Apify's web scraping and browser automation library for Node.js/TypeScript — HTTP and headless-browser crawlers with human-like anti-blocking defaults, queues, storage and proxies.
The TypeScript-native answer to production crawling: one API switches between cheap HTTP crawling and Playwright/Puppeteer when pages need a real browser, with anti-blocking fingerprints, request queues, proxy rotation and storage built in rather than bolted on. Reach for it when your stack is Node and the target fights back. NOT the pick for Python teams (its Python port is younger — Scrapy owns that ground), and mind the gravity: it's built by Apify and nudges toward their platform, though it runs fine standalone.
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README.md
A web scraping and browser automation library
Crawlee covers your crawling and scraping end-to-end and helps you build reliable scrapers. Fast.
Your crawlers will appear human-like and fly under the radar of modern bot protections even with the default configuration. Crawlee gives you the tools to crawl the web for links, scrape data, and store it to disk or cloud while staying configurable to suit your project's needs.
We recommend visiting the Introduction tutorial in Crawlee documentation for more information.
Crawlee requires Node.js 16 or higher.
With Crawlee CLI
The fastest way to try Crawlee out is to use the Crawlee CLI and choose the Getting started example. The CLI will install all the necessary dependencies and add boilerplate code for you to play with.
npx crawlee create my-crawler
cd my-crawler
npm start
Manual installation
If you prefer adding Crawlee into your own project, try the example below. Because it uses PlaywrightCrawler we also need to install Playwright. It's not bundled with Crawlee to reduce install size.
npm install crawlee playwright
import { PlaywrightCrawler, Dataset } from 'crawlee';
// PlaywrightCrawler crawls the web using a headless
// browser controlled by the Playwright library.
const crawler = new PlaywrightCrawler({
// Use the requestHandler to process each of the crawled pages.
async requestHandler({ request, page, enqueueLinks, log }) {
const title = await page.title();
log.info(`Title of ${request.loadedUrl} is '${title}'`);
// Save results as JSON to ./storage/datasets/default
await Dataset.pushData({ title, url: request.loadedUrl });
// Extract links from the current page
// and add them to the crawling queue.
await en
Continue your stack
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