I assume the author is talking about `fold`, as in `[A] -> B -> ((B,A) -> B) -> B`, and not what I often think of as reduce as `[A] -> ((A,A) -> A) -> A`.
`fold` is awesome and super useful. It's the easiest and most convenient way to turn a collection into a single value. Put me anecdotally in the opposite bucket.
Even in the world of functional programming, there's an argument to be made that `fold` is a bit of a code smell, in a similar vein as `while` being slightly smelly in an imperative code base. There's good reasons for each to be used, but they are such low level iteration primitives that you might be better off with a higher one (e.g. for loops or iterators in imperative programs; in FP you might reach for monoidic reduces (as opposed to folds where the accumulator is a different type from the list element), monadic traverses, or recursion schemes). Even though you can implement iterators or for loops in terms of while loops, you probably shouldn't, and similar for functional traversals.
In languages like python or Java though, you don't really have access to many of the higher power functional traversals however. So that puts you into a similar kind of bind as working in a language with only while loops
Map and Filter are nice because they let you reason locally about a single element in isolation. Reduce(Fold) forces you to reason globally about intermediate results. Reduce also forces you to conjure up a "zero" value of the relevant type, which isn't usually difficult but it does constitute some extra mental overhead.
I like reduce in principle since it generalizes a simple concept pretty nicely. I don't use it that much in practice since its alternatives just require less brainpower. It competes against using local mutable state with a loop or iterator combinator which I would argue are easier to wrap your head around (i.e. loop with variable/map with closure). I would argue its one of those cases where something is just harder to do/understand in functional vs imperative programming.
Well yeah, it's the lowest-level array function. All of the others can be written with reduce, but not vice-versa. Of course it's going to be less friendly.
At least in Python, I've found that "reduce" is very rarely needed. Most of the times, "sum" is enough, sometimes with "start" values customized (set it to [] to flatten an array for example). It is both easier to read, faster, and needs no imports. It also works great with list comprehensions - "sum(foo(x) for x in input if x > 5)" is much easier to read than reduce equivalent.
If you are multiplying, you are likely doing heavy math, and you'll be using numpy - which does not need reduce either.
If you are going to return a list of dict, then it's much faster to mutate the results, so using "reduce" will have significant performance implications (unless you want to return input argument, mis-using it as a glorified "for" loop)
And if returning not a list/dict, if you can use "min" or "max" or "any" or "all" or "next" (take the first element), then you should use it - it will be easier to read and faster too.
So what does this leave us for "reduce"? Frankly, not much. I've only seen it in merging immutable status codes, and that was pretty niche usecase to begin with.
(this was all for Python. In other languages without nice list of built-ins reduce might make more sense)
Has the performance of sum on lists of lists in Python been fixed? It used to be pretty abysmal. But I suppose some would say that if you need to consider performance at all, you’re in the wrong language… :)
For numerical code I like einops.reduce more than numpy/pytorch sum reductions because you can reduce over named dimensions. It’s much more readable than having to reason through axis indexing again every time you come back to the code
Reduce requires knowing that the sum of zero entities is zero but the multiply of zero entities is one. They forget to throw the correct number and think that reduce() just do not work for them.
I assume the author is talking about `fold`, as in `[A] -> B -> ((B,A) -> B) -> B`, and not what I often think of as reduce as `[A] -> ((A,A) -> A) -> A`.
`fold` is awesome and super useful. It's the easiest and most convenient way to turn a collection into a single value. Put me anecdotally in the opposite bucket.
Even in the world of functional programming, there's an argument to be made that `fold` is a bit of a code smell, in a similar vein as `while` being slightly smelly in an imperative code base. There's good reasons for each to be used, but they are such low level iteration primitives that you might be better off with a higher one (e.g. for loops or iterators in imperative programs; in FP you might reach for monoidic reduces (as opposed to folds where the accumulator is a different type from the list element), monadic traverses, or recursion schemes). Even though you can implement iterators or for loops in terms of while loops, you probably shouldn't, and similar for functional traversals.
In languages like python or Java though, you don't really have access to many of the higher power functional traversals however. So that puts you into a similar kind of bind as working in a language with only while loops
Map and Filter are nice because they let you reason locally about a single element in isolation. Reduce(Fold) forces you to reason globally about intermediate results. Reduce also forces you to conjure up a "zero" value of the relevant type, which isn't usually difficult but it does constitute some extra mental overhead.
The name itself is confusing to begin with.
I come across reduce once in a few months, then I think it's a neat trick and a nice to have function.
then I forget it's even available and don't ever use unless these days LLM brings it up again.
I like reduce in principle since it generalizes a simple concept pretty nicely. I don't use it that much in practice since its alternatives just require less brainpower. It competes against using local mutable state with a loop or iterator combinator which I would argue are easier to wrap your head around (i.e. loop with variable/map with closure). I would argue its one of those cases where something is just harder to do/understand in functional vs imperative programming.
It's part of the functional trio: map, filter, reduce--and half of MapReduce.
Well yeah, it's the lowest-level array function. All of the others can be written with reduce, but not vice-versa. Of course it's going to be less friendly.
At least in Python, I've found that "reduce" is very rarely needed. Most of the times, "sum" is enough, sometimes with "start" values customized (set it to [] to flatten an array for example). It is both easier to read, faster, and needs no imports. It also works great with list comprehensions - "sum(foo(x) for x in input if x > 5)" is much easier to read than reduce equivalent.
If you are multiplying, you are likely doing heavy math, and you'll be using numpy - which does not need reduce either.
If you are going to return a list of dict, then it's much faster to mutate the results, so using "reduce" will have significant performance implications (unless you want to return input argument, mis-using it as a glorified "for" loop)
And if returning not a list/dict, if you can use "min" or "max" or "any" or "all" or "next" (take the first element), then you should use it - it will be easier to read and faster too.
So what does this leave us for "reduce"? Frankly, not much. I've only seen it in merging immutable status codes, and that was pretty niche usecase to begin with.
(this was all for Python. In other languages without nice list of built-ins reduce might make more sense)
Has the performance of sum on lists of lists in Python been fixed? It used to be pretty abysmal. But I suppose some would say that if you need to consider performance at all, you’re in the wrong language… :)
For numerical code I like einops.reduce more than numpy/pytorch sum reductions because you can reduce over named dimensions. It’s much more readable than having to reason through axis indexing again every time you come back to the code
Reduce requires knowing that the sum of zero entities is zero but the multiply of zero entities is one. They forget to throw the correct number and think that reduce() just do not work for them.
I've always like reduce myself, didn't realize others had a negative attitude towards it.