def test_analyze_entity_sentiment(self):
        # Setup Expected Response
        language = "language-1613589672"
        expected_response = {"language": language}
        expected_response = language_service_pb2.AnalyzeEntitySentimentResponse(
            **expected_response)

        # Mock the API response
        channel = ChannelStub(responses=[expected_response])
        patch = mock.patch("google.api_core.grpc_helpers.create_channel")
        with patch as create_channel:
            create_channel.return_value = channel
            client = language_v1.LanguageServiceClient()

        # Setup Request
        document = {}

        response = client.analyze_entity_sentiment(document)
        assert expected_response == response

        assert len(channel.requests) == 1
        expected_request = language_service_pb2.AnalyzeEntitySentimentRequest(
            document=document)
        actual_request = channel.requests[0][1]
        assert expected_request == actual_request
    def analyze_entity_sentiment(self,
                                 document,
                                 encoding_type=None,
                                 options=None):
        """
        Finds entities, similar to ``AnalyzeEntities`` in the text and analyzes
        sentiment associated with each entity and its mentions.

        Example:
            >>> from google.cloud import language_v1
            >>>
            >>> client = language_v1.LanguageServiceClient()
            >>>
            >>> document = {}
            >>>
            >>> response = client.analyze_entity_sentiment(document)

        Args:
            document (Union[dict, ~google.cloud.language_v1.types.Document]): Input document.
                If a dict is provided, it must be of the same form as the protobuf
                message :class:`~google.cloud.language_v1.types.Document`
            encoding_type (~google.cloud.language_v1.types.EncodingType): The encoding type used by the API to calculate offsets.
            options (~google.gax.CallOptions): Overrides the default
                settings for this call, e.g, timeout, retries etc.

        Returns:
            A :class:`~google.cloud.language_v1.types.AnalyzeEntitySentimentResponse` instance.

        Raises:
            :exc:`google.gax.errors.GaxError` if the RPC is aborted.
            :exc:`ValueError` if the parameters are invalid.
        """
        request = language_service_pb2.AnalyzeEntitySentimentRequest(
            document=document, encoding_type=encoding_type)
        return self._analyze_entity_sentiment(request, options)
Пример #3
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    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_v1.LanguageServiceClient()

        # Mock request
        document = {}

        # Mock response
        language = 'language-1613589672'
        expected_response = {'language': language}
        expected_response = language_service_pb2.AnalyzeEntitySentimentResponse(
            **expected_response)
        grpc_stub.AnalyzeEntitySentiment.return_value = expected_response

        response = client.analyze_entity_sentiment(document)
        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)
        self.assertEqual(expected_request, actual_request)
Пример #4
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    def analyze_entity_sentiment(
            self,
            document,
            encoding_type=None,
            retry=google.api_core.gapic_v1.method.DEFAULT,
            timeout=google.api_core.gapic_v1.method.DEFAULT):
        """
        Finds entities, similar to ``AnalyzeEntities`` in the text and analyzes
        sentiment associated with each entity and its mentions.

        Example:
            >>> from google.cloud import language_v1
            >>>
            >>> client = language_v1.LanguageServiceClient()
            >>>
            >>> document = {}
            >>>
            >>> response = client.analyze_entity_sentiment(document)

        Args:
            document (Union[dict, ~google.cloud.language_v1.types.Document]): Input document.
                If a dict is provided, it must be of the same form as the protobuf
                message :class:`~google.cloud.language_v1.types.Document`
            encoding_type (~google.cloud.language_v1.types.EncodingType): The encoding type used by the API to calculate offsets.
            retry (Optional[google.api_core.retry.Retry]):  A retry object used
                to retry requests. If ``None`` is specified, requests will not
                be retried.
            timeout (Optional[float]): The amount of time, in seconds, to wait
                for the request to complete. Note that if ``retry`` is
                specified, the timeout applies to each individual attempt.

        Returns:
            A :class:`~google.cloud.language_v1.types.AnalyzeEntitySentimentResponse` instance.

        Raises:
            google.api_core.exceptions.GoogleAPICallError: If the request
                    failed for any reason.
            google.api_core.exceptions.RetryError: If the request failed due
                    to a retryable error and retry attempts failed.
            ValueError: If the parameters are invalid.
        """
        request = language_service_pb2.AnalyzeEntitySentimentRequest(
            document=document, encoding_type=encoding_type)
        return self._analyze_entity_sentiment(
            request, retry=retry, timeout=timeout)
    def test_analyze_entity_sentiment(self):
        # Setup Expected Response
        language = 'language-1613589672'
        expected_response = {'language': language}
        expected_response = language_service_pb2.AnalyzeEntitySentimentResponse(
            **expected_response)

        # Mock the API response
        channel = ChannelStub(responses=[expected_response])
        client = language_v1.LanguageServiceClient(channel=channel)

        # Setup Request
        document = {}

        response = client.analyze_entity_sentiment(document)
        assert expected_response == response

        assert len(channel.requests) == 1
        expected_request = language_service_pb2.AnalyzeEntitySentimentRequest(
            document=document)
        actual_request = channel.requests[0][1]
        assert expected_request == actual_request
    def analyze_entity_sentiment(
        self,
        document,
        encoding_type=None,
        retry=google.api_core.gapic_v1.method.DEFAULT,
        timeout=google.api_core.gapic_v1.method.DEFAULT,
        metadata=None,
    ):
        """
        Finds entities, similar to ``AnalyzeEntities`` in the text and analyzes
        sentiment associated with each entity and its mentions.

        Example:
            >>> from google.cloud import language_v1
            >>>
            >>> client = language_v1.LanguageServiceClient()
            >>>
            >>> # TODO: Initialize `document`:
            >>> document = {}
            >>>
            >>> response = client.analyze_entity_sentiment(document)

        Args:
            document (Union[dict, ~google.cloud.language_v1.types.Document]): Input document.

                If a dict is provided, it must be of the same form as the protobuf
                message :class:`~google.cloud.language_v1.types.Document`
            encoding_type (~google.cloud.language_v1.enums.EncodingType): The encoding type used by the API to calculate offsets.
            retry (Optional[google.api_core.retry.Retry]):  A retry object used
                to retry requests. If ``None`` is specified, requests will not
                be retried.
            timeout (Optional[float]): The amount of time, in seconds, to wait
                for the request to complete. Note that if ``retry`` is
                specified, the timeout applies to each individual attempt.
            metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
                that is provided to the method.

        Returns:
            A :class:`~google.cloud.language_v1.types.AnalyzeEntitySentimentResponse` instance.

        Raises:
            google.api_core.exceptions.GoogleAPICallError: If the request
                    failed for any reason.
            google.api_core.exceptions.RetryError: If the request failed due
                    to a retryable error and retry attempts failed.
            ValueError: If the parameters are invalid.
        """
        # Wrap the transport method to add retry and timeout logic.
        if "analyze_entity_sentiment" not in self._inner_api_calls:
            self._inner_api_calls[
                "analyze_entity_sentiment"] = google.api_core.gapic_v1.method.wrap_method(
                    self.transport.analyze_entity_sentiment,
                    default_retry=self.
                    _method_configs["AnalyzeEntitySentiment"].retry,
                    default_timeout=self.
                    _method_configs["AnalyzeEntitySentiment"].timeout,
                    client_info=self._client_info,
                )

        request = language_service_pb2.AnalyzeEntitySentimentRequest(
            document=document, encoding_type=encoding_type)
        return self._inner_api_calls["analyze_entity_sentiment"](
            request, retry=retry, timeout=timeout, metadata=metadata)