This project is a web scraping application that extracts product details from Flipkart's mobile section. The scraper gathers information on various products, including their names, prices, descriptions, and ratings, across multiple pages. It is designed to help users understand how to collect and organize data from e-commerce websites for analysis.
- Scrapes product names, prices, descriptions, and ratings.
- Navigates through multiple pages of product listings.
- Utilizes Selenium for dynamic content handling and BeautifulSoup for data extraction.
- Saves the collected data into a CSV file for further analysis.
- Python
- Selenium
- BeautifulSoup
- Pandas
To run this project, you'll need to have Python installed on your machine. Follow these steps to set up the environment:
-
Clone this repository:
git clone https://github.com/arya-io/Flipkart_Scraping.git
-
Navigate to the project directory:
cd Flipkart_Scraping -
Install the required libraries:
pip install -r requirements.txt
- Open the Jupyter Notebook file
Flipkart_Scraping.ipynb. - Run each cell step-by-step to execute the web scraping process.
- The scraped data will be saved in
Flipkart_Scraping.csvin the project directory.
Please ensure you comply with Flipkart's terms of service when scraping their website.
Contributions are welcome! Please feel free to submit a pull request or open an issue for any enhancements or suggestions.
This project is licensed under the MIT License - see the LICENSE file for details.