Source code for airflow.providers.amazon.aws.triggers.kinesis_analytics
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from __future__ import annotations
from typing import TYPE_CHECKING
from airflow.providers.amazon.aws.hooks.kinesis_analytics import KinesisAnalyticsV2Hook
from airflow.providers.amazon.aws.triggers.base import AwsBaseWaiterTrigger
if TYPE_CHECKING:
from airflow.providers.amazon.aws.hooks.base_aws import AwsGenericHook
[docs]class KinesisAnalyticsV2ApplicationOperationCompleteTrigger(AwsBaseWaiterTrigger):
"""
Trigger when a Managed Service for Apache Flink application Start or Stop is complete.
:param application_name: Application name.
:param waiter_name: The name of the waiter for stop or start application.
:param waiter_delay: The amount of time in seconds to wait between attempts. (default: 120)
:param waiter_max_attempts: The maximum number of attempts to be made. (default: 75)
:param aws_conn_id: The Airflow connection used for AWS credentials.
"""
def __init__(
self,
application_name: str,
waiter_name: str,
waiter_delay: int = 120,
waiter_max_attempts: int = 75,
aws_conn_id: str | None = "aws_default",
**kwargs,
) -> None:
super().__init__(
serialized_fields={"application_name": application_name, "waiter_name": waiter_name},
waiter_name=waiter_name,
waiter_args={"ApplicationName": application_name},
failure_message=f"AWS Managed Service for Apache Flink Application {application_name} failed.",
status_message=f"Status of AWS Managed Service for Apache Flink Application {application_name} is",
status_queries=["ApplicationDetail.ApplicationStatus"],
return_key="application_name",
return_value=application_name,
waiter_delay=waiter_delay,
waiter_max_attempts=waiter_max_attempts,
aws_conn_id=aws_conn_id,
**kwargs,
)
[docs] def hook(self) -> AwsGenericHook:
return KinesisAnalyticsV2Hook(
aws_conn_id=self.aws_conn_id,
region_name=self.region_name,
verify=self.verify,
config=self.botocore_config,
)