Source code for airflow.example_dags.example_dataset_alias_with_no_taskflow

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"""
Example DAG for demonstrating the behavior of the DatasetAlias feature in Airflow, including conditional and
dataset expression-based scheduling.

Notes on usage:

Turn on all the DAGs.

Before running any DAG, the schedule of the "dataset_alias_example_alias_consumer_with_no_taskflow" DAG will show as "unresolved DatasetAlias".
This is expected because the dataset alias has not been resolved into any dataset yet.

Once the "dataset_s3_bucket_producer_with_no_taskflow" DAG is triggered, the "dataset_s3_bucket_consumer_with_no_taskflow" DAG should be triggered upon completion.
This is because the dataset alias "example-alias-no-taskflow" is used to add a dataset event to the dataset "s3://bucket/my-task-with-no-taskflow"
during the "produce_dataset_events_through_dataset_alias_with_no_taskflow" task. Also, the schedule of the "dataset_alias_example_alias_consumer_with_no_taskflow" DAG should change to "Dataset" as
the dataset alias "example-alias-no-taskflow" is now resolved to the dataset "s3://bucket/my-task-with-no-taskflow" and this DAG should also be triggered.
"""

from __future__ import annotations

import pendulum

from airflow import DAG
from airflow.datasets import Dataset, DatasetAlias
from airflow.operators.python import PythonOperator

with DAG(
    dag_id="dataset_s3_bucket_producer_with_no_taskflow",
    start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
    schedule=None,
    catchup=False,
    tags=["producer", "dataset"],
):

[docs] def produce_dataset_events(): pass
PythonOperator( task_id="produce_dataset_events", outlets=[Dataset("s3://bucket/my-task-with-no-taskflow")], python_callable=produce_dataset_events, ) with DAG( dag_id="dataset_alias_example_alias_producer_with_no_taskflow", start_date=pendulum.datetime(2021, 1, 1, tz="UTC"), schedule=None, catchup=False, tags=["producer", "dataset-alias"], ):
[docs] def produce_dataset_events_through_dataset_alias_with_no_taskflow(*, outlet_events=None): bucket_name = "bucket" object_path = "my-task" outlet_events["example-alias-no-taskflow"].add(Dataset(f"s3://{bucket_name}/{object_path}"))
PythonOperator( task_id="produce_dataset_events_through_dataset_alias_with_no_taskflow", outlets=[DatasetAlias("example-alias-no-taskflow")], python_callable=produce_dataset_events_through_dataset_alias_with_no_taskflow, ) with DAG( dag_id="dataset_s3_bucket_consumer_with_no_taskflow", start_date=pendulum.datetime(2021, 1, 1, tz="UTC"), schedule=[Dataset("s3://bucket/my-task-with-no-taskflow")], catchup=False, tags=["consumer", "dataset"], ):
[docs] def consume_dataset_event(): pass
PythonOperator(task_id="consume_dataset_event", python_callable=consume_dataset_event) with DAG( dag_id="dataset_alias_example_alias_consumer_with_no_taskflow", start_date=pendulum.datetime(2021, 1, 1, tz="UTC"), schedule=[DatasetAlias("example-alias-no-taskflow")], catchup=False, tags=["consumer", "dataset-alias"], ):
[docs] def consume_dataset_event_from_dataset_alias(*, inlet_events=None): for event in inlet_events[DatasetAlias("example-alias-no-taskflow")]: print(event)
PythonOperator( task_id="consume_dataset_event_from_dataset_alias", python_callable=consume_dataset_event_from_dataset_alias, inlets=[DatasetAlias("example-alias-no-taskflow")], )

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