"""Weather service: geocoding, Open-Meteo 7-day forecast, caching, change detection."""

import logging
from datetime import datetime, timezone

import httpx
from sqlalchemy import select

from fabledassistant.models import async_session
from fabledassistant.models.weather_cache import WeatherCache

logger = logging.getLogger(__name__)

NOMINATIM_URL = "https://nominatim.openstreetmap.org/search"
OPEN_METEO_URL = "https://api.open-meteo.com/v1/forecast"
OPEN_METEO_DAILY = (
    "temperature_2m_max,temperature_2m_min,precipitation_sum,"
    "precipitation_probability_max,weathercode,windspeed_10m_max"
)

# WMO weather code → description (subset; covers the most common codes)
_WMO_CODES: dict[int, str] = {
    0: "Clear sky",
    1: "Mainly clear", 2: "Partly cloudy", 3: "Overcast",
    45: "Fog", 48: "Depositing rime fog",
    51: "Drizzle: light", 53: "Drizzle: moderate", 55: "Drizzle: dense",
    61: "Rain: slight", 63: "Rain: moderate", 65: "Rain: heavy",
    71: "Snow: slight", 73: "Snow: moderate", 75: "Snow: heavy",
    77: "Snow grains",
    80: "Rain showers: slight", 81: "Rain showers: moderate", 82: "Rain showers: violent",
    85: "Snow showers: slight", 86: "Snow showers: heavy",
    95: "Thunderstorm",
    96: "Thunderstorm with slight hail", 99: "Thunderstorm with heavy hail",
}


def describe_weathercode(code: int) -> str:
    return _WMO_CODES.get(code, f"Unknown (code {code})")


def parse_forecast(raw: dict) -> list[dict]:
    """Convert Open-Meteo daily response into a clean list of day dicts."""
    daily = raw.get("daily", {})
    dates = daily.get("time", [])
    precip_prob = daily.get("precipitation_probability_max", [])
    return [
        {
            "date": dates[i],
            "temp_max": daily.get("temperature_2m_max", [])[i],
            "temp_min": daily.get("temperature_2m_min", [])[i],
            "precip_mm": daily.get("precipitation_sum", [])[i],
            "precip_probability": precip_prob[i] if i < len(precip_prob) else None,
            "weathercode": daily.get("weathercode", [])[i],
            "description": describe_weathercode(daily.get("weathercode", [])[i]),
            "windspeed_max": daily.get("windspeed_10m_max", [])[i],
        }
        for i in range(len(dates))
    ]


def detect_changes(old_days: list[dict], new_days: list[dict]) -> list[str]:
    """Return human-readable change strings where the forecast has meaningfully shifted."""
    old_by_date = {d["date"]: d for d in old_days}
    changes = []
    for day in new_days:
        date = day["date"]
        old = old_by_date.get(date)
        if not old:
            continue
        notes = []
        # Weather condition changed
        if day["weathercode"] != old["weathercode"]:
            notes.append(
                f"conditions changed from '{describe_weathercode(old['weathercode'])}' "
                f"to '{describe_weathercode(day['weathercode'])}'"
            )
        # Precipitation appeared or disappeared (threshold: 1mm)
        was_dry = old["precip_mm"] < 1.0
        now_wet = day["precip_mm"] >= 1.0
        was_wet = old["precip_mm"] >= 1.0
        now_dry = day["precip_mm"] < 1.0
        if was_dry and now_wet:
            notes.append(f"rain now expected ({day['precip_mm']:.1f}mm)")
        elif was_wet and now_dry:
            notes.append("rain no longer expected")
        # Temperature shifted by 4°C or more
        temp_shift = abs(day["temp_max"] - old["temp_max"])
        if temp_shift >= 4:
            direction = "warmer" if day["temp_max"] > old["temp_max"] else "colder"
            notes.append(f"high temperature {direction} by {temp_shift:.0f}°C")
        if notes:
            changes.append(f"{date}: " + "; ".join(notes))
    return changes


def parse_weather_card_data(
    cache_row,
    temp_unit: str = "C",
) -> dict | None:
    """
    Parse a WeatherCache row into the metadata.weather card schema.
    Returns None if the cache is stale (older than 24 hours) or unavailable.
    """
    from datetime import date, timedelta

    if cache_row is None or cache_row.fetched_at is None:
        return None

    age_seconds = (datetime.now(timezone.utc) - cache_row.fetched_at).total_seconds()
    if age_seconds > 86400:
        return None

    raw = cache_row.forecast_json or {}
    current_weather = raw.get("current_weather", {})
    days = parse_forecast(raw)

    today_str = date.today().isoformat()
    yesterday_str = (date.today() - timedelta(days=1)).isoformat()

    today_day = next((d for d in days if d["date"] == today_str), None)
    yesterday_day = next((d for d in days if d["date"] == yesterday_str), None)
    future_days = [d for d in days if d["date"] > today_str][:5]

    imperial = temp_unit == "F"

    def to_temp(c: float) -> int:
        return round(c * 9 / 5 + 32) if imperial else round(c)

    def to_wind(kmh: float) -> int:
        return round(kmh * 0.621371) if imperial else round(kmh)

    def day_label(date_str: str) -> str:
        from datetime import date as _date
        try:
            return _date.fromisoformat(date_str).strftime("%a")
        except ValueError:
            return date_str

    wind_unit = "mph" if imperial else "km/h"

    return {
        "location": getattr(cache_row, "location_label", ""),
        "fetched_at": cache_row.fetched_at.isoformat(),
        "current_temp": to_temp(current_weather.get("temperature", 0)),
        "condition": describe_weathercode(current_weather.get("weathercode", 0)),
        "today_high": to_temp(today_day["temp_max"]) if today_day else None,
        "today_low": to_temp(today_day["temp_min"]) if today_day else None,
        "yesterday_high": to_temp(yesterday_day["temp_max"]) if yesterday_day else None,
        "yesterday_low": to_temp(yesterday_day["temp_min"]) if yesterday_day else None,
        "wind_unit": wind_unit,
        "forecast": [
            {
                "day": day_label(d["date"]),
                "condition": d["description"],
                "high": to_temp(d["temp_max"]),
                "low": to_temp(d["temp_min"]),
                "precip_probability": d["precip_probability"],
                "precip_mm": d["precip_mm"],
                "windspeed_max": to_wind(d["windspeed_max"]),
            }
            for d in future_days
        ],
    }


async def get_cached_weather_rows(user_id: int) -> list:
    """Return raw WeatherCache ORM rows for a user (for card parsing)."""
    async with async_session() as session:
        result = await session.execute(
            select(WeatherCache).where(WeatherCache.user_id == user_id)
        )
        return list(result.scalars().all())


async def geocode(query: str) -> tuple[float, float, str]:
    """Return (lat, lon, display_name) for a place name using Nominatim."""
    async with httpx.AsyncClient(timeout=10.0, headers={"User-Agent": "FabledAssistant/1.0"}) as client:
        resp = await client.get(NOMINATIM_URL, params={"q": query, "format": "json", "limit": 1})
        resp.raise_for_status()
        results = resp.json()
        if not results:
            raise ValueError(f"No geocoding result for: {query!r}")
        r = results[0]
        return float(r["lat"]), float(r["lon"]), r.get("display_name", query)


async def fetch_current_conditions(lat: float, lon: float) -> dict | None:
    """Fetch current temperature + conditions + next 3 hours precipitation.

    Lightweight call — no daily forecast, no caching needed.
    Returns dict with: temperature, windspeed, weathercode, description,
    and precip_next_3h (list of hourly precip probabilities).
    """
    try:
        async with httpx.AsyncClient(timeout=10.0) as client:
            resp = await client.get(OPEN_METEO_URL, params={
                "latitude": lat,
                "longitude": lon,
                "current_weather": "true",
                "hourly": "precipitation_probability",
                "forecast_days": 1,
                "timezone": "auto",
            })
            resp.raise_for_status()
            data = resp.json()

        current = data.get("current_weather", {})
        hourly = data.get("hourly", {})
        hourly_times = hourly.get("time", [])
        hourly_precip = hourly.get("precipitation_probability", [])

        # Find the current hour index and get next 3 hours of precip
        current_time = current.get("time", "")
        precip_next_3h = []
        try:
            idx = next(i for i, t in enumerate(hourly_times) if t >= current_time)
            precip_next_3h = hourly_precip[idx:idx + 3]
        except (StopIteration, IndexError):
            pass

        code = current.get("weathercode", 0)
        return {
            "temperature": current.get("temperature"),
            "windspeed": current.get("windspeed"),
            "weathercode": code,
            "description": describe_weathercode(code),
            "time": current_time,
            "precip_next_3h": precip_next_3h,
        }
    except Exception:
        logger.debug("Failed to fetch current conditions for %s, %s", lat, lon, exc_info=True)
        return None


async def fetch_hourly_precip(lat: float, lon: float) -> dict[str, int]:
    """Fetch today's hourly precipitation probabilities.

    Returns a dict of ISO hour string → probability percentage, e.g.:
    {"2026-04-08T14:00": 65, "2026-04-08T15:00": 80, ...}
    """
    try:
        async with httpx.AsyncClient(timeout=10.0) as client:
            resp = await client.get(OPEN_METEO_URL, params={
                "latitude": lat,
                "longitude": lon,
                "hourly": "precipitation_probability",
                "forecast_days": 1,
                "timezone": "auto",
            })
            resp.raise_for_status()
            data = resp.json()
        hourly = data.get("hourly", {})
        times = hourly.get("time", [])
        probs = hourly.get("precipitation_probability", [])
        return {t: p for t, p in zip(times, probs) if p is not None}
    except Exception:
        logger.debug("Failed to fetch hourly precip for %s, %s", lat, lon, exc_info=True)
        return {}


async def _fetch_open_meteo(lat: float, lon: float) -> dict:
    """Fetch 7-day forecast from Open-Meteo with current conditions and yesterday's data."""
    async with httpx.AsyncClient(timeout=15.0) as client:
        resp = await client.get(OPEN_METEO_URL, params={
            "latitude": lat,
            "longitude": lon,
            "daily": OPEN_METEO_DAILY,
            "current_weather": "true",
            "past_days": 1,
            "timezone": "auto",
            "forecast_days": 7,
        })
        resp.raise_for_status()
        return resp.json()


async def refresh_location_cache(
    user_id: int, location_key: str, location_label: str, lat: float, lon: float
) -> WeatherCache:
    """Fetch fresh forecast and update the cache row for one location."""
    raw = await _fetch_open_meteo(lat, lon)
    async with async_session() as session:
        result = await session.execute(
            select(WeatherCache).where(
                WeatherCache.user_id == user_id,
                WeatherCache.location_key == location_key,
            )
        )
        cache = result.scalars().first()
        if cache is None:
            cache = WeatherCache(
                user_id=user_id,
                location_key=location_key,
                location_label=location_label,
            )
            session.add(cache)
        # Rotate: current becomes previous before overwriting
        cache.previous_json = cache.forecast_json
        cache.forecast_json = raw
        cache.location_label = location_label
        cache.fetched_at = datetime.now(timezone.utc)
        await session.commit()
        await session.refresh(cache)
        return cache


async def get_cached_weather(user_id: int) -> list[dict]:
    """Return all cached weather entries for the user, with parsed days and change notes."""
    async with async_session() as session:
        result = await session.execute(
            select(WeatherCache).where(WeatherCache.user_id == user_id)
        )
        rows = list(result.scalars().all())

    out = []
    for row in rows:
        current_days = parse_forecast(row.forecast_json) if row.forecast_json else []
        previous_days = parse_forecast(row.previous_json) if row.previous_json else []
        changes = detect_changes(previous_days, current_days) if previous_days else []
        out.append({
            "location_key": row.location_key,
            "location_label": row.location_label,
            "fetched_at": row.fetched_at.isoformat(),
            "days": current_days,
            "changes_since_last_fetch": changes,
        })
    return out