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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.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: aws connection to uses
: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")
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:
if event is None or 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")
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
