airflow.providers.microsoft.azure.hooks.data_factory¶
Spelling exceptions.
Module Contents¶
Classes¶
| Type class for the pipeline run info dictionary. | |
| Azure Data Factory pipeline operation statuses. | |
| A hook to interact with Azure Data Factory. | |
| An Async Hook that connects to Azure DataFactory to perform pipeline operations. | 
Functions¶
| 
 | Provide the targeted factory to the decorated function in case it isn't specified. | 
| 
 | Get field from extra, first checking short name, then for backcompat we check for prefixed name. | 
| Provide the targeted factory to the async decorated function in case it isn't specified. | 
Attributes¶
- airflow.providers.microsoft.azure.hooks.data_factory.provide_targeted_factory(func)[source]¶
- Provide the targeted factory to the decorated function in case it isn’t specified. - If - resource_group_nameor- factory_nameis not provided it defaults to the value specified in the connection extras.
- class airflow.providers.microsoft.azure.hooks.data_factory.PipelineRunInfo[source]¶
- Bases: - airflow.typing_compat.TypedDict- Type class for the pipeline run info dictionary. 
- class airflow.providers.microsoft.azure.hooks.data_factory.AzureDataFactoryPipelineRunStatus[source]¶
- Azure Data Factory pipeline operation statuses. 
- exception airflow.providers.microsoft.azure.hooks.data_factory.AzureDataFactoryPipelineRunException[source]¶
- Bases: - airflow.exceptions.AirflowException- An exception that indicates a pipeline run failed to complete. 
- airflow.providers.microsoft.azure.hooks.data_factory.get_field(extras, field_name, strict=False)[source]¶
- Get field from extra, first checking short name, then for backcompat we check for prefixed name. 
- class airflow.providers.microsoft.azure.hooks.data_factory.AzureDataFactoryHook(azure_data_factory_conn_id=default_conn_name)[source]¶
- Bases: - airflow.hooks.base.BaseHook- A hook to interact with Azure Data Factory. - Parameters
- azure_data_factory_conn_id (str) – The Azure Data Factory connection id. 
 - update_factory(factory, resource_group_name=None, factory_name=None, **config)[source]¶
- Update the factory. - Parameters
- Raises
- AirflowException – If the factory does not exist. 
- Returns
- The factory. 
- Return type
- azure.mgmt.datafactory.models.Factory 
 
 - create_factory(factory, resource_group_name=None, factory_name=None, **config)[source]¶
- Create the factory. - Parameters
- Raises
- AirflowException – If the factory already exists. 
- Returns
- The factory. 
- Return type
- azure.mgmt.datafactory.models.Factory 
 
 - get_linked_service(linked_service_name, resource_group_name=None, factory_name=None, **config)[source]¶
- Get the linked service. - Parameters
- Returns
- The linked service. 
- Return type
- azure.mgmt.datafactory.models.LinkedServiceResource 
 
 - update_linked_service(linked_service_name, linked_service, resource_group_name=None, factory_name=None, **config)[source]¶
- Update the linked service. - Parameters
- linked_service_name (str) – The linked service name. 
- linked_service (azure.mgmt.datafactory.models.LinkedServiceResource) – The linked service resource definition. 
- resource_group_name (str | None) – The resource group name. 
- factory_name (str | None) – The factory name. 
- config (Any) – Extra parameters for the ADF client. 
 
- Raises
- AirflowException – If the linked service does not exist. 
- Returns
- The linked service. 
- Return type
- azure.mgmt.datafactory.models.LinkedServiceResource 
 
 - create_linked_service(linked_service_name, linked_service, resource_group_name=None, factory_name=None, **config)[source]¶
- Create the linked service. - Parameters
- linked_service_name (str) – The linked service name. 
- linked_service (azure.mgmt.datafactory.models.LinkedServiceResource) – The linked service resource definition. 
- resource_group_name (str | None) – The resource group name. 
- factory_name (str | None) – The factory name. 
- config (Any) – Extra parameters for the ADF client. 
 
- Raises
- AirflowException – If the linked service already exists. 
- Returns
- The linked service. 
- Return type
- azure.mgmt.datafactory.models.LinkedServiceResource 
 
 - delete_linked_service(linked_service_name, resource_group_name=None, factory_name=None, **config)[source]¶
- Delete the linked service. 
 - get_dataset(dataset_name, resource_group_name=None, factory_name=None, **config)[source]¶
- Get the dataset. 
 - update_dataset(dataset_name, dataset, resource_group_name=None, factory_name=None, **config)[source]¶
- Update the dataset. - Parameters
- Raises
- AirflowException – If the dataset does not exist. 
- Returns
- The dataset. 
- Return type
- azure.mgmt.datafactory.models.DatasetResource 
 
 - create_dataset(dataset_name, dataset, resource_group_name=None, factory_name=None, **config)[source]¶
- Create the dataset. - Parameters
- Raises
- AirflowException – If the dataset already exists. 
- Returns
- The dataset. 
- Return type
- azure.mgmt.datafactory.models.DatasetResource 
 
 - delete_dataset(dataset_name, resource_group_name=None, factory_name=None, **config)[source]¶
- Delete the dataset. 
 - get_dataflow(dataflow_name, resource_group_name=None, factory_name=None, **config)[source]¶
- Get the dataflow. 
 - update_dataflow(dataflow_name, dataflow, resource_group_name=None, factory_name=None, **config)[source]¶
- Update the dataflow. - Parameters
- Raises
- AirflowException – If the dataset does not exist. 
- Returns
- The dataflow. 
- Return type
- azure.mgmt.datafactory.models.DataFlow 
 
 - create_dataflow(dataflow_name, dataflow, resource_group_name=None, factory_name=None, **config)[source]¶
- Create the dataflow. - Parameters
- Raises
- AirflowException – If the dataset already exists. 
- Returns
- The dataset. 
- Return type
- azure.mgmt.datafactory.models.DataFlow 
 
 - delete_dataflow(dataflow_name, resource_group_name=None, factory_name=None, **config)[source]¶
- Delete the dataflow. 
 - get_pipeline(pipeline_name, resource_group_name=None, factory_name=None, **config)[source]¶
- Get the pipeline. 
 - update_pipeline(pipeline_name, pipeline, resource_group_name=None, factory_name=None, **config)[source]¶
- Update the pipeline. - Parameters
- Raises
- AirflowException – If the pipeline does not exist. 
- Returns
- The pipeline. 
- Return type
- azure.mgmt.datafactory.models.PipelineResource 
 
 - create_pipeline(pipeline_name, pipeline, resource_group_name=None, factory_name=None, **config)[source]¶
- Create the pipeline. - Parameters
- Raises
- AirflowException – If the pipeline already exists. 
- Returns
- The pipeline. 
- Return type
- azure.mgmt.datafactory.models.PipelineResource 
 
 - delete_pipeline(pipeline_name, resource_group_name=None, factory_name=None, **config)[source]¶
- Delete the pipeline. 
 - run_pipeline(pipeline_name, resource_group_name=None, factory_name=None, **config)[source]¶
- Run a pipeline. 
 - get_pipeline_run(run_id, resource_group_name=None, factory_name=None, **config)[source]¶
- Get the pipeline run. 
 - get_pipeline_run_status(run_id, resource_group_name=None, factory_name=None)[source]¶
- Get a pipeline run’s current status. 
 - wait_for_pipeline_run_status(run_id, expected_statuses, resource_group_name=None, factory_name=None, check_interval=60, timeout=60 * 60 * 24 * 7)[source]¶
- Waits for a pipeline run to match an expected status. - Parameters
- run_id (str) – The pipeline run identifier. 
- expected_statuses (str | set[str]) – The desired status(es) to check against a pipeline run’s current status. 
- resource_group_name (str | None) – The resource group name. 
- factory_name (str | None) – The factory name. 
- check_interval (int) – Time in seconds to check on a pipeline run’s status. 
- timeout (int) – Time in seconds to wait for a pipeline to reach a terminal status or the expected status. 
 
- Returns
- Boolean indicating if the pipeline run has reached the - expected_status.
- Return type
 
 - cancel_pipeline_run(run_id, resource_group_name=None, factory_name=None, **config)[source]¶
- Cancel the pipeline run. 
 - get_trigger(trigger_name, resource_group_name=None, factory_name=None, **config)[source]¶
- Get the trigger. 
 - update_trigger(trigger_name, trigger, resource_group_name=None, factory_name=None, **config)[source]¶
- Update the trigger. - Parameters
- Raises
- AirflowException – If the trigger does not exist. 
- Returns
- The trigger. 
- Return type
- azure.mgmt.datafactory.models.TriggerResource 
 
 - create_trigger(trigger_name, trigger, resource_group_name=None, factory_name=None, **config)[source]¶
- Create the trigger. - Parameters
- Raises
- AirflowException – If the trigger already exists. 
- Returns
- The trigger. 
- Return type
- azure.mgmt.datafactory.models.TriggerResource 
 
 - delete_trigger(trigger_name, resource_group_name=None, factory_name=None, **config)[source]¶
- Delete the trigger. 
 - start_trigger(trigger_name, resource_group_name=None, factory_name=None, **config)[source]¶
- Start the trigger. 
 - stop_trigger(trigger_name, resource_group_name=None, factory_name=None, **config)[source]¶
- Stop the trigger. 
 - rerun_trigger(trigger_name, run_id, resource_group_name=None, factory_name=None, **config)[source]¶
- Rerun the trigger. 
 
- airflow.providers.microsoft.azure.hooks.data_factory.provide_targeted_factory_async(func)[source]¶
- Provide the targeted factory to the async decorated function in case it isn’t specified. - If - resource_group_nameor- factory_nameis not provided it defaults to the value specified in the connection extras.
- class airflow.providers.microsoft.azure.hooks.data_factory.AzureDataFactoryAsyncHook(azure_data_factory_conn_id=default_conn_name)[source]¶
- Bases: - AzureDataFactoryHook- An Async Hook that connects to Azure DataFactory to perform pipeline operations. - Parameters
- azure_data_factory_conn_id (str) – The Azure Data Factory connection id. 
 - async get_pipeline_run(run_id, resource_group_name=None, factory_name=None, **config)[source]¶
- Connect to Azure Data Factory asynchronously to get the pipeline run details by run id. 
 
