Automated Price Comparison and Tracking System

In today’s rapidly evolving e-commerce landscape, product prices fluctuate frequently due to various factors such as demand, supply, seller strategies, seasonal sales, and exclusive discounts. Consumers often struggle to track these frequent price changes manually, making it difficult to determine the best time to purchase a product. This project, "Flipkart Price Tracker Using Python," is designed to address this issue by automating the process of monitoring price variations of products listed on Flipkart. The system utilizes web scraping techniques with BeautifulSoup and Requests to extract real-time price data from Flipkart’s website. The collected data is then stored in a structured database to maintain historical records of price fluctuations. By analyzing the stored data, users can easily compare old and current prices, identify trends in pricing, and make informed purchasing decisions. Additionally, this system eliminates the need for users to manually check prices repeatedly. Instead, it provides a user-friendly interface to display tracked prices efficiently. This document provides a comprehensive overview of the project, including the problem statement, objectives, proposed solution, system implementation, results, and analysis. By leveraging Python for data extraction and database management, this project offers an effective solution for consumers to make better shopping decisions.