About python
A set of Python conventions and tooling guidance for developers writing or changing Python 3.11+ code. It covers typing, data modeling, async tasks, testing, packaging, and a strict mypy baseline.
Key features
- 01Type public function signatures
- 02Prefer Protocols and dataclasses
- 03Use pathlib and safe defaults
- 04Structure async tasks with TaskGroup
- 05Use pytest fixtures and parametrization
- 06Set strict mypy and Ruff tooling
Use cases
- 01Applying consistent conventions to new Python code
- 02Reviewing changes for typing and async safety
- 03Setting up packaging, linting, and test practices
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ alexander-danilenko/ cortex-ai-skills --skill pythonAfter installing, type/pythonin Claude Code to confirm it loaded.
Details
From the project READMEPython
House conventions for Python 3.11+. Apply them to code you are writing or changing — don't refactor untouched files to match unless asked.
Conventions
-
Type every public signature and keep
mypy --strictgreen. Types on internals are optional; types at the boundary are what stop a caller passing the wrong thing. -
Built-in generics and
X | None—list[str],dict[str, int],str | None.typing.ListandOptional[str]are the pre-3.10 spelling and only cost an import. -
Protocolover ABC inheritance. Structural typing lets any correctly-shaped object satisfy the contract — including a test double — with no inheritance tree to maintain. -
Dataclasses for data,
slots=Trueandfrozen=Truewhere they fit. They generate__init__,__repr__, and__eq__correctly; a hand-written__init__is where field drift starts. Pydantic is for validation and (de)serialisation at a boundary, not for plain records. -
pathlib, notos.path. Operator joins can't silently produce a wrong path from a stray separator. -
Never a mutable default argument.
def f(items=[])shares one list across every call — a bug that only appears on the second call. Default toNoneand build inside. -
asyncio.TaskGroupover baregather(3.11+): it cancels siblings on failure and reports viaExceptionGroup, so a crashed task can't leave the rest running detached. Useasync with asyncio.timeout(n)for deadlines. -
Hold a reference to every
create_task. The event loop only keeps a weak reference, so a fire-and-forget task can be garbage-collected mid-execution and simply vanish — no error, no result. Keep them in asetand discard on completion:_tasks: set[asyncio.Task[None]] = set() def spawn(coro: Coroutine[None, None, None]) -> None: task = asyncio.create_task(coro) _tasks.add(task) task.add_done_callback(_tasks.discard) -
Never a bare
except:— it swallowsKeyboardInterruptandSystemExit. Catch what you can actually handle. -
Google-style docstrings on public functions and classes, carrying intent rather than a restatement of the signature. The
documentationskill has the full rule. -
pytest: fixtures for setup,
parametrizefor cases. A loop inside one test reports a single failure and hides which case broke;parametrizenames each one. -
Poetry and
pyproject.tomlfor packaging, ruff for lint and format, and apy.typedmarker on any package whose types consumers should see. Use asrc/layout — it stops tests from importing the working directory instead of the installed package, which is how a broken package still passes its own suite.
Tooling baseline
strict = true covers most of it; these add the checks that catch real bugs rather than style. --strict-markers matters more than it looks: without it a typo'd @pytest.mark.integraton silently does nothing and the test runs where you thought it was excluded.
[tool.mypy]
strict = true
warn_unreachable = true
warn_redundant_casts = true
warn_unused_ignores = true
[[tool.mypy.overrides]]
module = "untyped_dep.*"
ignore_missing_imports = true
[tool.pytest.ini_options]
addopts = ["-ra", "--strict-markers", "--strict-config"]