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.
from __future__ import annotations

import json
from datetime import timedelta
from typing import TYPE_CHECKING, Any, Sequence

from airflow.configuration import conf
from airflow.exceptions import AirflowException
from airflow.providers.amazon.aws.hooks.step_function import StepFunctionHook
from airflow.providers.amazon.aws.links.step_function import (
    StateMachineDetailsLink,
    StateMachineExecutionsDetailsLink,
)
from airflow.providers.amazon.aws.operators.base_aws import AwsBaseOperator
from airflow.providers.amazon.aws.triggers.step_function import StepFunctionsExecutionCompleteTrigger
from airflow.providers.amazon.aws.utils import validate_execute_complete_event
from airflow.providers.amazon.aws.utils.mixins import aws_template_fields

if TYPE_CHECKING:
    from airflow.utils.context import Context


[docs]class StepFunctionStartExecutionOperator(AwsBaseOperator[StepFunctionHook]): """ An Operator that begins execution of an AWS Step Function State Machine. Additional arguments may be specified and are passed down to the underlying BaseOperator. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:StepFunctionStartExecutionOperator` :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: 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 do_xcom_push: if True, execution_arn is pushed to XCom with key execution_arn. :param waiter_max_attempts: Maximum number of attempts to poll the execution. :param waiter_delay: Number of seconds between polling the state of the execution. :param deferrable: If True, the operator will wait asynchronously for the job to complete. This implies waiting for completion. This mode requires aiobotocore module to be installed. (default: False, but can be overridden in config file by setting default_deferrable to True) :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] aws_hook_class = StepFunctionHook
[docs] template_fields: Sequence[str] = aws_template_fields("state_machine_arn", "name", "input")
[docs] ui_color = "#f9c915"
def __init__( self, *, state_machine_arn: str, name: str | None = None, state_machine_input: dict | str | None = None, waiter_max_attempts: int = 30, waiter_delay: int = 60, deferrable: bool = conf.getboolean("operators", "default_deferrable", fallback=False), **kwargs, ): super().__init__(**kwargs) self.state_machine_arn = state_machine_arn self.name = name self.input = state_machine_input self.waiter_delay = waiter_delay self.waiter_max_attempts = waiter_max_attempts self.deferrable = deferrable
[docs] def execute(self, context: Context): StateMachineDetailsLink.persist( context=context, operator=self, region_name=self.hook.conn_region_name, aws_partition=self.hook.conn_partition, state_machine_arn=self.state_machine_arn, ) if not (execution_arn := self.hook.start_execution(self.state_machine_arn, self.name, self.input)): raise AirflowException(f"Failed to start State Machine execution for: {self.state_machine_arn}") StateMachineExecutionsDetailsLink.persist( context=context, operator=self, region_name=self.hook.conn_region_name, aws_partition=self.hook.conn_partition, execution_arn=execution_arn, ) self.log.info("Started State Machine execution for %s: %s", self.state_machine_arn, execution_arn) if self.deferrable: self.defer( trigger=StepFunctionsExecutionCompleteTrigger( execution_arn=execution_arn, waiter_delay=self.waiter_delay, waiter_max_attempts=self.waiter_max_attempts, aws_conn_id=self.aws_conn_id, region_name=self.region_name, botocore_config=self.botocore_config, verify=self.verify, ), method_name="execute_complete", timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay), ) return execution_arn
[docs] def execute_complete(self, context: Context, event: dict[str, Any] | None = None) -> None: event = validate_execute_complete_event(event) if event["status"] != "success": raise AirflowException(f"Trigger error: event is {event}") self.log.info("State Machine execution completed successfully") return event["execution_arn"]
[docs]class StepFunctionGetExecutionOutputOperator(AwsBaseOperator[StepFunctionHook]): """ An Operator that returns the output of an AWS Step Function State Machine execution. Additional arguments may be specified and are passed down to the underlying BaseOperator. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:StepFunctionGetExecutionOutputOperator` :param execution_arn: ARN of the Step Function State Machine Execution :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] aws_hook_class = StepFunctionHook
[docs] template_fields: Sequence[str] = aws_template_fields("execution_arn")
[docs] ui_color = "#f9c915"
def __init__(self, *, execution_arn: str, **kwargs): super().__init__(**kwargs) self.execution_arn = execution_arn
[docs] def execute(self, context: Context): StateMachineExecutionsDetailsLink.persist( context=context, operator=self, region_name=self.hook.conn_region_name, aws_partition=self.hook.conn_partition, execution_arn=self.execution_arn, ) execution_status = self.hook.describe_execution(self.execution_arn) response = None if "output" in execution_status: response = json.loads(execution_status["output"]) elif "error" in execution_status: response = json.loads(execution_status["error"]) self.log.info("Got State Machine Execution output for %s", self.execution_arn) return response

Was this entry helpful?