E `Field` do Pydantic retorna uma instância de `FieldInfo` também.

    `Body` também retorna objetos de uma subclasse de `FieldInfo` diretamente. E tem outras que você verá mais tarde que são subclasses da classe `Body`.

    Actually, `Query`, `Path` and others you'll see next create objects of subclasses of a common `Param` class, which is itself a subclass of Pydantic's `FieldInfo` class.

    And Pydantic's `Field` returns an instance of `FieldInfo` as well.

    `Body` also returns objects of a subclass of `FieldInfo` directly. And there are others you will see later that are subclasses of the `Body` class.

This simple case is handled automatically by FastAPI because the return type annotation is the class (or a subclass) of `Response`.

And tools will also be happy because both `RedirectResponse` and `JSONResponse` are subclasses of `Response`, so the type annotation is correct.

### Annotate a Response Subclass

You can also use a subclass of `Response` in the type annotation:

```Python hl_lines="8-9"

Esto puede ser útil, por ejemplo, para devolver cookies o headers personalizados.

## Devolver una `Response`

De hecho, puedes devolver cualquier `Response` o cualquier subclase de la misma.

!!! tip "Consejo"
    `JSONResponse` en sí misma es una subclase de `Response`.

Y cuando devuelves una `Response`, **FastAPI** la pasará directamente.

    as a dependency. All other OAuth2 classes inherit from it and customize it for
    each OAuth2 flow.

    You normally would not create a new class inheriting from it but use one of the
    existing subclasses, and maybe compose them if you want to support multiple flows.

    Read more about it in the
    [FastAPI docs for Security](https://fastapi.tiangolo.com/tutorial/security/).
    """

    def __init__(

* Decompressing gzip-compressed request bodies.
* Automatically logging all request bodies.

## Handling custom request body encodings

Let's see how to make use of a custom `Request` subclass to decompress gzip requests.

And an `APIRoute` subclass to use that custom request class.

### Create a custom `GzipRequest` class

!!! tip

### `UserInDB` model

Now, let's create a `UserInDB` model.

This will have the data that is actually stored in the database.

We don't create it as a subclass of Pydantic's `BaseModel` but as a subclass of our own `User`, because it will have all the attributes in `User` plus a couple more:

```Python hl_lines="31-33"
{!../../../docs_src/nosql_databases/tutorial001.py!}
```

!!! note

avoids/fixes a potential security issue: as the returned object is passed directly to Pydantic, if the returned object was a subclass of the `response_model` (e.g. you return a `UserInDB` that inherits from `User` but contains extra fields, like `hashed_password`, and `User` is used in the `response_model`), it would still pass the validation (because `UserInDB` is a subclass of `User`) and the object would be returned as-is, including the `hashed_password`. To fix this, the declared `response_model`...

And these models are all sharing a lot of the data and duplicating attribute names and types.

We could do better.

We can declare a `UserBase` model that serves as a base for our other models. And then we can make subclasses of that model that inherit its attributes (type declarations, validation, etc).

All the data conversion, validation, documentation, etc. will still work as normally.

```

### `RequestValidationError` vs `ValidationError`

!!! warning "Aviso"
    Você pode pular estes detalhes técnicos caso eles não sejam importantes para você neste momento.

`RequestValidationError` é uma subclasse do <a href="https://docs.pydantic.dev/latest/#error-handling" class="external-link" target="_blank">`ValidationError`</a> existente no Pydantic.