"/items/{item_id}",
    response_model=Item,
    responses={
        200: {
            "content": {"image/png": {}},
            "description": "Return the JSON item or an image.",
        }
    },
)
async def read_item(item_id: str, img: bool | None = None):
    if img:
        return FileResponse("image.png", media_type="image/png")
    else:

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


class Offer(BaseModel):
    name: str
    description: str | None = None

## Container Image Nedir { #what-is-a-container-image }

Bir **container**, bir **container image**'dan çalıştırılır.

  private val client = OkHttpClient()

  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",

    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)
    }
  }

---
jjbb-template: periodic-trigger-lgc.yml
vars:
  - periodic-job: elastic+elasticsearch+%BRANCH%+periodic+eql-correctness
  - lgc-job: elastic+elasticsearch+%BRANCH%+intake

---
jjbb-template: periodic-trigger-lgc.yml
vars:
  - periodic-job: elastic+elasticsearch+%BRANCH%+periodic+platform-support
  - lgc-job: elastic+elasticsearch+%BRANCH%+intake

pkg image, method (*NYCbCrA) SubImage(Rectangle) Image
pkg image, method (*NYCbCrA) YCbCrAt(int, int) color.YCbCr
pkg image, method (*NYCbCrA) YOffset(int, int) int
pkg image, type NYCbCrA struct
pkg image, type NYCbCrA struct, A []uint8
pkg image, type NYCbCrA struct, AStride int
pkg image, type NYCbCrA struct, embedded YCbCr
pkg image/color, method (NYCbCrA) RGBA() (uint32, uint32, uint32, uint32)

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


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


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


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

## Ein Docker-Image für FastAPI erstellen { #build-a-docker-image-for-fastapi }

Okay, wollen wir jetzt etwas bauen! 🚀

Ich zeige Ihnen, wie Sie ein **Docker-Image** für FastAPI **von Grund auf** erstellen, basierend auf dem **offiziellen Python**-Image.

Das ist, was Sie in **den meisten Fällen** tun möchten, zum Beispiel: