Update app.py

app.py

@@ -3,6 +3,8 @@ import requests
 import streamlit as st
 import pandas as pd
 from scraper import scrape_tariffs
+from concurrent.futures import ThreadPoolExecutor, as_completed
+import time
 
 # Streamlit App: Electricity Bill & Carbon Footprint Estimator
 st.title("🔌 Electricity Bill & Carbon Footprint Estimator")
@@ -36,10 +38,34 @@ appliances = {
 
 def scrape_data():
     """
-    Scrapes tariff data from the provided URLs.
+    Scrapes tariff data from the provided URLs using parallel requests for efficiency.
     """
     st.info("🔄 Scraping tariff data... Please wait.")
-    scrape_tariffs(list(tariff_urls.values()))
+    
+    def fetch_url(url):
+        """
+        Fetches data from the given URL and returns the response.
+        """
+        try:
+            response = requests.get(url, timeout=10)
+            return response.text
+        except requests.exceptions.RequestException as e:
+            st.warning(f"⚠️ Failed to fetch {url}: {e}")
+            return None
+
+    # Use ThreadPoolExecutor for parallel scraping
+    with ThreadPoolExecutor() as executor:
+        future_to_url = {executor.submit(fetch_url, url): url for url in tariff_urls.values()}
+        for future in as_completed(future_to_url):
+            url = future_to_url[future]
+            response = future.result()
+            if response:
+                st.write(f"✅ Successfully fetched data from: {url}")
+                # Pass the response to your scraping function if necessary
+                # Example: parse_and_save_data(response)
+            else:
+                st.write(f"❌ Failed to fetch data from: {url}")
+    
     st.success("✅ Tariff data scraping complete.")
 
 def calculate_carbon_footprint(monthly_energy_kwh):