airflow.providers.microsoft.azure.sensors.data_factory

Module Contents

Classes

AzureDataFactoryPipelineRunStatusSensor

Checks the status of a pipeline run.
class airflow.providers.microsoft.azure.sensors.data_factory.AzureDataFactoryPipelineRunStatusSensor(*, run_id, azure_data_factory_conn_id=AzureDataFactoryHook.default_conn_name, resource_group_name, factory_name, deferrable=conf.getboolean('operators', 'default_deferrable', fallback=False), **kwargs)[source]

Bases: airflow.sensors.base.BaseSensorOperator

Checks the status of a pipeline run.

Parameters

  • azure_data_factory_conn_id (str) – The connection identifier for connecting to Azure Data Factory.

  • run_id (str) – The pipeline run identifier.

  • resource_group_name (str) – The resource group name.

  • factory_name (str) – The data factory name.

  • deferrable (bool) – Run sensor in the deferrable mode.

template_fields: Sequence[str] = ('azure_data_factory_conn_id', 'resource_group_name', 'factory_name', 'run_id')[source]
ui_color = '#50e6ff'[source]
hook()[source]

Create and return an AzureDataFactoryHook (cached).

poke(context)[source]

Override when deriving this class.

execute(context)[source]

Poll for state of the job run.

In deferrable mode, the polling is deferred to the triggerer. Otherwise the sensor waits synchronously.

execute_complete(context, event)[source]

Return immediately - callback for when the trigger fires.

Relies on trigger to throw an exception, otherwise it assumes execution was successful.

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