{"id":54543,"date":"2024-06-14T16:52:03","date_gmt":"2024-06-14T15:52:03","guid":{"rendered":"https:\/\/proxidize.com\/?post_type=use-cases&p=54543"},"modified":"2025-10-02T12:17:14","modified_gmt":"2025-10-02T11:17:14","slug":"web-scraping-with-beautiful-soup","status":"publish","type":"blog","link":"https:\/\/proxidize.com\/blog\/web-scraping-with-beautiful-soup\/","title":{"rendered":"Basics of Web Scraping with Beautiful Soup"},"content":{"rendered":"\n

Web scraping is an important technique for extracting information from websites, allowing users to gather data efficiently and systematically. By automating the process of collecting data, web scraping can save time and provide access to large amounts of information that would be impossible to gather manually.<\/p>\n\n\n\n

In this article, we will put our knowledge into practice with the basics of web scraping with Beautiful Soup, a powerful Python library designed for parsing HTML and XML documents. For a comprehensive understanding of web scraping, you can read our previous articles on web scraping<\/a> and web scraping tools<\/a>. They provide a solid foundation for anyone new to the field and looking to hit the ground running.<\/p>\n\n\n\n

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What is Beautiful Soup?<\/h2>\n\n\n\n

Beautiful Soup is a versatile library in Python that can be used for web scraping. It pulls data out of HTML and XML files and creates a parse tree from page source codes that can be used to extract data easily. This lends itself well to applications in research, business intelligence, and competitive analysis, among others.<\/p>\n\n\n\n

HTML and XML are standard languages used to create and structure data on the web. HTML  is mainly used to create web pages and web applications. It defines elements like headings, paragraphs, and links. XML, on the other hand, is designed to store and transport data in a way that is both readable by humans and machines.<\/p>\n\n\n\n

A parse tree, in the context of web scraping, is a hierarchical structure that represents the syntax of a document. It breaks the document down into its constituent parts, such as tags, attributes, and text, in a tree-like format. This structure allows for easy navigation of the document, making data extraction more efficient.<\/p>\n\n\n\n

When you make an HTTP request to a webpage, the server responds with the page\u2019s HTML content \u2014 which you can see by looking at the page source of any web page. Beautiful Soup takes this raw HTML and transforms it into a parse tree, which lets you find specific elements as needed.<\/p>\n\n\n\n

Compared to other web scraping libraries, Beautiful Soup has its advantages. Unlike Selenium, which is designed for interacting with dynamic and JavaScript-heavy web pages, Beautiful Soup excels at parsing and extracting data from static HTML content. It is also simpler and more lightweight than comprehensive frameworks like Scrapy.<\/p>\n\n\n\n

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Understanding HTML Structure<\/h2>\n\n\n\n

HTML documents are structured with tags, which we\u2019ve learned to identify elements like headings, paragraphs, links, and images. Each tag is enclosed in angle brackets (e.g. <tag>), and many elements have opening and closing tags (e.g. <p><\/p> for paragraphs). Tags can also have attributes that provide additional information about the element, such as id, class, and src for images.<\/p>\n\n\n\n

Understanding HTML is important for web scraping because it lets you navigate to and extract the specific data you need from the page. This, in turn, will enable you to write more precise scripts.<\/p>\n\n\n\n

Here is a simple example of HTML.<\/p>\n\n\n\n

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