We live in a world where we buy things online. There are many websites that sell things and they have a lot of details about the products they sell. These details include the price of the products what other people think of them and what the products are. It takes a time to look at all these details by hand. That is why we use something called web scraping to collect details from websites. This project is about a system that uses Python to collect details from Flipkart. The system uses tools like Requests and Beautiful Soup and Selenium to get details about the products on Flipkart. We want to know the names of the products how much they cost what people think of them and what they are. We take the details we collect. Make them clean and easy to use. We store the Flipkart details in a format like a CSV file or a SQL database. We can use the Flipkart details we collect to see what is happening in the market. This system shows how we can use automation and collecting Flipkart details to help us make decisions and to do research on Flipkart products. The system is designed to extract product details from Flipkart. It uses Python to do this. We use the collected Flipkart data to do things like market analysis, price comparison and consumer behavior analysis. Consumer behavior analysis is the study of what people buy from Flipkart and why they buy these products from Flipkart. This project is about using automation to collect details from websites like Flipkart. It shows how this can be useful, for people who want to do research or make business decisions using Flipkart details. We can learn a lot from the details we collect from Flipkart. We can use Flipkart details to make decisions.
Web Scraping, Python, Flipkart, Data Extraction, BeautifulSoup, E-commerce Analysis, Data Mining
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