superset rename 源码
superset rename 代码
文件路径：/superset/utils/pandas_postprocessing/rename.py
# 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 typing import Dict, Optional, Union
import pandas as pd
from flask_babel import gettext as _
from pandas._typing import Level
from superset.exceptions import InvalidPostProcessingError
from superset.utils.pandas_postprocessing.utils import validate_column_args
@validate_column_args("columns")
def rename(
df: pd.DataFrame,
columns: Dict[str, Union[str, None]],
inplace: bool = False,
level: Optional[Level] = None,
) -> pd.DataFrame:
"""
Alter column name of DataFrame
:param df: DataFrame to rename.
:param columns: The offset string representing target conversion.
:param inplace: Whether to return a new DataFrame.
:param level: In case of a MultiIndex, only rename labels in the specified level.
:return: DataFrame after rename
:raises InvalidPostProcessingError: If the request is unexpected
"""
if not columns:
return df
try:
_rename_level = df.columns.get_level_values(level=level)
except (IndexError, KeyError) as err:
raise InvalidPostProcessingError from err
if all(new_name in _rename_level for new_name in columns.values()):
raise InvalidPostProcessingError(_("Label already exists"))
if inplace:
df.rename(columns=columns, inplace=inplace, level=level)
return df
return df.rename(columns=columns, inplace=inplace, level=level)
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