#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
"""
Example Airflow DAG that creates, gets, lists, updates, purges, pauses, resumes
and deletes Queues in the Google Cloud Tasks service in the Google Cloud.
Required setup:
- GCP_APP_ENGINE_LOCATION: GCP Project's App Engine location `gcloud app describe | grep locationId`.
"""
from __future__ import annotations
import os
from datetime import datetime
from google.api_core.retry import Retry
from google.cloud.tasks_v2.types import Queue
from google.protobuf.field_mask_pb2 import FieldMask
from airflow import models
from airflow.decorators import task
from airflow.models.baseoperator import chain
from airflow.operators.bash import BashOperator
from airflow.providers.google.cloud.operators.tasks import (
CloudTasksQueueCreateOperator,
CloudTasksQueueDeleteOperator,
CloudTasksQueueGetOperator,
CloudTasksQueuePauseOperator,
CloudTasksQueuePurgeOperator,
CloudTasksQueueResumeOperator,
CloudTasksQueuesListOperator,
CloudTasksQueueUpdateOperator,
)
from airflow.utils.trigger_rule import TriggerRule
[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]DAG_ID = "cloud_tasks_queue"
[docs]LOCATION = os.environ.get("GCP_APP_ENGINE_LOCATION", "europe-west2")
[docs]QUEUE_ID = f"queue-{ENV_ID}-{DAG_ID.replace('_', '-')}"
with models.DAG(
dag_id=DAG_ID,
schedule="@once",
start_date=datetime(2021, 1, 1),
catchup=False,
tags=["example", "tasks"],
) as dag:
@task(task_id="random_string")
[docs] def generate_random_string():
"""
Generate random string for queue and task names.
Queue name cannot be repeated in preceding 7 days and
task name in the last 1 hour.
"""
import random
import string
return "".join(random.choices(string.ascii_uppercase + string.digits, k=8))
random_string = generate_random_string()
# [START create_queue]
create_queue = CloudTasksQueueCreateOperator(
location=LOCATION,
task_queue=Queue(stackdriver_logging_config=dict(sampling_ratio=0.5)),
queue_name=QUEUE_ID + "{{ task_instance.xcom_pull(task_ids='random_string') }}",
retry=Retry(maximum=10.0),
timeout=5,
task_id="create_queue",
)
# [END create_queue]
# [START delete_queue]
delete_queue = CloudTasksQueueDeleteOperator(
location=LOCATION,
queue_name=QUEUE_ID + "{{ task_instance.xcom_pull(task_ids='random_string') }}",
task_id="delete_queue",
)
# [END delete_queue]
delete_queue.trigger_rule = TriggerRule.ALL_DONE
# [START resume_queue]
resume_queue = CloudTasksQueueResumeOperator(
location=LOCATION,
queue_name=QUEUE_ID + "{{ task_instance.xcom_pull(task_ids='random_string') }}",
task_id="resume_queue",
)
# [END resume_queue]
# [START pause_queue]
pause_queue = CloudTasksQueuePauseOperator(
location=LOCATION,
queue_name=QUEUE_ID + "{{ task_instance.xcom_pull(task_ids='random_string') }}",
task_id="pause_queue",
)
# [END pause_queue]
# [START purge_queue]
purge_queue = CloudTasksQueuePurgeOperator(
location=LOCATION,
queue_name=QUEUE_ID + "{{ task_instance.xcom_pull(task_ids='random_string') }}",
task_id="purge_queue",
)
# [END purge_queue]
# [START get_queue]
get_queue = CloudTasksQueueGetOperator(
location=LOCATION,
queue_name=QUEUE_ID + "{{ task_instance.xcom_pull(task_ids='random_string') }}",
task_id="get_queue",
)
get_queue_result = BashOperator(
task_id="get_queue_result",
bash_command=f"echo {get_queue.output}",
)
# [END get_queue]
# [START update_queue]
update_queue = CloudTasksQueueUpdateOperator(
task_queue=Queue(stackdriver_logging_config=dict(sampling_ratio=1)),
location=LOCATION,
queue_name=QUEUE_ID + "{{ task_instance.xcom_pull(task_ids='random_string') }}",
update_mask=FieldMask(paths=["stackdriver_logging_config.sampling_ratio"]),
task_id="update_queue",
)
# [END update_queue]
# [START list_queue]
list_queue = CloudTasksQueuesListOperator(location=LOCATION, task_id="list_queue")
# [END list_queue]
chain(
random_string,
create_queue,
update_queue,
pause_queue,
resume_queue,
purge_queue,
get_queue,
get_queue_result,
list_queue,
delete_queue,
)
from tests.system.utils.watcher import watcher
# This test needs watcher in order to properly mark success/failure
# when "tearDown" task with trigger rule is part of the DAG
list(dag.tasks) >> watcher()
from tests.system.utils import get_test_run # noqa: E402
# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)
[docs]test_run = get_test_run(dag)
