Automated Website Suggestion for E-Commerce through Web Scraping

Capturing real time product information from e-commerce platforms is the core task of the project. In this project by using python web crawling technologies like beautiful soup and selenium we crawl the details of requested product from different e-commerce platforms such as Amazon, Beautiful Soup, which is a python library is used to get requests from users. After getting the requests, Requests library is used to fetch the HTML content of the target e-commerce pages. From the fetched HTML content, specific products details like name, price, description, ratings, discounts, delivery charges, and reviews are extracted and saved as a csv file. Then the details of the product with minimum price is identified after conducting a comparative analysis and displayed. This automation enhance consumer decision making by aggregating and analyzing product data from online retailers in real time. The performance of the proposed project will be evaluated by using error rate and by measuring speed retrival