from typing import List, Optional, Union
import uuid
from sqlalchemy.orm import Session
from models.weather_forecast import WeatherForecast
from schemas.weather_forecast import WeatherForecastCreate, WeatherForecastUpdate, WeatherForecastSchema
from datetime import datetime
from sqlalchemy import func

def get_weather_forecasts(db: Session) -> List[WeatherForecastSchema]:
    """
    Retrieves a fixed list of 10 weather forecasts for different countries.

    Args:
        db (Session): The database session (not used).

    Returns:
        List[WeatherForecastSchema]: A list of 10 weather forecast objects.
    """
    return WeatherForecastSchema.forecasts

def get_weather_forecast_by_id(db: Session, forecast_id: Union[str, uuid.UUID]) -> Optional[WeatherForecast]:
    """
    Retrieves a weather forecast by its ID.

    Args:
        db (Session): The database session.
        forecast_id (Union[str, uuid.UUID]): The ID of the weather forecast.

    Returns:
        Optional[WeatherForecast]: The weather forecast object if found, otherwise None.
    """
    return db.query(WeatherForecast).filter(WeatherForecast.id == forecast_id).first()

def create_weather_forecast(db: Session, forecast_data: WeatherForecastCreate) -> WeatherForecastSchema:
    """
    Creates a new weather forecast in the database.

    Args:
        db (Session): The database session.
        forecast_data (WeatherForecastCreate): The data for the weather forecast to create.

    Returns:
        WeatherForecastSchema: The newly created weather forecast object.
    """
    db_forecast = WeatherForecast(**forecast_data.dict())
    db.add(db_forecast)
    db.commit()
    db.refresh(db_forecast)
    return WeatherForecastSchema.from_orm(db_forecast)

def update_weather_forecast(
    db: Session, forecast_id: Union[str, uuid.UUID], forecast_data: WeatherForecastUpdate
) -> WeatherForecastSchema:
    """
    Updates an existing weather forecast in the database.

    Args:
        db (Session): The database session.
        forecast_id (Union[str, uuid.UUID]): The ID of the weather forecast to update.
        forecast_data (WeatherForecastUpdate): The updated data for the weather forecast.

    Returns:
        WeatherForecastSchema: The updated weather forecast object.
    """
    db_forecast = db.query(WeatherForecast).filter(WeatherForecast.id == forecast_id).first()
    if not db_forecast:
        raise ValueError(f"Weather forecast with ID {forecast_id} not found")

    update_data = forecast_data.dict(exclude_unset=True)
    for field, value in update_data.items():
        setattr(db_forecast, field, value)

    db.commit()
    db.refresh(db_forecast)
    return WeatherForecastSchema.from_orm(db_forecast)

def delete_weather_forecast(db: Session, forecast_id: Union[str, uuid.UUID]) -> bool:
    """
    Deletes a weather forecast from the database.

    Args:
        db (Session): The database session.
        forecast_id (Union[str, uuid.UUID]): The ID of the weather forecast to delete.

    Returns:
        bool: True if the weather forecast was successfully deleted, False otherwise.
    """
    db_forecast = db.query(WeatherForecast).filter(WeatherForecast.id == forecast_id).first()
    if not db_forecast:
        return False

    db.delete(db_forecast)
    db.commit()
    return True

def get_average_temperature_by_location(db: Session, location: str, start_date: datetime, end_date: datetime) -> Optional[float]:
    """
    Retrieves the average temperature for a given location and date range.

    Args:
        db (Session): The database session.
        location (str): The location to filter by.
        start_date (datetime): The start date of the date range (inclusive).
        end_date (datetime): The end date of the date range (inclusive).

    Returns:
        Optional[float]: The average temperature if forecasts are found, otherwise None.
    """
    avg_temp = db.query(func.avg(WeatherForecast.temperature)).filter(
        WeatherForecast.location == location,
        WeatherForecast.date >= start_date,
        WeatherForecast.date <= end_date,
    ).scalar()

    return avg_temp if avg_temp is not None else None