Bus factor = 1: hugely popular projects, single point of failure
A repo's bus factor is the smallest number of top contributors who together hold ≥50% of all contributions. A bus factor of 1 means: one person is the project. If they stop, momentum stalls.
Out of 200 popular Python projects, 41 have bus factor = 1. The most exposed:
| Project | Stars | Maintainer holding 50%+ |
|---|---|---|
| EbookFoundation/free-programming-books | 388,403 | @vhf |
| donnemartin/system-design-primer | 348,823 | @donnemartin |
| vinta/awesome-python | 297,915 | @vinta |
| AUTOMATIC1111/stable-diffusion-webui | 163,078 | @AUTOMATIC1111 |
| 521xueweihan/HelloGitHub | 157,120 | @521xueweihan |
| open-webui/open-webui | 137,303 | @tjbck |
| Comfy-Org/ComfyUI | 113,135 | @comfyanonymous |
| Shubhamsaboo/awesome-llm-apps | 110,589 | @Shubhamsaboo |
| openai/whisper | 99,579 | @jongwook |
| fastapi/fastapi | 98,245 | @tiangolo |
Awesome-lists owning their bus factor is fine. But FastAPI, ComfyUI, Whisper, open-webui are critical infrastructure for a lot of people. Worth keeping in mind when you ship them in production.
"Active-looking" but actually dormant
These are not archived, they look maintained on the surface, yet nobody pushed a commit in the last 4 weeks:
- donnemartin/system-design-primer — 348k stars, last push 57d ago
- TheAlgorithms/Python — 221k stars, no commits in 4w
- AUTOMATIC1111/stable-diffusion-webui — 163k stars, last push 75d ago
- ytdl-org/youtube-dl — 140k stars, last push 85d ago
- openai/whisper — 99k stars, last push 30d ago
- 3b1b/manim — 86k stars, last push 27d ago
Some are by design (curated lists, finished tools). Others are slowly going stale.
Release cadence extremes
Shipping fastest among popular projects:
| Project | Avg gap between releases | Stars |
|---|---|---|
| FoundationAgents/OpenManus | 0 days | 56,279 |
| PostHog/posthog | 0.2 days | 34,515 |
| gradio-app/gradio | 0.3 days | 42,600 |
| langchain-ai/langchain | 0.4 days | 136,866 |
| langchain-ai/langgraph | 0.4 days | 32,160 |
Slowest cadence at 5k+ stars:
| Project | Avg gap | Stars |
|---|---|---|
| trailofbits/algo | 815 days | 30,229 |
| satwikkansal/wtfpython | 698 days | 36,933 |
| deepfakes/faceswap | 623 days | 55,237 |
| swisskyrepo/PayloadsAllTheThings | 552 days | 77,735 |
| sherlock-project/sherlock | 434 days | 83,392 |
A long gap is not automatically bad — finished tools, security playbooks, and content collections do not need weekly releases.
What 5000+ star Python projects are about
Top topics across the 200 repos:
python 92
ai 36
llm 34
deep-learning 21
machine-learning 20
pytorch 18
hacktoberfest 17
openai 17
chatgpt 17
rag 15
agents 14
ai-agents 13
cli 11
data-science 11
gpt 10
The Python OSS leaderboard in 2026 is overwhelmingly an AI agents / RAG / LLM-app leaderboard.
Aggregates
- Total stars across the 200 repos: 12,498,901
- Total forks: 1,981,076
- Median Health Score: 91 / 100
- With explicit OSS license: 188 / 200 (12 repos still have no license — risky to depend on those)
How to reproduce / explore your own list
I packaged the analysis as a one-shot Apify Actor — you give it a search query (or a list of owner/repo) and a free GitHub token, you get one row per repo with all the metrics above plus a transparent breakdown of how the Health Score is computed.
GitHub Repository Insights on Apify Store
Free trial, then $0.005 per analyzed repo. You can also clone the input from this post (language: Python, minStars: 5000, pushedSince: 2025-12-01, maxResults: 200) and re-run it against any other language or topic.
If you find more interesting patterns, drop them in the comments — I am curious what your stack looks like.