Add weather_fether_data

weather_data_fetcher.py

@@ -0,0 +1,117 @@
+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}")