def test_synthesize_speech_flattened():
client = TextToSpeechClient(credentials=credentials.AnonymousCredentials())
# Mock the actual call within the gRPC stub, and fake the request.
with mock.patch.object(
type(client._transport.synthesize_speech), "__call__"
) as call:
# Designate an appropriate return value for the call.
call.return_value = cloud_tts.SynthesizeSpeechResponse()
# Call the method with a truthy value for each flattened field,
# using the keyword arguments to the method.
response = client.synthesize_speech(
input=cloud_tts.SynthesisInput(text="text_value"),
voice=cloud_tts.VoiceSelectionParams(language_code="language_code_value"),
audio_config=cloud_tts.AudioConfig(
audio_encoding=cloud_tts.AudioEncoding.LINEAR16
),
)
# 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].input == cloud_tts.SynthesisInput(text="text_value")
assert args[0].voice == cloud_tts.VoiceSelectionParams(
language_code="language_code_value"
)
assert args[0].audio_config == cloud_tts.AudioConfig(
audio_encoding=cloud_tts.AudioEncoding.LINEAR16
)
def test_synthesize_speech_flattened_error():
client = TextToSpeechClient(credentials=credentials.AnonymousCredentials())
# Attempting to call a method with both a request object and flattened
# fields is an error.
with pytest.raises(ValueError):
client.synthesize_speech(
cloud_tts.SynthesizeSpeechRequest(),
input=cloud_tts.SynthesisInput(text="text_value"),
voice=cloud_tts.VoiceSelectionParams(language_code="language_code_value"),
audio_config=cloud_tts.AudioConfig(
audio_encoding=cloud_tts.AudioEncoding.LINEAR16
),
)