:py:mod:`astronomer.providers.microsoft.azure.triggers.data_factory`
====================================================================

.. py:module:: astronomer.providers.microsoft.azure.triggers.data_factory


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

Classes
~~~~~~~

.. autoapisummary::

   astronomer.providers.microsoft.azure.triggers.data_factory.ADFPipelineRunStatusSensorTrigger
   astronomer.providers.microsoft.azure.triggers.data_factory.AzureDataFactoryTrigger




.. py:class:: ADFPipelineRunStatusSensorTrigger(run_id, azure_data_factory_conn_id, poke_interval, resource_group_name = None, factory_name = None)

   Bases: :py:obj:`airflow.triggers.base.BaseTrigger`

   ADFPipelineRunStatusSensorTrigger is fired as deferred class with params to run the task in trigger worker, when
   ADF Pipeline is running

   :param run_id: The pipeline run identifier.
   :param azure_data_factory_conn_id: The connection identifier for connecting to Azure Data Factory.
   :param poke_interval:  polling period in seconds to check for the status
   :param resource_group_name: The resource group name.
   :param factory_name: The data factory name.

   .. py:method:: serialize()

      Serializes ADFPipelineRunStatusSensorTrigger arguments and classpath.


   .. py:method:: run()
      :async:

      Make async connection to Azure Data Factory, polls for the pipeline run status



.. py:class:: AzureDataFactoryTrigger(run_id, azure_data_factory_conn_id, end_time, resource_group_name = None, factory_name = None, wait_for_termination = True, check_interval = 60)

   Bases: :py:obj:`airflow.triggers.base.BaseTrigger`

   AzureDataFactoryTrigger is triggered when Azure data factory pipeline job succeeded or failed.
   When wait_for_termination is set to False it triggered immediately with success status

   :param run_id: Run id of a Azure data pipeline run job.
   :param azure_data_factory_conn_id: The connection identifier for connecting to Azure Data Factory.
   :param end_time: Time in seconds when triggers will timeout.
   :param resource_group_name: The resource group name.
   :param factory_name: The data factory name.
   :param wait_for_termination: Flag to wait on a pipeline run's termination.
   :param check_interval: Time in seconds to check on a pipeline run's status.

   .. py:attribute:: QUEUED
      :annotation: = Queued

      

   .. py:attribute:: IN_PROGRESS
      :annotation: = InProgress

      

   .. py:attribute:: SUCCEEDED
      :annotation: = Succeeded

      

   .. py:attribute:: FAILED
      :annotation: = Failed

      

   .. py:attribute:: CANCELING
      :annotation: = Canceling

      

   .. py:attribute:: CANCELLED
      :annotation: = Cancelled

      

   .. py:attribute:: INTERMEDIATE_STATES
      :annotation: :List[str]

      

   .. py:attribute:: FAILURE_STATES
      :annotation: :List[str]

      

   .. py:attribute:: SUCCESS_STATES
      :annotation: :List[str]

      

   .. py:attribute:: TERMINAL_STATUSES
      :annotation: :List[str]

      

   .. py:method:: serialize()

      Serializes AzureDataFactoryTrigger arguments and classpath.


   .. py:method:: run()
      :async:

      Make async connection to Azure Data Factory, polls for the pipeline run status