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

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from __future__ import annotations

import json

from airflow.exceptions import AirflowFailException
from airflow.providers.amazon.aws.hooks.base_aws import AwsBaseHook


[docs]class StepFunctionHook(AwsBaseHook): """ Interact with an AWS Step Functions State Machine. Provide thin wrapper around :external+boto3:py:class:`boto3.client("stepfunctions") <SFN.Client>`. Additional arguments (such as ``aws_conn_id``) may be specified and are passed down to the underlying AwsBaseHook. .. seealso:: - :class:`airflow.providers.amazon.aws.hooks.base_aws.AwsBaseHook` """ def __init__(self, *args, **kwargs) -> None: kwargs["client_type"] = "stepfunctions" super().__init__(*args, **kwargs)
[docs] def start_execution( self, state_machine_arn: str, name: str | None = None, state_machine_input: dict | str | None = None, is_redrive_execution: bool = False, ) -> str: """ Start Execution of the State Machine. .. seealso:: - :external+boto3:py:meth:`SFN.Client.start_execution` :param state_machine_arn: AWS Step Function State Machine ARN. :param is_redrive_execution: Restarts unsuccessful executions of Standard workflows that did not complete successfully in the last 14 days. :param name: The name of the execution. :param state_machine_input: JSON data input to pass to the State Machine. :return: Execution ARN. """ if is_redrive_execution: if not name: raise AirflowFailException( "Execution name is required to start RedriveExecution for %s.", state_machine_arn ) elements = state_machine_arn.split(":stateMachine:") execution_arn = f"{elements[0]}:execution:{elements[1]}:{name}" self.conn.redrive_execution(executionArn=execution_arn) self.log.info( "Successfully started RedriveExecution for Step Function State Machine: %s.", state_machine_arn, ) return execution_arn execution_args = {"stateMachineArn": state_machine_arn} if name is not None: execution_args["name"] = name if state_machine_input is not None: if isinstance(state_machine_input, str): execution_args["input"] = state_machine_input elif isinstance(state_machine_input, dict): execution_args["input"] = json.dumps(state_machine_input) self.log.info("Executing Step Function State Machine: %s", state_machine_arn) response = self.conn.start_execution(**execution_args) return response.get("executionArn")
[docs] def describe_execution(self, execution_arn: str) -> dict: """ Describe a State Machine Execution. .. seealso:: - :external+boto3:py:meth:`SFN.Client.describe_execution` :param execution_arn: ARN of the State Machine Execution. :return: Dict with execution details. """ return self.get_conn().describe_execution(executionArn=execution_arn)

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