extra.put("reloadable_ja_stop", JapaneseStopTokenFilterFactory::new);
        extra.put("kanji_number", KanjiNumberFilterFactory::new);
        extra.put("kuromoji_pos_concat", PosConcatenationFilterFactory::new);
        extra.put("char_type", CharTypeFilterFactory::new);
        extra.put("number_concat", NumberConcatenationFilterFactory::new);

            # TODO: remove when deprecating Pydantic v1
            {
                "detail": [
                    {
                        "type": "value_error.extra",
                        "loc": ["cookie", "extra"],
                        "msg": "extra fields not permitted",
                    }
                ]
            }
        )
    )


def test_openapi_schema(client: TestClient):

</div>

## Forbid Extra Form Fields

In some special use cases (probably not very common), you might want to **restrict** the form fields to only those declared in the Pydantic model. And **forbid** any **extra** fields.

/// note

This is supported since FastAPI version `0.114.0`. 🤓

///

You can use Pydantic's model configuration to `forbid` any `extra` fields:

//// tab | Python 3.9+

        "/login/", data={"username": "Foo", "password": "secret", "extra": "extra"}
    )
    assert response.status_code == 422
    assert response.json() == {
        "detail": [
            {
                "type": "extra_forbidden",
                "loc": ["body", "extra"],
                "msg": "Extra inputs are not permitted",
                "input": "extra",
            }
        ]
    }


@needs_pydanticv2

///

## Add extra information

You can declare extra information in `Field`, `Query`, `Body`, etc. And it will be included in the generated JSON Schema.

You will learn more about adding extra information later in the docs, when learning to declare examples.

/// warning

Extra keys passed to `Field` will also be present in the resulting OpenAPI schema for your application.

        "parameters": [
            {
                "required": False,
                "schema": {"title": "Extra Param 1"},
                "name": "extra_param_1",
                "in": "query",
            },
            {
                "required": True,
                "schema": {"title": "Extra Param 2"},
                "name": "extra_param_2",
                "in": "query",
            },
        ]
    },

        deprecated: Union[deprecated, str, bool, None] = None,
        include_in_schema: bool = True,
        json_schema_extra: Union[Dict[str, Any], None] = None,
        **extra: Any,
    ):
        if example is not _Unset:
            warnings.warn(
                "`example` has been deprecated, please use `examples` instead",
                category=DeprecationWarning,

Dessa forma, seu esquema aparecerá na interface de documentação da API:

<img src="/img/tutorial/dataclasses/image01.png">

## Dataclasses em Estruturas de Dados Aninhadas

Você também pode combinar `dataclasses` com outras anotações de tipo para criar estruturas de dados aninhadas.

Em alguns casos, você ainda pode ter que usar a versão do Pydantic das `dataclasses`. Por exemplo, se você tiver erros com a documentação da API gerada automaticamente.

            Any additional JSON schema data.
            """
        ),
    ] = None,
    **extra: Annotated[
        Any,
        Doc(
            """
            Include extra fields used by the JSON Schema.
            """
        ),
        deprecated(
            """
            The `extra` kwargs is deprecated. Use `json_schema_extra` instead.
            """
        ),
    ],
) -> Any:

        "/login/", data={"username": "Foo", "password": "secret", "extra": "extra"}
    )
    assert response.status_code == 422
    assert response.json() == {
        "detail": [
            {
                "type": "extra_forbidden",
                "loc": ["body", "extra"],
                "msg": "Extra inputs are not permitted",
                "input": "extra",
            }
        ]
    }


@needs_pydanticv2