When should I use Crawlee instead of Cheerio for web scraping?

Choosing between Crawlee and Cheerio for your web scraping project depends on the complexity of your target websites, scalability requirements, and whether you need to handle JavaScript-rendered content. While Cheerio is a lightweight HTML parser, Crawlee is a full-featured web scraping framework that provides comprehensive crawling capabilities, browser automation, and production-ready features.

Understanding the Core Differences

Cheerio is a fast, flexible jQuery-like library for parsing and manipulating HTML in Node.js. It's designed for static HTML parsing and doesn't execute JavaScript or manage complex crawling workflows.

Crawlee is a complete web scraping and browser automation framework built on top of libraries like Puppeteer, Playwright, and Cheerio itself. It provides request management, proxy rotation, session handling, and automatic retries out of the box.

When to Use Cheerio

Simple Static HTML Parsing

Cheerio excels when you're dealing with straightforward HTML parsing tasks on static websites. If the content you need is present in the initial HTML response without JavaScript rendering, Cheerio is the ideal choice.

const cheerio = require('cheerio');
const axios = require('axios');

async function scrapeStaticPage() {
  const { data } = await axios.get('https://example.com/products');
  const $ = cheerio.load(data);

  const products = [];
  $('.product-item').each((i, element) => {
    products.push({
      title: $(element).find('.product-title').text(),
      price: $(element).find('.product-price').text(),
      url: $(element).find('a').attr('href')
    });
  });

  return products;
}

Performance-Critical Applications

Cheerio's lightweight nature makes it significantly faster than browser-based solutions. When you're scraping thousands of simple pages and performance is crucial, Cheerio's minimal overhead provides excellent throughput.

Low Memory Requirements

Since Cheerio doesn't launch browser instances, it consumes minimal memory—typically just a few megabytes per request compared to hundreds of megabytes for headless browsers.

Quick Prototyping

For rapid experimentation and testing selectors, Cheerio's simple API allows you to quickly iterate and validate your scraping logic.

When to Use Crawlee

JavaScript-Rendered Content

Modern single-page applications (SPAs) built with React, Vue, Angular, or other JavaScript frameworks require a browser to render content. Crawlee integrates with Puppeteer and Playwright to handle these scenarios.

import { PlaywrightCrawler } from 'crawlee';

const crawler = new PlaywrightCrawler({
  requestHandler: async ({ page, request, enqueueLinks }) => {
    // Wait for dynamic content to load
    await page.waitForSelector('.dynamic-content');

    const products = await page.$$eval('.product-item', items => {
      return items.map(item => ({
        title: item.querySelector('.product-title')?.textContent,
        price: item.querySelector('.product-price')?.textContent,
        reviews: item.querySelector('.reviews')?.textContent
      }));
    });

    console.log(`Scraped ${products.length} products from ${request.url}`);

    // Automatically discover and queue new links
    await enqueueLinks({
      selector: '.pagination a',
      label: 'LISTING'
    });
  }
});

await crawler.run(['https://example.com/products']);

Complex Multi-Page Crawling

When you need to crawl hundreds or thousands of pages with automatic link discovery, request queueing, and state management, Crawlee provides a robust foundation.

import { CheerioCrawler, Dataset } from 'crawlee';

const crawler = new CheerioCrawler({
  maxRequestsPerCrawl: 1000,
  requestHandler: async ({ $, request, enqueueLinks }) => {
    if (request.label === 'CATEGORY') {
      // Extract product links from category pages
      await enqueueLinks({
        selector: '.product-link',
        label: 'PRODUCT'
      });
    } else if (request.label === 'PRODUCT') {
      // Extract product details
      const product = {
        title: $('.product-title').text(),
        price: $('.product-price').text(),
        description: $('.product-description').text(),
        images: $('.product-image').map((i, el) => $(el).attr('src')).get()
      };

      await Dataset.pushData(product);
    }
  }
});

await crawler.run([
  { url: 'https://example.com/category/electronics', label: 'CATEGORY' }
]);

Production-Ready Features Required

Crawlee includes enterprise-grade features essential for production scraping:

Automatic retries: Failed requests are automatically retried with exponential backoff
Request throttling: Configurable concurrency and rate limiting to avoid overwhelming servers
Session management: Automatic cookie and session handling
Proxy rotation: Built-in support for proxy pools and rotation strategies
Storage management: Persistent queues and datasets that survive crashes

import { PlaywrightCrawler, ProxyConfiguration } from 'crawlee';

const proxyConfiguration = new ProxyConfiguration({
  proxyUrls: [
    'http://proxy1.example.com:8000',
    'http://proxy2.example.com:8000'
  ]
});

const crawler = new PlaywrightCrawler({
  proxyConfiguration,
  maxRequestRetries: 5,
  maxConcurrency: 10,
  requestHandlerTimeoutSecs: 60,

  requestHandler: async ({ page, request }) => {
    // Your scraping logic here
  },

  failedRequestHandler: async ({ request }) => {
    console.log(`Request ${request.url} failed ${request.retryCount} times`);
  }
});

User Interactions Required

When you need to handle authentication, fill forms, click buttons, or simulate user behavior, Crawlee's browser automation capabilities are essential.

import { PlaywrightCrawler } from 'crawlee';

const crawler = new PlaywrightCrawler({
  requestHandler: async ({ page, request }) => {
    // Handle login
    if (request.label === 'LOGIN') {
      await page.fill('#username', 'your-username');
      await page.fill('#password', 'your-password');
      await page.click('button[type="submit"]');
      await page.waitForNavigation();
    }

    // Handle infinite scroll
    if (request.label === 'FEED') {
      for (let i = 0; i < 5; i++) {
        await page.evaluate(() => window.scrollTo(0, document.body.scrollHeight));
        await page.waitForTimeout(2000);
      }

      const posts = await page.$$eval('.post', items => {
        return items.map(item => ({
          content: item.textContent,
          timestamp: item.querySelector('.timestamp')?.textContent
        }));
      });
    }
  }
});

Dealing with Anti-Bot Measures

Websites with bot detection, CAPTCHAs, or fingerprinting require browser-based scraping with realistic headers, timing, and behavior patterns. Crawlee's session management and browser fingerprint handling help bypass these measures.

Large-Scale Data Extraction

When building a production scraper that needs to handle failures gracefully, resume interrupted jobs, and scale across multiple machines, Crawlee's architecture provides the necessary reliability.

Hybrid Approach: Using Both

In many cases, the optimal solution combines both tools. Use Crawlee for navigation and initial page loading, then switch to Cheerio for fast HTML parsing.

import { PlaywrightCrawler } from 'crawlee';
import cheerio from 'cheerio';

const crawler = new PlaywrightCrawler({
  requestHandler: async ({ page, request }) => {
    // Use Playwright for navigation and JavaScript rendering
    await page.waitForSelector('.product-list');

    // Get the rendered HTML
    const html = await page.content();

    // Switch to Cheerio for fast parsing
    const $ = cheerio.load(html);

    const products = [];
    $('.product-item').each((i, element) => {
      products.push({
        title: $(element).find('.product-title').text().trim(),
        price: parseFloat($(element).find('.product-price').text().replace(/[^0-9.]/g, '')),
        rating: $(element).find('.rating').attr('data-rating')
      });
    });

    console.log(`Extracted ${products.length} products`);
  }
});

Decision Matrix

| Requirement | Cheerio | Crawlee | |------------|---------|---------| | Static HTML parsing | ✅ Excellent | ✅ Good (via CheerioCrawler) | | JavaScript-rendered content | ❌ No | ✅ Yes | | Speed for simple pages | ✅ Very Fast | ⚠️ Slower (browser overhead) | | Memory efficiency | ✅ Minimal | ⚠️ High (browser instances) | | Link discovery & crawling | ⚠️ Manual | ✅ Automatic | | Request queuing | ❌ Manual | ✅ Built-in | | Proxy rotation | ❌ Manual | ✅ Built-in | | Session management | ❌ Manual | ✅ Built-in | | Auto-retry logic | ❌ Manual | ✅ Built-in | | User interactions | ❌ No | ✅ Yes | | Production features | ❌ Build yourself | ✅ Included | | Learning curve | ✅ Simple | ⚠️ Moderate |

Code Comparison

Simple Product Scraping with Cheerio

const cheerio = require('cheerio');
const axios = require('axios');

async function scrapeProducts(url) {
  try {
    const { data } = await axios.get(url);
    const $ = cheerio.load(data);

    const products = $('.product').map((i, el) => ({
      name: $(el).find('h2').text(),
      price: $(el).find('.price').text()
    })).get();

    return products;
  } catch (error) {
    console.error('Scraping failed:', error);
    return [];
  }
}

Same Task with Crawlee

import { CheerioCrawler, Dataset } from 'crawlee';

const crawler = new CheerioCrawler({
  maxConcurrency: 5,
  requestHandler: async ({ $, request }) => {
    const products = $('.product').map((i, el) => ({
      name: $(el).find('h2').text(),
      price: $(el).find('.price').text(),
      url: request.url
    })).get();

    await Dataset.pushData(products);
  }
});

await crawler.run(['https://example.com/products']);
const results = await Dataset.getData();

Performance Considerations

For a typical scraping job of 10,000 simple product pages:

Cheerio approach: - Memory: ~50-100 MB - Time: 5-10 minutes (with proper rate limiting) - CPU: Low

Crawlee with CheerioCrawler: - Memory: ~100-200 MB - Time: 6-12 minutes (includes queue management overhead) - CPU: Low-Medium

Crawlee with PlaywrightCrawler: - Memory: ~2-4 GB - Time: 30-60 minutes (browser rendering overhead) - CPU: High

Conclusion

Choose Cheerio when you're working with static HTML, need maximum performance, and can implement crawling logic yourself. It's perfect for simple scraping tasks and situations where you're in full control of the workflow.

Choose Crawlee when you need JavaScript rendering, automatic link discovery, built-in reliability features, or are building production-grade scrapers. The framework's overhead is justified by the robustness and maintainability it provides.

For many projects, starting with Cheerio makes sense for prototyping and validating your approach. As complexity grows, migrating to Crawlee's CheerioCrawler provides production features while maintaining similar parsing logic. When JavaScript rendering becomes necessary, switching to PlaywrightCrawler or PuppeteerCrawler is a natural progression within the same framework.

Remember that web scraping should always respect websites' terms of service and robots.txt files. Consider using professional web scraping APIs that handle infrastructure, proxy management, and anti-bot measures for you when building production applications.

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