Web Scraping

Web scraping is the automated collection and extraction of data from web pages or other web responses. A scraper fetches content, parses the fields it needs, and stores normalized results for analysis or another application.

Fetching may use a basic HTTP client for static responses or a browser engine when a page depends on JavaScript and interactive state. Parsing can rely on HTML selectors, structured data, embedded JSON, or documented response formats. Storage ranges from a local file to a database, but useful systems also record source URLs, collection times, and enough context to detect stale or malformed results.

Scraping differs from crawling, though one system may do both. A crawler discovers URLs by following links. A scraper extracts specific data from pages that are already known or discovered during the crawl. Reliable projects bound concurrency, retry temporary failures, validate returned content, deduplicate records, and watch for page changes that break selectors.

Automation should respect site terms, access controls, robots.txt guidance, and applicable law. Do not treat a technically reachable page as permission to collect or reuse its contents.

The complete Python web scraping guide gives an end-to-end example.

Related terms: web crawler and headless browser.