WELCOME TO webscraping.space * Now serving fresh web scraping tutorials * No JavaScript frameworks were harmed in the scraping of these pages * Please sign the guestbook * UNDER CONSTRUCTION -- but the content works! * Bookmark this page (Ctrl+D)WELCOME TO webscraping.space * Now serving fresh web scraping tutorials * No JavaScript frameworks were harmed in the scraping of these pages * Please sign the guestbook * UNDER CONSTRUCTION -- but the content works! * Bookmark this page (Ctrl+D)
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webscraping.space

A field guide to scraping the modern web.

A no-nonsense, hands-on blog about extracting data from websites. From your first requests.get() to scrapers that survive at scale. We cover Python and Node.js, HTML parsing, headless browsers, anti-bot defenses, and how to stay on the right side of robots.txt. New posts whenever the spider finishes crawling.

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What is web scraping?

Web scraping is the automated extraction of data from web pages. A scraper is a program that downloads HTML (or intercepts a site API responses), parses the structure, and pulls out the fields you care about. Prices, articles, contact info, product catalogs, research datasets.

In practice a modern scraper combines three pieces: a fetcher (an HTTP client or a headless browser), a parser (CSS or XPath selectors over the DOM), and a pipeline (dedup, storage, scheduling). The hard part is rarely the parsing. It is fetching reliably when the site rate-limits you, fingerprints your TLS handshake, or hides content behind JavaScript and bot detection.

If a human can see it in a browser, a scraper can capture it. The only real questions are how much load you place on the target and whether the site terms let you.

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Where to start