Update app.py

app.py

@@ -1,103 +1,103 @@
-# import streamlit as st
-# import pandas as pd
-# import plotly.express as px
-# from app_backend import fetch_weather, generate_synthetic_data, optimize_load
-
-# # Constants
-# API_KEY = "84e26811a314599e940f343b4d5894a7"
-# LOCATION = "Pakistan"
-
-# # Sidebar
-# st.sidebar.title("Smart Grid Dashboard")
-# location = st.sidebar.text_input("Enter Location", LOCATION)
-
-# # Fetch and display weather data
-# weather = fetch_weather(API_KEY, location)
-# if weather:
-#     st.sidebar.write(f"Temperature: {weather['temperature']} °C")
-#     st.sidebar.write(f"Wind Speed: {weather['wind_speed']} m/s")
-#     st.sidebar.write(f"Weather: {weather['weather']}")
+import streamlit as st
+import pandas as pd
+import plotly.express as px
+from app_backend import fetch_weather, generate_synthetic_data, optimize_load
 
-# # Main dashboard with tabs
-# tabs = st.tabs(["Home", "Electricity Storage", "Electricity Trading"])
+# Constants
+API_KEY = "84e26811a314599e940f343b4d5894a7"
+LOCATION = "Pakistan"
 
-# with tabs[0]:
-#     st.title("Real-Time Smart Grid Dashboard")
+# Sidebar
+st.sidebar.title("Smart Grid Dashboard")
+location = st.sidebar.text_input("Enter Location", LOCATION)
 
-#     # Generate synthetic data
-#     data = generate_synthetic_data()
+# Fetch and display weather data
+weather = fetch_weather(API_KEY, location)
+if weather:
+    st.sidebar.write(f"Temperature: {weather['temperature']} °C")
+    st.sidebar.write(f"Wind Speed: {weather['wind_speed']} m/s")
+    st.sidebar.write(f"Weather: {weather['weather']}")
 
-#     # Plot total consumption, grid generation, and storage usage
-#     fig = px.line(data, x="timestamp", y=["total_consumption_kwh", "grid_generation_kwh", "storage_usage_kwh"],
-#                   title="Energy Consumption, Generation, and Storage Usage Over Time",
-#                   labels={"value": "Energy (kWh)", "variable": "Energy Source"})
-#     st.plotly_chart(fig)
+# Main dashboard with tabs
+tabs = st.tabs(["Home", "Electricity Storage", "Electricity Trading"])
 
-#     # Grid health overview
-#     st.subheader("Grid Health Overview")
-#     grid_health_counts = data["grid_health"].value_counts()
-#     st.bar_chart(grid_health_counts)
+with tabs[0]:
+    st.title("Real-Time Smart Grid Dashboard")
 
-#     # Optimization recommendations
-#     current_demand = data["total_consumption_kwh"].iloc[-1]
-#     current_solar = data["solar_output_kw"].iloc[-1]
-#     current_wind = data["wind_output_kw"].iloc[-1]
-#     recommendation = optimize_load(current_demand, current_solar, current_wind)
+    # Generate synthetic data
+    data = generate_synthetic_data()
 
-#     st.subheader("Recommendations")
-#     st.write(f"Current Load Demand: {current_demand} kWh")
-#     st.write(f"Solar Output: {current_solar} kW")
-#     st.write(f"Wind Output: {current_wind} kW")
-#     st.write(f"Recommendation: {recommendation}")
+    # Plot total consumption, grid generation, and storage usage
+    fig = px.line(data, x="timestamp", y=["total_consumption_kwh", "grid_generation_kwh", "storage_usage_kwh"],
+                  title="Energy Consumption, Generation, and Storage Usage Over Time",
+                  labels={"value": "Energy (kWh)", "variable": "Energy Source"})
+    st.plotly_chart(fig)
 
-# with tabs[1]:
-#     st.title("Energy Storage Overview")
+    # Grid health overview
+    st.subheader("Grid Health Overview")
+    grid_health_counts = data["grid_health"].value_counts()
+    st.bar_chart(grid_health_counts)
 
-#     # Total energy stored
-#     total_storage = 500  # Example of total energy storage
-#     st.subheader(f"Total Energy Stored: {total_storage} kWh")
+    # Optimization recommendations
+    current_demand = data["total_consumption_kwh"].iloc[-1]
+    current_solar = data["solar_output_kw"].iloc[-1]
+    current_wind = data["wind_output_kw"].iloc[-1]
+    recommendation = optimize_load(current_demand, current_solar, current_wind)
 
-#     # Energy storage contribution from different sources
-#     st.subheader("Energy Storage Contributions")
-#     energy_sources = pd.DataFrame({
-#         "Source": ["Wind", "Solar", "Turbine"],
-#         "Energy (kW/min)": [5, 7, 10]
-#     })
-#     st.bar_chart(energy_sources.set_index("Source"))
+    st.subheader("Recommendations")
+    st.write(f"Current Load Demand: {current_demand} kWh")
+    st.write(f"Solar Output: {current_solar} kW")
+    st.write(f"Wind Output: {current_wind} kW")
+    st.write(f"Recommendation: {recommendation}")
 
-#     # Show energy storage status with a rounded circle
-#     st.subheader("Energy Storage Circle")
-#     st.markdown("Energy storage is a combination of contributions from different renewable sources.")
+with tabs[1]:
+    st.title("Energy Storage Overview")
 
-#     # Visualization of energy storage circle using Plotly
-#     storage_data = {
-#         "Source": ["Wind", "Solar", "Turbine"],
-#         "Energy": [5, 7, 10],
-#     }
-#     storage_df = pd.DataFrame(storage_data)
-#     fig = px.pie(storage_df, names="Source", values="Energy", title="Energy Storage Sources")
-#     st.plotly_chart(fig)
+    # Total energy stored
+    total_storage = 500  # Example of total energy storage
+    st.subheader(f"Total Energy Stored: {total_storage} kWh")
+
+    # Energy storage contribution from different sources
+    st.subheader("Energy Storage Contributions")
+    energy_sources = pd.DataFrame({
+        "Source": ["Wind", "Solar", "Turbine"],
+        "Energy (kW/min)": [5, 7, 10]
+    })
+    st.bar_chart(energy_sources.set_index("Source"))
+
+    # Show energy storage status with a rounded circle
+    st.subheader("Energy Storage Circle")
+    st.markdown("Energy storage is a combination of contributions from different renewable sources.")
+
+    # Visualization of energy storage circle using Plotly
+    storage_data = {
+        "Source": ["Wind", "Solar", "Turbine"],
+        "Energy": [5, 7, 10],
+    }
+    storage_df = pd.DataFrame(storage_data)
+    fig = px.pie(storage_df, names="Source", values="Energy", title="Energy Storage Sources")
+    st.plotly_chart(fig)
 
-# with tabs[2]:
-#     st.title("Energy Trading Overview")
+with tabs[2]:
+    st.title("Energy Trading Overview")
 
-#     # Energy cubes
-#     st.subheader("Energy Cubes Stored")
-#     energy_cubes = pd.DataFrame({
-#         "Country": ["China", "Sri Lanka", "Bangladesh"],
-#         "Energy (kWh)": [100, 200, 300],
-#         "Shareable": [True, True, False]
-#     })
+    # Energy cubes
+    st.subheader("Energy Cubes Stored")
+    energy_cubes = pd.DataFrame({
+        "Country": ["China", "Sri Lanka", "Bangladesh"],
+        "Energy (kWh)": [100, 200, 300],
+        "Shareable": [True, True, False]
+    })
 
-#     # Displaying the energy cubes in a grid
-#     st.write("Stored energy can be shared with other countries.")
-#     st.dataframe(energy_cubes)
+    # Displaying the energy cubes in a grid
+    st.write("Stored energy can be shared with other countries.")
+    st.dataframe(energy_cubes)
 
-#     # Visualization of energy that can be shared
-#     st.subheader("Energy Trading Visualization")
-#     st.markdown("The following energy amounts are available for sharing with different countries.")
-#     trading_fig = px.bar(energy_cubes, x="Country", y="Energy (kWh)", color="Shareable", title="Energy Trading")
-#     st.plotly_chart(trading_fig)
+    # Visualization of energy that can be shared
+    st.subheader("Energy Trading Visualization")
+    st.markdown("The following energy amounts are available for sharing with different countries.")
+    trading_fig = px.bar(energy_cubes, x="Country", y="Energy (kWh)", color="Shareable", title="Energy Trading")
+    st.plotly_chart(trading_fig)
 
 
 # code 2
@@ -476,108 +476,108 @@
 # code 5
 
 
-import streamlit as st
-import pandas as pd
-import plotly.express as px
-from app_backend import fetch_weather, generate_synthetic_data, optimize_load
+# import streamlit as st
+# import pandas as pd
+# import plotly.express as px
+# from app_backend import fetch_weather, generate_synthetic_data, optimize_load
 
-# Constants
-API_KEY = "84e26811a314599e940f343b4d5894a7"
-LOCATION = "Pakistan"
+# # Constants
+# API_KEY = "84e26811a314599e940f343b4d5894a7"
+# LOCATION = "Pakistan"
 
-# Sidebar
-st.sidebar.title("Smart Grid Dashboard")
-location = st.sidebar.text_input("Enter Location", LOCATION)
+# # Sidebar
+# st.sidebar.title("Smart Grid Dashboard")
+# location = st.sidebar.text_input("Enter Location", LOCATION)
 
-# Fetch and display weather data
-weather = fetch_weather(API_KEY, location)
-if weather:
-    st.sidebar.write(f"Temperature: {weather['temperature']} °C")
-    st.sidebar.write(f"Wind Speed: {weather['wind_speed']} m/s")
-    st.sidebar.write(f"Weather: {weather['weather']}")
+# # Fetch and display weather data
+# weather = fetch_weather(API_KEY, location)
+# if weather:
+#     st.sidebar.write(f"Temperature: {weather['temperature']} °C")
+#     st.sidebar.write(f"Wind Speed: {weather['wind_speed']} m/s")
+#     st.sidebar.write(f"Weather: {weather['weather']}")
 
 
 
-# Tabs
-tab_home, tab_storage, tab_trading = st.tabs(["Home", "Power Storage", "Electricity Trade Management"])
+# # Tabs
+# tab_home, tab_storage, tab_trading = st.tabs(["Home", "Power Storage", "Electricity Trade Management"])
 
-# Home Tab
-with tab_home:
-    st.title("Real-Time Smart Grid Dashboard")
+# # Home Tab
+# with tab_home:
+#     st.title("Real-Time Smart Grid Dashboard")
 
-    # Generate synthetic data
-    data = generate_synthetic_data()
+#     # Generate synthetic data
+#     data = generate_synthetic_data()
 
-    # Grid Health
-    # st.subheader("Grid Health Overview")
-    # grid_health_counts = data["grid_health"].value_counts()
-    # st.bar_chart(grid_health_counts)
+#     # Grid Health
+#     # st.subheader("Grid Health Overview")
+#     # grid_health_counts = data["grid_health"].value_counts()
+#     # st.bar_chart(grid_health_counts)
 
-    # Power Consumption, Generation & Storage Graph
-    st.subheader("Power Consumption, Generation & Storage")
-    fig = px.line(data, x="timestamp", y=["load_demand_kwh", "solar_output_kw", "wind_output_kw"], 
-                  title="Power Consumption, Generation & Storage", labels={"value": "Power (MW)"})
-    fig.update_traces(line=dict(width=2))
-    st.plotly_chart(fig)
+#     # Power Consumption, Generation & Storage Graph
+#     st.subheader("Power Consumption, Generation & Storage")
+#     fig = px.line(data, x="timestamp", y=["load_demand_kwh", "solar_output_kw", "wind_output_kw"], 
+#                   title="Power Consumption, Generation & Storage", labels={"value": "Power (MW)"})
+#     fig.update_traces(line=dict(width=2))
+#     st.plotly_chart(fig)
 
-    # Grid Health
-    st.subheader("Grid Health Overview")
-    grid_health_counts = data["grid_health"].value_counts()
-    st.bar_chart(grid_health_counts)
+#     # Grid Health
+#     st.subheader("Grid Health Overview")
+#     grid_health_counts = data["grid_health"].value_counts()
+#     st.bar_chart(grid_health_counts)
 
     
-    # Optimization Recommendations
-    current_demand = data["load_demand_kwh"].iloc[-1]
-    current_solar = data["solar_output_kw"].iloc[-1]
-    current_wind = data["wind_output_kw"].iloc[-1]
-    recommendation = optimize_load(current_demand, current_solar, current_wind)
+#     # Optimization Recommendations
+#     current_demand = data["load_demand_kwh"].iloc[-1]
+#     current_solar = data["solar_output_kw"].iloc[-1]
+#     current_wind = data["wind_output_kw"].iloc[-1]
+#     recommendation = optimize_load(current_demand, current_solar, current_wind)
 
-    st.subheader("Recommendations")
-    st.write(f"Current Load Demand: {current_demand} MW")
-    st.write(f"Solar Output: {current_solar} MW")
-    st.write(f"Wind Output: {current_wind} MW")
-    st.write(f"Recommendation: {recommendation}")
+#     st.subheader("Recommendations")
+#     st.write(f"Current Load Demand: {current_demand} MW")
+#     st.write(f"Solar Output: {current_solar} MW")
+#     st.write(f"Wind Output: {current_wind} MW")
+#     st.write(f"Recommendation: {recommendation}")
 
-# Storage Tab
-with tab_storage:
-    st.title("Energy Storage Overview")
+# # Storage Tab
+# with tab_storage:
+#     st.title("Energy Storage Overview")
 
-    # Energy Contribution by Resources
-    st.subheader("Energy Contribution Percentage by Resources")
-    energy_data = {
-        "Wind": 5,
-        "Solar": 7,
-        "Turbine": 10
-    }
-    energy_df = pd.DataFrame(list(energy_data.items()), columns=["Source", "Energy (MW)"])
-    fig = px.pie(energy_df, values="Energy (MW)", names="Source", title="Energy Contribution by Resources")
-    st.plotly_chart(fig)
+#     # Energy Contribution by Resources
+#     st.subheader("Energy Contribution Percentage by Resources")
+#     energy_data = {
+#         "Wind": 5,
+#         "Solar": 7,
+#         "Turbine": 10
+#     }
+#     energy_df = pd.DataFrame(list(energy_data.items()), columns=["Source", "Energy (MW)"])
+#     fig = px.pie(energy_df, values="Energy (MW)", names="Source", title="Energy Contribution by Resources")
+#     st.plotly_chart(fig)
 
-    # Energy Storage Merge
-    st.subheader("Total Energy Stored")
-    st.write("Energy stored from all sources:")
-    energy_stored = sum(energy_data.values())
-    st.write(f"Total Energy Stored: {energy_stored} MW")
-    st.write("Energy sources merged into total energy storage:")
-    st.write(f"Total Energy Stored in Grid: {energy_stored} MW")
-
-# Trading Tab
-with tab_trading:
-    st.title("Electricity Trade Management")
-
-    # Simulating Electricity Trade (Energy cubes & trading)
-    st.subheader("Energy Trade Overview")
-    energy_trade = {
-        "USA": 50,
-        "Germany": 40,
-        "India": 30
-    }
-    trade_df = pd.DataFrame(list(energy_trade.items()), columns=["Country", "Energy (MW)"])
-    fig = px.bar(trade_df, x="Country", y="Energy (MW)", title="Energy Trading Overview")
-    st.plotly_chart(fig)
+#     # Energy Storage Merge
+#     st.subheader("Total Energy Stored")
+#     st.write("Energy stored from all sources:")
+#     energy_stored = sum(energy_data.values())
+#     st.write(f"Total Energy Stored: {energy_stored} MW")
+#     st.write("Energy sources merged into total energy storage:")
+#     st.write(f"Total Energy Stored in Grid: {energy_stored} MW")
+
+# # Trading Tab
+# with tab_trading:
+#     st.title("Electricity Trade Management")
+
+#     # Simulating Electricity Trade (Energy cubes & trading)
+#     st.subheader("Energy Trade Overview")
+#     energy_trade = {
+#         "USA": 50,
+#         "Germany": 40,
+#         "India": 30
+#     }
+#     trade_df = pd.DataFrame(list(energy_trade.items()), columns=["Country", "Energy (MW)"])
+#     fig = px.bar(trade_df, x="Country", y="Energy (MW)", title="Energy Trading Overview")
+#     st.plotly_chart(fig)
 
-    st.write("Energy cubes available for trading:")
-    st.write("The system can trade energy with other countries.")
+#     st.write("Energy cubes available for trading:")
+#     st.write("The system can trade energy with other countries.")
 
 # code 6