crawleevsferret

Apache-2.0 175 26 22,720

341.9 thousand (month) Apr 22 2022 3.16.0(2026-04-09 07:36:53 ago)

5,964 8 34 Apache-2.0

Oct 28 2020 58.1 thousand (month) v2.0.0-alpha.7(2026-04-07 15:33:51 ago)

Crawlee is a modern web scraping and browser automation framework for JavaScript and TypeScript, built by Apify. It is the successor to the Apify SDK and provides a unified interface for building reliable web scrapers and crawlers that can scale from simple scripts to large-scale data extraction projects.

Crawlee supports multiple crawling strategies through different crawler classes:

CheerioCrawler For fast, lightweight HTML scraping using Cheerio (no browser needed). Best for static pages.
PlaywrightCrawler Uses Playwright for full browser automation. Handles JavaScript-rendered pages, SPAs, and complex interactions.
PuppeteerCrawler Similar to PlaywrightCrawler but uses Puppeteer as the browser automation backend.
HttpCrawler Minimal crawler for raw HTTP requests without HTML parsing.

Key features include:

Automatic request queue management with configurable concurrency and rate limiting
Built-in proxy rotation with session management
Persistent request queue and dataset storage (local or cloud via Apify)
Automatic retry and error handling with configurable strategies
TypeScript-first design with full type safety
Middleware-like request/response hooks (preNavigationHooks, postNavigationHooks)
Output pipelines for storing extracted data
Easy deployment to Apify cloud platform

Crawlee is considered the most feature-complete web scraping framework in the JavaScript/TypeScript ecosystem, comparable to Python's Scrapy but with native browser automation support.

Ferret is a web scraping system. It aims to simplify data extraction from the web for UI testing, machine learning, analytics and more. ferret allows users to focus on the data. It abstracts away the technical details and complexity of underlying technologies using its own declarative language. It is extremely portable, extensible, and fast.

Features

Declarative language
Support of both static and dynamic web pages
Embeddable
Extensible

Ferret is always implemented in Python through pyfer

Highlights

populartypescriptextendiblemiddlewaresoutput-pipelineslarge-scaleproxy

Example Use

```javascript import { PlaywrightCrawler, Dataset } from 'crawlee'; // Create a crawler with Playwright for JS rendering const crawler = new PlaywrightCrawler({ // Limit concurrency to avoid overwhelming the target maxConcurrency: 5, // This function is called for each URL async requestHandler({ request, page, enqueueLinks }) { const title = await page.title(); // Extract data from the page const products = await page.$$eval('.product', (els) => els.map((el) => ({ name: el.querySelector('.name')?.textContent, price: el.querySelector('.price')?.textContent, })) ); // Store extracted data await Dataset.pushData({ url: request.url, title, products, }); // Follow links to crawl more pages await enqueueLinks({ globs: ['https://example.com/products/**'], }); }, }); // Start crawling await crawler.run(['https://example.com/products']); ```

```go // Example scraper for Google in Ferret: LET google = DOCUMENT("https://www.google.com/", { driver: "cdp", userAgent: "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/76.0.3809.87 Safari/537.36" }) HOVER(google, 'input[name="q"]') WAIT(RAND(100)) INPUT(google, 'input[name="q"]', @criteria, 30) WAIT(RAND(100)) CLICK(google, 'input[name="btnK"]') WAITFOR EVENT "navigation" IN google WAIT_ELEMENT(google, "#res") LET results = ELEMENTS(google, X("//*[text() = 'Search Results']/following-sibling::*/*")) FOR el IN results RETURN { title: INNER_TEXT(el, 'h3')?, description: INNER_TEXT(el, X("//em/parent::*")), url: ELEMENT(el, 'a')?.attributes.href } ```

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