def analyze_entity_sentiment(self, document, encoding_type, options=None):
"""
Finds entities, similar to ``AnalyzeEntities`` in the text and analyzes
sentiment associated with each entity and its mentions.
Example:
>>> from google.cloud.gapic.language.v1beta2 import language_service_client
>>> from google.cloud.gapic.language.v1beta2 import enums
>>> from google.cloud.proto.language.v1beta2 import language_service_pb2
>>> client = language_service_client.LanguageServiceClient()
>>> document = language_service_pb2.Document()
>>> encoding_type = enums.EncodingType.NONE
>>> response = client.analyze_entity_sentiment(document, encoding_type)
Args:
document (:class:`google.cloud.proto.language.v1beta2.language_service_pb2.Document`): Input document.
encoding_type (enum :class:`google.cloud.gapic.language.v1beta2.enums.EncodingType`): The encoding type used by the API to calculate offsets.
options (:class:`google.gax.CallOptions`): Overrides the default
settings for this call, e.g, timeout, retries etc.
Returns:
A :class:`google.cloud.proto.language.v1beta2.language_service_pb2.AnalyzeEntitySentimentResponse` instance.
Raises:
:exc:`google.gax.errors.GaxError` if the RPC is aborted.
:exc:`ValueError` if the parameters are invalid.
"""
# Create the request object.
request = language_service_pb2.AnalyzeEntitySentimentRequest(
document=document, encoding_type=encoding_type)
return self._analyze_entity_sentiment(request, options)
def test_analyze_entity_sentiment(self, mock_create_stub):
# Mock gRPC layer
grpc_stub = mock.Mock()
mock_create_stub.return_value = grpc_stub
client = language_service_client.LanguageServiceClient()
# Mock request
document = language_service_pb2.Document()
encoding_type = enums.EncodingType.NONE
# Mock response
language = 'language-1613589672'
expected_response = language_service_pb2.AnalyzeEntitySentimentResponse(
language=language)
grpc_stub.AnalyzeEntitySentiment.return_value = expected_response
response = client.analyze_entity_sentiment(document, encoding_type)
self.assertEqual(expected_response, response)
grpc_stub.AnalyzeEntitySentiment.assert_called_once()
args, kwargs = grpc_stub.AnalyzeEntitySentiment.call_args
self.assertEqual(len(args), 2)
self.assertEqual(len(kwargs), 1)
self.assertIn('metadata', kwargs)
actual_request = args[0]
expected_request = language_service_pb2.AnalyzeEntitySentimentRequest(
document=document, encoding_type=encoding_type)
self.assertEqual(expected_request, actual_request)