Python's map and filter already run over iterators. If you're talking about creating filters that are composable, so that you could do filter1 = filter(predi

Python's map and filter already run over iterators. If you're talking about creating filters that are composable, so that you could do filter1 = filter(predicate1) # curried filter filter2 = filter(predicate2) # curried filter pipeline = compose(filter1, filter2) pipeline(<generator of some kind>) and make it so that the sequence of operations will be for el in some_generator: if predicate1(el) and predicate2(el): <accumulate value> Then I would say defining them in this way is useful and important--transducers are exactly one way of doing this! A critical aspect I didn't go into detail on is the idea of a take function. In the github repo, T.take(3) is the portion that allows the transducer to operate of an infinite stream of values. This is the piece your workflow example would need to take into account. How could I apply a filter followed by something that takes 3 passing values from an infinite sequence? I'm sure you could come up with a way, and it would be worth comparing to the transducer approach :). (it's worth noting that currying map, filter, etc.. are very complimentary to the transducer approach)