Aleksandr Andrukhov <******@****.***> 1705057939 +0300

Kani Kim <******@****.***> 1707659311 +0900

SwftAlpc <******@****.***> 1705334896 +0900

Nils Lindemann <******@****.***> 1711821718 +0100

So, a Python class is also a **callable**.

Then, in **FastAPI**, you could use a Python class as a dependency.

What FastAPI actually checks is that it is a "callable" (function, class or anything else) and the parameters defined.

If you pass a "callable" as a dependency in **FastAPI**, it will analyze the parameters for that "callable", and process them in the same way as the parameters for a *path operation function*. Including sub-dependencies.

LeeeeT <******@****.***> 1680341164 +0300

Sebastián Ramírez <******@****.***> 1697522351 +0400

def test_response_model_no_annotation_return_invalid_dict():
    with pytest.raises(ResponseValidationError) as excinfo:
        client.get("/response_model-no_annotation-return_invalid_dict")
    assert "missing" in str(excinfo.value)


def test_response_model_no_annotation_return_invalid_model():
    with pytest.raises(ResponseValidationError) as excinfo:
        client.get("/response_model-no_annotation-return_invalid_model")

            firDiagnostic as KtPsiDiagnostic,
            token,
        )
    }
    add(FirErrors.INTERFACE_AS_FUNCTION) { firDiagnostic ->
        InterfaceAsFunctionImpl(
            firSymbolBuilder.classifierBuilder.buildClassLikeSymbol(firDiagnostic.a),
            firDiagnostic as KtPsiDiagnostic,
            token,
        )
    }
    add(FirErrors.EXPECT_CLASS_AS_FUNCTION) { firDiagnostic ->

                    <mxGeometry relative="1" as="geometry">
                        <mxPoint x="410" y="400" as="targetPoint"/>
                        <mxPoint x="585" y="1050" as="sourcePoint"/>
                        <Array as="points"/>
                    </mxGeometry>
                </mxCell>