evanli/github-ranking

★ 11,123PythonAudience · developerComplexity · 1/5Setup · easy

Mindmap

mindmap
  root((github-ranking))
    What it does
      Daily star counts
      Fork counts
      Per-language top 100
    Data shown
      Project name
      Stars and forks
      Language and description
    How it works
      Python fetch script
      Daily scheduled update
      Git commit history
    Audience
      Developers
      Tech researchers
      Open-source explorers

mindmap root((github-ranking)) What it does Daily star counts Fork counts Per-language top 100 Data shown Project name Stars and forks Language and description How it works Python fetch script Daily scheduled update Git commit history Audience Developers Tech researchers Open-source explorers

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Things people build with this

USE CASE 1

Discover the most popular open-source libraries in a specific programming language

USE CASE 2

Research which projects are trending on GitHub to inform technology choices

USE CASE 3

Browse the top 100 repositories per language to find widely-used tools and frameworks

Tech stack

Python

Getting it running

Difficulty · easy Time to first run · 5min

In plain English

Github-Ranking is a reference project that tracks and publishes the most-starred and most-forked repositories on GitHub. It updates automatically every day, so the numbers stay current rather than becoming stale snapshots. The main README itself is a large data document. It lists the top repositories overall by stars and by forks, then breaks down the top 100 repositories for each programming language individually: Python, JavaScript, Java, Go, Rust, TypeScript, and many others including smaller languages like Haskell, Elixir, and Lua. Each entry shows the project name, its star and fork counts, the primary language, open issue count, a short description, and the date of the last commit. The Python code in the repository handles the data collection and automatic updates. A scheduled process fetches fresh data from GitHub and regenerates the ranking tables on a daily basis. The results are committed directly to the repository, so anyone can browse historical snapshots through the commit history. This is primarily a reference resource rather than a tool you install or run yourself. Its main audience is developers who want a quick overview of which projects are most popular on GitHub, whether for discovering widely-used libraries, understanding what languages are trending, or simply satisfying curiosity about the overall shape of open-source activity. The data is organized so you can jump directly to a specific language's top 100 list without wading through everything else. The full README is longer than what was shown.

Copy-paste prompts

Prompt 1

Using github-ranking, show me the top 10 most-starred Python repositories and a one-line description of each

Prompt 2

How does the github-ranking Python script fetch data from GitHub and commit updated rankings automatically?

Prompt 3

How can I fork github-ranking and modify the Python script to track repositories by topic rather than by language?

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