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

seria equivalente a:

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

...porque `user_in.dict()` é um `dict`, e depois fazemos o Python "desembrulhá-lo" passando-o para UserInDB precedido por `**`.

Então, obtemos um modelo Pydantic a partir dos dados em outro modelo Pydantic.

& 🚥 👥 🤙:

```Python
print(user_dict)
```

👥 🔜 🤚 🐍 `dict` ⏮️:

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

#### 🎁 `dict`

🚥 👥 ✊ `dict` 💖 `user_dict` & 🚶‍♀️ ⚫️ 🔢 (⚖️ 🎓) ⏮️ `**user_dict`, 🐍 🔜 "🎁" ⚫️. ⚫️ 🔜 🚶‍♀️ 🔑 & 💲 `user_dict` 🔗 🔑-💲 ❌.

    schemas: Optional[Dict[str, Union[Schema, Reference]]] = None
    responses: Optional[Dict[str, Union[Response, Reference]]] = None
    parameters: Optional[Dict[str, Union[Parameter, Reference]]] = None
    examples: Optional[Dict[str, Union[Example, Reference]]] = None
    requestBodies: Optional[Dict[str, Union[RequestBody, Reference]]] = None
    headers: Optional[Dict[str, Union[Header, Reference]]] = None

    /** The path of the HTML: /admin/dict/admin_dict.jsp */
    HtmlNext path_AdminDict_AdminDictJsp = new HtmlNext("/admin/dict/admin_dict.jsp");

    /** The path of the HTML: /admin/dict/kuromoji/admin_dict_kuromoji.jsp */
    HtmlNext path_AdminDictKuromoji_AdminDictKuromojiJsp = new HtmlNext("/admin/dict/kuromoji/admin_dict_kuromoji.jsp");

    /** The path of the HTML: /admin/dict/kuromoji/admin_dict_kuromoji_details.jsp */

labels.dict_mapping_list_link=Liste
labels.dict_mapping_link_create=Neu erstellen
labels.dict_mapping_link_edit=Bearbeiten
labels.dict_mapping_link_delete=Löschen
labels.dict_mapping_link_details=Details
labels.dict_mapping_link_download=Herunterladen
labels.dict_mapping_link_upload=Hochladen
labels.dict_mapping_source=Quelle
labels.dict_mapping_target=Ziel
labels.dict_mapping_button_download=Herunterladen
labels.dict_mapping_button_upload=Hochladen

labels.dict_mapping_link_delete	=	Supprimer
labels.dict_mapping_link_details	=	Détails
labels.dict_mapping_link_download	=	Télécharger
labels.dict_mapping_link_upload	=	Envoyer
labels.dict_mapping_source	=	Source
labels.dict_mapping_target	=	Cible
labels.dict_mapping_button_download	=	Télécharger
labels.dict_mapping_button_upload	=	Envoyer
labels.dict_mapping_file	=	Mapping File
labels.dict_kuromoji_configuration	=	Kuromoji List

labels.dict_synonym_link_details=Details
labels.dict_synonym_link_download=Download
labels.dict_synonym_link_upload=Upload
labels.dict_synonym_source=Source
labels.dict_synonym_target=Target
labels.dict_synonym_button_download=Download
labels.dict_synonym_button_upload=Upload
labels.dict_synonym_file=Synonym File
labels.dict_mapping_configuration=Mapping List
labels.dict_mapping_title=Mapping List

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

будет равнозначен такому:

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

...потому что `user_in.dict()` - это `dict`, и затем мы указываем, чтобы Python его "распаковал", когда передаём его в `UserInDB` и ставим перед ним `**`.

    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```

#### A Pydantic model from the contents of another

As in the example above we got `user_dict` from `user_in.dict()`, this code:

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

would be equivalent to:

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

    SecretStr: str,
    set: list,
    UUID: str,
    Url: str,
    AnyUrl: str,
}


def generate_encoders_by_class_tuples(
    type_encoder_map: Dict[Any, Callable[[Any], Any]],
) -> Dict[Callable[[Any], Any], Tuple[Any, ...]]:
    encoders_by_class_tuples: Dict[Callable[[Any], Any], Tuple[Any, ...]] = defaultdict(
        tuple
    )
    for type_, encoder in type_encoder_map.items():