we won' go into too much detail about what the algorithm doesratherwe'll focus on some of the ways we can apply the iterator pattern or iterator protocol to this problem let' now write program that performs the following steps in order load the sample data from the file and construct model from it generate random colors classify each color and output it to file in the same format as the input once we have this second csv fileanother kivy program can load the file and render each colorasking human user to confirm or deny the accuracy of the predictionthus informing us of how accurate our algorithm and initial data set are the first step is fairly simple generator that loads csv data and converts it into format that is amenable to our needsimport csv dataset_filename 'colors csvdef load_colors(filename)with open(filenameas dataset_filelines csv reader(dataset_filefor line in linesyield tuple(float(yfor in line[ : ])line[ we haven' seen the csv reader function before it returns an iterator over the lines in the file each value returned by the iterator is list of strings in our casewe could have just split on commas and been finebut csv reader also takes care of managing quotation marks and various other nuances of the comma-separated value format we then loop over these lines and convert them to tuple of color and namewhere the color is tuple of three floating value integers this tuple is constructed using generator expression there might be more readable ways to construct this tupledo you think the code brevity and the speed of generator expression is worth the obfuscationinstead of returning list of color tuplesit yields them one at timethus constructing generator object nowwe need hundred random colors there are so many ways this can be donea list comprehension with nested generator expression[tuple(random(for in range( )for in range( ) basic generator function class that implements the __iter__ and __next__ protocols