Python Code Style

When to use this skill

Use Python Code Style when an AI agent needs a reusable SKILL.md workflow for this job: 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.

When not to use it

Skip Python Code Style when the task is outside the coding category, or when a more specific skill in this directory already covers the same workflow with clearer triggers.

How to install

1. Personal install: create ~/.claude/skills/python-code-style/SKILL.md (and any bundled scripts) so Claude Code, Claude Desktop, and compatible agents can load it in every project.
2. Project install: commit the same folder at .claude/skills/python-code-style/ so teammates get the skill with the repo.
3. Restart the agent session after copying files so it re-scans the skills directory, then ask for the task in words that match the skill description.

Full install guide for Claude, Cursor, and Codex

What this skill does

# 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

```bash # 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.

```toml # 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:

```bash ruff check --fix . # Lint and auto-fix ruff format . # Format code ```

### Pattern 2: Type Checking Configuration

Configure strict type checking for production code.

```toml # 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.

```toml [tool.pyright] pythonVersion = "3.12" typeCheckingMode = "strict" ```

### Pattern 3: Naming Conventions

Follow PEP 8 with emphasis on clarity over brevity.

**Files and Modules:**

```python # 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:**

```python # 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:**

```python # 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.

```python # 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:

```python # 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:**

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

**Complex Function:**

```python 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:**

```python 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.

```python # 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:**

```markdown # 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):**

```markdown # 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

Intended uses

• 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