import requests
from datetime import date, datetime, timedelta
from modules.weather import Weather
def fetch_json(url: str, timeout: int = 10) -> dict:
    resp = requests.get(url, timeout=timeout)
    resp.raise_for_status()
    data = resp.json()
    if data.get("error"):
        raise RuntimeError(f"Open-Meteo API error: {data.get('reason', data)}")
    if "daily" not in data:
        raise RuntimeError(f"Unexpected Open-Meteo response: {data}")
    return data
def did_or_will_rain(
    target_date,
    latitude,
    longitude,
    forecast_threshold=50,
):
    """
    Returns True if:
      - it rained on a past date
      - rain is forecast on a future date above the threshold

    Parameters
    ----------
    target_date : str | date | datetime
        Date to check ("YYYY-MM-DD" or date object)
    latitude : float
    longitude : float
    forecast_threshold : int
        Minimum rain probability (%) for future dates

    Returns
    -------
    bool
    """

    # Normalize date
    if isinstance(target_date, str):
        target_date = datetime.strptime(target_date, "%Y-%m-%d").date()
    elif isinstance(target_date, datetime):
        target_date = target_date.date()

    today = date.today()

    # Historical date
    if target_date < today:
        url = (
            "https://archive-api.open-meteo.com/v1/archive"
            f"?latitude={latitude}"
            f"&longitude={longitude}"
            f"&start_date={target_date}"
            f"&end_date={target_date}"
            "&daily=precipitation_sum"
            "&timezone=auto"
        )

        data = fetch_json(url)

        rain_mm = data["daily"]["precipitation_sum"][0]
        return rain_mm > 0

    # Today / future date
    else:
        url = (
            "https://api.open-meteo.com/v1/forecast"
            f"?latitude={latitude}"
            f"&longitude={longitude}"
            "&daily=precipitation_probability_max,precipitation_sum"
            "&forecast_days=16"
            "&timezone=auto"
        )

        data = fetch_json(url)
        
        dates = data["daily"]["time"]

        target_date_str = target_date.isoformat()

        if target_date_str not in dates:
            raise ValueError("Date outside forecast range")

        idx = dates.index(target_date_str)

        probability = data["daily"]["precipitation_probability_max"][idx]
        precipitation = data["daily"]["precipitation_sum"][idx]

        return (
            probability >= forecast_threshold
            or precipitation > 0
        )
    

def weather_comment(code: int) -> str:
    WMO_CODES = {
    0:  "☀️ Sunny",
    1:  "🌤️ Mainly clear",
    2:  "⛅ Partly cloudy",
    3:  "☁️ Cloudy",
    45: "🌫️ Foggy",
    48: "🌫️ Icy fog",
    51: "🌦️ Light drizzle",
    53: "🌦️ Moderate drizzle",
    55: "🌧️ Dense drizzle",
    56: "🌨️ Light freezing drizzle",
    57: "🌨️ Heavy freezing drizzle",
    61: "🌧️ Slight rain",
    63: "🌧️ Moderate rain",
    65: "🌧️ Heavy rain",
    66: "🌨️ Light freezing rain",
    67: "🌨️ Heavy freezing rain",
    71: "❄️ Slight snowfall",
    73: "❄️ Moderate snowfall",
    75: "❄️ Heavy snowfall",
    77: "🌨️ Snow grains",
    80: "🌦️ Slight rain showers",
    81: "🌧️ Moderate rain showers",
    82: "⛈️ Violent rain showers",
    85: "🌨️ Slight snow showers",
    86: "🌨️ Heavy snow showers",
    95: "⛈️ Thunderstorm",
    96: "⛈️ Thunderstorm with slight hail",
    99: "⛈️ Thunderstorm with heavy hail",
}
    return WMO_CODES.get(code, "Unknown weather")
    

def weather_values(date, latitude, longitude):
    # return temperature, wind, precipitation, and a comment (cloudy/sunny/rainy/windy)
    url = (
        "https://api.open-meteo.com/v1/forecast"
        f"?latitude={latitude}"
        f"&longitude={longitude}"
        "&daily=temperature_2m_max,temperature_2m_min,precipitation_sum,precipitation_probability_max,windspeed_10m_max,weathercode"
        "&forecast_days=16"
        "&timezone=auto"
    )
    data = fetch_json(url)
    dates = data["daily"]["time"]
    # date_str = date.isoformat() if isinstance(date, date) else date
    date_str = date.isoformat()
    if date_str not in dates:
        raise ValueError("Date outside forecast range")
    idx = dates.index(date_str)
    temp_max = data["daily"]["temperature_2m_max"][idx]
    temp_min = data["daily"]["temperature_2m_min"][idx]
    precipitation = data["daily"]["precipitation_sum"][idx]
    precipitation_probability = data["daily"]["precipitation_probability_max"][idx]
    windspeed = data["daily"]["windspeed_10m_max"][idx]
    weathercode = data["daily"]["weathercode"][idx]

    comment = weather_comment(weathercode)
    return Weather(
        temp_max=temp_max,
        temp_min=temp_min,
        precipitation=precipitation,
        precipitation_probability=precipitation_probability,
        wind_speed=windspeed,
        comment=comment,
    )

def last_rained_date(latitude, longitude, days_back=15):
    url = (
        "https://archive-api.open-meteo.com/v1/archive"
        f"?latitude={latitude}"
        f"&longitude={longitude}"
        f"&start_date={(date.today() - timedelta(days=days_back + 1 )).isoformat()}"
        f"&end_date={(date.today() - timedelta(days=1)).isoformat()}" # YESTERDAY
        "&daily=precipitation_sum"
        "&timezone=auto"
    )

    data = fetch_json(url)
    dates = data["daily"]["time"]
    precipitation = data["daily"]["precipitation_sum"]

    for d, p in zip(reversed(dates), reversed(precipitation)):
        if p > 5:  # Consider it rained if precipitation > 5mm
            return date.fromisoformat(d)

    return None  # No rain in the past `days_back` days

# Marseille
LAT = 43.2965
LON = 5.3698

# Did it rain yesterday?
print(did_or_will_rain("2026-06-03", LAT, LON))

# Will it rain tomorrow?
print(did_or_will_rain("2026-06-04", LAT, LON))

# Require at least 70% confidence
print(
    did_or_will_rain(
        "2026-06-05",
        LAT,
        LON,
        forecast_threshold=70,
    ))