Update app.py

app.py

@@ -2,6 +2,7 @@
 import streamlit as st
 import scraper
 
+# URLs for different companies
 tariff_urls = {
     "IESCO": "https://iesco.com.pk/index.php/customer-services/tariff-guide",
     "FESCO": "https://fesco.com.pk/tariff",
@@ -16,27 +17,51 @@ tariff_urls = {
 def main():
     st.title("PowerCalc: AI-Driven Bill & Carbon Footprint Tracker")
     
+    # User input
     company = st.selectbox("Select your electricity company", list(tariff_urls.keys()))
     appliance_name = st.text_input("Appliance Name")
     load = st.number_input("Load of Appliance (kW)", min_value=0.0)
     daily_usage = st.number_input("Daily Usage Time (hours)", min_value=0.0)
     
     if st.button("Calculate"):
+        # Fetch the tariff data for the selected company
         url = tariff_urls.get(company)
         tariff_data = scraper.fetch_tariff_data(url)
-        monthly_bill = calculate_monthly_bill(tariff_data, load, daily_usage)
-        carbon_footprint = calculate_carbon_footprint(load, daily_usage)
         
-        st.write(f"Monthly Bill: {monthly_bill}")
-        st.write(f"Carbon Footprint: {carbon_footprint}")
+        if tariff_data:
+            # Calculate monthly bill and carbon footprint
+            monthly_bill = calculate_monthly_bill(tariff_data, load, daily_usage)
+            carbon_footprint = calculate_carbon_footprint(load, daily_usage)
+            
+            st.write(f"Monthly Bill for {appliance_name}: Rs. {monthly_bill}")
+            st.write(f"Carbon Footprint: {carbon_footprint} kg CO2")
+        else:
+            st.write("Error fetching tariff data. Please try again.")
 
 def calculate_monthly_bill(tariff_data, load, daily_usage):
-    # Implement the bill calculation logic
-    pass
+    daily_consumption = load * daily_usage  # kWh per day
+    monthly_consumption = daily_consumption * 30  # kWh per month
+    
+    total_bill = 0
+    for slab in tariff_data:
+        slab_range = slab['slab'].split('-')
+        lower_limit = float(slab_range[0])
+        upper_limit = float(slab_range[1]) if len(slab_range) > 1 else float('inf')
+        
+        if monthly_consumption > lower_limit:
+            consumption_in_slab = min(monthly_consumption, upper_limit) - lower_limit
+            total_bill += consumption_in_slab * slab['rate']
+    
+    return round(total_bill, 2)
 
 def calculate_carbon_footprint(load, daily_usage):
-    # Implement the carbon footprint calculation logic
-    pass
+    daily_consumption = load * daily_usage  # kWh per day
+    monthly_consumption = daily_consumption * 30  # kWh per month
+    
+    # Assuming 0.92 kg CO2 per kWh
+    emissions_factor = 0.92
+    carbon_footprint = monthly_consumption * emissions_factor
+    return round(carbon_footprint, 2)
 
 if __name__ == "__main__":
     main()