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"), )