seanghaeli commented on code in PR #68917:
URL: https://github.com/apache/airflow/pull/68917#discussion_r3807833711
##########
airflow-core/tests/unit/models/test_dagrun.py:
##########
@@ -1509,71 +1511,121 @@ def
test_dagrun_success_handles_empty_deadline_list(self, mock_prune, dag_maker,
mock_prune.assert_not_called()
assert dag_run.state == DagRunState.SUCCESS
- @mock.patch.object(Variable, "get")
+ @pytest.mark.parametrize(
+ ("interval", "failure"),
+ [
+ pytest.param(VariableInterval("missing_key"), nullcontext(),
id="missing_variable"),
+ pytest.param(
+ datetime.timedelta(hours=1),
+ mock.patch(
+
"airflow.serialization.definitions.dag.decode_deadline_alert",
+ autospec=True,
+ side_effect=ValueError("corrupt deadline alert blob"),
+ ),
+ id="decode_failure",
+ ),
+ pytest.param(
+ datetime.timedelta(hours=1),
+ mock.patch.object(
+ SerializedReferenceModels.FixedDatetimeDeadline,
+ "evaluate_with",
+ autospec=True,
+ side_effect=RuntimeError("evaluate_with failed"),
+ ),
+ id="evaluate_with_failure",
+ ),
+ ],
+ )
@mock.patch.object(Deadline, "prune_deadlines")
- def test_dagrun_deadline_variable_interval_stable(self, _, mock_get,
session, deadline_test_dag):
Review Comment:
It may not be a real gap, there's no real reason why a deadline would need
to re-resolve mid-run. So, my instinct is to leave it out for the present day.
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