Upgrade to Pydantic 2

airflow/serialization/serde.py

@@ -319,7 +319,7 @@ def _is_pydantic(cls: Any) -> bool:
     Checking is done by attributes as it is significantly faster than
     using isinstance.
     """
-    return hasattr(cls, "__validators__") and hasattr(cls, "__fields__") and hasattr(cls, "dict")
+    return hasattr(cls, "model_config") and hasattr(cls, "model_fields") and hasattr(cls, "model_fields_set")
 
 
 def _register():

setup.cfg

@@ -122,7 +122,7 @@ install_requires =
     pendulum>=2.0
     pluggy>=1.0
     psutil>=4.2.0
-    pydantic>=1.10.0
+    pydantic>=2.3.0
     pygments>=2.0.1
     pyjwt>=2.0.0
     python-daemon>=3.0.0

setup.py

@@ -409,7 +409,11 @@ def write_version(filename: str = str(AIRFLOW_SOURCES_ROOT / "airflow" / "git_ve
 
 _devel_only_amazon = [
     "aws_xray_sdk",
-    "moto[cloudformation, glue]>=4.0",
+    "moto[glue]>=4.0",
+    # TODO: Remove the two below after https://github.com/aws/serverless-application-model/pull/3282
+    # gets released and add back "cloudformation" extra to moto above
+    "openapi-spec-validator >=0.2.8",
+    "jsonschema>=3.0",
     f"mypy-boto3-rds>={_MIN_BOTO3_VERSION}",
     f"mypy-boto3-redshift-data>={_MIN_BOTO3_VERSION}",
     f"mypy-boto3-s3>={_MIN_BOTO3_VERSION}",

tests/serialization/test_pydantic_models.py

@@ -17,8 +17,6 @@
 # under the License.
 from __future__ import annotations
 
-from pydantic import parse_raw_as
-
 from airflow.jobs.job import Job
 from airflow.jobs.local_task_job_runner import LocalTaskJobRunner
 from airflow.models.dataset import (
@@ -49,7 +47,7 @@ def test_serializing_pydantic_task_instance(session, create_task_instance):
     json_string = pydantic_task_instance.json()
     print(json_string)
 
-    deserialized_model = parse_raw_as(TaskInstancePydantic, json_string)
+    deserialized_model = TaskInstancePydantic.model_validate_json(json_string)
     assert deserialized_model.dag_id == dag_id
     assert deserialized_model.state == State.RUNNING
     assert deserialized_model.try_number == ti.try_number
@@ -68,7 +66,7 @@ def test_serializing_pydantic_dagrun(session, create_task_instance):
     json_string = pydantic_dag_run.json()
     print(json_string)
 
-    deserialized_model = parse_raw_as(DagRunPydantic, json_string)
+    deserialized_model = DagRunPydantic.model_validate_json(json_string)
     assert deserialized_model.dag_id == dag_id
     assert deserialized_model.state == State.RUNNING
 
@@ -85,7 +83,7 @@ def test_serializing_pydantic_local_task_job(session, create_task_instance):
     json_string = pydantic_job.json()
     print(json_string)
 
-    deserialized_model = parse_raw_as(JobPydantic, json_string)
+    deserialized_model = JobPydantic.model_validate_json(json_string)
     assert deserialized_model.dag_id == dag_id
     assert deserialized_model.job_type == "LocalTaskJob"
     assert deserialized_model.state == State.RUNNING
@@ -139,17 +137,17 @@ def test_serializing_pydantic_dataset_event(session, create_task_instance, creat
     json_string_dr = pydantic_dag_run.json()
     print(json_string_dr)
 
-    deserialized_model1 = parse_raw_as(DatasetEventPydantic, json_string1)
+    deserialized_model1 = DatasetEventPydantic.model_validate_json(json_string1)
     assert deserialized_model1.dataset.id == 1
     assert deserialized_model1.dataset.uri == "one"
     assert len(deserialized_model1.dataset.consuming_dags) == 1
     assert len(deserialized_model1.dataset.producing_tasks) == 1
 
-    deserialized_model2 = parse_raw_as(DatasetEventPydantic, json_string2)
+    deserialized_model2 = DatasetEventPydantic.model_validate_json(json_string2)
     assert deserialized_model2.dataset.id == 2
     assert deserialized_model2.dataset.uri == "two"
     assert len(deserialized_model2.dataset.consuming_dags) == 0
     assert len(deserialized_model2.dataset.producing_tasks) == 0
 
-    deserialized_dr = parse_raw_as(DagRunPydantic, json_string_dr)
+    deserialized_dr = DagRunPydantic.model_validate_json(json_string_dr)
     assert len(deserialized_dr.consumed_dataset_events) == 3