FastAPI

When to Use

• APIs: The default choice for modern Python APIs.
• Machine Learning: Native integration with Pydantic makes JSON <-> Model interaction seamless.
• Performance: Built on Starlette and Pydantic v2, it rivals Node.js and Go in benchmarks.

Quick Start

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class Item(BaseModel):
    name: str
    price: float

@app.post("/items/")
async def create_item(item: Item):
    return {"name": item.name, "price": item.price}

Core Concepts

Pydantic Models

Dependency Injection

async def read_users(db: Session = Depends(get_db)):

OpenAPI (Swagger)

/docs

Best Practices (2025)

• Use Pydantic v2: Ensure you are on v2 for the massive Rust-based performance boost.
• Use

  lifespan

  : Use the new

  lifespan

  context manager for startup/shutdown events instead of deprecated

  on_event

  .
• Type Everything: The more you type, the better the auto-generated docs and validation.

• Don't block the loop: Run CPU bound code (image processing, heavy math) in

  def

  endpoints (threadpool), not

  async def

  (event loop), or use background tasks.

References

• FastAPI Documentation