Consistent code style and clear documentation make codebases maintainable and collaborative. This skill covers modern Python tooling, naming conventions, and documentation standards.
- 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
Install tools, run formatters, or rewrite files only when the user asks for it.
Let tools handle formatting debates. Configure once, enforce automatically.
Follow PEP 8 conventions with meaningful, descriptive names.
Docstrings should be maintained alongside the code they describe.
Modern Python code should include type hints for all public APIs.
Install the tools inside a virtual environment, and pin exact versions of ruff and mypy as project development dependencies, ideally in a lockfile with hashes, so local runs and CI use the same versions. Present install commands to the user and run them only when the user asks.
# Install modern tooling
pip install ruff mypy
# pyproject.toml
[tool.ruff]
line-length = 120
target-version = "py312" # Adjust based on your project's minimum Python version
[tool.mypy]
strict = true
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"
These commands rewrite files in place across the whole directory. Run them when the user asks, from the project root with a clean or committed git working tree. Limit the target to the intended source and test folders where possible, exclude vendored or generated code in the ruff config, and review the resulting changes with git before committing.
Run with:
ruff check --fix . # Lint and auto-fix
ruff format . # Format code
Configure strict type checking for production code.
# pyproject.toml
[tool.mypy]
python_version = "3.12" # Adjust based on your project's minimum Python version
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" # Adjust based on your project's minimum Python version
typeCheckingMode = "strict"
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"
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
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
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)
.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} "
)
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
\`\`\`
The api key value in the README Quick Start example is a placeholder. Load real API keys from an environment variable or secret store documented in the Configuration section, and keep them out of source code and commits.
CHANGELOG Format (Keep a Changelog):
# Changelog
## [Unreleased]
### Added
- New feature X
### Changed
- Modified behavior of Y
### Fixed
- Bug in Z
- 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+ - Set the ruff target version, mypy python version, and pyright python version to your project's minimum supported Python; for new projects, Python 3.12+ is recommended for modern language features