Пример #1
0
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")
Пример #2
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def test_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.recognize(
            cloud_speech.RecognizeRequest(),
            config=cloud_speech.RecognitionConfig(
                encoding=cloud_speech.RecognitionConfig.AudioEncoding.LINEAR16
            ),
            audio=cloud_speech.RecognitionAudio(content=b"content_blob"),
        )
Пример #3
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def test_recognize(transport: str = "grpc",
                   request_type=cloud_speech.RecognizeRequest):
    client = SpeechClient(
        credentials=credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # 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()

        response = client.recognize(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]

        assert args[0] == cloud_speech.RecognizeRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, cloud_speech.RecognizeResponse)