _ in CATEGORIES}
	57	+
	58	+
	59	+def coord_key(lat: float, lng: float) -> str:
	60	+ return f"{round(lat, 4)},{round(lng, 4)}"
	61	+
	62	+
	63	+def _haversine_m(lat1: float, lng1: float, lat2: float, lng2: float) -> float:
	64	+ r = 6371000.0
	65	+ p1, p2 = math.radians(lat1), math.radians(lat2)
	66	+ dp, dl = math.radians(lat2 - lat1), math.radians(lng2 - lng1)
	67	+ a = math.sin(dp / 2) ** 2 + math.cos(p1) * math.cos(p2) * math.sin(dl / 2) ** 2
	68	+ return 2 * r * math.asin(math.sqrt(a))
	69	+
	70	+
	71	+def _tile_of(lat: float, lng: float) -> tuple[int, int]:
	72	+ return (math.floor(lat / TILE), math.floor(lng / TILE))
	73	+
	74	+
	75	+def _build_tile_query(ty: int, tx: int) -> str:
	76	+ """Tous les POI des catégories dans la tuile (bbox élargie de la marge)."""
	77	+ s = ty * TILE - TILE_MARGIN
	78	+ n = (ty + 1) * TILE + TILE_MARGIN
	79	+ w = tx * TILE - TILE_MARGIN
	80	+ e = (tx + 1) * TILE + TILE_MARGIN
	81	+ bbox = f"{s:.4f},{w:.4f},{n:.4f},{e:.4f}"
	82	+ parts = [f"nwr{sel}({bbox});" for _c, _l, sel, _r in CATEGORIES]
	83	+ return f'[out:json][timeout:180];({"".join(parts)});out center tags;'
	84	+
	85	+
	86	+def _match_category(tags: dict) -> str \| None:
	87	+ """Retrouve la catégorie Lou-Ka d'un élément OSM retourné."""
	88	+ shop = tags.get("shop")
	89	+ amenity = tags.get("amenity")
	90	+ leisure = tags.get("leisure")
	91	+ if shop == "supermarket":
	92	+ return "epicerie"
	93	+ if shop == "convenience":
	94	+ return "depanneur"
	95	+ if amenity == "pharmacy":
	96	+ return "pharmacie"
	97	+ if amenity == "school":
	98	+ return "ecole"
	99	+ if amenity in ("kindergarten", "childcare"):
	100	+ return "garderie"
	101	+ if leisure == "park":
	102	+ return "parc"
	103	+ if tags.get("highway") == "bus_stop":
	104	+ return "bus"
	105	+ if tags.get("railway") == "station" and tags.get("station") == "subway":
	106	+ return "metro"
	107	+ if leisure == "fitness_centre":
	108	+ return "gym"
	109	+ if amenity == "cafe":
	110	+ return "cafe"
	111	+ if amenity in ("clinic", "doctors"):
	112	+ return "clinique"
	113	+ if amenity == "hospital":
	114	+ return "hopital"
	115	+ if amenity == "library":
	116	+ return "bibliotheque"
	117	+ return None
	118	+
	119	+
	120	+_RADII = {cat: radius for cat, _l, _s, radius in CATEGORIES}
	121	+
	122	+
	123	+class PoiClient:
	124	+ def __init__(self) -> None:
	125	+ self.session = requests.Session()
	126	+ self.session.headers["User-Agent"] = USER_AGENT
	127	+ self._last = 0.0
	128	+ self._url_idx = 0
	129	+
	130	+ def _post(self, query: str) -> list \| None:
	131	+ """POST Overpass avec throttling et rotation de miroir sur erreur."""
	132	+ wait = REQUEST_DELAY - (time.time() - self._last)
	133	+ if wait > 0:
	134	+ time.sleep(wait)
	135	+ for essai in range(len(OVERPASS_URLS)):
	136	+ url = OVERPASS_URLS[(self._url_idx + essai) % len(OVERPASS_URLS)]
	137	+ try:
	138	+ resp = self.session.post(url, data={"data": query}, timeout=90)
	139	+ self._last = time.time()
	140	+ resp.raise_for_status()
	141	+ self._url_idx = (self._url_idx + essai) % len(OVERPASS_URLS)
	142	+ return resp.json().get("elements") or []
	143	+ except Exception:
	144	+ self._last = time.time()
	145	+ continue
	146	+ return None
	147	+
	148	+ def fetch_tile(self, ty: int, tx: int) -> list[dict] \| None:
	149	+ """Tous les POI catégorisés d'une tuile : [{cat, name, lat, lng}]."""
	150	+ elements = self._post(_build_tile_query(ty, tx))
	151	+ if elements is None:
	152	+ return None
	153	+ pois = []
	154	+ for el in elements:
	155	+ tags = el.get("tags") or {}
	156	+ cat = _match_category(tags)
	157	+ if cat is None:
	158	+ continue
	159	+ elat = el.get("lat") or (el.get("center") or {}).get("lat")
	160	+ elng = el.get("lon") or (el.get("center") or {}).get("lon")
	161	+ if elat is None or elng is None:
	162	+ continue
	163	+ pois.append({"cat": cat, "name": (tags.get("name") or LABELS[cat])[:60],
	164	+ "lat": elat, "lng": elng})
	165	+ return pois
	166	+
	167	+
	168	+def _nearest_by_cat(lat: float, lng: float, pois_by_cat: dict[str, list[dict]]) -> list[dict]:
	169	+ """Plus proche POI de chaque catégorie (dans son rayon), trié par distance."""
	170	+ out = []
	171	+ for cat, pois in pois_by_cat.items():
	172	+ radius = _RADII[cat]
	173	+ # préfiltre rectangulaire bon marché avant l'haversine
	174	+ dlat_max = radius / 111000.0
	175	+ dlng_max = radius / (111000.0 * max(0.2, math.cos(math.radians(lat))))
	176	+ best = None
	177	+ for p in pois:
	178	+ if abs(p["lat"] - lat) > dlat_max or abs(p["lng"] - lng) > dlng_max:
	179	+ continue
	180	+ d = _haversine_m(lat, lng, p["lat"], p["lng"])
	181	+ if d <= radius and (best is None or d < best["dist_m"]):
	182	+ best = {"cat": cat, "name": p["name"], "dist_m": round(d)}
	183	+ if best:
	184	+ out.append(best)
	185	+ return sorted(out, key=lambda p: p["dist_m"])
	186	+
	187	+
	188	+def run(limit: int \| None = None) -> dict:
	189	+ """Remplit poi_cache pour les immeubles géolocalisés qui n'y sont pas.
	190	+
	191	+ `limit` borne le nombre de requêtes Overpass de cette exécution
	192	+ (les entrées déjà en cache ne coûtent rien).
	193	+ """
	194	+ con = db.connect()
	195	+ client = PoiClient()
	196	+ rows = con.execute(
	197	+ """SELECT DISTINCT ROUND(lat,4) la, ROUND(lng,4) ln FROM listings
	198	+ WHERE active=1 AND lat IS NOT NULL AND lng IS NOT NULL""").fetchall()
	199	+
	200	+ now = time.time()
	201	+ a_faire: list[tuple[float, float]] = []
	202	+ skipped = 0
	203	+ for r in rows:
	204	+ cached = con.execute(
	205	+ "SELECT ts FROM poi_cache WHERE coord_key=?",
	206	+ (f"{r['la']},{r['ln']}",)).fetchone()
	207	+ if cached and now - (cached["ts"] or 0) < REFRESH_AFTER:
	208	+ skipped += 1
	209	+ else:
	210	+ a_faire.append((r["la"], r["ln"]))
	211	+ if limit is not None:
	212	+ a_faire = a_faire[:limit]
	213	+
	214	+ # 1) télécharger les POI des tuiles nécessaires (une requête par tuile)
	215	+ tuiles = sorted({_tile_of(la, ln) for la, ln in a_faire})
	216	+ pois_by_tile: dict[tuple[int, int], dict[str, list[dict]]] = {}
	217	+ tile_errors = []
	218	+ for t in tuiles:
	219	+ res = client.fetch_tile(*t)
	220	+ if res is None:
	221	+ tile_errors.append(t)
	222	+ else:
	223	+ by_cat: dict[str, list[dict]] = {}
	224	+ for p in res:
	225	+ by_cat.setdefault(p["cat"], []).append(p)
	226	+ pois_by_tile[t] = by_cat
	227	+
	228	+ # 2) calcul local du plus proche par catégorie pour chaque immeuble
	229	+ done = errors = 0
	230	+ for la, ln in a_faire:
	231	+ t = _tile_of(la, ln)
	232	+ if t not in pois_by_tile:
	233	+ errors += 1 # tuile en échec : re-tentée au prochain run
	234	+ continue
	235	+ pois = _nearest_by_cat(la, ln, pois_by_tile[t])
	236	+ con.execute(
	237	+ "INSERT INTO poi_cache (coord_key, lat, lng, pois, ts) VALUES (?,?,?,?,?)"
	238	+ " ON CONFLICT(coord_key) DO UPDATE SET pois=excluded.pois, ts=excluded.ts",
	239	+ (coord_key(la, ln), la, ln, json.dumps(pois, ensure_ascii=False), now))
	240	+ done += 1
	241	+ con.commit()
	242	+
	243	+ con.close()
	244	+ stats = {"fetched": done, "cached": skipped, "errors": errors,
	245	+ "tiles": len(tuiles), "tile_errors": len(tile_errors),
	246	+ "total_coords": len(rows)}
	247	+ print(f"[immo-ka] poi {stats}")
	248	+ return stats

added immoka/quality.py +254 −0

		`@@ -0,0 +1,254 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# quality.py : contrôle qualité des annonces — score de complétude, contrôles de
	5	+# cohérence immobiliers, seuil de publication (quarantaine sous le seuil).
	6	+#
	7	+# `refresh(con)` recalcule pour toutes les annonces actives :
	8	+# - quality_score : complétude 0-100 (pondération des champs décisifs)
	9	+# - quality_issues : JSON (anomalies détectées, dures ou informatives)
	10	+# - published : 1 = affichable sur le site, 0 = quarantaine
	11	+# et les champs dérivés dans details : prix_pi2 (prix/superficie) et
	12	+# transaction (vente \| location, détectée du libellé de prix).
	13	+#
	14	+# Règle de publication : prix plausible + ville + type de bien + au moins une
	15	+# image + contenu exploitable (description ou caractéristiques). Une annonce
	16	+# sous le seuil reste en base (re-synchronisée/enrichie aux prochains cycles)
	17	+# mais n'est pas affichée — elle sort de quarantaine dès qu'elle est complétée.
	18	+# -----------------------------------------------------------------------------
	19	+from __future__ import annotations
	20	+
	21	+import json
	22	+import os
	23	+import re
	24	+import sqlite3
	25	+import time
	26	+
	27	+from .normalize import strip_accents
	28	+
	29	+# bornes de plausibilité (marché québécois)
	30	+PRICE_SALE_MIN, PRICE_SALE_MAX = 20_000, 80_000_000
	31	+PRICE_RENT_MIN, PRICE_RENT_MAX = 300, 25_000
	32	+AREA_MIN, AREA_MAX = 120, 25_000 # superficie habitable (pi²)
	33	+LOT_MAX = 200_000_000 # terrain (pi²) — grandes terres
	34	+YEAR_MIN = 1600
	35	+
	36	+_RENT_RE = re.compile(r"/\smois\|par mois\|/\smth\|/\s*month\|\bmensuel\|\ba louer\b\|"
	37	+ r"\blouer\b\|\blocation\b\|\blease\b\|\bfor rent\b")
	38	+
	39	+
	40	+def _transaction(price, price_label: str, title: str) -> str:
	41	+ """vente \| location — détectée du libellé (jamais confondre loyer et prix)."""
	42	+ key = strip_accents(f"{price_label} {title}".lower())
	43	+ if _RENT_RE.search(key):
	44	+ return "location"
	45	+ if price is not None and price < PRICE_RENT_MAX:
	46	+ # montant de loyer sans mot-clé : trop bas pour une vente au Québec
	47	+ return "location"
	48	+ return "vente"
	49	+
	50	+
	51	+def assess(row: dict) -> tuple[int, list[str], int, dict]:
	52	+ """(score 0-100, anomalies, publiable 0/1, champs dérivés) pour une annonce.
	53	+
	54	+ `row` : dict aux clés des colonnes listings (features/details/images
	55	+ peuvent être des chaînes JSON ou déjà décodés)."""
	56	+
	57	+ def _json(v, default):
	58	+ if isinstance(v, (list, dict)):
	59	+ return v
	60	+ try:
	61	+ return json.loads(v) if v else default
	62	+ except (TypeError, ValueError):
	63	+ return default
	64	+
	65	+ images = _json(row.get("images"), [])
	66	+ features = _json(row.get("features"), [])
	67	+ details = _json(row.get("details"), {})
	68	+ desc = (row.get("description") or "").strip()
	69	+ price = row.get("price")
	70	+ issues: list[str] = []
	71	+ derived: dict = {}
	72	+
	73	+ tx = _transaction(price, row.get("price_label") or "", row.get("title") or "")
	74	+ derived["transaction"] = tx
	75	+
	76	+ # -- cohérence : prix plausible pour le type de transaction ----------------
	77	+ price_ok = price is not None and price > 0
	78	+ if price_ok:
	79	+ lo, hi = ((PRICE_RENT_MIN, PRICE_RENT_MAX) if tx == "location"
	80	+ else (PRICE_SALE_MIN, PRICE_SALE_MAX))
	81	+ if not (lo <= price <= hi):
	82	+ issues.append(f"prix_hors_bornes:{price:.0f}$ ({tx})")
	83	+ price_ok = False
	84	+
	85	+ # -- cohérence : superficies plausibles -------------------------------------
	86	+ area = row.get("area_sqft")
	87	+ area_ok = area is not None and AREA_MIN <= area <= AREA_MAX
	88	+ if area is not None and not area_ok:
	89	+ issues.append(f"superficie_improbable:{area:.0f}pi2")
	90	+ lot = row.get("lot_sqft")
	91	+ if lot is not None and not (0 < lot <= LOT_MAX):
	92	+ issues.append(f"terrain_improbable:{lot:.0f}pi2")
	93	+
	94	+ # -- cohérence : pièces / chambres ------------------------------------------
	95	+ beds, baths = row.get("bedrooms"), row.get("bathrooms")
	96	+ if beds is not None and not (0 <= beds <= 30):
	97	+ issues.append(f"chambres_improbables:{beds}")
	98	+ beds = None
	99	+ if baths is not None and not (0 <= baths <= 20):
	100	+ issues.append(f"sdb_improbables:{baths}")
	101	+ baths = None
	102	+ ptype = (row.get("property_type") or "").strip()
	103	+ if beds and ptype == "Condo" and beds > 8:
	104	+ issues.append(f"chambres_vs_type:{beds}ch_condo")
	105	+
	106	+ # -- cohérence : année de construction ---------------------------------------
	107	+ year = row.get("year_built")
	108	+ current_year = time.gmtime().tm_year
	109	+ if year is not None and not (YEAR_MIN <= year <= current_year + 3):
	110	+ issues.append(f"annee_invalide:{year}")
	111	+
	112	+ # -- champ dérivé : prix au pi² (et m²) ---------------------------------------
	113	+ if price_ok and area_ok and tx == "vente":
	114	+ ppsf = price / area
	115	+ derived["prix_pi2"] = round(ppsf)
	116	+ derived["prix_m2"] = round(ppsf * 10.7639)
	117	+ if not (30 <= ppsf <= 3500):
	118	+ issues.append(f"prix_pi2_extreme:{ppsf:.0f}")
	119	+
	120	+ # -- score de complétude (0-100) ----------------------------------------------
	121	+ n_img = len(images)
	122	+ has_contact = bool(row.get("broker_name") or row.get("broker_phone"))
	123	+ score = 0
	124	+ score += 15 if price_ok else 0
	125	+ score += 8 if (row.get("city") or "").strip() else 0
	126	+ score += 7 if (row.get("address") or "").strip() else 0
	127	+ score += 8 if ptype else 0
	128	+ score += 10 if n_img >= 1 else 0
	129	+ score += 5 if n_img >= 8 else 0
	130	+ score += 12 if len(desc) >= 300 else 8 if len(desc) >= 80 else 4 if desc else 0
	131	+ score += 6 if beds is not None else 0
	132	+ score += 5 if baths is not None else 0
	133	+ score += 8 if area_ok else 0
	134	+ score += 4 if year is not None else 0
	135	+ score += 7 if row.get("lat") is not None else 0
	136	+ score += 3 if has_contact else 0
	137	+ score += 2 if lot is not None else 0
	138	+
	139	+ # -- seuil de publication ---------------------------------------------------
	140	+ # (une annonce SANS image reste publiable : le frontend applique l'image de
	141	+ # secours par type de bien ; le drapeau sans_image la marque à re-vérifier)
	142	+ if n_img < 1:
	143	+ issues.append("sans_image")
	144	+ # vendue/louée à la source : archivée (plus jamais affichée en résultats)
	145	+ statut = (row.get("status") or "").strip().lower()
	146	+ vendue = statut in ("vendu", "vendue", "loue", "louee", "loué", "louée",
	147	+ "sold", "rented", "retire", "retiré")
	148	+ if vendue:
	149	+ issues.append(f"statut:{statut}")
	150	+ # House-Ka : les cartes DDF (liste) n'ont ni description ni type — la
	151	+ # fiche s'enrichit au fil des passes de détail. Publication dès que le
	152	+ # prix est plausible et la ville connue ; type/description comptent dans
	153	+ # le score seulement.
	154	+ publishable = (
	155	+ not vendue
	156	+ and price_ok
	157	+ and bool((row.get("city") or "").strip())
	158	+ )
	159	+ if not publishable:
	160	+ why = []
	161	+ if not price_ok:
	162	+ why.append("prix")
	163	+ if not (row.get("city") or "").strip():
	164	+ why.append("ville")
	165	+ issues.append("quarantaine:" + "+".join(why))
	166	+
	167	+ return score, issues, int(publishable), derived
	168	+
	169	+
	170	+def refresh(con: sqlite3.Connection, sources: list[str] \| None = None) -> dict:
	171	+ """Recalcule score/anomalies/publication pour les annonces actives.
	172	+
	173	+ Appelé après chaque synchronisation (ingest.run) — quelques secondes pour
	174	+ ~80 k lignes. Retourne un résumé {actives, publiees, quarantaine}."""
	175	+ _ensure_columns(con)
	176	+ sql = ("SELECT uid, source, title, price, price_label, city, address,"
	177	+ " property_type,"
	178	+ " bedrooms, bathrooms, area_sqft, lot_sqft, year_built, lat, status,"
	179	+ " broker_name, broker_phone, description, features, details, images,"
	180	+ " quality_score, quality_issues, published"
	181	+ " FROM listings WHERE active=1")
	182	+ args: list = []
	183	+ if sources:
	184	+ sql += f" AND source IN ({','.join('?' * len(sources))})"
	185	+ args = list(sources)
	186	+ updates = []
	187	+ n = pub = 0
	188	+ for r in con.execute(sql, args):
	189	+ row = dict(r)
	190	+ score, issues, publishable, derived = assess(row)
	191	+ n += 1
	192	+ pub += publishable
	193	+ details = {}
	194	+ try:
	195	+ details = json.loads(row.get("details") or "{}")
	196	+ except ValueError:
	197	+ pass
	198	+ changed_details = any(details.get(k) != v for k, v in derived.items())
	199	+ issues_json = json.dumps(issues, ensure_ascii=False) if issues else None
	200	+ if (score != row.get("quality_score") or publishable != row.get("published")
	201	+ or issues_json != row.get("quality_issues") or changed_details):
	202	+ details.update(derived)
	203	+ updates.append((score, issues_json, publishable,
	204	+ json.dumps(details, ensure_ascii=False), row["uid"]))
	205	+ if updates:
	206	+ con.executemany(
	207	+ "UPDATE listings SET quality_score=?, quality_issues=?, published=?,"
	208	+ " details=? WHERE uid=?", updates)
	209	+ con.commit()
	210	+ return {"actives": n, "publiees": pub, "quarantaine": n - pub,
	211	+ "recalculees": len(updates)}
	212	+
	213	+
	214	+def _ensure_columns(con: sqlite3.Connection) -> None:
	215	+ cols = {r["name"] for r in con.execute("PRAGMA table_info(listings)")}
	216	+ if "quality_score" not in cols:
	217	+ con.execute("ALTER TABLE listings ADD COLUMN quality_score INTEGER")
	218	+ if "quality_issues" not in cols:
	219	+ con.execute("ALTER TABLE listings ADD COLUMN quality_issues TEXT")
	220	+ if "published" not in cols:
	221	+ # 1 par défaut : la 1re passe refresh() met la vraie valeur partout
	222	+ con.execute("ALTER TABLE listings ADD COLUMN published INTEGER DEFAULT 1")
	223	+ con.execute("CREATE INDEX IF NOT EXISTS idx_listings_published"
	224	+ " ON listings(published)")
	225	+ con.commit()
	226	+
	227	+
	228	+def summary(con: sqlite3.Connection) -> dict:
	229	+ """Statistiques qualité pour /api/stats : complétude, quarantaine, anomalies."""
	230	+ _ensure_columns(con)
	231	+ row = con.execute(
	232	+ "SELECT COUNT(*) actives, SUM(published) publiees,"
	233	+ " ROUND(AVG(quality_score),1) completude_moyenne"
	234	+ " FROM listings WHERE active=1 AND dup_hidden=0").fetchone()
	235	+ per_source = [dict(r) for r in con.execute(
	236	+ "SELECT source, COUNT(*) n, SUM(published) publiees,"
	237	+ " ROUND(AVG(quality_score),1) completude,"
	238	+ " SUM(CASE WHEN quality_issues IS NOT NULL THEN 1 ELSE 0 END) anomalies"
	239	+ " FROM listings WHERE active=1 AND dup_hidden=0"
	240	+ " GROUP BY source ORDER BY n DESC")]
	241	+ anomalies: dict[str, int] = {}
	242	+ for r in con.execute(
	243	+ "SELECT quality_issues FROM listings WHERE active=1 AND dup_hidden=0"
	244	+ " AND quality_issues IS NOT NULL"):
	245	+ try:
	246	+ for issue in json.loads(r["quality_issues"]):
	247	+ anomalies[issue.split(":")[0]] = anomalies.get(issue.split(":")[0], 0) + 1
	248	+ except ValueError:
	249	+ continue
	250	+ d = dict(row)
	251	+ d["quarantaine"] = (d.get("actives") or 0) - (d.get("publiees") or 0)
	252	+ d["anomalies"] = dict(sorted(anomalies.items(), key=lambda kv: -kv[1]))
	253	+ d["par_source"] = per_source
	254	+ return d

added immoka/quartier.py +229 −0

		`@@ -0,0 +1,229 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# quartier.py : statistiques de quartier par annonce (à la Centris, en libre)
	5	+# Base statique data/quartier.db construite par scripts/build_*.py :
	6	+# - da_poly / da_stats : aires de diffusion 2021 + profil du recensement
	7	+# - da_pmd : mesures de proximité StatCan (scores 0..1)
	8	+# - da_defav : défavorisation matérielle/sociale INSPQ (quintiles)
	9	+# - heat : classe d'îlot de chaleur/fraîcheur INSPQ par immeuble
	10	+# - crime_mtl / igc : actes criminels SPVM (points) + indice de gravité
	11	+# Jointure : lat/lng -> DAUID par point-dans-polygone local (préfiltre bbox),
	12	+# mémorisée dans listings.dauid à l'enrichissement (boucle watch).
	13	+# -----------------------------------------------------------------------------
	14	+from __future__ import annotations
	15	+
	16	+import json
	17	+import math
	18	+import sqlite3
	19	+import time
	20	+from pathlib import Path
	21	+
	22	+from . import db
	23	+
	24	+QUARTIER_DB = Path(__file__).resolve().parent.parent / "data" / "quartier.db"
	25	+
	26	+# villes couvertes par les points SPVM (agglomération de Montréal)
	27	+_VILLES_SPVM = {"montreal", "montreal-est", "montreal-ouest", "westmount",
	28	+ "cote saint-luc", "cote-saint-luc", "hampstead", "mont-royal",
	29	+ "outremont", "verdun", "lasalle", "lachine", "anjou",
	30	+ "saint-leonard", "saint-laurent", "ahuntsic", "dorval",
	31	+ "pointe-claire", "kirkland", "beaconsfield", "dollard-des-ormeaux"}
	32	+
	33	+# correspondance ville -> fragment du nom de service dans la table igc
	34	+_IGC_SERVICE = {
	35	+ "quebec": "SPVQ", "levis": "Lévis", "montreal": "SPVM",
	36	+ "laval": "Laval", "longueuil": "Longueuil",
	37	+}
	38	+
	39	+
	40	+def disponible() -> bool:
	41	+ return QUARTIER_DB.exists()
	42	+
	43	+
	44	+def _connect() -> sqlite3.Connection:
	45	+ con = sqlite3.connect(f"file:{QUARTIER_DB}?mode=ro", uri=True)
	46	+ con.row_factory = sqlite3.Row
	47	+ return con
	48	+
	49	+
	50	+# ---------------------------------------------------------------------------
	51	+# lat/lng -> DAUID (point dans polygone, préfiltre bbox)
	52	+# ---------------------------------------------------------------------------
	53	+
	54	+def _dans_anneau(lat: float, lng: float, anneau: list) -> bool:
	55	+ """Lancer de rayon (even-odd). anneau = [[lng, lat], ...]."""
	56	+ dedans = False
	57	+ n = len(anneau)
	58	+ j = n - 1
	59	+ for i in range(n):
	60	+ xi, yi = anneau[i][0], anneau[i][1]
	61	+ xj, yj = anneau[j][0], anneau[j][1]
	62	+ if (yi > lat) != (yj > lat) and \
	63	+ lng < (xj - xi) * (lat - yi) / (yj - yi + 1e-12) + xi:
	64	+ dedans = not dedans
	65	+ j = i
	66	+ return dedans
	67	+
	68	+
	69	+def dauid_for(qcon: sqlite3.Connection, lat: float, lng: float) -> str \| None:
	70	+ rows = qcon.execute(
	71	+ "SELECT dauid, poly FROM da_poly WHERE lat_min<=? AND lat_max>=?"
	72	+ " AND lng_min<=? AND lng_max>=?", (lat, lat, lng, lng)).fetchall()
	73	+ for r in rows:
	74	+ anneaux = json.loads(r["poly"])
	75	+ # even-odd sur tous les anneaux (les trous annulent)
	76	+ compte = sum(1 for a in anneaux if _dans_anneau(lat, lng, a))
	77	+ if compte % 2 == 1:
	78	+ return r["dauid"]
	79	+ return None
	80	+
	81	+
	82	+# ---------------------------------------------------------------------------
	83	+# Assemblage pour la fiche
	84	+# ---------------------------------------------------------------------------
	85	+
	86	+def _cle_ville(city: str) -> str:
	87	+ import unicodedata
	88	+ s = "".join(c for c in unicodedata.normalize("NFD", city or "")
	89	+ if unicodedata.category(c) != "Mn")
	90	+ return s.strip().lower()
	91	+
	92	+
	93	+def _crime_mtl(qcon: sqlite3.Connection, lat: float, lng: float) -> dict \| None:
	94	+ """Comptage des actes criminels SPVM à < 500 m : 12 mois vs 12 précédents."""
	95	+ dlat = 500 / 111000.0
	96	+ dlng = 500 / (111000.0 * max(0.2, math.cos(math.radians(lat))))
	97	+ now = time.time()
	98	+ rows = qcon.execute(
	99	+ "SELECT lat, lng, ts, categorie FROM crime_mtl WHERE lat BETWEEN ? AND ?"
	100	+ " AND lng BETWEEN ? AND ? AND ts >= ?",
	101	+ (lat - dlat, lat + dlat, lng - dlng, lng + dlng, now - 730 * 86400)).fetchall()
	102	+ recent = avant = 0
	103	+ cats: dict[str, list[int]] = {} # categorie -> [12 mois, 12 prec.]
	104	+ for r in rows:
	105	+ # distance exacte (le bbox est un carré)
	106	+ d = math.hypot((r["lat"] - lat) * 111000.0,
	107	+ (r["lng"] - lng) * 111000.0 * math.cos(math.radians(lat)))
	108	+ if d > 500:
	109	+ continue
	110	+ c = cats.setdefault(r["categorie"] or "Autre", [0, 0])
	111	+ if r["ts"] >= now - 365 * 86400:
	112	+ recent += 1
	113	+ c[0] += 1
	114	+ else:
	115	+ avant += 1
	116	+ c[1] += 1
	117	+ if recent == 0 and avant == 0:
	118	+ return None
	119	+ categories = [{"nom": k, "n": v[0], "n_prec": v[1]}
	120	+ for k, v in sorted(cats.items(),
	121	+ key=lambda kv: -(kv[1][0] + kv[1][1]))]
	122	+ return {"type": "points", "rayon_m": 500, "douze_mois": recent,
	123	+ "douze_mois_precedents": avant, "categories": categories}
	124	+
	125	+
	126	+def _crime_igc(qcon: sqlite3.Connection, city: str) -> dict \| None:
	127	+ service = _IGC_SERVICE.get(_cle_ville(city))
	128	+ if not service:
	129	+ return None
	130	+ row = qcon.execute(
	131	+ "SELECT annee, indice FROM igc WHERE service LIKE '%' \|\| ? \|\| '%'"
	132	+ " ORDER BY annee DESC LIMIT 1", (service,)).fetchone()
	133	+ if row is None or row["indice"] is None:
	134	+ return None
	135	+ ref = qcon.execute(
	136	+ "SELECT indice FROM igc WHERE service LIKE '%canada%' AND annee=?",
	137	+ (row["annee"],)).fetchone()
	138	+ return {"type": "igc", "ville": city, "annee": row["annee"],
	139	+ "indice": round(row["indice"], 1),
	140	+ "indice_canada": round(ref["indice"], 1) if ref and ref["indice"] else None}
	141	+
	142	+
	143	+def fiche_quartier(lat: float \| None, lng: float \| None, city: str,
	144	+ dauid: str \| None = None) -> dict \| None:
	145	+ """Bloc « Le quartier » d'une fiche. None si données indisponibles."""
	146	+ if not disponible() or lat is None or lng is None:
	147	+ return None
	148	+ qcon = _connect()
	149	+ try:
	150	+ if not dauid:
	151	+ dauid = dauid_for(qcon, lat, lng)
	152	+ out: dict = {"dauid": dauid}
	153	+
	154	+ if dauid:
	155	+ r = qcon.execute("SELECT * FROM da_stats WHERE dauid=?", (dauid,)).fetchone()
	156	+ if r:
	157	+ out["demographie"] = {k: r[k] for k in
	158	+ ("population", "densite", "age_median",
	159	+ "revenu_median", "pct_locataires",
	160	+ "loyer_moyen", "pct_francais", "pct_univ")}
	161	+ # rangs centiles québécois (0-100) — voir scripts/merge_quartier.py
	162	+ r = qcon.execute("SELECT * FROM da_pmd_pct WHERE dauid=?", (dauid,)).fetchone()
	163	+ if r:
	164	+ out["proximite"] = {k: r[k] / 100.0 for k in r.keys()
	165	+ if k != "dauid" and r[k] is not None}
	166	+ r = qcon.execute("SELECT quintile_materiel, quintile_social FROM da_defav"
	167	+ " WHERE dauid=?", (dauid,)).fetchone()
	168	+ if r:
	169	+ out["defavorisation"] = dict(r)
	170	+
	171	+ # îlot de chaleur : coordonnée exacte, sinon la plus proche (~120 m)
	172	+ key = f"{round(lat, 4)},{round(lng, 4)}"
	173	+ r = qcon.execute("SELECT classe, ecart FROM heat WHERE coord_key=?",
	174	+ (key,)).fetchone()
	175	+ if r is None:
	176	+ r = qcon.execute(
	177	+ "SELECT classe, ecart FROM heat WHERE coord_key LIKE ?"
	178	+ " AND classe IS NOT NULL LIMIT 1",
	179	+ (f"{round(lat, 3)}%",)).fetchone()
	180	+ if r and r["classe"] is not None:
	181	+ out["chaleur"] = {"classe": r["classe"], "ecart": r["ecart"]}
	182	+
	183	+ # criminalité : points SPVM sur l'île, indice IGC ailleurs
	184	+ crime = None
	185	+ if _cle_ville(city) in _VILLES_SPVM:
	186	+ crime = _crime_mtl(qcon, lat, lng)
	187	+ if crime is None:
	188	+ crime = _crime_igc(qcon, city)
	189	+ if crime:
	190	+ out["crime"] = crime
	191	+
	192	+ return out if len(out) > 1 else None
	193	+ except sqlite3.Error:
	194	+ return None
	195	+ finally:
	196	+ qcon.close()
	197	+
	198	+
	199	+# ---------------------------------------------------------------------------
	200	+# Enrichissement : mémoriser le DAUID de chaque annonce (boucle watch)
	201	+# ---------------------------------------------------------------------------
	202	+
	203	+def enrich(limit: int \| None = None) -> dict:
	204	+ """Remplit listings.dauid pour les annonces géolocalisées qui ne l'ont pas."""
	205	+ if not disponible():
	206	+ print("[immo-ka] quartier: data/quartier.db absent — étape sautée")
	207	+ return {"enriched": 0, "missing_db": True}
	208	+ con = db.connect()
	209	+ qcon = _connect()
	210	+ rows = con.execute(
	211	+ "SELECT uid, lat, lng FROM listings WHERE active=1 AND lat IS NOT NULL"
	212	+ " AND (dauid IS NULL OR dauid='')").fetchall()
	213	+ if limit is not None:
	214	+ rows = rows[:limit]
	215	+ done = introuvable = 0
	216	+ for r in rows:
	217	+ d = dauid_for(qcon, r["lat"], r["lng"])
	218	+ con.execute("UPDATE listings SET dauid=? WHERE uid=?",
	219	+ (d or "hors-zone", r["uid"]))
	220	+ if d:
	221	+ done += 1
	222	+ else:
	223	+ introuvable += 1
	224	+ con.commit()
	225	+ qcon.close()
	226	+ con.close()
	227	+ stats = {"enriched": done, "hors_zone": introuvable, "candidats": len(rows)}
	228	+ print(f"[immo-ka] quartier {stats}")
	229	+ return stats

added immoka/schema.py +153 −0

		`@@ -0,0 +1,153 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de maisons à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# schema.py : modèle de données standardisé (PropertyListing)
	5	+# -----------------------------------------------------------------------------
	6	+"""Schéma standard d'une propriété à vendre et normalisation des champs.
	7	+
	8	+Chaque connecteur, peu importe l'agence source (RE/MAX, Sutton, Via Capitale…),
	9	+doit produire des objets `PropertyListing` conformes à ce schéma. La méthode
	10	+`finalize()` applique ensuite la couche de normalisation commune
	11	+(immoka/normalize.py) : prix, type de propriété canonique, superficies en pi²,
	12	+chambres/salles de bains… — les connecteurs restent simples et remplissent
	13	+les champs bruts.
	14	+"""
	15	+from __future__ import annotations
	16	+
	17	+import hashlib
	18	+import json
	19	+from dataclasses import dataclass, field, asdict
	20	+
	21	+from .normalize import (
	22	+ clean_address,
	23	+ clean_description,
	24	+ clean_title,
	25	+ extract_bedrooms_bathrooms,
	26	+ normalize_property_type,
	27	+ parse_area_sqft,
	28	+ parse_int,
	29	+ parse_lot_sqft,
	30	+ parse_price,
	31	+ parse_year,
	32	+ price_is_from,
	33	+ strip_accents,
	34	+)
	35	+
	36	+__all__ = ["PropertyListing"]
	37	+
	38	+
	39	+@dataclass
	40	+class PropertyListing:
	41	+ """Propriété à vendre standardisée Immo-Ka."""
	42	+
	43	+ source: str # id de l'agence (voir data/sources.json)
	44	+ external_id: str # identifiant chez la source (souvent le n° Centris/MLS)
	45	+ url: str # page de la propriété chez la source
	46	+ title: str = "" # ex. "Maison à étages à vendre — Lévis"
	47	+ address: str = "" # adresse civique
	48	+ sector: str = "" # quartier/arrondissement
	49	+ city: str = "" # Québec, Lévis, Montréal…
	50	+ region: str = "" # région administrative (Capitale-Nationale…)
	51	+ property_type: str = "" # Maison, Condo, Duplex, Terrain… (canonique)
	52	+ price: float \| None = None # prix demandé ($ CAD)
	53	+ price_label: str = "" # texte original (ex. "459 000 $ +tx")
	54	+ bedrooms: int \| None = None # chambres
	55	+ bathrooms: int \| None = None # salles de bains
	56	+ powder_rooms: int \| None = None # salles d'eau
	57	+ area_sqft: float \| None = None # superficie habitable (pi²)
	58	+ lot_sqft: float \| None = None # superficie du terrain (pi²)
	59	+ year_built: int \| None = None
	60	+ mls: str = "" # numéro Centris/MLS si affiché par la source
	61	+ status: str = "a-vendre" # a-vendre \| vendu \| conditionnel
	62	+ broker_name: str = "" # courtier inscripteur
	63	+ broker_phone: str = ""
	64	+ agency: str = "" # sous-agence / bureau (ex. « Royal LePage Altitude »,
	65	+ # « Groupe Sutton - Synergie ») — affichage des
	66	+ # Sources par sous-agence
	67	+ description: str = ""
	68	+ features: list[str] = field(default_factory=list) # caractéristiques (texte source)
	69	+ details: dict = field(default_factory=dict) # champs structurés (JSON)
	70	+ images: list[str] = field(default_factory=list) # URLs absolues
	71	+ lat: float \| None = None
	72	+ lng: float \| None = None
	73	+
	74	+ @property
	75	+ def uid(self) -> str:
	76	+ return f"{self.source}:{self.external_id}"
	77	+
	78	+ def content_hash(self) -> str:
	79	+ """Hash du contenu pour la détection de changements (pseudo-webhook)."""
	80	+ payload = asdict(self)
	81	+ blob = json.dumps(payload, sort_keys=True, ensure_ascii=False)
	82	+ return hashlib.sha256(blob.encode("utf-8")).hexdigest()
	83	+
	84	+ def finalize(self) -> "PropertyListing":
	85	+ """Applique la normalisation commune. Appelé par le pipeline d'ingestion.
	86	+
	87	+ Idempotent ; ne remplace jamais une valeur explicite du connecteur.
	88	+ """
	89	+ self.title = clean_title(self.title)
	90	+ self.address = clean_address(self.address)
	91	+ self.city = (self.city or "").strip()
	92	+ self.property_type = normalize_property_type(self.property_type)
	93	+ self.description = clean_description(self.description)
	94	+
	95	+ # galerie : URLs valides seulement, placeholders retirés, doublons
	96	+ # (même photo en deux tailles) dédupliqués — voir immoka/imgaudit.py
	97	+ from .imgaudit import clean_gallery
	98	+ self.images = clean_gallery(self.images)
	99	+
	100	+ if self.price is None:
	101	+ self.price = parse_price(self.price_label)
	102	+ if self.price_label and price_is_from(self.price_label):
	103	+ self.details.setdefault("price_from", True)
	104	+
	105	+ # promotion details -> colonnes : les champs structurés de la fiche
	106	+ # (tableau DDF/Centris) priment sur l'extraction de texte libre ci-dessous
	107	+ if not self.property_type:
	108	+ for k in ("Building Type", "Property Type", "Type",
	109	+ "Type de propriété", "Genre de propriété"):
	110	+ if self.details.get(k):
	111	+ self.property_type = normalize_property_type(str(self.details[k]))
	112	+ break
	113	+ if self.year_built is None:
	114	+ for k in ("Constructed Date", "Année de construction"):
	115	+ if self.details.get(k):
	116	+ self.year_built = parse_year(self.details[k])
	117	+ break
	118	+ if self.area_sqft is None:
	119	+ for k in ("Size Interior", "Superficie habitable"):
	120	+ if self.details.get(k):
	121	+ self.area_sqft = parse_area_sqft(str(self.details[k]))
	122	+ break
	123	+ if self.lot_sqft is None:
	124	+ for k in ("Land Size", "Superficie du terrain"):
	125	+ if self.details.get(k):
	126	+ self.lot_sqft = parse_lot_sqft(str(self.details[k]))
	127	+ break
	128	+
	129	+ texte = " ".join(filter(None, (self.title, self.description,
	130	+ " ".join(self.features))))
	131	+ if self.bedrooms is None or self.bathrooms is None:
	132	+ beds, baths = extract_bedrooms_bathrooms(texte)
	133	+ if self.bedrooms is None:
	134	+ self.bedrooms = beds
	135	+ if self.bathrooms is None:
	136	+ self.bathrooms = baths
	137	+ if self.area_sqft is None:
	138	+ self.area_sqft = parse_area_sqft(texte)
	139	+ if self.lot_sqft is None and "terrain" in strip_accents(texte.lower()):
	140	+ self.lot_sqft = parse_lot_sqft(texte)
	141	+ self.year_built = parse_int(self.year_built)
	142	+
	143	+ # sous-agence : à défaut, on retombe sur le courtier/agence inscripteur
	144	+ if not self.agency:
	145	+ self.agency = self.broker_name
	146	+
	147	+ # coordonnées fournies par la source : rejeter tout point hors du
	148	+ # territoire couvert — le CANADA au complet (lat/lng inversés, 0/0, coquilles)
	149	+ if self.lat is not None and self.lng is not None:
	150	+ if not (41.6 <= self.lat <= 83.2 and -141.1 <= self.lng <= -52.5):
	151	+ self.lat = self.lng = None
	152	+
	153	+ return self

added immoka/seo.py +823 −0

		`@@ -0,0 +1,823 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# House-Ka — Homes-for-sale aggregator (Canada outside Québec, Ontario first)
	3	+# Author: Simon-Pierre Boucher — contact@spboucher.ai
	4	+# seo.py : server-side HTML rendering for search engines.
	5	+#
	6	+# The React SPA is untouched: this module pre-fills the initial HTML served by
	7	+# the web.py catch-all — unique <title>/meta/canonical/og:, schema.org JSON-LD,
	8	+# content and internal links inside <div id="root"> (replaced by React on
	9	+# mount). Also generates robots.txt and the sitemaps.
	10	+#
	11	+# Pages served:
	12	+# / enriched home (stats + city/type links)
	13	+# /property/{uid}[/{slug}] listing page (301 to the canonical slug,
	14	+# 410 if withdrawn, 404 if unknown)
	15	+# /for-sale/{city}[/{type}] programmatic city pages (+ type)
	16	+# /type/{type} per-property-type page (Canada-wide)
	17	+# /stats /agencies /terms /privacy /account /rates /contact dedicated meta
	18	+# /robots.txt /sitemap.xml /sitemaps/*.xml
	19	+# -----------------------------------------------------------------------------
	20	+from __future__ import annotations
	21	+
	22	+import html
	23	+import json
	24	+import os
	25	+import re
	26	+import time
	27	+import unicodedata
	28	+from datetime import datetime, timezone
	29	+from pathlib import Path
	30	+from urllib.parse import quote
	31	+
	32	+from fastapi.responses import HTMLResponse, PlainTextResponse, RedirectResponse, Response
	33	+
	34	+from . import db
	35	+
	36	+ROOT = Path(__file__).resolve().parent.parent
	37	+FRONTEND_DIST = ROOT / "frontend" / "dist"
	38	+FRONTEND_DIR = FRONTEND_DIST if FRONTEND_DIST.exists() else ROOT / "frontend"
	39	+
	40	+BASE_URL = os.environ.get("IMMOKA_BASE_URL", "https://www.house-ka.com").rstrip("/")
	41	+SITE_NAME = "House-Ka"
	42	+
	43	+# same visibility rule as /api/listings (DDF dedup + displayable price)
	44	+VISIBLE = "active=1 AND dup_hidden=0 AND published=1"
	45	+MIN_LISTINGS = 3 # quality floor: no near-empty city/type pages
	46	+PAGE_SIZE = 48 # listings per page on programmatic pages
	47	+
	48	+# province name (region column) -> two-letter code for schema.org
	49	+_PROVINCE_CODE = {
	50	+ "ontario": "ON", "british columbia": "BC", "alberta": "AB",
	51	+ "saskatchewan": "SK", "manitoba": "MB", "new brunswick": "NB",
	52	+ "nova scotia": "NS", "prince edward island": "PE",
	53	+ "newfoundland and labrador": "NL", "yukon": "YT",
	54	+ "northwest territories": "NT", "nunavut": "NU", "quebec": "QC",
	55	+}
	56	+
	57	+# -----------------------------------------------------------------------------
	58	+# Utilities
	59	+# -----------------------------------------------------------------------------
	60	+
	61	+def slugify(s: str) -> str:
	62	+ """URL slug — SAME algorithm as slugify() in frontend/src/api.ts."""
	63	+ s = unicodedata.normalize("NFKD", s or "").encode("ascii", "ignore").decode()
	64	+ s = re.sub(r"[^a-z0-9]+", "-", s.lower()).strip("-")
	65	+ return s[:80].strip("-")
	66	+
	67	+
	68	+def listing_slug(row) -> str:
	69	+ """Listing slug — SAME logic as listingPath() in frontend/src/api.ts."""
	70	+ base = slugify(row["address"] or row["title"] or "")
	71	+ city = slugify(row["city"] or "")
	72	+ if city and city not in base:
	73	+ base = slugify(f"{base} {city}") if base else city
	74	+ return base
	75	+
	76	+
	77	+def _esc(s) -> str:
	78	+ return html.escape(str(s or ""), quote=True)
	79	+
	80	+
	81	+def _fmt_n(n) -> str:
	82	+ return f"{int(n):,}"
	83	+
	84	+
	85	+def _fmt_price(p) -> str:
	86	+ return f"${_fmt_n(round(p))}" if p is not None else "Price on request"
	87	+
	88	+
	89	+def _iso_date(ts) -> str:
	90	+ try:
	91	+ return datetime.fromtimestamp(float(ts), tz=timezone.utc).strftime("%Y-%m-%d")
	92	+ except (TypeError, ValueError):
	93	+ return datetime.now(tz=timezone.utc).strftime("%Y-%m-%d")
	94	+
	95	+
	96	+# small in-memory TTL cache (data changes at watch pace, ~1 h)
	97	+_cache: dict[str, tuple[float, object]] = {}
	98	+
	99	+
	100	+def _cached(key: str, ttl: float, build):
	101	+ now = time.time()
	102	+ hit = _cache.get(key)
	103	+ if hit and now - hit[0] < ttl:
	104	+ return hit[1]
	105	+ val = build()
	106	+ _cache[key] = (now, val)
	107	+ return val
	108	+
	109	+
	110	+# -----------------------------------------------------------------------------
	111	+# Slug registries (cities, types) — rebuilt every 15 min
	112	+# -----------------------------------------------------------------------------
	113	+
	114	+def _build_registry() -> dict:
	115	+ con = db.connect()
	116	+ cities: dict[str, dict] = {}
	117	+ for r in con.execute(
	118	+ f"SELECT city, COUNT(*) n FROM listings WHERE {VISIBLE}"
	119	+ " AND city<>'' GROUP BY city"):
	120	+ slug = slugify(r["city"])
	121	+ if len(slug) < 2:
	122	+ continue
	123	+ e = cities.setdefault(slug, {"label": r["city"], "n": 0, "values": [], "best": 0})
	124	+ e["n"] += r["n"]
	125	+ e["values"].append(r["city"])
	126	+ if r["n"] > e["best"]:
	127	+ e["best"] = r["n"]; e["label"] = r["city"]
	128	+ types: dict[str, dict] = {}
	129	+ for r in con.execute(
	130	+ f"SELECT property_type, COUNT(*) n FROM listings WHERE {VISIBLE}"
	131	+ " AND property_type<>'' GROUP BY property_type"):
	132	+ slug = slugify(r["property_type"])
	133	+ if len(slug) < 2:
	134	+ continue
	135	+ e = types.setdefault(slug, {"label": r["property_type"], "n": 0, "values": [], "best": 0})
	136	+ e["n"] += r["n"]
	137	+ e["values"].append(r["property_type"])
	138	+ if r["n"] > e["best"]:
	139	+ e["best"] = r["n"]; e["label"] = r["property_type"]
	140	+ city_types: dict[tuple[str, str], int] = {}
	141	+ for r in con.execute(
	142	+ f"SELECT city, property_type, COUNT(*) n FROM listings WHERE {VISIBLE}"
	143	+ " AND city<>'' AND property_type<>'' GROUP BY city, property_type"):
	144	+ cs, ts_ = slugify(r["city"]), slugify(r["property_type"])
	145	+ if len(cs) < 2 or len(ts_) < 2:
	146	+ continue
	147	+ city_types[(cs, ts_)] = city_types.get((cs, ts_), 0) + r["n"]
	148	+ con.close()
	149	+ return {"cities": cities, "types": types, "city_types": city_types}
	150	+
	151	+
	152	+def registry() -> dict:
	153	+ return _cached("registry", 900, _build_registry)
	154	+
	155	+
	156	+# -----------------------------------------------------------------------------
	157	+# Template: dist/index.html, stripped of its static <title>/description
	158	+# -----------------------------------------------------------------------------
	159	+
	160	+_tpl_cache: tuple[float, str] \| None = None
	161	+
	162	+
	163	+def _template() -> str:
	164	+ global _tpl_cache
	165	+ path = FRONTEND_DIR / "index.html"
	166	+ mtime = path.stat().st_mtime
	167	+ if _tpl_cache and _tpl_cache[0] == mtime:
	168	+ return _tpl_cache[1]
	169	+ tpl = path.read_text(encoding="utf-8")
	170	+ tpl = re.sub(r"<title>.?</title>\s", "", tpl, flags=re.S)
	171	+ tpl = re.sub(r'<meta name="description"[^>]>\s', "", tpl)
	172	+ tpl = re.sub(r'<meta (?:property="og:\|name="twitter:)[^>]>\s', "", tpl)
	173	+ _tpl_cache = (mtime, tpl)
	174	+ return tpl
	175	+
	176	+
	177	+def _page(title: str, description: str, canonical: str, body: str,
	178	+ jsonld: list[dict] \| None = None, og_image: str \| None = None,
	179	+ og_type: str = "website", noindex: bool = False,
	180	+ status: int = 200) -> HTMLResponse:
	181	+ head = [
	182	+ f"<title>{_esc(title)}</title>",
	183	+ f'<meta name="description" content="{_esc(description)}" />',
	184	+ f'<link rel="canonical" href="{_esc(canonical)}" />',
	185	+ f'<meta property="og:site_name" content="{SITE_NAME}" />',
	186	+ '<meta property="og:locale" content="en_CA" />',
	187	+ f'<meta property="og:type" content="{og_type}" />',
	188	+ f'<meta property="og:title" content="{_esc(title)}" />',
	189	+ f'<meta property="og:description" content="{_esc(description)}" />',
	190	+ f'<meta property="og:url" content="{_esc(canonical)}" />',
	191	+ ]
	192	+ if og_image:
	193	+ head.append(f'<meta property="og:image" content="{_esc(og_image)}" />')
	194	+ else:
	195	+ og_image = BASE_URL + "/og.png"
	196	+ head.append(f'<meta property="og:image" content="{_esc(og_image)}" />')
	197	+ head.append('<meta property="og:image:width" content="1200" />')
	198	+ head.append('<meta property="og:image:height" content="630" />')
	199	+ head.append('<meta name="twitter:card" content="summary_large_image" />')
	200	+ head.append(f'<meta name="twitter:image" content="{_esc(og_image)}" />')
	201	+ if noindex:
	202	+ head.append('<meta name="robots" content="noindex" />')
	203	+ for obj in (jsonld or []):
	204	+ head.append('<script type="application/ld+json">'
	205	+ + json.dumps(obj, ensure_ascii=False) + "</script>")
	206	+ tpl = _template()
	207	+ out = tpl.replace("</head>", " " + "\n ".join(head) + "\n </head>", 1)
	208	+ out = out.replace('<div id="root"></div>',
	209	+ f'<div id="root"><div class="container seo-ssr">{body}</div></div>', 1)
	210	+ return HTMLResponse(out, status_code=status)
	211	+
	212	+
	213	+# -----------------------------------------------------------------------------
	214	+# Reusable HTML blocks
	215	+# -----------------------------------------------------------------------------
	216	+
	217	+def fiche_href(uid: str, slug: str = "") -> str:
	218	+ path = f"/property/{quote(uid, safe='')}"
	219	+ return path + (f"/{slug}" if slug else "")
	220	+
	221	+
	222	+def _item_li(r) -> str:
	223	+ href = fiche_href(r["uid"], listing_slug(r))
	224	+ bits = [b for b in [
	225	+ r["property_type"],
	226	+ f"{r['bedrooms']} bed" if r["bedrooms"] is not None else "",
	227	+ f"{r['bathrooms']} bath" if r["bathrooms"] is not None else "",
	228	+ f"{_fmt_n(round(r['area_sqft']))} sq ft" if r["area_sqft"] else "",
	229	+ ] if b]
	230	+ name = r["address"] or r["title"] or "Property"
	231	+ loc = ", ".join(x for x in [r["sector"], r["city"]] if x)
	232	+ return (f'<li><a href="{href}"><strong>{_esc(name)}</strong></a> — '
	233	+ f'{_esc(_fmt_price(r["price"]))}'
	234	+ + (f' · {_esc(" · ".join(bits))}' if bits else "")
	235	+ + (f' · {_esc(loc)}' if loc else "") + "</li>")
	236	+
	237	+
	238	+def _agg_stats(con, cities: list[str] \| None = None,
	239	+ types_values: list[str] \| None = None) -> dict:
	240	+ where = VISIBLE
	241	+ args: list = []
	242	+ if cities:
	243	+ where += f" AND city IN ({','.join('?' * len(cities))})"
	244	+ args += cities
	245	+ if types_values:
	246	+ where += f" AND property_type IN ({','.join('?' * len(types_values))})"
	247	+ args += types_values
	248	+ row = con.execute(
	249	+ f"SELECT COUNT(*) n, AVG(price) avg_p, MIN(price) min_p, MAX(price) max_p"
	250	+ f" FROM listings WHERE {where}", args).fetchone()
	251	+ med = None
	252	+ if row["n"]:
	253	+ med_row = con.execute(
	254	+ f"SELECT price FROM listings WHERE {where}"
	255	+ f" ORDER BY price LIMIT 1 OFFSET ?", args + [row["n"] // 2]).fetchone()
	256	+ med = med_row["price"] if med_row else None
	257	+ return {"n": row["n"], "avg": row["avg_p"], "med": med,
	258	+ "min": row["min_p"], "max": row["max_p"], "where": where, "args": args}
	259	+
	260	+
	261	+def _pagination_html(base_path: str, page: int, pages: int) -> str:
	262	+ if pages <= 1:
	263	+ return ""
	264	+ out = ['<nav class="seo-pages" aria-label="Pagination">']
	265	+ if page > 1:
	266	+ prev = base_path if page == 2 else f"{base_path}?page={page - 1}"
	267	+ out.append(f'<a rel="prev" href="{prev}">← Previous page</a> ')
	268	+ out.append(f"<span>Page {page} of {pages}</span>")
	269	+ if page < pages:
	270	+ out.append(f' <a rel="next" href="{base_path}?page={page + 1}">Next page →</a>')
	271	+ out.append("</nav>")
	272	+ return "".join(out)
	273	+
	274	+
	275	+def _breadcrumb_ld(crumbs: list[tuple[str, str]]) -> dict:
	276	+ return {
	277	+ "@context": "https://schema.org",
	278	+ "@type": "BreadcrumbList",
	279	+ "itemListElement": [
	280	+ {"@type": "ListItem", "position": i + 1, "name": name,
	281	+ "item": BASE_URL + path}
	282	+ for i, (name, path) in enumerate(crumbs)
	283	+ ],
	284	+ }
	285	+
	286	+
	287	+# -----------------------------------------------------------------------------
	288	+# Home
	289	+# -----------------------------------------------------------------------------
	290	+
	291	+def _home_data() -> dict:
	292	+ def build():
	293	+ con = db.connect()
	294	+ row = con.execute(
	295	+ f"SELECT COUNT(*) total, COUNT(DISTINCT city) cities,"
	296	+ f" COUNT(DISTINCT source) sources, AVG(price) avg_p"
	297	+ f" FROM listings WHERE {VISIBLE}").fetchone()
	298	+ recent = [dict(r) for r in con.execute(
	299	+ f"SELECT uid, address, title, city, sector, property_type, price,"
	300	+ f" bedrooms, bathrooms, area_sqft FROM listings WHERE {VISIBLE}"
	301	+ f" ORDER BY first_seen DESC LIMIT 12")]
	302	+ con.close()
	303	+ return {**dict(row), "recent": recent}
	304	+ return _cached("home", 900, build)
	305	+
	306	+
	307	+def render_home() -> HTMLResponse:
	308	+ d = _home_data()
	309	+ reg = registry()
	310	+ total = _fmt_n(d["total"])
	311	+ title = f"House-Ka — {total} homes for sale across Canada · A Groupe KA service"
	312	+ desc = (f"{total} homes for sale in {_fmt_n(d['cities'])} Canadian cities and towns, "
	313	+ f"aggregated from {d['sources']} brokerage sources on the CREA DDF feed — "
	314	+ f"continuously updated. Average asking price: {_fmt_price(d['avg_p'])}.")
	315	+ top_cities = sorted(reg["cities"].items(), key=lambda kv: -kv[1]["n"])[:60]
	316	+ types = sorted(reg["types"].items(), key=lambda kv: -kv[1]["n"])
	317	+ body = [
	318	+ f"<h1>Homes for sale across Canada — {total} listings from real-estate brokerages</h1>",
	319	+ f"<p>House-Ka continuously aggregates homes for sale publicly listed by Canadian "
	320	+ f"real-estate brokerages and teams (CREA DDF feed) — {d['sources']} sources, "
	321	+ f"{_fmt_n(d['cities'])} cities, average asking price {_esc(_fmt_price(d['avg_p']))}. "
	322	+ f"Every listing links back to the brokerage's original page. Coverage starts with "
	323	+ f"Ontario and grows across the rest of Canada. Looking for Québec? "
	324	+ f'See our sister site <a href="https://www.immo-ka.com" rel="noopener">Immo-Ka</a>.</p>',
	325	+ "<h2>Homes for sale by city</h2>",
	326	+ "<ul>" + "".join(
	327	+ f'<li><a href="/for-sale/{s}">Homes for sale in {_esc(e["label"])}</a>'
	328	+ f" ({_fmt_n(e['n'])})</li>"
	329	+ for s, e in top_cities if e["n"] >= MIN_LISTINGS) + "</ul>",
	330	+ "<h2>By property type</h2>",
	331	+ "<ul>" + "".join(
	332	+ f'<li><a href="/type/{s}">{_esc(e["label"])} for sale in Canada</a>'
	333	+ f" ({_fmt_n(e['n'])})</li>"
	334	+ for s, e in types if e["n"] >= MIN_LISTINGS) + "</ul>",
	335	+ "<h2>Latest listings</h2>",
	336	+ "<ul>" + "".join(_item_li(r) for r in d["recent"]) + "</ul>",
	337	+ '<p><a href="/stats">Market statistics</a> · '
	338	+ '<a href="/agencies">Covered brokerages</a> · '
	339	+ '<a href="/rates">Mortgage rates</a></p>',
	340	+ ]
	341	+ jsonld = [{
	342	+ "@context": "https://schema.org",
	343	+ "@type": "WebSite",
	344	+ "name": SITE_NAME,
	345	+ "url": BASE_URL + "/",
	346	+ "inLanguage": "en-CA",
	347	+ "description": desc,
	348	+ "potentialAction": {
	349	+ "@type": "SearchAction",
	350	+ "target": {"@type": "EntryPoint",
	351	+ "urlTemplate": BASE_URL + "/?q={search_term_string}"},
	352	+ "query-input": "required name=search_term_string",
	353	+ },
	354	+ }, {
	355	+ "@context": "https://schema.org",
	356	+ "@type": "Organization",
	357	+ "name": "Groupe-Ka",
	358	+ "url": BASE_URL + "/",
	359	+ "email": "contact@groupe-ka.com",
	360	+ }]
	361	+ return _page(title, desc, BASE_URL + "/", "".join(body), jsonld)
	362	+
	363	+
	364	+# -----------------------------------------------------------------------------
	365	+# Programmatic pages: city, city+type, type
	366	+# -----------------------------------------------------------------------------
	367	+
	368	+def _render_category(city_slug: str \| None, type_slug: str \| None,
	369	+ page: int) -> HTMLResponse:
	370	+ reg = registry()
	371	+ city = reg["cities"].get(city_slug) if city_slug else None
	372	+ ptype = reg["types"].get(type_slug) if type_slug else None
	373	+ if (city_slug and not city) or (type_slug and not ptype):
	374	+ return render_404()
	375	+ if city_slug and type_slug and reg["city_types"].get((city_slug, type_slug), 0) < 1:
	376	+ return render_404()
	377	+
	378	+ con = db.connect()
	379	+ st = _agg_stats(con, city["values"] if city else None,
	380	+ ptype["values"] if ptype else None)
	381	+ if st["n"] < 1:
	382	+ con.close()
	383	+ return render_404()
	384	+
	385	+ pages = max(1, -(-st["n"] // PAGE_SIZE))
	386	+ if page < 1 or page > pages:
	387	+ con.close()
	388	+ return render_404()
	389	+ rows = con.execute(
	390	+ f"SELECT uid, address, title, city, sector, property_type, price,"
	391	+ f" bedrooms, bathrooms, area_sqft FROM listings WHERE {st['where']}"
	392	+ f" ORDER BY price IS NULL, price ASC LIMIT ? OFFSET ?",
	393	+ st["args"] + [PAGE_SIZE, (page - 1) * PAGE_SIZE]).fetchall()
	394	+
	395	+ # internal linking
	396	+ links = []
	397	+ if city:
	398	+ tlinks = []
	399	+ for (cs, ts_), n in sorted(reg["city_types"].items(), key=lambda kv: -kv[1]):
	400	+ if cs == city_slug and n >= 1 and ts_ in reg["types"] and ts_ != type_slug:
	401	+ lbl = reg["types"][ts_]["label"]
	402	+ tlinks.append(f'<li><a href="/for-sale/{cs}/{ts_}">'
	403	+ f"{_esc(lbl)} for sale in {_esc(city['label'])}</a> ({_fmt_n(n)})</li>")
	404	+ if tlinks:
	405	+ links.append("<h2>Other property types in "
	406	+ + _esc(city["label"]) + "</h2><ul>" + "".join(tlinks[:20]) + "</ul>")
	407	+ if type_slug:
	408	+ links.append(f'<p><a href="/for-sale/{city_slug}">All homes for sale '
	409	+ f"in {_esc(city['label'])}</a> · "
	410	+ f'<a href="/type/{type_slug}">{_esc(ptype["label"])} for sale in Canada</a></p>')
	411	+ top = sorted(reg["cities"].items(), key=lambda kv: -kv[1]["n"])[:30]
	412	+ links.append("<h2>Other cities</h2><ul>" + "".join(
	413	+ f'<li><a href="/for-sale/{s}{"/" + type_slug if type_slug and (s, type_slug) in reg["city_types"] else ""}">'
	414	+ f'Homes for sale in {_esc(e["label"])}</a> ({_fmt_n(e["n"])})</li>'
	415	+ for s, e in top if s != city_slug and e["n"] >= MIN_LISTINGS) + "</ul>")
	416	+ con.close()
	417	+
	418	+ if city and ptype:
	419	+ base_path = f"/for-sale/{city_slug}/{type_slug}"
	420	+ h1 = f"{ptype['label']} for sale in {city['label']}"
	421	+ what = f"{ptype['label'].lower()} listings in {city['label']}"
	422	+ elif city:
	423	+ base_path = f"/for-sale/{city_slug}"
	424	+ h1 = f"Homes for sale in {city['label']}"
	425	+ what = f"homes for sale in {city['label']}"
	426	+ else:
	427	+ base_path = f"/type/{type_slug}"
	428	+ h1 = f"{ptype['label']} for sale in Canada"
	429	+ what = f"{ptype['label'].lower()} listings across Canada"
	430	+
	431	+ canonical = BASE_URL + base_path + (f"?page={page}" if page > 1 else "")
	432	+ title = f"{h1} — {_fmt_n(st['n'])} listings" + (f" (page {page})" if page > 1 else "") + " \| House-Ka"
	433	+ desc = (f"{_fmt_n(st['n'])} {what}: median price {_fmt_price(st['med'])}, "
	434	+ f"average price {_fmt_price(st['avg'])}. Listings from Canadian brokerages "
	435	+ f"on the CREA DDF feed, continuously updated.")
	436	+ stats_p = (f"<p><strong>{_fmt_n(st['n'])}</strong> listings · median price "
	437	+ f"<strong>{_esc(_fmt_price(st['med']))}</strong> · average price "
	438	+ f"<strong>{_esc(_fmt_price(st['avg']))}</strong> · from "
	439	+ f"{_esc(_fmt_price(st['min']))} to {_esc(_fmt_price(st['max']))}.</p>")
	440	+ crumbs = [("Home", "/")]
	441	+ if city:
	442	+ crumbs.append((f"For sale in {city['label']}", f"/for-sale/{city_slug}"))
	443	+ if ptype:
	444	+ crumbs.append((f"{ptype['label']}", base_path))
	445	+ else:
	446	+ crumbs.append((h1, base_path))
	447	+ body = ('<nav aria-label="Breadcrumb">'
	448	+ + " › ".join(f'<a href="{p}">{_esc(n)}</a>' for n, p in crumbs)
	449	+ + f"</nav><h1>{_esc(h1)}</h1>" + stats_p
	450	+ + "<ul>" + "".join(_item_li(r) for r in rows) + "</ul>"
	451	+ + _pagination_html(base_path, page, pages)
	452	+ + "".join(links))
	453	+ return _page(title, desc, canonical, body, [_breadcrumb_ld(crumbs)])
	454	+
	455	+
	456	+# -----------------------------------------------------------------------------
	457	+# Listing page
	458	+# -----------------------------------------------------------------------------
	459	+
	460	+_TYPE_SCHEMA = {
	461	+ "house": "SingleFamilyResidence", "condo": "Apartment",
	462	+ "cottage": "House", "semi-detached": "House", "townhouse": "House",
	463	+ "duplex": "Residence", "triplex": "Residence",
	464	+ "multi-family": "Residence", "mobile-home": "House",
	465	+}
	466	+
	467	+
	468	+def render_listing(uid: str, slug: str \| None) -> Response:
	469	+ con = db.connect()
	470	+ row = con.execute("SELECT * FROM listings WHERE uid=?", (uid,)).fetchone()
	471	+ con.close()
	472	+ if row is None:
	473	+ return render_404()
	474	+
	475	+ city_slug = slugify(row["city"] or "")
	476	+ city_known = city_slug in registry()["cities"]
	477	+ city_href = f"/for-sale/{city_slug}" if city_known else "/"
	478	+
	479	+ if not row["active"]:
	480	+ # withdrawn / sold → 410 Gone, with escape hatches
	481	+ name = row["address"] or row["title"] or "Property"
	482	+ body = (f"<h1>This property is no longer for sale</h1>"
	483	+ f"<p>The listing “{_esc(name)}” ({_esc(row['city'] or 'Canada')}) has been "
	484	+ f"withdrawn or sold.</p><ul>"
	485	+ + (f'<li><a href="{city_href}">Homes for sale in '
	486	+ f"{_esc(row['city'])}</a></li>" if city_known else "")
	487	+ + '<li><a href="/">All homes for sale across Canada</a></li></ul>')
	488	+ return _page(f"Listing withdrawn — {name} \| {SITE_NAME}",
	489	+ "This listing has been withdrawn or sold.",
	490	+ BASE_URL + fiche_href(uid), body, noindex=True, status=410)
	491	+
	492	+ expected = listing_slug(row)
	493	+ if expected and slug != expected:
	494	+ return RedirectResponse(BASE_URL + fiche_href(uid, expected), status_code=301)
	495	+
	496	+ d = dict(row)
	497	+ images = json.loads(d.get("images") or "[]")
	498	+ features = json.loads(d.get("features") or "[]")
	499	+ name = d["address"] or d["title"] or "Property for sale"
	500	+ loc = ", ".join(x for x in [d["sector"], d["city"]] if x) or "Canada"
	501	+ canonical = BASE_URL + fiche_href(uid, expected)
	502	+ ptype = d["property_type"] or "Property"
	503	+
	504	+ specs = [(lbl, val) for lbl, val in [
	505	+ ("Type", ptype),
	506	+ ("Price", _fmt_price(d["price"]) if d["price"] is not None else d["price_label"]),
	507	+ ("Bedrooms", d["bedrooms"]),
	508	+ ("Bathrooms", d["bathrooms"]),
	509	+ ("Half baths", d["powder_rooms"]),
	510	+ ("Living area", f"{_fmt_n(round(d['area_sqft']))} sq ft" if d["area_sqft"] else None),
	511	+ ("Lot", f"{_fmt_n(round(d['lot_sqft']))} sq ft" if d["lot_sqft"] else None),
	512	+ ("Year built", d["year_built"]),
	513	+ ("City", d["city"]),
	514	+ ("Neighbourhood", d["sector"]),
	515	+ ("MLS® number", d["mls"]),
	516	+ ("Agent", d["broker_name"]),
	517	+ ("Brokerage", d["agency"]),
	518	+ ] if val not in (None, "", 0)]
	519	+ descr = (d["description"] or "").strip()
	520	+ if len(descr) > 1500:
	521	+ descr = descr[:1500].rsplit(" ", 1)[0] + "…"
	522	+
	523	+ type_slug = slugify(ptype)
	524	+ crumbs = [("Home", "/")]
	525	+ if city_known:
	526	+ crumbs.append((f"For sale in {d['city']}", city_href))
	527	+ if (city_slug, type_slug) in registry()["city_types"]:
	528	+ crumbs.append((ptype, f"/for-sale/{city_slug}/{type_slug}"))
	529	+ crumbs.append((name, fiche_href(uid, expected)))
	530	+
	531	+ body = [
	532	+ '<nav aria-label="Breadcrumb">'
	533	+ + " › ".join(f'<a href="{p}">{_esc(n)}</a>' for n, p in crumbs[:-1])
	534	+ + f" › {_esc(name)}</nav>",
	535	+ f"<h1>{_esc(name)}</h1>",
	536	+ f"<p><strong>{_esc(ptype)} for sale in {_esc(loc)}</strong> — "
	537	+ f"{_esc(_fmt_price(d['price']) if d['price'] is not None else (d['price_label'] or 'Price on request'))}</p>",
	538	+ ]
	539	+ if images:
	540	+ body.append("".join(
	541	+ f'<img src="{_esc(u)}" alt="{_esc(name)} — photo {i + 1}" loading="lazy" />'
	542	+ for i, u in enumerate(images[:3])))
	543	+ body.append("<h2>Key facts</h2><ul>" + "".join(
	544	+ f"<li><strong>{_esc(l)}:</strong> {_esc(v)}</li>" for l, v in specs) + "</ul>")
	545	+ if descr:
	546	+ body.append(f"<h2>Description</h2><p>{_esc(descr)}</p>")
	547	+ if features:
	548	+ body.append("<h2>Details</h2><ul>" + "".join(
	549	+ f"<li>{_esc(f)}</li>" for f in features[:20]) + "</ul>")
	550	+ if d["url"]:
	551	+ body.append(f'<p><a href="{_esc(d["url"])}" rel="noopener">'
	552	+ f"See the original listing at {_esc(d['broker_name'] or d['agency'] or 'the brokerage')}</a></p>")
	553	+ if city_known:
	554	+ body.append(f'<p><a href="{city_href}">Homes for sale in {_esc(d["city"])}</a>'
	555	+ + (f' · <a href="/for-sale/{city_slug}/{type_slug}">{_esc(ptype)} for sale in '
	556	+ f'{_esc(d["city"])}</a>'
	557	+ if (city_slug, type_slug) in registry()["city_types"] else "") + "</p>")
	558	+
	559	+ about_type = _TYPE_SCHEMA.get(type_slug, "Residence")
	560	+ region_code = _PROVINCE_CODE.get((d["region"] or "").strip().lower(), "ON")
	561	+ about: dict = {
	562	+ "@type": about_type,
	563	+ "name": name,
	564	+ "address": {"@type": "PostalAddress",
	565	+ "streetAddress": d["address"] or None,
	566	+ "addressLocality": d["city"] or None,
	567	+ "addressRegion": region_code, "addressCountry": "CA"},
	568	+ }
	569	+ if d["lat"] is not None and d["lng"] is not None:
	570	+ about["geo"] = {"@type": "GeoCoordinates",
	571	+ "latitude": d["lat"], "longitude": d["lng"]}
	572	+ if d["bedrooms"] is not None:
	573	+ about["numberOfBedrooms"] = d["bedrooms"]
	574	+ if d["bathrooms"] is not None:
	575	+ about["numberOfBathroomsTotal"] = d["bathrooms"]
	576	+ if d["area_sqft"]:
	577	+ about["floorSize"] = {"@type": "QuantitativeValue",
	578	+ "value": round(d["area_sqft"]), "unitCode": "FTK"}
	579	+ if d["year_built"]:
	580	+ about["yearBuilt"] = d["year_built"]
	581	+ about = {k: v for k, v in about.items() if v is not None}
	582	+ about["address"] = {k: v for k, v in about["address"].items() if v is not None}
	583	+ jsonld: list[dict] = [{
	584	+ "@context": "https://schema.org",
	585	+ "@type": "RealEstateListing",
	586	+ "name": name,
	587	+ "url": canonical,
	588	+ "inLanguage": "en-CA",
	589	+ "datePosted": _iso_date(d.get("first_seen")),
	590	+ "image": images[:6] or None,
	591	+ "about": about,
	592	+ }, _breadcrumb_ld(crumbs)]
	593	+ if d["price"] is not None:
	594	+ jsonld[0]["offers"] = {"@type": "Offer", "price": round(d["price"], 2),
	595	+ "priceCurrency": "CAD",
	596	+ "availability": "https://schema.org/InStock"}
	597	+ jsonld[0] = {k: v for k, v in jsonld[0].items() if v is not None}
	598	+
	599	+ title = f"{name} — {ptype} for sale, {d['city'] or 'Canada'} \| {_fmt_price(d['price']) if d['price'] is not None else 'Price on request'}"
	600	+ meta_desc = (f"{ptype} for sale in {loc}"
	601	+ + (f", {d['bedrooms']} bedrooms" if d["bedrooms"] else "")
	602	+ + (f", {_fmt_n(round(d['area_sqft']))} sq ft" if d["area_sqft"] else "")
	603	+ + f" — {_fmt_price(d['price']) if d['price'] is not None else 'price on request'}. "
	604	+ + (descr[:120] + "…" if len(descr) > 120 else descr))
	605	+ return _page(title, meta_desc, canonical, "".join(body), jsonld,
	606	+ og_image=images[0] if images else None, og_type="article")
	607	+
	608	+
	609	+# -----------------------------------------------------------------------------
	610	+# Static SPA pages (dedicated meta) and 404
	611	+# -----------------------------------------------------------------------------
	612	+
	613	+_STATIC_META = {
	614	+ "/stats": ("Canadian housing market statistics",
	615	+ "Average prices, listing volumes by source and data quality — "
	616	+ "continuous statistics from House-Ka.",
	617	+ False),
	618	+ "/agencies": ("Covered brokerages",
	619	+ "All the Canadian real-estate brokerages and teams aggregated by "
	620	+ "House-Ka through the CREA DDF feed.",
	621	+ False),
	622	+ "/rates": (
	623	+ "Mortgage rates in Canada — live comparator",
	624	+ "Compare mortgage rates actually published by RBC, TD, BMO, CIBC, "
	625	+ "Scotiabank, NBC, Desjardins, Tangerine, EQ and more — fixed and variable, "
	626	+ "with official source, freshness and history. Continuously collected by House-Ka.",
	627	+ False),
	628	+ "/terms": ("Terms of use",
	629	+ "Terms of use of the House-Ka platform (Groupe-Ka).", False),
	630	+ "/privacy": ("Privacy policy",
	631	+ "House-Ka privacy policy (Groupe-Ka) — PIPEDA.", False),
	632	+ "/account": ("My account", "Your Groupe KA account on House-Ka.", True),
	633	+ "/contact": ("Contact — Groupe KA",
	634	+ "Write to Groupe KA: contact@groupe-ka.com (projects and data), "
	635	+ "info@groupe-ka.com (media), admin@groupe-ka.com (legal and privacy). "
	636	+ "House-Ka is a Groupe KA service — https://www.groupe-ka.com.",
	637	+ False),
	638	+}
	639	+
	640	+
	641	+def render_static(path: str) -> HTMLResponse:
	642	+ t, desc, noindex = _STATIC_META[path]
	643	+ body = f"<h1>{_esc(t)}</h1><p>{_esc(desc)}</p>"
	644	+ return _page(f"{t} \| {SITE_NAME}", desc, BASE_URL + path, body, noindex=noindex)
	645	+
	646	+
	647	+def render_404() -> HTMLResponse:
	648	+ body = ('<h1>Page not found</h1><p>The requested link does not exist.</p>'
	649	+ '<p><a href="/">All homes for sale across Canada</a></p>')
	650	+ return _page(f"Page not found \| {SITE_NAME}", "Page not found.",
	651	+ BASE_URL + "/", body, noindex=True, status=404)
	652	+
	653	+
	654	+# -----------------------------------------------------------------------------
	655	+# robots.txt and sitemaps
	656	+# -----------------------------------------------------------------------------
	657	+
	658	+FICHES_PER_SITEMAP = 40000
	659	+
	660	+
	661	+def robots_txt() -> PlainTextResponse:
	662	+ return PlainTextResponse(
	663	+ "User-agent: *\n"
	664	+ "Allow: /\n"
	665	+ "Disallow: /api/\n"
	666	+ "Disallow: /account\n"
	667	+ f"\nSitemap: {BASE_URL}/sitemap.xml\n")
	668	+
	669	+
	670	+def _xml(urls: list[str]) -> Response:
	671	+ body = ('<?xml version="1.0" encoding="UTF-8"?>\n'
	672	+ '<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">\n'
	673	+ + "\n".join(urls) + "\n</urlset>")
	674	+ return Response(body, media_type="application/xml")
	675	+
	676	+
	677	+def _url_el(loc: str, lastmod: str \| None = None) -> str:
	678	+ lm = f"<lastmod>{lastmod}</lastmod>" if lastmod else ""
	679	+ return f" <url><loc>{html.escape(loc)}</loc>{lm}</url>"
	680	+
	681	+
	682	+def sitemap_index() -> Response:
	683	+ def build():
	684	+ con = db.connect()
	685	+ n = con.execute(f"SELECT COUNT(*) c FROM listings WHERE {VISIBLE}").fetchone()["c"]
	686	+ last = con.execute(
	687	+ f"SELECT MAX(updated_at) m FROM listings WHERE {VISIBLE}").fetchone()["m"]
	688	+ con.close()
	689	+ parts = -(-n // FICHES_PER_SITEMAP) or 1
	690	+ lm = _iso_date(last)
	691	+ maps = [f"{BASE_URL}/sitemaps/listings-{i + 1}.xml" for i in range(parts)]
	692	+ maps += [f"{BASE_URL}/sitemaps/cities.xml",
	693	+ f"{BASE_URL}/sitemaps/cities-types.xml",
	694	+ f"{BASE_URL}/sitemaps/types.xml",
	695	+ f"{BASE_URL}/sitemaps/pages.xml"]
	696	+ body = ('<?xml version="1.0" encoding="UTF-8"?>\n'
	697	+ '<sitemapindex xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">\n'
	698	+ + "\n".join(f" <sitemap><loc>{html.escape(m)}</loc>"
	699	+ f"<lastmod>{lm}</lastmod></sitemap>" for m in maps)
	700	+ + "\n</sitemapindex>")
	701	+ return body
	702	+ return Response(_cached("sm:index", 3600, build), media_type="application/xml")
	703	+
	704	+
	705	+def sitemap_file(name: str) -> Response:
	706	+ m = re.fullmatch(r"listings-(\d+)\.xml", name)
	707	+ if m:
	708	+ part = int(m.group(1))
	709	+
	710	+ def build():
	711	+ con = db.connect()
	712	+ rows = con.execute(
	713	+ f"SELECT uid, address, title, city, updated_at FROM listings"
	714	+ f" WHERE {VISIBLE} ORDER BY uid LIMIT ? OFFSET ?",
	715	+ (FICHES_PER_SITEMAP, (part - 1) * FICHES_PER_SITEMAP)).fetchall()
	716	+ con.close()
	717	+ if not rows:
	718	+ return None
	719	+ return [_url_el(BASE_URL + fiche_href(r["uid"], listing_slug(r)),
	720	+ _iso_date(r["updated_at"])) for r in rows]
	721	+ urls = _cached(f"sm:listings:{part}", 3600, build)
	722	+ if urls is None:
	723	+ return Response("Sitemap not found", status_code=404)
	724	+ return _xml(urls)
	725	+
	726	+ if name == "cities.xml":
	727	+ def build():
	728	+ reg = registry()
	729	+ lm = _city_lastmod()
	730	+ return [_url_el(f"{BASE_URL}/for-sale/{s}", lm.get(s))
	731	+ for s, e in sorted(reg["cities"].items())
	732	+ if e["n"] >= MIN_LISTINGS]
	733	+ return _xml(_cached("sm:cities", 3600, build))
	734	+
	735	+ if name == "cities-types.xml":
	736	+ def build():
	737	+ reg = registry()
	738	+ lm = _city_lastmod()
	739	+ return [_url_el(f"{BASE_URL}/for-sale/{cs}/{ts_}", lm.get(cs))
	740	+ for (cs, ts_), n in sorted(reg["city_types"].items())
	741	+ if n >= MIN_LISTINGS and cs in reg["cities"] and ts_ in reg["types"]
	742	+ and reg["cities"][cs]["n"] >= MIN_LISTINGS]
	743	+ return _xml(_cached("sm:cities-types", 3600, build))
	744	+
	745	+ if name == "types.xml":
	746	+ def build():
	747	+ reg = registry()
	748	+ return [_url_el(f"{BASE_URL}/type/{s}")
	749	+ for s, e in sorted(reg["types"].items()) if e["n"] >= MIN_LISTINGS]
	750	+ return _xml(_cached("sm:types", 3600, build))
	751	+
	752	+ if name == "pages.xml":
	753	+ return _xml([_url_el(f"{BASE_URL}{p}")
	754	+ for p in ["/", "/stats", "/agencies", "/rates",
	755	+ "/terms", "/privacy"]])
	756	+
	757	+ return Response("Sitemap not found", status_code=404)
	758	+
	759	+
	760	+def _city_lastmod() -> dict[str, str]:
	761	+ def build():
	762	+ con = db.connect()
	763	+ out: dict[str, str] = {}
	764	+ for r in con.execute(
	765	+ f"SELECT city, MAX(updated_at) m FROM listings WHERE {VISIBLE}"
	766	+ " AND city<>'' GROUP BY city"):
	767	+ s = slugify(r["city"])
	768	+ if s:
	769	+ prev = out.get(s)
	770	+ cur = _iso_date(r["m"])
	771	+ out[s] = max(prev, cur) if prev else cur
	772	+ con.close()
	773	+ return out
	774	+ return _cached("sm:citylastmod", 3600, build)
	775	+
	776	+
	777	+# -----------------------------------------------------------------------------
	778	+# Slug resolution for the frontend (client-side /for-sale pages)
	779	+# -----------------------------------------------------------------------------
	780	+
	781	+def resolve_slugs(ville: str \| None, ptype: str \| None) -> dict \| None:
	782	+ reg = registry()
	783	+ out: dict = {}
	784	+ if ville:
	785	+ e = reg["cities"].get(ville)
	786	+ if not e:
	787	+ return None
	788	+ out["city"] = e["label"]
	789	+ out["city_n"] = e["n"]
	790	+ if ptype:
	791	+ e = reg["types"].get(ptype)
	792	+ if not e:
	793	+ return None
	794	+ out["property_type"] = e["label"]
	795	+ out["type_n"] = e["n"]
	796	+ return out
	797	+
	798	+
	799	+# -----------------------------------------------------------------------------
	800	+# Routing: called by the web.py catch-all
	801	+# -----------------------------------------------------------------------------
	802	+
	803	+def render_for_path(path: str, query: dict) -> Response \| None:
	804	+ """SEO HTML for `path` (e.g. “/for-sale/ottawa”), or None → raw index."""
	805	+ path = path.rstrip("/") or "/"
	806	+ try:
	807	+ page = max(1, int(query.get("page", "1")))
	808	+ except ValueError:
	809	+ page = 1
	810	+
	811	+ if path == "/":
	812	+ return render_home()
	813	+ if path in _STATIC_META:
	814	+ return render_static(path)
	815	+
	816	+ parts = [p for p in path.split("/") if p]
	817	+ if parts[0] == "property" and len(parts) in (2, 3):
	818	+ return render_listing(parts[1], parts[2] if len(parts) == 3 else None)
	819	+ if parts[0] == "for-sale" and len(parts) in (2, 3):
	820	+ return _render_category(parts[1], parts[2] if len(parts) == 3 else None, page)
	821	+ if parts[0] == "type" and len(parts) == 2:
	822	+ return _render_category(None, parts[1], page)
	823	+ return render_404()

added immoka/stats.py +1034 −0

		`@@ -0,0 +1,1034 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# stats.py : tableau de bord analytique /api/stats/dashboard + rapport PDF
	5	+# /api/stats/report (module Stats commun Groupe KA v2 — voir
	6	+# frontend/src/ka/stats/SPEC.md). Toutes les valeurs viennent de la base
	7	+# (listings, price_log, sync_log) — AUCUNE statistique inventée : une
	8	+# mesure indisponible est simplement omise (le front affiche un état vide).
	9	+# v2 : sparklines KPI, jauges (géolocalisation, photos, publiable),
	10	+# multi-courbes (prix médian par type / grande ville), barres empilées
	11	+# (nouvelles inscriptions par bannière), distributions (prix, superficie,
	12	+# année de construction), heatmap horaire 7×24, tableaux quarantaine &
	13	+# bannières, records enrichis.
	14	+# -----------------------------------------------------------------------------
	15	+from __future__ import annotations
	16	+
	17	+import json
	18	+import statistics
	19	+import threading
	20	+import time
	21	+import unicodedata
	22	+from datetime import date, datetime, timedelta
	23	+from pathlib import Path
	24	+from zoneinfo import ZoneInfo
	25	+
	26	+from . import db
	27	+
	28	+TZ = ZoneInfo("America/Toronto")
	29	+SQFT_PER_M2 = 10.7639104
	30	+ROOT = Path(__file__).resolve().parent.parent
	31	+SOURCES_PATH = ROOT / "data" / "sources.json"
	32	+
	33	+# Position vs estimation Vrai-Prix (mêmes seuils que le fair value Lou-Ka) :
	34	+# sous le marché si écart <= -8 %, au-dessus si >= +8 % ; les écarts hors
	35	+# (-50 %, +100 %) sont presque toujours des erreurs de lecture -> ignorés.
	36	+FV_SEUIL_SOUS = -0.08
	37	+FV_SEUIL_SUR = 0.08
	38	+FV_DEV_BOUNDS = (-0.50, 1.00)
	39	+# bornes de plausibilité des prix de vente résidentiels (journal de prix) :
	40	+# les écarts extrêmes sont des erreurs de source, pas de vraies baisses.
	41	+PRICE_MIN, PRICE_MAX = 25_000, 50_000_000
	42	+
	43	+# Même règle de visibilité que le reste de l'API (web.DEDUP_CLAUSE) :
	44	+# doublons de sous-agences masqués + « Prix sur demande » exclus.
	45	+VISIBLE = " AND dup_hidden=0 AND published=1"
	46	+
	47	+PERIOD_LABELS = {
	48	+ "auj": "Aujourd'hui", "7j": "7 jours", "30j": "30 jours",
	49	+ "3m": "3 mois", "6m": "6 mois", "12m": "12 mois",
	50	+ "annee": "Année en cours", "tout": "Toute la période",
	51	+}
	52	+
	53	+# --- cache serveur (>= 5 min par période, contrat SPEC) -----------------------
	54	+_CACHE: dict[str, tuple[float, dict]] = {}
	55	+_CACHE_TTL = 300
	56	+_CACHE_LOCK = threading.Lock()
	57	+
	58	+
	59	+# --- utilitaires --------------------------------------------------------------
	60	+def _today() -> date:
	61	+ return datetime.now(TZ).date()
	62	+
	63	+
	64	+def _iso(d: date) -> str:
	65	+ return d.isoformat()
	66	+
	67	+
	68	+def _parse(d: str) -> date \| None:
	69	+ try:
	70	+ return date.fromisoformat(d[:10])
	71	+ except (ValueError, TypeError):
	72	+ return None
	73	+
	74	+
	75	+def _epoch(d: date) -> float:
	76	+ """Minuit local (heure de l'Est) du jour donné, en epoch."""
	77	+ return datetime(d.year, d.month, d.day, tzinfo=TZ).timestamp()
	78	+
	79	+
	80	+def resolve_period(period: str \| None, frm: str \| None, to: str \| None,
	81	+ data_start: date) -> tuple[date, date, str]:
	82	+ today = _today()
	83	+ f, t = _parse(frm or ""), _parse(to or "")
	84	+ if f and t:
	85	+ if t < f:
	86	+ f, t = t, f
	87	+ return f, t, f"{_iso(f)} → {_iso(t)}"
	88	+ p = (period or "30j").lower()
	89	+ spans = {"7j": 6, "30j": 29, "3m": 89, "6m": 181, "12m": 364}
	90	+ if p == "auj":
	91	+ return today, today, PERIOD_LABELS["auj"]
	92	+ if p == "annee":
	93	+ return date(today.year, 1, 1), today, PERIOD_LABELS["annee"]
	94	+ if p == "tout":
	95	+ return data_start, today, PERIOD_LABELS["tout"]
	96	+ days = spans.get(p, 29)
	97	+ label = PERIOD_LABELS.get(p, PERIOD_LABELS["30j"])
	98	+ return today - timedelta(days=days), today, label
	99	+
	100	+
	101	+def _fold(s: str) -> str:
	102	+ return "".join(c for c in unicodedata.normalize("NFKD", s.lower().strip())
	103	+ if not unicodedata.combining(c))
	104	+
	105	+
	106	+def _median(vals: list[float]) -> float \| None:
	107	+ # défensif : la DB peut contenir des prix NULL — on les écarte
	108	+ vals = [v for v in vals if isinstance(v, (int, float))]
	109	+ return statistics.median(vals) if vals else None
	110	+
	111	+
	112	+def _fmt_money(v: float) -> str:
	113	+ return f"{round(v):,}".replace(",", " ") + " $"
	114	+
	115	+
	116	+def _fmt_pct(cur: float, prev: float) -> float \| None:
	117	+ if prev <= 0:
	118	+ return None
	119	+ return round((cur - prev) / prev * 100.0, 1)
	120	+
	121	+
	122	+def _daterange(a: date, b: date):
	123	+ d = a
	124	+ while d <= b:
	125	+ yield d
	126	+ d += timedelta(days=1)
	127	+
	128	+
	129	+def _source_names() -> dict[str, str]:
	130	+ """id -> nom lisible depuis data/sources.json (repli : id brut)."""
	131	+ try:
	132	+ reg = json.loads(SOURCES_PATH.read_text(encoding="utf-8"))["sources"]
	133	+ return {s["id"]: s.get("name") or s["id"] for s in reg}
	134	+ except (OSError, ValueError, KeyError, TypeError):
	135	+ return {}
	136	+
	137	+
	138	+# Familles de connecteurs (mêmes règles que web._FRANCHISES — dupliquées ici
	139	+# pour éviter l'import circulaire web ⇄ stats)
	140	+_FAMILLES = [
	141	+ ("RE/MAX", lambda s: s == "remax_quebec" or s.startswith("remax_ag_")),
	142	+ ("Via Capitale", lambda s: s == "via_capitale" or s.startswith("via_ag_")),
	143	+ ("Century 21", lambda s: s == "century21" or s.startswith("c21_ag_")),
	144	+ ("Royal LePage", lambda s: s == "royal_lepage"),
	145	+ ("Groupe Sutton", lambda s: s == "sutton"),
	146	+ ("Keller Williams", lambda s: s.startswith("kw_")),
	147	+ ("DuProprio", lambda s: s == "duproprio"),
	148	+ ("Vendre.ca", lambda s: s == "vendre_ag_ca"),
	149	+]
	150	+
	151	+
	152	+def _famille_of(source: str, names: dict[str, str]) -> str:
	153	+ for name, match in _FAMILLES:
	154	+ if match(source):
	155	+ return name
	156	+ return names.get(source, source)
	157	+
	158	+
	159	+def _downsample(pts: list[dict], keep: int = 40) -> list[dict]:
	160	+ """Réduit une série de points {t,v} à <= keep points (sparklines)."""
	161	+ if len(pts) <= keep:
	162	+ return pts
	163	+ step = (len(pts) - 1) / (keep - 1)
	164	+ return [pts[round(i * step)] for i in range(keep)]
	165	+
	166	+
	167	+# Libellés lisibles des motifs de quarantaine/anomalies (quality.py)
	168	+_MOTIFS_QUALITE = {
	169	+ "quarantaine": "Sous le seuil de publication",
	170	+ "sans_image": "Sans image (secours affiché)",
	171	+ "prix_hors_bornes": "Prix hors bornes",
	172	+ "superficie_improbable": "Superficie improbable",
	173	+ "terrain_improbable": "Terrain improbable",
	174	+ "chambres_improbables": "Chambres improbables",
	175	+ "sdb_improbables": "Salles de bain improbables",
	176	+ "chambres_vs_type": "Chambres vs type incohérents",
	177	+ "annee_invalide": "Année de construction invalide",
	178	+ "prix_pi2_extreme": "Prix au pi² extrême",
	179	+}
	180	+
	181	+
	182	+# --- calcul du tableau de bord ------------------------------------------------
	183	+def _compute(frm_q: str \| None, to_q: str \| None, period: str \| None) -> dict:
	184	+ con = db.connect()
	185	+ try:
	186	+ return _compute_con(con, frm_q, to_q, period)
	187	+ finally:
	188	+ con.close()
	189	+
	190	+
	191	+def _compute_con(con, frm_q, to_q, period) -> dict:
	192	+ today = _today()
	193	+ row = con.execute("SELECT MIN(first_seen) m FROM listings").fetchone()
	194	+ data_start = (datetime.fromtimestamp(row["m"], TZ).date()
	195	+ if row and row["m"] else today)
	196	+
	197	+ frm, to, label = resolve_period(period, frm_q, to_q, data_start)
	198	+ to = min(to, today)
	199	+ # fenêtre observée : la collecte a commencé le data_start — les séries
	200	+ # sont bornées à ce qui a réellement été mesuré (rien d'extrapolé).
	201	+ s_frm = max(frm, data_start)
	202	+ s_to = max(to, s_frm)
	203	+ ep_frm, ep_to = _epoch(s_frm), _epoch(s_to + timedelta(days=1))
	204	+ ndays = (s_to - s_frm).days + 1
	205	+ # période précédente de même longueur (pour les deltas)
	206	+ p_frm, p_to = s_frm - timedelta(days=ndays), s_frm - timedelta(days=1)
	207	+ # deltas seulement si la période précédente a été observée EN ENTIER —
	208	+ # comparer à une fenêtre tronquée fausserait les variations.
	209	+ prev_ok = p_frm >= data_start
	210	+ ep_pfrm, ep_pto = _epoch(p_frm), _epoch(p_to + timedelta(days=1))
	211	+
	212	+ # ---- reconstruction « annonces actives par jour » (événements) ----------
	213	+ actives_by_day: dict[str, int] = {}
	214	+ deltas: dict[date, int] = {}
	215	+ for r in con.execute(
	216	+ "SELECT date(first_seen,'unixepoch','localtime') fs,"
	217	+ " date(last_seen,'unixepoch','localtime') ls, active"
	218	+ " FROM listings WHERE 1=1" + VISIBLE):
	219	+ d0 = _parse(r["fs"])
	220	+ if d0 is None:
	221	+ continue
	222	+ deltas[d0] = deltas.get(d0, 0) + 1
	223	+ if not r["active"]:
	224	+ d1 = (_parse(r["ls"]) or d0) + timedelta(days=1)
	225	+ deltas[d1] = deltas.get(d1, 0) - 1
	226	+ run = 0
	227	+ for d in _daterange(data_start, today):
	228	+ run += deltas.get(d, 0)
	229	+ actives_by_day[_iso(d)] = run
	230	+
	231	+ # ---- KPI -----------------------------------------------------------------
	232	+ snap = con.execute(
	233	+ "SELECT COUNT(*) n, AVG(price) avg_p,"
	234	+ " COUNT(DISTINCT NULLIF(city,'')) cities"
	235	+ " FROM listings WHERE active=1" + VISIBLE).fetchone()
	236	+ prices = [r["price"] for r in con.execute(
	237	+ "SELECT price FROM listings WHERE active=1" + VISIBLE)]
	238	+ med_price = _median(prices)
	239	+ ppm2 = [r["v"] for r in con.execute(
	240	+ "SELECT price/(area_sqft/" + str(SQFT_PER_M2) + ") v FROM listings"
	241	+ " WHERE active=1 AND area_sqft>=200" + VISIBLE)]
	242	+ med_ppm2 = _median(ppm2)
	243	+ n_ppm2 = len(ppm2)
	244	+
	245	+ new_cur = con.execute(
	246	+ "SELECT COUNT(*) n FROM listings WHERE first_seen>=? AND first_seen<?"
	247	+ + VISIBLE, (ep_frm, ep_to)).fetchone()["n"]
	248	+ new_prev = con.execute(
	249	+ "SELECT COUNT(*) n FROM listings WHERE first_seen>=? AND first_seen<?"
	250	+ + VISIBLE, (ep_pfrm, ep_pto)).fetchone()["n"] if prev_ok else 0
	251	+ gone_cur = con.execute(
	252	+ "SELECT COUNT(*) n FROM listings WHERE active=0 AND last_seen>=?"
	253	+ " AND last_seen<?" + VISIBLE, (ep_frm, ep_to)).fetchone()["n"]
	254	+ gone_prev = con.execute(
	255	+ "SELECT COUNT(*) n FROM listings WHERE active=0 AND last_seen>=?"
	256	+ " AND last_seen<?" + VISIBLE, (ep_pfrm, ep_pto)).fetchone()["n"] if prev_ok else 0
	257	+ conn_cur = con.execute(
	258	+ "SELECT COUNT(DISTINCT source) n FROM sync_log WHERE ok=1 AND ts>=?"
	259	+ " AND ts<?", (ep_frm, ep_to)).fetchone()["n"]
	260	+
	261	+ act_now = snap["n"]
	262	+ act_prev = actives_by_day.get(_iso(p_to)) if prev_ok else None
	263	+
	264	+ def kpi(id_, lbl, val, unit="", dpct=None):
	265	+ k = {"id": id_, "label": lbl, "value": val, "unit": unit}
	266	+ if dpct is not None:
	267	+ k["delta_pct"] = dpct
	268	+ k["direction"] = "up" if dpct >= 0 else "down"
	269	+ return k
	270	+
	271	+ kpis = [
	272	+ kpi("actives", "Annonces actives", act_now, "",
	273	+ _fmt_pct(act_now, act_prev) if act_prev else None),
	274	+ kpi("nouvelles", "Nouvelles annonces (période)", new_cur, "",
	275	+ _fmt_pct(new_cur, new_prev) if prev_ok and new_prev else None),
	276	+ kpi("retirees", "Vendues / retirées (période)", gone_cur, "",
	277	+ _fmt_pct(gone_cur, gone_prev) if prev_ok and gone_prev else None),
	278	+ ]
	279	+ if snap["avg_p"]:
	280	+ kpis.append(kpi("prix_moyen", "Prix moyen demandé",
	281	+ round(snap["avg_p"]), "$"))
	282	+ if med_price:
	283	+ kpis.append(kpi("prix_median", "Prix médian demandé",
	284	+ round(med_price), "$"))
	285	+ if med_ppm2 and n_ppm2 >= 100:
	286	+ kpis.append(kpi("prix_m2",
	287	+ f"Prix médian au m² ({n_ppm2:,} annonces avec superficie)".replace(",", " "),
	288	+ round(med_ppm2), "$/m²"))
	289	+ # prix au pi² déclaré à la source (details.prix_pi2) — médiane
	290	+ ppi2 = [r["v"] for r in con.execute(
	291	+ "SELECT CAST(json_extract(details,'$.prix_pi2') AS REAL) v"
	292	+ " FROM listings WHERE active=1" + VISIBLE +
	293	+ " AND CAST(json_extract(details,'$.prix_pi2') AS REAL)"
	294	+ " BETWEEN 30 AND 10000")]
	295	+ med_ppi2 = _median(ppi2)
	296	+ if med_ppi2 and len(ppi2) >= 100:
	297	+ kpis.append(kpi(
	298	+ "prix_pi2",
	299	+ f"Prix médian au pi² ({len(ppi2):,} annonces le déclarant)".replace(",", " "),
	300	+ round(med_ppi2), "$/pi²"))
	301	+ # jours sur le marché (annonces actives) — médiane depuis first_seen
	302	+ now_ts = time.time()
	303	+ dom = [max((now_ts - r["fs"]) / 86400.0, 0.0) for r in con.execute(
	304	+ "SELECT first_seen fs FROM listings WHERE active=1" + VISIBLE)]
	305	+ med_dom = _median(dom)
	306	+ if med_dom is not None and dom:
	307	+ kpis.append(kpi("jours_marche", "Jours sur le marché (médiane, actives)",
	308	+ round(med_dom, 1), "j"))
	309	+ # baisses de prix observées dans la période (journal price_log) —
	310	+ # une entrée par annonce, bornes de plausibilité (voir en tête de fichier)
	311	+ drops = con.execute(
	312	+ """SELECT l.city city, MAX(p1.price - p2.price) amt,
	313	+ date(MAX(p2.ts),'unixepoch','localtime') dt
	314	+ FROM price_log p1
	315	+ JOIN price_log p2 ON p2.uid = p1.uid AND p2.ts > p1.ts
	316	+ JOIN listings l ON l.uid = p1.uid
	317	+ WHERE p2.ts>=? AND p2.ts<? AND p2.price < p1.price
	318	+ AND p1.price BETWEEN ? AND ? AND p2.price BETWEEN ? AND ?
	319	+ AND p2.price >= p1.price * 0.5 AND l.dup_hidden=0 AND l.published=1
	320	+ GROUP BY l.uid ORDER BY amt DESC""",
	321	+ (ep_frm, ep_to, PRICE_MIN, PRICE_MAX, PRICE_MIN, PRICE_MAX)).fetchall()
	322	+ kpis.append(kpi("baisses_prix", "Baisses de prix observées (période)",
	323	+ len(drops)))
	324	+ # qualité des données (quality.py) : score moyen + quarantaine
	325	+ qual = con.execute(
	326	+ "SELECT ROUND(AVG(quality_score),1) c FROM listings WHERE active=1"
	327	+ + VISIBLE).fetchone()
	328	+ quar = con.execute(
	329	+ "SELECT COUNT(*) n FROM listings"
	330	+ " WHERE active=1 AND dup_hidden=0 AND published=0").fetchone()["n"]
	331	+ if qual["c"] is not None:
	332	+ kpis.append(kpi("qualite", "Score de qualité moyen des fiches",
	333	+ qual["c"], "/100"))
	334	+ kpis.append(kpi("quarantaine", "Annonces en quarantaine (qualité)",
	335	+ quar))
	336	+ # position des prix vs estimation Vrai-Prix (juste valeur) — un seul
	337	+ # balayage réutilisé par le KPI, l'anneau et le tableau par ville
	338	+ b_lo, b_hi = FV_DEV_BOUNDS
	339	+ fv_rows = con.execute(
	340	+ "SELECT city, (price - CAST(json_extract(vraiprix,'$.value') AS REAL))"
	341	+ " / CAST(json_extract(vraiprix,'$.value') AS REAL) dev"
	342	+ " FROM listings WHERE active=1" + VISIBLE +
	343	+ " AND CAST(json_extract(vraiprix,'$.value') AS REAL) > 0"
	344	+ " AND price BETWEEN ? AND ?", (PRICE_MIN, PRICE_MAX)).fetchall()
	345	+ fv_sous = fv_marche = fv_sur = 0
	346	+ fv_city: dict[str, list[float]] = {}
	347	+ for r in fv_rows:
	348	+ dev = r["dev"]
	349	+ if dev is None or not (b_lo < dev < b_hi):
	350	+ continue
	351	+ if dev <= FV_SEUIL_SOUS:
	352	+ fv_sous += 1
	353	+ elif dev >= FV_SEUIL_SUR:
	354	+ fv_sur += 1
	355	+ else:
	356	+ fv_marche += 1
	357	+ if r["city"]:
	358	+ fv_city.setdefault(r["city"], []).append(dev)
	359	+ fv_n = fv_sous + fv_marche + fv_sur
	360	+ if fv_n:
	361	+ kpis.append(kpi("sous_marche", "Annonces sous l'estimation Vrai-Prix",
	362	+ fv_sous))
	363	+ kpis.append(kpi("villes", "Villes couvertes", snap["cities"]))
	364	+ kpis.append(kpi("connecteurs", "Connecteurs actifs (période)", conn_cur))
	365	+ # indice de tension : retraits / nouvelles entrées (mesuré, pas modélisé)
	366	+ if new_cur >= 50:
	367	+ kpis.append(kpi("tension", "Tension — retraits / nouvelles",
	368	+ round(100.0 * gone_cur / new_cur, 1), "%"))
	369	+
	370	+ # ---- jauges (v2) : couvertures mesurées sur les annonces publiées --------
	371	+ gauges: list[dict] = []
	372	+ if act_now:
	373	+ g_geo = con.execute(
	374	+ "SELECT COUNT(*) n FROM listings WHERE active=1"
	375	+ " AND lat IS NOT NULL AND lng IS NOT NULL" + VISIBLE).fetchone()["n"]
	376	+ g_photo = con.execute(
	377	+ "SELECT COUNT(*) n FROM listings WHERE active=1"
	378	+ " AND images IS NOT NULL AND images<>'' AND images<>'[]'"
	379	+ + VISIBLE).fetchone()["n"]
	380	+ g_vp = con.execute(
	381	+ "SELECT COUNT(*) n FROM listings WHERE active=1" + VISIBLE +
	382	+ " AND CAST(json_extract(vraiprix,'$.value') AS REAL) > 0"
	383	+ ).fetchone()["n"]
	384	+ gauges.append({"id": "geoloc", "label": "Fiches géolocalisées",
	385	+ "value": round(100.0 * g_geo / act_now, 1),
	386	+ "max": 100, "unit": "%"})
	387	+ gauges.append({"id": "photos", "label": "Fiches avec photos",
	388	+ "value": round(100.0 * g_photo / act_now, 1),
	389	+ "max": 100, "unit": "%"})
	390	+ if g_vp:
	391	+ gauges.append({"id": "vraiprix",
	392	+ "label": "Fiches avec estimation Vrai-Prix",
	393	+ "value": round(100.0 * g_vp / act_now, 1),
	394	+ "max": 100, "unit": "%"})
	395	+ act_all = con.execute(
	396	+ "SELECT COUNT(*) n FROM listings WHERE active=1 AND dup_hidden=0"
	397	+ ).fetchone()["n"]
	398	+ if act_all:
	399	+ gauges.append({"id": "publiable",
	400	+ "label": "Hors quarantaine (qualité publiable)",
	401	+ "value": round(100.0 * (act_all - quar) / act_all, 1),
	402	+ "max": 100, "unit": "%"})
	403	+ if qual["c"] is not None:
	404	+ gauges.append({"id": "completude",
	405	+ "label": "Complétude moyenne des fiches (0–100)",
	406	+ "value": qual["c"], "max": 100})
	407	+
	408	+ # ---- séries quotidiennes ---------------------------------------------------
	409	+ days = [_iso(d) for d in _daterange(s_frm, s_to)]
	410	+ new_by_day = {r["d"]: r["n"] for r in con.execute(
	411	+ "SELECT date(first_seen,'unixepoch','localtime') d, COUNT(*) n"
	412	+ " FROM listings WHERE first_seen>=? AND first_seen<?" + VISIBLE +
	413	+ " GROUP BY d", (ep_frm, ep_to))}
	414	+ gone_by_day = {r["d"]: r["n"] for r in con.execute(
	415	+ "SELECT date(last_seen,'unixepoch','localtime') d, COUNT(*) n"
	416	+ " FROM listings WHERE active=0 AND last_seen>=? AND last_seen<?"
	417	+ + VISIBLE + " GROUP BY d", (ep_frm, ep_to))}
	418	+ series = []
	419	+ if len(days) >= 2:
	420	+ series = [
	421	+ {"id": "actives", "title": "Annonces actives par jour",
	422	+ "unit": "annonces", "kind": "line",
	423	+ "points": [{"t": d, "v": actives_by_day.get(d, 0)} for d in days]},
	424	+ {"id": "nouvelles", "title": "Nouvelles annonces par jour",
	425	+ "unit": "annonces", "kind": "bar",
	426	+ "points": [{"t": d, "v": new_by_day.get(d, 0)} for d in days]},
	427	+ {"id": "retraits", "title": "Retraits (vendues / retirées) par jour",
	428	+ "unit": "annonces", "kind": "bar",
	429	+ "points": [{"t": d, "v": gone_by_day.get(d, 0)} for d in days]},
	430	+ ]
	431	+ # prix médian demandé des nouvelles inscriptions (jours à >= 3 entrées
	432	+ # seulement — rien d'interpolé, l'axe saute les jours creux)
	433	+ med_day: list[dict] = []
	434	+ day_prices: dict[str, list[float]] = {}
	435	+ for r in con.execute(
	436	+ "SELECT date(first_seen,'unixepoch','localtime') d, price"
	437	+ " FROM listings WHERE first_seen>=? AND first_seen<?" + VISIBLE +
	438	+ " AND price BETWEEN ? AND ?",
	439	+ (ep_frm, ep_to, PRICE_MIN, PRICE_MAX)):
	440	+ day_prices.setdefault(r["d"], []).append(r["price"])
	441	+ for d in days:
	442	+ ps = day_prices.get(d)
	443	+ if ps and len(ps) >= 3:
	444	+ med_day.append({"t": d, "v": round(statistics.median(ps))})
	445	+ if len(med_day) >= 5:
	446	+ series.append({
	447	+ "id": "prix_median_nouvelles",
	448	+ "title": "Prix médian demandé des nouvelles inscriptions"
	449	+ " (jours à ≥ 3 entrées)",
	450	+ "unit": "$", "kind": "area", "points": med_day})
	451	+ # comparaison période précédente (même longueur) : seulement si elle
	452	+ # a réellement été observée en entier (rien d'extrapolé)
	453	+ if prev_ok:
	454	+ pdays = [_iso(d) for d in _daterange(p_frm, p_to)]
	455	+ series[0]["compare"] = [{"t": d, "v": actives_by_day.get(d, 0)}
	456	+ for d in pdays]
	457	+ cmp_new = {r["d"]: r["n"] for r in con.execute(
	458	+ "SELECT date(first_seen,'unixepoch','localtime') d, COUNT(*) n"
	459	+ " FROM listings WHERE first_seen>=? AND first_seen<?" + VISIBLE +
	460	+ " GROUP BY d", (ep_pfrm, ep_pto))}
	461	+ series[1]["compare"] = [{"t": d, "v": cmp_new.get(d, 0)}
	462	+ for d in pdays]
	463	+
	464	+ # ---- sparklines des KPI (v2) — mêmes données que les séries ---------------
	465	+ if len(days) >= 2:
	466	+ conn_day = {r["d"]: r["n"] for r in con.execute(
	467	+ "SELECT date(ts,'unixepoch','localtime') d,"
	468	+ " COUNT(DISTINCT source) n FROM sync_log"
	469	+ " WHERE ok=1 AND ts>=? AND ts<? GROUP BY d", (ep_frm, ep_to))}
	470	+ sparks = {
	471	+ "actives": [{"t": d, "v": actives_by_day.get(d, 0)} for d in days],
	472	+ "nouvelles": [{"t": d, "v": new_by_day.get(d, 0)} for d in days],
	473	+ "retirees": [{"t": d, "v": gone_by_day.get(d, 0)} for d in days],
	474	+ "connecteurs": [{"t": d, "v": conn_day.get(d, 0)} for d in days],
	475	+ }
	476	+ for k in kpis:
	477	+ sp = sparks.get(k["id"])
	478	+ if sp and any(p["v"] for p in sp):
	479	+ k["spark"] = _downsample(sp)
	480	+
	481	+ # ---- multi-courbes (v2) : prix médian des nouvelles inscriptions ----------
	482	+ # Buckets quotidiens (<= 45 j) ou hebdomadaires ; un bucket n'est gardé que
	483	+ # si CHAQUE groupe y compte >= 3 inscriptions (axes alignés, rien d'inventé).
	484	+ def _multiserie(id_, title, group_sql, top_n):
	485	+ weekly = ndays > 45
	486	+ bucket_sql = ("strftime('%Y-%m-%d', first_seen, 'unixepoch',"
	487	+ " 'localtime', 'weekday 1', '-6 days')" if weekly else
	488	+ "date(first_seen,'unixepoch','localtime')")
	489	+ rows = con.execute(
	490	+ f"SELECT {group_sql} g, {bucket_sql} b, price FROM listings"
	491	+ " WHERE first_seen>=? AND first_seen<?" + VISIBLE +
	492	+ f" AND price BETWEEN ? AND ? AND {group_sql} <> ''",
	493	+ (ep_frm, ep_to, PRICE_MIN, PRICE_MAX)).fetchall()
	494	+ vol: dict[str, int] = {}
	495	+ data: dict[str, dict[str, list[float]]] = {}
	496	+ for r in rows:
	497	+ if "/" in r["g"]: # libellés composites de sources ("Laval /
	498	+ continue # North Shore") — bruit, pas une vraie ville
	499	+ vol[r["g"]] = vol.get(r["g"], 0) + 1
	500	+ data.setdefault(r["g"], {}).setdefault(r["b"], []).append(r["price"])
	501	+ groups = [g for g, _ in sorted(vol.items(), key=lambda kv: -kv[1])[:top_n]]
	502	+ if len(groups) < 2:
	503	+ return None
	504	+ buckets = sorted({b for g in groups for b in data[g]
	505	+ if all(len(data[gg].get(b, [])) >= 3 for gg in groups)})
	506	+ if len(buckets) < 4:
	507	+ return None
	508	+ return {"id": id_, "title": title + (" (semaines)" if weekly else ""),
	509	+ "unit": "$",
	510	+ "series": [{"label": g, "points": [
	511	+ {"t": b, "v": round(statistics.median(data[g][b]))}
	512	+ for b in buckets]} for g in groups]}
	513	+
	514	+ multiseries = []
	515	+ ms_type = _multiserie(
	516	+ "prix_type", "Prix médian des nouvelles inscriptions par type",
	517	+ "property_type", 3)
	518	+ if ms_type:
	519	+ multiseries.append(ms_type)
	520	+ ms_ville = _multiserie(
	521	+ "prix_ville", "Prix médian des nouvelles inscriptions — grandes villes",
	522	+ "city", 4)
	523	+ if ms_ville:
	524	+ multiseries.append(ms_ville)
	525	+
	526	+ # ---- barres empilées (v2) : nouvelles inscriptions par bannière -----------
	527	+ names = _source_names()
	528	+ stacked = []
	529	+ if len(days) >= 2:
	530	+ weekly_st = ndays > 60
	531	+ bucket_st = ("strftime('%Y-%m-%d', first_seen, 'unixepoch',"
	532	+ " 'localtime', 'weekday 1', '-6 days')" if weekly_st else
	533	+ "date(first_seen,'unixepoch','localtime')")
	534	+ fam_day: dict[str, dict[str, int]] = {}
	535	+ fam_tot: dict[str, int] = {}
	536	+ for r in con.execute(
	537	+ f"SELECT source s, {bucket_st} b, COUNT(*) n FROM listings"
	538	+ " WHERE first_seen>=? AND first_seen<?" + VISIBLE +
	539	+ " GROUP BY source, b", (ep_frm, ep_to)):
	540	+ fam = _famille_of(r["s"], names)
	541	+ fam_day.setdefault(fam, {})
	542	+ fam_day[fam][r["b"]] = fam_day[fam].get(r["b"], 0) + r["n"]
	543	+ fam_tot[fam] = fam_tot.get(fam, 0) + r["n"]
	544	+ if fam_tot:
	545	+ top_fams = [f for f, _ in
	546	+ sorted(fam_tot.items(), key=lambda kv: -kv[1])[:5]]
	547	+ others = [f for f in fam_day if f not in top_fams]
	548	+ keys = top_fams + (["Autres"] if others else [])
	549	+ buckets_st = sorted({b for d_ in fam_day.values() for b in d_})
	550	+ pts = []
	551	+ for b in buckets_st:
	552	+ vals = [fam_day[f].get(b, 0) for f in top_fams]
	553	+ if others:
	554	+ vals.append(sum(fam_day[f].get(b, 0) for f in others))
	555	+ pts.append({"t": b, "values": vals})
	556	+ if len(pts) >= 2:
	557	+ stacked.append({
	558	+ "id": "ajouts_bannieres",
	559	+ "title": "Nouvelles inscriptions par bannière"
	560	+ + (" (semaines)" if weekly_st else ""),
	561	+ "unit": "inscriptions", "keys": keys, "points": pts})
	562	+
	563	+ # ---- distributions (v2) : prix, superficie, année de construction ---------
	564	+ distributions = []
	565	+ price_bins = [("< 100 k$", 0, 100e3)] + [
	566	+ (f"{i}00–{i+1}00 k$", i * 100e3, (i + 1) * 100e3) for i in range(1, 10)
	567	+ ] + [("1–1,5 M$", 1e6, 1.5e6), ("1,5–2 M$", 1.5e6, 2e6),
	568	+ ("2 M$ +", 2e6, None)]
	569	+ bins_p = []
	570	+ for lbl, lo, hi in price_bins:
	571	+ q = ("SELECT COUNT(*) n FROM listings WHERE active=1 AND price>=?"
	572	+ + VISIBLE)
	573	+ args: list = [lo]
	574	+ if hi is not None:
	575	+ q += " AND price<?"
	576	+ args.append(hi)
	577	+ bins_p.append({"label": lbl,
	578	+ "value": con.execute(q, args).fetchone()["n"]})
	579	+ if sum(b["value"] for b in bins_p):
	580	+ distributions.append({
	581	+ "id": "prix", "unit": "annonces",
	582	+ "title": "Distribution des prix demandés (annonces actives)",
	583	+ "bins": bins_p})
	584	+ area_bins = [("< 500", 100, 500), ("500–1 000", 500, 1000),
	585	+ ("1 000–1 500", 1000, 1500), ("1 500–2 000", 1500, 2000),
	586	+ ("2 000–2 500", 2000, 2500), ("2 500–3 000", 2500, 3000),
	587	+ ("3 000–4 000", 3000, 4000), ("4 000 +", 4000, 20000)]
	588	+ bins_a = [{"label": f"{lbl} pi²",
	589	+ "value": con.execute(
	590	+ "SELECT COUNT(*) n FROM listings WHERE active=1"
	591	+ " AND area_sqft>=? AND area_sqft<?" + VISIBLE,
	592	+ (lo, hi)).fetchone()["n"]}
	593	+ for lbl, lo, hi in area_bins]
	594	+ if sum(b["value"] for b in bins_a) >= 100:
	595	+ distributions.append({
	596	+ "id": "superficie", "unit": "annonces",
	597	+ "title": "Distribution des superficies habitables (renseignées)",
	598	+ "bins": bins_a})
	599	+ yr_now = today.year
	600	+ year_bins = ([("< 1900", 1600, 1900), ("1900–1949", 1900, 1950)] +
	601	+ [(f"{d}–{d+9}", d, d + 10) for d in range(1950, 2020, 10)] +
	602	+ [("2020 +", 2020, yr_now + 2)])
	603	+ bins_y = [{"label": lbl,
	604	+ "value": con.execute(
	605	+ "SELECT COUNT(*) n FROM listings WHERE active=1"
	606	+ " AND year_built>=? AND year_built<?" + VISIBLE,
	607	+ (lo, hi)).fetchone()["n"]}
	608	+ for lbl, lo, hi in year_bins]
	609	+ if sum(b["value"] for b in bins_y) >= 100:
	610	+ distributions.append({
	611	+ "id": "annee", "unit": "annonces",
	612	+ "title": "Distribution des années de construction (renseignées)",
	613	+ "bins": bins_y})
	614	+
	615	+ # ---- heatmap horaire (v2) : détection des nouvelles annonces (7×24) -------
	616	+ # first_seen = moment où la synchronisation a détecté l'annonce — c'est le
	617	+ # rythme réel d'alimentation de la plateforme (8 dernières semaines).
	618	+ h56 = _epoch(max(data_start, s_to - timedelta(days=55)))
	619	+ hourly_cells = [
	620	+ {"dow": (int(r["w"]) + 6) % 7, "hour": int(r["h"]), "value": r["n"]}
	621	+ for r in con.execute(
	622	+ "SELECT strftime('%w', first_seen,'unixepoch','localtime') w,"
	623	+ " strftime('%H', first_seen,'unixepoch','localtime') h, COUNT(*) n"
	624	+ " FROM listings WHERE first_seen>=? AND first_seen<?" + VISIBLE +
	625	+ " GROUP BY w, h", (h56, _epoch(s_to + timedelta(days=1))))]
	626	+ hourly = ({"title": "Détection de nouvelles annonces par heure"
	627	+ " (8 dernières semaines)", "cells": hourly_cells}
	628	+ if len(hourly_cells) >= 12 else None)
	629	+
	630	+ # ---- répartitions (photo des annonces actives) -----------------------------
	631	+ types = [{"label": r["t"] or "Autre / non précisé", "value": r["n"]}
	632	+ for r in con.execute(
	633	+ "SELECT property_type t, COUNT(*) n FROM listings"
	634	+ " WHERE active=1" + VISIBLE +
	635	+ " GROUP BY property_type ORDER BY n DESC LIMIT 9")]
	636	+ ranges = [("Moins de 200 k$", 0, 200e3), ("200 – 300 k$", 200e3, 300e3),
	637	+ ("300 – 400 k$", 300e3, 400e3), ("400 – 500 k$", 400e3, 500e3),
	638	+ ("500 – 750 k$", 500e3, 750e3), ("750 k$ – 1 M$", 750e3, 1e6),
	639	+ ("1 – 2 M$", 1e6, 2e6), ("2 M$ et plus", 2e6, None)]
	640	+ price_items = []
	641	+ for lbl, lo, hi in ranges:
	642	+ q = "SELECT COUNT(*) n FROM listings WHERE active=1 AND price>=?" + VISIBLE
	643	+ args: list = [lo]
	644	+ if hi is not None:
	645	+ q += " AND price<?"
	646	+ args.append(hi)
	647	+ price_items.append({"label": lbl,
	648	+ "value": con.execute(q, args).fetchone()["n"]})
	649	+ # nouvelles inscriptions de la période par fourchette + delta honnête
	650	+ # (vs période précédente entièrement observée seulement)
	651	+ new_price_items = []
	652	+ for lbl, lo, hi in ranges:
	653	+ base = ("SELECT COUNT(*) n FROM listings WHERE first_seen>=?"
	654	+ " AND first_seen<? AND price>=?" + VISIBLE)
	655	+ args_c: list = [ep_frm, ep_to, lo]
	656	+ args_p: list = [ep_pfrm, ep_pto, lo]
	657	+ if hi is not None:
	658	+ base += " AND price<?"
	659	+ args_c.append(hi)
	660	+ args_p.append(hi)
	661	+ n_c = con.execute(base, args_c).fetchone()["n"]
	662	+ item = {"label": lbl, "value": n_c}
	663	+ if prev_ok:
	664	+ n_p = con.execute(base, args_p).fetchone()["n"]
	665	+ if n_p:
	666	+ item["delta_pct"] = _fmt_pct(n_c, n_p)
	667	+ new_price_items.append(item)
	668	+ beds = [{"label": ("8 chambres et +" if r["b"] >= 8
	669	+ else f"{int(r['b'])} chambre" + ("s" if r["b"] > 1 else "")),
	670	+ "value": r["n"]}
	671	+ for r in con.execute(
	672	+ "SELECT MIN(bedrooms,8) b, COUNT(*) n FROM listings"
	673	+ " WHERE active=1 AND bedrooms IS NOT NULL" + VISIBLE +
	674	+ " GROUP BY MIN(bedrooms,8) ORDER BY b")]
	675	+ names = _source_names()
	676	+ by_source = [{"label": names.get(r["s"], r["s"]), "value": r["n"]}
	677	+ for r in con.execute(
	678	+ "SELECT source s, COUNT(*) n FROM listings"
	679	+ " WHERE active=1" + VISIBLE +
	680	+ " GROUP BY source ORDER BY n DESC LIMIT 12")]
	681	+ breakdowns = []
	682	+ if fv_n:
	683	+ breakdowns.append({
	684	+ "id": "fairvalue",
	685	+ "title": "Position des prix demandés vs estimation Vrai-Prix",
	686	+ "kind": "donut", "items": [
	687	+ {"label": "Sous le marché", "value": fv_sous},
	688	+ {"label": "Dans le marché", "value": fv_marche},
	689	+ {"label": "Au-dessus du marché", "value": fv_sur}]})
	690	+ breakdowns += [
	691	+ {"id": "types", "title": "Répartition par type de propriété",
	692	+ "kind": "donut", "items": types},
	693	+ {"id": "prix", "title": "Répartition par fourchette de prix demandé",
	694	+ "kind": "bar", "items": price_items},
	695	+ ]
	696	+ if sum(i["value"] for i in new_price_items):
	697	+ breakdowns.append({
	698	+ "id": "prix_nouvelles",
	699	+ "title": "Nouvelles inscriptions par fourchette de prix (période)",
	700	+ "kind": "bar", "items": new_price_items})
	701	+ if beds:
	702	+ breakdowns.append({"id": "chambres",
	703	+ "title": "Répartition par nombre de chambres (renseignées)",
	704	+ "kind": "bar", "items": beds})
	705	+ if by_source:
	706	+ breakdowns.append({"id": "sources",
	707	+ "title": "Top sources (annonces actives)",
	708	+ "kind": "bar", "items": by_source})
	709	+
	710	+ # ---- géographie : par région (fusion accents/casse, libellé le + fréquent)
	711	+ reg_counts: dict[str, dict[str, int]] = {}
	712	+ for r in con.execute(
	713	+ "SELECT region, COUNT(*) n FROM listings WHERE active=1"
	714	+ " AND region<>''" + VISIBLE + " GROUP BY region"):
	715	+ raw = (r["region"] or "").strip()
	716	+ key = _fold(raw)
	717	+ if not key or key.isdigit():
	718	+ continue
	719	+ reg_counts.setdefault(key, {})[raw] = reg_counts.get(key, {}).get(raw, 0) + r["n"]
	720	+ geo_items = []
	721	+ for key, variants in reg_counts.items():
	722	+ best_variant = max(variants, key=variants.get)
	723	+ geo_items.append({"label": best_variant, "value": sum(variants.values())})
	724	+ geo_items.sort(key=lambda x: -x["value"])
	725	+ geo = ({"title": "Annonces actives par région", "items": geo_items[:14]}
	726	+ if geo_items else None)
	727	+
	728	+ # ---- heatmap : nouvelles annonces par jour (26 dernières semaines max) ----
	729	+ h_frm = max(data_start, s_to - timedelta(days=181))
	730	+ hm = [{"date": r["d"], "value": r["n"]} for r in con.execute(
	731	+ "SELECT date(first_seen,'unixepoch','localtime') d, COUNT(*) n"
	732	+ " FROM listings WHERE first_seen>=? AND first_seen<?" + VISIBLE +
	733	+ " GROUP BY d", (_epoch(h_frm), _epoch(s_to + timedelta(days=1))))]
	734	+ heatmap = ({"title": "Nouvelles annonces par jour", "cells": hm}
	735	+ if len(hm) >= 2 else None)
	736	+
	737	+ # ---- tableaux ---------------------------------------------------------------
	738	+ # Top villes : actives, prix moyen/médian, nouvelles sur la période + delta
	739	+ city_prices: dict[str, list[float]] = {}
	740	+ for r in con.execute(
	741	+ "SELECT city, price FROM listings WHERE active=1 AND city<>''"
	742	+ + VISIBLE):
	743	+ city_prices.setdefault(r["city"], []).append(r["price"])
	744	+ new_city = {r["city"]: r["n"] for r in con.execute(
	745	+ "SELECT city, COUNT(*) n FROM listings WHERE city<>''"
	746	+ " AND first_seen>=? AND first_seen<?" + VISIBLE + " GROUP BY city",
	747	+ (ep_frm, ep_to))}
	748	+ new_city_prev = {r["city"]: r["n"] for r in con.execute(
	749	+ "SELECT city, COUNT(*) n FROM listings WHERE city<>''"
	750	+ " AND first_seen>=? AND first_seen<?" + VISIBLE + " GROUP BY city",
	751	+ (ep_pfrm, ep_pto))} if prev_ok else {}
	752	+ gone_city = {r["city"]: r["n"] for r in con.execute(
	753	+ "SELECT city, COUNT(*) n FROM listings WHERE active=0 AND city<>''"
	754	+ " AND last_seen>=? AND last_seen<?" + VISIBLE + " GROUP BY city",
	755	+ (ep_frm, ep_to))}
	756	+ top = sorted(city_prices.items(), key=lambda kv: -len(kv[1]))[:50]
	757	+ top_rows = []
	758	+ for city, ps in top:
	759	+ n_new = new_city.get(city, 0)
	760	+ n_prev = new_city_prev.get(city, 0)
	761	+ net = n_new - gone_city.get(city, 0)
	762	+ d = _fmt_pct(n_new, n_prev) if prev_ok and n_prev else None
	763	+ pn = [v for v in ps if isinstance(v, (int, float))] # prix NULL écartés
	764	+ top_rows.append([
	765	+ city, len(ps),
	766	+ _fmt_money(sum(pn) / len(pn)) if pn else "—",
	767	+ _fmt_money(statistics.median(pn)) if pn else "—", n_new,
	768	+ f"{'+' if net >= 0 else ''}{net}",
	769	+ (f"{'+' if d >= 0 else ''}{str(d).replace('.', ',')} %"
	770	+ if d is not None else "—"),
	771	+ ])
	772	+ tables = [{
	773	+ "id": "top_villes", "title": "Top villes",
	774	+ "columns": ["Ville", "Actives", "Prix moyen", "Prix médian",
	775	+ "Nouvelles (période)", "Δ net (période)", "Var. nouvelles"],
	776	+ "rows": top_rows,
	777	+ }]
	778	+ # Top sources : actives, prix moyen, nouvelles, qualité, quarantaine, synchro
	779	+ top_srcs = con.execute(
	780	+ """SELECT source s, COUNT(*) n,
	781	+ AVG(CASE WHEN price>0 THEN price END) avg_p,
	782	+ SUM(CASE WHEN first_seen>=? AND first_seen<? THEN 1 ELSE 0 END) new_n,
	783	+ ROUND(AVG(quality_score),0) qual
	784	+ FROM listings WHERE active=1""" + VISIBLE +
	785	+ " GROUP BY source ORDER BY n DESC LIMIT 50", (ep_frm, ep_to)).fetchall()
	786	+ quar_src = {r["s"]: r["n"] for r in con.execute(
	787	+ "SELECT source s, COUNT(*) n FROM listings"
	788	+ " WHERE active=1 AND dup_hidden=0 AND published=0 GROUP BY source")}
	789	+ last_sync = {r["source"]: r["ts"] for r in con.execute(
	790	+ "SELECT source, MAX(ts) ts FROM sync_log WHERE ok=1 GROUP BY source")}
	791	+ if top_srcs:
	792	+ src_rows = []
	793	+ for r in top_srcs:
	794	+ ls = last_sync.get(r["s"])
	795	+ src_rows.append([
	796	+ names.get(r["s"], r["s"]), r["n"],
	797	+ _fmt_money(r["avg_p"]) if r["avg_p"] else "—",
	798	+ r["new_n"],
	799	+ f"{r['qual']:.0f} /100" if r["qual"] is not None else "—",
	800	+ quar_src.get(r["s"], 0),
	801	+ (datetime.fromtimestamp(ls, TZ).strftime("%Y-%m-%d %H:%M")
	802	+ if ls else "—")])
	803	+ tables.append({
	804	+ "id": "top_sources", "title": "Top sources & courtiers",
	805	+ "columns": ["Source", "Annonces actives", "Prix moyen",
	806	+ "Nouvelles (période)", "Qualité", "Quarantaine",
	807	+ "Dernière synchro"],
	808	+ "rows": src_rows})
	809	+ # Délai de présence (retirées de la période) par ville
	810	+ dur_city: dict[str, list[float]] = {}
	811	+ for r in con.execute(
	812	+ "SELECT city, (last_seen-first_seen)/86400.0 d FROM listings"
	813	+ " WHERE active=0 AND city<>'' AND last_seen>=? AND last_seen<?"
	814	+ + VISIBLE, (ep_frm, ep_to)):
	815	+ dur_city.setdefault(r["city"], []).append(max(r["d"], 0.0))
	816	+ dur_rows = []
	817	+ for city, ds in sorted(dur_city.items(), key=lambda kv: -len(kv[1]))[:50]:
	818	+ if len(ds) < 3:
	819	+ continue
	820	+ dur_rows.append([
	821	+ city, len(ds),
	822	+ str(round(sum(ds) / len(ds), 1)).replace(".", ","),
	823	+ str(round(statistics.median(ds), 1)).replace(".", ","),
	824	+ ])
	825	+ if dur_rows:
	826	+ tables.append({
	827	+ "id": "delai_villes",
	828	+ "title": "Délai de présence avant retrait, par ville (période)",
	829	+ "columns": ["Ville", "Retirées", "Délai moyen (j)", "Délai médian (j)"],
	830	+ "rows": dur_rows,
	831	+ })
	832	+ # Écart moyen à l'estimation Vrai-Prix par ville (volume suffisant)
	833	+ fv_rows_city = []
	834	+ for city, devs in sorted(fv_city.items(), key=lambda kv: -len(kv[1]))[:25]:
	835	+ if len(devs) < 50:
	836	+ continue
	837	+ dev_pct = round(100.0 * sum(devs) / len(devs), 1)
	838	+ fv_rows_city.append([
	839	+ city, len(devs),
	840	+ f"{'+' if dev_pct >= 0 else ''}{str(dev_pct).replace('.', ',')} %",
	841	+ sum(1 for d in devs if d <= FV_SEUIL_SOUS)])
	842	+ if fv_rows_city:
	843	+ tables.append({
	844	+ "id": "fv_villes",
	845	+ "title": "Écart à l'estimation Vrai-Prix par ville",
	846	+ "columns": ["Ville", "Annonces évaluées", "Écart moyen",
	847	+ "Sous le marché"],
	848	+ "rows": fv_rows_city})
	849	+ # Couche qualité : anomalies & quarantaine par motif (quality.py)
	850	+ anomalies: dict[str, int] = {}
	851	+ for r in con.execute(
	852	+ "SELECT quality_issues FROM listings WHERE active=1"
	853	+ " AND dup_hidden=0 AND quality_issues IS NOT NULL"):
	854	+ try:
	855	+ for issue in json.loads(r["quality_issues"]):
	856	+ key = issue.split(":")[0]
	857	+ anomalies[key] = anomalies.get(key, 0) + 1
	858	+ except ValueError:
	859	+ continue
	860	+ if anomalies and act_all:
	861	+ tables.append({
	862	+ "id": "quarantaine_motifs",
	863	+ "title": "Couche qualité — anomalies et quarantaine par motif",
	864	+ "columns": ["Motif", "Annonces touchées", "% des actives"],
	865	+ "rows": [[_MOTIFS_QUALITE.get(k, k), v,
	866	+ str(round(100.0 * v / act_all, 1)).replace(".", ",") + " %"]
	867	+ for k, v in sorted(anomalies.items(), key=lambda kv: -kv[1])],
	868	+ })
	869	+ # Bannières / familles de connecteurs : volume, nouvelles, prix, fraîcheur
	870	+ fam_info: dict[str, dict] = {}
	871	+ for r in con.execute(
	872	+ "SELECT source s, price p FROM listings WHERE active=1" + VISIBLE):
	873	+ e = fam_info.setdefault(_famille_of(r["s"], names),
	874	+ {"srcs": set(), "prices": [], "new": 0,
	875	+ "sync": None})
	876	+ e["srcs"].add(r["s"])
	877	+ e["prices"].append(r["p"])
	878	+ for r in con.execute(
	879	+ "SELECT source s, COUNT(*) n FROM listings WHERE first_seen>=?"
	880	+ " AND first_seen<?" + VISIBLE + " GROUP BY source",
	881	+ (ep_frm, ep_to)):
	882	+ fam = _famille_of(r["s"], names)
	883	+ if fam in fam_info:
	884	+ fam_info[fam]["new"] += r["n"]
	885	+ for src, ts in last_sync.items():
	886	+ fam = _famille_of(src, names)
	887	+ if fam in fam_info:
	888	+ e = fam_info[fam]
	889	+ e["sync"] = max(e["sync"] or 0, ts)
	890	+ if fam_info:
	891	+ fam_rows = []
	892	+ for fam, e in sorted(fam_info.items(),
	893	+ key=lambda kv: -len(kv[1]["prices"]))[:30]:
	894	+ fam_rows.append([
	895	+ fam, len(e["srcs"]), len(e["prices"]), e["new"],
	896	+ (_fmt_money(statistics.median(pn))
	897	+ if (pn := [v for v in e["prices"]
	898	+ if isinstance(v, (int, float))]) else "—"),
	899	+ (datetime.fromtimestamp(e["sync"], TZ).strftime("%Y-%m-%d %H:%M")
	900	+ if e["sync"] else "—")])
	901	+ tables.append({
	902	+ "id": "familles",
	903	+ "title": "Bannières & familles de connecteurs",
	904	+ "columns": ["Bannière / famille", "Connecteurs", "Annonces actives",
	905	+ "Nouvelles (période)", "Prix médian",
	906	+ "Dernière synchro"],
	907	+ "rows": fam_rows})
	908	+
	909	+ # ---- records & faits marquants ---------------------------------------------
	910	+ records = []
	911	+ if new_by_day:
	912	+ best = max(new_by_day.items(), key=lambda kv: kv[1])
	913	+ records.append({"label": "Jour record de nouvelles annonces",
	914	+ "value": f"{best[1]:,} annonces".replace(",", " "),
	915	+ "date": best[0]})
	916	+ if gone_by_day:
	917	+ worst = max(gone_by_day.items(), key=lambda kv: kv[1])
	918	+ records.append({"label": "Jour record de retraits",
	919	+ "value": f"{worst[1]:,} annonces".replace(",", " "),
	920	+ "date": worst[0]})
	921	+ fast = con.execute(
	922	+ "SELECT city, address, (last_seen-first_seen)/86400.0 d,"
	923	+ " date(last_seen,'unixepoch','localtime') dt FROM listings"
	924	+ " WHERE active=0 AND last_seen>=? AND last_seen<?"
	925	+ " AND last_seen-first_seen>=3600" # >= 1 h : écarte les artefacts de sync
	926	+ + VISIBLE + " ORDER BY (last_seen-first_seen) ASC LIMIT 1",
	927	+ (ep_frm, ep_to)).fetchone()
	928	+ if fast:
	929	+ d = fast["d"]
	930	+ val = (f"{round(d * 24, 1)} h" if d < 1 else f"{round(d, 1)} j").replace(".", ",")
	931	+ records.append({"label": "Retrait le plus rapide (mise en ligne → retrait)",
	932	+ "value": val + (f" · {fast['city']}" if fast["city"] else ""),
	933	+ "date": fast["dt"]})
	934	+ if drops: # balayage price_log fait plus haut (KPI baisses_prix)
	935	+ drop = drops[0]
	936	+ records.append({"label": "Plus forte baisse de prix demandé",
	937	+ "value": "−" + _fmt_money(drop["amt"]) +
	938	+ (f" · {drop['city']}" if drop["city"] else ""),
	939	+ "date": drop["dt"]})
	940	+ if new_city:
	941	+ c, n = max(new_city.items(), key=lambda kv: kv[1])
	942	+ records.append({"label": "Ville la plus active (nouvelles annonces)",
	943	+ "value": f"{c} — {n:,} annonces".replace(",", " ")})
	944	+ if top_srcs:
	945	+ src = max(top_srcs, key=lambda r: r["new_n"])
	946	+ if src["new_n"]:
	947	+ records.append({"label": "Source la plus active (nouvelles annonces)",
	948	+ "value": f"{names.get(src['s'], src['s'])}"
	949	+ f" — {src['new_n']:,}".replace(",", " ")})
	950	+ top_price = con.execute(
	951	+ "SELECT city, price FROM listings WHERE active=1" + VISIBLE +
	952	+ " AND price BETWEEN ? AND ? ORDER BY price DESC LIMIT 1",
	953	+ (PRICE_MIN, PRICE_MAX)).fetchone()
	954	+ if top_price:
	955	+ records.append({"label": "Inscription active la plus chère",
	956	+ "value": _fmt_money(top_price["price"]) +
	957	+ (f" · {top_price['city']}"
	958	+ if top_price["city"] else "")})
	959	+ med_cities = {c: statistics.median(pn) for c, ps in city_prices.items()
	960	+ if len(pn := [v for v in ps
	961	+ if isinstance(v, (int, float))]) >= 30}
	962	+ if med_cities:
	963	+ c_hi = max(med_cities, key=med_cities.get)
	964	+ c_lo = min(med_cities, key=med_cities.get)
	965	+ records.append({"label": "Ville la plus chère (prix médian, ≥ 30 annonces)",
	966	+ "value": f"{c_hi} — {_fmt_money(med_cities[c_hi])}"})
	967	+ records.append({"label": "Ville la plus abordable (prix médian, ≥ 30 annonces)",
	968	+ "value": f"{c_lo} — {_fmt_money(med_cities[c_lo])}"})
	969	+ big_area = con.execute(
	970	+ "SELECT city, area_sqft a FROM listings WHERE active=1" + VISIBLE +
	971	+ " AND area_sqft BETWEEN 100 AND 50000"
	972	+ " ORDER BY area_sqft DESC LIMIT 1").fetchone()
	973	+ if big_area:
	974	+ records.append({"label": "Plus grande superficie habitable (plausible)",
	975	+ "value": f"{round(big_area['a']):,} pi²".replace(",", " ") +
	976	+ (f" · {big_area['city']}"
	977	+ if big_area["city"] else "")})
	978	+ if fam_info:
	979	+ fam_big = max(fam_info.items(), key=lambda kv: len(kv[1]["srcs"]))
	980	+ if len(fam_big[1]["srcs"]) > 1:
	981	+ records.append({"label": "Bannière au plus grand réseau agrégé",
	982	+ "value": f"{fam_big[0]} — "
	983	+ f"{len(fam_big[1]['srcs'])} connecteurs"})
	984	+
	985	+ out = {
	986	+ "updated": datetime.now(TZ).isoformat(timespec="seconds"),
	987	+ "period": {"from": _iso(frm), "to": _iso(to), "label": label,
	988	+ "observed_from": _iso(data_start)},
	989	+ "kpis": kpis,
	990	+ "series": series,
	991	+ "breakdowns": breakdowns,
	992	+ "tables": tables,
	993	+ "records": records,
	994	+ }
	995	+ if gauges:
	996	+ out["gauges"] = gauges
	997	+ if multiseries:
	998	+ out["multiseries"] = multiseries
	999	+ if stacked:
	1000	+ out["stacked"] = stacked
	1001	+ if distributions:
	1002	+ out["distributions"] = distributions
	1003	+ if geo:
	1004	+ out["geo"] = geo
	1005	+ if heatmap:
	1006	+ out["heatmap"] = heatmap
	1007	+ if hourly:
	1008	+ out["hourly"] = hourly
	1009	+ try:
	1010	+ from . import statsextra, statsfiche
	1011	+ pnls = statsfiche.panels(con) + statsextra.panels(con)
	1012	+ if pnls:
	1013	+ out["panels"] = pnls
	1014	+ except Exception:
	1015	+ pass
	1016	+ return out
	1017	+
	1018	+
	1019	+def dashboard(period: str \| None = None, frm: str \| None = None,
	1020	+ to: str \| None = None) -> dict:
	1021	+ key = f"{period or ''}\|{frm or ''}\|{to or ''}"
	1022	+ now = time.time()
	1023	+ with _CACHE_LOCK:
	1024	+ hit = _CACHE.get(key)
	1025	+ if hit and now - hit[0] < _CACHE_TTL:
	1026	+ return hit[1]
	1027	+ data = _compute(frm, to, period)
	1028	+ with _CACHE_LOCK:
	1029	+ _CACHE[key] = (time.time(), data)
	1030	+ # garder le cache borné
	1031	+ if len(_CACHE) > 64:
	1032	+ for k in sorted(_CACHE, key=lambda k: _CACHE[k][0])[:32]:
	1033	+ _CACHE.pop(k, None)
	1034	+ return data

added immoka/vraiprix_local.py +187 −0

		`@@ -0,0 +1,437 @@`
	1	+# -----------------------------------------------------------------------------
	2	+# Immo-Ka — Agrégateur de propriétés à vendre (province de Québec)
	3	+# Auteur : Simon-Pierre Boucher — contact@spboucher.ai
	4	+# vraiprix_local.py : appariement LOCAL contre la base Vrai-Prix (vraiprix.db,
	5	+# 3,7 M unités d'évaluation avec adresse, lat/lng, estimation, fourchette).
	6	+# Une jointure d'adresse (FTS) par annonce → remplit d'un coup :
	7	+# · lat/lng manquants (géocodage instantané, sans API externe)
	8	+# · l'estimation Vrai-Prix (valeur + P10-P90 + lien /estimation/{id})
	9	+# Bien plus rapide que l'API vrai-prix (une requête réseau par annonce).
	10	+# -----------------------------------------------------------------------------
	11	+from __future__ import annotations
	12	+
	13	+import json
	14	+import os
	15	+import re
	16	+import sqlite3
	17	+import time
	18	+import unicodedata
	19	+
	20	+from . import db
	21	+
	22	+# Emplacement de la base Vrai-Prix (copiée à côté de immoka.db sur le nœud).
	23	+VP_DB = os.environ.get(
	24	+ "VRAIPRIX_DB",
	25	+ str((__import__("pathlib").Path(__file__).resolve().parent.parent
	26	+ / "data" / "vraiprix.db")))
	27	+SITE = "https://www.vrai-prix.com"
	28	+_BBOX = (44.5, 63.0, -80.0, -56.0) # Québec
	29	+
	30	+
	31	+def _norm(s: str) -> str:
	32	+ return "".join(c for c in unicodedata.normalize("NFD", (s or "").lower())
	33	+ if unicodedata.category(c) != "Mn").strip()
	34	+
	35	+
	36	+# mots de « type de voie » ignorés dans l'appariement (variabilité rue/av/boul…)
	37	+_VOIE = {"rue", "av", "ave", "avenue", "boul", "boulevard", "bd", "blvd",
	38	+ "ch", "chemin", "place", "pl", "rang", "rangs", "rg", "montee",
	39	+ "montée", "mtee", "cote", "côte", "route", "rte", "terrasse", "tsse",
	40	+ "ter", "impasse", "imp", "croissant", "crois", "croiss", "cours",
	41	+ "allee", "allée", "prom", "promenade", "carre", "aut", "autoroute",
	42	+ "de", "du", "des", "la", "le", "les", "l", "d", "et", "sur",
	43	+ "est", "ouest", "nord", "sud", "st", "ste", "saint", "sainte"}
	44	+
	45	+_APP_RE = r"\b(?:app?t?\|appartement\|unite\|suite\|local\|bureau\|#)\s*[\w-]+"
	46	+
	47	+
	48	+def _street_words(norm_addr: str) -> set:
	49	+ """Mots significatifs de la rue (sans n° civique, type de voie, n° d'app.)."""
	50	+ a = re.sub(_APP_RE, " ", norm_addr.split(",")[0])
	51	+ a = re.sub(r"[^a-z0-9 ]+", " ", a)
	52	+ a = re.sub(r"^\s*\d+[a-z]{0,2}(?:\s+\d+)?\s+", " ", a) # civique(s) en tête
	53	+ toks = [t for t in a.split() if t]
	54	+ return {t for t in toks if t not in _VOIE and len(t) > 1}
	55	+
	56	+
	57	+def _addr_parts(address: str) -> tuple[list, list]:
	58	+ """→ (civiques candidats, mots de rue). Gère « 822Z » (suffixe de lettre),
	59	+ « 102 50 Rue X » (app-civique : les deux nombres sont candidats) et
	60	+ conserve les rues numériques (« Route 202 », « 117e Avenue »)."""
	61	+ a = _norm(address).split(",")[0]
	62	+ a = re.sub(_APP_RE, " ", a)
	63	+ a = re.sub(r"[^a-z0-9 ]+", " ", a)
	64	+ toks = [t for t in a.split() if t]
	65	+ civs = []
	66	+ while toks and len(civs) < 2:
	67	+ m = re.match(r"^(\d+)[a-z]{0,2}$", toks[0])
	68	+ if not m:
	69	+ break
	70	+ if civs and not toks[0].isdigit(): # ordinal de rue (2e, 3e…) : garder
	71	+ break
	72	+ civs.append(m.group(1))
	73	+ toks = toks[1:]
	74	+ words = [t for t in toks if t not in _VOIE and len(t) > 1]
	75	+ return civs, words
	76	+
	77	+
	78	+def _fts_query(address: str) -> tuple[str, str]:
	79	+ """Requête FTS AND (n° civique + mots significatifs de la rue)."""
	80	+ civs, words = _addr_parts(address)
	81	+ civ = civs[-1] if civs else ""
	82	+ parts = ([civ] if civ else []) + words
	83	+ if not parts:
	84	+ return "", civ
	85	+ return " AND ".join(f'"{p}"' for p in parts), civ
	86	+
	87	+
	88	+def available() -> bool:
	89	+ return os.path.exists(VP_DB)
	90	+
	91	+
	92	+def _pack(r) -> dict:
	93	+ d = {
	94	+ "id": r["id_provinc"], "lat": r["lat"], "lng": r["lng"],
	95	+ "value": r["est_hedo"] or r["est_2026"], "low": r["p10"], "high": r["p90"],
	96	+ "confidence": None, "confidence_pct": None,
	97	+ "url": f"{SITE}/estimation/{r['id_provinc']}",
	98	+ }
	99	+ d.update(_role_fields(r))
	100	+ return d
	101	+
	102	+
	103	+# clés « rôle d'évaluation » ajoutées au JSON vraiprix (valeurs officielles)
	104	+ROLE_KEYS = ("valeur_role", "valeur_terrain", "valeur_batiment",
	105	+ "annee_construction_role", "superficie_terrain_role_m2",
	106	+ "aire_etages_role_m2")
	107	+
	108	+
	109	+def _role_fields(r) -> dict:
	110	+ """Champs du rôle d'évaluation foncière de l'unité appariée (officiels) :
	111	+ valeurs (rôle/terrain/bâtiment), année de construction et superficies."""
	112	+ out = {}
	113	+ for src, dst in (("valeur_role", "valeur_role"),
	114	+ ("valeur_terrain", "valeur_terrain"),
	115	+ ("valeur_batiment", "valeur_batiment"),
	116	+ ("annee_construction", "annee_construction_role"),
	117	+ ("superficie_terrain_m2", "superficie_terrain_role_m2"),
	118	+ ("aire_etages_m2", "aire_etages_role_m2")):
	119	+ try:
	120	+ v = r[src]
	121	+ except (KeyError, IndexError):
	122	+ v = None
	123	+ if v:
	124	+ out[dst] = v
	125	+ return out
	126	+
	127	+
	128	+# le terrain du rôle d'une COPROPRIÉTÉ est souvent celui de l'immeuble entier :
	129	+# jamais de repli lot_sqft pour ces types
	130	+_NO_LOT_TYPES = ("condo", "appartement", "loft", "copropriete")
	131	+
	132	+
	133	+def _apply_role_fallback(con, uid: str, year_built, lot_sqft,
	134	+ property_type: str, est: dict) -> tuple[int, int]:
	135	+ """Repli des COLONNES depuis le rôle quand la source ne fournit rien :
	136	+ year_built ← annee_construction_role, lot_sqft ← superficie_terrain_role_m2
	137	+ (sauf copropriétés). Provenance marquée dans details.*_source='role'.
	138	+ Retourne (année_remplie, terrain_rempli) ∈ {0,1}²."""
	139	+ fy = fl = 0
	140	+ y = est.get("annee_construction_role")
	141	+ if year_built is None and y and 1600 <= int(y) <= 2049:
	142	+ con.execute(
	143	+ "UPDATE listings SET year_built=?,"
	144	+ " details=json_set(COALESCE(details,'{}'),'$.year_built_source','role')"
	145	+ " WHERE uid=? AND year_built IS NULL", (int(y), uid))
	146	+ fy = 1
	147	+ t = est.get("superficie_terrain_role_m2")
	148	+ pt = _norm(property_type or "")
	149	+ if (lot_sqft is None and t and float(t) > 0
	150	+ and not any(k in pt for k in _NO_LOT_TYPES)):
	151	+ con.execute(
	152	+ "UPDATE listings SET lot_sqft=?,"
	153	+ " details=json_set(COALESCE(details,'{}'),'$.lot_sqft_source','role')"
	154	+ " WHERE uid=? AND lot_sqft IS NULL",
	155	+ (round(float(t) * 10.7639), uid))
	156	+ fl = 1
	157	+ return fy, fl
	158	+
	159	+
	160	+def _meters(a1: float, o1: float, a2: float, o2: float) -> float:
	161	+ """Distance approx. en mètres (équirectangulaire, ~exact à courte portée)."""
	162	+ import math
	163	+ dlat = (a2 - a1) * 111_000.0
	164	+ dlng = (o2 - o1) * 111_000.0 * math.cos(math.radians(a1))
	165	+ return (dlat * dlat + dlng * dlng) ** 0.5
	166	+
	167	+
	168	+# mots génériques ignorés dans la comparaison de municipalités
	169	+_MUNI_GEN = {"saint", "sainte", "ville", "de", "du", "des", "la", "le", "les",
	170	+ "sur", "au", "aux", "lac", "notre", "dame", "canton", "cantons",
	171	+ "municipalite", "paroisse", "village", "mont"}
	172	+
	173	+
	174	+def _muni_norm(s: str) -> str:
	175	+ s = re.sub(r"[^a-z0-9 ]+", " ", _norm(s or ""))
	176	+ s = re.sub(r"\bst\b", "saint", s)
	177	+ s = re.sub(r"\bste\b", "sainte", s)
	178	+ return " ".join(s.split())
	179	+
	180	+
	181	+def _muni_one(nc: str, um: str) -> bool:
	182	+ if nc in um or um in nc:
	183	+ return True
	184	+ return bool((set(nc.split()) - _MUNI_GEN) & (set(um.split()) - _MUNI_GEN))
	185	+
	186	+
	187	+def _muni_match(city: str, unit_muni: str, address: str = "") -> bool:

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