grab vs requests-html

Python web scraping libraries compared

grab and requests-html both combine HTTP access with HTML extraction for Python scraping. grab adds a task-based crawler framework and queue options, while requests-html offers a compact Requests-style interface with optional Chromium rendering for JavaScript-generated content.

grabrequests-html
LanguagePythonPython
LicenseMITMIT
Stars2.5k13.8k
Forks273996
Last analyzedOct 3, 2026Oct 3, 2026

Key differences

  • grab provides Spider for organizing scraping tasks, parallel requests, retries, and task queues; requests-html focuses on fetching and parsing pages through a compact library interface.
  • grab supports XPath-based DOM queries and helpers for forms and uploads; requests-html supports both CSS and XPath selection, along with link extraction and text searches.
  • grab offers task queue backends including in-memory storage, Redis, and MongoDB; requests-html can parse an HTML string directly without making a request.
  • requests-html can render JavaScript-generated content using Chromium via pyppeteer; grab's listed features focus on HTTP requests and HTML extraction.
  • grab's update targets Python 2.7 through 3.13 and changes exception imports from older weblib exceptions; requests-html's README states support for Python 3.6 and above.
  • Both projects use the MIT license and are not marked archived in the supplied data; requests-html has more listed stars and forks.

Choose grab if you…

  • need a task-based crawler with parallel requests, retry handling, or persistent queues.
  • want HTTP handling, XPath extraction, and Spider workflows in one library.
  • need session cookies, form submissions, or HTTP and SOCKS proxy support.
Read the grab analysis →

Choose requests-html if you…

  • want a compact Requests-style API for lightweight scraping scripts.
  • need CSS selection, link extraction, or direct parsing of an HTML string.
  • need optional Chromium rendering to inspect JavaScript-generated page content.
Read the requests-html analysis →

Compare the numbers side by side, or add more projects

This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.