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"""
Example Airflow DAG for testing Google DataPipelines Create Data Pipeline Operator.
"""
from __future__ import annotations
import os
from datetime import datetime
from pathlib import Path
from airflow import models
from airflow.providers.google.cloud.operators.datapipeline import (
CreateDataPipelineOperator,
RunDataPipelineOperator,
)
from airflow.providers.google.cloud.operators.gcs import GCSCreateBucketOperator, GCSDeleteBucketOperator
from airflow.providers.google.cloud.transfers.local_to_gcs import LocalFilesystemToGCSOperator
from airflow.utils.trigger_rule import TriggerRule
[docs]DAG_ID = "google-datapipeline"
[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]GCP_PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT")
[docs]GCP_LOCATION = os.environ.get("location", "us-central1")
[docs]PIPELINE_NAME = os.environ.get("DATA_PIPELINE_NAME", "defualt-pipeline-name")
[docs]PIPELINE_TYPE = "PIPELINE_TYPE_BATCH"
[docs]BUCKET_NAME = f"bucket_{DAG_ID}_{ENV_ID}"
[docs]FILE_NAME = "kinglear.txt"
[docs]TEMPLATE_FILE = "word-count.json"
[docs]DATAPIPELINES_JOB_NAME = "test-job-name"
[docs]TEMP_LOCATION = f"gs://{BUCKET_NAME}/temp"
[docs]GCS_PATH = f"gs://{BUCKET_NAME}/templates/{TEMPLATE_FILE}"
[docs]OUTPUT = f"gs://{BUCKET_NAME}/results/hello"
[docs]FILE_LOCAL_PATH = str(Path(__file__).parent / "resources" / FILE_NAME)
[docs]TEMPLATE_LOCAL_PATH = str(Path(__file__).parent / "resources" / TEMPLATE_FILE)
with models.DAG(
DAG_ID,
schedule="@once",
start_date=datetime(2021, 1, 1),
catchup=False,
tags=["example", "datapipeline"],
) as dag:
[docs] create_bucket = GCSCreateBucketOperator(task_id="create_bucket", bucket_name=BUCKET_NAME)
upload_file = LocalFilesystemToGCSOperator(
task_id="upload_file_to_bucket",
src=FILE_LOCAL_PATH,
dst=FILE_NAME,
bucket=BUCKET_NAME,
)
upload_template = LocalFilesystemToGCSOperator(
task_id="upload_template_to_bucket",
src=TEMPLATE_LOCAL_PATH,
dst=TEMPLATE_FILE,
bucket=BUCKET_NAME,
)
# [START howto_operator_create_data_pipeline]
create_data_pipeline = CreateDataPipelineOperator(
task_id="create_data_pipeline",
project_id=GCP_PROJECT_ID,
location=GCP_LOCATION,
body={
"name": f"projects/{GCP_PROJECT_ID}/locations/{GCP_LOCATION}/pipelines/{PIPELINE_NAME}",
"type": PIPELINE_TYPE,
"workload": {
"dataflowFlexTemplateRequest": {
"launchParameter": {
"containerSpecGcsPath": GCS_PATH,
"jobName": DATAPIPELINES_JOB_NAME,
"environment": {"tempLocation": TEMP_LOCATION},
"parameters": {
"inputFile": INPUT_FILE,
"output": OUTPUT,
},
},
"projectId": GCP_PROJECT_ID,
"location": GCP_LOCATION,
}
},
},
)
# [END howto_operator_create_data_pipeline]
delete_bucket = GCSDeleteBucketOperator(
task_id="delete_bucket", bucket_name=BUCKET_NAME, trigger_rule=TriggerRule.ALL_DONE
)
(create_bucket >> upload_file >> upload_template >> create_data_pipeline >> delete_bucket)
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()
# [START howto_operator_run_data_pipeline]
run_data_pipeline = RunDataPipelineOperator(
task_id="run_data_pipeline",
data_pipeline_name=PIPELINE_NAME,
project_id=GCP_PROJECT_ID,
)
# [END howto_operator_run_data_pipeline]
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)