old_contents: import luigi
  import pandas as pd
  from Data_Prep.generate_base_data import GenerateBase
  
  # Generate Features
  class GenerateFeatures(luigi.Task):
      current_dir = luigi.Parameter()
      config = luigi.DictParameter()
  
      def requires(self):
          return GenerateBase(self.current_dir, self.config)
  
      def output(self):
          return luigi.LocalTarget(self.current_dir + self.config['feature_file'])
  
      def is_zero(self, val):
          if val == 0:
              return 1
          return 0
  
      def run(self):
          df = pd.read_csv(self.current_dir + self.config['base_file'])
          print(df.columns)
          new_df = df[['donation_ct', 'volume']]
          new_df['is_zero_duration'] = df.apply(lambda r: self.is_zero(r['duration']), axis=1)
          new_df['avg_vol_per_ct'] = df['avg_vol']/df['avg_ct']
          new_df.to_csv(self.output().path, index=False)
          return new_df
  
new_contents: import luigi
  import pandas as pd
  from Data_Prep.generate_base_data import GenerateBase
  
  # Generate Features
  class GenerateFeatures(luigi.Task):
      current_dir = luigi.Parameter()
      config = luigi.DictParameter()
  
      def requires(self):
          return GenerateBase(self.current_dir, self.config)
  
      def output(self):
          return luigi.LocalTarget(self.current_dir + self.config['feature_file'])
  
      def is_zero(self, val):
          if val == 0:
              return 1
          return 0
  
      def run(self):
          df = pd.read_csv(self.current_dir + self.config['base_file'])
          print(df.columns)
          new_df = df[list(self.config['origin_cols'])]
          new_df['is_zero_duration'] = df.apply(lambda r: self.is_zero(r['duration']), axis=1)
          new_df['avg_vol_per_ct'] = df['avg_vol']/df['avg_ct']
          new_df.to_csv(self.output().path, index=False)
          return new_df
  
subject: update luigi code