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• Use requests parameters to customize the HTTP request (e.g., add headers, modify the User-Agent).
• Handle anti-scraping measures by rotating User-Agents, adding delays between requests, or using a proxy.
• Use other libraries like scrapy or pyquery for more complex web scraping tasks.

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   Web scraping, the process of automatically extracting data from websites, has become a crucial skill in data collection and analysis. Python, with its simplicity and extensive libraries, is an ideal programming language for web scraping tasks. Libraries such as requests for handling HTTP requests and BeautifulSoup for parsing HTML and XML documents are particularly useful.