Source code for airflow.example_dags.example_datasets

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"""
Example DAG for demonstrating behavior of Datasets feature.

Notes on usage:

Turn on all the dags.

DAG example_dataset_dag1 should run because it's on a schedule.

After example_dataset_dag1 runs, example_dataset_dag3_req_dag1 should be triggered immediately
because its only dataset dependency is managed by example_dataset_dag1.

No other dags should be triggered.  Note that even though example_dataset_dag4_req_dag1_dag2 depends on
the dataset in example_dataset_dag1, it will not be triggered until example_dataset_dag2 runs
(and example_dataset_dag2 is left with no schedule so that we can trigger it manually).

Next, trigger example_dataset_dag2.  After example_dataset_dag2 finishes,
example_dataset_dag4_req_dag1_dag2 should run.

Dags example_dataset_dag5_req_dag1_D and example_dataset_dag6_req_DD should not run because they depend on
datasets that never get updated.
"""
from __future__ import annotations

import pendulum

from airflow import DAG, Dataset
from airflow.operators.bash import BashOperator

# [START dataset_def]
[docs]dag1_dataset = Dataset('s3://dag1/output_1.txt', extra={'hi': 'bye'})
# [END dataset_def]
[docs]dag2_dataset = Dataset('s3://dag2/output_1.txt', extra={'hi': 'bye'})

with DAG(
    dag_id='dataset_produces_1',
    catchup=False,
    start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
    schedule='@daily',
    tags=['produces', 'dataset-scheduled'],
) as dag1:
    # [START task_outlet]
    BashOperator(outlets=[dag1_dataset], task_id='producing_task_1', bash_command="sleep 5")
    # [END task_outlet]

with DAG(
    dag_id='dataset_produces_2',
    catchup=False,
    start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
    schedule=None,
    tags=['produces', 'dataset-scheduled'],
) as dag2:
    BashOperator(outlets=[dag2_dataset], task_id='producing_task_2', bash_command="sleep 5")

# [START dag_dep]
with DAG(
    dag_id='dataset_consumes_1',
    catchup=False,
    start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
    schedule=[dag1_dataset],
    tags=['consumes', 'dataset-scheduled'],
) as dag3:
    # [END dag_dep]
    BashOperator(
        outlets=[Dataset('s3://consuming_1_task/dataset_other.txt')],
        task_id='consuming_1',
        bash_command="sleep 5",
    )

with DAG(
    dag_id='dataset_consumes_1_and_2',
    catchup=False,
    start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
    schedule=[dag1_dataset, dag2_dataset],
    tags=['consumes', 'dataset-scheduled'],
) as dag4:
    BashOperator(
        outlets=[Dataset('s3://consuming_2_task/dataset_other_unknown.txt')],
        task_id='consuming_2',
        bash_command="sleep 5",
    )

with DAG(
    dag_id='dataset_consumes_1_never_scheduled',
    catchup=False,
    start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
    schedule=[
        dag1_dataset,
        Dataset('s3://this-dataset-doesnt-get-triggered'),
    ],
    tags=['consumes', 'dataset-scheduled'],
) as dag5:
    BashOperator(
        outlets=[Dataset('s3://consuming_2_task/dataset_other_unknown.txt')],
        task_id='consuming_3',
        bash_command="sleep 5",
    )

with DAG(
    dag_id='dataset_consumes_unknown_never_scheduled',
    catchup=False,
    start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
    schedule=[
        Dataset('s3://unrelated/dataset3.txt'),
        Dataset('s3://unrelated/dataset_other_unknown.txt'),
    ],
    tags=['dataset-scheduled'],
) as dag6:
    BashOperator(
        task_id='unrelated_task',
        outlets=[Dataset('s3://unrelated_task/dataset_other_unknown.txt')],
        bash_command="sleep 5",
    )