import requests
from datetime import datetime, timedelta
import pandas as pd


class WeatherDataFetcher:
    def __init__(self, api_key):
        self.api_key = api_key
    
    def get_lat_lon(self, city_name):
        """
        Fetches the latitude and longitude for a given city name.

        Parameters:
        - city_name: The name of the city (including state and country).

        Returns:
        - A tuple (latitude, longitude) if successful, None otherwise.
        """
        url = f'http://api.openweathermap.org/geo/1.0/direct?q={city_name}&limit=1&appid={self.api_key}'
        try:
            response = requests.get(url)
            data = response.json()
            if data:
                return data[0]['lat'], data[0]['lon']
            else:
                print('No geo data found')
                return None
        except Exception as e:
            print(f"Error fetching geo data: {e}")
            return None
        
    def fetch_weather_data(self, lat, lon, start_date, end_date):
        """
        Fetches weather data for a given set of coordinates within a specified date range
        and adds latitude and longitude to the DataFrame.

        Parameters:
        - lat: Latitude of the location.
        - lon: Longitude of the location.
        - start_date: The start date as a datetime object.
        - end_date: The end date as a datetime object.

        Returns:
        - A pandas DataFrame containing the weather data along with latitude and longitude.
        """
        daily_data_frames = []
        current_date = start_date
        
        while current_date <= end_date:
            timestamp = int(datetime.timestamp(current_date))
            url = f'https://history.openweathermap.org/data/2.5/history/city?lat={lat}&lon={lon}&type=hour&start={timestamp}&appid={self.api_key}'
            
            response = requests.get(url)
            if response.status_code == 200:
                data = response.json()
                if 'list' in data:
                    df_day = pd.json_normalize(data['list'])
                    # Add latitude and longitude as columns
                    df_day['latitude'] = lat
                    df_day['longitude'] = lon
                    df_day['date'] = current_date.strftime('%Y-%m-%d')
                    daily_data_frames.append(df_day)
                else:
                    print(f"No 'list' key found in data for {current_date.strftime('%Y-%m-%d')}")
            else:
                print(f"Failed to retrieve data for {current_date.strftime('%Y-%m-%d')} with status code {response.status_code}")
            
            current_date += timedelta(days=1)

        if daily_data_frames:
            df_all_days = pd.concat(daily_data_frames, ignore_index=True)
            return self.expand_weather_column(df_all_days)
        else:
            return pd.DataFrame()
        
    def expand_weather_column(self,df):
    # Check if 'weather' column exists
        if 'weather' in df.columns:
        # Extract weather details
            df['weather_id'] = df['weather'].apply(lambda x: x[0]['id'] if x else None)
            df['weather_main'] = df['weather'].apply(lambda x: x[0]['main'] if x else None)
            df['weather_description'] = df['weather'].apply(lambda x: x[0]['description'] if x else None)
            df['weather_icon'] = df['weather'].apply(lambda x: x[0]['icon'] if x else None)
        
        # Drop the original 'weather' column
            df = df.drop('weather', axis=1)
        return df
    
    def fetch_weather_for_cities(self, cities, start_date, end_date):
        all_cities_weather_data = []

        for city_name in cities:
            lat_lon = self.get_lat_lon(city_name)  # Call the method within the same class
            if lat_lon:
                lat, lon = lat_lon
                df_weather = self.fetch_weather_data(lat, lon, start_date, end_date)  
                if not df_weather.empty:
                    df_weather['city'] = city_name  # Add a column for the city name
                    all_cities_weather_data.append(df_weather)
                else:
                    print(f"No weather data retrieved for {city_name}.")
            else:
                print(f"Failed to get latitude and longitude for {city_name}.")

        if all_cities_weather_data:
            all_data_df = pd.concat(all_cities_weather_data, ignore_index=True)
            return all_data_df
        else:
            return pd.DataFrame()
        
    def save_to_csv(self, df, file_name):
        try:
            df.to_csv(file_name, index=False) 
            print(f"Data successfully saved to {file_name}.")
        except Exception as e:
            print(f"Failed to save data to CSV. Error: {e}")