tax: float | None = None
    tags: set[str] = set()
    images: list[Image] | None = None


class Offer(BaseModel):
    name: str
    description: str | None = None
    price: float
    items: list[Item]


@app.post("/offers/")
async def create_offer(offer: Offer):

    tax: Union[float, None] = None
    tags: set[str] = set()
    images: Union[list[Image], None] = None


class Offer(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    items: list[Item]


@app.post("/offers/")
async def create_offer(offer: Offer):

Google as part of the Go project.

Google hereby grants to You a perpetual, worldwide, non-exclusive,
no-charge, royalty-free, irrevocable (except as stated in this section)
patent license to make, have made, use, offer to sell, sell, import,
transfer and otherwise run, modify and propagate the contents of this
implementation of Go, where such license applies only to those patent
claims, both currently owned or controlled by Google and acquired in

import java.util.Optional;

import org.apache.maven.api.services.Lookup;
import org.apache.maven.api.services.LookupException;

import static java.util.Objects.requireNonNull;

/**
 * Proto-{@link Lookup} offer ways to provide early components to invoker.
 */
public class ProtoLookup implements Lookup {
    private final Map<Class<?>, Object> components;

    private ProtoLookup(Map<Class<?>, Object> components) {

Puedes definir modelos anidados tan profundamente como desees:

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

/// info | Información

Observa cómo `Offer` tiene una lista de `Item`s, que a su vez tienen una lista opcional de `Image`s

///

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

Você pode definir modelos profundamente aninhados de forma arbitrária:

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

/// info | Informação

Observe como `Offer` tem uma lista de `Item`s, que por sua vez têm uma lista opcional de `Image`s

///

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

Sie können beliebig tief verschachtelte Modelle definieren:

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

/// info | Info

Beachten Sie, wie `Offer` eine Liste von `Item`s hat, die ihrerseits eine optionale Liste von `Image`s haben.

///

## Bodys aus reinen Listen { #bodies-of-pure-lists }

## Deeply nested models { #deeply-nested-models }

You can define arbitrarily deeply nested models:

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

/// info

Notice how `Offer` has a list of `Item`s, which in turn have an optional list of `Image`s

///

## Bodies of pure lists { #bodies-of-pure-lists }

`images` 키가 어떻게 이미지 객체 리스트를 갖는지 주목하세요.

///

## 깊게 중첩된 모델

단독으로 깊게 중첩된 모델을 정의할 수 있습니다:

{* ../../docs_src/body_nested_models/tutorial007.py hl[9,14,20,23,27] *}

/// 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

/// info

请注意 `images` 键现在具有一组 image 对象是如何发生的。

///

## 深度嵌套模型

你可以定义任意深度的嵌套模型：

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

/// 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]
```