code: import pandas as p
  import numpy as np
  from file_setup_helper import FileSetupHelper as fsh
  from preprocess_data import PreprocessData as pd
  from model_export import ModelExport as me
  import sys
  from sklearn.linear_model import Ridge
  
  def main():
      #call for file download with given date
      file_name = fsh(sys.argv[1], 1460, 0).download_csv()
  
      #aquire features and target data filenames
      features_file_name, target_file_name = pd(file_name).preprocess(True, None)
  
      #init model, and open the features and target file
      #(drop column added by pandas and bypass 29.02 potential error)
      model = Ridge(alpha=1, fit_intercept=True)
      X_train = p.read_csv(features_file_name).drop(['Unnamed: 0', 'Date_29.02'], axis=1)
      y_train = p.read_csv(target_file_name).drop(['Unnamed: 0'], axis=1)
  
      #export model with the given datasets and model
      me(model, X_train, y_train).fit_and_export(sys.argv[2])
  
  if __name__ == '__main__':
      main()
  
apis: pandas.read_csv sklearn.linear_model.Ridge