crawleevsfirecrawl

Apache-2.0 175 26 22,720

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

- - - None

Apr 01 2024 0.0.0(2025-03-15 00:00:00 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.

Firecrawl is an AI-powered web scraping API that converts web pages into clean Markdown or structured data, optimized for use with large language models (LLMs) and retrieval-augmented generation (RAG) pipelines. It handles JavaScript rendering, anti-bot bypass, and content extraction automatically.

Firecrawl offers multiple modes:

Scrape Convert a single URL into clean Markdown, HTML, or structured data. Handles JavaScript rendering and anti-bot protections automatically.
Crawl Crawl an entire website starting from a URL, with configurable depth, URL patterns, and page limits. Returns all pages as clean Markdown.
Map Quickly discover all URLs on a website without fully scraping each page. Useful for sitemap generation and crawl planning.
Extract Use LLMs to extract specific structured data from pages based on a schema definition.

Key features:

Clean Markdown output ideal for LLM context windows
Automatic JavaScript rendering with headless browsers
Built-in anti-bot bypass for protected websites
Structured extraction with JSON schemas
Batch crawling with webhook notifications
Python and JavaScript SDKs

Firecrawl is a commercial API service (requires API key, has a free tier) backed by Y Combinator. It has become one of the most popular tools for feeding web content into AI applications and is widely used in the LLM/RAG ecosystem.

Note: while the primary service is an API, the core is open source and can be self-hosted.

Highlights

populartypescriptextendiblemiddlewaresoutput-pipelineslarge-scaleproxy

ai-poweredpopularasync

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']); ```

```python from firecrawl import FirecrawlApp app = FirecrawlApp(api_key="YOUR_API_KEY") # Scrape a single page - get clean markdown result = app.scrape_url("https://example.com/blog/article") print(result["markdown"]) # clean markdown content # Extract structured data with a schema result = app.scrape_url( "https://example.com/product/123", params={ "formats": ["extract"], "extract": { "schema": { "type": "object", "properties": { "name": {"type": "string"}, "price": {"type": "number"}, "description": {"type": "string"}, }, } }, }, ) print(result["extract"]) # {"name": "...", "price": 29.99, ...} # Crawl an entire website crawl_result = app.crawl_url( "https://example.com", params={"limit": 100, "scrapeOptions": {"formats": ["markdown"]}}, ) for page in crawl_result["data"]: print(page["metadata"]["title"], page["markdown"][:100]) # Map all URLs on a site map_result = app.map_url("https://example.com") print(f"Found {len(map_result['links'])} URLs") ```

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