Fastapi | Tutorial Pdf [better]

FastAPI is built on top of Starlette for the web parts and Pydantic for the data parts. It is designed to be easy to use for developers while providing production-grade performance. Key features include:

from sqlalchemy import Column, Integer, String from database import Base class DBUser(Base): __tablename__ = "users" id = Column(Integer, primary_key=True, index=True) username = Column(String, unique=True, index=True) email = Column(String, unique=True, index=True) Use code with caution. 3. Dependency Injection in Routes ( main.py )

from fastapi import Header, HTTPException async def verify_token(x_token: str = Header(...)): if x_token != "super-secret-token": raise HTTPException(status_code=400, detail="X-Token header invalid") return x_token @app.get("/protected-data/", dependencies=[Depends(verify_token)]) def get_protected_data(): return "data": "This is highly secured information." Use code with caution. 8. Authentication and Security (JWT)

| Concept | Code Snippet | |---------|---------------| | Basic app | app = FastAPI() | | GET | @app.get("/path") | | POST | @app.post("/path") | | Path param | def fn(item_id: int) | | Query param | def fn(q: str = None) | | Body | def fn(item: Item) | | Depends | def fn(db = Depends(get_db)) | | Exception | raise HTTPException(404, "msg") | | Response model | @app.get("/", response_model=Item) | | Docs URL | /docs or /redoc | fastapi tutorial pdf

from fastapi import FastAPI, Query, Path app = FastAPI() @app.get("/products/product_id") def get_product( product_id: int = Path(..., title="The ID of the product", ge=1), q: str = Query(None, min_length=3, max_length=50) ): return "product_id": product_id, "search_query": q Use code with caution.

class Item(BaseModel): name: str price: float is_offer: bool = False # default value

Very high performance, on par with NodeJS and Go (thanks to Starlette and Pydantic) 1. FastAPI is built on top of Starlette for

gunicorn main:app -w 4 -k uvicorn.workers.UvicornWorker --bind 0.0.0.0:8000

FastAPI does not require a specific database, but it works seamlessly with SQLAlchemy, Tortoise ORM, and databases like PostgreSQL, MySQL, and SQLite. Using an asynchronous database driver is recommended to leverage FastAPI's performance. Summary and PDF Export

FastAPI reads the incoming JSON, validates the data types against the Product model, and passes it to the function as a clean Python object. Connecting a Database (SQLAlchemy & Tortoise) Authentication and Security (JWT) | Concept | Code

Middlewares process requests before they reach path routing endpoints, and modify responses before they leave.

from pydantic import BaseModel, EmailStr class UserBase(BaseModel): email: EmailStr class UserCreate(UserBase): password: str class UserResponse(UserBase): id: int is_active: bool class Config: orm_mode = True Use code with caution. crud.py Handles database queries and operations.