python

name	python
description	Expert Python language skill for writing, refactoring, and testing idiomatic Python 3 code. You MUST load this skill when developing Python modules, classes, or scripts.
license	MIT

Skill: python

Use this skill when developing Python code. For inline bash script Python execution, refer to the python-cli skill.

WHEN TO USE

• Writing new Python 3 scripts, modules, or classes.
• Refactoring existing Python code for performance, readability, or modern syntax.
• Writing unit tests using pytest or unittest.
• Debugging complex Python tracebacks or logic errors.

WHEN NOT TO USE

• When executing one-off shell pipeline data transformations (use python-cli instead).
• For writing shell scripts (bash) or other languages (JS/TS, Go, Rust).
• When managing project dependencies or virtual environments (use pipenv or pipfile skills instead).

Common Pitfalls

• Ignoring Type Hints: Writing naked functions without typing module annotations, making the code harder to maintain and refactor.
• Mutable Default Arguments: Using def foo(items=[]) instead of def foo(items=None).
• Catch-All Exceptions: Using a bare except: or except Exception: without logging the traceback or re-raising, swallowing critical errors silently.

Core Principles

• Idiomatic Python: Follow PEP 8 guidelines for code style. Use standard Python naming conventions.
• Type Hinting: Always use type hints (typing module) for function signatures and class attributes.
• Modern Features: Utilize modern Python 3.11+ features like match/case, dataclasses, and standard library enhancements when applicable.
• Docstrings: Document classes and functions using standard docstring formats (e.g., Google or Sphinx style) describing arguments, return types, and exceptions raised.
• Testing: Ensure all business logic is covered by unit tests (e.g., using pytest).

Usage Patterns

Dataclasses and Type Hints

Use dataclasses for robust data structures:

from dataclasses import dataclass, field
from typing import List, Optional

@dataclass
class User:
    id: int
    username: str
    email: Optional[str] = None
    roles: List[str] = field(default_factory=list)

    def is_admin(self) -> bool:
        """Check if the user has the 'admin' role."""
        return 'admin' in self.roles

Error Handling

Use explicit exception handling:

import logging

logger = logging.getLogger(__name__)

def process_data(data: dict) -> None:
    try:
        value = data['key']
        # Process value
    except KeyError as e:
        logger.error(f"Missing required key: {e}")
        raise ValueError("Invalid data format") from e