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):

    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:

///

## Corpos de listas puras { #bodies-of-pure-lists }

Se o valor de primeiro nível do corpo JSON que você espera for um `array` do JSON (uma` lista` do Python), você pode declarar o tipo no parâmetro da função, da mesma forma que nos modelos do Pydantic:

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

como em:

                return false;
            }

            String mimeTypeStr = mimeType.toString();
            // Support PDF and common image formats
            return "application/pdf".equals(mimeTypeStr) || "image/jpeg".equals(mimeTypeStr) || "image/png".equals(mimeTypeStr);
        }

        @Override
        public boolean isAvailable() {
            return available;
        }

pkg image/color, type CMYK struct, K uint8
pkg image/color, type CMYK struct, M uint8
pkg image/color, type CMYK struct, Y uint8
pkg image/color, var CMYKModel Model
pkg image/gif, const DisposalBackground = 2
pkg image/gif, const DisposalBackground ideal-int
pkg image/gif, const DisposalNone = 1
pkg image/gif, const DisposalNone ideal-int
pkg image/gif, const DisposalPrevious = 3
pkg image/gif, const DisposalPrevious ideal-int

more full featured testing library such as [MockServer](https://www.mock-server.com/).

GraalVM Native Image
--------------------

Building your native images with [GraalVM] should work automatically.

See the okcurl module for an example build.

```shell
$ ./gradlew okcurl:nativeImage
$ ./okcurl/build/graal/okcurl https://httpbin.org/get

                    LOGGER.warn("Attempt {}/{} to pull Docker base image {} failed", attempt, maxAttempts, baseImage);
                }
            }

            // If we successfully ran `docker pull` above, we would have returned before this point.
            throw new GradleException("Failed to pull Docker base image [" + baseImage + "], all attempts failed");
        }

        @Override

      tags:
        - key: name
          value: pick* # match objects with tag 'name', all values starting with 'pick'
      metadata:
        - key: content-type
          value: image/* # match objects with 'content-type', all values starting with 'image/'
      size:
        lessThan: "10MiB" # match objects with size less than this value (e.g. 10MiB)
        greaterThan: 1MiB # match objects with size greater than this value (e.g. 1MiB)

///

## 컨테이너 이미지 배포하기 { #deploy-the-container-image }

컨테이너(Docker) 이미지를 만든 후에는 이를 배포하는 여러 방법이 있습니다.

예를 들어:

* 단일 서버에서 **Docker Compose**로
* **Kubernetes** 클러스터로
* Docker Swarm Mode 클러스터로
* Nomad 같은 다른 도구로
* 컨테이너 이미지를 받아 배포해주는 클라우드 서비스로

## `uv`를 사용하는 도커 이미지 { #docker-image-with-uv }