webscraping

Web scraping is the process of automatically extracting data from websites using software programs. It typically involves fetching web pages, parsing the markup or rendered DOM, and extracting targeted information such as product names, prices, reviews, or metadata. Scraping is often paired with web crawling, a broader activity that discovers content by following links, while scraping focuses on retrieving and structuring data from the retrieved pages. The resulting data is usually stored in structured formats such as CSV, JSON, or a database for analysis, indexing, or reuse in other applications.

Techniques and tools for web scraping include making HTTP requests with libraries like requests or urllib, and parsing HTML with tools such as BeautifulSoup or lxml. More advanced frameworks like Scrapy support large-scale scraping projects. For sites that render content with JavaScript, browser automation tools such as Selenium or Playwright simulate user interaction to access the rendered content, sometimes using headless browsers.

Common applications include price monitoring, market research, competitive intelligence, data journalism, and the compilation of large datasets for academic or business use. Challenges include anti-scraping measures such as CAPTCHA, IP blocking, and rate limiting, as well as difficulties with dynamic content, authentication, and legal or ethical considerations.

Legal and ethical considerations emphasize compliance with a site’s terms of service and copyright or privacy laws. Respecting robots.txt, using responsible request rates, and obtaining permission when necessary are widely recommended. When possible, using official APIs is preferred for obtaining data with proper licensing and stability.