alleneubank/claude-code · Archived

python-best-practices

Use when reading or writing Python files (.py, pyproject.toml, requirements.txt).

All-time #6073 First seen Jan 20, 2026
8-week activity · all time api

Installation

$ npx skills add alleneubank/claude-code --skill python-best-practices

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 52
License LICENSE
Default branch main
Open issues 1
Status Archived

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,924 B
  • docs SUMMARY.md 1,713 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 2,041 installs

SKILL.md

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:

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 mutation

Discriminated unions with Literal:

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:

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:

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:

try:
    data = json.loads(raw)
except json.JSONDecodeError as err:
    raise ValueError(f"invalid JSON payload: {err}") from err

Structured Logging

Use a module-level logger with %s formatting (deferred string interpolation):

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 widget

Optional: ty

For fast type checking, consider ty from Astral (creators of ruff and uv). Written in Rust, significantly faster than mypy or pyright.

uvx ty check          # run directly, no install needed
uvx ty check src/     # check specific path
# 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 integration
  • mypy — mature, extensive plugin ecosystem