Are there standard sorting functions in SML? The documentation on the Internet is so scarce I couldn't find any.
There is no sorting functionality defined in the SML Basis Library, but most implementations extend the basis library and add extra functionality.
As such MosML has both an ArraySort and a Listsort module, and SML/NJ has a LIST_SORT signature with a ListMergeSort implementation. It also features some other sorting features on arrays as MosML. See the toc of the SML/NJ Library Manual, for a full list.
As Jesper Reenberg points out, Standard ML compilers have each their own (non-standard, ironically) sorting libraries. Since the documentation for these lacks examples, here is how to sort a list of strings in ascending order using the various modules:
In SML/NJ and MLton, using the ListMergeSort.sort function:
- fun sortStrings ss = ListMergeSort.sort (fn (s : string, t) => s > t) ss;
[autoloading]
[library $SMLNJ-LIB/Util/smlnj-lib.cm is stable]
[autoloading done]
val sortStrings = fn : string list -> string list
- sortStrings ["World","Hello"];
val it = ["Hello","World"] : string list
The quirk with this library function is that it takes a "greater than" boolean predicate. Since Standard ML's > operator is overloaded, but defaults to int, I have to somehow explicitly annotate that I'm comparing strings.
In Moscow ML, using the Listsort.sort function:
- load "Listsort";
> val it = () : unit
- fun sortStrings ss = Listsort.sort String.compare ss;
> val sortStrings = fn : string list -> string list
- sortStrings ["World", "Hello"];
> val it = ["Hello", "World"] : string list
The quirk with this library is that Moscow ML's interactive REPL does not auto-load Listsort. Typing load "Listsort"; is only necessary in the interactive REPL; when compiling programs, load is not used.
In Poly/ML, there is no library for sorting, so you have to define your own sorting function.
If neither of these sorting functions are sufficient, here is a number of other sorting functions written in Standard ML:
True QuickSort in Standard ML compares a naive QuickSort (that isn't really a QuickSort) with an implementation of Hoare's algorithm by John Coleman.
Rosetta Code's MergeSort in Standard ML:
fun merge cmp ([], ys) = ys
| merge cmp (xs, []) = xs
| merge cmp (xs as x::xs', ys as y::ys') =
case cmp (x, y) of
GREATER => y :: merge cmp (xs, ys')
| _ => x :: merge cmp (xs', ys)
fun sort cmp [] = []
| sort cmp [x] = [x]
| sort cmp xs =
let
val ys = List.take (xs, length xs div 2)
val zs = List.drop (xs, length xs div 2)
in
merge cmp (sort cmp ys, sort cmp zs)
end
Here is a standard quicksort
fun qsort(func) =
let fun sort [] = []
| sort (lhd :: ltl) =
sort (List.filter (fn x => func (x, lhd)) ltl)
# [lhd]
# sort (List.filter (fn x => not (func(x, lhd)) ltl)
in sort
end
Just throw in some comparator (function that takes two elements with same type and return boolean) and it will return a sort function for you
If you got anymore question don't hesitate to ask. :)
How about this for sorting a list? You could always use reverse to get the reverse.
- fun sort(L) =
if L=[] then []
else if tl(L)=[] then L
else merge(sort(take(L)), sort(skip(L)));
val sort = fn : int list -> int list
See here.
here is my sml sorting algorithm
fun sort list = foldr (fn (x,lst)=> List.filter (fn a => a < x) lst # [x] # List.filter (fn a => a >= x) lst ) [] list;
sort [5,1,5,0,2,5,~2,5,~10,0];
output: [~10,~2,0,0,1,2,5,5,5,5]
I hope it helps
Related
I need to sort an integer list on haskell, from smaller to greater numbers, but i dont know where to start.
The recursion syntax is kinda difficult for me
A little bit of help would be great.
Ive done this but it does not solve my problem:
ordenarMemoria :: [Int] -> [Int]
ordenarMemoria [] = []
ordenarMemoria (x:y:xs)
| y > x = ordenarMemoria (y:xs)
| otherwise = ordenarMemoria (x:xs)
Thanks
You attempt is on the right track for a bubble sort, which is a good starting place for sorting. A few notes:
You handle the cases when the list is empty or has at least two elements (x and y), but you have forgotten the case when your list has exactly one element. You will always reach this case because you are calling your function recursively on smaller lists.
ordenarMemoria [x] = -- how do you sort a 1-element list?
Second note: in this pattern
ordenarMemoria (x:y:xs)
| y > x = ordenarMemoria (y:xs)
| otherwise = ordenarMemoria (x:xs)
you are sorting a list starting with two elements x and y. You compare x to y, and then sort the rest of the list after removing one of the two elements. This is all good.
The question I have is: what happened to the other element? A sorted list has to have all the same elements as the input, so you should use both x and y in the output. So in:
| y > x = ordenarMemoria (y:xs)
you have forgotten about x. Consider
| y > x = x : ordenarMemoria (y:xs)
which indicates to output x, then the sorted remainder.
The other branch forgets about one of the inputs, too.
After you fix the function, you might notice that the list gets a bit more sorted, but it is still not completely sorted. That's a property of the bubble sort—you might have to run it multiple times.
I'll highly recommend you read Learn You a Haskell, there is an online version here, it has a chapter where you can learn how to sort lists using recursion, like Quicksort for example:
quicksort :: (Ord a) => [a] -> [a]
quicksort [] = []
quicksort (x:xs) =
let smallerSorted = quicksort [a | a <- xs, a <= x]
biggerSorted = quicksort [a | a <- xs, a > x]
in smallerSorted ++ [x] ++ biggerSorted
I need to sort an integer list
How about sort from Data.List?
$ stack ghci
Prelude> :m + Data.List
Prelude Data.List> sort [2,3,1]
[1,2,3]
There are lots of choices. I generally recommend starting with bottom-up mergesort in Haskell, but heapsort isn't a bad choice either. Quicksort poses much more serious difficulties.
-- Given two lists, each of which is in increasing
-- order, produce a list in increasing order.
--
-- merge [1,4,5] [2,4,7] = [1,2,4,4,5,7]
merge :: Ord a => [a] -> [a] -> [a]
merge [] ys = ???
merge xs [] = ???
merge (x : xs) (y : ys)
| x <= y = ???
| otherwise = ???
-- Turn a list of elements into a list of lists
-- of elements, each of which has only one element.
--
-- splatter [1,2,3] = [[1], [2], [3]]
splatter :: [a] -> [[a]]
splatter = map ????
-- Given a list of sorted lists, merge the adjacent pairs of lists.
-- mergePairs [[1,3],[2,4],[0,8],[1,2],[5,7]]
-- = [[1,2,3,4],[0,1,2,8],[5,7]]
mergePairs :: Ord a => [[a]] -> [[a]]
mergePairs [] = ????
mergePairs [as] = ????
mergePairs (as : bs : more) = ????
-- Given a list of lists of sorted lists, merge them all
-- together into one list.
--
-- mergeToOne [[1,4],[2,3]] = [1,2,3,4]
mergeToOne :: Ord a => [[a]] -> [a]
mergeToOne [] = ???
mergeToOne [as] = ???
mergeToOne lots = ??? -- use mergePairs here
mergeSort :: Ord a => [a] -> [a]
mergeSort as = ???? -- Use splatter and mergeToOne
Once you've filled in the blanks above, try optimizing the sort by making splatter produce sorted lists of two or perhaps three elements instead of singletons.
Here is a modified either quicksort or insertion sort. It uses the fastest method of prefixing or suffixing values to the output list. If the next value is less than or greater than the first or last of the list, it is simply affixed to the beginning or end of the list. If the value is not less than the head value or greater than the last value then it must be inserted. The insertion is the same logic as the so-called quicksort above.
Now, the kicker. This function is made to run as a foldr function just to reduce the complexity of the the function. It can easily be converted to a recursive function but it runs fine with foldr.
f2x :: (Ord a) => a -> [a] -> [a]
f2x n ls
| null ls = [n]
| ( n <= (head ls) ) = n:ls -- ++[11]
| ( n >= (last ls) ) = ls ++ [n] -- ++ [22]
| True = [lx|lx <-ls,n > lx]++ n:[lx|lx <-ls,n < lx]
The comments after two line can be removed and the function can be run with scanr to see how many hits are with simple prefix or suffix of values and which are inserted somewhere other that the first or last value.
foldr f2x [] [5,4,3,2,1,0,9,8,7,6]
Or af = foldr a2x [] ... af [5,4,3,2,1,0,9,8,7,6] >-> [0,1,2,3,4,5,6,7,8,9]
EDIT 5/18/2018
The best thing about Stack Overflow is the people like #dfeuer that make you think. #dfeuer suggested using partition. I am like a child, not knowing how. I expressed my difficulty with partition but #dfeuer forced me to see how to use it. #dfeuer also pointed out that the use of last in the above function was wasteful. I did not know that, either.
The following function uses partition imported from Data.List.
partition outputs a tuple pair. This function is also meant to use with foldr. It is a complete insertion sort function.
ft nv ls = b++[nv]++e where (b,e) = partition (<=nv) ls
Use it like above
foldr ft [] [5,4,3,2,1,0,9,8,7,6]
Haskell and functional programming is all about using existing functions in other functions.
putEleInSortedListA :: Ord a => a -> [a] -> [a]
putEleInSortedListA a [] = [a]
putEleInSortedListA a (b:bs)
| a < b = a : b : bs
| otherwise = b: putEleInSortedListA a bs
sortListA :: Ord a => [a] -> [a]
sortListA la = foldr (\a b -> putEleInSortedListA a b) [] la
I am new to Haskell, and I want to make 1 function that will take two lists and merge then together, and then sort the combined list from smallest to biggest.
this should be done in the command line without using modules.
This is what i currently have, I am having trouble getting the "sortList" function to work, and also I do not know how to combine these 3 lines into 1 function.
let combineList xs ys = xs++ys
let zs = combineList xs ys
let sortList (z:zs) = if (head zs) < z then (zs:z) else (z:(sortList zs))
How to sort list in ghci:
Prelude> :m + Data.List
Prelude Data.List> sort [1,4,2,0]
[0,1,2,4]
About your functions
let combineList xs ys = xs++ys
What is a point to create another alias for append function? But if you're really wants one - it could be defined like let combineList = (++).
let zs = combineList xs ys
It makes no sense because xs and ys are unknown outside of your combineList.
let sortList (z:zs) = if (head zs) < z then (zs:z) else (z:(sort zs))
This definition is not valid because it doesn't cover and empty list case and (zs:z) produces infinite type and sort is not defined yet. And you can get head of zs just by another pattern matching. And maybe you don't wanna to make another recursive call in the then part of if statement. And finally I should admit that this sorting algorithm doesn't work at all.
It's a bit awkward to define a sorting function within the ghci. I thing the easiest way to do it would be to write the sorting function in a file, and then loading it into ghci. For instance, you could write this concise (though not in-place!) version of quicksort in a file called sort.hs (taken from the HaskellWiki):
quicksort :: Ord a => [a] -> [a]
quicksort [] = []
quicksort (p:xs) = (quicksort lesser) ++ [p] ++ (quicksort greater)
where
lesser = filter (< p) xs
greater = filter (>= p) xs
and load it into ghci:
> :l sort.hs
If you really want to define the function in ghci, you can do something like this (from the Haskell user's guide):
> :{
> let { quicksort [] = []
> ; quicksort (p:xs) = (quicksort (filter (< p) xs)) ++ [p] ++ (quicksort (filter (>= p) xs))
> }
> :}
once this is defined, you can do
> let combineAndSort xs ys = quicksort (xs ++ ys)
As another answer already explained, it would of course be quicker to just import sort from Data.List, but it is definitely a good exercise to do it manually.
Your question suggests that you are a bit confused about the scope of variables in Haskell. In this line
> let combineList xs ys = xs++ys
you introduce the variables xs and ys. Mentioning them to the left of the equals sign just means that combineList takes two variables, and in the body of that function, you are going to refer to these variables as xs and ys. It doesn't introduce the names outside of the function, so the next line
> let zs = combineList xs ys
doesn't really make sense, because the names xs and ys are only valid within the scope of combineList. To make zs have a value, you need to give combineList some concrete arguments, eg.:
> let zs = combineList [2,4,6] [1,3,5] --> [2,4,6,1,3,5]
But since the body of combineList is so simple, it would actually be easier to just do:
> let zs = [2,4,6] ++ [1,3,5] --> [2,4,6,1,3,5]
The last line is
> let sortList (z:zs) = if (head zs) < z then (zs:z) else (z:(sortList zs))
I think this line has confused you a lot, because there are quite a lot of different errors here. The answer by ДМИТРИЙ МАЛИКОВ mentions most of them, I would encourage you to try understand each of the errors he mentions.
Say I have any list like this:
[4,5,6,7,1,2,3,4,5,6,1,2]
I need a Haskell function that will transform this list into a list of lists which are composed of the segments of the original list which form a series in ascending order. So the result should look like this:
[[4,5,6,7],[1,2,3,4,5,6],[1,2]]
Any suggestions?
You can do this by resorting to manual recursion, but I like to believe Haskell is a more evolved language. Let's see if we can develop a solution that uses existing recursion strategies. First some preliminaries.
{-# LANGUAGE NoMonomorphismRestriction #-}
-- because who wants to write type signatures, amirite?
import Data.List.Split -- from package split on Hackage
Step one is to observe that we want to split the list based on a criteria that looks at two elements of the list at once. So we'll need a new list with elements representing a "previous" and "next" value. There's a very standard trick for this:
previousAndNext xs = zip xs (drop 1 xs)
However, for our purposes, this won't quite work: this function always outputs a list that's shorter than the input, and we will always want a list of the same length as the input (and in particular we want some output even when the input is a list of length one). So we'll modify the standard trick just a bit with a "null terminator".
pan xs = zip xs (map Just (drop 1 xs) ++ [Nothing])
Now we're going to look through this list for places where the previous element is bigger than the next element (or the next element doesn't exist). Let's write a predicate that does that check.
bigger (x, y) = maybe False (x >) y
Now let's write the function that actually does the split. Our "delimiters" will be values that satisfy bigger; and we never want to throw them away, so let's keep them.
ascendingTuples = split . keepDelimsR $ whenElt bigger
The final step is just to throw together the bit that constructs the tuples, the bit that splits the tuples, and a last bit of munging to throw away the bits of the tuples we don't care about:
ascending = map (map fst) . ascendingTuples . pan
Let's try it out in ghci:
*Main> ascending [4,5,6,7,1,2,3,4,5,6,1,2]
[[4,5,6,7],[1,2,3,4,5,6],[1,2]]
*Main> ascending [7,6..1]
[[7],[6],[5],[4],[3],[2],[1]]
*Main> ascending []
[[]]
*Main> ascending [1]
[[1]]
P.S. In the current release of split, keepDelimsR is slightly stricter than it needs to be, and as a result ascending currently doesn't work with infinite lists. I've submitted a patch that makes it lazier, though.
ascend :: Ord a => [a] -> [[a]]
ascend xs = foldr f [] xs
where
f a [] = [[a]]
f a xs'#(y:ys) | a < head y = (a:y):ys
| otherwise = [a]:xs'
In ghci
*Main> ascend [4,5,6,7,1,2,3,4,5,6,1,2]
[[4,5,6,7],[1,2,3,4,5,6],[1,2]]
This problem is a natural fit for a paramorphism-based solution. Having (as defined in that post)
para :: (a -> [a] -> b -> b) -> b -> [a] -> b
foldr :: (a -> b -> b) -> b -> [a] -> b
para c n (x : xs) = c x xs (para c n xs)
foldr c n (x : xs) = c x (foldr c n xs)
para c n [] = n
foldr c n [] = n
we can write
partition_asc xs = para c [] xs where
c x (y:_) ~(a:b) | x<y = (x:a):b
c x _ r = [x]:r
Trivial, since the abstraction fits.
BTW they have two kinds of map in Common Lisp - mapcar
(processing elements of an input list one by one)
and maplist (processing "tails" of a list). With this idea we get
import Data.List (tails)
partition_asc2 xs = foldr c [] . init . tails $ xs where
c (x:y:_) ~(a:b) | x<y = (x:a):b
c (x:_) r = [x]:r
Lazy patterns in both versions make it work with infinite input lists
in a productive manner (as first shown in Daniel Fischer's answer).
update 2020-05-08: not so trivial after all. Both head . head . partition_asc $ [4] ++ undefined and the same for partition_asc2 fail with *** Exception: Prelude.undefined. The combining function g forces the next element y prematurely. It needs to be more carefully written to be productive right away before ever looking at the next element, as e.g. for the second version,
partition_asc2' xs = foldr c [] . init . tails $ xs where
c (x:ys) r#(~(a:b)) = (x:g):gs
where
(g,gs) | not (null ys)
&& x < head ys = (a,b)
| otherwise = ([],r)
(again, as first shown in Daniel's answer).
You can use a right fold to break up the list at down-steps:
foldr foo [] xs
where
foo x yss = (x:zs) : ws
where
(zs, ws) = case yss of
(ys#(y:_)) : rest
| x < y -> (ys,rest)
| otherwise -> ([],yss)
_ -> ([],[])
(It's a bit complicated in order to have the combining function lazy in the second argument, so that it works well for infinite lists too.)
One other way of approaching this task (which, in fact lays the fundamentals of a very efficient sorting algorithm) is using the Continuation Passing Style a.k.a CPS which, in this particular case applied to folding from right; foldr.
As is, this answer would only chunk up the ascending chunks however, it would be nice to chunk up the descending ones at the same time... preferably in reverse order all in O(n) which would leave us with only binary merging of the obtained chunks for a perfectly sorted output. Yet that's another answer for another question.
chunks :: Ord a => [a] -> [[a]]
chunks xs = foldr go return xs $ []
where
go :: Ord a => a -> ([a] -> [[a]]) -> ([a] -> [[a]])
go c f = \ps -> let (r:rs) = f [c]
in case ps of
[] -> r:rs
[p] -> if c > p then (p:r):rs else [p]:(r:rs)
*Main> chunks [4,5,6,7,1,2,3,4,5,6,1,2]
[[4,5,6,7],[1,2,3,4,5,6],[1,2]]
*Main> chunks [4,5,6,7,1,2,3,4,5,4,3,2,6,1,2]
[[4,5,6,7],[1,2,3,4,5],[4],[3],[2,6],[1,2]]
In the above code c stands for current and p is for previous and again, remember we are folding from right so previous, is actually the next item to process.
I'm very new to SML and I am trying a list exercise. The goal is sum up the previous numbers of a list and create a new list. For example, an input list [1, 4, 6, 9] would return [1, 5, 11, 20].
This is my solution so far, but I think the issue is with how I'm defining the function.
fun rec sum:int list -> int list =
if tl(list) = nil then
hd(list)
else
hd :: sum((hd(tail) + hd(tl(list)))::tl(tl(list)));
Besides that you are using rec as a function name, then you have some minor issues to work on.
The explicit type annotation you have made is treated as an annotation of the function result.
Thus, according to what you have written, then it should return a function and not the expected
list. This is clearly seen from the below example:
- fun rec_ sum : int list -> int list = raise Domain;
val rec_ = fn : 'a -> int list -> int list
Your should be careful of using the head and tail functions, when you don't do any checks on the
number of elements in the list. This could be done with either the length function, or (even
easier and often better) by pattern matching the number of elements.
Your code contains sum as a function call and tail as an variable. The variable tail has never
been defined, and using sum as a function call, makes me believe that you are actually using rec
as a keyword, but don't know what it means.
The keyword rec is used, when defining functions using the val keyword. In this case, rec is
needed to be able to define recursive functions (not a big surprise). In reality, the keyword fun
is syntactic sugar (a derived form) of val rec.
The following 3 are examples of how it could have been made:
The first is a simple, straight forward solution.
fun sumList1 (x::y::xs) = x :: sumList1 (x+y::xs)
| sumList1 xs = xs
This second example, uses a helper function, with an added argument (an accumulator). The list is constructed in the reverse order, to avoid using the slow append (#) operator. Thus we reverse the list before returning it:
fun sumList2 xs =
let
fun sumList' [] acc = rev acc
| sumList' [x] acc = rev (x::acc)
| sumList' (x :: y :: xs) acc = sumList' (y+x :: xs) (x :: acc)
in
sumList' xs []
end
The last example, show how small and easy it can be, if you use the standard list functions. Here the fold left is used, to go through all elements. Again note that the list is constructed in the reverse order, thus it is reversed as the last step:
fun sumList3 [] = []
| sumList3 (x::xs) = rev (foldl (fn (a, b) => hd b + a :: b) [x] xs)
try this -
fun recList ([], index, sum) = []
| recList (li, index, sum) =
if index=0 then
hd li :: recList (tl li, index+1, hd li)
else
sum + hd li :: recList (tl li, index+1, sum + hd li)
fun recSum li = recList (li, 0, 0)
In your case -
recSum([1,4,6,9]) ;
will give
val it = [1,5,11,20] : int list
also don't use rec as fun name -it keyword .
okay, this is probably going to be in the prelude, but: is there a standard library function for finding the unique elements in a list? my (re)implementation, for clarification, is:
has :: (Eq a) => [a] -> a -> Bool
has [] _ = False
has (x:xs) a
| x == a = True
| otherwise = has xs a
unique :: (Eq a) => [a] -> [a]
unique [] = []
unique (x:xs)
| has xs x = unique xs
| otherwise = x : unique xs
I searched for (Eq a) => [a] -> [a] on Hoogle.
First result was nub (remove duplicate elements from a list).
Hoogle is awesome.
The nub function from Data.List (no, it's actually not in the Prelude) definitely does something like what you want, but it is not quite the same as your unique function. They both preserve the original order of the elements, but unique retains the last
occurrence of each element, while nub retains the first occurrence.
You can do this to make nub act exactly like unique, if that's important (though I have a feeling it's not):
unique = reverse . nub . reverse
Also, nub is only good for small lists.
Its complexity is quadratic, so it starts to get slow if your list can contain hundreds of elements.
If you limit your types to types having an Ord instance, you can make it scale better.
This variation on nub still preserves the order of the list elements, but its complexity is O(n * log n):
import qualified Data.Set as Set
nubOrd :: Ord a => [a] -> [a]
nubOrd xs = go Set.empty xs where
go s (x:xs)
| x `Set.member` s = go s xs
| otherwise = x : go (Set.insert x s) xs
go _ _ = []
In fact, it has been proposed to add nubOrd to Data.Set.
import Data.Set (toList, fromList)
uniquify lst = toList $ fromList lst
I think that unique should return a list of elements that only appear once in the original list; that is, any elements of the orginal list that appear more than once should not be included in the result.
May I suggest an alternative definition, unique_alt:
unique_alt :: [Int] -> [Int]
unique_alt [] = []
unique_alt (x:xs)
| elem x ( unique_alt xs ) = [ y | y <- ( unique_alt xs ), y /= x ]
| otherwise = x : ( unique_alt xs )
Here are some examples that highlight the differences between unique_alt and unqiue:
unique [1,2,1] = [2,1]
unique_alt [1,2,1] = [2]
unique [1,2,1,2] = [1,2]
unique_alt [1,2,1,2] = []
unique [4,2,1,3,2,3] = [4,1,2,3]
unique_alt [4,2,1,3,2,3] = [4,1]
I think this would do it.
unique [] = []
unique (x:xs) = x:unique (filter ((/=) x) xs)
Another way to remove duplicates:
unique :: [Int] -> [Int]
unique xs = [x | (x,y) <- zip xs [0..], x `notElem` (take y xs)]
Algorithm in Haskell to create a unique list:
data Foo = Foo { id_ :: Int
, name_ :: String
} deriving (Show)
alldata = [ Foo 1 "Name"
, Foo 2 "Name"
, Foo 3 "Karl"
, Foo 4 "Karl"
, Foo 5 "Karl"
, Foo 7 "Tim"
, Foo 8 "Tim"
, Foo 9 "Gaby"
, Foo 9 "Name"
]
isolate :: [Foo] -> [Foo]
isolate [] = []
isolate (x:xs) = (fst f) : isolate (snd f)
where
f = foldl helper (x,[]) xs
helper (a,b) y = if name_ x == name_ y
then if id_ x >= id_ y
then (x,b)
else (y,b)
else (a,y:b)
main :: IO ()
main = mapM_ (putStrLn . show) (isolate alldata)
Output:
Foo {id_ = 9, name_ = "Name"}
Foo {id_ = 9, name_ = "Gaby"}
Foo {id_ = 5, name_ = "Karl"}
Foo {id_ = 8, name_ = "Tim"}
A library-based solution:
We can use that style of Haskell programming where all looping and recursion activities are pushed out of user code and into suitable library functions. Said library functions are often optimized in ways that are way beyond the skills of a Haskell beginner.
A way to decompose the problem into two passes goes like this:
produce a second list that is parallel to the input list, but with duplicate elements suitably marked
eliminate elements marked as duplicates from that second list
For the first step, duplicate elements don't need a value at all, so we can use [Maybe a] as the type of the second list. So we need a function of type:
pass1 :: Eq a => [a] -> [Maybe a]
Function pass1 is an example of stateful list traversal where the state is the list (or set) of distinct elements seen so far. For this sort of problem, the library provides the mapAccumL :: (s -> a -> (s, b)) -> s -> [a] -> (s, [b]) function.
Here the mapAccumL function requires, besides the initial state and the input list, a step function argument, of type s -> a -> (s, Maybe a).
If the current element x is not a duplicate, the output of the step function is Just x and x gets added to the current state. If x is a duplicate, the output of the step function is Nothing, and the state is passed unchanged.
Testing under the ghci interpreter:
$ ghci
GHCi, version 8.8.4: https://www.haskell.org/ghc/ :? for help
λ>
λ> stepFn s x = if (elem x s) then (s, Nothing) else (x:s, Just x)
λ>
λ> import Data.List(mapAccumL)
λ>
λ> pass1 xs = mapAccumL stepFn [] xs
λ>
λ> xs2 = snd $ pass1 "abacrba"
λ> xs2
[Just 'a', Just 'b', Nothing, Just 'c', Just 'r', Nothing, Nothing]
λ>
Writing a pass2 function is even easier. To filter out Nothing non-values, we could use:
import Data.Maybe( fromJust, isJust)
pass2 = (map fromJust) . (filter isJust)
but why bother at all ? - as this is precisely what the catMaybes library function does.
λ>
λ> import Data.Maybe(catMaybes)
λ>
λ> catMaybes xs2
"abcr"
λ>
Putting it all together:
Overall, the source code can be written as:
import Data.Maybe(catMaybes)
import Data.List(mapAccumL)
uniques :: (Eq a) => [a] -> [a]
uniques = let stepFn s x = if (elem x s) then (s, Nothing) else (x:s, Just x)
in catMaybes . snd . mapAccumL stepFn []
This code is reasonably compatible with infinite lists, something occasionally referred to as being “laziness-friendly”:
λ>
λ> take 5 $ uniques $ "abacrba" ++ (cycle "abcrf")
"abcrf"
λ>
Efficiency note:
If we anticipate that it is possible to find many distinct elements in the input list and we can have an Ord a instance, the state can be implemented as a Set object rather than a plain list, this without having to alter the overall structure of the solution.
Here's a solution that uses only Prelude functions:
uniqueList theList =
if not (null theList)
then head theList : filter (/= head theList) (uniqueList (tail theList))
else []
I'm assuming this is equivalent to running two or three nested "for" loops (running through each element, then running through each element again to check for other elements with the same value, then removing those other elements) so I'd estimate this is O(n^2) or O(n^3)
Might even be better than reversing a list, nubbing it, then reversing it again, depending on your circumstances.