} else if (bodyHasUnknownEncoding(request.headers)) {
          logger.log("--> END ${request.method} (encoded body omitted)")
        } else if (requestBody.isDuplex()) {
          logger.log("--> END ${request.method} (duplex request body omitted)")
        } else if (requestBody.isOneShot()) {
          logger.log("--> END ${request.method} (one-shot body omitted)")
        } else {
          var buffer = Buffer()

		w.writeType(buf, typ.Elem())

	case *types.Struct:
		buf.WriteString("struct")

	case *types.Pointer:
		buf.WriteByte('*')
		w.writeType(buf, typ.Elem())

	case *types.Tuple:
		panic("should never see a tuple type")

	case *types.Signature:
		buf.WriteString("func")
		w.writeSignature(buf, typ)

	case *types.Interface:
		buf.WriteString("interface{")

{!> ../../docs_src/body_nested_models/tutorial002.py!}
```

### Объявление `list` с указанием типов для вложенных элементов

Объявление типов для элементов (внутренних типов) вложенных в такие типы как `list`, `dict`, `tuple`:

* Если у вас Python версии ниже чем 3.9, импортируйте их аналог из модуля `typing`
* Передайте внутренний(ие) тип(ы) как "параметры типа", используя квадратные скобки: `[` и `]`

В Python версии 3.9 это будет выглядеть так:

### typing의 `List` 임포트

먼저, 파이썬 표준 `typing` 모듈에서 `List`를 임포트합니다:

```Python hl_lines="1"
{!../../docs_src/body_nested_models/tutorial002.py!}
```

### 타입 매개변수로 `List` 선언

`list`, `dict`, `tuple`과 같은 타입 매개변수(내부 타입)를 갖는 타입을 선언하려면:

* `typing` 모듈에서 임포트
* 대괄호를 사용하여 "타입 매개변수"로 내부 타입 전달: `[` 및 `]`

```Python
from typing import List

my_list: List[str]
```

이 모든 것은 타입 선언을 위한 표준 파이썬 문법입니다.

```Python hl_lines="1"
{!> ../../docs_src/body_nested_models/tutorial002.py!}
```

### Declare a `list` with a type parameter

To declare types that have type parameters (internal types), like `list`, `dict`, `tuple`:

* If you are in a Python version lower than 3.9, import their equivalent version from the `typing` module
* Pass the internal type(s) as "type parameters" using square brackets: `[` and `]`

In Python 3.9 it would be:

    dependentSchemas: Optional[Dict[str, "SchemaOrBool"]] = None
    prefixItems: Optional[List["SchemaOrBool"]] = None
    # TODO: uncomment and remove below when deprecating Pydantic v1
    # It generales a list of schemas for tuples, before prefixItems was available
    # items: Optional["SchemaOrBool"] = None
    items: Optional[Union["SchemaOrBool", List["SchemaOrBool"]]] = None
    contains: Optional["SchemaOrBool"] = None

 *  New: `mockwebserver3.SocketPolicy` is now a sealed interface. This is one of several
    backwards-incompatible API changes that may impact early adopters of this alpha API.

 *  New: `mockwebserver3.Stream` for duplex streams.

 *  New: `mockwebserver3.MockResponseBody` for streamed response bodies.

 *  New: `mockwebserver3.MockResponse` is now immutable, with a `Builder`.

  override fun createRequestBody(
    request: Request,
    contentLength: Long,
  ): Sink {
    return when {
      request.body?.isDuplex() == true -> throw ProtocolException(
        "Duplex connections are not supported for HTTP/1",
      )
      request.isChunked -> newChunkedSink() // Stream a request body of unknown length.
      contentLength != -1L -> newKnownLengthSink() // Stream a request body of a known length.

```

////

/// tip

❕ `{"name", "description"}` ✍ `set` ⏮️ 📚 2️⃣ 💲.

⚫️ 🌓 `set(["name", "description"])`.

///

#### ⚙️ `list`Ⓜ ↩️ `set`Ⓜ

🚥 👆 💭 ⚙️ `set` & ⚙️ `list` ⚖️ `tuple` ↩️, FastAPI 🔜 🗜 ⚫️ `set` & ⚫️ 🔜 👷 ☑:

//// tab | 🐍 3️⃣.6️⃣ & 🔛

```Python hl_lines="31  37"
{!> ../../docs_src/response_model/tutorial006.py!}
```

////

### 从 typing 导入 `List`

首先，从 Python 的标准库 `typing` 模块中导入 `List`：

```Python hl_lines="1"
{!> ../../docs_src/body_nested_models/tutorial002.py!}
```

### 声明具有子类型的 List

要声明具有子类型的类型，例如 `list`、`dict`、`tuple`：

* 从 `typing` 模块导入它们
* 使用方括号 `[` 和 `]` 将子类型作为「类型参数」传入

```Python
from typing import List

my_list: List[str]
```

这完全是用于类型声明的标准 Python 语法。

对具有子类型的模型属性也使用相同的标准语法。