Overview

Cheerio is a fast, lightweight HTML/XML parser for Node.js that implements a jQuery-like API. Unlike Puppeteer, it does not run a browser — it parses raw HTML strings, making it 100x faster and ideal for scraping server-rendered pages, parsing HTML files, and transforming HTML content. Pair it with fetch or axios for web scraping, or use it standalone for HTML processing.

Instructions

Step 1: Installation

bash

npm install cheerio

Step 2: Parse HTML and Extract Data

javascript

// parse_html.js — Load HTML and extract structured data with CSS selectors
import * as cheerio from 'cheerio'

const html = `
<html>
  <body>
    <h1>Products</h1>
    <div class="product" data-id="1">
      <h2>Widget Pro</h2>
      <span class="price">$29.99</span>
      <a href="/products/widget-pro">Details</a>
    </div>
    <div class="product" data-id="2">
      <h2>Gadget Max</h2>
      <span class="price">$49.99</span>
      <a href="/products/gadget-max">Details</a>
    </div>
  </body>
</html>`

const $ = cheerio.load(html)

// Extract all products
const products = []
$('.product').each((i, el) => {
  products.push({
    id: $(el).attr('data-id'),
    title: $(el).find('h2').text().trim(),
    price: $(el).find('.price').text().trim(),
    link: $(el).find('a').attr('href'),
  })
})

console.log(products)
// [{ id: '1', title: 'Widget Pro', price: '$29.99', link: '/products/widget-pro' }, ...]

Step 3: Web Scraping with Fetch

javascript

// scrape_site.js — Fetch a page and extract data
import * as cheerio from 'cheerio'

async function scrape(url) {
  const response = await fetch(url)
  const html = await response.text()
  const $ = cheerio.load(html)

  // Extract all links
  const links = []
  $('a[href]').each((i, el) => {
    links.push({
      text: $(el).text().trim(),
      href: $(el).attr('href'),
    })
  })

  // Extract meta tags
  const meta = {
    title: $('title').text(),
    description: $('meta[name="description"]').attr('content'),
    ogImage: $('meta[property="og:image"]').attr('content'),
  }

  return { links, meta }
}

Step 4: Advanced Selectors and Traversal

javascript

// selectors.js — Complex CSS selectors and DOM traversal
const $ = cheerio.load(html)

// Attribute selectors
$('a[href^="https"]')           // links starting with https
$('img[src$=".png"]')           // PNG images
$('div[class*="product"]')      // divs with "product" in class

// Traversal
$('.product').first()            // first product
$('.product').last()             // last product
$('.product').eq(2)              // third product (0-indexed)
$('.price').parent()             // parent of each .price element
$('.product').children('h2')     // direct h2 children
$('.product').find('.price')     // descendants matching .price
$('.product').next()             // next sibling
$('.product').prev()             // previous sibling

// Filtering
$('.product').filter((i, el) => {
  const price = parseFloat($(el).find('.price').text().replace('$', ''))
  return price < 50
})

// Text and HTML
$('.product').first().text()     // all text content, flattened
$('.product').first().html()     // inner HTML

Step 5: Table Extraction

javascript

// extract_table.js — Parse HTML tables into structured data
function extractTable($, tableSelector) {
  /**
   * Convert an HTML table to an array of objects using headers as keys.
   * Args:
   *   $: Cheerio instance
   *   tableSelector: CSS selector for the table element
   */
  const headers = []
  $(`${tableSelector} thead th`).each((i, el) => {
    headers.push($(el).text().trim())
  })

  const rows = []
  $(`${tableSelector} tbody tr`).each((i, tr) => {
    const row = {}
    $(tr).find('td').each((j, td) => {
      row[headers[j]] = $(td).text().trim()
    })
    rows.push(row)
  })
  return rows
}

// Usage
const tableData = extractTable($, '#pricing-table')
// [{ Plan: 'Free', Price: '$0', Users: '1' }, { Plan: 'Pro', Price: '$29', Users: '10' }]

Step 6: HTML Transformation

javascript

// transform.js — Modify HTML content
const $ = cheerio.load(html)

// Add class
$('.product').addClass('featured')

// Remove elements
$('.ad-banner').remove()

// Replace content
$('h1').text('Updated Title')

// Wrap elements
$('.product').wrap('<section class="product-section"></section>')

// Add attributes
$('a').attr('target', '_blank')
$('img').attr('loading', 'lazy')

// Get modified HTML
const modifiedHtml = $.html()

Examples

Example 1: Build a price monitoring scraper

User prompt: "Scrape product prices from 5 competitor websites daily and save to a CSV. The sites are server-rendered (no JavaScript needed)."

The agent will:

Use fetch + cheerio for each site (no browser overhead).
Write site-specific selectors for product name, price, and availability.
Parse prices into numbers, normalize currency.
Append results to a CSV with timestamps.
Set up as a cron job for daily execution.

Example 2: Extract and clean article content from HTML

User prompt: "I have 1,000 saved HTML pages from a blog. Extract just the article title, author, date, and body text from each, ignoring navigation, ads, and footers."

The agent will:

Read each HTML file, load with cheerio.
Extract content using article-specific selectors (article, .post-content, etc.).
Strip HTML tags from body, normalize whitespace.
Output structured JSON with title, author, date, and clean text.

Guidelines

Use cheerio for server-rendered pages (where the HTML contains the data you need). For SPAs or JavaScript-rendered content, use Puppeteer instead.
Cheerio does not execute JavaScript, fetch external resources, or render CSS — it only parses the HTML string you give it.
Always call .trim() on extracted text — HTML often contains whitespace, newlines, and indentation that clutters results.
Use .attr('href') and .attr('src') to get link/image URLs. Remember these may be relative — resolve them against the base URL.
For large-scale scraping, cheerio is 100x faster than Puppeteer and uses negligible memory. It can process thousands of pages per second.
Combine cheerio with fetch or axios for scraping, and add delays between requests to avoid overwhelming target servers.

cheerio

Usage

Getting Started

Example Prompts

Documentation

Overview

Instructions

Step 1: Installation

Step 2: Parse HTML and Extract Data

Step 3: Web Scraping with Fetch

Step 4: Advanced Selectors and Traversal

Step 5: Table Extraction

Step 6: HTML Transformation

Examples

Example 1: Build a price monitoring scraper

Example 2: Extract and clean article content from HTML

Guidelines

Information

Use Cases