from __future__ import annotations

from typing import Any

from farm_data.models import SensorData
from farm_data.services import build_ai_farm_snapshot

from .services import get_forecast_for_location


WMO_CONDITIONS = {
    0: "صاف",
    1: "عمدتاً صاف",
    2: "نیمه‌ابری",
    3: "ابری",
    45: "مه",
    48: "مه یخ‌زده",
    51: "نم‌نم باران",
    61: "بارش خفیف",
    63: "بارش متوسط",
    65: "بارش شدید",
    71: "برف خفیف",
    80: "رگبار",
    95: "رعد و برق",
}


def _safe_number(value, default=0):
    return default if value is None else value


def _average(values, default=0):
    clean_values = [value for value in values if value is not None]
    if not clean_values:
        return default
    return sum(clean_values) / len(clean_values)


def _weather_condition(weather_code):
    return WMO_CONDITIONS.get(weather_code, "نامشخص")


def _build_farm_weather_card(forecasts: list[Any], *, farm_uuid: str | None = None, ai_snapshot: dict[str, Any] | None = None) -> dict[str, Any]:
    if not forecasts:
        return {
            "condition": "نامشخص",
            "temperature": 0,
            "unit": "°C",
            "humidity": 0,
            "windSpeed": 0,
            "windUnit": "km/h",
            "chartData": {"labels": [], "series": [[]]},
            "source_metadata": {
                "weather": {"source": "center_location_forecast", "policy": "center_location_latest_forecast"},
                "agronomic_metrics": {"source": "build_ai_farm_snapshot", "policy": "cluster_block_farm_aggregated"},
            },
        }

    current_forecast = forecasts[0]
    labels = [str(forecast.forecast_date) for forecast in forecasts[:7]]
    series = [[round(_safe_number(forecast.temperature_mean, 0)) for forecast in forecasts[:7]]]

    return {
        "condition": _weather_condition(current_forecast.weather_code),
        "temperature": round(_safe_number(current_forecast.temperature_mean, current_forecast.temperature_max)),
        "unit": "°C",
        "humidity": round(_average([current_forecast.humidity_mean], default=0)),
        "windSpeed": round(_safe_number(current_forecast.wind_speed_max, 0)),
        "windUnit": "km/h",
        "chartData": {
            "labels": labels,
            "series": series,
        },
        "source_metadata": {
            "weather": {"source": "center_location_forecast", "policy": "center_location_latest_forecast"},
            "agronomic_metrics": {
                "source": "build_ai_farm_snapshot",
                "policy": "cluster_block_farm_aggregated",
                "available": bool(ai_snapshot),
            },
        },
    }


class FarmWeatherService:
    def get_farm_weather_card(self, *, farm_uuid: str) -> dict[str, Any]:
        sensor = (
            SensorData.objects.select_related("center_location")
            .filter(farm_uuid=farm_uuid)
            .first()
        )
        if sensor is None:
            raise ValueError("Farm not found.")

        forecasts = get_forecast_for_location(sensor.center_location, days=7)
        ai_snapshot = build_ai_farm_snapshot(farm_uuid)
        return _build_farm_weather_card(forecasts, farm_uuid=farm_uuid, ai_snapshot=ai_snapshot)