Source code for tests.system.google.cloud.cloud_run.example_cloud_run

#
# 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 uses Google Cloud Run Operators."""

from __future__ import annotations

import os
from datetime import datetime

from google.cloud.run_v2 import Job
from google.cloud.run_v2.types import k8s_min

from airflow.models.dag import DAG
from airflow.operators.python import PythonOperator
from airflow.providers.google.cloud.operators.cloud_run import (
    CloudRunCreateJobOperator,
    CloudRunDeleteJobOperator,
    CloudRunExecuteJobOperator,
    CloudRunListJobsOperator,
    CloudRunUpdateJobOperator,
)
from airflow.utils.trigger_rule import TriggerRule

[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID", "default")
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT", "default")
[docs]DAG_ID = "cloud_run"
[docs]region = "us-central1"
[docs]job_name_prefix = "cloudrun-system-test-job"
[docs]job1_name = f"{job_name_prefix}1-{ENV_ID}"
[docs]job2_name = f"{job_name_prefix}2-{ENV_ID}"
[docs]job3_name = f"{job_name_prefix}3-{ENV_ID}"
[docs]create1_task_name = "create-job1"
[docs]create2_task_name = "create-job2"
[docs]create3_task_name = "create-job3"
[docs]execute1_task_name = "execute-job1"
[docs]execute2_task_name = "execute-job2"
[docs]execute3_task_name = "execute-job3"
[docs]update_job1_task_name = "update-job1"
[docs]delete1_task_name = "delete-job1"
[docs]delete2_task_name = "delete-job2"
[docs]list_jobs_limit_task_name = "list-jobs-limit"
[docs]list_jobs_task_name = "list-jobs"
[docs]clean1_task_name = "clean-job1"
[docs]clean2_task_name = "clean-job2"
def _assert_executed_jobs_xcom(ti): job1_dicts = ti.xcom_pull(task_ids=[execute1_task_name], key="return_value") assert job1_name in job1_dicts[0]["name"] job2_dicts = ti.xcom_pull(task_ids=[execute2_task_name], key="return_value") assert job2_name in job2_dicts[0]["name"] job3_dicts = ti.xcom_pull(task_ids=[execute3_task_name], key="return_value") assert job3_name in job3_dicts[0]["name"] def _assert_created_jobs_xcom(ti): job1_dicts = ti.xcom_pull(task_ids=[create1_task_name], key="return_value") assert job1_name in job1_dicts[0]["name"] job2_dicts = ti.xcom_pull(task_ids=[create2_task_name], key="return_value") assert job2_name in job2_dicts[0]["name"] job3_dicts = ti.xcom_pull(task_ids=[create3_task_name], key="return_value") assert job3_name in job3_dicts[0]["name"] def _assert_updated_job(ti): job_dicts = ti.xcom_pull(task_ids=[update_job1_task_name], key="return_value") job_dict = job_dicts[0] assert job_dict["labels"]["somelabel"] == "label1" def _assert_jobs(ti): job_dicts = ti.xcom_pull(task_ids=[list_jobs_task_name], key="return_value") job1_exists = False job2_exists = False for job_dict in job_dicts[0]: if job1_exists and job2_exists: break if job1_name in job_dict["name"]: job1_exists = True if job2_name in job_dict["name"]: job2_exists = True assert job1_exists assert job2_exists def _assert_one_job(ti): job_dicts = ti.xcom_pull(task_ids=[list_jobs_limit_task_name], key="return_value") assert len(job_dicts[0]) == 1 # [START howto_cloud_run_job_instance_creation] def _create_job_instance() -> Job: """ Create a Cloud Run job configuration with google.cloud.run_v2.Job object. As a minimum the configuration must contain a container image name in its template. The rest of the configuration parameters are optional and will be populated with default values if not set. """ job = Job() container = k8s_min.Container() container.image = "us-docker.pkg.dev/cloudrun/container/job:latest" container.resources.limits = {"cpu": "2", "memory": "1Gi"} job.template.template.containers.append(container) return job # [END howto_cloud_run_job_instance_creation] # [START howto_cloud_run_job_dict_creation] def _create_job_dict() -> dict: """ Create a Cloud Run job configuration with a Python dict. As a minimum the configuration must contain a container image name in its template. """ return { "template": { "template": { "containers": [ { "image": "us-docker.pkg.dev/cloudrun/container/job:latest", "resources": { "limits": {"cpu": "1", "memory": "512Mi"}, "cpu_idle": False, "startup_cpu_boost": False, }, "name": "", "command": [], "args": [], "env": [], "ports": [], "volume_mounts": [], "working_dir": "", "depends_on": [], } ], "volumes": [], "execution_environment": 0, "encryption_key": "", }, "labels": {}, "annotations": {}, "parallelism": 0, "task_count": 0, }, "name": "", "uid": "", "generation": "0", "labels": {}, "annotations": {}, "creator": "", "last_modifier": "", "client": "", "client_version": "", "launch_stage": 0, "observed_generation": "0", "conditions": [], "execution_count": 0, "reconciling": False, "satisfies_pzs": False, "etag": "", } # [END howto_cloud_run_job_dict_creation] def _create_job_instance_with_label(): job = _create_job_instance() job.labels = {"somelabel": "label1"} return job with DAG( DAG_ID, schedule="@once", start_date=datetime(2021, 1, 1), catchup=False, tags=["example", "cloud", "run"], ) as dag: # [START howto_operator_cloud_run_create_job]
[docs] create1 = CloudRunCreateJobOperator( task_id=create1_task_name, project_id=PROJECT_ID, region=region, job_name=job1_name, job=_create_job_instance(), dag=dag, )
# [END howto_operator_cloud_run_create_job] create2 = CloudRunCreateJobOperator( task_id=create2_task_name, project_id=PROJECT_ID, region=region, job_name=job2_name, job=_create_job_dict(), dag=dag, ) create3 = CloudRunCreateJobOperator( task_id=create3_task_name, project_id=PROJECT_ID, region=region, job_name=job3_name, job=Job.to_dict(_create_job_instance()), dag=dag, ) assert_created_jobs = PythonOperator( task_id="assert-created-jobs", python_callable=_assert_created_jobs_xcom, dag=dag ) # [START howto_operator_cloud_run_execute_job] execute1 = CloudRunExecuteJobOperator( task_id=execute1_task_name, project_id=PROJECT_ID, region=region, job_name=job1_name, dag=dag, deferrable=False, ) # [END howto_operator_cloud_run_execute_job] # [START howto_operator_cloud_run_execute_job_deferrable_mode] execute2 = CloudRunExecuteJobOperator( task_id=execute2_task_name, project_id=PROJECT_ID, region=region, job_name=job2_name, dag=dag, deferrable=True, ) # [END howto_operator_cloud_run_execute_job_deferrable_mode] # [START howto_operator_cloud_run_execute_job_with_overrides] overrides = { "container_overrides": [ { "name": "job", "args": ["python", "main.py"], "env": [{"name": "ENV_VAR", "value": "value"}], "clear_args": False, } ], "task_count": 1, "timeout": "60s", } execute3 = CloudRunExecuteJobOperator( task_id=execute3_task_name, project_id=PROJECT_ID, region=region, overrides=overrides, job_name=job3_name, dag=dag, deferrable=False, ) # [END howto_operator_cloud_run_execute_job_with_overrides] assert_executed_jobs = PythonOperator( task_id="assert-executed-jobs", python_callable=_assert_executed_jobs_xcom, dag=dag ) list_jobs_limit = CloudRunListJobsOperator( task_id=list_jobs_limit_task_name, project_id=PROJECT_ID, region=region, dag=dag, limit=1 ) assert_jobs_limit = PythonOperator(task_id="assert-jobs-limit", python_callable=_assert_one_job, dag=dag) # [START howto_operator_cloud_run_list_jobs] list_jobs = CloudRunListJobsOperator( task_id=list_jobs_task_name, project_id=PROJECT_ID, region=region, dag=dag ) # [END howto_operator_cloud_run_list_jobs] assert_jobs = PythonOperator(task_id="assert-jobs", python_callable=_assert_jobs, dag=dag) # [START howto_operator_cloud_update_job] update_job1 = CloudRunUpdateJobOperator( task_id=update_job1_task_name, project_id=PROJECT_ID, region=region, job_name=job1_name, job=_create_job_instance_with_label(), dag=dag, ) # [END howto_operator_cloud_update_job] assert_job_updated = PythonOperator( task_id="assert-job-updated", python_callable=_assert_updated_job, dag=dag ) # [START howto_operator_cloud_delete_job] delete_job1 = CloudRunDeleteJobOperator( task_id="delete-job1", project_id=PROJECT_ID, region=region, job_name=job1_name, dag=dag, trigger_rule=TriggerRule.ALL_DONE, ) # [END howto_operator_cloud_delete_job] delete_job2 = CloudRunDeleteJobOperator( task_id="delete-job2", project_id=PROJECT_ID, region=region, job_name=job2_name, dag=dag, trigger_rule=TriggerRule.ALL_DONE, ) delete_job3 = CloudRunDeleteJobOperator( task_id="delete-job3", project_id=PROJECT_ID, region=region, job_name=job3_name, dag=dag, trigger_rule=TriggerRule.ALL_DONE, ) ( (create1, create2, create3) >> assert_created_jobs >> (execute1, execute2, execute3) >> assert_executed_jobs >> list_jobs_limit >> assert_jobs_limit >> list_jobs >> assert_jobs >> update_job1 >> assert_job_updated >> (delete_job1, delete_job2, delete_job3) ) from dev.tests_common.test_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 dev.tests_common.test_utils.system_tests 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)

Was this entry helpful?