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Your typical definition of map, filter etc includes concrete usage of e.g. lists. These don't. Transducers are not just currying or partial application of the map function over lists, they isolate the logic of map, filter etc from lists or any particular context, allowing them to be used in very different (e.g. non-collection) contexts.

> they isolate the logic of map, filter etc from lists or any particular context

Is it correct to say that the relationship between the new forms of map/filter/etc, reduction functions, and transducers is something like this:

"traditional" (map f l) is equivalent to (foldl (mapR f) l []), where (mapR f) is the "reduction function" corresponding to map. (mapR would still be list specific)

the new (map f) is a transducer that takes a reduction function and returns another reduction function; given idR, the "identity reduction function" for foldl such that (foldl idR l []) = l, ((map f) idR) = mapR.

Furthermore, given reduction functions mapRR such that (foldr (mapRR f) l []) == (map f l) and idRR such that (foldr idRR l []) = l, then ((map f) idRR) = mapRR. (Because all the list-specific things in the output reduction function come from the input reduction function, the transducer (map f) doesn't need to know anything about lists, so can be used in other contexts as well -- one minor-but-perhaps-easier-to-illustrate aspect of that is, even when used with lists, (map f) is independent of the folding direction, unlike the reduction functions mapR and mapRR.)

(I know this is barely even scratching the surface of the applications, but I'm trying to confirm that I've got the concept right.)

> isolate the logic of map, filter etc from lists or any particular context

so Functors (fmap)? fmap still uses regular old fns, no machinery.

http://clojuredocs.org/clojure_contrib/clojure.contrib.gener... http://learnyouahaskell.com/making-our-own-types-and-typecla...

I feel that same confusion as you. In Haskell terms, what is it Rich have implemented or perhaps even invented?

I'm not sure I grok this, but I think that the main points are:

- reducers can work on tree structures, and thus can exploit parallelism. This would be like using a map that requires only the Foldable typeclass

- In Haskell you have stream/vector fusion, but it's not obvious to know when ghc will actually exploit it, you might want to use something like Control.Monad.Stream or Data.Vector. In theory it might be generalized to all Foldables, but in practice for now it might be a good enough compromise to stick to a limited number of types (the one that support such transducers)

So: nothing terribly new/groundbreaking, but it might bring something like stream fusion to the masses (of clojure developers :P )

Comparing transducers to stream fusion is far narrower than the scope of their applicability.

They are more comparable to Oleg's Enumerators (http://okmij.org/ftp/Haskell/Iteratee/describe.pdf), in that you compose a series of computations and then push data through them. The type signature is similar:

    type Iteratee el m a -- a processor of 'els' in the monad 'm' returning a type 'a'

    type Enumerator el m a = Iteratee el m a -> m (Iteratee el m a)
The Enumerators library is complicated by the presence of monads and by trying to automatically close handles when the stream is processed. In some ways it seems that the goal of solving the lazy IO problem led to missing a much simpler abstraction. Transducers seem to be simpler and more focused on just abstracting stream/map-reduce computation.

While not mentioned in the blog post, the transducers implementation supports both early termination and result completion/flushing/cleanup.

there does seem to be some overlap with stream fusion -- which was all about exploiting the optimization opportunities when separating the collection operation from the kernel performed on each element.

We called the bits in the middle "step functions" , which could be combined with "consumers", "producers" and "transformers".

And the algebra generalizes hugely (not just collections) but to things like concurrent processes, data flow programs etc.


Things to think about in a non-Haskell settings: how do you prevent reordering side-effects? Can execeptions/non-termination being reordered be observed?

By "map in a non-collection context", what would be an example? Say, mapping a boolean negation function over the bits of an integer, to produce its complement? How does that look with transducers?

Well, the most obvious value to me is that you can create algorithms that defer their action- So instead of having a function that operates on a collection, you can have a function that will operate on a collection at a future date, even if the collection does not yet exist. (that's what the clojure reducer library does)

(And if you say "deferring an action is just another term for 'functions'" then that's exactly the point, lifting more algorithmic logic into composable functions)

Alan Perlis Epigram #2.

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