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"""
Example Airflow DAG that shows how to use Google Dataprep.
"""
from __future__ import annotations
import os
from datetime import datetime
from airflow import models
from airflow.providers.google.cloud.operators.dataprep import (
DataprepCopyFlowOperator,
DataprepDeleteFlowOperator,
DataprepGetJobGroupOperator,
DataprepGetJobsForJobGroupOperator,
DataprepRunFlowOperator,
DataprepRunJobGroupOperator,
)
from airflow.providers.google.cloud.operators.gcs import GCSCreateBucketOperator, GCSDeleteBucketOperator
from airflow.providers.google.cloud.sensors.dataprep import DataprepJobGroupIsFinishedSensor
from airflow.utils.trigger_rule import TriggerRule
[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]DAG_ID = "example_dataprep"
[docs]GCP_PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT")
[docs]GCS_BUCKET_NAME = f"dataprep-bucket-{DAG_ID}-{ENV_ID}"
[docs]GCS_BUCKET_PATH = f"gs://{GCS_BUCKET_NAME}/task_results/"
[docs]FLOW_ID = os.environ.get("FLOW_ID")
[docs]RECIPE_ID = os.environ.get("RECIPE_ID")
[docs]RECIPE_NAME = os.environ.get("RECIPE_NAME")
[docs]WRITE_SETTINGS = (
{
"writesettings": [
{
"path": GCS_BUCKET_PATH,
"action": "create",
"format": "csv",
}
],
},
)
with models.DAG(
DAG_ID,
schedule="@once",
start_date=datetime(2021, 1, 1), # Override to match your needs
catchup=False,
tags=["example", "dataprep"],
render_template_as_native_obj=True,
) as dag:
[docs] create_bucket_task = GCSCreateBucketOperator(
task_id="create_bucket",
bucket_name=GCS_BUCKET_NAME,
project_id=GCP_PROJECT_ID,
)
# [START how_to_dataprep_run_job_group_operator]
run_job_group_task = DataprepRunJobGroupOperator(
task_id="run_job_group",
project_id=GCP_PROJECT_ID,
body_request={
"wrangledDataset": {"id": RECIPE_ID},
"overrides": WRITE_SETTINGS,
},
)
# [END how_to_dataprep_run_job_group_operator]
# [START how_to_dataprep_copy_flow_operator]
copy_task = DataprepCopyFlowOperator(
task_id="copy_flow",
project_id=GCP_PROJECT_ID,
flow_id=FLOW_ID,
name=f"dataprep_example_flow_{DAG_ID}_{ENV_ID}",
)
# [END how_to_dataprep_copy_flow_operator]
# [START how_to_dataprep_dataprep_run_flow_operator]
run_flow_task = DataprepRunFlowOperator(
task_id="run_flow",
project_id=GCP_PROJECT_ID,
flow_id="{{ task_instance.xcom_pull('copy_flow')['id'] }}",
body_request={
"overrides": {
RECIPE_NAME: WRITE_SETTINGS,
},
},
)
# [END how_to_dataprep_dataprep_run_flow_operator]
# [START how_to_dataprep_get_job_group_operator]
get_job_group_task = DataprepGetJobGroupOperator(
task_id="get_job_group",
project_id=GCP_PROJECT_ID,
job_group_id="{{ task_instance.xcom_pull('run_flow')['data'][0]['id'] }}",
embed="",
include_deleted=False,
)
# [END how_to_dataprep_get_job_group_operator]
# [START how_to_dataprep_get_jobs_for_job_group_operator]
get_jobs_for_job_group_task = DataprepGetJobsForJobGroupOperator(
task_id="get_jobs_for_job_group",
job_group_id="{{ task_instance.xcom_pull('run_flow')['data'][0]['id'] }}",
)
# [END how_to_dataprep_get_jobs_for_job_group_operator]
# [START how_to_dataprep_job_group_finished_sensor]
check_flow_status_sensor = DataprepJobGroupIsFinishedSensor(
task_id="check_flow_status",
job_group_id="{{ task_instance.xcom_pull('run_flow')['data'][0]['id'] }}",
)
# [END how_to_dataprep_job_group_finished_sensor]
# [START how_to_dataprep_job_group_finished_sensor]
check_job_group_status_sensor = DataprepJobGroupIsFinishedSensor(
task_id="check_job_group_status",
job_group_id="{{ task_instance.xcom_pull('run_job_group')['id'] }}",
)
# [END how_to_dataprep_job_group_finished_sensor]
# [START how_to_dataprep_delete_flow_operator]
delete_flow_task = DataprepDeleteFlowOperator(
task_id="delete_flow",
flow_id="{{ task_instance.xcom_pull('copy_flow')['id'] }}",
)
# [END how_to_dataprep_delete_flow_operator]
delete_flow_task.trigger_rule = TriggerRule.ALL_DONE
delete_bucket_task = GCSDeleteBucketOperator(
task_id="delete_bucket",
bucket_name=GCS_BUCKET_NAME,
trigger_rule=TriggerRule.ALL_DONE,
)
(
# TEST SETUP
create_bucket_task
>> copy_task
# TEST BODY
>> [run_job_group_task, run_flow_task]
>> get_job_group_task
>> get_jobs_for_job_group_task
# TEST TEARDOWN
>> check_flow_status_sensor
>> [delete_flow_task, check_job_group_status_sensor]
>> delete_bucket_task
)
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)
