ferruzzi commented on code in PR #70421: URL: https://github.com/apache/airflow/pull/70421#discussion_r3732484703
########## airflow-core/tests/unit/models/test_prune_deadlines.py: ########## @@ -0,0 +1,137 @@ +# 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. +""" +Adversarial QA coverage for ``Deadline.prune_deadlines``. Review Comment: Claude comments? ########## airflow-core/tests/unit/models/test_prune_deadlines.py: ########## @@ -0,0 +1,137 @@ +# 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. +""" +Adversarial QA coverage for ``Deadline.prune_deadlines``. + +``prune_deadlines`` is the batch-delete path the scheduler invokes (via +``DagRun.update_state`` -> ``dagrun.py:1237``) when a DagRun completes on time: Review Comment: This whole docstring is odd, but the line number in particular is pretty pointless and will drift in no time, if it hasn't already. ########## airflow-core/tests/unit/models/test_deadline_alert.py: ########## @@ -117,6 +117,35 @@ def test_deadline_alert_repr(self, deadline_alert_orm, deadline_reference): assert "interval=1m" in repr_str assert repr(deadline_alert_orm.callback_def) in repr_str + @pytest.mark.parametrize( + ("interval", "expected"), + [ + # Post-0117 shape: interval is the serialized dict, not a bare number. + pytest.param( + {"__classname__": "datetime.timedelta", "__data__": 7200.0}, "interval=2h", id="timedelta_2h" + ), + # A corrupted dict without ``__data__`` must still render (no raise) as dynamic. + pytest.param({"unexpected": "shape"}, "interval=dynamic", id="corrupted_dict_dynamic"), + ], + ) + def test_deadline_alert_repr_does_not_raise_on_json_dict_interval( + self, deadline_alert_orm, interval, expected + ): + """``DeadlineAlert.__repr__`` must never raise for the PRODUCTION (JSON-dict) ``interval`` shape. Review Comment: Similar to above, we don't generally have a novel for a test docstring when the test's name is usually pretty self-documenting. ########## airflow-core/tests/unit/models/test_prune_deadlines.py: ########## @@ -0,0 +1,137 @@ +# 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. +""" +Adversarial QA coverage for ``Deadline.prune_deadlines``. + +``prune_deadlines`` is the batch-delete path the scheduler invokes (via +``DagRun.update_state`` -> ``dagrun.py:1237``) when a DagRun completes on time: +deadlines that no longer need to fire are removed. These tests drill into the +on-time/overdue/pending selection logic, the (lack of) batching, callback +cascade behaviour, and concurrent-mutation edge cases against a real DB. +""" + +from __future__ import annotations + +from datetime import timedelta +from typing import TYPE_CHECKING + +import pytest +import time_machine +from sqlalchemy import select + +from airflow.models import DagRun +from airflow.models.callback import Callback +from airflow.models.deadline import Deadline +from airflow.providers.standard.operators.empty import EmptyOperator +from airflow.sdk.definitions.callback import AsyncCallback +from airflow.utils.state import DagRunState + +from tests_common.test_utils import db +from unit.models import DEFAULT_DATE + +if TYPE_CHECKING: + from sqlalchemy.orm import Session + +DAG_ID = "qaw18_prune_dag" Review Comment: "qaw18"?? ########## airflow-core/src/airflow/models/deadline_alert.py: ########## @@ -57,11 +57,14 @@ def __repr__(self): interval_seconds = None + # Legacy rows store a bare number instead of a serialized dict. if isinstance(self.interval, (int, float)): interval_seconds = int(self.interval) - elif isinstance(self.interval, datetime.timedelta): - interval_seconds = int(self.interval.total_seconds()) + elif isinstance(self.interval, dict): + data = self.interval.get("__data__") + if isinstance(data, (int, float)): + interval_seconds = int(data) Review Comment: It might be safer to check if `__classname__ == "datetime.timedelta"` instead, otherwise I think this could catch a broader scope than intended. I may be overthinking this one though. ########## airflow-core/tests/unit/models/test_prune_deadlines.py: ########## @@ -0,0 +1,137 @@ +# 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. +""" +Adversarial QA coverage for ``Deadline.prune_deadlines``. + +``prune_deadlines`` is the batch-delete path the scheduler invokes (via +``DagRun.update_state`` -> ``dagrun.py:1237``) when a DagRun completes on time: +deadlines that no longer need to fire are removed. These tests drill into the +on-time/overdue/pending selection logic, the (lack of) batching, callback +cascade behaviour, and concurrent-mutation edge cases against a real DB. +""" + +from __future__ import annotations + +from datetime import timedelta +from typing import TYPE_CHECKING + +import pytest +import time_machine +from sqlalchemy import select + +from airflow.models import DagRun +from airflow.models.callback import Callback +from airflow.models.deadline import Deadline +from airflow.providers.standard.operators.empty import EmptyOperator +from airflow.sdk.definitions.callback import AsyncCallback +from airflow.utils.state import DagRunState + +from tests_common.test_utils import db +from unit.models import DEFAULT_DATE + +if TYPE_CHECKING: + from sqlalchemy.orm import Session + +DAG_ID = "qaw18_prune_dag" + + +async def _qaw18_callback(): + pass + + +CALLBACK_PATH = f"{__name__}.{_qaw18_callback.__name__}" + + +def _clean_db(): + db.clear_db_dags() + db.clear_db_runs() + db.clear_db_deadline() + + [email protected] +def dagrun(session, dag_maker): + with dag_maker(DAG_ID): + EmptyOperator(task_id="task_id") + with time_machine.travel(DEFAULT_DATE): + dag_maker.create_dagrun(state=DagRunState.QUEUED, logical_date=DEFAULT_DATE) + session.commit() + return session.scalars(select(DagRun)).one() + + +def _make_deadline(session: Session, *, dagrun_id: int, deadline_time, state=None) -> Deadline: + deadline = Deadline( + deadline_time=deadline_time, + callback=AsyncCallback(CALLBACK_PATH), + dagrun_id=dagrun_id, + dag_id=DAG_ID, + deadline_alert_id=None, + ) + session.add(deadline) + session.flush() + if state is not None: + deadline.callback.state = state + session.add(deadline.callback) + session.flush() + return deadline + + [email protected]_test +class TestPruneDeadlines: + @staticmethod + def setup_method(): + _clean_db() + Review Comment: If we need to clean the db before our tests, then something else is leaving artifacts that should not be there, this will hide issues. ########## airflow-core/src/airflow/serialization/definitions/deadline.py: ########## @@ -320,7 +320,15 @@ def serialize_reference(self) -> dict: def deserialize_reference(cls, reference_data: dict): from airflow.serialization.helpers import find_registered_custom_deadline_reference - custom_class = find_registered_custom_deadline_reference(reference_data["__class_path"]) + class_path = reference_data.get("__class_path") + if not class_path: + raise ValueError( Review Comment: Better messaging. 👍 -- This is an automated message from the Apache Git Service. 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