Source code for tests.system.google.cloud.vertex_ai.example_vertex_ai_auto_ml_list_training

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"""
Example Airflow DAG for Google Vertex AI service testing Auto ML operations.
"""

from __future__ import annotations

import os
from datetime import datetime

from airflow.models.dag import DAG
from airflow.providers.google.cloud.operators.vertex_ai.auto_ml import ListAutoMLTrainingJobOperator


[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 = "vertex_ai_auto_ml_operations"


[docs]
REGION = "us-central1"



with DAG(
    f"{DAG_ID}_list_training_job",
    schedule="@once",
    start_date=datetime(2021, 1, 1),
    catchup=False,
    tags=["example", "vertex_ai", "auto_ml", "list_operation"],
) as dag:
    # [START how_to_cloud_vertex_ai_list_auto_ml_training_job_operator]

[docs]
    list_auto_ml_training_job = ListAutoMLTrainingJobOperator(
        task_id="list_auto_ml_training_job",
        region=REGION,
        project_id=PROJECT_ID,
    )

    # [END how_to_cloud_vertex_ai_list_auto_ml_training_job_operator]

    # ### Everything below this line is not part of example ###
    # ### Just for system tests purpose ###
    from 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 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)