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)