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"),
)
