[Haskell-cafe] "no-coding" functional data structures via lazyness
Janis Voigtlaender
voigt at tcs.inf.tu-dresden.de
Tue Jul 10 05:30:24 EDT 2007
Jonathan Cast wrote:
> On Tuesday 10 July 2007, Dave Bayer wrote:
>
>>On Jul 9, 2007, at 6:52 PM, Donald Bruce Stewart wrote:
>>
>>>bayer:
>>>
>>>>Learning Haskell, the Prelude.ShowS type stood out as odd, exploiting
>>>>the implementation of lazy evaluation to avoid explicitly writing an
>>>>efficient concatenable list data structure.
>>>
>>>See also
>>> http://hackage.haskell.org/cgi-bin/hackage-scripts/package/
>>>dlist-0.3
>>
>>Thanks; I added a link to the dlist package from my discussion of
>>this idiom on the Wiki page
>> http://www.haskell.org/haskellwiki/Prime_numbers
>>
>>On Jul 9, 2007, at 3:19 PM, Jonathan Cast wrote:
>>
>>>I think we usually call it `exploiting laziness'. . .
>>
>>My motivation in asking for a name was to be able to find other
>>Haskell one-liners adequately replacing chapters of data structure
>>books for problems of modest scale, e.g. finding the 5,000,000th
>>prime. So far, I know concatenable lists, and heaps. Is there a Wiki
>>page where someone teaches this principle for a dozen other classic
>>data structures? Your "one-liner" made me laugh, but it didn't help
>>me in googling, I would have preferred a one-liner teaching me
>>another classic data structure, or an explanation of why burrowing
>>into the GHC implementation gives such a speed advantage over a
>>carefully written explicit data structure.
>>
>>People in other camps don't really "get" lazy evaluation, even many
>>of our ML neighbors. It would pay to communicate this better to the
>>outside world.
>
>
> Unfortunately, I'm afraid all I can do at this point is wish you luck in your
> search.
Maybe it is worth pointing out that the "concatenable lists" trick can
be extended to various other operations on lists. For example, if one
just changes a few definitions in the DList-package as follows:
newtype DList a = DL { unDL :: forall b. (a -> b) -> [b] -> [b] }
fromList = \xs -> DL ((++) . (flip List.map xs))
toList = ($[]) . ($ id) . unDL
empty = DL (const id)
singleton = \x -> DL ((++) . (:[]) . ($ x))
cons x xs = DL (\f -> (f x:) . unDL xs f)
snoc xs x = DL (\f -> unDL xs f . (f x:))
append xs ys = DL (\f -> unDL xs f . unDL ys f)
map f xs = DL (unDL xs . (.f))
one gets "concatenable, mappable lists" in the sense that for those
lists now also map can be done in O(1).
(Of course, the actual cost of computing the mapped function on each
eventually demanded list element is not saved, but there is no O(spine)
cost anymore for distributing the function to each position in the list.
Rather, this becomes O(1), just as the cost of append goes down from
O(spine of the first list) to O(1). If there are repeated maps, such as
in a naive definition of inits, the improvement can be considerable.)
Similar tricks can be played with reverse, filter, (...?).
Just how, can be seen from:
http://wwwtcs.inf.tu-dresden.de/~voigt/p114-voigtlaender.pdf
http://wwwtcs.inf.tu-dresden.de/~voigt/icfp2002-slides.pdf
http://wwwtcs.inf.tu-dresden.de/~voigt/Vanish.lhs
Ciao, Janis.
--
Dr. Janis Voigtlaender
http://wwwtcs.inf.tu-dresden.de/~voigt/
mailto:voigt at tcs.inf.tu-dresden.de
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