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Posted to commits@superset.apache.org by el...@apache.org on 2024/05/15 21:49:19 UTC
(superset) branch elizabeth/tune-logging created (now eb36e279c6)
This is an automated email from the ASF dual-hosted git repository.
elizabeth pushed a change to branch elizabeth/tune-logging
in repository https://gitbox.apache.org/repos/asf/superset.git
at eb36e279c6 warning emits an error
This branch includes the following new commits:
new eb36e279c6 warning emits an error
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(superset) 01/01: warning emits an error
Posted by el...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
elizabeth pushed a commit to branch elizabeth/tune-logging
in repository https://gitbox.apache.org/repos/asf/superset.git
commit eb36e279c6600c458cb8f0a3d7d41b1a6404912d
Author: Elizabeth Thompson <es...@gmail.com>
AuthorDate: Wed May 15 14:49:06 2024 -0700
warning emits an error
---
superset/utils/pandas_postprocessing/compare.py | 10 +++++++++-
1 file changed, 9 insertions(+), 1 deletion(-)
diff --git a/superset/utils/pandas_postprocessing/compare.py b/superset/utils/pandas_postprocessing/compare.py
index b20682027f..96d4335e52 100644
--- a/superset/utils/pandas_postprocessing/compare.py
+++ b/superset/utils/pandas_postprocessing/compare.py
@@ -19,12 +19,17 @@ from typing import Optional
import pandas as pd
from flask_babel import gettext as _
from pandas import DataFrame
+from pandas.errors import PerformanceWarning
from superset.constants import PandasPostprocessingCompare
from superset.exceptions import InvalidPostProcessingError
from superset.utils.core import TIME_COMPARISON
from superset.utils.pandas_postprocessing.utils import validate_column_args
+import logging
+
+logger = logging.getLogger(__name__)
+
@validate_column_args("source_columns", "compare_columns")
def compare( # pylint: disable=too-many-arguments
@@ -81,5 +86,8 @@ def compare( # pylint: disable=too-many-arguments
df = pd.concat([df, diff_df], axis=1)
if drop_original_columns:
- df = df.drop(source_columns + compare_columns, axis=1)
+ try:
+ df = df.drop(source_columns + compare_columns, axis=1)
+ except PerformanceWarning as ex:
+ logger.warning(ex)
return df