background: currentColor;
  -webkit-mask-image: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 24 24' fill='none' stroke='currentColor' stroke-width='2.5' stroke-linecap='round' stroke-linejoin='round'%3E%3Crect x='3' y='7' width='14' height='14' rx='2'/%3E%3Cpath d='M7 3h14v14'/%3E%3C/svg%3E");
  -webkit-mask-size: contain;
  -webkit-mask-repeat: no-repeat;

        }
    ]
}
```

/// info

注意 `images` 鍵現在是一個由 image 物件組成的列表。

///

## 深度巢狀模型 { #deeply-nested-models }

你可以定義任意深度的巢狀模型：

{* ../../docs_src/body_nested_models/tutorial007_py310.py hl[7,12,18,21,25] *}

/// info

請注意，`Offer` 具有一個 `Item` 的列表，而每個 `Item` 又有一個可選的 `Image` 列表。

///

## 純列表的本文 { #bodies-of-pure-lists }

  private static final String IMGUR_CLIENT_ID = "9199fdef135c122";
  private static final MediaType MEDIA_TYPE_PNG = MediaType.get("image/png");

  private final OkHttpClient client = new OkHttpClient();

  public void run() throws Exception {
    // Use the imgur image upload API as documented at https://api.imgur.com/endpoints/image
    final ProgressListener progressListener = new ProgressListener() {
      boolean firstUpdate = true;

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:

                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;
        }

   * are inclusive). For example, to match any lowercase letter of the English alphabet, use {@code
   * CharMatcher.inRange('a', 'z')}.
   *
   * @throws IllegalArgumentException if {@code endInclusive < startInclusive}
   */
  public static CharMatcher inRange(char startInclusive, char endInclusive) {
    return new InRange(startInclusive, endInclusive);
  }

  /**

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

from fastapi import FastAPI
from pydantic import BaseModel, HttpUrl

app = FastAPI()


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


@app.post("/images/multiple/")
async def create_multiple_images(images: list[Image]):