Update app_backend.py

app_backend.py

@@ -148,87 +148,87 @@
 # code 4
 
 
-# import pandas as pd
-# import numpy as np
-# import requests
-# from datetime import datetime
-
-# # Function to fetch real-time weather data
-# def fetch_weather(api_key, location):
-#     url = f"http://api.openweathermap.org/data/2.5/weather?q={location}&appid={api_key}&units=metric"
-#     response = requests.get(url).json()
-#     if response["cod"] == 200:
-#         return {
-#             "temperature": response["main"]["temp"],
-#             "wind_speed": response["wind"]["speed"],
-#             "weather": response["weather"][0]["description"]
-#         }
-#     return None
-
-# # Generate synthetic grid data
-# def generate_synthetic_data():
-#     time_index = pd.date_range(start=datetime.now(), periods=24, freq="H")
-#     return pd.DataFrame({
-#         "timestamp": time_index,
-#         "load_demand_kwh": np.random.randint(200, 500, len(time_index)),
-#         "solar_output_kw": np.random.randint(50, 150, len(time_index)),
-#         "wind_output_kw": np.random.randint(30, 120, len(time_index)),
-#         "grid_health": np.random.choice(["Good", "Moderate", "Critical"], len(time_index))
-#     })
-
-# # Load optimization recommendation
-# def optimize_load(demand, solar, wind):
-#     renewable_supply = solar + wind
-#     if renewable_supply >= demand:
-#         return "Grid Stable"
-#     return "Use Backup or Adjust Load"
-
-# if __name__ == "__main__":
-#     print("Backend ready!")
+import pandas as pd
+import numpy as np
+import requests
+from datetime import datetime
+
+# Function to fetch real-time weather data
+def fetch_weather(api_key, location):
+    url = f"http://api.openweathermap.org/data/2.5/weather?q={location}&appid={api_key}&units=metric"
+    response = requests.get(url).json()
+    if response["cod"] == 200:
+        return {
+            "temperature": response["main"]["temp"],
+            "wind_speed": response["wind"]["speed"],
+            "weather": response["weather"][0]["description"]
+        }
+    return None
+
+# Generate synthetic grid data
+def generate_synthetic_data():
+    time_index = pd.date_range(start=datetime.now(), periods=24, freq="H")
+    return pd.DataFrame({
+        "timestamp": time_index,
+        "load_demand_kwh": np.random.randint(200, 500, len(time_index)),
+        "solar_output_kw": np.random.randint(50, 150, len(time_index)),
+        "wind_output_kw": np.random.randint(30, 120, len(time_index)),
+        "grid_health": np.random.choice(["Good", "Moderate", "Critical"], len(time_index))
+    })
+
+# Load optimization recommendation
+def optimize_load(demand, solar, wind):
+    renewable_supply = solar + wind
+    if renewable_supply >= demand:
+        return "Grid Stable"
+    return "Use Backup or Adjust Load"
+
+if __name__ == "__main__":
+    print("Backend ready!")
 
 
 
 # code 5
 
 
-import random
-import pandas as pd 
-def fetch_data():
-    # Simulating fetching data from a database or API
-    data = {
-        'temperature': random.uniform(-10, 30),
-        'wind_speed': random.uniform(0, 20),
-        'weather_condition': random.choice(['Clear', 'Overcast Clouds', 'Thunderstorm', 'Rain']),
-        'timestamps': pd.date_range("2025-01-01", periods=10, freq='H'),
-        'total_consumption': [random.uniform(50, 100) for _ in range(10)],
-        'grid_generation': [random.uniform(30, 80) for _ in range(10)],
-        'storage_usage': [random.uniform(10, 30) for _ in range(10)],
-        'solar_storage': random.uniform(10, 30),
-        'wind_storage': random.uniform(10, 30),
-        'hydro_storage': random.uniform(10, 30),
-        'total_storage': random.uniform(50, 100),
-    }
-    return data
-
-def generate_recommendations(data):
-    recommendations = []
-    if data['total_consumption'][-1] > data['grid_generation'][-1]:
-        recommendations.append("Consider integrating additional renewable sources to meet the current demand.")
-    if data['storage_usage'][-1] > data['total_storage'] * 0.8:
-        recommendations.append("Energy storage is running low. Consider optimizing the grid or adding more storage.")
-    return recommendations
-
-def grid_health_status(data):
-    status = "Grid is operating normally."
-    if data['total_consumption'][-1] > 90:
-        status = "Warning: High consumption detected!"
-    if data['wind_speed'] > 15:
-        status = "Warning: High wind speeds, may affect wind turbine output."
-    return status
-
-def generate_trading_options(data):
-    if data['total_storage'] > 60:
-        return "Energy is available for export to neighboring countries."
-    else:
-        return "Energy reserves are low. Trading is not recommended at this moment."
+# import random
+# import pandas as pd 
+# def fetch_data():
+#     # Simulating fetching data from a database or API
+#     data = {
+#         'temperature': random.uniform(-10, 30),
+#         'wind_speed': random.uniform(0, 20),
+#         'weather_condition': random.choice(['Clear', 'Overcast Clouds', 'Thunderstorm', 'Rain']),
+#         'timestamps': pd.date_range("2025-01-01", periods=10, freq='H'),
+#         'total_consumption': [random.uniform(50, 100) for _ in range(10)],
+#         'grid_generation': [random.uniform(30, 80) for _ in range(10)],
+#         'storage_usage': [random.uniform(10, 30) for _ in range(10)],
+#         'solar_storage': random.uniform(10, 30),
+#         'wind_storage': random.uniform(10, 30),
+#         'hydro_storage': random.uniform(10, 30),
+#         'total_storage': random.uniform(50, 100),
+#     }
+#     return data
+
+# def generate_recommendations(data):
+#     recommendations = []
+#     if data['total_consumption'][-1] > data['grid_generation'][-1]:
+#         recommendations.append("Consider integrating additional renewable sources to meet the current demand.")
+#     if data['storage_usage'][-1] > data['total_storage'] * 0.8:
+#         recommendations.append("Energy storage is running low. Consider optimizing the grid or adding more storage.")
+#     return recommendations
+
+# def grid_health_status(data):
+#     status = "Grid is operating normally."
+#     if data['total_consumption'][-1] > 90:
+#         status = "Warning: High consumption detected!"
+#     if data['wind_speed'] > 15:
+#         status = "Warning: High wind speeds, may affect wind turbine output."
+#     return status
+
+# def generate_trading_options(data):
+#     if data['total_storage'] > 60:
+#         return "Energy is available for export to neighboring countries."
+#     else:
+#         return "Energy reserves are low. Trading is not recommended at this moment."