Delete app.py

app.py

@@ -1,143 +0,0 @@
-import os
-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")
-st.sidebar.header("⚙️ User Input")
-
-# Tariff URLs for scraping
-tariff_urls = {
-    "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",
-    "TESCO": "https://tesco.gov.pk/index.php/electricity-traiff",
-}
-
-# Predefined appliances and their power in watts
-appliances = {
-    "LED Bulb (10W)": 10,
-    "Ceiling Fan (75W)": 75,
-    "Refrigerator (150W)": 150,
-    "Air Conditioner (1.5 Ton, 1500W)": 1500,
-    "Washing Machine (500W)": 500,
-    "Television (100W)": 100,
-    "Laptop (65W)": 65,
-    "Iron (1000W)": 1000,
-    "Microwave Oven (1200W)": 1200,
-    "Water Heater (2000W)": 2000,
-}
-
-def scrape_data():
-    """
-    Scrapes tariff data from the provided URLs using parallel requests for efficiency.
-    """
-    st.info("🔄 Scraping tariff data... Please wait.")
-    
-    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):
-    """
-    Calculates the carbon footprint based on energy consumption in kWh.
-    """
-    carbon_emission_factor = 0.75  # kg CO2 per kWh
-    return monthly_energy_kwh * carbon_emission_factor
-
-# Sidebar: Scrape Tariff Data
-if st.sidebar.button("Scrape Tariff Data"):
-    scrape_data()
-
-# Sidebar: Tariff Selection
-st.sidebar.subheader("💡 Select Tariff")
-try:
-    tariff_data = pd.read_csv("data/tariffs.csv")
-    tariff_types = tariff_data["category"].unique()
-    selected_tariff = st.sidebar.selectbox("Select your tariff category:", tariff_types)
-    rate_per_kwh = tariff_data[tariff_data["category"] == selected_tariff]["rate"].iloc[0]
-    st.sidebar.write(f"Rate per kWh: **{rate_per_kwh} PKR**")
-except FileNotFoundError:
-    st.sidebar.error("⚠️ Tariff data not found. Please scrape the data first.")
-    rate_per_kwh = 0
-
-# Sidebar: User Inputs for Appliances
-st.sidebar.subheader("🏠 Add Appliances")
-selected_appliance = st.sidebar.selectbox("Select an appliance:", list(appliances.keys()))
-appliance_power = appliances[selected_appliance]
-appliance_quantity = st.sidebar.number_input(
-    "Enter quantity:", min_value=1, max_value=10, value=1
-)
-usage_hours = st.sidebar.number_input(
-    "Enter usage hours per day:", min_value=1, max_value=24, value=5
-)
-
-# Add appliance details to the main list
-if "appliance_list" not in st.session_state:
-    st.session_state["appliance_list"] = []
-
-if st.sidebar.button("Add Appliance"):
-    st.session_state["appliance_list"].append(
-        {
-            "appliance": selected_appliance,
-            "power": appliance_power,
-            "quantity": appliance_quantity,
-            "hours": usage_hours,
-        }
-    )
-
-# Display the list of added appliances
-st.subheader("📋 Added Appliances")
-if st.session_state["appliance_list"]:
-    for idx, appliance in enumerate(st.session_state["appliance_list"], start=1):
-        st.write(
-            f"{idx}. **{appliance['appliance']}** - "
-            f"{appliance['power']}W, {appliance['quantity']} unit(s), "
-            f"{appliance['hours']} hours/day"
-        )
-
-# Electricity Bill and Carbon Footprint Calculation
-if st.session_state["appliance_list"] and rate_per_kwh > 0:
-    total_daily_energy_kwh = sum(
-        (appliance["power"] * appliance["quantity"] * appliance["hours"]) / 1000
-        for appliance in st.session_state["appliance_list"]
-    )
-    monthly_energy_kwh = total_daily_energy_kwh * 30  # Assume 30 days in a month
-    bill_amount = monthly_energy_kwh * rate_per_kwh  # Dynamic tariff rate
-    carbon_footprint = calculate_carbon_footprint(monthly_energy_kwh)
-
-    st.subheader("💵 Electricity Bill & 🌍 Carbon Footprint")
-    st.write(f"💵 **Estimated Electricity Bill**: **{bill_amount:.2f} PKR**")
-    st.write(f"🌍 **Estimated Carbon Footprint**: **{carbon_footprint:.2f} kg CO2 per month**")
-else:
-    st.info("ℹ️ Add appliances to calculate the electricity bill and carbon footprint.")