Async-First Scraping at Scale

What We Do With Node.js Web Scraping

• Non-blocking event loop handles thousands of concurrent requests
• Puppeteer built by Google engineers for Chrome automation
• Cheerio delivers jQuery-style parsing at native speed
• Streams API for memory-efficient processing of huge datasets
• npm ecosystem with 1M+ packages for any scraping need
• TypeScript support for maintainable, enterprise-grade scrapers

Node.js Web Scraping Tech Stack

const puppeteer = require('puppeteer');
const pLimit = require('p-limit');

const limit = pLimit(10); // 10 concurrent browsers

async function scrapePage(url) {
  const browser = await puppeteer.launch({ headless: 'new' });
  const page = await browser.newPage();
  
  await page.setUserAgent('Mozilla/5.0 ...');
  await page.goto(url, { waitUntil: 'networkidle2' });
  
  const data = await page.evaluate(() => {
    return Array.from(document.querySelectorAll('.product')).map(el => ({
      title: el.querySelector('h2')?.textContent,
      price: el.querySelector('.price')?.textContent,
    }));
  });
  
  await browser.close();
  return data;
}

const urls = ['https://example.com/page/1', '...'];
const results = await Promise.all(urls.map(url => limit(() => scrapePage(url))));

* This is a simplified example. Production scrapers include error handling, proxies, and rate limiting.

Common Use Cases

• 1
  High-volume URL processing (100k+ pages per day)
• 2
  Real-time scraping APIs with Express.js webhooks
• 3
  TypeScript scraping microservices with NestJS
• 4
  Distributed scraping workers using Bull + Redis queues
• 5
  Chrome extension backends that extract page data
• 6
  Serverless scraping functions on AWS Lambda / Vercel