Github Awesome List Scraper

What Does GitHub Awesome List Scraper Do?

GitHub Awesome List Scraper is an Apify actor that extracts curated resources, tools, and libraries from GitHub's popular "awesome" lists. These community-maintained lists are treasure troves of high-quality software, frameworks, and learning resources organized by category. This actor parses the README content and returns structured data with names, descriptions, URLs, and categories.

Why Scrape GitHub Awesome Lists?

Awesome lists on GitHub are among the best curated collections of developer resources, but manually browsing and copying data from these long pages is tedious. This scraper automates the extraction, giving you a clean dataset of all resources with their categories and descriptions. Use it for competitive analysis, technology landscape mapping, resource aggregation, or building recommendation systems.

How to Use This GitHub Awesome List Scraper

1. Provide one or more GitHub awesome list repository URLs.
2. Set the maximum number of items to extract per list.
3. Run the actor and retrieve your structured dataset.

The scraper parses the markdown README of each repository, identifying section headings as categories and list items with links as individual resources.

Input Parameters

Parameter	Type	Description	Default
listUrls	array	GitHub awesome list repository URLs	["https://github.com/sindresorhus/awesome"]
maxResults	integer	Maximum items to extract per list	100

Output Data

Each extracted item includes:

• name - Resource or tool name
• description - Brief description text
• url - Link to the resource
• category - Section heading the item belongs to
• sourceList - The awesome list URL it was scraped from

Cost of Usage

This actor runs efficiently on the Apify platform:

• Per result: $0.01
• Per 1,000 results: $10
• Actor start cost: $0.005

Most awesome lists contain 100-500 items and can be scraped in under a minute using minimal resources.

Tips and Best Practices

• Use full GitHub URLs like https://github.com/sindresorhus/awesome.
• You can scrape multiple awesome lists in a single run by providing multiple URLs.
• Some awesome lists link to sub-lists. Provide those sub-list URLs directly for focused extraction.
• Results are categorized based on the heading structure of the list.

Also check out these related scrapers:

• Wikipedia Article Extractor - Extract structured content from Wikipedia
• Lobsters Tech News Scraper - Curated tech news and articles
• NPR Article Scraper - News articles from NPR