Web Scraping Tutorial: Extract Data from Websites Using Python

This tutorial demonstrates how to efficiently extract data from websites using Python, a powerful tool for web scraping automation. We'll build a Python script to scrape product information, covering essential steps, potential difficulties, and effective data management techniques.

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Understanding Web Scraping

Web scraping extracts data from websites and organizes it into a usable format. This is invaluable for various applications, including data analysis, price comparisons, and creating machine learning datasets. However, it's crucial to adhere to a website's terms of service and maintain ethical scraping practices.

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Script Functionality Explained

This tutorial uses a sample website to illustrate product data scraping. The script performs these key functions:

1. Comprehensive Link Discovery: A recursive function systematically discovers and collects all internal website links to a defined depth.

2. Product Link Filtering: Isolates links that conform to a specific product URL pattern.

3. Product Page Data Extraction: Retrieves product information, such as descriptions, images, and categories, from the filtered links.

4. Data Storage and Organization: Saves the extracted data in a JSON file for convenient access and future use.

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