import logging
from typing import Optional, Dict, Any, List

import requests

from app.utils import config

logging.basicConfig(
    format="%(asctime)s [%(levelname)s] %(message)s",
    level=logging.INFO,
)


def fetch_forecast(
    q: str,
    days: int = 3,
    alerts: str = "yes",
    aqi: str = "yes",
    lang: Optional[str] = None,
) -> Dict[str, Any]:
    if not config.WEATHER_API_KEY:
        raise RuntimeError("WEATHER_API_KEY is not configured")

    url = "http://api.weatherapi.com/v1/forecast.json"
    params: Dict[str, Any] = {
        "key": config.WEATHER_API_KEY,
        "q": q,
        "days": max(1, min(int(days), 14)),
        "alerts": alerts,
        "aqi": aqi,
    }
    if lang:
        params["lang"] = lang

    resp = requests.get(url, params=params, timeout=10)
    resp.raise_for_status()
    return resp.json()


def _summarize_alerts(alerts_obj: Any, limit: int = 3) -> str:
    if not alerts_obj or not isinstance(alerts_obj, dict):
        return "No alerts."
    alerts = alerts_obj.get("alert") or []
    if not alerts:
        return "No alerts."

    lines: List[str] = ["Alerts:"]
    for a in alerts[: max(1, limit)]:
        headline = a.get("headline") or a.get("event") or "Alert"
        severity = a.get("severity") or "Unknown"
        urgency = a.get("urgency") or "Unknown"
        effective = a.get("effective") or ""
        expires = a.get("expires") or ""
        time_part = ""
        if effective or expires:
            time_part = f" ({effective} → {expires})"
        lines.append(f"- {headline} | severity={severity}, urgency={urgency}{time_part}")
    if len(alerts) > limit:
        lines.append(f"- (+{len(alerts) - limit} more)")
    return "\n".join(lines)


def summarize_forecast(data: Dict[str, Any], include_alerts: bool = True) -> str:
    loc = data.get("location") or {}
    cur = data.get("current") or {}
    forecast = (data.get("forecast") or {}).get("forecastday") or []
    alerts_obj = data.get("alerts") or {}

    name = loc.get("name") or loc.get("region") or "this area"
    country = loc.get("country") or ""
    where = f"{name}, {country}".strip().strip(",")

    cond = (cur.get("condition") or {}).get("text", "Unknown")
    temp_c = cur.get("temp_c", "?")
    humidity = cur.get("humidity", "?")
    wind_kph = cur.get("wind_kph", "?")

    lines: List[str] = [
        f"Weather for {where}:",
        f"- Now: {cond}, {temp_c}°C, humidity {humidity}%, wind {wind_kph} kph",
    ]

    if forecast:
        lines.append("Forecast:")
        for d in forecast[:3]:
            date = d.get("date", "")
            day = d.get("day") or {}
            day_cond = (day.get("condition") or {}).get("text", "Unknown")
            maxt = day.get("maxtemp_c", "?")
            mint = day.get("mintemp_c", "?")
            rain_chance = day.get("daily_chance_of_rain", "?")
            lines.append(f"- {date}: {day_cond}, {mint}–{maxt}°C, rain chance {rain_chance}%")

    if include_alerts:
        lines.append(_summarize_alerts(alerts_obj))

    return "\n".join(lines).strip()


def forecast_summary_for_state(state: str) -> str:
    q = f"{state}, Nigeria"
    data = fetch_forecast(
        q=q,
        days=getattr(config, "WEATHER_FORECAST_DAYS", 3),
        alerts=getattr(config, "WEATHER_ALERTS", "yes"),
        aqi=getattr(config, "WEATHER_AQI", "yes"),
    )
    return summarize_forecast(data, include_alerts=True)


def alerts_for_q(q: str) -> Dict[str, Any]:
    data = fetch_forecast(
        q=q,
        days=getattr(config, "WEATHER_FORECAST_DAYS", 3),
        alerts=getattr(config, "WEATHER_ALERTS", "yes"),
        aqi=getattr(config, "WEATHER_AQI", "yes"),
    )
    return {
        "location": data.get("location"),
        "alerts": data.get("alerts") or {},
    }


def forecast_summary_for_gps(lat: float, lon: float) -> str:
    q = f"{lat},{lon}"
    data = fetch_forecast(
        q=q,
        days=getattr(config, "WEATHER_FORECAST_DAYS", 3),
        alerts=getattr(config, "WEATHER_ALERTS", "yes"),
        aqi=getattr(config, "WEATHER_AQI", "yes"),
    )
    return summarize_forecast(data, include_alerts=True)