docs-archive/apache-airflow-providers-amazon/8.26.0/_sources/_api/airflow/providers/amazon/aws/sensors/batch/index.rst.txt

:py:mod:`airflow.providers.amazon.aws.sensors.batch`
====================================================

.. py:module:: airflow.providers.amazon.aws.sensors.batch


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

Classes
~~~~~~~

.. autoapisummary::

   airflow.providers.amazon.aws.sensors.batch.BatchSensor
   airflow.providers.amazon.aws.sensors.batch.BatchComputeEnvironmentSensor
   airflow.providers.amazon.aws.sensors.batch.BatchJobQueueSensor




.. py:class:: BatchSensor(*, job_id, aws_conn_id = 'aws_default', region_name = None, deferrable = conf.getboolean('operators', 'default_deferrable', fallback=False), poke_interval = 30, max_retries = 4200, **kwargs)


   Bases: :py:obj:`airflow.sensors.base.BaseSensorOperator`

   Poll the state of the Batch Job until it reaches a terminal state; fails if the job fails.

   .. seealso::
       For more information on how to use this sensor, take a look at the guide:
       :ref:`howto/sensor:BatchSensor`

   :param job_id: Batch job_id to check the state for
   :param aws_conn_id: aws connection to use, defaults to 'aws_default'
       If this is None or empty then the default boto3 behaviour is used. If
       running Airflow in a distributed manner and aws_conn_id is None or
       empty, then default boto3 configuration would be used (and must be
       maintained on each worker node).
   :param region_name: aws region name associated with the client
   :param deferrable: Run sensor in the deferrable mode.
   :param poke_interval: polling period in seconds to check for the status of the job.
   :param max_retries: Number of times to poll for job state before
       returning the current state.

   .. py:attribute:: template_fields
      :type: Sequence[str]
      :value: ('job_id',)

      

   .. py:attribute:: template_ext
      :type: Sequence[str]
      :value: ()

      

   .. py:attribute:: ui_color
      :value: '#66c3ff'

      

   .. py:method:: poke(context)

      Override when deriving this class.


   .. py:method:: execute(context)

      Derive when creating an operator.

      Context is the same dictionary used as when rendering jinja templates.

      Refer to get_template_context for more context.


   .. py:method:: execute_complete(context, event)

      Execute when the trigger fires - returns immediately.

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


   .. py:method:: get_hook()

      Create and return a BatchClientHook.


   .. py:method:: hook()



.. py:class:: BatchComputeEnvironmentSensor(compute_environment, aws_conn_id = 'aws_default', region_name = None, **kwargs)


   Bases: :py:obj:`airflow.sensors.base.BaseSensorOperator`

   Poll the state of the Batch environment until it reaches a terminal state; fails if the environment fails.

   .. seealso::
       For more information on how to use this sensor, take a look at the guide:
       :ref:`howto/sensor:BatchComputeEnvironmentSensor`

   :param compute_environment: Batch compute environment name

   :param aws_conn_id: aws connection to use, defaults to 'aws_default'
       If this is None or empty then the default boto3 behaviour is used. If
       running Airflow in a distributed manner and aws_conn_id is None or
       empty, then default boto3 configuration would be used (and must be
       maintained on each worker node).

   :param region_name: aws region name associated with the client

   .. py:attribute:: template_fields
      :type: Sequence[str]
      :value: ('compute_environment',)

      

   .. py:attribute:: template_ext
      :type: Sequence[str]
      :value: ()

      

   .. py:attribute:: ui_color
      :value: '#66c3ff'

      

   .. py:method:: hook()

      Create and return a BatchClientHook.


   .. py:method:: poke(context)

      Override when deriving this class.



.. py:class:: BatchJobQueueSensor(job_queue, treat_non_existing_as_deleted = False, aws_conn_id = 'aws_default', region_name = None, **kwargs)


   Bases: :py:obj:`airflow.sensors.base.BaseSensorOperator`

   Poll the state of the Batch job queue until it reaches a terminal state; fails if the queue fails.

   .. seealso::
       For more information on how to use this sensor, take a look at the guide:
       :ref:`howto/sensor:BatchJobQueueSensor`

   :param job_queue: Batch job queue name

   :param treat_non_existing_as_deleted: If True, a non-existing Batch job queue is considered as a deleted
       queue and as such a valid case.

   :param aws_conn_id: aws connection to use, defaults to 'aws_default'
       If this is None or empty then the default boto3 behaviour is used. If
       running Airflow in a distributed manner and aws_conn_id is None or
       empty, then default boto3 configuration would be used (and must be
       maintained on each worker node).

   :param region_name: aws region name associated with the client

   .. py:attribute:: template_fields
      :type: Sequence[str]
      :value: ('job_queue',)

      

   .. py:attribute:: template_ext
      :type: Sequence[str]
      :value: ()

      

   .. py:attribute:: ui_color
      :value: '#66c3ff'

      

   .. py:method:: hook()

      Create and return a BatchClientHook.


   .. py:method:: poke(context)

      Override when deriving this class.