| name | flask |
| description | Flask Python microframework with blueprints and extensions. Use for lightweight APIs. |
Flask
Flask is a lightweight WSGI web application framework. It is designed to make getting started quick and easy, with the ability to scale up to complex applications. Flask 3.0 (2025) fully supports async routes.
When to Use
- Microservices: Minimal boilerplate makes it great for small services.
- Flexibility: You validly choose your ORM (SQLAlchemy, Peewee) and Auth provider.
- Data Science APIs: The standard for wrapping ML models (PyTorch/TensorFlow) in an API.
Quick Start (Async)
from flask import Flask
import asyncio
app = Flask(__name__)
@app.route("/")
async def hello():
await asyncio.sleep(1)
return "Hello form Async Flask!"
Core Concepts
The Application Context
Flask uses thread-locals (or context-vars in async) to make request and g globally accessible during a request.
Blueprints
Organize a group of related views and other code. auth_bp = Blueprint('auth', __name__).
Best Practices (2025)
Do:
- Use
Quart or Flask 3.0+: Ensure you are using modern async features if your app is I/O bound.
- Use
pydantic: Use Pydantic for request validation (via libraries like flask-pydantic or just raw).
- Application Factory Pattern: Always use
create_app() to ensure your app is testable.
Don't:
- Don't use global state: Use
current_app or g to store request-scoped data.
References
