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

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.


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 :param name: The name of the execution. :param state_machine_input: JSON data input to pass to the State Machine :param aws_conn_id: aws connection to uses :param do_xcom_push: if True, execution_arn is pushed to XCom with key execution_arn. """
[docs] template_fields: Sequence[str] = ('state_machine_arn', 'name', 'input')
[docs] template_ext: Sequence[str] = ()
[docs] ui_color = '#f9c915'
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 :param aws_conn_id: aws connection to use, defaults to 'aws_default' """
[docs] template_fields: Sequence[str] = ('execution_arn',)
[docs] template_ext: Sequence[str] = ()
[docs] ui_color = '#f9c915'
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

Was this entry helpful?