Source code for airflow.providers.amazon.aws.sensors.dms

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from __future__ import annotations

from collections.abc import Iterable, Sequence
from typing import TYPE_CHECKING

from airflow.exceptions import AirflowException
from airflow.providers.amazon.aws.hooks.dms import DmsHook
from airflow.providers.amazon.aws.sensors.base_aws import AwsBaseSensor
from airflow.providers.amazon.aws.utils.mixins import aws_template_fields

if TYPE_CHECKING:
    from airflow.utils.context import Context


[docs]class DmsTaskBaseSensor(AwsBaseSensor[DmsHook]): """ Contains general sensor behavior for DMS task. Subclasses should set ``target_statuses`` and ``termination_statuses`` fields. :param replication_task_arn: AWS DMS replication task ARN :param target_statuses: the target statuses, sensor waits until the task reaches any of these states :param termination_statuses: the termination statuses, sensor fails when the task reaches any of these states :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 = DmsHook
[docs] template_fields: Sequence[str] = aws_template_fields("replication_task_arn")
def __init__( self, replication_task_arn: str, target_statuses: Iterable[str] | None = None, termination_statuses: Iterable[str] | None = None, **kwargs, ): super().__init__(**kwargs) self.replication_task_arn = replication_task_arn self.target_statuses: Iterable[str] = target_statuses or [] self.termination_statuses: Iterable[str] = termination_statuses or []
[docs] def poke(self, context: Context): if not (status := self.hook.get_task_status(self.replication_task_arn)): raise AirflowException( f"Failed to read task status, task with ARN {self.replication_task_arn} not found" ) self.log.info("DMS Replication task (%s) has status: %s", self.replication_task_arn, status) if status in self.target_statuses: return True if status in self.termination_statuses: raise AirflowException(f"Unexpected status: {status}") return False
[docs]class DmsTaskCompletedSensor(DmsTaskBaseSensor): """ Pokes DMS task until it is completed. .. seealso:: For more information on how to use this sensor, take a look at the guide: :ref:`howto/sensor:DmsTaskCompletedSensor` :param replication_task_arn: AWS DMS replication task ARN :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 """ def __init__(self, **kwargs): kwargs["target_statuses"] = ["stopped"] kwargs["termination_statuses"] = [ "creating", "deleting", "failed", "failed-move", "modifying", "moving", "ready", "testing", ] super().__init__(**kwargs)

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