In today’s online shopping world, prices for the same product can vary across platforms like Amazon, Flipkart, Snapdeal, and Croma. To help users find the best deal, I built a real-time product price comparison tool using Python and web scraping.
💡 Project Overview
The goal of my project was simple:
Allow users to enter a product name → fetch live prices from multiple e-commerce websites → display results in a clean web page.
🛠️ Tech Stack Used
Python (main logic)
Selenium (for dynamic page scraping)
BeautifulSoup (for parsing HTML)
HTML/CSS (for front-end)
Flask (optional, for running web locally)
🔍 How It Works
User enters a product name in the HTML form.
The Python backend uses separate scripts to scrape:
Amazon
Flipkart
Snapdeal
Croma
It fetches:
Product Name
Price
Product URL
(Optional) Image
The data is shown on results.html page.
Clicking the URL takes user directly to the product listing.
🧠 Key Challenges Faced
Handling different HTML structures on each site.
Dynamic content loading via JavaScript (solved using Selenium).
Avoiding scraping blocks (using user-agent tricks and time delays).
Optimizing performance by letting users choose which websites to scrape.
🎯 Features
✅ Real-time scraping (no CSV files)
✅ Website selection filter (e.g., Amazon only, or Amazon + Flipkart)
✅ Simple UI (HTML + CSS)
✅ Results with name, price, and clickable product links
📸 Sample Output
A user searches “Redmi Note 13” → sees prices from 3 sites side-by-side → clicks the cheapest → buys it!
🧩 What's Next?
Add more websites (e.g., Ajio, TataCliq)
Add product images to improve UI
Host the project on cloud (Render or Railway)
📂 Codebase
I’ve structured the project into:
index.html – front end form
scrape_amazon.py, scrape_flipkart.py, etc. – individual scrapers
results.html – to display results
main.py – master controller for logic (optional Flask app)
🚀 Final Thoughts
This project helped me learn:
Real-world Python scraping
Managing HTML forms and back-end integration
Handling edge cases and data inconsistencies
It’s a great example of applying Python to solve practical e-commerce problems.
I’m proud of how it turned out, and I look forward to improving it further!
📂 Full Project Code: View on GitHub
💬 Have questions or want to try it out? DM me or leave a comment
— Ayesha Shaikh
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