Web Scraping with Beautiful Soup - Scraping Seller Details

This Jupyter Notebook provides a demonstration of web scraping using Beautiful Soup to extract seller details from a website. The notebook focuses on retrieving information such as phone numbers, addresses, and names of sellers. Before using this script, make sure to review and comply with the website's terms of service and legal requirements.

Requirements

• Python 3.x
• Jupyter Notebook
• BeautifulSoup (bs4)
• Requests

Install the required packages using the following command:

pip install beautifulsoup4 requests

Usage

1. Download the Jupyter Notebook file (webscraping.ipynb).

2. Open the Jupyter Notebook in your local environment.

3. Modify the following variables in the notebook:

   • target_url: The URL of the website you want to scrape.
   • phone_selector: The HTML selector for the phone numbers.
   • address_selector: The HTML selector for the addresses.
   • name_selector: The HTML selector for the seller names.

target_url = 'https://example.com'
phone_selector = 'your-phone-selector'
address_selector = 'your-address-selector'
name_selector = 'your-name-selector'

4. Run the notebook cell by cell to execute the scraping process.

The notebook will fetch the specified information from the provided website and display the details within the notebook.

Important Notes

• Respect the website's terms of service and policies.
• Web scraping may be subject to legal restrictions, so ensure compliance with applicable laws.
• Introduce delays between requests to avoid overloading the server and being blocked.
• Regularly check and update your code if the website's structure changes.

Disclaimer

This notebook is provided for educational purposes only. Use it responsibly and ensure that your actions comply with the legal and ethical standards of web scraping. The developer is not responsible for any misuse of this notebook.