drillion

Python practice drills that come back before you forget them. Graded by pytest, runs on your machine.

drillion is a local web app with 171 short Python tasks, each tagged with the concept it practises so you can go straight at what you want to get better at. Every task ships its own pytest test, and many draw fresh data each time you open them, so you cannot pass by remembering last week's answer. Pass one and it comes back in 2 days, then 4, 8, 16, and on up to 120; fail and it costs you nothing but the attempt. There is no login, no account and no server but yours: the tasks are folders of Markdown and Python on your disk, and your progress is one JSON file.

Install

Any of these serves http://127.0.0.1:8765. The first three need Python 3.13 or newer and open your browser for you; Docker needs nothing but Docker, and opens nothing.

Try it — uvx

uvx drillion

Downloads, runs, and leaves nothing installed. Your progress still persists between runs; only drillion itself is temporary.

Keep it — uv tool install

uv tool install drillion
drillion

Puts drillion on your PATH. uv tool upgrade drillion updates it.

Keep it — pip

pip install drillion
drillion

The same thing without uv. Use a virtualenv if you keep your system Python clean.

Docker

docker run -p 127.0.0.1:8765:8765 -v drillion:/data ghcr.io/vazome/drillion

The image carries the tasks and the page; the named volume keeps your work across upgrades. Open http://127.0.0.1:8765 yourself — the container never opens a browser. compose.yaml is the same thing plus restart: unless-stopped, so drillion comes back after a reboot; save that one file anywhere and docker compose up -d.

Commands

drillion              # serve the web UI (default)
drillion selfcheck    # solve every task with its own reference — proves the set still works
drillion doctor       # say why a task folder would be skipped

Your progress

Everything drillion owns lives under one root: tasks/, which is where your code is saved, and progress.json, which holds your cards, notes and archived solutions. From a clone that root is the checkout. Installed, it is a per-user data directory that the first run seeds from the tasks inside the wheel. In Docker it is the volume at /data. An upgrade never writes over a root that already has tasks in it, so nothing you have written is at risk. See docs/configuration.md for the environment variables and the Docker bind-mount recipe.

Docs

• How a sitting works, and why — the loop, the ladder, the grading rules
• Configuration — environment, data root, Docker, release verification
• Authoring a task — tiers, difficulty, tags, the folder format
• CONTEXT.md — the vocabulary the code, the API and the UI all use
• DESIGN.md — the UI brief; web/README.md for the frontend
• docs/adr/ — decisions worth their own page

Contributing

The most useful contribution is a new task. Open an issue with the New task template first, then read CONTRIBUTING.md for the dev loop and the contract a task is graded against, and AGENTS.md for how the project decides things. Bugs and ideas go in Issues; a vulnerability goes through SECURITY.md, which also spells out what running drillion does to your machine.

License

MIT — see LICENSE. 84 of the 171 tasks carry Markdown adapted from Exercism's Python track (also MIT); each names its origin in a source: field and an attribution footer, and NOTICE reproduces the notice that travels with them.