(superset) branch fix-semantic-layer-post-processing-typeerror created (now eab66ee4410)

[el...@apache.org]

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eschutho pushed a change to branch fix-semantic-layer-post-processing-typeerror
in repository https://gitbox.apache.org/repos/asf/superset.git


      at eab66ee4410 fix(semantic-layer): wrap raw pandas TypeError/DataError from post-processing as QueryObjectValidationError

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     new eab66ee4410 fix(semantic-layer): wrap raw pandas TypeError/DataError from post-processing as QueryObjectValidationError

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(superset) 01/01: fix(semantic-layer): wrap raw pandas TypeError/DataError from post-processing as QueryObjectValidationError

[el...@apache.org]

This is an automated email from the ASF dual-hosted git repository.

eschutho pushed a commit to branch fix-semantic-layer-post-processing-typeerror
in repository https://gitbox.apache.org/repos/asf/superset.git

commit eab66ee4410937c3b7b4bde067c7abc2f9f0c604
Author: Elizabeth Thompson <es...@gmail.com>
AuthorDate: Mon Sep 21 16:38:52 2026 +0000

    fix(semantic-layer): wrap raw pandas TypeError/DataError from post-processing as QueryObjectValidationError
    
    SemanticView.get_query_result caught only InvalidPostProcessingError from
    query_object.exec_post_processing, so a raw pandas TypeError (or
    pandas.errors.DataError) — e.g. resample().mean() on a result set that
    carries an object-dtype dimension alongside numeric metrics — propagated as
    an opaque 500 instead of the project's normal 400 QueryObjectValidationError.
    
    Widen the catch to also translate TypeError/DataError, mirroring the fix for
    the sibling ExploreMixin.get_query_result path in apache/superset#44463.
    
    Co-Authored-By: Claude Opus 4.8 <no...@anthropic.com>
---
 superset/semantic_layers/models.py              |  3 ++
 tests/unit_tests/semantic_layers/models_test.py | 45 +++++++++++++++++++++++++
 2 files changed, 48 insertions(+)

diff --git a/superset/semantic_layers/models.py b/superset/semantic_layers/models.py
index c0f81e34591..dbb9eba1ce3 100644
--- a/superset/semantic_layers/models.py
+++ b/superset/semantic_layers/models.py
@@ -27,6 +27,7 @@ from dataclasses import dataclass
 from functools import cached_property
 from typing import Any, TYPE_CHECKING
 
+import pandas as pd
 import pyarrow as pa
 import sqlalchemy as sa
 from flask_appbuilder import Model
@@ -375,6 +376,8 @@ class SemanticView(AuditMixinNullable, Model):
                 result.df = query_object.exec_post_processing(result.df)
             except InvalidPostProcessingError as ex:
                 raise QueryObjectValidationError(ex.message) from ex
+            except (TypeError, pd.errors.DataError) as ex:
+                raise QueryObjectValidationError(str(ex)) from ex
         return result
 
     def get_query_str(self, query_obj: QueryObjectDict) -> str:
diff --git a/tests/unit_tests/semantic_layers/models_test.py b/tests/unit_tests/semantic_layers/models_test.py
index ff201c469e9..e260476310f 100644
--- a/tests/unit_tests/semantic_layers/models_test.py
+++ b/tests/unit_tests/semantic_layers/models_test.py
@@ -1002,6 +1002,51 @@ def test_semantic_view_get_query_result_wraps_post_processing_errors(
         view.get_query_result(mock_query_object)
 
 
+def test_semantic_view_get_query_result_wraps_post_processing_type_error(
+    mock_implementation: MagicMock,
+) -> None:
+    """
+    A raw ``TypeError`` from pandas inside ``exec_post_processing`` (e.g.
+    ``resample.mean()`` on a DataFrame that carries an object-dtype column
+    alongside numeric metrics — a normal real-world query result) must be
+    surfaced as ``QueryObjectValidationError`` (400) rather than propagating
+    as a system 500, matching the dataset flow in
+    ``superset/models/helpers.py`` (apache/superset#44463).
+    """
+    import pandas as pd
+
+    from superset.common.query_object import QueryObject
+    from superset.exceptions import QueryObjectValidationError
+
+    view = SemanticView()
+
+    # DatetimeIndex + object-dtype "category" column makes
+    # ``df.resample("1D").mean()`` raise a raw TypeError in pandas >= 2.x.
+    df = pd.DataFrame(
+        {"metric": [1.0, 2.0], "category": ["a", "b"]},
+        index=pd.to_datetime(["2023-01-01", "2023-01-03"]),
+    )
+
+    query_object = QueryObject(
+        row_limit=10,
+        post_processing=[
+            {"operation": "resample", "options": {"method": "mean", "rule": "1D"}}
+        ],
+    )
+
+    mock_result = MagicMock()
+    mock_result.df = df
+
+    with (
+        patch(
+            "superset.semantic_layers.models.get_results",
+            return_value=mock_result,
+        ),
+        pytest.raises(QueryObjectValidationError),
+    ):
+        view.get_query_result(query_object)
+
+
 def test_semantic_view_get_query_result_skips_post_processing_on_empty_df(
     mock_implementation: MagicMock,
 ) -> None: