async def test_long_running_recognize_flattened_async():
    client = SpeechAsyncClient(
        credentials=credentials.AnonymousCredentials(), )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
            type(client._client._transport.long_running_recognize),
            "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam"))
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.long_running_recognize(
            config=cloud_speech.RecognitionConfig(
                encoding=cloud_speech.RecognitionConfig.AudioEncoding.LINEAR16
            ),
            audio=cloud_speech.RecognitionAudio(content=b"content_blob"),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]

        assert args[0].config == cloud_speech.RecognitionConfig(
            encoding=cloud_speech.RecognitionConfig.AudioEncoding.LINEAR16)

        assert args[0].audio == cloud_speech.RecognitionAudio(
            content=b"content_blob")
def test_recognize_flattened():
    client = SpeechClient(credentials=credentials.AnonymousCredentials(), )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client._transport.recognize),
                           "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = cloud_speech.RecognizeResponse()

        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.recognize(
            config=cloud_speech.RecognitionConfig(
                encoding=cloud_speech.RecognitionConfig.AudioEncoding.LINEAR16
            ),
            audio=cloud_speech.RecognitionAudio(content=b"content_blob"),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]

        assert args[0].config == cloud_speech.RecognitionConfig(
            encoding=cloud_speech.RecognitionConfig.AudioEncoding.LINEAR16)

        assert args[0].audio == cloud_speech.RecognitionAudio(
            content=b"content_blob")
def test_long_running_recognize_flattened_error():
    client = SpeechClient(credentials=credentials.AnonymousCredentials(), )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.long_running_recognize(
            cloud_speech.LongRunningRecognizeRequest(),
            config=cloud_speech.RecognitionConfig(
                encoding=cloud_speech.RecognitionConfig.AudioEncoding.LINEAR16
            ),
            audio=cloud_speech.RecognitionAudio(content=b"content_blob"),
        )