ARG BASE_DISTRIBUTION=debug

# Version is the base image version from the TLD Makefile
ARG BASE_VERSION=latest
ARG ISTIO_BASE_REGISTRY=gcr.io/istio-release

# The following section is used as base image if BASE_DISTRIBUTION=debug
FROM ${ISTIO_BASE_REGISTRY}/base:${BASE_VERSION} as debug

# The following section is used as base image if BASE_DISTRIBUTION=distroless

## Bodies of pure lists

If the top level value of the JSON body you expect is a JSON `array` (a Python `list`), you can declare the type in the parameter of the function, the same as in Pydantic models:

```Python
images: List[Image]
```

or in Python 3.9 and above:

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

as in:

=== "Python 3.9+"

        track: stable
    spec:
      containers:
      - image: docker.io/istio/proxy_debug:unittest
        name: istio-proxy
        resources: {}
      - image: fake.docker.io/google-samples/hello-go-gke:1.0
        name: hello
        ports:
        - containerPort: 80
          name: http
        resources: {}
      initContainers:
      - image: docker.io/istio/proxy_init:unittest-test
        name: istio-init

!!! warning
    There's a high chance that you **don't** need this base image or any other similar one, and would be better off by building the image from scratch as [described above in: Build a Docker Image for FastAPI](#build-a-docker-image-for-fastapi).

This image has an **auto-tuning** mechanism included to set the **number of worker processes** based on the CPU cores available.

{!../../../docs_src/body_nested_models/tutorial007.py!}
```

!!! info "정보"
    `Offer`가 선택사항 `Image` 리스트를 차례로 갖는 `Item` 리스트를 어떻게 가지고 있는지 주목하세요

## 순수 리스트의 본문

예상되는 JSON 본문의 최상위 값이 JSON `array`(파이썬 `list`)면, Pydantic 모델에서와 마찬가지로 함수의 매개변수에서 타입을 선언할 수 있습니다:

```Python
images: List[Image]
```

이를 아래처럼:

```Python hl_lines="15"
{!../../../docs_src/body_nested_models/tutorial008.py!}
```

mkdocs-material==9.5.18
mdx-include >=1.4.1,<2.0.0
mkdocs-redirects>=1.2.1,<1.3.0
typer >=0.12.0
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==10.3.0
# For image processing by Material for MkDocs
cairosvg==2.7.0
mkdocstrings[python]==0.24.3
griffe-typingdoc==0.2.2
# For griffe, it formats with black
black==24.3.0

## Offizielles Docker-Image mit Gunicorn – Uvicorn

Es gibt ein offizielles Docker-Image, in dem Gunicorn mit Uvicorn-Workern ausgeführt wird, wie in einem vorherigen Kapitel beschrieben: [Serverworker – Gunicorn mit Uvicorn](server-workers.md){.internal-link target=_blank}.

    {!> ../../../docs_src/body_nested_models/tutorial007.py!}
    ```

!!! info
    请注意 `Offer` 拥有一组 `Item` 而反过来 `Item` 又是一个可选的 `Image` 列表是如何发生的。

## 纯列表请求体

如果你期望的 JSON 请求体的最外层是一个 JSON `array`（即 Python `list`），则可以在路径操作函数的参数中声明此类型，就像声明 Pydantic 模型一样：

```Python
images: List[Image]
```

例如：

=== "Python 3.9+"

    ```Python hl_lines="13"

```
# Create bucket named `images` in myminio
mc mb myminio/images
# Add notification configuration on the `images` bucket using the MySQL ARN. The --suffix argument filters events.
mc event add myminio/images arn:minio:sqs::1:postgresql --suffix .jpg
# Print out the notification configuration on the `images` bucket.
mc event list myminio/images
mc event list myminio/images

  fun run() {
    // Use the imgur image upload API as documented at https://api.imgur.com/endpoints/image
    val requestBody =
      MultipartBody.Builder()
        .setType(MultipartBody.FORM)
        .addFormDataPart("title", "Square Logo")
        .addFormDataPart(
          "image",
          "logo-square.png",
          File("docs/images/logo-square.png").asRequestBody(MEDIA_TYPE_PNG),
        )