Update app.py

app.py

@@ -36,7 +36,90 @@ class DataCollector:
             'Hyderabad': {'lat': 25.3960, 'lon': 68.3578}
         }
 
-    # [Previous methods remain the same...]
+    def fetch_weather_data(self):
+        """Fetch weather data from OpenMeteo"""
+        weather_data = []
+        for city, coords in self.cities.items():
+            try:
+                url = f"https://api.open-meteo.com/v1/forecast?latitude={coords['lat']}&longitude={coords['lon']}&hourly=temperature_2m,relativehumidity_2m,precipitation,windspeed_10m&daily=temperature_2m_max,temperature_2m_min,precipitation_sum&timezone=auto&past_days=7"
+                response = requests.get(url)
+                data = response.json()
+                
+                # Hourly data
+                hourly_df = pd.DataFrame({
+                    'datetime': pd.to_datetime(data['hourly']['time']),
+                    'temperature': data['hourly']['temperature_2m'],
+                    'humidity': data['hourly']['relativehumidity_2m'],
+                    'precipitation': data['hourly']['precipitation'],
+                    'wind_speed': data['hourly']['windspeed_10m']
+                })
+                
+                # Daily data
+                daily_df = pd.DataFrame({
+                    'date': pd.to_datetime(data['daily']['time']),
+                    'temp_max': data['daily']['temperature_2m_max'],
+                    'temp_min': data['daily']['temperature_2m_min'],
+                    'precipitation_sum': data['daily']['precipitation_sum']
+                })
+                
+                weather_data.append({
+                    'city': city,
+                    'hourly': hourly_df,
+                    'daily': daily_df,
+                    'coords': coords
+                })
+            except Exception as e:
+                st.error(f"Error fetching weather data for {city}: {e}")
+                continue
+        
+        return weather_data if weather_data else None
+
+    def fetch_usgs_earthquake_data(self):
+        """Fetch earthquake data from USGS website"""
+        try:
+            # USGS API endpoint for past month's earthquakes
+            url = "https://earthquake.usgs.gov/earthquakes/feed/v1.0/summary/2.5_month.geojson"
+            response = requests.get(url)
+            data = response.json()
+            
+            # Filter for Pakistan region
+            pakistan_data = {
+                "type": "FeatureCollection",
+                "features": [
+                    feature for feature in data["features"]
+                    if 60.878 <= feature["geometry"]["coordinates"][0] <= 77.840
+                    and 23.692 <= feature["geometry"]["coordinates"][1] <= 37.097
+                ]
+            }
+            return pakistan_data
+        except Exception as e:
+            st.error(f"Error fetching earthquake data: {e}")
+            return None
+
+    def fetch_air_quality_data(self):
+        """Fetch air quality data from OpenMeteo"""
+        aqi_data = []
+        for city, coords in self.cities.items():
+            try:
+                url = f"https://air-quality-api.open-meteo.com/v1/air-quality?latitude={coords['lat']}&longitude={coords['lon']}&hourly=pm10,pm2_5,carbon_monoxide,nitrogen_dioxide,ozone&timezone=auto&past_days=7"
+                response = requests.get(url)
+                data = response.json()
+                
+                df = pd.DataFrame({
+                    'datetime': pd.to_datetime(data['hourly']['time']),
+                    'PM10': data['hourly']['pm10'],
+                    'PM2.5': data['hourly']['pm2_5'],
+                    'CO': data['hourly']['carbon_monoxide'],
+                    'NO2': data['hourly']['nitrogen_dioxide'],
+                    'O3': data['hourly']['ozone'],
+                    'city': city
+                })
+                aqi_data.append(df)
+            except Exception as e:
+                st.error(f"Error fetching AQI data for {city}: {e}")
+                continue
+        
+        return pd.concat(aqi_data, ignore_index=True) if aqi_data else None
 
     def create_ml_features(self, weather_data):
         """Create features for ML predictions"""