'full_name': None,
}
```

#### Desembrulhando um `dict`

Se tomarmos um `dict` como `user_dict` e passarmos para uma função (ou classe) com `**user_dict`, o Python irá "desembrulhá-lo". Ele passará as chaves e valores do `user_dict` diretamente como argumentos chave-valor.

Então, continuando com o `user_dict` acima, escrevendo:

```Python
UserInDB(**user_dict)
```

Resultaria em algo equivalente a:

```Python

    title: Biosecurity risk assessments made easy.
    img: https://fastapi.tiangolo.com/img/sponsors/exoflare.png
  # - url: https://testdriven.io/courses/tdd-fastapi/
  #   title: Learn to build high-quality web apps with best practices
  #   img: https://fastapi.tiangolo.com/img/sponsors/testdriven.svg

Learn more about the
[TensorFlow Community](https://www.tensorflow.org/community) and how to
[Contribute](https://www.tensorflow.org/community/contribute).

## Courses

* [Coursera](https://www.coursera.org/search?query=TensorFlow)
* [Udacity](https://www.udacity.com/courses/all?search=TensorFlow)
* [Edx](https://www.edx.org/search?q=TensorFlow)

## License

import jcifs.smb.SmbFile;
import jcifs.smb.SmbNamedPipe;
import jcifs.smb.SmbTransportPoolImpl;

/**
 * Base implementation of CIFS context providing core functionality for SMB operations.
 * This class serves as the foundation for context implementations in the jCIFS library.
 *
 * @author mbechler
 */
public class BaseContext extends AbstractCIFSContext {

    private final Configuration config;

Puedes declarar los `examples` específicos de OpenAPI en FastAPI con el parámetro `openapi_examples` para:

* `Path()`
* `Query()`
* `Header()`
* `Cookie()`
* `Body()`
* `Form()`
* `File()`

Las claves del `dict` identifican cada ejemplo, y cada valor es otro `dict`.

Cada `dict` específico del ejemplo en los `examples` puede contener:

* `summary`: Descripción corta del ejemplo.

        V42
    }

    /**
     * Gets the identifier of the model from which the problem originated. The identifier is derived from the
     * information that is available at the point the problem occurs and as such merely serves as best effort
     * to provide information to the user to track the problem back to its origin.
     *
     * @return The identifier of the model from which the problem originated or an empty string if unknown, never

Ostatnia ankieta <abbr title="coroczna ankieta przeprowadza w środowisku programistów języka Python">Python developer survey</abbr> jasno wskazuje, że <a href="https://www.jetbrains.com/research/python-developers-survey-2017/#tools-and-features" class="external-link" target="_blank">najczęściej używaną funkcjonalnością jest autouzupełnianie w edytorze</a>.

Neste caso, o **FastAPI** perceberá que existe mais de um parâmetro de corpo na função (dois parâmetros que são modelos Pydantic).

Então, ele usará o nome dos parâmetros como chaves (nome dos campos) no corpo, e espera um corpo como:

```JSON
{
    "item": {
        "name": "Foo",
        "description": "The pretender",
        "price": 42.0,
        "tax": 3.2
    },
    "user": {

En este caso, **FastAPI** notará que hay más de un parámetro del cuerpo en la función (hay dos parámetros que son modelos de Pydantic).

Entonces, usará los nombres de los parámetros como claves (nombres de campo) en el cuerpo, y esperará un cuerpo como:

```JSON
{
    "item": {
        "name": "Foo",
        "description": "The pretender",
        "price": 42.0,
        "tax": 3.2
    },

FastAPI CLI takes the path to your Python program (e.g. `main.py`) and automatically detects the `FastAPI` instance (commonly named `app`), determines the correct import process, and then serves it.

For production you would use `fastapi run` instead. 🚀