"""
Per-user filter matching.

Each user has one row in user_filters. A flat matches the user if all
of the user's non-null constraints are satisfied. Empty filters = matches all.
"""
import logging
from typing import Iterable

logger = logging.getLogger("web.matching")


# German labels per filter dimension. The order also defines the order chips
# appear in the "Rausgefilterte Wohnungen" section.
_REASON_ORDER = ("Zimmer", "Preis", "Größe", "WBS", "Bezirk")


def flat_filter_failures(flat: dict, f: dict | None) -> list[str]:
    """Return the German labels of filter dimensions the flat fails. Empty list = full match.

    Each label appears at most once (rooms_min and rooms_max both map to "Zimmer"),
    in stable _REASON_ORDER so chips render consistently. Berlin-Bezirk filter:
    empty string = no filter = all Bezirke match. When active, flats with an
    unknown/unmapped PLZ count as a Bezirk failure — if the user bothered to
    narrow by district, we shouldn't sneak in flats we couldn't place.
    """
    if not f:
        return []
    failures: set[str] = set()

    rooms = flat.get("rooms") or 0.0
    rent = flat.get("total_rent") or 0.0
    size = flat.get("size") or 0.0
    wbs_str = str(flat.get("wbs", "")).strip().lower()

    if f.get("rooms_min") is not None and rooms < float(f["rooms_min"]):
        failures.add("Zimmer")
    if f.get("rooms_max") is not None and rooms > float(f["rooms_max"]):
        failures.add("Zimmer")
    if f.get("max_rent") is not None and rent > float(f["max_rent"]):
        failures.add("Preis")
    if f.get("min_size") is not None and size < float(f["min_size"]):
        failures.add("Größe")

    wbs_req = (f.get("wbs_required") or "").strip().lower()
    if wbs_req == "yes":
        if not wbs_str or wbs_str in ("kein", "nein", "no", "ohne", "-"):
            failures.add("WBS")
    elif wbs_req == "no":
        if wbs_str and wbs_str not in ("kein", "nein", "no", "ohne", "-"):
            failures.add("WBS")

    districts_csv = (f.get("districts") or "").strip()
    if districts_csv:
        selected = {d.strip() for d in districts_csv.split(",") if d.strip()}
        flat_district = (flat.get("district") or "").strip()
        if not flat_district or flat_district not in selected:
            failures.add("Bezirk")

    return [r for r in _REASON_ORDER if r in failures]


def flat_matches_filter(flat: dict, f: dict | None) -> bool:
    """f is a user_filters row converted to dict (or None = no filter set)."""
    return not flat_filter_failures(flat, f)


def row_to_dict(row) -> dict:
    if row is None:
        return {}
    try:
        return {k: row[k] for k in row.keys()}
    except Exception:
        return dict(row)