import streamlit as st
import requests
import pandas as pd
from datetime import datetime

st.title('SuperKart Data Viewer')
st.markdown('A simple Streamlit app to fetch data from the Flask API deployed on Hugging Face.')

# Define the API endpoint URL.
# *** REPLACE with your actual deployed Flask API URL ***
api_url = "https://<YOUR-FLASK-SPACE-ID>.hf.space/data"

def fetch_data():
    try:
        response = requests.get(api_url)
        if response.status_code == 200:
            return response.json()
        else:
            st.error(f"Error fetching data from API: {response.status_code} - {response.text}")
            return None
    except requests.exceptions.RequestException as e:
        st.error(f"Failed to connect to the API: {e}")
        return None

if st.button('Fetch and Process Data'):
    with st.spinner('Fetching and processing data...'):
        data = fetch_data()
        if data:
            df = pd.DataFrame(data)
            df['Years_Since_Establishment'] = datetime.now().year - df['Store_Establishment_Year']
            df['Product_MRP_per_Weight'] = df['Product_MRP'] / df['Product_Weight']
            st.success('Data fetched and processed successfully!')
            st.dataframe(df)