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, )

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