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Example Airflow DAG for testing Google Dataflow Beam Pipeline Operator with Python.

from __future__ import annotations

import os
from datetime import datetime

from airflow.models.dag import DAG
from airflow.providers.apache.beam.hooks.beam import BeamRunnerType
from airflow.providers.apache.beam.operators.beam import BeamRunPythonPipelineOperator
from import DataflowStopJobOperator
from import GCSCreateBucketOperator, GCSDeleteBucketOperator
from airflow.utils.trigger_rule import TriggerRule

[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]DAG_ID = "dataflow_native_python"
[docs]RESOURCE_DATA_BUCKET = "airflow-system-tests-resources"
[docs]BUCKET_NAME = f"bucket_{DAG_ID}_{ENV_ID}"
[docs]GCS_TMP = f"gs://{BUCKET_NAME}/temp/"
[docs]GCS_STAGING = f"gs://{BUCKET_NAME}/staging/"
[docs]GCS_OUTPUT = f"gs://{BUCKET_NAME}/output"
[docs]GCS_PYTHON_SCRIPT = f"gs://{RESOURCE_DATA_BUCKET}/dataflow/python/"
[docs]LOCATION = "europe-west3"
[docs]default_args = { "dataflow_default_options": { "tempLocation": GCS_TMP, "stagingLocation": GCS_STAGING, } }
with DAG( DAG_ID, default_args=default_args, schedule="@once", start_date=datetime(2021, 1, 1), catchup=False, tags=["example", "dataflow"], ) as dag:
[docs] create_bucket = GCSCreateBucketOperator(task_id="create_bucket", bucket_name=BUCKET_NAME)
# [START howto_operator_start_python_job] start_python_job = BeamRunPythonPipelineOperator( runner=BeamRunnerType.DataflowRunner, task_id="start_python_job", py_file=GCS_PYTHON_SCRIPT, py_options=[], pipeline_options={ "output": GCS_OUTPUT, }, py_requirements=["apache-beam[gcp]==2.47.0"], py_interpreter="python3", py_system_site_packages=False, dataflow_config={"location": LOCATION, "job_name": "start_python_job"}, ) # [END howto_operator_start_python_job] start_python_job_local = BeamRunPythonPipelineOperator( task_id="start_python_job_local", py_file="apache_beam.examples.wordcount", py_options=["-m"], pipeline_options={ "output": GCS_OUTPUT, }, py_requirements=["apache-beam[gcp]==2.47.0"], py_interpreter="python3", py_system_site_packages=False, ) # [START howto_operator_stop_dataflow_job] stop_dataflow_job = DataflowStopJobOperator( task_id="stop_dataflow_job", location=LOCATION, job_name_prefix="start-python-pipeline", ) # [END howto_operator_stop_dataflow_job] delete_bucket = GCSDeleteBucketOperator( task_id="delete_bucket", bucket_name=BUCKET_NAME, trigger_rule=TriggerRule.ALL_DONE ) ( # TEST SETUP create_bucket # TEST BODY >> start_python_job >> start_python_job_local >> stop_dataflow_job # TEST TEARDOWN >> 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() from tests.system.utils import get_test_run # noqa: E402 # Needed to run the example DAG with pytest (see: tests/system/
[docs]test_run = get_test_run(dag)

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