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

• Use ruff - Single tool for linting and formatting

• Enable strict mypy - Catch type errors before runtime

• 120 character lines - Modern standard for readability

• Descriptive names - Clarity over brevity

• Absolute imports - More maintainable than relative

• Google-style docstrings - Consistent, readable documentation

• Document public APIs - Every public function needs a docstring

• Keep docs updated - Treat documentation as code

• Automate in CI - Run linters on every commit

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