```Python
UserInDB(
    username = user_dict["username"],
    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```

#### Ein Pydantic-Modell aus den Inhalten eines anderen erstellen.

Da wir in obigem Beispiel `user_dict` mittels `user_in.dict()` erzeugt haben, ist dieser Code:

```Python
user_dict = user_in.dict()
UserInDB(**user_dict)
```

そして呼び出すと:

```Python
print(user_dict)
```

以下のようなPythonの`dict`を得ることができます:

```Python
{
    'username': 'john',
    'password': 'secret',
    'email': '******@****.***',
    'full_name': None,
}
```

#### `dict`の展開

`user_dict`のような`dict`を受け取り、それを`**user_dict`を持つ関数（またはクラス）に渡すと、Pythonはそれを「展開」します。これは`user_dict`のキーと値を直接キー・バリューの引数として渡します。

そこで上述の`user_dict`の続きを以下のように書くと:

)
```

或更精准，直接把可能会用到的内容与 `user_dict` 一起使用：

```Python
UserInDB(
    username = user_dict["username"],
    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```

#### 用其它模型中的内容生成 Pydantic 模型

上例中 ，从 `user_in.dict()` 中得到了 `user_dict`，下面的代码：

```Python
user_dict = user_in.dict()
UserInDB(**user_dict)
```

等效于：

    if license_info:
        info["license"] = license_info
    output: Dict[str, Any] = {"openapi": openapi_version, "info": info}
    if servers:
        output["servers"] = servers
    components: Dict[str, Dict[str, Any]] = {}
    paths: Dict[str, Dict[str, Any]] = {}
    webhook_paths: Dict[str, Dict[str, Any]] = {}
    operation_ids: Set[str] = set()

import types
from enum import Enum
from typing import Any, Callable, Dict, Set, Type, TypeVar, Union

from pydantic import BaseModel

DecoratedCallable = TypeVar("DecoratedCallable", bound=Callable[..., Any])
UnionType = getattr(types, "UnionType", Union)
ModelNameMap = Dict[Union[Type[BaseModel], Type[Enum]], str]

In diesen Fällen können Sie die Python-Technik zum „Entpacken“ eines `dict`s mit `**dict_to_unpack` verwenden:

```Python
old_dict = {
    "old key": "old value",
    "second old key": "second old value",
}
new_dict = {**old_dict, "new key": "new value"}
```

Hier wird `new_dict` alle Schlüssel-Wert-Paare von `old_dict` plus das neue Schlüssel-Wert-Paar enthalten:

```Python
{

For those cases, you can use the Python technique of "unpacking" a `dict` with `**dict_to_unpack`:

```Python
old_dict = {
    "old key": "old value",
    "second old key": "second old value",
}
new_dict = {**old_dict, "new key": "new value"}
```

Here, `new_dict` will contain all the key-value pairs from `old_dict` plus the new key-value pair:

```Python
{
    "old key": "old value",

### 关于 `{**note.dict(), "id": last_record_id}`

`note` 是 Pydantic `Note` 对象：

`note.dict()` 返回包含如下数据的**字典**：

```Python
{
    "text": "Some note",
    "completed": False,
}
```

但它不包含 `id` 字段。

因此要新建一个包含 `note.dict()` 键值对的**字典**：

```Python
{**note.dict()}
```

`**note.dict()` 直接**解包**键值对， 因此，`{**note.dict()}` 是 `note.dict()` 的副本。

        # removed or not.
    else:
        dist_path = site_path / lang
        shutil.rmtree(dist_path, ignore_errors=True)
    current_dir = os.getcwd()
    os.chdir(lang_path)
    shutil.rmtree(build_site_dist_path, ignore_errors=True)
    subprocess.run(["mkdocs", "build", "--site-dir", build_site_dist_path], check=True)
    shutil.copytree(build_site_dist_path, dist_path, dirs_exist_ok=True)
    os.chdir(current_dir)

* A variável `items_s` é um `set`, e cada um de seus itens é do tipo `bytes`.

#### `Dict`

Para definir um `dict`, você passa 2 parâmetros de tipo, separados por vírgulas.

O primeiro parâmetro de tipo é para as chaves do `dict`.

O segundo parâmetro de tipo é para os valores do `dict`:

```Python hl_lines="1 4"
{!../../../docs_src/python_types/tutorial008.py!}
```

Isso significa que: