* <a href="https://hub.docker.com/_/redis" class="external-link" target="_blank">Redis</a>, etc.

By using a pre-made container image it's very easy to **combine** and use different tools. For example, to try out a new database. In most cases, you can use the **official images**, and just configure them with environment variables.

</blockquote>

## Investigação

Ao usar todas as alternativas anteriores, eu tive a chance de aprender com todas elas, aproveitar ideias e combiná-las da melhor maneira que encontrei para mim e para os times de desenvolvedores com os quais trabalhava.

Por exemplo, estava claro que idealmente ele deveria ser baseado nos _type hints_ padrões do Python.

You will get completion in code you might even consider impossible before. As for example, the `price` key inside a JSON body (that could have been nested) that comes from a request.

No more typing the wrong key names, coming back and forth between docs, or scrolling up and down to find if you finally used `username` or `user_name`.

### Short

In this case, the `status_code` used will be the default one for the `RedirectResponse`, which is `307`.

---

You can also use the `status_code` parameter combined with the `response_class` parameter:

```Python hl_lines="2  7  9"
{!../../../docs_src/custom_response/tutorial006c.py!}
```

### `StreamingResponse`

    return burgers
```

With `async def`, Python knows that, inside that function, it has to be aware of `await` expressions, and that it can "pause" ⏸ the execution of that function and go do something else 🔀 before coming back.

When you want to call an `async def` function, you have to "await" it. So, this won't work:

```Python
# This won't work, because get_burgers was defined with: async def
burgers = get_burgers(2)
```

    * Automatic and clear errors when the data is invalid.
    * Validation even for deeply nested JSON objects.
* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
    * JSON.
    * Path parameters.
    * Query parameters.
    * Cookies.
    * Headers.
    * Forms.
    * Files.

## Pydantic `Settings`

Fortunately, Pydantic provides a great utility to handle these settings coming from environment variables with <a href="https://docs.pydantic.dev/latest/usage/pydantic_settings/" class="external-link" target="_blank">Pydantic: Settings management</a>.

### Install `pydantic-settings`

!!! check "**FastAPI** inspirado para"
    Ser um microframework. Fazer ele fácil para misturar e combinar com ferramentas e partes necessárias.

    Ser simples e com sistema de roteamento fácil de usar.

### <a href="https://requests.readthedocs.io" class="external-link" target="_blank">Requests</a>

    * Automatic and clear errors when the data is invalid.
    * Validation even for deeply nested JSON objects.
* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
    * JSON.
    * Path parameters.
    * Query parameters.
    * Cookies.
    * Headers.
    * Forms.
    * Files.

!!! check "A inspiré **FastAPI** à"
Être un micro-framework. Il est donc facile de combiner les outils et les pièces nécessaires.

Proposer un système de routage simple et facile à utiliser.

### <a href="https://requests.readthedocs.io" class="external-link" target="_blank">Requests</a>