from typing import Union

from fastapi import FastAPI
from pydantic.v1 import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None

    class Config:
        schema_extra = {
            "examples": [
                {
                    "name": "Foo",
                    "description": "A very nice Item",

from typing import Annotated, Union

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None


@app.put("/items/{item_id}")
async def update_item(
    item_id: int,
    item: Annotated[
        Item,
        Body(
            examples=[
                {

<img src="/img/tutorial/path-params/image02.png">

Und viele weitere kompatible Tools. Inklusive Codegenerierung für viele Sprachen.

## Pydantic { #pydantic }

Die ganze Datenvalidierung wird hinter den Kulissen von <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> durchgeführt, Sie profitieren also von dessen Vorteilen. Und Sie wissen, dass Sie in guten Händen sind.

from typing import Annotated

from fastapi import Depends, FastAPI, HTTPException, status
from fastapi.security import OAuth2PasswordBearer, OAuth2PasswordRequestForm
from pydantic import BaseModel

fake_users_db = {
    "johndoe": {
        "username": "johndoe",
        "full_name": "John Doe",
        "email": "******@****.***",
        "hashed_password": "fakehashedsecret",
        "disabled": False,
    },
    "alice": {

import logging
from typing import Literal

from github import Github
from github.PullRequestReview import PullRequestReview
from pydantic import BaseModel, SecretStr
from pydantic_settings import BaseSettings


class LabelSettings(BaseModel):
    await_label: str | None = None
    number: int


default_config = {"approved-2": LabelSettings(await_label="awaiting-review", number=2)}


class Settings(BaseSettings):

## 요구사항

FastAPI는 거인들의 어깨 위에 서 있습니다:

* 웹 부분을 위한 <a href="https://www.starlette.dev/" class="external-link" target="_blank">Starlette</a>.
* 데이터 부분을 위한 <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a>.

## 설치

<div class="termy">

```console
$ pip install fastapi

---> 100%
```

</div>

`SQLModel`을 가져오고 데이터베이스 모델을 생성합니다:

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[1:11] hl[7:11] *}

`Hero` 클래스는 Pydantic 모델과 매우 유사합니다 (실제로 내부적으로 *Pydantic 모델이기도 합니다*).

몇 가지 차이점이 있습니다:

* `table=True`는 SQLModel에 이 모델이 *테이블 모델*이며, 단순한 데이터 모델이 아니라 SQL 데이터베이스의 **테이블**을 나타낸다는 것을 알려줍니다. (다른 일반적인 Pydantic 클래스처럼) 단순한 *데이터 모델*이 아닙니다.

from fastapi import Body, FastAPI
from pydantic import BaseModel, Field

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = Field(
        default=None, title="The description of the item", max_length=300
    )
    price: float = Field(gt=0, description="The price must be greater than zero")
    tax: float | None = None


@app.put("/items/{item_id}")

from typing import Any, Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None
    tags: list[str] = []


@app.post("/items/", response_model=Item)
async def create_item(item: Item) -> Any:
    return item


@app.get("/items/", response_model=list[Item])

## Requisitos { #requirements }

Después de probar varias alternativas, decidí que iba a usar <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">**Pydantic**</a> por sus ventajas.