class_docstr: Checks the status of a pipeline run.
  
  :param azure_data_factory_conn_id: The connection identifier for connecting to Azure Data Factory.
  :param run_id: The pipeline run identifier.
  :param resource_group_name: The resource group name.
  :param factory_name: The data factory name.
  :param deferrable: Run sensor in the deferrable mode.
code: def __init__(
      self,
      *,
      run_id: str,
      azure_data_factory_conn_id: str = AzureDataFactoryHook.default_conn_name,
      resource_group_name: str,
      factory_name: str,
      deferrable: bool = conf.getboolean(
          "operators", "default_deferrable", fallback=False
      ),
      **kwargs,
  ) -> None:
      super().__init__(**kwargs)
      self.azure_data_factory_conn_id = azure_data_factory_conn_id
      self.run_id = run_id
      self.resource_group_name = resource_group_name
      self.factory_name = factory_name
  
      self.deferrable = deferrable
  
file_path: airflow/airflow/providers/microsoft/azure/sensors/data_factory.py
imports: from __future__ import annotations
  from datetime import timedelta
  from functools import cached_property
  from typing import TYPE_CHECKING, Sequence
  from airflow.configuration import conf
  from airflow.exceptions import AirflowException, AirflowSkipException
  from airflow.providers.microsoft.azure.hooks.data_factory import AzureDataFactoryHook, AzureDataFactoryPipelineRunException, AzureDataFactoryPipelineRunStatus
  from airflow.providers.microsoft.azure.triggers.data_factory import ADFPipelineRunStatusSensorTrigger
  from airflow.sensors.base import BaseSensorOperator
label_desc: Use image node_id 1 to create a new AzureDataFactoryPipelineRunStatusSensor object from inherited base classes: BaseSensorOperator with example: obj = AzureDataFactoryPipelineRunStatusSensor()