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

### 📣 `list` ⏮️ 🆎 🔢

📣 🆎 👈 ✔️ 🆎 🔢 (🔗 🆎), 💖 `list`, `dict`, `tuple`:

* 🚥 👆 🐍 ⏬ 🔅 🌘 3️⃣.9️⃣, 🗄 👫 🌓 ⏬ ⚪️➡️ `typing` 🕹
* 🚶‍♀️ 🔗 🆎(Ⓜ) "🆎 🔢" ⚙️ ⬜ 🗜: `[` & `]`

🐍 3️⃣.9️⃣ ⚫️ 🔜:

```Python
my_list: list[str]
```

⏬ 🐍 ⏭ 3️⃣.9️⃣, ⚫️ 🔜:

```Python

  // are executed asynchronously this must outlive the queued op, so it can't be
  // function-local to Execute.
  mutable std::unique_ptr<CancellationManager> default_cancellation_manager_;
};

// Contains a tuple of tensors, one on each of the `underlying_devices_` of the
// ParallelDevice.
class ParallelTensor {
 public:
  // Construct a ParallelTensor from TensorHandles placed on the component

   *
   * <pre>{@code
   * for (B b0 : sets.get(0)) {
   *   for (B b1 : sets.get(1)) {
   *     ...
   *     ImmutableList<B> tuple = ImmutableList.of(b0, b1, ...);
   *     // operate on tuple
   *   }
   * }
   * }</pre>
   *
   * <p>Note that if any input set is empty, the Cartesian product will also be empty. If no sets at

    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

		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:

```

////

/// 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!}
```

////

 *
 * This nesting is typical but not strict. For example, when calls use "Expect: continue" the
 * request body start and end events occur within the response header events. Similarly,
 * [duplex calls][RequestBody.isDuplex] interleave the request and response bodies.
 *
 * Since connections may be reused, the proxy selection, DNS, and connect events may not be present