"""Sub-agente: Criminalidad.

Fuentes: SpotCrime (scraping) + FBI UCR API (key opcional).
Retorna datos fail-soft — si falla, devuelve dict vacío con error.
"""

from __future__ import annotations

import os
import time
import requests
from bs4 import BeautifulSoup
from data_fetchers.base import USER_AGENT, DEFAULT_TIMEOUT


FBI_API_KEY = os.getenv("FBI_UCR_API_KEY", "")
FBI_BASE = "https://api.usa.gov/crime/fbi/cde"


def run(lat: float, lon: float, address: str) -> dict:
    """Recopila datos de criminalidad para la ubicación."""
    result = {
        "score_input": {},
        "crimes_recent": [],
        "crime_types": {},
        "trend": "desconocido",
        "sources": [],
        "errors": [],
    }

    # --- SpotCrime scraping ---
    try:
        spot = _spotcrime(lat, lon)
        result["crimes_recent"] = spot.get("crimes", [])
        result["crime_types"] = spot.get("by_type", {})
        result["sources"].append("SpotCrime.com")
    except Exception as e:
        result["errors"].append(f"SpotCrime: {e}")

    # --- FBI UCR API (solo si hay key) ---
    if FBI_API_KEY:
        try:
            fbi = _fbi_ucr(address)
            result["fbi_data"] = fbi
            result["sources"].append("FBI UCR API")
        except Exception as e:
            result["errors"].append(f"FBI UCR: {e}")

    # Score input: cantidad de crímenes en los últimos 30 días
    total = len(result["crimes_recent"])
    result["score_input"]["total_crimes_30d"] = total
    result["score_input"]["has_violent"] = any(
        c.get("type", "").lower() in ("assault", "robbery", "shooting", "homicide")
        for c in result["crimes_recent"]
    )

    return result


def _spotcrime(lat: float, lon: float) -> dict:
    """Scraping básico de SpotCrime para el área."""
    url = f"https://spotcrime.com/crimes.json?lat={lat}&lon={lon}&callback=spotcrime"
    headers = {"User-Agent": USER_AGENT, "Referer": "https://spotcrime.com"}
    time.sleep(2)
    r = requests.get(url, headers=headers, timeout=DEFAULT_TIMEOUT)
    r.raise_for_status()

    # SpotCrime devuelve JSONP — extraer JSON interior
    text = r.text
    if text.startswith("spotcrime("):
        text = text[len("spotcrime("):-1]

    import json
    data = json.loads(text)
    crimes = data.get("crimes", [])

    by_type: dict = {}
    for c in crimes:
        t = c.get("type", "Other")
        by_type[t] = by_type.get(t, 0) + 1

    return {"crimes": crimes[:50], "by_type": by_type}


def _fbi_ucr(address: str) -> dict:
    """FBI UCR API — estadísticas por estado/ciudad."""
    # Extraer estado de la dirección (últimas 2 letras antes del ZIP)
    import re
    m = re.search(r",\s*([A-Z]{2})\s+\d{5}", address.upper())
    state = m.group(1) if m else "FL"

    url = f"{FBI_BASE}/summarized/state/{state}/all?API_KEY={FBI_API_KEY}&from=2020&to=2023"
    r = requests.get(url, timeout=DEFAULT_TIMEOUT, headers={"User-Agent": USER_AGENT})
    r.raise_for_status()
    return r.json()


def score(data: dict) -> int:
    """Calcula score 0-100 de seguridad (100 = muy seguro)."""
    if not data or not data.get("score_input"):
        return 50  # neutral si no hay datos

    total = data["score_input"].get("total_crimes_30d", 0)
    has_violent = data["score_input"].get("has_violent", False)

    # Base score inversamente proporcional a crímenes
    if total == 0:
        base = 90
    elif total <= 5:
        base = 75
    elif total <= 15:
        base = 60
    elif total <= 30:
        base = 45
    elif total <= 50:
        base = 30
    else:
        base = 15

    # Penalización por crimen violento
    if has_violent:
        base = max(0, base - 15)

    return min(100, max(0, base))