Update app.py

app.py

@@ -1,29 +1,44 @@
 # app.py
 import os
 import streamlit as st
-from scraper import fetch_tariff_from_url  # Import the scraper function
-from bs4 import BeautifulSoup
-import urllib3
+from scraper import fetch_tariff_from_url
 import requests
 import plotly.graph_objects as go
 
-# ... (Other imports and constants like APPLIANCE_OPTIONS, EMISSION_FACTORS, CITIES)
+APPLIANCE_OPTIONS = { ... }  # Your existing appliance list
 
-# Combine the calculate_total_units and get_heating_degree_days functions here
-
-def calculate_footprint(distance_car, distance_bus, distance_plane, electricity_usage, diet_type, shopping_spent_pkr, city, house_area, exchange_rate):
-    # ... (Existing footprint calculation logic)
+# Tariff and Carbon Footprint related functions
+def calculate_total_units():
+    ...
 
 def get_exchange_rate():
-    # ... (Existing exchange rate function)
+    """Fetch the real-time USD to PKR conversion rate."""
+    try:
+        response = requests.get("https://open.er-api.com/v6/latest/PKR")
+        response.raise_for_status()
+        data = response.json()
+        if "rates" in data and "USD" in data["rates"]:
+            return 1 / data["rates"]["USD"]
+        else:
+            st.error("Exchange rate data is missing expected fields.")
+            return 300
+    except Exception as e:
+        st.error(f"Error fetching exchange rate: {e}")
+        return 300
+
+def get_heating_degree_days(latitude, longitude):
+    ...
+
+def calculate_footprint(distance_car, distance_bus, distance_plane, electricity_usage, diet_type, shopping_spent_pkr, city, house_area, exchange_rate):
+    ...
 
 # Streamlit App
 st.title("PowerCalc: AI-Driven Bill & Carbon Footprint Tracker")
 
-# Tariff Input Section
+# Tariff Input and Appliance Section
 st.sidebar.subheader("Fetch Tariff Data")
 tariff_url = st.sidebar.text_input("Enter URL to scrape tariff data:")
-load_type = st.sidebar.selectbox("Select Load Type", ["Residential", "Commercial", "Industrial", "Agriculture"]) 
+load_type = st.sidebar.selectbox("Select Load Type", ["Residential", "Commercial", "Industrial", "Agriculture"])
 
 if st.sidebar.button("Fetch Tariff"):
     rate = fetch_tariff_from_url(tariff_url, load_type)
@@ -33,42 +48,14 @@ if st.sidebar.button("Fetch Tariff"):
     else:
         st.sidebar.warning("Failed to fetch tariff rate. Ensure the URL and load type are correct.")
 
-# Appliance Input Section
-# ... (Existing code for adding appliances and displaying the list)
+# Add Appliances Section
+...
 
-# Monthly Bill Calculation Section
-if st.button("Calculate Monthly Bill"):
-    # ... (Existing code for calculating and displaying the bill)
-
-# Carbon Footprint Calculation Section
-st.header("Carbon Footprint Calculator")
+# Calculate Carbon Footprint Section
+st.header("Calculate Carbon Footprint")
 city = st.selectbox("Select the Nearest City", options=list(CITIES.keys()))
-distance_car = st.number_input("Monthly Distance Traveled by Car (km)", min_value=0.0)
-distance_bus = st.number_input("Monthly Distance Traveled by Bus (km)", min_value=0.0)
-distance_plane = st.number_input("Monthly Distance Traveled by Plane (km)", min_value=0.0)
-electricity_usage = st.number_input("Monthly Electricity Usage (kWh)", min_value=0.0)
-diet_type = st.radio("Diet Type", options=["meat_diet", "veg_diet"], index=0)
-shopping_spent_pkr = st.number_input("Monthly Shopping Expenditure (PKR)", min_value=0.0)
-house_area = st.number_input("House Area (m²)", min_value=0.0)
-
-exchange_rate = get_exchange_rate()
-st.info(f"Real-time USD to PKR exchange rate: {exchange_rate:.2f} PKR/USD")
-
+...
 if st.button("Calculate Carbon Footprint"):
-    result = calculate_footprint(
-        distance_car,
-        distance_bus,
-        distance_plane,
-        electricity_usage,
-        diet_type,
-        shopping_spent_pkr,
-        city,
-        house_area,
-        exchange_rate,
-    )
+    result = calculate_footprint(...)
     st.subheader(f"Your Estimated Monthly Carbon Footprint: {result['total_emissions']:.2f} kg CO2")
-    breakdown = result["breakdown"]
-    labels = list(breakdown.keys())
-    values = list(breakdown.values())
-    fig = go.Figure(data=[go.Pie(labels=labels, values=values, title="Carbon Footprint Breakdown")])
-    st.plotly_chart(fig)
+    ...