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# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
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#
# http://www.apache.org/licenses/LICENSE-2.0
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# software distributed under the License is distributed on an
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# KIND, either express or implied. See the License for the
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from __future__ import annotations
from collections.abc import Collection, Sequence
from typing import TYPE_CHECKING, Any
from airflow.configuration import conf
from airflow.exceptions import AirflowException
from airflow.providers.amazon.aws.hooks.mwaa import MwaaHook
from airflow.providers.amazon.aws.sensors.base_aws import AwsBaseSensor
from airflow.providers.amazon.aws.triggers.mwaa import MwaaDagRunCompletedTrigger
from airflow.providers.amazon.aws.utils import validate_execute_complete_event
from airflow.providers.amazon.aws.utils.mixins import aws_template_fields
from airflow.utils.state import DagRunState
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]
class MwaaDagRunSensor(AwsBaseSensor[MwaaHook]):
"""
Waits for a DAG Run in an MWAA Environment to complete.
If the DAG Run fails, an AirflowException is thrown.
.. seealso::
For more information on how to use this sensor, take a look at the guide:
:ref:`howto/sensor:MwaaDagRunSensor`
:param external_env_name: The external MWAA environment name that contains the DAG Run you want to wait for
(templated)
:param external_dag_id: The DAG ID in the external MWAA environment that contains the DAG Run you want to wait for
(templated)
:param external_dag_run_id: The DAG Run ID in the external MWAA environment that you want to wait for (templated)
:param success_states: Collection of DAG Run states that would make this task marked as successful, default is
``{airflow.utils.state.DagRunState.SUCCESS}`` (templated)
:param failure_states: Collection of DAG Run states that would make this task marked as failed and raise an
AirflowException, default is ``{airflow.utils.state.DagRunState.FAILED}`` (templated)
:param deferrable: If True, the sensor will operate in deferrable mode. This mode requires aiobotocore
module to be installed.
(default: False, but can be overridden in config file by setting default_deferrable to True)
:param poke_interval: Polling period in seconds to check for the status of the job. (default: 60)
:param max_retries: Number of times before returning the current state. (default: 720)
: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 = MwaaHook
[docs]
template_fields: Sequence[str] = aws_template_fields(
"external_env_name",
"external_dag_id",
"external_dag_run_id",
"success_states",
"failure_states",
"deferrable",
"max_retries",
"poke_interval",
)
def __init__(
self,
*,
external_env_name: str,
external_dag_id: str,
external_dag_run_id: str,
success_states: Collection[str] | None = None,
failure_states: Collection[str] | None = None,
deferrable: bool = conf.getboolean("operators", "default_deferrable", fallback=False),
poke_interval: int = 60,
max_retries: int = 720,
**kwargs,
):
super().__init__(**kwargs)
[docs]
self.success_states = set(success_states) if success_states else {DagRunState.SUCCESS.value}
[docs]
self.failure_states = set(failure_states) if failure_states else {DagRunState.FAILED.value}
if len(self.success_states & self.failure_states):
raise ValueError("success_states and failure_states must not have any values in common")
[docs]
self.external_env_name = external_env_name
[docs]
self.external_dag_id = external_dag_id
[docs]
self.external_dag_run_id = external_dag_run_id
[docs]
self.deferrable = deferrable
[docs]
self.poke_interval = poke_interval
[docs]
self.max_retries = max_retries
[docs]
def poke(self, context: Context) -> bool:
self.log.info(
"Poking for DAG run %s of DAG %s in MWAA environment %s",
self.external_dag_run_id,
self.external_dag_id,
self.external_env_name,
)
response = self.hook.invoke_rest_api(
env_name=self.external_env_name,
path=f"/dags/{self.external_dag_id}/dagRuns/{self.external_dag_run_id}",
method="GET",
)
# If RestApiStatusCode == 200, the RestApiResponse must have the "state" key, otherwise something terrible has
# happened in the API and KeyError would be raised
# If RestApiStatusCode >= 300, a botocore exception would've already been raised during the
# self.hook.invoke_rest_api call
# The scope of this sensor is going to only be raising AirflowException due to failure of the DAGRun
state = response["RestApiResponse"]["state"]
if state in self.failure_states:
raise AirflowException(
f"The DAG run {self.external_dag_run_id} of DAG {self.external_dag_id} in MWAA environment {self.external_env_name} "
f"failed with state: {state}"
)
return state in self.success_states
[docs]
def execute_complete(self, context: Context, event: dict[str, Any] | None = None) -> None:
validate_execute_complete_event(event)
[docs]
def execute(self, context: Context):
if self.deferrable:
self.defer(
trigger=MwaaDagRunCompletedTrigger(
external_env_name=self.external_env_name,
external_dag_id=self.external_dag_id,
external_dag_run_id=self.external_dag_run_id,
success_states=self.success_states,
failure_states=self.failure_states,
waiter_delay=self.poke_interval,
waiter_max_attempts=self.max_retries,
aws_conn_id=self.aws_conn_id,
),
method_name="execute_complete",
)
else:
super().execute(context=context)