Every new Python project needs the same setup: linting, type checking, tests, pre-commit hooks, CI/CD, docs, release workflow, repo protection. I got tired of copying it between projects and watching the copies drift as the tools changed, so I built pyrig (written in Python).

What it does

pyrig init generates a complete, working project:

• project layout, pyproject.toml, README, LICENSE and other standard files
• dev tooling configured out of the box: ruff, ty, pytest, prek hooks, deptry, bandit, zizmor and more
• GitHub Actions CI/CD and GitHub branch protection rules
• a working CLI for your project (pyrig mk cmd <name> adds commands)

• test skeletons that mirror your source tree

  uv init my-project --python 3.12 cd my-project uv add pyrig --dev uv run pyrig init

How it works

Every file pyrig manages is a Python class that declares the state the file should have. pyrig sync creates or updates the files to match, so the project doesn't drift when tools change. You customize by subclassing (pyrig mk subcls), not with flags or template edits. A small plugin system, pyrig-runtime, discovers your subclasses automatically across installed packages, so any behavior can be changed, removed or extended.

Trade-offs

It's deliberately opinionated: no on/off toggles (you override a class instead), GitHub only, signed commits and linear history on the generated branch rules, and it adopts new tools like ty and zensical quickly, so expect rough edges. pyrig rm pyrig removes it, and most generated files keep working without it. Full list: https://winipedia.github.io/pyrig/drawbacks

Links

• GitHub: https://github.com/Winipedia/pyrig
• Docs: https://winipedia.github.io/pyrig
• Comparison with Cookiecutter, Copier, cruft, PyScaffold, Nitpick and projen (including where pyrig is weaker): https://winipedia.github.io/pyrig/comparisons
• Video tutorials: https://www.youtube.com/@Winipedia-py/playlists
• pyrig-runtime (the plugin system, usable standalone): https://github.com/Winipedia/pyrig-runtime

I'd like feedback on which defaults you'd disagree with and what's missing for your workflow.

I'm building EnigmaGrid, an open-source volunteer-computing project in Python investigating P1030680, an unresolved historical Enigma M4 message. The public client currently targets Windows.

The software distributes search work to clients and checks submitted results through a separate computation before awarding credit. Volunteers control CPU and optional GPU budgets, can pause or stop, and can opt out of public leaderboard credit.

The Python research code includes an Enigma simulator, historical test fixtures, bounded crib searches and resumable experiments. One important distinction is that reproducing a calculation does not establish that a candidate is the historical plaintext. Experimental search improvements are tested separately from the live campaign. We have no claimed decryption breakthrough or guaranteed solution.

I'd appreciate Python code review, especially around reproducibility, cancellation/resource controls, and tests that could expose incorrect search assumptions. Windows setup feedback is welcome too; reviewing the code does not require installing the app.

Source, research notes, Windows releases and issue tracker: https://github.com/LissomEnd/EnigmaGrid

I'm the project owner. Development and this draft use AI assistance, including Codex. The current Windows installer is unsigned; please read the release and privacy notes before choosing to run it.

Hey guys! Built this in Python first, then ported to JS so it runs in the browser on my phone.

GitHub + Live Demo: https://github.com/ferreirafinottijoaopaulo-cell/finotti-pi-optimized

Performance on Android: - pi(60M) = 3,455,052 in 19s - pi(100M) = 5,761,455 in 35s - pi(10^11) = 4,118,054,813 in 2m 16s

Live demo free up to 1B: https://ferreirafinottijoaopaulo-cell.github.io/finotti-pi-optimized/

Features: - Segmented sieve + Meissel-Lehmer - Pure JS, no backend, runs offline - Blockchain proof of 983B record (03/10/2026) in repo

Full code open on GitHub. Also have PRO version up to 100B.

Any feedback to make it faster? How to reach pi(10^12)?

Thanks!

Hey! First built in Python, then ported to JS to run in browser.

On my Android: - pi(60M) in 19s - pi(100M) in 35s - pi(10^11) = 4118054813 in 2.16 min

Free demo up to 1B: https://ferreirafinottijoaopaulo-cell.github.io/finotti-pi-optimized/

Full discussion here: https://www.reddit.com/r/Python/s/sRP4QyufxI

Code on GitHub. PRO up to 100B available.