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    Python is a popular choice for web scraping due to its simplicity, readability, and a rich ecosystem of libraries designed for this purpose. Here are some of the most commonly used Python libraries for web scraping:

    BeautifulSoup

    BeautifulSoup is a widely-used library for parsing HTML and XML documents. It creates a parse tree for parsing HTML and XML documents and provides methods and Pythonic idioms for iterating, searching, and modifying the parse tree. It's known for its simplicity and ease of use, making it great for beginners and for quick scraping tasks.

    Example:

    import requests
    from bs4 import BeautifulSoup

    # Making a GET request
    r = requests.get('https://www.geeksforgeeks.org/python-programming-language/')

    # Parsing the HTML
    soup = BeautifulSoup(r.content, 'html.parser')
    print(soup.prettify())

    Attributes: Simple API, supports different parsers, automatically handles encodings.

    Scrapy

    Scrapy is a powerful and popular framework for extracting data from websites. It provides a complete toolset for web scraping, including a robust scheduler and an advanced pipeline system for storing scraped data. Scrapy is well-suited for large-scale scraping projects and offers flexibility in extracting data using XPath or CSS expressions.

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    Python Web Scraping: Full Tutorial With Examples (2025)
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    What tools can we use for web scraping with Python?
    List of tools we can use for web scraping with Python. Simple web scraping for static websites. Using Selenium for dynamic content or Javascript-heavy site. MechanicalSoup to automate some tasks in the browser. We have a lot of libraries in Python that we can use for scraping data from a website. Here are some of them:
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