Lee-W commented on code in PR #63962:
URL: https://github.com/apache/airflow/pull/63962#discussion_r2963857953
##########
airflow-core/src/airflow/jobs/scheduler_job_runner.py:
##########
@@ -1912,17 +1912,18 @@ def _create_dag_runs(self, dag_models:
Collection[DagModel], session: Session) -
active_runs=active_runs_of_dags.get(dag_model.dag_id),
)
continue
- if dag_model.next_dagrun is None and
dag_model.timetable_partitioned is False:
+ if dag_model.next_dagrun is None and not
dag_model.timetable_partitioned:
self.log.error(
"dag_model.next_dagrun is None; expected datetime",
dag_id=dag_model.dag_id,
)
continue
if dag_model.next_dagrun_create_after is None:
- self.log.error(
- "dag_model.next_dagrun_create_after is None; expected
datetime",
- dag_id=dag_model.dag_id,
- )
+ if not dag_model.timetable_partitioned:
+ self.log.error(
+ "dag_model.next_dagrun_create_after is None; expected
datetime",
+ dag_id=dag_model.dag_id,
+ )
Review Comment:
```suggestion
if dag_model.timetable_partitioned is False:
# non partition-aware Dags
if dag_model.next_dagrun is None:
self.log.error(
"dag_model.next_dagrun is None; expected datetime",
dag_id=dag_model.dag_id,
)
continue
if dag_model.next_dagrun_create_after is None:
self.log.error(
"dag_model.next_dagrun_create_after is None;
expected datetime",
dag_id=dag_model.dag_id,
)
continue
else:
# partition-aware Dags
if dag_model.partition_key is None:
self.log.error(
"dag_model.next_dagrun_partition_key is None;
expected str",
dag_id=dag_model.dag_id,
)
```
##########
airflow-core/src/airflow/jobs/scheduler_job_runner.py:
##########
@@ -1912,17 +1912,18 @@ def _create_dag_runs(self, dag_models:
Collection[DagModel], session: Session) -
active_runs=active_runs_of_dags.get(dag_model.dag_id),
)
continue
- if dag_model.next_dagrun is None and
dag_model.timetable_partitioned is False:
+ if dag_model.next_dagrun is None and not
dag_model.timetable_partitioned:
self.log.error(
"dag_model.next_dagrun is None; expected datetime",
dag_id=dag_model.dag_id,
)
continue
if dag_model.next_dagrun_create_after is None:
- self.log.error(
- "dag_model.next_dagrun_create_after is None; expected
datetime",
- dag_id=dag_model.dag_id,
- )
+ if not dag_model.timetable_partitioned:
+ self.log.error(
+ "dag_model.next_dagrun_create_after is None; expected
datetime",
+ dag_id=dag_model.dag_id,
+ )
Review Comment:
but overall idea is right
##########
airflow-core/src/airflow/jobs/scheduler_job_runner.py:
##########
@@ -1912,17 +1912,18 @@ def _create_dag_runs(self, dag_models:
Collection[DagModel], session: Session) -
active_runs=active_runs_of_dags.get(dag_model.dag_id),
)
continue
- if dag_model.next_dagrun is None and
dag_model.timetable_partitioned is False:
+ if dag_model.next_dagrun is None and not
dag_model.timetable_partitioned:
self.log.error(
"dag_model.next_dagrun is None; expected datetime",
dag_id=dag_model.dag_id,
)
continue
if dag_model.next_dagrun_create_after is None:
- self.log.error(
- "dag_model.next_dagrun_create_after is None; expected
datetime",
- dag_id=dag_model.dag_id,
- )
+ if not dag_model.timetable_partitioned:
+ self.log.error(
+ "dag_model.next_dagrun_create_after is None; expected
datetime",
+ dag_id=dag_model.dag_id,
+ )
Review Comment:
I think we should do something like it
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