Analysis updated 2026-05-18
Visualize how many nixpkgs packages exist under each two-letter name prefix.
Compare package counts across different nixpkgs forks, tags, or commits.
See how excluding lib-prefixed packages changes the package distribution.
Explore package density with an interactive, zoomable heatmap in the browser.
| arunoruto/nixpkgs-stats | 0xallam/my-recipe | 0xhassaan/nn-from-scratch | |
|---|---|---|---|
| Stars | 0 | — | 0 |
| Language | Python | Python | Python |
| Last pushed | — | 2022-11-22 | — |
| Maintenance | — | Dormant | — |
| Setup difficulty | easy | moderate | moderate |
| Complexity | 2/5 | 2/5 | 4/5 |
| Audience | developer | general | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires a local nixpkgs checkout on disk and the uv Python tool to run the Streamlit app.
nixpkgs-stats is a small tool for visualizing how packages are organized inside nixpkgs, the large collection of software packages used by the Nix package manager. Rather than reading through the raw file structure yourself, this tool scans the pkgs/by-name folder of a nixpkgs checkout and turns it into a heatmap, a grid style chart where color shows how many packages fall under each two letter prefix. The first letter of the prefix runs along one axis and the second letter runs along the other, so you can see at a glance which letter combinations have the most packages. You point the tool at any nixpkgs folder you already have on your computer, whether that is a fork, a specific tag, or a particular commit. It shows you the latest commit hash and date of that checkout so you know exactly what version you are looking at. You can choose whether to count each package directory once or to count every individual .nix file instead, and you can switch to a logarithmic color scale, which helps when one prefix has far more packages than the rest and would otherwise wash out the chart. There is also an option to exclude packages that start with lib, since the README notes that filtering these out can significantly change the numbers in that particular prefix. The chart itself is built with Plotly, so it is interactive: you can hover over any cell to see its exact count and zoom in on areas you want to look at more closely. To run it, you use a command that starts a Streamlit web app in your browser. From there you type in the path to your nixpkgs folder, adjust the counting options in the sidebar, and click Scan to generate the heatmap. The tool depends on Streamlit for the interface, Plotly for the chart, pandas and numpy for handling the data, GitPython for reading repository metadata, and Kaleido for exporting static images.
A tool that scans a local nixpkgs checkout and draws an interactive heatmap showing how packages are distributed across two-letter name prefixes.
Mainly Python. The stack also includes Python, Streamlit, Plotly.
No license information is stated in the README.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.