Scrapling vs crawl4ai

Crawler rivals. Both tagged crawler, data-extraction. Six rounds of real GitHub data, an AI referee, and the crowd picks a side.

Red corner

Blue corner

D4Vinci/Scrapling: 101,442 stars, Python. 🕷️ The BEST Web Scraping framework that handles everything from a single request to a full-scale crawl! Don't be shy, join here: https://d…
unclecode/crawl4ai: 87,213 stars, Python. Official Crawl4AI Cloud: a hosted web scraping, extraction, and search API for AI agents. Free API key, 1,000 credits a month, no card. Ful…

Scrapling vs crawl4ai: tale of the tape

GitHub data as of November 11, 2026

Scrapling has 1.2 times as many GitHub stars as crawl4ai (101,442 vs 87,213). In the last 6 days, Scrapling gained more stars: +4,027 (+4.1%) against +272 (+0.3%) for crawl4ai. Scrapling saw more development in the last 52 weeks with 785 commits, against 418 for crawl4ai. crawl4ai is the older project (created May 2024), Scrapling started in October 2024. Both are written mainly in Python.

	D4Vinci/Scrapling	unclecode/crawl4ai
Stars	101,442	87,213
Stars gained, last 6 days	+4,027	+272
Growth, last 6 days	+4.1%	+0.3%
Avg. stars per day since creation	134	95
Forks	10,576	9,088
Commits, last 52 weeks	785	418
Open issues	22	331
Best Repocharts rank today	#26 in AI	#31 in AI
Language	Python	Python
License	BSD-3-Clause	Apache-2.0
Created	Oct 13, 2024	May 9, 2024
Last push	Nov 9, 2026	Nov 10, 2026

Quick answers

Which is more popular, Scrapling or crawl4ai?

Scrapling has 1.2 times as many GitHub stars as crawl4ai (101,442 vs 87,213) (Repocharts data as of November 11, 2026).

Which is growing faster, Scrapling or crawl4ai?

In the last 6 days, Scrapling gained more stars: +4,027 (+4.1%) against +272 (+0.3%) for crawl4ai.

Which is more actively developed?

Scrapling saw more development in the last 52 weeks with 785 commits, against 418 for crawl4ai.

What languages are Scrapling and crawl4ai written in?

Both are written mainly in Python.

How does RepoClash compare Scrapling and crawl4ai?

RepoClash scores both repositories in six rounds (popularity, momentum, activity, community, maintenance and freshness) from public GitHub data, adds an AI referee's verdict and lets developers vote for their favorite. Star counts are updated daily.