[GitHub] [airflow] Taragolis commented on a diff in pull request #29776: Add Pydantic-powered ORM models serialization for internal API.

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

Taragolis commented on code in PR #29776:
URL: https://github.com/apache/airflow/pull/29776#discussion_r1118547021


##########
tests/models/test_pydantic_models.py:
##########
@@ -0,0 +1,151 @@
+#
+# 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.
+from __future__ import annotations
+
+from pydantic import parse_raw_as
+
+from airflow.jobs.local_task_job import LocalTaskJob
+from airflow.jobs.pydantic.base_job import BaseJobPydantic
+from airflow.models.dataset import (
+    DagScheduleDatasetReference,
+    DatasetEvent,
+    DatasetModel,
+    TaskOutletDatasetReference,
+)
+from airflow.models.pydantic.dag_run import DagRunPydantic
+from airflow.models.pydantic.dataset import DatasetEventPydantic
+from airflow.models.pydantic.taskinstance import TaskInstancePydantic
+from airflow.utils import timezone
+from airflow.utils.state import State
+from airflow.utils.types import DagRunType
+from tests.models import DEFAULT_DATE
+
+
+def test_serializing_pydantic_task_instance(session, create_task_instance):
+    dag_id = "test-dag"
+    ti = create_task_instance(dag_id=dag_id, session=session)
+    ti.state = State.RUNNING
+    ti.next_kwargs = {"foo": "bar"}
+    session.commit()
+
+    pydantic_task_instance = TaskInstancePydantic.from_orm(ti)
+
+    json_string = pydantic_task_instance.json()
+    print(json_string)

Review Comment:
   Just a wondering why the choise is `pydantic` and not `attrs` or `dataclasses` which we already use in Airflow and supported in SQLA:
   - [2.0.x](https://docs.sqlalchemy.org/en/20/orm/dataclasses.html#integration-with-dataclasses-and-attrs)
   - [1.4.x](https://docs.sqlalchemy.org/en/14/orm/dataclasses.html#integration-with-dataclasses-and-attrs)



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