///

## 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
images: List[Image]
```

이를 아래처럼:

# Finally: Run your script of choice.
#   If you've clicked on a test result from our CI (via a dashboard or GitHub link),
#   click to "Invocation Details" and find BUILD_CONFIG, which will contain a
#   "build_file" item that indicates the script used.
ci/official/wheel.sh

# Advanced: Select specific build/test targets with "any.sh".
# TF_ANY_TARGETS=":your/target" TF_ANY_MODE="test" ci/official/any.sh

                            final List<RequestParameter> result = new ArrayList<>();
                            for (Object item : list) {
                                if (item instanceof List<?> pair) {
                                    if (pair.size() == 2 && pair.get(0) instanceof String name

    list.set(0, 4.0);
    assertThat(newArray).isEqualTo(new double[] {0.0, 1.0, 2.0});
    newArray[1] = 5.0;
    assertThat((double) list.get(1)).isEqualTo(1.0);
  }

  // This test stems from a real bug found by andrewk
  public void testAsList_subList_toArray_roundTrip() {
    double[] array = {0.0, 1.0, 2.0, 3.0};
    List<Double> list = Doubles.asList(array);

        if (node.hasChildNodes()) {
            final NodeList nodeList = node.getChildNodes();
            for (int i = 0; i < nodeList.getLength(); i++) {
                final Node childNode = nodeList.item(i);
                parseTextContent(childNode, buf);
            }
        } else if (node.getNodeType() == Node.TEXT_NODE) {
            final String value = node.getTextContent();
            if (value != null) {

### Validação

* Validação para a maioria dos (ou todos?) **tipos de dados** do Python, incluindo:
    * objetos JSON (`dict`).
    * arrays JSON (`list`), definindo tipos dos itens.
    * campos String (`str`), definindo tamanho mínimo e máximo.
    * Numbers (`int`, `float`) com valores mínimos e máximos, etc.

* Validação de tipos mais exóticos, como:
    * URL.
    * Email.
    * UUID.

 *
 * <p>Advantages compared to {@code long[]}:
 *
 * <ul>
 *   <li>All the many well-known advantages of immutability (read <i>Effective Java</i>, third
 *       edition, Item 17).
 *   <li>Has the value-based (not identity-based) {@link #equals}, {@link #hashCode}, and {@link
 *       #toString} behavior you expect.

 *
 * <p>Advantages compared to {@code int[]}:
 *
 * <ul>
 *   <li>All the many well-known advantages of immutability (read <i>Effective Java</i>, third
 *       edition, Item 17).
 *   <li>Has the value-based (not identity-based) {@link #equals}, {@link #hashCode}, and {@link
 *       #toString} behavior you expect.

Hepsi varsayılan olarak **çalışıyor**.


### Doğrulama

* Neredeyse bütün (ya da hepsi?) Python **data typeları** için doğrulama, kapsadıkları:
    * JSON objeleri (`dict`).
    * JSON array (`list`) item type'ı belirtirken.
    * String (`str`) parametresi, minimum ve maksimum uzunluk gibi sınırlandırmalar yaparken.
    * Numaralar (`int`, `float`) maksimum ve minimum gibi sınırlandırmalar yaparken.

But by default, it all **"just works"**.

### Validation { #validation }

* Validation for most (or all?) Python **data types**, including:
    * JSON objects (`dict`).
    * JSON array (`list`) defining item types.
    * String (`str`) fields, defining min and max lengths.
    * Numbers (`int`, `float`) with min and max values, etc.

* Validation for more exotic types, like:
    * URL.
    * Email.
    * UUID.