:mod:`airflow.contrib.operators.gcp_natural_language_operator`
==============================================================

.. py:module:: airflow.contrib.operators.gcp_natural_language_operator


Module Contents
---------------

.. py:class:: CloudLanguageAnalyzeEntitiesOperator(document, encoding_type=None, retry=None, timeout=None, metadata=None, gcp_conn_id='google_cloud_default', *args, **kwargs)

   Bases: :class:`airflow.models.BaseOperator`

   Finds named entities in the text along with entity types,
   salience, mentions for each entity, and other properties.

   .. seealso::
       For more information on how to use this operator, take a look at the guide:
       :ref:`howto/operator:CloudLanguageAnalyzeEntitiesOperator`

   :param document: Input document.
       If a dict is provided, it must be of the same form as the protobuf message Document
   :type document: dict or google.cloud.language_v1.types.Document
   :param encoding_type: The encoding type used by the API to calculate offsets.
   :type encoding_type: google.cloud.language_v1.types.EncodingType
   :param retry: A retry object used to retry requests. If None is specified, requests will not be
       retried.
   :param timeout: 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.
   :type timeout: float
   :param metadata: Additional metadata that is provided to the method.
   :type metadata: seq[tuple[str, str]]]
   :param gcp_conn_id: The connection ID to use connecting to Google Cloud Platform.
   :type gcp_conn_id: str

   .. attribute:: template_fields
      :annotation: = ['document', 'gcp_conn_id']

      
   .. method:: execute(self, context)


.. py:class:: CloudLanguageAnalyzeEntitySentimentOperator(document, encoding_type=None, retry=None, timeout=None, metadata=None, gcp_conn_id='google_cloud_default', *args, **kwargs)

   Bases: :class:`airflow.models.BaseOperator`

   Finds entities, similar to AnalyzeEntities in the text and analyzes sentiment associated with each
   entity and its mentions.

   .. seealso::
       For more information on how to use this operator, take a look at the guide:
       :ref:`howto/operator:CloudLanguageAnalyzeEntitySentimentOperator`

   :param document: Input document.
       If a dict is provided, it must be of the same form as the protobuf message Document
   :type document: dict or google.cloud.language_v1.types.Document
   :param encoding_type: The encoding type used by the API to calculate offsets.
   :type encoding_type: google.cloud.language_v1.types.EncodingType
   :param retry: A retry object used to retry requests. If None is specified, requests will not be
       retried.
   :param timeout: 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.
   :type timeout: float
   :param metadata: Additional metadata that is provided to the method.
   :type metadata: seq[tuple[str, str]]]
   :rtype: google.cloud.language_v1.types.AnalyzeEntitiesResponse
   :param gcp_conn_id: The connection ID to use connecting to Google Cloud Platform.
   :type gcp_conn_id: str

   .. attribute:: template_fields
      :annotation: = ['document', 'gcp_conn_id']

      
   .. method:: execute(self, context)


.. py:class:: CloudLanguageAnalyzeSentimentOperator(document, encoding_type=None, retry=None, timeout=None, metadata=None, gcp_conn_id='google_cloud_default', *args, **kwargs)

   Bases: :class:`airflow.models.BaseOperator`

   Analyzes the sentiment of the provided text.

   .. seealso::
       For more information on how to use this operator, take a look at the guide:
       :ref:`howto/operator:CloudLanguageAnalyzeSentimentOperator`

   :param document: Input document.
       If a dict is provided, it must be of the same form as the protobuf message Document
   :type document: dict or google.cloud.language_v1.types.Document
   :param encoding_type: The encoding type used by the API to calculate offsets.
   :type encoding_type: google.cloud.language_v1.types.EncodingType
   :param retry: A retry object used to retry requests. If None is specified, requests will not be
       retried.
   :param timeout: 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.
   :type timeout: float
   :param metadata: Additional metadata that is provided to the method.
   :type metadata: sequence[tuple[str, str]]]
   :rtype: google.cloud.language_v1.types.AnalyzeEntitiesResponse
   :param gcp_conn_id: The connection ID to use connecting to Google Cloud Platform.
   :type gcp_conn_id: str

   .. attribute:: template_fields
      :annotation: = ['document', 'gcp_conn_id']

      
   .. method:: execute(self, context)


.. py:class:: CloudLanguageClassifyTextOperator(document, retry=None, timeout=None, metadata=None, gcp_conn_id='google_cloud_default', *args, **kwargs)

   Bases: :class:`airflow.models.BaseOperator`

   Classifies a document into categories.

   .. seealso::
       For more information on how to use this operator, take a look at the guide:
       :ref:`howto/operator:CloudLanguageClassifyTextOperator`

   :param document: Input document.
       If a dict is provided, it must be of the same form as the protobuf message Document
   :type document: dict or google.cloud.language_v1.types.Document
   :param retry: A retry object used to retry requests. If None is specified, requests will not be
       retried.
   :param timeout: 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.
   :type timeout: float
   :param metadata: Additional metadata that is provided to the method.
   :type metadata: sequence[tuple[str, str]]]
   :param gcp_conn_id: The connection ID to use connecting to Google Cloud Platform.
   :type gcp_conn_id: str

   .. attribute:: template_fields
      :annotation: = ['document', 'gcp_conn_id']

      
   .. method:: execute(self, context)