Rather than building scraping infrastructure from scratch for every project, a scraper framework provides opinionated scaffolding for common scraping tasks. Components typically include: a downloader that handles HTTP fetching, retries, and proxy rotation; a spider interface for defining extraction logic per page type; a middleware pipeline for pre/post-processing requests and responses; an item pipeline for validating and storing extracted data; and a scheduler for managing the crawl queue.
Scrapy is the dominant Python scraper framework, with a rich ecosystem of plugins covering browser integration (scrapy-playwright), proxy rotation, user-agent spoofing, MongoDB export, and more. For JavaScript environments, Crawlee (by Apify) provides a similar structured framework with Playwright integration. Colly is a popular Go alternative.
Frameworks trade flexibility for productivity: they enforce a project structure, provide battle-tested solutions to common problems (deduplication, politeness, error handling), and make it easy to scale from local development to distributed deployment. Custom one-off scrapers often start simpler (just `requests` + `BeautifulSoup`) and graduate to a framework as complexity grows.