Source code for airflow.providers.amazon.aws.operators.step_function
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import json
from typing import TYPE_CHECKING, Optional, Sequence, Union
from airflow.exceptions import AirflowException
from airflow.models import BaseOperator
from airflow.providers.amazon.aws.hooks.step_function import StepFunctionHook
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class StepFunctionStartExecutionOperator(BaseOperator):
"""
An Operator that begins execution of an Step Function State Machine
Additional arguments may be specified and are passed down to the underlying BaseOperator.
.. seealso::
:class:`~airflow.models.BaseOperator`
:param state_machine_arn: ARN of the Step Function State Machine
:type state_machine_arn: str
:param name: The name of the execution.
:type name: Optional[str]
:param state_machine_input: JSON data input to pass to the State Machine
:type state_machine_input: Union[Dict[str, any], str, None]
:param aws_conn_id: aws connection to uses
:type aws_conn_id: str
:param do_xcom_push: if True, execution_arn is pushed to XCom with key execution_arn.
:type do_xcom_push: bool
"""
[docs] template_fields: Sequence[str] = ('state_machine_arn', 'name', 'input')
[docs] template_ext: Sequence[str] = ()
def __init__(
self,
*,
state_machine_arn: str,
name: Optional[str] = None,
state_machine_input: Union[dict, str, None] = None,
aws_conn_id: str = 'aws_default',
region_name: Optional[str] = None,
**kwargs,
):
super().__init__(**kwargs)
self.state_machine_arn = state_machine_arn
self.name = name
self.input = state_machine_input
self.aws_conn_id = aws_conn_id
self.region_name = region_name
[docs] def execute(self, context: 'Context'):
hook = StepFunctionHook(aws_conn_id=self.aws_conn_id, region_name=self.region_name)
execution_arn = hook.start_execution(self.state_machine_arn, self.name, self.input)
if execution_arn is None:
raise AirflowException(f'Failed to start State Machine execution for: {self.state_machine_arn}')
self.log.info('Started State Machine execution for %s: %s', self.state_machine_arn, execution_arn)
return execution_arn
[docs]class StepFunctionGetExecutionOutputOperator(BaseOperator):
"""
An Operator that begins execution of an Step Function State Machine
Additional arguments may be specified and are passed down to the underlying BaseOperator.
.. seealso::
:class:`~airflow.models.BaseOperator`
:param execution_arn: ARN of the Step Function State Machine Execution
:type execution_arn: str
:param aws_conn_id: aws connection to use, defaults to 'aws_default'
:type aws_conn_id: str
"""
[docs] template_fields: Sequence[str] = ('execution_arn',)
[docs] template_ext: Sequence[str] = ()
def __init__(
self,
*,
execution_arn: str,
aws_conn_id: str = 'aws_default',
region_name: Optional[str] = None,
**kwargs,
):
super().__init__(**kwargs)
self.execution_arn = execution_arn
self.aws_conn_id = aws_conn_id
self.region_name = region_name
[docs] def execute(self, context: 'Context'):
hook = StepFunctionHook(aws_conn_id=self.aws_conn_id, region_name=self.region_name)
execution_status = hook.describe_execution(self.execution_arn)
execution_output = json.loads(execution_status['output']) if 'output' in execution_status else None
self.log.info('Got State Machine Execution output for %s', self.execution_arn)
return execution_output