[GitHub] [airflow] vincbeck commented on a diff in pull request #28900: Convert DagFileProcessor.execute_callbacks to Internal API

["vincbeck (via GitHub)" <gi...@apache.org>]

vincbeck commented on code in PR #28900:
URL: https://github.com/apache/airflow/pull/28900#discussion_r1131330638


##########
airflow/models/pydantic/dagrun.py:
##########
@@ -14,35 +14,32 @@
 # KIND, either express or implied.  See the License for the
 # specific language governing permissions and limitations
 # under the License.
+from __future__ import annotations
 
 from datetime import datetime
-from typing import List, Optional
 
 from pydantic import BaseModel as BaseModelPydantic
 
-from airflow.models.pydantic.dataset import DatasetEventPydantic
-
 
 class DagRunPydantic(BaseModelPydantic):
     """Serializable representation of the DagRun ORM SqlAlchemyModel used by internal API."""
 
     id: int
     dag_id: str
-    queued_at: Optional[datetime]
+    queued_at: datetime | None
     execution_date: datetime
-    start_date: Optional[datetime]
-    end_date: Optional[datetime]
+    start_date: datetime | None
+    end_date: datetime | None
     state: str
-    run_id: Optional[str]
-    creating_job_id: Optional[int]
+    run_id: str | None
+    creating_job_id: int | None
     external_trigger: bool
     run_type: str
-    data_interval_start: Optional[datetime]
-    data_interval_end: Optional[datetime]
-    last_scheduling_decision: Optional[datetime]
-    dag_hash: Optional[str]
+    data_interval_start: datetime | None
+    data_interval_end: datetime | None
+    last_scheduling_decision: datetime | None
+    dag_hash: str | None
     updated_at: datetime
-    consumed_dataset_events: List[DatasetEventPydantic]

Review Comment:
   I could not find this one in `airflow/models/dag.py`, hence I removed it. Again, I might miss something



##########
airflow/models/pydantic/dagrun.py:
##########
@@ -14,35 +14,32 @@
 # KIND, either express or implied.  See the License for the

Review Comment:
   I renamed this one to make sense with dagrun.py in `airflow/models`. Happy to revert if it does not make sense 



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