Python Best Practices

Python Best Practices Skill

This skill provides guidance on Python development best practices, patterns, and conventions.

Code Style

Naming Conventions

• Variables/Functions: snake_case
• Classes: PascalCase
• Constants: UPPER_SNAKE_CASE
• Private: _single_leading_underscore
• "Dunder": __double_underscore__ (reserved for Python)

Formatting

• 4 spaces for indentation (never tabs)
• Max line length: 88-120 characters (project dependent)
• Use Black or Ruff for auto-formatting
• Blank lines: 2 between top-level definitions, 1 within classes

Type Hints

# Function signatures
def process_data(items: list[str], limit: int = 10) -> dict[str, int]:
    ...

# Optional values
def find_user(user_id: int) -> User | None:
    ...

# Complex types
from typing import TypeVar, Generic, Protocol

T = TypeVar('T')

class Repository(Protocol[T]):
    def get(self, id: int) -> T | None: ...
    def save(self, entity: T) -> None: ...

Error Handling

# DO: Specific exceptions
try:
    user = get_user(user_id)
except UserNotFoundError:
    logger.warning(f"User {user_id} not found")
    return None

# DON'T: Bare except
try:
    user = get_user(user_id)
except:  # Bad - catches everything including KeyboardInterrupt
    pass

# Custom exceptions
class DomainError(Exception):
    """Base class for domain exceptions."""
    pass

class UserNotFoundError(DomainError):
    def __init__(self, user_id: int):
        self.user_id = user_id
        super().__init__(f"User {user_id} not found")

Data Classes and Models

from dataclasses import dataclass, field
from datetime import datetime

@dataclass
class User:
    id: int
    name: str
    email: str
    created_at: datetime = field(default_factory=datetime.now)
    tags: list[str] = field(default_factory=list)

    def __post_init__(self):
        self.email = self.email.lower()

# For validation, use Pydantic
from pydantic import BaseModel, EmailStr, Field

class UserCreate(BaseModel):
    name: str = Field(min_length=1, max_length=100)
    email: EmailStr

    model_config = {"str_strip_whitespace": True}

Async Patterns

import asyncio
from typing import AsyncIterator

# Async context manager
class AsyncDatabaseConnection:
    async def __aenter__(self) -> "AsyncDatabaseConnection":
        await self.connect()
        return self

    async def __aexit__(self, exc_type, exc_val, exc_tb):
        await self.close()

# Async generator
async def stream_results(query: str) -> AsyncIterator[dict]:
    async with get_connection() as conn:
        async for row in conn.execute(query):
            yield dict(row)

# Concurrent execution
async def fetch_all(urls: list[str]) -> list[Response]:
    async with aiohttp.ClientSession() as session:
        tasks = [fetch_one(session, url) for url in urls]
        return await asyncio.gather(*tasks)

Testing

import pytest
from unittest.mock import Mock, patch, AsyncMock

# Fixtures
@pytest.fixture
def sample_user():
    return User(id=1, name="Test", email="test@example.com")

@pytest.fixture
def mock_db():
    with patch("myapp.database.get_connection") as mock:
        yield mock

# Parametrized tests
@pytest.mark.parametrize("input,expected", [
    ("hello", "HELLO"),
    ("World", "WORLD"),
    ("", ""),
])
def test_uppercase(input: str, expected: str):
    assert uppercase(input) == expected

# Async tests
@pytest.mark.asyncio
async def test_async_fetch():
    result = await fetch_data("http://example.com")
    assert result.status == 200

# Exception testing
def test_invalid_input_raises():
    with pytest.raises(ValueError, match="must be positive"):
        process_value(-1)

Project Structure

myproject/
├── src/
│   └── myproject/
│       ├── __init__.py
│       ├── core/           # Business logic
│       ├── api/            # API layer
│       ├── models/         # Data models
│       └── utils/          # Utilities
├── tests/
│   ├── conftest.py         # Shared fixtures
│   ├── unit/
│   └── integration/
├── pyproject.toml          # Project config
├── README.md
└── .env.example

Dependencies

# pyproject.toml
[project]
name = "myproject"
version = "0.1.0"
requires-python = ">=3.11"
dependencies = [
    "pydantic>=2.0",
    "httpx>=0.24",
]

[project.optional-dependencies]
dev = [
    "pytest>=7.0",
    "pytest-asyncio>=0.21",
    "ruff>=0.1",
    "mypy>=1.0",
]

[tool.ruff]
line-length = 88
target-version = "py311"

[tool.mypy]
strict = true

Common Anti-Patterns to Avoid

1. Mutable default arguments

   # Bad
   def add_item(item, items=[]):
       items.append(item)
       return items
   
   # Good
   def add_item(item, items=None):
       if items is None:
           items = []
       items.append(item)
       return items
   

2. Using type() for type checking

   # Bad
   if type(x) == list:
   
   # Good
   if isinstance(x, list):
   

3. Catching too broadly

   # Bad
   except Exception:
   
   # Good
   except (ValueError, TypeError):
   

4. String concatenation in loops

   # Bad
   result = ""
   for item in items:
       result += str(item)
   
   # Good
   result = "".join(str(item) for item in items)