description: High Performance Object Storage
    digest: 25fa2740480d1ebc9e64340854a6c42d3a7bc39c2a77378da91b21f144faa9af
    home: https://min.io
    icon: https://min.io/resources/img/logo/MINIO_wordmark.png
    keywords:
    - minio
    - storage
    - object-storage
    - s3
    - cluster
    maintainers:
    - email: ******@****.***
      name: MinIO, Inc
    name: minio
    sources:

apiVersion: v1
description: High Performance Object Storage
name: minio
version: 5.4.0
appVersion: RELEASE.2024-12-18T13-15-44Z
keywords:
  - minio
  - storage
  - object-storage
  - s3
  - cluster
home: https://min.io
icon: https://min.io/resources/img/logo/MINIO_wordmark.png
sources:
- https://github.com/minio/minio
maintainers:
- name: MinIO, Inc

identifiers:
repository-code: 'https://github.com/fastapi/fastapi'
url: 'https://fastapi.tiangolo.com'
abstract: >-
  FastAPI framework, high performance, easy to learn, fast to code,
  ready for production
keywords:
  - fastapi
  - pydantic
  - starlette

So, we get a Pydantic model from the data in another Pydantic model.

#### Unpacking a `dict` and extra keywords { #unpacking-a-dict-and-extra-keywords }

And then adding the extra keyword argument `hashed_password=hashed_password`, like in:

```Python
UserInDB(**user_in.model_dump(), hashed_password=hashed_password)
```

...ends up being like:

     * those keywords are replaced by, for example, the actual timestamp.
     *
     * @see ArtifactCoordinates#getVersionConstraint()
     */
    @Nonnull
    Version getVersion();

    /**
     * {@return the version or meta-version of the artifact}.
     * A meta-version is a version suffixed with the {@code SNAPSHOT} keyword.

- AWS S3's [reserved keywords](https://docs.aws.amazon.com/AmazonS3/latest/dev/s3-glacier-select-sql-reference-keyword-list.html) list is not yet respected.

Así, obtenemos un modelo Pydantic a partir de los datos en otro modelo Pydantic.

#### Desempaquetando un `dict` y palabras clave adicionales { #unpacking-a-dict-and-extra-keywords }

Y luego agregando el argumento de palabra clave adicional `hashed_password=hashed_password`, como en:

```Python
UserInDB(**user_in.dict(), hashed_password=hashed_password)
```

...termina siendo como:

Auf diese Weise erhalten wir ein Pydantic-Modell aus den Daten eines anderen Pydantic-Modells.

#### Ein `dict` entpacken und zusätzliche Schlüsselwort-Argumente { #unpacking-a-dict-and-extra-keywords }

Und dann fügen wir das zusätzliche Schlüsselwort-Argument `hashed_password=hashed_password` hinzu, wie in:

```Python
UserInDB(**user_in.model_dump(), hashed_password=hashed_password)
```

Таким образом мы получаем Pydantic-модель на основе данных из другой Pydantic-модели.

#### Распаковка `dict` и дополнительные именованные аргументы { #unpacking-a-dict-and-extra-keywords }

И затем, если мы добавим дополнительный именованный аргумент `hashed_password=hashed_password` как здесь:

```Python
UserInDB(**user_in.dict(), hashed_password=hashed_password)
```

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

#### Desembrulhando um `dict` e palavras-chave extras { #unpacking-a-dict-and-extra-keywords }

E, então, adicionando o argumento de palavra-chave extra `hashed_password=hashed_password`, como em:

```Python
UserInDB(**user_in.dict(), hashed_password=hashed_password)
```

...acaba sendo como: