def analyze_entity_sentiment( self, request: language_service.AnalyzeEntitySentimentRequest = None, *, document: language_service.Document = None, encoding_type: language_service.EncodingType = None, retry: retries.Retry = gapic_v1.method.DEFAULT, timeout: float = None, metadata: Sequence[Tuple[str, str]] = (), ) -> language_service.AnalyzeEntitySentimentResponse: r"""Finds entities, similar to [AnalyzeEntities][google.cloud.language.v1beta2.LanguageService.AnalyzeEntities] in the text and analyzes sentiment associated with each entity and its mentions. Args: request (google.cloud.language_v1beta2.types.AnalyzeEntitySentimentRequest): The request object. The entity-level sentiment analysis request message. document (google.cloud.language_v1beta2.types.Document): Required. Input document. This corresponds to the ``document`` field on the ``request`` instance; if ``request`` is provided, this should not be set. encoding_type (google.cloud.language_v1beta2.types.EncodingType): The encoding type used by the API to calculate offsets. This corresponds to the ``encoding_type`` field on the ``request`` instance; if ``request`` is provided, this should not be set. retry (google.api_core.retry.Retry): Designation of what errors, if any, should be retried. timeout (float): The timeout for this request. metadata (Sequence[Tuple[str, str]]): Strings which should be sent along with the request as metadata. Returns: google.cloud.language_v1beta2.types.AnalyzeEntitySentimentResponse: The entity-level sentiment analysis response message. """ # Create or coerce a protobuf request object. # Sanity check: If we got a request object, we should *not* have # gotten any keyword arguments that map to the request. has_flattened_params = any([document, encoding_type]) if request is not None and has_flattened_params: raise ValueError("If the `request` argument is set, then none of " "the individual field arguments should be set.") # Minor optimization to avoid making a copy if the user passes # in a language_service.AnalyzeEntitySentimentRequest. # There's no risk of modifying the input as we've already verified # there are no flattened fields. if not isinstance(request, language_service.AnalyzeEntitySentimentRequest): request = language_service.AnalyzeEntitySentimentRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if document is not None: request.document = document if encoding_type is not None: request.encoding_type = encoding_type # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[ self._transport.analyze_entity_sentiment] # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response
async def analyze_entity_sentiment( self, request: language_service.AnalyzeEntitySentimentRequest = None, *, document: language_service.Document = None, encoding_type: language_service.EncodingType = None, retry: retries.Retry = gapic_v1.method.DEFAULT, timeout: float = None, metadata: Sequence[Tuple[str, str]] = (), ) -> language_service.AnalyzeEntitySentimentResponse: r"""Finds entities, similar to [AnalyzeEntities][google.cloud.language.v1beta2.LanguageService.AnalyzeEntities] in the text and analyzes sentiment associated with each entity and its mentions. Args: request (:class:`google.cloud.language_v1beta2.types.AnalyzeEntitySentimentRequest`): The request object. The entity-level sentiment analysis request message. document (:class:`google.cloud.language_v1beta2.types.Document`): Required. Input document. This corresponds to the ``document`` field on the ``request`` instance; if ``request`` is provided, this should not be set. encoding_type (:class:`google.cloud.language_v1beta2.types.EncodingType`): The encoding type used by the API to calculate offsets. This corresponds to the ``encoding_type`` field on the ``request`` instance; if ``request`` is provided, this should not be set. retry (google.api_core.retry.Retry): Designation of what errors, if any, should be retried. timeout (float): The timeout for this request. metadata (Sequence[Tuple[str, str]]): Strings which should be sent along with the request as metadata. Returns: google.cloud.language_v1beta2.types.AnalyzeEntitySentimentResponse: The entity-level sentiment analysis response message. """ # Create or coerce a protobuf request object. # Sanity check: If we got a request object, we should *not* have # gotten any keyword arguments that map to the request. has_flattened_params = any([document, encoding_type]) if request is not None and has_flattened_params: raise ValueError( "If the `request` argument is set, then none of " "the individual field arguments should be set." ) request = language_service.AnalyzeEntitySentimentRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if document is not None: request.document = document if encoding_type is not None: request.encoding_type = encoding_type # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = gapic_v1.method_async.wrap_method( self._client._transport.analyze_entity_sentiment, default_retry=retries.Retry( initial=0.1, maximum=60.0, multiplier=1.3, predicate=retries.if_exception_type( core_exceptions.DeadlineExceeded, core_exceptions.ServiceUnavailable, ), deadline=600.0, ), default_timeout=600.0, client_info=DEFAULT_CLIENT_INFO, ) # Send the request. response = await rpc(request, retry=retry, timeout=timeout, metadata=metadata,) # Done; return the response. return response