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Example Airflow DAG for Google Cloud Storage sensors.
from __future__ import annotations

import os
from datetime import datetime
from pathlib import Path

from airflow import models
from airflow.models.baseoperator import chain
from airflow.operators.bash import BashOperator
from import GCSCreateBucketOperator, GCSDeleteBucketOperator
from import (
from import LocalFilesystemToGCSOperator
from airflow.utils.trigger_rule import TriggerRule

[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT")
[docs]DAG_ID = "gcs_sensor"
[docs]BUCKET_NAME = f"bucket_{DAG_ID}_{ENV_ID}"
[docs]FILE_NAME = "example_upload.txt"
[docs]UPLOAD_FILE_PATH = str(Path(__file__).parent / "resources" / FILE_NAME)
[docs]def workaround_in_debug_executor(cls): """ DebugExecutor change sensor mode from poke to reschedule. Some sensors don't work correctly in reschedule mode. They are decorated with `poke_mode_only` decorator to fail when mode is changed. This method creates dummy property to overwrite it and force poke method to always return True. """ cls.mode = dummy_mode_property() cls.poke = lambda self, ctx: True
[docs]def dummy_mode_property(): def mode_getter(self): return self._mode def mode_setter(self, value): self._mode = value return property(mode_getter, mode_setter)
with models.DAG( DAG_ID, schedule="@once", start_date=datetime(2021, 1, 1), catchup=False, tags=["gcs", "example"], ) as dag:
[docs] create_bucket = GCSCreateBucketOperator( task_id="create_bucket", bucket_name=BUCKET_NAME, project_id=PROJECT_ID
) workaround_in_debug_executor(GCSUploadSessionCompleteSensor) # [START howto_sensor_gcs_upload_session_complete_task] gcs_upload_session_complete = GCSUploadSessionCompleteSensor( bucket=BUCKET_NAME, prefix=FILE_NAME, inactivity_period=15, min_objects=1, allow_delete=True, previous_objects=set(), task_id="gcs_upload_session_complete_task", ) # [END howto_sensor_gcs_upload_session_complete_task] # [START howto_sensor_object_update_exists_task] gcs_update_object_exists = GCSObjectUpdateSensor( bucket=BUCKET_NAME, object=FILE_NAME, task_id="gcs_object_update_sensor_task", ) # [END howto_sensor_object_update_exists_task] upload_file = LocalFilesystemToGCSOperator( task_id="upload_file", src=UPLOAD_FILE_PATH, dst=FILE_NAME, bucket=BUCKET_NAME, ) # [START howto_sensor_object_exists_task] gcs_object_exists = GCSObjectExistenceSensor( bucket=BUCKET_NAME, object=FILE_NAME, task_id="gcs_object_exists_task", ) # [END howto_sensor_object_exists_task] # [START howto_sensor_object_exists_task_async] gcs_object_exists_async = GCSObjectExistenceAsyncSensor( bucket=BUCKET_NAME, object=FILE_NAME, task_id="gcs_object_exists_task_async", ) # [END howto_sensor_object_exists_task_async] # [START howto_sensor_object_with_prefix_exists_task] gcs_object_with_prefix_exists = GCSObjectsWithPrefixExistenceSensor( bucket=BUCKET_NAME, prefix=FILE_NAME[:5], task_id="gcs_object_with_prefix_exists_task", ) # [END howto_sensor_object_with_prefix_exists_task] delete_bucket = GCSDeleteBucketOperator( task_id="delete_bucket", bucket_name=BUCKET_NAME, trigger_rule=TriggerRule.ALL_DONE ) sleep = BashOperator(task_id="sleep", bash_command="sleep 5") chain( # TEST SETUP create_bucket, sleep, upload_file, # TEST BODY [gcs_object_exists, gcs_object_exists_async, gcs_object_with_prefix_exists], # TEST TEARDOWN delete_bucket, ) chain( create_bucket, # TEST BODY gcs_upload_session_complete, gcs_update_object_exists, 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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