from fastapi import FastAPI
from pydantic import BaseModel, HttpUrl

app = FastAPI()


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


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


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

mkdocs-material==9.7.0
mdx-include >=1.4.1,<2.0.0
mkdocs-redirects>=1.2.1,<1.3.0
typer == 0.16.0
pyyaml >=5.3.1,<7.0.0
# For Material for MkDocs, Chinese search
jieba==0.42.1
# For image processing by Material for MkDocs
pillow==11.3.0
# For image processing by Material for MkDocs
cairosvg==2.8.2
mkdocstrings[python]==0.30.1
griffe-typingdoc==0.3.0
griffe-warnings-deprecated==1.1.0
# For griffe, it formats with black
black==25.1.0

                <access kind="email"></access>
                <access kind="url">http://www.taro.com/</access>
                <image file="taro.png" />
        </item>
        <item sex="male" custid="B23456">
                <name>佐藤二朗</name>
                <access kind="email">******@****.***</access>
                <image file="jiro.png" />
        </item>
        <item sex="female" custid="C34567">
                <name>田中花子</name>

}


app = FastAPI()


@app.get(
    "/items/{item_id}",
    response_model=Item,
    responses={**responses, 200: {"content": {"image/png": {}}}},
)
async def read_item(item_id: str, img: Union[bool, None] = None):
    if img:
        return FileResponse("image.png", media_type="image/png")
    else:

    when {
      file.name.endsWith(".css") -> "text/css"
      file.name.endsWith(".gif") -> "image/gif"
      file.name.endsWith(".html") -> "text/html"
      file.name.endsWith(".jpeg") -> "image/jpeg"
      file.name.endsWith(".jpg") -> "image/jpeg"
      file.name.endsWith(".js") -> "application/javascript"
      file.name.endsWith(".png") -> "image/png"
      else -> "text/plain"
    }

  private fun Socket.peerName(): String {

///

## Bodys aus reinen Listen { #bodies-of-pure-lists }

Wenn das äußerste Element des JSON-Bodys, das Sie erwarten, ein JSON-`array` (eine Python-`list`) ist, können Sie den Typ im Funktionsparameter deklarieren, mit der gleichen Syntax wie in Pydantic-Modellen:

```Python
images: list[Image]
```

so wie in:

Native Image Tests
==================

This executes OkHttp's test suite inside a Graalvm image.

Execute
-------

The native image runs JUnit 5 tests in the project.

```
./gradlew -PgraalBuild=true --info native-image-tests:nativeTest

```
.
├── app
│   └── main.py
└── Dockerfile
```

## Construire l'image Docker

* Allez dans le répertoire du projet (dans lequel se trouve votre `Dockerfile`, contenant votre répertoire `app`).
* Construisez votre image FastAPI :

<div class="termy">

```console
$ docker build -t myimage .

---> 100%
```

</div>

## Démarrer le conteneur Docker

            assertEquals("text/html", mimeMap.getMimeType("htm"));
            assertEquals("image/jpeg", mimeMap.getMimeType("jpg"));
            assertEquals("image/jpeg", mimeMap.getMimeType("jpeg"));
            assertEquals("image/gif", mimeMap.getMimeType("gif"));
            assertEquals("image/png", mimeMap.getMimeType("png"));
        }

        @Test

  mssql:
    image: '${MSSQL_IMAGE}:latest'
    ports:
      - "127.0.0.1:9930:1433"
    environment:
      - TZ=Asia/Shanghai
      - ACCEPT_EULA=Y
      - MSSQL_SA_PASSWORD=LoremIpsum86
  tidb:
    image: 'pingcap/tidb:v6.5.0'
    ports:
      - "127.0.0.1:9940:4000"
    command: /tidb-server -store unistore -path "" -lease 0s > tidb.log 2>&1 &
  gaussdb:
    image: 'opengauss/opengauss:7.0.0-RC1.B023'