potiuk commented on a change in pull request #22311: URL: https://github.com/apache/airflow/pull/22311#discussion_r832105831
########## File path: tests/system/providers/google/bigquery/example_bigquery_dataset.py ########## @@ -0,0 +1,95 @@ +# +# 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 for Google BigQuery service testing dataset operations. +""" +import os +from datetime import datetime + +from airflow import models +from airflow.operators.bash import BashOperator +from airflow.providers.google.cloud.operators.bigquery import ( + BigQueryCreateEmptyDatasetOperator, + BigQueryDeleteDatasetOperator, + BigQueryGetDatasetOperator, + BigQueryUpdateDatasetOperator, +) +from airflow.utils.trigger_rule import TriggerRule + +ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID") +DAG_ID = "bigquery_dataset" + +DATASET_NAME = f"dataset_{DAG_ID}_{ENV_ID}" + + +with models.DAG( + DAG_ID, + schedule_interval="@once", + start_date=datetime(2021, 1, 1), + catchup=False, + tags=["example", "bigquery"], +) as dag: + # [START howto_operator_bigquery_create_dataset] + create_dataset = BigQueryCreateEmptyDatasetOperator(task_id="create_dataset", dataset_id=DATASET_NAME) + # [END howto_operator_bigquery_create_dataset] + + # [START howto_operator_bigquery_update_dataset] + update_dataset = BigQueryUpdateDatasetOperator( + task_id="update_dataset", + dataset_id=DATASET_NAME, + dataset_resource={"description": "Updated dataset"}, + ) + # [END howto_operator_bigquery_update_dataset] + + # [START howto_operator_bigquery_get_dataset] + get_dataset = BigQueryGetDatasetOperator(task_id="get-dataset", dataset_id=DATASET_NAME) + # [END howto_operator_bigquery_get_dataset] + + get_dataset_result = BashOperator( + task_id="get_dataset_result", + bash_command="echo \"{{ task_instance.xcom_pull('get-dataset')['id'] }}\"", + ) + + # [START howto_operator_bigquery_delete_dataset] + delete_dataset = BigQueryDeleteDatasetOperator( + task_id="delete_dataset", dataset_id=DATASET_NAME, delete_contents=True + ) + # [END howto_operator_bigquery_delete_dataset] + delete_dataset.trigger_rule = TriggerRule.ALL_DONE + + ( + # TEST BODY + create_dataset + >> update_dataset + >> get_dataset + >> get_dataset_result + # TEST TEARDOWN + >> delete_dataset + ) + + from tests.system.utils.watcher import watcher Review comment: Hmm. I thought a bit about our earlier discussion - https://github.com/apache/airflow/pull/22311#discussion_r829687607 with @ferruzzi and hmm. I changed my mind I think. I think we have an easy way to decrease the amount of code here indeed in almost the way suggested :). And remove one of the "pre-commit checks". ``` from tests.system.utils.watcher import watcher def get_test_run(dag, *, add_watcher: bool = False): def test_run(): if add_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() dag.clear(dag_run_state=State.NONE) dag.run() return test_run ``` And then in the DAG: ``` test_run = get_test_run(dag, add_watcher=True) ``` This way we; * do not need local import in the DAG * do not need the pre-commit to add watcher code * avoid code duplication WDYT? -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
