Jesse Wilson <******@****.***> 1703114827 -0500

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

        final String mimeType = responseData.getMimeType();
        if (mimeType == null) {
            return true;
        }

        return switch (mimeType) {
        case "image/png", "image/gif", "image/jpeg", "image/bmp" -> true;
        default -> false;
        };
    }

    protected Result saveImage(final ImageInputStream input, final File outputFile) throws IOException {

!!! 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.

  # Pulling an already-pulled container image will finish instantly, so
  # repeating the command costs nothing.
  docker pull "$TFCI_DOCKER_IMAGE" || sleep 15
  docker pull "$TFCI_DOCKER_IMAGE" || sleep 15
  docker pull "$TFCI_DOCKER_IMAGE"
fi 

if [[ "$TFCI_DOCKER_REBUILD_ENABLE" == 1 ]]; then
  DOCKER_BUILDKIT=1 docker build --cache-from "$TFCI_DOCKER_IMAGE" -t "$TFCI_DOCKER_IMAGE" $TFCI_DOCKER_REBUILD_ARGS

## 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}.

  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),
        )

        <img class="sponsor-image" src="/img/sponsors/platform-sh-banner.png" />
      </a>
    </div>
    <div class="item">
      <a title="Deploy FastAPI on AWS with a few clicks" style="display: block; position: relative;" href="https://www.porter.run" target="_blank">
        <span class="sponsor-badge">sponsor</span>
        <img class="sponsor-image" src="/img/sponsors/porter-banner.png" />
      </a>
    </div>

    withLocale(Locale("en", "US")) {
      val mediaType = parse("IMAGE/JPEG")
      assertEquals("image", mediaType.type)
      assertEquals("jpeg", mediaType.subtype)
    }
  }

  @Test fun testTurkishDotlessIWithTrTr() {
    withLocale(Locale("tr", "TR")) {
      val mediaType = parse("IMAGE/JPEG")
      assertEquals("image", mediaType.type)
      assertEquals("jpeg", mediaType.subtype)
    }
  }

## 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+"