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"""
Example Airflow DAG that creates, gets, lists, updates, purges, pauses, resumes
and deletes Queues in the Google Cloud Tasks service in the Google Cloud.
"""
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 = "europe-central2"
[docs]QUEUE_ID = f"queue-{ENV_ID}-{DAG_ID.replace('_', '-')}"
with models.DAG(
dag_id=DAG_ID,
schedule_interval='@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)
