How yuxiaopeng/github-ranking-ai works
This repository generates category-based GitHub repository rankings: it queries GitHub’s GraphQL API for star-sorted repositories, normalizes the results, then publishes top-10 tables and top-100 pages and archives the collected data as a dated CSV. The main entry point coordinates retrieval and these output stages. The graph follows the sampled Python code and README; the scheduled-update workflow is not included because its implementation was not sampled.
Main entry points: process.py Output builder · common.py GitHub API helpers · README.md Ranking README · Top100 Category rankings
Components 9
Collection
- Ranking runner
source/process.py - Category queries
source/process.py - GitHub API helpers
source/common.py
Publishing
- Output builder
source/process.py - Ranking README
README.md - Category rankings
Top100
Data archive
- Dated ranking CSV
Data
Other components
- Update runner
- GitHub GraphQL
Connections 8
- Update runner → Ranking runner: runs
- Ranking runner → Category queries: loads categories
source/process.py - Category queries → GitHub API helpers: requests data
source/process.py - GitHub API helpers → GitHub GraphQL: posts query
source/common.py - Ranking runner → Output builder: builds outputs
source/process.py - Output builder → Ranking README: writes top ten
source/process.py - Output builder → Category rankings: writes top hundred
source/process.py - Output builder → Dated ranking CSV: saves rankings
source/process.py