Web scraping is a powerful tool for extracting data from websites, and with Python, you can automate this process efficiently. In this tutorial, we'll walk through a Python script that scrapes product data from a website. We'll cover the key steps, challenges, and how to save and use the scraped data effectively.
What is Web Scraping?
Web scraping involves extracting data from websites and saving it in a structured format. This is especially useful for tasks like data analysis, price comparison, or building machine learning datasets. However, it's essential to respect website terms of service and ensure compliance with ethical guidelines.
How This Script Works
This tutorial demonstrates scraping product data from a sample website. The code performs the following tasks:
1. Find All Links on the Website: A recursive function identifies and collects all internal links on the website up to a specified depth.
2. Filter Product Links: Extracts only those links that match the product URL pattern.
3. Scrape Data from Product Pages: Retrieves product details, including descriptions, images, and categories, from filtered links.
4. Save and Manage Data: Stores the data in a JSON file for further use.
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