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from typing import TYPE_CHECKING, Optional, Sequence

from airflow.exceptions import AirflowException
from import BatchClientHook
from airflow.sensors.base import BaseSensorOperator

    from airflow.utils.context import Context

[docs]class BatchSensor(BaseSensorOperator): """ Asks for the state of the Batch Job execution until it reaches a failure state or success state. If the job fails, the task will fail. .. 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' """
[docs] template_fields: Sequence[str] = ('job_id',)
[docs] template_ext: Sequence[str] = ()
[docs] ui_color = '#66c3ff'
def __init__( self, *, job_id: str, aws_conn_id: str = 'aws_default', region_name: Optional[str] = None, **kwargs, ): super().__init__(**kwargs) self.job_id = job_id self.aws_conn_id = aws_conn_id self.region_name = region_name self.hook: Optional[BatchClientHook] = None
[docs] def poke(self, context: 'Context') -> bool: job_description = self.get_hook().get_job_description(self.job_id) state = job_description['status'] if state == BatchClientHook.SUCCESS_STATE: return True if state in BatchClientHook.INTERMEDIATE_STATES: return False if state == BatchClientHook.FAILURE_STATE: raise AirflowException(f'Batch sensor failed. AWS Batch job status: {state}') raise AirflowException(f'Batch sensor failed. Unknown AWS Batch job status: {state}')
[docs] def get_hook(self) -> BatchClientHook: """Create and return a BatchClientHook""" if self.hook: return self.hook self.hook = BatchClientHook( aws_conn_id=self.aws_conn_id, region_name=self.region_name, ) return self.hook

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