: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.

   :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
      :annotation: = ['InProgress', 'Stopping']

      

   .. py:attribute:: TERMINAL_STATE
      :annotation: = ['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.

   :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
      :annotation: = ['InProgress', 'Stopping', 'Stopped']

      

   .. py:attribute:: TERMINAL_STATE
      :annotation: = ['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.

   :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
      :annotation: = ['InProgress', 'Stopping', 'Stopped']

      

   .. py:attribute:: TERMINAL_STATE
      :annotation: = ['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.