def endpoint(data: ParamModelV1):  # pragma: no cover
            return data


def test_raises_pydantic_v1_model_in_return_type() -> None:
    class ReturnModelV1(BaseModel):
        name: str

    app = FastAPI()

    with pytest.raises(PydanticV1NotSupportedError):

        @app.get("/return")
        def endpoint() -> ReturnModelV1:  # pragma: no cover
            return ReturnModelV1(name="test")

        "info": {"title": "FastAPI", "version": "0.1.0"},
        "paths": {
            "/no_response_model-no_annotation-return_model": {
                "get": {
                    "summary": "No Response Model No Annotation Return Model",
                    "operationId": "no_response_model_no_annotation_return_model_no_response_model_no_annotation_return_model_get",
                    "responses": {

@app.get("/sync/dict-no-response-model")
def sync_dict_no_response_model():
    return {"name": "foo", "value": 123}


@app.get("/sync/dict-with-response-model", response_model=ItemOut)
def sync_dict_with_response_model(
    dep: Annotated[int, Depends(dep_b)],
):
    return {"name": "foo", "value": 123, "dep": dep}


@app.get("/sync/model-no-response-model")

                                }
                            },
                        },
                    },
                }
            },
            "/no-duplicates": {
                "post": {
                    "summary": "No Duplicates",
                    "operationId": "no_duplicates_no_duplicates_post",
                    "requestBody": {
                        "content": {

///

## Dataclasses em `response_model` { #dataclasses-in-response-model }

Você também pode usar `dataclasses` no parâmetro `response_model`:

{* ../../docs_src/dataclasses_/tutorial002_py310.py hl[1,6:12,18] *}

A dataclass será automaticamente convertida para uma dataclass Pydantic.

Así que, incluso con el código anterior que no usa Pydantic explícitamente, FastAPI está usando Pydantic para convertir esos dataclasses estándar en su propia versión de dataclasses de Pydantic.

Y por supuesto, soporta lo mismo:

* validación de datos

    "uvicorn[standard] >=0.12.0",
    # # Settings management
    "pydantic-settings >=2.0.0",
    # # Extra Pydantic data types
    "pydantic-extra-types >=2.0.0",
]

standard-no-fastapi-cloud-cli = [
    "fastapi-cli[standard-no-fastapi-cloud-cli] >=0.0.8",
    # For the test client
    "httpx >=0.23.0,<1.0.0",
    # For templates
    "jinja2 >=3.1.5",
    # For forms and file uploads
    "python-multipart >=0.0.18",

@callback_router.get(
    "{$callback_url}/callback/", responses={400: {"model": CustomModel}}
)
def callback_route():
    pass  # pragma: no cover


@app.post("/", callbacks=callback_router.routes)
def main_route(callback_url: HttpUrl):
    pass  # pragma: no cover


client = TestClient(app)


def test_openapi_schema():
    response = client.get("/openapi.json")

    assert response.status_code == 200, response.text
    assert response.json() == {"message": "No file sent"}


def test_post_uploadfile_no_body(client: TestClient):
    response = client.post("/uploadfile/")
    assert response.status_code == 200, response.text
    assert response.json() == {"message": "No upload file sent"}


def test_post_file(tmp_path: Path, client: TestClient):
    path = tmp_path / "test.txt"

        }

        fun assertHasNoError() {
            assertTrue("Has no error (${richReport.errors})", richReport.errors.isEmpty())
        }

        fun assertHasNoWarning() {
            assertTrue("Has no warning (${richReport.warnings})", richReport.warnings.isEmpty())
        }

        fun assertHasNoInformation() {
            assertTrue("Has no information (${richReport.information})", richReport.information.isEmpty())