old_contents: # Built-in modules
  import re
  # Third-party modules
  import pandas as pd
  # Hand-made modules
  from .base import DataFrameHandlerBase, BloscpackMixin
  
  OBJECTIVE_COLUMNS = ["kwh", ]
  REGEX_FLAG_NAME_PREFIX = "f_"
  REGEX_DROP_LABEL_NAME_PREFIXES = {
      "max_ws_",
      "ave_wv_",
      "ave_ws_",
      "max_tp_",
      "min_tp_",
      "sl_",
      "sd_",
      "vb_",
      "weather_",
      "dsr_",
      "dsd_",
      "dsr_"
  }
  DROP_LABEL_NAMES = [
      "weather",
      "weather_detail",
      "wind",
      "wave"
  ]
  
  
  class DatasetHandler(DataFrameHandlerBase, BloscpackMixin):
      def __init__(self):
          super().__init__()
          self.OBJECTIVE_COLUMNS = OBJECTIVE_COLUMNS
          self.REGEX_FLAG_NAME_PREFIX = REGEX_FLAG_NAME_PREFIX
          self.REGEX_DROP_LABEL_NAME_PREFIXES = REGEX_DROP_LABEL_NAME_PREFIXES
          self.DROP_LABEL_NAMES = DROP_LABEL_NAMES
  
      def separate_train_test(self, df: pd.DataFrame):
          df_train = df.loc[self.TRAIN_DATE_RANGE[0]:self.TRAIN_DATE_RANGE[1], :]
          df_test = df.loc[self.TEST_DATE_RANGE[0]:self.TEST_DATE_RANGE[1], :]
  
          return df_train, df_test
  
      def separate_X_y(self, df: pd.DataFrame):
          df_y = df.loc[:, self.OBJECTIVE_COLUMNS].copy(deep=True)
          df.drop(self.OBJECTIVE_COLUMNS, axis=1, inplace=True)
  
          return df, df_y
  
      def split_data_and_flags(self, df):
          pattern = re.compile("^" + self.REGEX_FLAG_NAME_PREFIX + ".*$")
          flag_col_name_list = [
              col_name for col_name in df.columns \
              if pattern.match(col_name)
          ]
  
          df_flags = df[flag_col_name_list].copy(deep=True)
          df.drop(flag_col_name_list, axis=1, inplace=True)
  
          return df, df_flags
  
      @staticmethod
      def get_regex_matched_col_name(col_name_list, regex_name_prefix_list):
          return [
              col_name \
              for col_name in col_name_list \
              for name_prefix in regex_name_prefix_list \
              if re.compile("^" + name_prefix + ".*$").match(col_name)
          ]
  
  
  if __name__ == '__main__':
      print("dataset maker !")
  
new_contents: # Built-in modules
  import re
  # Third-party modules
  import pandas as pd
  # Hand-made modules
  from .base import DataFrameHandlerBase, BloscpackMixin
  
  OBJECTIVE_COLUMNS = ["kwh", ]
  REGEX_FLAG_NAME_PREFIX = "f_"
  
  
  class DatasetHandler(DataFrameHandlerBase, BloscpackMixin):
      def __init__(self):
          super().__init__()
          self.OBJECTIVE_COLUMNS = OBJECTIVE_COLUMNS
          self.REGEX_FLAG_NAME_PREFIX = REGEX_FLAG_NAME_PREFIX
  
      def separate_train_test(self, df: pd.DataFrame):
          df_train = df.loc[self.TRAIN_DATE_RANGE[0]:self.TRAIN_DATE_RANGE[1], :]
          df_test = df.loc[self.TEST_DATE_RANGE[0]:self.TEST_DATE_RANGE[1], :]
  
          return df_train, df_test
  
      def separate_X_y(self, df: pd.DataFrame):
          df_y = df.loc[:, self.OBJECTIVE_COLUMNS].copy(deep=True)
          df.drop(self.OBJECTIVE_COLUMNS, axis=1, inplace=True)
  
          return df, df_y
  
      def split_data_and_flags(self, df):
          pattern = re.compile("^" + self.REGEX_FLAG_NAME_PREFIX + ".*$")
          flag_col_name_list = [
              col_name for col_name in df.columns \
              if pattern.match(col_name)
          ]
  
          df_flags = df[flag_col_name_list].copy(deep=True)
          df.drop(flag_col_name_list, axis=1, inplace=True)
  
          return df, df_flags
  
      @staticmethod
      def get_regex_matched_col_name(col_name_list, regex_name_prefix_list):
          return [
              col_name \
              for col_name in col_name_list \
              for name_prefix in regex_name_prefix_list \
              if re.compile("^" + name_prefix + ".*$").match(col_name)
          ]
  
  
  if __name__ == '__main__':
      print("dataset maker !")
  
subject: Remove DROP_LABEL_NAMES information