Today we look at a single module that clocks in at a mere 200 lines of code, including comments. In these few lines though is an optimisation that has a wide range of use cases - an optimisation taking an operation from O(n) to O(1). Now that’s my kinda optimisation!
dlist library provides an API that allows list appending to run in O(1) rather than O(n) time. Before we look at the magic that makes this unbelievable feat possible, let’s take a quick look at how the API works.
> toList $ append (fromList [1..5]) (fromList [1..10]) [1,2,3,4,5,1,2,3,4,5,6,7,8,9,10]
fromList to convert a Haskell list into a dlist. Next, we use the
append to combine 2 lists. Note that
dlist is a monoid so we could also use the more general
<> operator. Finally, to get back out of
dlist by calling
toList. There’s not much more to it!
So, now that we’ve seen this at work, we can ask ourselves how this works. The key to
dlist lies in function composition and partially applied functions. Rather than storing complete lists, and building new lists every time we call
append, we instead store a function that given a list will the original list prepended to the input to the function. This now lets us use function composition to build up our final list, and function composition is O(1). Let’s see this is a bit of code:
> :t ([1, 2] ++) ([1, 2] ++) :: Num a => [a] -> [a] > :t ([1, 2] ++) . ([3, 4] ++) ([1, 2] ++) . ([3, 4] ++) :: Num a => [a] -> [a] > ([1, 2] ++) . ([3, 4] ++) $  [1,2,3,4]
That’s almost all there is to it. Dlist simply wraps this up in a new type and provides instances for
Monoid, and a few other type classes we’d expect. It should that
dlist doesn’t make everything O(1) - at some point you will have to construct the list, which will be at least O(n). However, for specific usage patterns
dlist can give you a good boost in performance.
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