[v3-0-test] Fix Pydantic ForwardRef error by reordering discrimin…

…ated union definitions (#50688) In some rare cases, the DAG parse subprocess (`DagFileProcessorProcess`) could raise a `PydanticUserError` related to unresolved ForwardRefs in the discriminated union ToDagProcessor. This was caused by `TypeAdapter[ToDagProcessor]` being instantiated before `DagFileParseRequest` was defined. While this is not always reproducible, it can happen in forked subprocesses depending on import order. This change moves the union definitions (`ToDagProcessor`, `ToManager`) after the relevant Pydantic models are declared, ensuring all references are fully resolved at definition time. closes #50530 (cherry picked from commit 672ec99) Co-authored-by: Kaxil Naik <kaxilnaik@gmail.com>
apache · kaxil · May 20, 2025 · May 16, 2025 · May 19, 2025 · b9f9aa5a8f935d08cd6a244a6b7879a84e900b5d
commit b9f9aa5a8f935d08cd6a244a6b7879a84e900b5d
@@ -54,13 +54,47 @@
     from airflow.sdk.definitions.context import Context
     from airflow.typing_compat import Self
 
+
+class DagFileParseRequest(BaseModel):
+    """
+    Request for DAG File Parsing.
+
+    This is the request that the manager will send to the DAG parser with the dag file and
+    any other necessary metadata.
+    """
+
+    file: str
+
+    bundle_path: Path
+    """Passing bundle path around lets us figure out relative file path."""
+
+    requests_fd: int
+    callback_requests: list[CallbackRequest] = Field(default_factory=list)
+    type: Literal["DagFileParseRequest"] = "DagFileParseRequest"
+
+
+class DagFileParsingResult(BaseModel):
+    """
+    Result of DAG File Parsing.
+
+    This is the result of a successful DAG parse, in this class, we gather all serialized DAGs,
+    import errors and warnings to send back to the scheduler to store in the DB.
+    """
+
+    fileloc: str
+    serialized_dags: list[LazyDeserializedDAG]
+    warnings: list | None = None
+    import_errors: dict[str, str] | None = None
+    type: Literal["DagFileParsingResult"] = "DagFileParsingResult"
+
+
 ToManager = Annotated[
-    Union["DagFileParsingResult", GetConnection, GetVariable, PutVariable, DeleteVariable],
+    Union[DagFileParsingResult, GetConnection, GetVariable, PutVariable, DeleteVariable],
     Field(discriminator="type"),
 ]
 
 ToDagProcessor = Annotated[
-    Union["DagFileParseRequest", ConnectionResult, VariableResult, ErrorResponse, OKResponse],
+    Union[DagFileParseRequest, ConnectionResult, VariableResult, ErrorResponse, OKResponse],
     Field(discriminator="type"),
 ]
 
@@ -182,39 +216,6 @@ def _execute_dag_callbacks(dagbag: DagBag, request: DagCallbackRequest, log: Fil
             Stats.incr("dag.callback_exceptions", tags={"dag_id": request.dag_id})
 
 
-class DagFileParseRequest(BaseModel):
-    """
-    Request for DAG File Parsing.
-
-    This is the request that the manager will send to the DAG parser with the dag file and
-    any other necessary metadata.
-    """
-
-    file: str
-
-    bundle_path: Path
-    """Passing bundle path around lets us figure out relative file path."""
-
-    requests_fd: int
-    callback_requests: list[CallbackRequest] = Field(default_factory=list)
-    type: Literal["DagFileParseRequest"] = "DagFileParseRequest"
-
-
-class DagFileParsingResult(BaseModel):
-    """
-    Result of DAG File Parsing.
-
-    This is the result of a successful DAG parse, in this class, we gather all serialized DAGs,
-    import errors and warnings to send back to the scheduler to store in the DB.
-    """
-
-    fileloc: str
-    serialized_dags: list[LazyDeserializedDAG]
-    warnings: list | None = None
-    import_errors: dict[str, str] | None = None
-    type: Literal["DagFileParsingResult"] = "DagFileParsingResult"
-
-
 def in_process_api_server() -> InProcessExecutionAPI:
     from airflow.api_fastapi.execution_api.app import InProcessExecutionAPI