class_docstr: Executes a data factory pipeline.
  
  .. seealso::
      For more information on how to use this operator, take a look at the guide:
      :ref:`howto/operator:AzureDataFactoryRunPipelineOperator`
  
  :param azure_data_factory_conn_id: The connection identifier for connecting to Azure Data Factory.
  :param pipeline_name: The name of the pipeline to execute.
  :param wait_for_termination: Flag to wait on a pipeline run's termination.  By default, this feature is
      enabled but could be disabled to perform an asynchronous wait for a long-running pipeline execution
      using the ``AzureDataFactoryPipelineRunSensor``.
  :param resource_group_name: The resource group name. If a value is not passed in to the operator, the
      ``AzureDataFactoryHook`` will attempt to use the resource group name provided in the corresponding
      connection.
  :param factory_name: The data factory name. If a value is not passed in to the operator, the
      ``AzureDataFactoryHook`` will attempt to use the factory name provided in the corresponding
      connection.
  :param reference_pipeline_run_id: The pipeline run identifier. If this run ID is specified the parameters
      of the specified run will be used to create a new run.
  :param is_recovery: Recovery mode flag. If recovery mode is set to `True`, the specified referenced
      pipeline run and the new run will be grouped under the same ``groupId``.
  :param start_activity_name: In recovery mode, the rerun will start from this activity. If not specified,
      all activities will run.
  :param start_from_failure: In recovery mode, if set to true, the rerun will start from failed activities.
      The property will be used only if ``start_activity_name`` is not specified.
  :param parameters: Parameters of the pipeline run. These parameters are referenced in a pipeline via
      ``@pipeline().parameters.parameterName`` and will be used only if the ``reference_pipeline_run_id`` is
      not specified.
  :param timeout: Time in seconds to wait for a pipeline to reach a terminal status for non-asynchronous
      waits. Used only if ``wait_for_termination`` is True.
  :param check_interval: Time in seconds to check on a pipeline run's status for non-asynchronous waits.
      Used only if ``wait_for_termination`` is True.
  :param deferrable: Run operator in deferrable mode.
docstr: Create and return an AzureDataFactoryHook (cached).
docstr_tok: ["Create","and","return","an","AzureDataFactoryHook","(","cached",")","."]
code: def hook(self) -> AzureDataFactoryHook:
      """Create and return an AzureDataFactoryHook (cached)."""
      return AzureDataFactoryHook(
          azure_data_factory_conn_id=self.azure_data_factory_conn_id
      )
  
imports: from __future__ import annotations
  import time
  import warnings
  from functools import cached_property
  from typing import TYPE_CHECKING, Any, Sequence
  from airflow.configuration import conf
  from airflow.exceptions import AirflowException
  from airflow.hooks.base import BaseHook
  from airflow.models import BaseOperator, BaseOperatorLink, XCom
  from airflow.providers.microsoft.azure.hooks.data_factory import AzureDataFactoryHook, AzureDataFactoryPipelineRunException, AzureDataFactoryPipelineRunStatus, get_field
  from airflow.providers.microsoft.azure.triggers.data_factory import AzureDataFactoryTrigger
  from airflow.utils.log.logging_mixin import LoggingMixin
label_desc: Use image node_id 2 for calling the AzureDataFactoryRunPipelineOperator obj's underlying member method code with example usage: obj.hook() and returns: AzureDataFactoryHook