tests/dags/test_issue_1225.py

#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.


"""
DAG designed to test what happens when a DAG with pooled tasks is run
by a BackfillJob.
Addresses issue #1225.
"""
from datetime import datetime, timedelta

from airflow.models import DAG
from airflow.operators.dummy import DummyOperator
from airflow.operators.python import PythonOperator
from airflow.utils.trigger_rule import TriggerRule

DEFAULT_DATE = datetime(2016, 1, 1)
default_args = dict(start_date=DEFAULT_DATE, owner='airflow')


def fail():
    raise ValueError('Expected failure.')


# DAG tests backfill with pooled tasks
# Previously backfill would queue the task but never run it
dag1 = DAG(dag_id='test_backfill_pooled_task_dag', default_args=default_args)
dag1_task1 = DummyOperator(
    task_id='test_backfill_pooled_task',
    dag=dag1,
    pool='test_backfill_pooled_task_pool',
)

# dag2 has been moved to test_prev_dagrun_dep.py

# DAG tests that a Dag run that doesn't complete is marked failed
dag3 = DAG(dag_id='test_dagrun_states_fail', default_args=default_args)
dag3_task1 = PythonOperator(task_id='test_dagrun_fail', dag=dag3, python_callable=fail)
dag3_task2 = DummyOperator(
    task_id='test_dagrun_succeed',
    dag=dag3,
)
dag3_task2.set_upstream(dag3_task1)

# DAG tests that a Dag run that completes but has a failure is marked success
dag4 = DAG(dag_id='test_dagrun_states_success', default_args=default_args)
dag4_task1 = PythonOperator(
    task_id='test_dagrun_fail',
    dag=dag4,
    python_callable=fail,
)
dag4_task2 = DummyOperator(task_id='test_dagrun_succeed', dag=dag4, trigger_rule=TriggerRule.ALL_FAILED)
dag4_task2.set_upstream(dag4_task1)

# DAG tests that a Dag run that completes but has a root failure is marked fail
dag5 = DAG(dag_id='test_dagrun_states_root_fail', default_args=default_args)
dag5_task1 = DummyOperator(
    task_id='test_dagrun_succeed',
    dag=dag5,
)
dag5_task2 = PythonOperator(
    task_id='test_dagrun_fail',
    dag=dag5,
    python_callable=fail,
)

# DAG tests that a Dag run that is deadlocked with no states is failed
dag6 = DAG(dag_id='test_dagrun_states_deadlock', default_args=default_args)
dag6_task1 = DummyOperator(
    task_id='test_depends_on_past',
    depends_on_past=True,
    dag=dag6,
)
dag6_task2 = DummyOperator(
    task_id='test_depends_on_past_2',
    depends_on_past=True,
    dag=dag6,
)
dag6_task2.set_upstream(dag6_task1)


# DAG tests that a Dag run that doesn't complete but has a root failure is marked running
dag8 = DAG(dag_id='test_dagrun_states_root_fail_unfinished', default_args=default_args)
dag8_task1 = DummyOperator(
    task_id='test_dagrun_unfinished',  # The test will unset the task instance state after
    # running this test
    dag=dag8,
)
dag8_task2 = PythonOperator(
    task_id='test_dagrun_fail',
    dag=dag8,
    python_callable=fail,
)

# DAG tests that a Dag run that completes but has a root in the future is marked as success
dag9 = DAG(dag_id='test_dagrun_states_root_future', default_args=default_args)
dag9_task1 = DummyOperator(
    task_id='current',
    dag=dag9,
)
dag9_task2 = DummyOperator(
    task_id='future',
    dag=dag9,
    start_date=DEFAULT_DATE + timedelta(days=1),
)