from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class BaseItem(BaseModel):
    description: str
    type: str


class CarItem(BaseItem):
    type: str = "car"


class PlaneItem(BaseItem):
    type: str = "plane"
    size: int


items = {
    "item1": {"description": "All my friends drive a low rider", "type": "car"},
    "item2": {

from collections.abc import AsyncIterable, Iterable

from fastapi import FastAPI
from fastapi.sse import EventSourceResponse
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None


items = [
    Item(name="Plumbus", description="A multi-purpose household device."),
    Item(name="Portal Gun", description="A portal opening device."),

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


class User(BaseModel):
    username: str
    full_name: str | None = None


@app.put("/items/{item_id}")
async def update_item(
    *,
    item_id: int,
    item: Item,
    user: User,

If you want to secure your API, there are several better things you can do, for example:

* Make sure you have well defined Pydantic models for your request bodies and responses.
* Configure any required permissions and roles using dependencies.
* Never store plaintext passwords, only password hashes.

`SQLModel` をインポートしてデータベースモデルを作成します:

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

`Hero` クラスは Pydantic モデルによく似ています（実際には内部的に Pydantic モデルでもあります）。

いくつかの違いがあります:

* `table=True` は SQLModel に対して「これはテーブルモデルであり、SQL データベースのテーブルを表す。単なるデータモデル（通常の Pydantic クラス）ではない」と伝えます。

* `Field(primary_key=True)` は `id` が SQL データベースのプライマリキーであることを SQLModel に伝えます（SQL のプライマリキーについては SQLModel ドキュメントを参照してください）。

from fastapi import FastAPI
from fastapi.testclient import TestClient
from pydantic import BaseModel

app = FastAPI()


class MyModel(BaseModel):
    """
    A model with a form feed character in the title.
    \f
    Text after form feed character.
    """


@app.get("/foo")
def foo(v: MyModel):  # pragma: no cover
    pass


client = TestClient(app)


def test_openapi():

from fastapi import Depends, FastAPI, Security
from fastapi.security import APIKeyQuery
from fastapi.testclient import TestClient
from inline_snapshot import snapshot
from pydantic import BaseModel

app = FastAPI()

api_key = APIKeyQuery(name="key", description="API Key Query")


class User(BaseModel):
    username: str


def get_current_user(oauth_header: str = Security(api_key)):
    user = User(username=oauth_header)

    assert response.status_code == 500
    assert response.text == "Internal Server Error"


def test_broken_session_stream_raise():
    # Can raise ValueError on Pydantic v2 and ExceptionGroup on Pydantic v1
    with pytest.raises((ValueError, Exception)):
        client.get("/broken-session-stream")


def test_broken_session_stream_no_raise():
    """

我將 **FastAPI** 視為 APIStar 的「精神繼承者」，同時基於所有這些先前工具的經驗，改進並擴增了功能、型別系統與其他部分。

///

## **FastAPI** 所採用的工具 { #used-by-fastapi }

### [Pydantic](https://docs.pydantic.dev/) { #pydantic }

Pydantic 是基於 Python 型別提示，定義資料驗證、序列化與文件（使用 JSON Schema）的函式庫。

這讓它非常直覺。

它可與 Marshmallow 相提並論。儘管在效能測試中它比 Marshmallow 更快。而且因為它基於相同的 Python 型別提示，編輯器支援也很出色。

/// check | **FastAPI** 用於

from typing import Annotated

from fastapi import FastAPI, Header, HTTPException
from pydantic import BaseModel

fake_secret_token = "coneofsilence"

fake_db = {
    "foo": {"id": "foo", "title": "Foo", "description": "There goes my hero"},
    "bar": {"id": "bar", "title": "Bar", "description": "The bartenders"},
}

app = FastAPI()


class Item(BaseModel):
    id: str
    title: str
    description: str | None = None