Update app.py

app.py

@@ -5,6 +5,40 @@ from scraper import fetch_tariff_from_url
 import requests
 import plotly.graph_objects as go
 
+# Define the CITIES dictionary
+CITIES = {
+    "Islamabad": "IESCO",
+    "Faisalabad": "FESCO",
+    "Hyderabad": "HESCO",
+    "Karachi": "KE",
+    "Lahore": "LESCO",
+    "Peshawar": "PESCO",
+    "Quetta": "QESCO"
+}
+
+# Add a select box for the user to choose the nearest city
+city = st.selectbox("Select the Nearest City", options=list(CITIES.keys()))
+
+# Display the selected city and corresponding company
+st.write(f"You selected: {city}, served by: {CITIES[city]}")
+
+# Replace the URL with the selected city's company URL
+url_dict = {
+    "IESCO": "https://iesco.com.pk/index.php/customer-services/tariff-guide",
+    "FESCO": "https://fesco.com.pk/tariff",
+    "HESCO": "http://www.hesco.gov.pk/htmls/tariffs.htm",
+    "KE": "https://www.ke.com.pk/customer-services/tariff-structure/",
+    "LESCO": "https://www.lesco.gov.pk/ElectricityTariffs",
+    "PESCO": "https://pesconlinebill.pk/pesco-tariff/",
+    "QESCO": "http://qesco.com.pk/Tariffs.aspx"
+}
+
+# Use the selected company to fetch data
+selected_url = url_dict[CITIES[city]]
+st.write(f"Fetching data from: {selected_url}")
+
+# Continue with your scraping or data fetching logic using `selected_url`
+
 APPLIANCE_OPTIONS = { ... }  # Your existing appliance list
 
 # Tariff and Carbon Footprint related functions