Source code for airflow.providers.amazon.aws.sensors.batch
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from typing import TYPE_CHECKING, Optional, Sequence
from airflow.exceptions import AirflowException
from airflow.providers.amazon.aws.hooks.batch_client import BatchClientHook
from airflow.sensors.base import BaseSensorOperator
if TYPE_CHECKING:
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] = ()
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