omkarcloud/botasaurus

The All in One Framework to Build Undefeatable Scrapers

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Summary Information

Updated 39 minutes ago
Added to GitGenius on September 11th, 2026
Created on May 9th, 2023
Open Issues & Pull Requests: 57 (+0)
GitHub issues: Enabled
Number of forks: 496
Total Stargazers: 5,708 (+0)
Total Subscribers: 39 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 10.0 days
Mean response time: 70.7 days
90th percentile: 243.8 days
Tracked items: 102

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Only 3% of issues opened in the past year have been closed. Three people close 87% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 48
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 443 days
Stale 30+ days: 47
Stale 90+ days: 44

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • enhancement (2)
  • good first issue (2)
  • help wanted (2)

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

Botasaurus is a web scraping framework that helps developers build scrapers resistant to anti-bot detection systems.

The framework addresses the challenge of scraping websites protected by anti-bot measures like Cloudflare. It provides integrated tools for handling detection evasion, including support for undetectable browser automation and anti-detection techniques. The approach combines browser automation with anti-detection capabilities to allow scrapers to access protected content while avoiding blocks and captchas.

Developers should choose Botasaurus when building scrapers that need to bypass anti-bot systems on protected websites. It suits projects requiring reliable scraping of Cloudflare-protected sites or other anti-detection scenarios. The framework positions itself as an all-in-one solution, meaning it bundles scraping, browser automation, and anti-detection features together rather than requiring separate tool integration.

The project shows consistent development activity with regular updates and maintenance. The codebase demonstrates active problem-solving around anti-detection challenges. Documentation and examples are maintained to support users implementing the framework in their scraping projects.