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README.md

@@ -1,19 +1,11 @@
+
 ---
-title: SuperKart Frontend App
-emoji: 🚀
-colorFrom: red
-colorTo: red
-sdk: docker
-app_port: 8501
-tags:
-- streamlit
-pinned: false
-short_description: front end app
+title: SuperKart Data Viewer
+emoji: 📊
+colorFrom: blue
+colorTo: purple
+sdk: streamlit
 ---
 
-# Welcome to Streamlit!
-
-Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
-
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+# SuperKart Data Viewer
+This is a simple Streamlit application that fetches and displays data from a Flask API.

app.py

@@ -0,0 +1,34 @@
+
+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)

requirements.txt

@@ -1,3 +1,4 @@
-altair
+
+streamlit
 pandas
-streamlit
+requests