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Python Code Style

Seth HobsonCommunityCreated by Seth Hobson

  • Skill
  • Guidelines
  • Software development
  • MIT
  • Low risk

From the author

Python code style, linting, formatting, naming conventions, and documentation standards. Use when writing new code, reviewing style, configuring linters, writing docstrings, or establishing project standards.
— the description by Seth Hobson

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured approach to maintaining Python codebases through consistent style, naming conventions, and documentation. It outlines best practices for using modern linting and formatting tools, configuring type checkers, and structuring project documentation to improve maintainability and collaboration.

What it does

  • Defines naming conventions for modules, classes, and variables
  • Provides configuration patterns for linting and formatting tools like ruff
  • Details strict type checking configurations for mypy and pyright
  • Establishes standards for Google-style docstrings
  • Recommends project structure for README and CHANGELOG files
  • Advises on import organization and absolute path usage

When to use it

  • When initializing a new Python project
  • When establishing or updating team coding standards
  • When configuring automated linting and formatting pipelines
  • When writing or auditing docstrings for public APIs
  • When setting up project documentation and changelogs

Advantages

  • Promotes consistency across team-developed codebases
  • Reduces manual formatting effort through automated tooling
  • Improves code clarity with descriptive naming and type hints
  • Ensures public APIs are well-documented and maintainable
  • Simplifies project onboarding with standardized documentation structures

Usage examples

“How should I configure ruff for a new Python 3.12 project?”
The agent provides a pyproject.toml configuration snippet including line length settings, target version, and specific linting rules.
“What is the recommended way to document a complex function in Python?”
The agent provides a template for a Google-style docstring, including sections for arguments, return values, exceptions, and usage examples.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/wshobson/python-code-style/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip python-code-style.zip -d .agents/skills

Documentation by Seth Hobson

Python Code Style & Documentation

Consistent code style and clear documentation make codebases maintainable and collaborative. This skill covers modern Python tooling, naming conventions, and documentation standards.

When to Use This Skill

  • Setting up linting and formatting for a new project

  • Writing or reviewing docstrings

  • Establishing team coding standards

  • Configuring ruff, mypy, or pyright

  • Reviewing code for style consistency

  • Creating project documentation

Core Concepts

1. Automated Formatting

Let tools handle formatting debates. Configure once, enforce automatically.

2. Consistent Naming

Follow PEP 8 conventions with meaningful, descriptive names.

3. Documentation as Code

Docstrings should be maintained alongside the code they describe.

4. Type Annotations

Modern Python code should include type hints for all public APIs.

Quick Start

# Install modern tooling
pip install ruff mypy

# Configure in pyproject.toml
[tool.ruff]
line-length = 120
target-version = "py312"  # Adjust based on your project's minimum Python version

[tool.mypy]
strict = true

Fundamental Patterns

Pattern 1: Modern Python Tooling

Use ruff as an all-in-one linter and formatter. It replaces flake8, isort, and black with a single fast tool.

# pyproject.toml
[tool.ruff]
line-length = 120
target-version = "py312"  # Adjust based on your project's minimum Python version

[tool.ruff.lint]
select = [
    "E",    # pycodestyle errors
    "W",    # pycodestyle warnings
    "F",    # pyflakes
    "I",    # isort
    "B",    # flake8-bugbear
    "C4",   # flake8-comprehensions
    "UP",   # pyupgrade
    "SIM",  # flake8-simplify
]
ignore = ["E501"]  # Line length handled by formatter

[tool.ruff.format]
quote-style = "double"
indent-style = "space"

Run with:

ruff check --fix .  # Lint and auto-fix
ruff format .       # Format code
Pattern 2: Type Checking Configuration

Configure strict type checking for production code.

# pyproject.toml
[tool.mypy]
python_version = "3.12"
strict = true
warn_return_any = true
warn_unused_ignores = true
disallow_untyped_defs = true
disallow_incomplete_defs = true

[[tool.mypy.overrides]]
module = "tests.*"
disallow_untyped_defs = false

Alternative: Use pyright for faster checking.

[tool.pyright]
pythonVersion = "3.12"
typeCheckingMode = "strict"
Pattern 3: Naming Conventions

Follow PEP 8 with emphasis on clarity over brevity.

Files and Modules:

# Good: Descriptive snake_case
user_repository.py
order_processing.py
http_client.py

# Avoid: Abbreviations
usr_repo.py
ord_proc.py
http_cli.py

Classes and Functions:

# Classes: PascalCase
class UserRepository:
    pass

class HTTPClientFactory:  # Acronyms stay uppercase
    pass

# Functions and variables: snake_case
def get_user_by_email(email: str) -> User | None:
    retry_count = 3
    max_connections = 100

Constants:

# Module-level constants: SCREAMING_SNAKE_CASE
MAX_RETRY_ATTEMPTS = 3
DEFAULT_TIMEOUT_SECONDS = 30
API_BASE_URL = "https://api.example.com"
Pattern 4: Import Organization

Group imports in a consistent order: standard library, third-party, local.

# Standard library
import os
from collections.abc import Callable
from typing import Any

# Third-party packages
import httpx
from pydantic import BaseModel
from sqlalchemy import Column

# Local imports
from myproject.models import User
from myproject.services import UserService

Use absolute imports exclusively:

# Preferred
from myproject.utils import retry_decorator

# Avoid relative imports
from ..utils import retry_decorator

Advanced Patterns

Pattern 5: Google-Style Docstrings

Write docstrings for all public classes, methods, and functions.

Simple Function:

def get_user(user_id: str) -> User:
    """Retrieve a user by their unique identifier."""
    ...

Complex Function:

def process_batch(
    items: list[Item],
    max_workers: int = 4,
    on_progress: Callable[[int, int], None] | None = None,
) -> BatchResult:
    """Process items concurrently using a worker pool.

    Processes each item in the batch using the configured number of
    workers. Progress can be monitored via the optional callback.

    Args:
        items: The items to process. Must not be empty.
        max_workers: Maximum concurrent workers. Defaults to 4.
        on_progress: Optional callback receiving (completed, total) counts.

    Returns:
        BatchResult containing succeeded items and any failures with
        their associated exceptions.

    Raises:
        ValueError: If items is empty.
        ProcessingError: If the batch cannot be processed.

    Example:
        >>> result = process_batch(items, max_workers=8)
        >>> print(f"Processed {len(result.succeeded)} items")
    """
    ...

Class Docstring:

class UserService:
    """Service for managing user operations.

    Provides methods for creating, retrieving, updating, and
    deleting users with proper validation and error handling.

    Attributes:
        repository: The data access layer for user persistence.
        logger: Logger instance for operation tracking.

    Example:
        >>> service = UserService(repository, logger)
        >>> user = service.create_user(CreateUserInput(...))
    """

    def __init__(self, repository: UserRepository, logger: Logger) -> None:
        """Initialize the user service.

        Args:
            repository: Data access layer for users.
            logger: Logger for tracking operations.
        """
        self.repository = repository
        self.logger = logger
Pattern 6: Line Length and Formatting

Set line length to 120 characters for modern displays while maintaining readability.

# Good: Readable line breaks
def create_user(
    email: str,
    name: str,
    role: UserRole = UserRole.MEMBER,
    notify: bool = True,
) -> User:
    ...

# Good: Chain method calls clearly
result = (
    db.query(User)
    .filter(User.active == True)
    .order_by(User.created_at.desc())
    .limit(10)
    .all()
)

# Good: Format long strings
error_message = (
    f"Failed to process user {user_id}: "
    f"received status {response.status_code} "
    f"with body {response.text[:100]}"
)
Pattern 7: Project Documentation

README Structure:

# Project Name

Brief description of what the project does.

## Installation

\`\`\`bash
pip install myproject
\`\`\`

## Quick Start

\`\`\`python
from myproject import Client

client = Client(api_key="...")
result = client.process(data)
\`\`\`

## Configuration

Document environment variables and configuration options.

## Development

\`\`\`bash
pip install -e ".[dev]"
pytest
\`\`\`

CHANGELOG Format (Keep a Changelog):

# Changelog

## [Unreleased]

### Added
- New feature X

### Changed
- Modified behavior of Y

### Fixed
- Bug in Z

Best Practices Summary

  1. Use ruff - Single tool for linting and formatting

  2. Enable strict mypy - Catch type errors before runtime

  3. 120 character lines - Modern standard for readability

  4. Descriptive names - Clarity over brevity

  5. Absolute imports - More maintainable than relative

  6. Google-style docstrings - Consistent, readable documentation

  7. Document public APIs - Every public function needs a docstring

  8. Keep docs updated - Treat documentation as code

  9. Automate in CI - Run linters on every commit

  10. Target Python 3.10+ - For new projects, Python 3.12+ is recommended for modern language features

Files

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an API key, Needs Python

Security

What our scanner noticed· Low risk

  • Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Seth Hobson
Publisher
Seth Hobson (Community)
Source
wshobson/agents · plugins/python-development/skills/python-code-style · commit 4bde316
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Seth Hobson.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download python-code-style.zip