Map and filter usually have only one arg and if they have 2, the 2nd is almost always a 0-based index. They look identical in most languages, even when Microsoft chooses to call them Select and Where.
Reduce has an accumulator and a 2-arg function and languages are not very consistent amongst each other as to whether it's reduce(initial_acc, callback(acc, elem)) or reduce(callback(acc, elem), initial_acc) or reduce(callback(elem, acc), initial_acc) or what.
Hard to remember. Also some languages have a version of reduce that doesn't take an initial accumulator at all, which is just a footgun waiting for you to hit an empty collection. Also ALSO, the accumulator can easily become awkward in languages that don't support anonymous types or don't support easy mutation of an anonymous type record. Which is most of them!
Haskell got this right. You have foldr (right fold) and foldl' (left fold), and the order of the callback is opposite. If you do a left fold, then the initial accumulator is applied on the left; if you do a right fold, then the initial accumulator is applied on the right.
foldr f z [x1, x2, ..., xn] == x1 `f` (x2 `f` ... (xn `f` z)...)
foldl' f z [x1, x2, ..., xn] == (...((z `f` x1) `f` x2) `f`...) `f` xn
The mnemonic here is that the folding function (aka the callback) replaces the comma.
I find this slightly easier to remember than other languages. In contrast most other languages do not simultaneously provide a left fold and a right fold, so they do not consider this aspect, making things more difficult to remember.
That said I totally agree this requires more brainpower to read and write than map or filter. For this reason I have sometimes refactored code to use foldMap instead of foldr or foldl', so one no longer needs to think of the direction of the fold or the order of arguments.
It's still a complex and more abstract function than map or filter. Those do a single thing that's easy to grasp. reduce/fold can be easily abused to duplicate the effect of most other collection functions, at the cost of making the code less readable. Although for slightly-too-clever people, that could mean you only need to know one function instead of all of them.
But it hurts readability. If you're going to do it, at least don't use it anonymously, but give it a name that clearly describes what's going on.
But even then, there can be hidden performance traps. I've often seen javascript that used reduce and created the new accumulator by using a spread on the old accumulator and adding the new one: `[...acc, newValue]`. But that spread is another iteration inside a loop, turning it from O(n) to O(n^2). A for loop where you append it is much faster.
rspeele · · focus · HN ↗
Reduce has an accumulator and a 2-arg function and languages are not very consistent amongst each other as to whether it's reduce(initial_acc, callback(acc, elem)) or reduce(callback(acc, elem), initial_acc) or reduce(callback(elem, acc), initial_acc) or what.
Hard to remember. Also some languages have a version of reduce that doesn't take an initial accumulator at all, which is just a footgun waiting for you to hit an empty collection. Also ALSO, the accumulator can easily become awkward in languages that don't support anonymous types or don't support easy mutation of an anonymous type record. Which is most of them!
kccqzy · · focus · HN ↗
I find this slightly easier to remember than other languages. In contrast most other languages do not simultaneously provide a left fold and a right fold, so they do not consider this aspect, making things more difficult to remember.
That said I totally agree this requires more brainpower to read and write than map or filter. For this reason I have sometimes refactored code to use foldMap instead of foldr or foldl', so one no longer needs to think of the direction of the fold or the order of arguments.
mcv · · focus · HN ↗
But it hurts readability. If you're going to do it, at least don't use it anonymously, but give it a name that clearly describes what's going on.
But even then, there can be hidden performance traps. I've often seen javascript that used reduce and created the new accumulator by using a spread on the old accumulator and adding the new one: `[...acc, newValue]`. But that spread is another iteration inside a loop, turning it from O(n) to O(n^2). A for loop where you append it is much faster.