from pydantic import BaseModel, Field
from typing import Optional, List, Dict

class CurrentWeatherMetrics(BaseModel):
    temperature: Optional[float] = Field(None, description="Current temperature in °C")
    apparent_temperature: Optional[float] = Field(None, description="Apparent temperature in °C")
    wind_chill: Optional[float] = Field(None, description="Wind chill temperature in °C")
    dew_point: Optional[float] = Field(None, description="Dew point in °C")
    humidex: Optional[float] = Field(None, description="Humidex in °C")
    humidity: Optional[float] = Field(None, description="Relative humidity percentage (%)")
    pressure: Optional[float] = Field(None, description="Atmospheric pressure in hPa")
    rain_status: Optional[int] = Field(None, description="Rain status (0: Dry, 1: Wet)")
    rain_status_label: Optional[str] = Field("Dry", description="Human readable rain status label")
    wind_speed: Optional[float] = Field(None, description="Wind speed in km/h")
    gust_speed: Optional[float] = Field(None, description="Gust speed in km/h")
    wind_direction: Optional[float] = Field(None, description="Wind direction in degrees (0-360°)")
    illuminance_lux: Optional[float] = Field(None, description="Solar illuminance in LUX")
    uv_index: Optional[float] = Field(None, description="UV Index")
    battery_percent: Optional[float] = Field(None, description="Battery level (%)")
    linkquality_lqi: Optional[float] = Field(None, description="Zigbee signal strength (LQI)")
    updated_at: str = Field(..., description="Timestamp of metric evaluation")

class TimeSeriesPoint(BaseModel):
    timestamp: int
    value: float

class TimeSeriesMetric(BaseModel):
    name: str
    label: str
    unit: str
    data: List[TimeSeriesPoint]

class WeatherHistoryResponse(BaseModel):
    timeframe: str
    metrics: Dict[str, TimeSeriesMetric]