Analysis updated 2026-06-20
Scrape product prices, headlines, or table rows from a website by selecting HTML elements with CSS selectors.
Parse structured data out of HTML emails to extract order details or notification content.
Transform or clean up HTML markup in a build pipeline before publishing content.
Build a data extraction tool that turns any web page into structured JSON.
| cheeriojs/cheerio | honojs/hono | sequelize/sequelize | |
|---|---|---|---|
| Stars | 30,302 | 30,313 | 30,347 |
| Language | TypeScript | TypeScript | TypeScript |
| Setup difficulty | easy | easy | moderate |
| Complexity | 2/5 | 2/5 | 3/5 |
| Audience | developer | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Cheerio is a TypeScript library that lets you read and modify HTML or XML documents using a style that will feel familiar to anyone who has worked with jQuery, a once-ubiquitous JavaScript tool for selecting and changing elements on web pages. The key difference is that Cheerio runs on a server, not inside a browser, so it works with raw HTML strings rather than a live browser page. The practical use case is web scraping: you fetch the raw HTML of a web page, hand it to Cheerio, and then use CSS-style selectors to pinpoint the data you care about, a product price, a headline, a table row, and extract or modify it. You load the HTML, write something like "$('h2.title').text()" to find all h2 elements with a certain class and read their text, and get your result back instantly. Cheerio is built for speed and simplicity. It parses HTML using proven parsers (parse5 or htmlparser2), strips out the complex browser machinery that jQuery normally relies on, and gives you just the selection and manipulation API. It works in both server and browser environments. Developers reach for it when they need to process HTML programmatically, whether scraping a site, transforming markup in a build pipeline, or parsing structured data out of an HTML email.
A fast server-side library for reading and extracting data from HTML pages using familiar CSS-style selectors, without needing a full browser, the go-to tool for web scraping in Node.js.
Mainly TypeScript. The stack also includes TypeScript, JavaScript, Node.js.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.