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"""
Example Airflow DAG that demonstrates operators for the Google Cloud Video Intelligence service in the Google
Cloud Platform.
This DAG relies on the following OS environment variables:
* BUCKET_NAME - Google Cloud Storage bucket where the file exists.
"""
from __future__ import annotations
import os
from datetime import datetime
from google.api_core.retry import Retry
from airflow.models.baseoperator import chain
from airflow.models.dag import DAG
from airflow.providers.google.cloud.operators.gcs import GCSCreateBucketOperator, GCSDeleteBucketOperator
from airflow.providers.google.cloud.operators.video_intelligence import (
CloudVideoIntelligenceDetectVideoExplicitContentOperator,
CloudVideoIntelligenceDetectVideoLabelsOperator,
CloudVideoIntelligenceDetectVideoShotsOperator,
)
from airflow.providers.google.cloud.transfers.gcs_to_gcs import GCSToGCSOperator
from airflow.providers.standard.operators.bash import BashOperator
from airflow.utils.trigger_rule import TriggerRule
[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID", "default")
[docs]DAG_ID = "example_gcp_video_intelligence"
# Public bucket holding the sample data
[docs]BUCKET_NAME_SRC = "cloud-samples-data"
# Path to the data inside the public bucket
[docs]PATH_SRC = "video/cat.mp4"
# [START howto_operator_video_intelligence_os_args]
[docs]BUCKET_NAME_DST = f"bucket-src-{DAG_ID}-{ENV_ID}"
# [END howto_operator_video_intelligence_os_args]
# [START howto_operator_video_intelligence_other_args]
# [END howto_operator_video_intelligence_other_args]
with DAG(
DAG_ID,
schedule="@once",
start_date=datetime(2021, 1, 1),
catchup=False,
tags=["example"],
) as dag:
[docs] create_bucket = GCSCreateBucketOperator(task_id="create_bucket", bucket_name=BUCKET_NAME_DST)
copy_single_file = GCSToGCSOperator(
task_id="copy_single_gcs_file",
source_bucket=BUCKET_NAME_SRC,
source_object=PATH_SRC,
destination_bucket=BUCKET_NAME_DST,
destination_object=FILE_NAME,
)
# [START howto_operator_video_intelligence_detect_labels]
detect_video_label = CloudVideoIntelligenceDetectVideoLabelsOperator(
input_uri=INPUT_URI,
output_uri=None,
video_context=None,
timeout=5,
task_id="detect_video_label",
)
# [END howto_operator_video_intelligence_detect_labels]
# [START howto_operator_video_intelligence_detect_labels_result]
detect_video_label_result = BashOperator(
bash_command="echo {{ task_instance.xcom_pull('detect_video_label')"
"['annotationResults'][0]['shotLabelAnnotations'][0]['entity']}}",
task_id="detect_video_label_result",
)
# [END howto_operator_video_intelligence_detect_labels_result]
# [START howto_operator_video_intelligence_detect_explicit_content]
detect_video_explicit_content = CloudVideoIntelligenceDetectVideoExplicitContentOperator(
input_uri=INPUT_URI,
output_uri=None,
video_context=None,
retry=Retry(maximum=10.0),
timeout=5,
task_id="detect_video_explicit_content",
)
# [END howto_operator_video_intelligence_detect_explicit_content]
# [START howto_operator_video_intelligence_detect_explicit_content_result]
detect_video_explicit_content_result = BashOperator(
bash_command="echo {{ task_instance.xcom_pull('detect_video_explicit_content')"
"['annotationResults'][0]['explicitAnnotation']['frames'][0]}}",
task_id="detect_video_explicit_content_result",
)
# [END howto_operator_video_intelligence_detect_explicit_content_result]
# [START howto_operator_video_intelligence_detect_video_shots]
detect_video_shots = CloudVideoIntelligenceDetectVideoShotsOperator(
input_uri=INPUT_URI,
output_uri=None,
video_context=None,
retry=Retry(maximum=10.0),
timeout=5,
task_id="detect_video_shots",
)
# [END howto_operator_video_intelligence_detect_video_shots]
# [START howto_operator_video_intelligence_detect_video_shots_result]
detect_video_shots_result = BashOperator(
bash_command="echo {{ task_instance.xcom_pull('detect_video_shots')"
"['annotationResults'][0]['shotAnnotations'][0]}}",
task_id="detect_video_shots_result",
)
# [END howto_operator_video_intelligence_detect_video_shots_result]
delete_bucket = GCSDeleteBucketOperator(
task_id="delete_bucket", bucket_name=BUCKET_NAME_DST, trigger_rule=TriggerRule.ALL_DONE
)
chain(
# TEST SETUP
create_bucket,
copy_single_file,
# TEST BODY
detect_video_label,
detect_video_label_result,
detect_video_explicit_content,
detect_video_explicit_content_result,
detect_video_shots,
detect_video_shots_result,
# TEST TEARDOWN
delete_bucket,
)
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)