Comment by jfoutz | Hacker News Reader

Comment by jfoutz | Hacker News Reader

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hmm, i don't think lazyness is enough. for example, in the billion names example, let's say the first and last elements are valid. at the first step you'll wind up with something like

   validPerson : thunk

after n steps where n < 1e9

   validPerson : invalid : invalid : invalid : ... : thunk

then finally at n = 1e9

  validPerson : invalid : ... : validPerson

because the intermediate calculations still need to happen.

getting that first answer is cheap and quick. getting the second answer requires evaluating those billion - 1 thunks.

maybe you're thinking of list fusion? AFAIK, only haskell does that.

Perhaps i'm misunderstanding your point. But even then, lisp, scheme, smalltalk, python and perl don't implement map and filter in a lazy way. Of course, i'm thinking in terms of haskell lazy, perhaps, again, i'm misunderstanding and you mean something else.

In retrospect, i think i'll revise my opinion and say map.filter is probably a bigger code smell than referentially transparent mutation.

I understood from your comment that the imperative version "avoids building the name size list of persons" that you thought the declaritive version would construct an intermediate List[Person] the same size as the source list of names. Most modern languages (e.g. C#, F#, Clojure, Rust) implement map and filter using lazy sequences rather than eagerly constructing intermediate collections (admittedly I don't have much experience with the languages you list).

The use laziness will avoid the need to construct a large intermediate collection of Person instances. Obviously you'll need to iterate the entire source collection to find all valid Persons but the same applies to the imperative version. The lazy version composes better however and avoids extra work if some downstream caller only requires the first n valid Persons.

Oh! yes. Yes we're on the same page as far as laziness goes. The lazy version will only construct as much of the intermediate list as you need to get the next answer, and potentially the garbage collector can reclaim the parts of the intermediate list that have already gone past.

But, there's already a good clean functional composable answer to this kind of thing,

fold takes an operation (like map does) a list (like map does) and an accumulator for building up results, and it returns the resulting accumulator.

   foldl(op, names, acc){
       if(names.empty)
           return acc
       else
           foldl(op, names.tail, op(names.head, acc)
   }

so with tail recursion, you get no stack growth. (i mean head like the first element of names, and tail as everything else)

the op would look something like

   op(name, acc){
      let p = Person.init(name)
      if(p.isValid)
          return acc += [p]
      else
          return acc
      }

So fold trundles down the list of names, the op checks each name to see if it's good, and only adds the good names to the final list. whenever fold notices it's out of more names to try, it just returns whatever the current accumulator might be.

Map forces you to build the intermediate representation, which the imperative version avoids.

Even Java manages to get your example to work efficiently with map/filter. It's not rocket science. Just because some library designers screwed it up doesn't invalidate the whole concept.

but java provides collect. which is, like, the right way to do it.

I'm just sort of mystified that people are defending map.filter over filter.map (which isn't crazy, as name.isValidPerson isn't provided.) but, you know, fold is a thing.

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