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


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item = Body(embed=True)):
    results = {"item_id": item_id, "item": item}

from typing import Annotated

from fastapi import FastAPI
from fastapi.temp_pydantic_v1_params import Body
from pydantic.v1 import BaseModel


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


app = FastAPI()


@app.post("/items/")
async def create_item(item: Annotated[Item, Body(embed=True)]) -> Item:

from fastapi import FastAPI
from pydantic import BaseModel, HttpUrl

app = FastAPI()


class Image(BaseModel):
    url: HttpUrl
    name: str


@app.post("/images/multiple/")
async def create_multiple_images(images: list[Image]):

        bufferIndex += 24;

        String str;
        if (this.unicode) {
            if (fileNameLength > 0 && buffer[bufferIndex + fileNameLength - 1] == '\0'
                    && buffer[bufferIndex + fileNameLength - 2] == '\0') {
                fileNameLength -= 2;
            }
            str = Strings.fromUNIBytes(buffer, bufferIndex, fileNameLength);
        } else {

```Python hl_lines="1"
async def needy_dependency(fresh_value: Annotated[str, Depends(get_value, use_cache=False)]):
    return {"fresh_value": fresh_value}
```

////

//// tab | Python 3.9+ non-Annotated

/// tip | Dica

Utilize a versão com `Annotated` se possível.

///

```Python hl_lines="1"
async def needy_dependency(fresh_value: str = Depends(get_value, use_cache=False)):
    return {"fresh_value": fresh_value}

from typing import Annotated

from fastapi import Header, HTTPException


async def get_token_header(x_token: Annotated[str, Header()]):
    if x_token != "fake-super-secret-token":
        raise HTTPException(status_code=400, detail="X-Token header invalid")


async def get_query_token(token: str):
    if token != "jessica":

from fastapi import Depends, FastAPI

app = FastAPI()


class FixedContentQueryChecker:
    def __init__(self, fixed_content: str):
        self.fixed_content = fixed_content

    def __call__(self, q: str = ""):
        if q:
            return self.fixed_content in q
        return False


checker = FixedContentQueryChecker("bar")


@app.get("/query-checker/")

from fastapi import FastAPI

app = FastAPI()


@app.get("/items/{item_id}")
async def read_item(item_id: str, q: str | None = None, short: bool = False):
    item = {"item_id": item_id}
    if q:
        item.update({"q": q})
    if not short:
        item.update(
            {"description": "This is an amazing item that has a long description"}
        )

それぞれのタグ毎にひとつの辞書を含むリストをとります。

それぞれの辞書は以下をもつことができます:

* `name` (**必須**): *path operations* および `APIRouter` の `tags` パラメーターで使用するのと同じタグ名である `str`。
* `description`: タグの簡単な説明文である `str`。 Markdownで記述でき、ドキュメントUIに表示されます。
* `externalDocs`: 外部ドキュメントを説明するための `dict`:
    * `description`: 外部ドキュメントの簡単な説明文である `str`。
    * `url` (**必須**): 外部ドキュメントのURLである `str`。

### タグのためのメタデータの作成

`users` と `items` のタグを使った例でメタデータの追加を試してみましょう。

from typing import 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 = []


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