Update app_backend.py

app_backend.py

@@ -45,99 +45,99 @@
 # code2
 
 
+import pandas as pd
+import numpy as np
+from datetime import datetime, timedelta
+import requests
+
+# 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 data
+def generate_synthetic_data():
+    time_index = pd.date_range(start=datetime.now(), periods=24, freq="H")
+    return pd.DataFrame({
+        "timestamp": time_index,
+        "total_power_consumption_mw": np.random.randint(200, 500, len(time_index)),
+        "grid_generation_mw": np.random.randint(100, 300, len(time_index)),
+        "storage_utilization_mw": np.random.randint(50, 150, len(time_index)),
+    })
+
+# Generate storage data
+def generate_storage_data():
+    return {
+        "wind": 5,
+        "solar": 7,
+        "turbine": 10,
+        "total_stored_kwh": 2000
+    }
+
+# Export functions for use in Streamlit
+if __name__ == "__main__":
+    print("Backend ready!")
+
+
+# code 3
 # import pandas as pd
 # import numpy as np
 # from datetime import datetime, timedelta
-# import requests
 
-# # 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
+# # Function to fetch weather data remains unchanged
 
-# # Generate synthetic data
+# # 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,
-#         "total_power_consumption_mw": np.random.randint(200, 500, len(time_index)),
-#         "grid_generation_mw": np.random.randint(100, 300, len(time_index)),
-#         "storage_utilization_mw": np.random.randint(50, 150, len(time_index)),
+#         "power_consumption_mw": np.random.randint(50, 200, len(time_index)),
+#         "grid_generation_mw": np.random.randint(30, 150, len(time_index)),
+#         "storage_utilization_mw": np.random.randint(10, 50, len(time_index)),
+#         "grid_health": np.random.choice(["Good", "Moderate", "Critical"], len(time_index))
 #     })
 
-# # Generate storage data
+# # Generate synthetic storage data
 # def generate_storage_data():
+#     wind_storage = np.random.randint(5, 15)
+#     solar_storage = np.random.randint(7, 20)
+#     turbine_storage = np.random.randint(10, 25)
+#     total_storage = wind_storage + solar_storage + turbine_storage
 #     return {
-#         "wind": 5,
-#         "solar": 7,
-#         "turbine": 10,
-#         "total_stored_kwh": 2000
+#         "wind_storage_mw": wind_storage,
+#         "solar_storage_mw": solar_storage,
+#         "turbine_storage_mw": turbine_storage,
+#         "total_storage_mw": total_storage
 #     }
 
-# # Export functions for use in Streamlit
-# if __name__ == "__main__":
-#     print("Backend ready!")
-
-
-# code 3
-import pandas as pd
-import numpy as np
-from datetime import datetime, timedelta
-
-# Function to fetch weather data remains unchanged
-
-# 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,
-        "power_consumption_mw": np.random.randint(50, 200, len(time_index)),
-        "grid_generation_mw": np.random.randint(30, 150, len(time_index)),
-        "storage_utilization_mw": np.random.randint(10, 50, len(time_index)),
-        "grid_health": np.random.choice(["Good", "Moderate", "Critical"], len(time_index))
-    })
-
-# Generate synthetic storage data
-def generate_storage_data():
-    wind_storage = np.random.randint(5, 15)
-    solar_storage = np.random.randint(7, 20)
-    turbine_storage = np.random.randint(10, 25)
-    total_storage = wind_storage + solar_storage + turbine_storage
-    return {
-        "wind_storage_mw": wind_storage,
-        "solar_storage_mw": solar_storage,
-        "turbine_storage_mw": turbine_storage,
-        "total_storage_mw": total_storage
-    }
-
-# Generate synthetic trade data
-def generate_trade_data():
-    countries = ["Country A", "Country B", "Country C"]
-    exports = np.random.randint(10, 50, len(countries))
-    imports = np.random.randint(5, 30, len(countries))
-    return pd.DataFrame({
-        "country": countries,
-        "exports_mw": exports,
-        "imports_mw": imports
-    })
+# # Generate synthetic trade data
+# def generate_trade_data():
+#     countries = ["Country A", "Country B", "Country C"]
+#     exports = np.random.randint(10, 50, len(countries))
+#     imports = np.random.randint(5, 30, len(countries))
+#     return pd.DataFrame({
+#         "country": countries,
+#         "exports_mw": exports,
+#         "imports_mw": imports
+#     })
 
-# Updated optimization recommendation
-def optimize_load(demand, generation, storage):
-    if generation + storage >= demand:
-        return "Grid is Stable with Current Supply"
-    elif demand - (generation + storage) < 20:
-        return "Activate Backup or Optimize Load"
-    else:
-        return "Immediate Action Required: Adjust Load or Increase Generation"
+# # Updated optimization recommendation
+# def optimize_load(demand, generation, storage):
+#     if generation + storage >= demand:
+#         return "Grid is Stable with Current Supply"
+#     elif demand - (generation + storage) < 20:
+#         return "Activate Backup or Optimize Load"
+#     else:
+#         return "Immediate Action Required: Adjust Load or Increase Generation"
 
-# Export functions
-if __name__ == "__main__":
-    print("Backend ready for enhanced dashboard!")
+# # Export functions
+# if __name__ == "__main__":
+#     print("Backend ready for enhanced dashboard!")