I have a suggestion for improving clarity: word_bag: dict[str, int] = dict() # Multiset for line in raw_corpus: words = line.split()

I have a suggestion for improving clarity: word_bag: dict[str, int] = dict() # Multiset for line in raw_corpus: words = line.split() for word in words: if word in word_bag: word_bag[word] += 1 else: word_bag[word] = 1 Try: word_bag = collections.Counter() for line in raw_corpus: word_bag.update(line.split()) then, to filter: word_bag = {word: count for (word, count) in word_bag.items() if count >= min_frequency} or, if you can avoid printing the filtered word bag: return set(word for (word, count) in word_bag.items() if count >= min_frequency) Also, that: raw_corpus : list[list[str]], should be list[str]. It's your corpus which is a list[list[str]]. (And you might want to use "line_words" instead of "line" Could you explain why lines are processed independently? for i, line in enumerate(corpus): for j, target_word in enumerate(line): Does it make a difference that some lines have fewer words than others? I would think that for positive_words in sliding_window(flatten(corpus), window_size): using the sliding_window and flatting recipes at https://docs.python.org/3/library/itertools.html#itertools-recipes https://docs.python.org/3/library/itertools.html#itertools-r... would be more appropriate. Though using it directly would not handle the leading/trailing partial windows. I liked seeing the 'η' - I haven't yet used non-ASCII in my code!