Price Comparison Application for E-Commerce Using Web Scraping

Abstract: This paper presents a comprehensive approach to building a real-time e-commerce price comparison tool using Python, web scraping, and modern web frameworks. With the increasing prevalence of online shopping and growing cost awareness among consumers, a centralized platform that compares prices across popular websites significantly enhances the online shopping experience. Our system integrates scrapers for major e-commerce platforms including Amazon, Flipkart, Myntra, Croma, Google Shopping, and others. The tool displays optimized price comparisons, enables wishlist tracking, and offers statistical insights to users. The implementation leverages a Flask backend with Streamlit for the user interface, with SQLite database for persistence. Results show that users can save significant amounts on purchases through effective price comparison.

Keywords: E-commerce, Price Comparison, Web Scraping, Python, Flask, Streamlit, Data Analysis.