Python Standards

Auto-loads for projects with Python in their tech stack.

Metadata

Field	Value
Type	context
Applies to	python, fastapi, django, flask, pytest, pydantic, sqlalchemy, celery, poetry, asyncio, aiohttp, httpx

Core Principles

Simplicity - Simple, understandable code
Readability - Readability over cleverness
Maintainability - Code that’s easy to maintain
Testability - Code that’s easy to test
DRY - Don’t Repeat Yourself

Naming Conventions

Element	Convention	Example
Variables/Functions	snake_case	`get_user_by_id`, `is_active`
Classes	PascalCase	`UserService`, `ApiClient`
Constants	UPPER_SNAKE_CASE	`MAX_RETRY_COUNT`
Private	Prefix with `_`	`_internal_method`
Files/Modules	snake_case	`user_service.py`

Code Style

from dataclasses import dataclass
 
@dataclass
class User:
    id: str
    name: str
    email: str
    age: int | None = None
 
def get_user_by_id(user_id: str) -> User | None:
    if not user_id:
        raise ValueError("user_id cannot be empty")
    # implementation...

Best Practices

# Type hints everywhere
def process_items(items: list[str]) -> dict[str, int]:
    return {item: len(item) for item in items}
 
# Pydantic for validation
from pydantic import BaseModel, Field
 
class UserCreate(BaseModel):
    name: str = Field(..., min_length=2, max_length=50)
    email: EmailStr
    age: int | None = Field(None, ge=0, le=150)
 
# Prefer pathlib over os.path
from pathlib import Path
config_path = Path(__file__).parent / 'config.yaml'

Async/Await

async def fetch_user(user_id: str) -> User | None:
    async with httpx.AsyncClient() as client:
        response = await client.get(f"/users/{user_id}")
        return User(**response.json()) if response.status_code == 200 else None
 
# Gather for concurrent operations
async def fetch_all_users(user_ids: list[str]) -> list[User]:
    tasks = [fetch_user(uid) for uid in user_ids]
    return await asyncio.gather(*tasks)

Recommended Tooling

Tool	Purpose
`uv`	Package manager (faster than pip/poetry)
`ruff`	Linting (replaces flake8, isort, black)
`mypy` or `pyright`	Type checking
`pytest`	Testing with `pytest-cov`, `pytest-asyncio`

Production Checklist

Type hints everywhere
Pydantic for validation
Async for I/O operations
Structured logging (not print)
Environment variables via pydantic-settings
Custom exceptions for domain errors
Connection pooling for databases/HTTP

Overview TypeScript