GitHub Trending Scraper

Scrape GitHub's Trending page to discover the fastest-growing repositories and developers. Filter by programming language, time range, and spoken language, then export structured data with stars, forks, descriptions, contributor avatars, and topic tags. No API key or authentication required.

This actor parses the GitHub Trending HTML directly, extracts rich metadata for each item, and applies optional post-scrape sorting so you can rank results by total stars or stars gained in the period. Export results to JSON, CSV, or via API.

Features

• Two modes: repositories and developers
• Filter by programming language (e.g. python, rust, go)
• Time range support: daily, weekly, or monthly trending
• Spoken language code filter for localized trending
• Repository data: author, name, description, language, stars, forks, stars gained in period, top contributors, and topic tags
• Developer data: username, full name, profile URL, avatar, company ("Works for"), and their popular repo
• Post-scrape sorting by total stars or stars gained in the selected period
• Automatic rank assignment after sorting

Input

Field	Type	Default	Description
mode	String	repositories	Scrape type: repositories or developers
language	String	""	Programming language filter (e.g. python)
since	String	daily	Time range: daily, weekly, or monthly
spokenLanguageCode	String	""	Spoken language code (e.g. en) for localized trending
sortBy	String	""	Post-scrape sort: stars (total stars) or stars-today (gained in period). Leave empty for default GitHub order
maxItems	Integer	100	Maximum number of items to return

Example input

{
    "mode": "repositories",
    "language": "python",
    "since": "weekly",
    "sortBy": "stars-today",
    "maxItems": 50
}

Output

Repository output

{
    "rank": 1,
    "author": "openai",
    "name": "tiktoken",
    "fullName": "openai/tiktoken",
    "url": "https://github.com/openai/tiktoken",
    "description": "Fast BPE tokeniser for use with OpenAI's models",
    "language": "Python",
    "stars": 12000,
    "forks": 800,
    "starsGained": 450,
    "builtBy": [
        { "username": "user1", "avatarUrl": "https://avatars..." }
    ],
    "topics": ["tokenization", "openai", "gpt"]
}

Developer output

{
    "rank": 1,
    "username": "torvalds",
    "fullName": "Linus Torvalds",
    "profileUrl": "https://github.com/torvalds",
    "avatarUrl": "https://avatars...",
    "worksFor": "",
    "popularRepo": {
        "name": "linux",
        "url": "https://github.com/torvalds/linux",
        "description": "Linux kernel source tree"
    }
}

Use cases

• Technology scouting — discover rising frameworks, libraries, and tools before they go mainstream
• Market research — identify trending languages and developer ecosystem shifts
• Recruiting — find active top developers by language and region
• Content creation — power newsletters, blog posts, and dashboards about trending open source
• Investment intelligence — track momentum in specific technology categories
• Competitive analysis — monitor repos gaining traction in your domain

How to use

1. Open the actor on the Apify Store.
2. Select mode (repositories or developers).
3. Optionally set a language, since time range, and sortBy.
4. Click Start and wait for the run to complete.
5. Export results to JSON, CSV, Excel, or connect via the Apify API.

Schedule recurring runs to track trending repos over time and build a historical dataset of GitHub momentum.