Web scraping is the process of automatically collecting data from a website. This process is carried out using software or bots to extract and analyze specific information. Web scraping can be applied in various fields, for example:
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Data Collection and Analysis: Price comparison websites gather product information from e-commerce platforms to provide comparisons for users.
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Market Research: Companies collect information about products, prices, and other marketing strategies from competitors' websites.
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Academic Research: Researchers use web scraping to collect large datasets for their studies.
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News Aggregation: Articles and news from various news websites can be automatically gathered and compiled.
Web scraping typically involves several basic steps:
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Connecting to the Website: An HTTP request is sent to the target website.
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Retrieving HTML Code: The HTML content of the webpage is fetched.
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Processing HTML: The HTML code is parsed, and the target data elements are selected (e.g., specific tags or classes).
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Extracting Data: The parsed data is extracted and structured (e.g., saved into a database or CSV file).
Some commonly used tools and libraries for web scraping include:
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BeautifulSoup: A popular HTML and XML parsing library for Python.
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Scrapy: A powerful web scraping framework based on Python.
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Selenium: A tool used to automate web browsers, ideal for handling dynamic content.
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Puppeteer: A Node.js library that provides browser automation by controlling Google Chrome.