Source code for airflow.providers.amazon.aws.sensors.step_function

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from __future__ import annotations

import json
from typing import TYPE_CHECKING, Sequence

from airflow.exceptions import AirflowException
from airflow.providers.amazon.aws.hooks.step_function import StepFunctionHook
from airflow.providers.amazon.aws.sensors.base_aws import AwsBaseSensor
from airflow.providers.amazon.aws.utils.mixins import aws_template_fields

if TYPE_CHECKING:
    from airflow.utils.context import Context


[docs]class StepFunctionExecutionSensor(AwsBaseSensor[StepFunctionHook]): """ Poll the Step Function State Machine Execution until it reaches a terminal state; fails if the task fails. On successful completion of the Execution the Sensor will do an XCom Push of the State Machine's output to `output` .. seealso:: For more information on how to use this sensor, take a look at the guide: :ref:`howto/sensor:StepFunctionExecutionSensor` :param execution_arn: execution_arn to check the state of :param aws_conn_id: The Airflow connection used for AWS credentials. 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. If not specified then the default boto3 behaviour is used. :param verify: Whether or not to verify SSL certificates. See: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html :param botocore_config: Configuration dictionary (key-values) for botocore client. See: https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html """
[docs] INTERMEDIATE_STATES = ("RUNNING",)
[docs] FAILURE_STATES = ( "FAILED", "TIMED_OUT", "ABORTED", )
[docs] SUCCESS_STATES = ("SUCCEEDED",)
[docs] aws_hook_class = StepFunctionHook
[docs] template_fields: Sequence[str] = aws_template_fields("execution_arn")
[docs] ui_color = "#66c3ff"
def __init__(self, *, execution_arn: str, **kwargs): super().__init__(**kwargs) self.execution_arn = execution_arn
[docs] def poke(self, context: Context): execution_status = self.hook.describe_execution(self.execution_arn) state = execution_status["status"] output = json.loads(execution_status["output"]) if "output" in execution_status else None if state in self.FAILURE_STATES: raise AirflowException(f"Step Function sensor failed. State Machine Output: {output}") if state in self.INTERMEDIATE_STATES: return False self.log.info("Doing xcom_push of output") self.xcom_push(context, "output", output) return True

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