anil-matcha/webscraping

This repository contains a simple script that pulls product reviews from Flipkart, the popular Indian shopping site. You give it a search term like "laptops," and it goes out and grabs the review text that shoppers have left on matching product pages. If you are trying to understand what customers think about a category of products without clicking through dozens of pages yourself, this tool does the heavy lifting for you. Under the hood, the script works by acting like a regular web browser. It sends a request to Flipkart's website for your search term, downloads the resulting page content, and then sifts through the underlying HTML code to find the specific sections where reviews live. It relies on two common Python building blocks to do this: one to handle the actual web requests and fetch the pages, and another to parse and navigate the resulting text so the script can pull out the exact review data. Someone building a product, running market research, or analyzing consumer sentiment would find this useful. For example, if you are a founder deciding whether to sell a new laptop stand on Flipkart, you could use a script like this to collect what buyers complain about across existing listings. A product manager might use it to look for recurring feature requests in the reviews of competing products. The README is very sparse and does not go into detail about how the extracted reviews are saved or formatted after they are pulled. It is a lightweight utility rather than a full application, so anyone using it should expect a straightforward starting point that they might need to adapt for larger or more complex data-gathering projects.