"""property_type_inference.py — Heuristica para inferir tipo de propiedad.

Cada source (HUD, Miami-Dade clerk, Zillow, etc.) trae signals distintos. Esta
modulo centraliza la logica de inferencia para que:

1. Scrapers nuevos pueden pasar deals sin property_type y se infiere.
2. Backfill de deals legacy.
3. Una sola fuente de verdad para mapeo "deal info → property_type".

VALORES VALIDOS (alineados con orchestrator.DealInputs.property_type):
    sfr            - Single Family Residence (default residential)
    condo          - Condominium
    townhome       - Townhouse
    multi_family   - Duplex/triplex/quad/apartment
    land           - Vacant land / lot
    mobile_home    - Manufactured / mobile home
    commercial     - Commercial property (warehouse, retail, office)
    unknown        - Insufficient signal — UI shows neutral badge

CONVENCION: si no podemos inferir con confianza media+, retornar "unknown",
NUNCA adivinar "sfr" porque sesga downstream pipelines.
"""
from __future__ import annotations

from typing import Optional

VALID_TYPES = {
    "sfr", "condo", "townhome", "multi_family",
    "land", "mobile_home", "commercial", "unknown",
}

# Spanish labels para UI display
TYPE_LABELS_ES = {
    "sfr":          "Casa",
    "condo":        "Condo",
    "townhome":     "Townhouse",
    "multi_family": "Multi-familiar",
    "land":         "Terreno",
    "mobile_home":  "Mobile home",
    "commercial":   "Comercial",
    "unknown":      "—",
}

# Emoji badges para UI cards
TYPE_EMOJI = {
    "sfr":          "🏠",
    "condo":        "🏢",
    "townhome":     "🏘️",
    "multi_family": "🏬",
    "land":         "🌳",
    "mobile_home":  "🚐",
    "commercial":   "🏪",
    "unknown":      "❔",
}


# Keywords ordenados por especificidad (mas especifico primero gana)
_DESCRIPTION_KEYWORDS = [
    # (keyword_lower, property_type)
    # Land — debe chequear ANTES que "sfr" porque "vacant land" no tiene beds
    ("vacant land",       "land"),
    ("vacant lot",        "land"),
    ("raw land",          "land"),
    ("res vacant",        "land"),  # PA codigos Miami-Dade
    ("residential lot",   "land"),
    ("acreage",           "land"),
    ("buildable lot",     "land"),
    # Mobile home — chequear antes que SFR
    ("mobile home",       "mobile_home"),
    ("manufactured home", "mobile_home"),
    ("manufactured hous", "mobile_home"),
    ("mfd home",          "mobile_home"),
    # Condo
    ("condominium",       "condo"),
    (" condo ",           "condo"),  # space-padded para evitar match en "condominium" twice
    ("condo unit",        "condo"),
    # Townhouse
    ("townhouse",         "townhome"),
    ("townhome",          "townhome"),
    ("town home",         "townhome"),
    # Multi-family
    ("duplex",            "multi_family"),
    ("triplex",           "multi_family"),
    ("quadplex",          "multi_family"),
    ("quad plex",         "multi_family"),
    ("fourplex",          "multi_family"),
    ("multi-family",      "multi_family"),
    ("multi family",      "multi_family"),
    ("multifamily",       "multi_family"),
    ("apartment building","multi_family"),
    # Commercial
    ("warehouse",         "commercial"),
    ("retail space",      "commercial"),
    ("office building",   "commercial"),
    ("commercial",        "commercial"),
    # SFR keywords (less specific, last)
    ("single family",     "sfr"),
    ("single-family",     "sfr"),
    ("sfr",               "sfr"),
    ("sfh",               "sfr"),
]

# Address-level hints (e.g., "UNIT 4B", "APT 12")
_ADDRESS_CONDO_HINTS = ["unit ", "apt ", "#", "suite "]


def _scan_keywords(text: str) -> Optional[str]:
    """Returns property_type if any keyword matches, None otherwise."""
    t = f" {text.lower()} "  # pad for space-bounded matches
    for kw, ptype in _DESCRIPTION_KEYWORDS:
        if kw in t:
            return ptype
    return None


def infer_property_type(deal: dict) -> str:
    """Infiere property_type desde data del deal.

    Args:
        deal: dict con campos como source, listing_description, address, beds,
              baths, sqft, deal_type. No requiere todos.

    Returns:
        Uno de VALID_TYPES. "unknown" si no hay suficiente signal.

    HEURISTICA (en orden de prioridad):
    1. Si ya viene property_type valido → respetarlo (passthrough)
    2. Keywords en listing_description (mas especifico)
    3. Address hints (UNIT/APT → condo)
    4. beds == 0 + no signal contrario → land (auction lots con 0 beds)
    5. Source-based default:
       - hud_homestore: tiene beds populated → sfr (HUD es ~95% SFR)
       - zillow: tiene beds + sqft populated → sfr
       - miami_dade_clerk: sin beds → unknown (taxdeed/foreclosure data limitada)
    6. Fallback → unknown
    """
    # 1) Passthrough si ya viene set
    existing = (deal.get("property_type") or "").strip().lower()
    if existing in VALID_TYPES and existing != "unknown":
        return existing

    desc = (deal.get("listing_description") or "").strip()
    address = (deal.get("address") or "").strip()
    beds = deal.get("beds")
    sqft = deal.get("sqft")
    source = (deal.get("source") or "").strip().lower()

    # 2) Description keywords (most reliable signal)
    if desc:
        match = _scan_keywords(desc)
        if match:
            return match

    # 3) Address hints — "UNIT 4B" / "APT 12" → likely condo
    if address:
        addr_lower = address.lower()
        if any(hint in addr_lower for hint in _ADDRESS_CONDO_HINTS):
            return "condo"
        # Also check address for land/multi keywords
        match = _scan_keywords(address)
        if match:
            return match

    # 4) beds == 0 → land (vacant lot)
    if beds == 0:
        return "land"

    # 5) Source-based default (only if we have beds populated)
    if source == "hud_homestore" and beds and beds > 0:
        return "sfr"  # HUD listings son mayormente SFR
    if source == "zillow" and beds and beds > 0 and sqft and sqft > 0:
        return "sfr"  # Zillow houses listings

    # 6) Fallback — insufficient signal
    return "unknown"


def ensure_property_type(deal: dict) -> dict:
    """Devuelve el deal con property_type seteado (infiere si falta).

    Mutates-and-returns el dict para usar como `insert_deal(ensure_property_type(deal))`.
    """
    pt = infer_property_type(deal)
    deal["property_type"] = pt
    return deal


def label_for(property_type: Optional[str]) -> str:
    """Returns Spanish label + emoji para UI display, e.g. '🏠 Casa'."""
    pt = (property_type or "unknown").strip().lower()
    if pt not in VALID_TYPES:
        pt = "unknown"
    return f"{TYPE_EMOJI[pt]} {TYPE_LABELS_ES[pt]}"