How to use
- Copy the installation command and review the source package before installing it in your own agent environment.
- Check the source document for required tools, credentials and supported hosts.
- Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/alleneubank/claude-code --skill python-best-practicesBefore you start
- Installation does not include a model subscription, API allowance or permission to access your files.
- Repository stars and installation counts describe activity, not an independent quality or security test.
Original skill document
Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.
Python Best Practices
Follows type-first, functional, and error handling patterns from CLAUDE.md. This skill covers language-specific idioms only.
Make Illegal States Unrepresentable
Use Python's type system to prevent invalid states at type-check time.
Frozen dataclasses for immutable domain models:
python
from dataclasses import dataclass
from datetime import datetime
@dataclass(frozen=True)
class User:
id: str
email: str
name: str
created_at: datetime
# Frozen dataclasses are immutable — no accidental mutationDiscriminated unions with Literal:
python
from dataclasses import dataclass
from typing import Literal
@dataclass
class Success:
status: Literal["success"] = "success"
data: str
@dataclass
class Failure:
status: Literal["error"] = "error"
error: Exception
RequestState = Success | Failure
def handle_state(state: RequestState) -> None:
match state:
case Success(data=data):
render(data)
case Failure(error=err):
show_error(err)NewType for domain primitives:
python
from typing import NewType
UserId = NewType("UserId", str)
OrderId = NewType("OrderId", str)
def get_user(user_id: UserId) -> User:
# Type checker prevents passing OrderId here
...Protocol for structural typing:
python
from typing import Protocol
class Readable(Protocol):
def read(self, n: int = -1) -> bytes: ...
def process_input(source: Readable) -> bytes:
# Accepts any object with a read() method — no inheritance required
return source.read()Python-Specific Error Handling
Chain exceptions with from err to preserve the original traceback:
python
try:
data = json.loads(raw)
except json.JSONDecodeError as err:
raise ValueError(f"invalid JSON payload: {err}") from errStructured Logging
Use a module-level logger with %s formatting (deferred string interpolation):
python
import logging
logger = logging.getLogger("myapp.widgets")
def create_widget(name: str) -> Widget:
logger.debug("creating widget: %s", name)
widget = Widget(name=name)
logger.debug("created widget id=%s", widget.id)
return widgetOptional: ty
For fast type checking, consider ty from Astral (creators of ruff and uv). Written in Rust, significantly faster than mypy or pyright.
bash
uvx ty check # run directly, no install needed
uvx ty check src/ # check specific pathtoml
# pyproject.toml
[tool.ty]
python-version = "3.12"When to choose:
ty— fastest, good for CI and large codebases (early stage, rapidly evolving)pyright— most complete type inference, VS Code integrationmypy— mature, extensive plugin ecosystem
