Web Scraping
BeginnerThe automated extraction of data from websites at scale — the engine behind price intelligence, SEO tools, market research and most AI training corpora.
In depth
Web scraping is programmatic browsing: software requests pages the way a browser would, then parses the HTML (or underlying APIs) into structured data — prices, listings, reviews, rankings, schedules. Done at scale it powers comparison shopping, search-intelligence platforms, academic research, lead generation and the datasets behind modern AI.
How it works in practice
A scraper has four jobs: fetch (HTTP clients or headless browsers for JavaScript-heavy sites), parse (CSS selectors, XPath, JSON), store (databases, warehouses), and survive — the part this industry exists for. Targets defend themselves with rate limits, IP reputation, browser fingerprinting and CAPTCHAs, so production scrapers pair rotating proxies with realistic headers, human-like pacing and fingerprint management.
The proxy connection
- Rate limits are per-IP — rotating pools spread requests until limits stop binding.
- Geo-content requires exiting from the right country; localized prices and SERPs differ by city.
- Trust tiers map to proxy types: tolerant targets accept datacenter; hardened ones demand residential or mobile.
Legality and ethics
Scraping publicly accessible data is broadly lawful in many jurisdictions (US courts in hiQ v. LinkedIn repeatedly held that public-data scraping does not violate anti-hacking law), but terms of service, copyright, and personal-data regulations like GDPR still apply. Responsible scrapers respect robots.txt where practical, throttle politely, avoid logged-in data they have no right to, and never overwhelm small sites.
Examples
- A travel aggregator scrapes airline and hotel sites hourly to power its fare comparison.
- An investment fund tracks retailer stock levels across regions as an alternative data signal.
- An SEO platform collects search results for millions of keywords daily to compute rank movements.
Common use cases
FAQs
Scraping publicly available data is generally lawful — US case law (hiQ v. LinkedIn) supports it — but it is not a blanket license: contracts you accepted, copyright on the content, and privacy laws covering personal data all still apply. High-stakes projects warrant legal review.
Because defenses count requests per IP. A single address making thousands of requests is rate-limited or banned within minutes; a rotating pool makes the same workload look like ordinary distributed visitors.
Start with datacenter for speed and cost. Escalate to residential when you hit blocks or need city-level geo-targeting, and reserve mobile for the most hostile targets. Many pipelines mix tiers by target difficulty.