skills/python-patterns/SKILL.md
Python development principles and decision-making. Framework selection, async patterns, type hints, project structure. Teaches thinking, not copying.
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Python development principles and decision-making for 2025. Learn to THINK, not memorize patterns.
Use this skill when making Python architecture decisions, choosing frameworks, designing async patterns, or structuring Python projects.
This skill teaches decision-making principles, not fixed code to copy.
What are you building?
│
├── API-first / Microservices
│ └── FastAPI (async, modern, fast)
│
├── Full-stack web / CMS / Admin
│ └── Django (batteries-included)
│
├── Simple / Script / Learning
│ └── Flask (minimal, flexible)
│
├── AI/ML API serving
│ └── FastAPI (Pydantic, async, uvicorn)
│
└── Background workers
└── Celery + any framework
| Factor | FastAPI | Django | Flask | |--------|---------|--------|-------| | Best for | APIs, microservices | Full-stack, CMS | Simple, learning | | Async | Native | Django 5.0+ | Via extensions | | Admin | Manual | Built-in | Via extensions | | ORM | Choose your own | Django ORM | Choose your own | | Learning curve | Low | Medium | Low |
async def is better when:
├── I/O-bound operations (database, HTTP, file)
├── Many concurrent connections
├── Real-time features
├── Microservices communication
└── FastAPI/Starlette/Django ASGI
def (sync) is better when:
├── CPU-bound operations
├── Simple scripts
├── Legacy codebase
├── Team unfamiliar with async
└── Blocking libraries (no async version)
I/O-bound → async (waiting for external)
CPU-bound → sync + multiprocessing (computing)
Don't:
├── Mix sync and async carelessly
├── Use sync libraries in async code
└── Force async for CPU work
| Need | Async Library | |------|---------------| | HTTP client | httpx | | PostgreSQL | asyncpg | | Redis | aioredis / redis-py async | | File I/O | aiofiles | | Database ORM | SQLAlchemy 2.0 async, Tortoise |
Always type:
├── Function parameters
├── Return types
├── Class attributes
├── Public APIs
Can skip:
├── Local variables (let inference work)
├── One-off scripts
├── Tests (usually)
# These are patterns, understand them:
# Optional → might be None
from typing import Optional
def find_user(id: int) -> Optional[User]: ...
# Union → one of multiple types
def process(data: str | dict) -> None: ...
# Generic collections
def get_items() -> list[Item]: ...
def get_mapping() -> dict[str, int]: ...
# Callable
from typing import Callable
def apply(fn: Callable[[int], str]) -> str: ...
When to use Pydantic:
├── API request/response models
├── Configuration/settings
├── Data validation
├── Serialization
Benefits:
├── Runtime validation
├── Auto-generated JSON schema
├── Works with FastAPI natively
└── Clear error messages
Small project / Script:
├── main.py
├── utils.py
└── requirements.txt
Medium API:
├── app/
│ ├── __init__.py
│ ├── main.py
│ ├── models/
│ ├── routes/
│ ├── services/
│ └── schemas/
├── tests/
└── pyproject.toml
Large application:
├── src/
│ └── myapp/
│ ├── core/
│ ├── api/
│ ├── services/
│ ├── models/
│ └── ...
├── tests/
└── pyproject.toml
Organize by feature or layer:
By layer:
├── routes/ (API endpoints)
├── services/ (business logic)
├── models/ (database models)
├── schemas/ (Pydantic models)
└── dependencies/ (shared deps)
By feature:
├── users/
│ ├── routes.py
│ ├── service.py
│ └── schemas.py
└── products/
└── ...
Django supports async:
├── Async views
├── Async middleware
├── Async ORM (limited)
└── ASGI deployment
When to use async in Django:
├── External API calls
├── WebSocket (Channels)
├── High-concurrency views
└── Background task triggering
Model design:
├── Fat models, thin views
├── Use managers for common queries
├── Abstract base classes for shared fields
Views:
├── Class-based for complex CRUD
├── Function-based for simple endpoints
├── Use viewsets with DRF
Queries:
├── select_related() for FKs
├── prefetch_related() for M2M
├── Avoid N+1 queries
└── Use .only() for specific fields
Use async def when:
├── Using async database drivers
├── Making as
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