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Mission of the Project

To build an efficient and reliable web scraping system that extracts real-time product information from Flipkart, enabling users to analyze prices, discounts, ratings, delivery details, and customer reviews. The project aims to simplify data collection for market research, price comparison, and business insights by automating the process with accurate, structured, and clean datasets.

Introduction

The Flipkart Web Scraping Project automatically collects and analyzes product data from one of India's largest e-commerce platforms. It extracts essential product details — name, price, discount, rating, delivery time, and customer reviews — in a structured format for further analysis and insight generation.

Problem Statement

E-commerce platforms like Flipkart contain vast amounts of product information, but manually collecting and analyzing this data is time-consuming, repetitive, and prone to human error. Businesses, students, and researchers need accurate and up-to-date product details for market analysis, price comparison, and trend forecasting.

Key Features

Homepage rendering
Dynamic URL routing
HTML template rendering
Form handling
CSV-ready data saving
Easy to extend

How It Works

User Request Flask Route Backend Logic BS4 Scraping CSV Output

Tools & Technologies

Python
Flask
HTML/CSS
VS Code

Demo & Repository