sum sum( * for in fitsstd abs(sum length mean** )** print('min ='min(fits)'max ='max(fits)print('average ='round(mean )'standard deviation ='round(std )print("\nevolution ends"print the final outputbest_ind tools selbest(population )[ print('\nbest individual:\ 'best_indprint('\nnumber of ones:'sum(best_ind)following would be the outputevolution process starts evaluated individuals generation evaluated individuals min max average standard deviation generation evaluated individuals min max average standard deviation generation evaluated individuals min max average standard deviation generation evaluated individuals min max average standard deviation evolution ends best individual[ number of ones