"""/timeline — events grouped by month (global, or one entity + what it develops)."""
from __future__ import annotations

from typing import Any

from fastapi import APIRouter, Query, Request

from aiatlas.api.common import COMPANY_TYPES, EVENT_COLS, EVENT_FROM, cached, change_event, csv, resolve_entity
from aiatlas.db import connection, fetch_all

router = APIRouter(prefix="/api/v1/timeline", tags=["timeline"])


@router.get("")
@cached(120)
async def timeline(request: Request, entity: str | None = None, year: int | None = Query(None, ge=1950, le=2100), category: str | None = None,
                   importance_min: int | None = Query(None, ge=0, le=3), limit: int = Query(200, ge=1, le=1000)) -> dict[str, Any]:
    where = ["ev.event_type <> 'DOCUMENT_CHANGED'"]
    params: dict[str, Any] = {"lim": limit}
    async with connection() as conn:
        if entity:
            row = await resolve_entity(conn, entity)
            if row["entity_type"] in COMPANY_TYPES:
                where.append("(ev.entity_id = :eid or ev.entity_id in (select id from entities where organization_id = :eid union "
                             "select object_id from relations where subject_id = :eid and predicate in ('develops','owns','operates','published') and valid_to is null))")
            else:
                where.append("ev.entity_id = :eid")
            params["eid"] = row["id"]
        if year:
            where.append("extract(year from coalesce(ev.effective_at, ev.observed_at)) = :year")
            params["year"] = year
        if category:
            where.append("ev.category = any(cast(:cats as text[]))")
            params["cats"] = csv(category)
        if importance_min is not None:
            where.append("ev.importance >= :imp")
            params["imp"] = importance_min
        rows = await fetch_all(conn, f"select to_char(coalesce(ev.effective_at, ev.observed_at) at time zone 'UTC', 'YYYY-MM') as month, {EVENT_COLS} from {EVENT_FROM} "
                                     f"where {' and '.join(where)} order by coalesce(ev.effective_at, ev.observed_at) desc, ev.id desc limit :lim", **params)
    groups: dict[str, list[dict[str, Any]]] = {}
    for r in rows:
        groups.setdefault(r["month"], []).append(change_event(r))
    return {"items": [{"month": m, "count": len(evs), "events": evs} for m, evs in groups.items()], "total": len(rows)}