FastAPI 預設回傳 JSON 回應。

如果你宣告了[回應模型](../tutorial/response-model.md)，FastAPI 會使用 Pydantic 將資料序列化為 JSON。

如果你沒有宣告回應模型，FastAPI 會使用在[JSON 相容編碼器](../tutorial/encoder.md)中解釋的 `jsonable_encoder`，並將結果放進 `JSONResponse`。

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

The same way, there are many compatible tools. Including code generation tools for many languages.

## Pydantic { #pydantic }

All the data validation is performed under the hood by [Pydantic](https://docs.pydantic.dev/), so you get all the benefits from it. And you know you are in good hands.

from fastapi import FastAPI
from fastapi.responses import JSONResponse
from pydantic import BaseModel


class Item(BaseModel):
    id: str
    value: str


class Message(BaseModel):
    message: str


app = FastAPI()


@app.get(
    "/items/{item_id}",
    response_model=Item,
    responses={
        404: {"model": Message, "description": "The item was not found"},
        200: {

from collections.abc import AsyncIterable
from typing import Annotated

from fastapi import FastAPI, Header
from fastapi.sse import EventSourceResponse, ServerSentEvent
from pydantic import BaseModel

app = FastAPI()


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


items = [
    Item(name="Plumbus", price=32.99),
    Item(name="Portal Gun", price=999.99),
    Item(name="Meeseeks Box", price=49.99),
]

from typing import Annotated

from fastapi import FastAPI, Form
from pydantic import BaseModel

app = FastAPI()


class FormData(BaseModel):
    username: str
    password: str


@app.post("/login/")
async def login(data: Annotated[FormData, Form()]):

from fastapi import FastAPI
from fastapi.encoders import jsonable_encoder
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str | None = None
    description: str | None = None
    price: float | None = None
    tax: float = 10.5
    tags: list[str] = []


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The bartenders", "price": 62, "tax": 20.2},

from typing import Annotated

from fastapi import FastAPI, Form
from pydantic import BaseModel

app = FastAPI()


class FormData(BaseModel):
    username: str
    password: str
    model_config = {"extra": "forbid"}


@app.post("/login/")
async def login(data: Annotated[FormData, Form()]):

Each of those response `dict`s can have a key `model`, containing a Pydantic model, just like `response_model`.

**FastAPI** will take that model, generate its JSON Schema and include it in the correct place in OpenAPI.

For example, to declare another response with a status code `404` and a Pydantic model `Message`, you can write:

{* ../../docs_src/additional_responses/tutorial001_py310.py hl[18,22] *}

from fastapi import FastAPI
from pydantic import BaseModel, EmailStr

app = FastAPI()


class UserIn(BaseModel):
    username: str
    password: str
    email: EmailStr
    full_name: str | None = None


class UserOut(BaseModel):
    username: str
    email: EmailStr
    full_name: str | None = None


class UserInDB(BaseModel):
    username: str
    hashed_password: str
    email: EmailStr

もしあなたのAPIのセキュリティを強化したいなら、いくつかのよりよい方法があります。例を示すと、

* リクエストボディとレスポンスのためのPydanticモデルの定義を見直す。
* 依存関係に基づきすべての必要なパーミッションとロールを設定する。
* パスワードを絶対に平文で保存しない。パスワードハッシュのみを保存する。
* pwdlibやJWTトークンに代表される、よく知られた暗号化ツールを使って実装する。
* そして必要なところでは、もっと細かいパーミッション制御をOAuth2スコープを使って行う。
* ...など