Portfolio concentration
62%
Top three share
Shows whether the organization is driven by one breakout repo or several visible projects.
Breadth
30 repos
Visible snapshot
0 repositories updated in the last 90 days.
Leading language
JavaScript
Portfolio mix
JavaScript (22), Processing (3), Java (2)
Average size
28
Stars per repository
Useful for distinguishing one flagship-heavy publisher from a repeatable portfolio.
62%
of the visible star count comes from this organization's top three repositories.
28
stars per repository in this same snapshot.
JavaScript
is the most common language here, with 0 repositories updated in the last 90 days.
Why this rank
This organization stands out because its public portfolio is relatively balanced across 30 repositories.
Organization pages work best when you separate portfolio breadth from flagship concentration. In Coding Train's case, the visible top three repositories account for about 62% of total stars in this snapshot, which helps explain whether the organization is known for one breakout project or for a broader repeatable portfolio.
The dominant language mix here is JavaScript (22), Processing (3), Java (2). That makes this page useful not just for popularity checks, but also for seeing what technical shape an organization's public ecosystem actually has.
| # | Repository | Language | Stars |
|---|---|---|---|
| 1 | codingtrain/Wave-Function-Collapse | JavaScript | 216 |
| 2 | codingtrain/Coding-Challenges Let's put any example code that is not p5 web editor in this repo to link from new website. | JavaScript | 189 |
| 3 | codingtrain/Creative-Coding-Processing-Full-Course Full Course: Creative Coding with Processing 4! | Processing | 113 |
| 4 | codingtrain/Nebula-AppleSoft-Basic AppleSoft Basic source code for Nebula class "What is Code?" | BASIC | 51 |
| 5 | codingtrain/Directional-Boring Horizontal Directional Drilling Simulation | JavaScript | 47 |
| 6 | codingtrain/Oregon-Trail A p5.js version of the Apple ][ Oregon Trail Game | JavaScript | 34 |
| 7 | codingtrain/Genuary-2023 All code from Genuary 2023 Speed Run | Processing | 22 |
| 8 | codingtrain/Robot-Controllers | JavaScript | 20 |
| 9 | codingtrain/Pi-in-the-Sky | JavaScript | 18 |
| 10 | codingtrain/Monty-Hall Monty Hall Problem Demonstration! | JavaScript | 14 |
| 11 | codingtrain/Bizarro-Devin | JavaScript | 13 |
| 12 | codingtrain/GenuaryDay4-Fidenza-Base Base Code for Fidenza Genuary Day 4 | Java | 12 |
| 13 | codingtrain/Happy-New-Year-2022 Code from today's Live Stream | Roff | 11 |
| 14 | codingtrain/p5-gemini | JavaScript | 10 |
| 15 | codingtrain/sockets-and-p5 | JavaScript | 9 |
| 16 | codingtrain/Wordle-Simulation A Wordle Simulation to test out ideas in p5.js | JavaScript | 9 |
| 17 | codingtrain/Genuary-Day18-VHS | JavaScript | 9 |
| 18 | codingtrain/YouTube-API-Experiments Working on some experiments with YouTube API | JavaScript | 7 |
| 19 | codingtrain/Coding-in-the-Cabana Source code for Coding in the Cabana Episodes | Java | 7 |
| 20 | codingtrain/Genuary-25-Racer-1979 Genuary Day 25 Racer - (1979) - Apple II | JavaScript | 6 |
| 21 | codingtrain/genuary-2025 Speed run for Genuary 2025 | 3 | |
| 22 | codingtrain/voice-dataset-prep node.js code to prepare dataset for training voice model (piper tts) | JavaScript | 3 |
| 23 | codingtrain/fine-tuning-dataset Idea for using an LLM to generate fine-tuning dataset from transcripts | JavaScript | 2 |
| 24 | codingtrain/Semantic-Retrieval-Tests | JavaScript | 2 |
| 25 | codingtrain/Logo-Animations Speculative Animations for Coding Train Logo | JavaScript | 2 |
| 26 | codingtrain/Embeddings-Live | JavaScript | 2 |
| 27 | codingtrain/node-project-demo Demo for setting up a node.js project | JavaScript | 2 |
| 28 | codingtrain/Coding-Train-Logo | Processing | 2 |
| 29 | codingtrain/MeowMeow Meow? | JavaScript | 1 |
| 30 | codingtrain/coding-train-transcripts A project to collect transcripts from Coding Train videos | JavaScript | 1 |
Total stars are useful as a discovery signal, but they do not tell you whether a team maintains every repository equally. Pair this page with release cadence, maintainer activity, and the flagship concentration shown above before making adoption decisions.
For broader background on GitStar's ranking logic and editorial guidance, see Methodology & Editorial Standards.