:py:mod:`astronomer.providers.amazon.aws.triggers.sagemaker`
============================================================

.. py:module:: astronomer.providers.amazon.aws.triggers.sagemaker


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

Classes
~~~~~~~

.. autoapisummary::

   astronomer.providers.amazon.aws.triggers.sagemaker.SagemakerProcessingTrigger
   astronomer.providers.amazon.aws.triggers.sagemaker.SagemakerTrigger
   astronomer.providers.amazon.aws.triggers.sagemaker.SagemakerTrainingWithLogTrigger




.. py:class:: SagemakerProcessingTrigger(job_name, poll_interval, end_time, aws_conn_id = 'aws_default')


   Bases: :py:obj:`airflow.triggers.base.BaseTrigger`

   SagemakerProcessingTrigger is fired as deferred class with params to run the task in triggerer.

   This class is deprecated and will be removed in 2.0.0.
   Use :class: `~airflow.providers.amazon.aws.triggers.sagemaker.SageMakerTrigger` instead

   :param job_name: name of the job to check status
   :param poll_interval:  polling period in seconds to check for the status
   :param aws_conn_id: AWS connection ID for sagemaker
   :param end_time: the end time in seconds. Any
           SageMaker jobs that run longer than this will fail.

   .. py:attribute:: NON_TERMINAL_STATES
      :value: ('InProgress', 'Stopping')

      

   .. py:attribute:: TERMINAL_STATE
      :value: ('Failed',)

      

   .. py:method:: serialize()

      Serializes SagemakerProcessingTrigger arguments and classpath.


   .. py:method:: run()
      :async:

      Makes async connection to sagemaker async hook and gets job status for a job submitted by the operator.
      Trigger returns a failure event if any error and success in state return the success event.



.. py:class:: SagemakerTrigger(job_name, job_type, response_key, poke_interval, end_time = None, aws_conn_id = 'aws_default')


   Bases: :py:obj:`airflow.triggers.base.BaseTrigger`

   SagemakerTrigger is common trigger for both transform and training sagemaker job and it is
    fired as deferred class with params to run the task in triggerer.

   This class is deprecated and will be removed in 2.0.0.
   Use :class: `~airflow.providers.amazon.aws.triggers.sagemaker.SageMakerTrigger` instead

   :param job_name: name of the job to check status
   :param job_type: Type of the sagemaker job whether it is Transform or Training
   :param response_key: The key which needs to be look in the response.
   :param poke_interval:  polling period in seconds to check for the status
   :param end_time: Time in seconds to wait for a job run to reach a terminal status.
   :param aws_conn_id: AWS connection ID for sagemaker

   .. py:attribute:: NON_TERMINAL_STATES
      :value: ('InProgress', 'Stopping', 'Stopped')

      

   .. py:attribute:: TERMINAL_STATE
      :value: ('Failed',)

      

   .. py:method:: serialize()

      Serializes SagemakerTrigger arguments and classpath.


   .. py:method:: run()
      :async:

      Makes async connection to sagemaker async hook and gets job status for a job submitted by the operator.
      Trigger returns a failure event if any error and success in state return the success event.


   .. py:method:: get_job_status(hook, job_name, job_type)
      :staticmethod:
      :async:

      Based on the job type the SageMakerHookAsync connect to sagemaker related function
      and get the response of the job and return it



.. py:class:: SagemakerTrainingWithLogTrigger(job_name, instance_count, status, poke_interval, end_time = None, aws_conn_id = 'aws_default')


   Bases: :py:obj:`airflow.triggers.base.BaseTrigger`

   SagemakerTrainingWithLogTrigger is fired as deferred class with params to run the task in triggerer.

   This class is deprecated and will be removed in 2.0.0.
   Use :class: `~airflow.providers.amazon.aws.triggers.sagemaker.SageMakerTrainingPrintLogTrigger` instead

   :param job_name: name of the job to check status
   :param instance_count: count of the instance created for running the training job
   :param status: The status of the training job created.
   :param poke_interval:  polling period in seconds to check for the status
   :param end_time: Time in seconds to wait for a job run to reach a terminal status.
   :param aws_conn_id: AWS connection ID for sagemaker

   .. py:attribute:: NON_TERMINAL_STATES
      :value: ('InProgress', 'Stopping', 'Stopped')

      

   .. py:attribute:: TERMINAL_STATE
      :value: ('Failed',)

      

   .. py:method:: serialize()

      Serializes SagemakerTrainingWithLogTrigger arguments and classpath.


   .. py:method:: run()
      :async:

      Makes async connection to sagemaker async hook and gets job status for a job submitted by the operator.
      Trigger returns a failure event if any error and success in state return the success event.