June 2009 - Haskell-Cafe

PatternSignatures (rant)
by Johannes Waldmann 06 Apr '18

06 Apr '18

Dear all, (this is a rant - please ignore) why has "PatternSignatures" been renamed to "ScopedTypeVariables" (in ghc-6.10)? show me the alleged "type variable" in this code: do x :: Int <- [ 1 .. 10 ] ; return $ x^2 and why on earth do I need to use a language extension at all to get to the most basic thing of declarative programming: to declare the type of an identifier? This seriously hurts (me, at least) when teaching Haskell. Thanks - J.W.

4 4

Commutative monads vs Applicative functors
by Ronald Guida 09 Jul '16

09 Jul '16

I have a few questions about commutative monads and applicative functors. >From what I have read about applicative functors, they are weaker than monads because with a monad, I can use the results of a computation to select between alternative future computations and their side effects, whereas with an applicative functor, I can only select between the results of computations, while the structure of those computations and their side effects are fixed in advance. But then there are commutative monads. I'm not exactly sure what a commutative monad is, but my understanding is that in a commutative monad the order of side effects does not matter. This leads me to wonder, are commutative monads still stronger than applicative functors, or are they equivalent? And by the way, what exactly is a commutative monad?

6 6

Cannot understand liftM2
by Nicola Paolucci 13 Feb '12

13 Feb '12

Hi All, I'm loving learning Haskell quite a bit. It is stretching my brain but in a delightfull way. I've googled, I've hoogled but I haven't found a clear explanation for what exactly liftM2 does in the context below. Using the cool lambdabot "pointless" utility I found out that: > \x -> snd(x) - fst(x) is the same as: > liftM2 (-) snd fst I like the elegance of this but I cannot reconcile it with its type. I can't understand it. I check the signature of liftM2 and I get: Prelude> :t liftM2 Prelude> liftM2 :: (Monad m) => (a1 -> a2 -> r) -> m a1 -> m a2 -> m r Can someone help me understand what's happening here ? What does a Monad have to do with a simple subtraction ? What is actually the "m" of my example ? I am sure if I get this I'll be another step closer to illumination ... Thanks, Nick

15 18

Infinite types should be optionally allowed
by Job Vranish 22 Feb '11

22 Feb '11

There are good reasons against allowing infinite types by default (mostly, that a lot of things type check that are normally not what we want). An old haskell cafe conversation on the topic is here: http://www.nabble.com/There%27s-nothing-wrong-with-infinite-types!-td771373… However, I think infinite types should be allowed, but only with an explicit type signature. In other words, don't allow infinite types to be inferred, but if they are specified, let them pass. I think it would be very hard to shoot yourself in the foot this way. Newtype is the standard solution to situations where you really need an infinite type, but in some cases this can be a big annoyance. Using newtype sacrifices data type abstraction and very useful type classes like Functor. You can use multiparameter type classes and functional dependencies to recover some of the lost abstraction, but then type checking becomes harder to reason about and the code gets way more ugly (If you doubt, let me know, I have some examples). Allowing infinite types would fix this. I'm imagining a syntax something like this: someFunctionThatCreatesInfiniteType :: a -> b | b = [(a, b)] Thoughts? Opinions? Am I missing anything obvious? - Job

3 10

IORef memory leak
by Jim Snow 15 Oct '10

15 Oct '10

I'm having some trouble with excessive memory use in a program that uses a lot of IORefs. I was able to write a much simpler program which exhibits the same sort of behavior. It appears that "modifyIORef" and "writeIORef" leak memory; perhaps they keep a reference to the old value. I tried both ghc-6.8.3 and ghc-6.10.1. Is this a known limitation, or is this a ghc bug, or am I using IORefs in the wrong way? -jim module Main where import Data.IORef import Control.Monad -- Leaks memory leakcheck1 ior = do go 1000000000 where go 0 = return () go n = do modifyIORef ior (+1) go (n-1) -- Leaks memory leakcheck2 ior = do go 1000000000 where go 0 = return () go n = do x <- readIORef ior writeIORef ior (x+1) go (n-1) -- Runs in constant memory leakcheck3 ior = do go 1000000000 where go 0 = return () go n = do x <- readIORef ior go (n-1) main :: IO () main = do ior <- newIORef 0 leakcheck2 ior compiled with: ghc -O2 --make Leak.hs -o Leak

10 17

Help with Bird problem 3.3.3
by Peter Hilal 11 Jun '10

11 Jun '10

I'm working my way through Bird's _Introduction to Functional Programming Using Haskell_. I'd appreciate any help with problem 3.3.3, which is: "Division of natural numbers can be specified by the condition (n * m) / n = m for all positive n and all m. Construct a program for division and prove that it meets the specification." The required construction relies on the following definitions: data Nat = Zero| Succ Nat (+) :: Nat -> Nat m + Zero = m m + Succ n = Succ (m + n) (*) :: Nat -> Nat m * Zero = Zero m * Succ n = m * n + m Proceeding as Bird does in Sec. 3.2.2, where he derives the definition of "-" from the specification "(m + n) - n = m", I've so far gotten the first case, in which m matches the pattern "Zero", simply by (i) substituting Zero for m in the specification, (ii) substituting Succ n for n in the specification (solely because n is constrained to be positive), and (iii) reducing by applying the first equation of "*": Case Zero: (Succ n * Zero) / Succ n = Zero ≡ {first equation of "*"} Zero / Succ n = Zero Easy enough, and completely intuitive, since we expect Zero divided by any non-Zero finite number to be Zero. The next case, in which m matches the pattern "Succ m", is where I get stuck, and I really have no intuition about what the definition is supposed to be. My first step is to substitute "Succ m" for "m" in the given specification, and to substitute Succ n for n in the specification (for the same reason, as above, that n is constrained to be positive), and then to use the definition of "*" to reduce the equation: Case Succ m: Succ n * Succ m / Succ n = Succ m ≡ {second equation of "*"} (Succ n * m + Succ n) / Succ n = Succ m Where do I go from here? Thank you so much.

5 4

really difficult for a beginner like me...
by Ivan Amarquaye 24 Mar '10

24 Mar '10

Hi everyone, this is my first posting on here and this was what drove me here and the quest to know more as i anticipate a lot of help and direction in this quite new and different environment haskell.I have this paper that i'm working on and need to solve these scenarios/ cases based on some sample codes: Scenarios/cases: 1) Allow words to be hyphenated and treat the hyphenated word as a single word (including the hyphen). 2) As for no. 2 but if the hyphen is the last character on a line treat the hyphenated word as a single word without the hyphen. 3) Treat a capitalised word (one or more capital letters) the same as lower case, i.e. only the lower case word appears in the index. 4) Treat a word ending in an ‘s’ as a plural and thus the same as the singular, i.e. only the singular appears in the index. 5) As for no. 5 but (a) treat suffix ‘ss’ as not a plural; and (b) treat the plural suffixes ‘sses’, ‘zzes’, ‘oes’, ‘xes’, ‘shes’, ‘ches’ the same as the singular, i.e. without the ‘es’, e.g. “branches” (except for 4- and 5-letter plurals with suffices ‘oes’ and ‘ches’, e.g. “floes”, and 4-letter plural suffix ‘xes’); and (c) treat the plural suffix ‘ies’ (except for 4-letter plurals, e.g. “pies”) as the singular suffix ‘y’. 6) Make the output more readable in the form of an index table. 7) Use an output file 8) Include a user-friendly menu by which the user can choose input and output file names. This is the code i'm supposed tomodify and in some cases create new functions to support.I also need some explanation as the various approaches in solving them.............................................................................................. The function makeIndex given a document produces a list of entries. Each entry is a word and a list of line numbers (for words > 4 letters) Type definitions: import Prelude -- hiding (Word) -- predefined Word hidden, so we can define ours -- type String = [Char] defined in Prelude type Doc = String type Line = String type Word = String -- our version makeIndex :: Doc -> [ ([Int], Word) ] A data-directed design considers a sequence of functions (i.e using composition operator ‘.’) to transform the document of type, Doc, into an index of type, [ ([Int], Word) ]. splitUp the document, doc, into a list of lines, [Line]. numLines pairs each line with a line number, [(Int, Line)]. allNumWords splits lines into words and line no., [(Int, Word)]. sortLs sorts words into alphabetical order, [(Int, Word)]. makeLists makes a list for each line number, [([Int], Word)]. amalgamate nos. into a list of nos. for each word, [([Int], Word)]. shorten into a list for words > 4 letters, [([Int], Word)]. makeIndex = shorten . -- [([Int], Word)] -> [([Int], Word)] amalgamate . -- [([Int], Word)] -> [([Int], Word)] makeLists . -- [(Int, Word)] -> [([Int], Word)] sortLs . -- [(Int, Word)] -> [(Int, Word)] allNumWords . -- [(Int, Line)] -> [(Int, Word)] numLines . -- [Line] -> [(Int, Line)] splitUp -- Doc -> [Line] Last -- [a] -> [a ] splitUp function splitUp :: Doc -> [Line] splitUp [] = [] splitUp text = takeWhile (/='\n') text : -- first line (splitUp . -- splitup other lines dropWhile (==’\n’) . -- delete 1st newline(s) dropWhile (/='\n')) text -- other lines Example: splitUp “hello world\n\nnext world” => [“hello world”, “next world”] numLines function: numLines :: [Line] -> [(Int, Line)] numLines lines -- list of pairs of = zip [1 .. length lines] lines -- line no. & line Example: numLines [“hello world”, “next world”] => [(1, “hello world”), (2, “next world”)] splitWords function: -- for each line -- a) split into words -- b) attach line no. to each word splitWords :: Line -> [Word] -- a) splitWords [ ] = [ ] splitWords line = takeWhile isLetter line : -- first word in line (splitWords . -- split other words dropWhile (not.isLetter && Last ==’-’) . -- delete separators dropWhile isLetter) line -- other words where isLetter ch = (‘a’<=ch) && (ch<=’z’) || (‘A’<=ch) && (ch<=’Z’) Example: splitWords “hello world” => [“hello”, “world”] allNumWords function: numWords :: (Int, Line) -> [(Int, Word)] -- b) numWords (number, line) = map addLineNum ( splitWords line) -- all line pairs where addLineNum word = (number, word) -- a pair allNumWords :: [(Int, Line)] -> [(Int, Word)] allNumWords = concat . map numWords -- doc pairs Examples: addLineNum “hello” => (1, “hello”) numWords (1, “hello world”) => [(1, “hello”), (1, “world”)] allNumWords [(1, “hello world”), (2, “next world”)] => [(1, “hello”), (1, “world”), (2, “next”), (2, “world”)] SortLs function: sortLs :: [(Int, Word)] -> [(Int, Word)] sortLs [ ] = [ ] sortLs (a:x) = sortLs [b | b <- x, compare b a] -- sort 1st half ++ [a] ++ -- 1st in middle sortLs [b | b <- x, compare a b] -- sort 2nd half where compare (n1, w1) (n2, w2) = (w1 < w2) -- 1st word less || (w1 == w2 && n1 < n2) -- check no. Example: sortLs [(1, “hello”), (1, “world”), (2, “next”), (2, “world”)] => [(1, “hello”), (2, “next”), (1, “world”), (2, “world”)] makeLists function: makeLists :: [(Int, Word)] -> [([Int], Word)] makeLists = map mk -- all pairs where mk (num, word) = ([num], word) -- list of single no. Examples: mk (1, “hello”) => ([1], “hello”) makeLists [(1, “hello”), (2, “next”), (1, “world”), (2, “world”)] => [([1], “hello”), ([2], “next”), ([1], “world”), ([2], “world”)] Amalgamate function: amalgamate :: [([Int], Word)] -> [([Int], Word)] amalgamate [ ] = [ ] amalgamate [a] = [a] amalgamate ((n1, w1) : (n2, w2) : rest) -- pairs of pairs | w1 /= w2 = (n1, w1) : amalgamate ((n2, w2) : rest) | otherwise = amalgamate ((n1 ++ n2, w1) : rest) -- if words are same grow list of numbers Example: amalgamate [([1], “hello”), ([2], “next”), ([1], “world”), ([2], “world”)] => [([1], “hello”), ([2], “next”), ([1, 2], “world”)] Shorten function: shorten :: [([Int], Word)] -> [([Int], Word)] shorten = filter long -- keep pairs >4 where long (num, word) = length word > 4 -- check word >4 Example: shorten [([1], “hello”), ([2], “next”), ([1, 2], “world”)] => [([1], “hello”), ([1, 2], “world”)] _________________________________________________________________ Connect to the next generation of MSN Messenger http://imagine-msn.com/messenger/launch80/default.aspx?locale=en-us&source=…

6 8

Arch Haskell News: Nov 23 2008
by Don Stewart 16 Jan '10

16 Jan '10

News about Haskell on Arch Linux * Arch now has 734 Haskell packages now * That’s an increase of 29 new packages in the last 8 days! * 3.6 new Haskell releases are occuring each day. Noteworthy, * haskell-hledger-0.2: “A ledger-compatible text-based accounting tool.” * gitit-0.3.1: “Wiki using HAppS, git, and pandoc.” * lhc-20081121: “Lhc Haskell Compiler” * haskell-hosc-0.6: “Haskell Open Sound Control” * haskell-flickr-0.3.2: “Haskell binding to the Flickr API” * haskell-delicious-0.3.2: “Accessing the del.icio.us APIs from Haskell (v2)” * haskell-mediawiki 0.2.3: “Interfacing with the MediaWiki API” * darcs-2.1.2.2: “a distributed, interactive, smart revision control system” Full update list, http://archhaskell.wordpress.com/2008/11/24/arch-haskell-news-nov-23-2008/ -- Don

24 56

Performance of functional priority queues
by Richard O'Keefe 29 Dec '09

29 Dec '09

There's a current thread in the Erlang mailing list about priority queues. I'm aware of, for example, the Brodal/Okasaki paper and the David King paper. I'm also aware of James Cook's priority queue package in Hackage, have my own copy of Okasaki's book, and have just spent an hour searching the web. One of the correspondents in that thread claims that it is provably impossible to have an efficient priority queue implementation without mutability. I think he's cuckoo. But I'd like to have some numbers to back me up. Can anyone point me to some actual benchmark results comparing priority queue performance *with* mutation and priority queue performance *without* mutation, in the same functional or mostly-functional language?

16 24

Re: Code and Perf. Data for Prime Finders (was: Genuine Eratosthenes sieve)
by Dave Bayer 29 Dec '09

29 Dec '09

Here is another prime sieve. It is about half the length of the fastest contributed code (ONeillPrimes) and nearly as fast until it blows up on garbage collection: > % cat ONeillPrimes.hs | grep -v "^--" | wc > 185 1105 6306 > % cat BayerPrimes.hs | grep -v "^--" | wc > 85 566 2418 > > [Integer] -O 1*10^6 2*10^6 3*10^6 4*10^6 5*10^6 > --------------------------------------------------------- > ONeillPrimes | 3.555 | 7.798 | 12.622 | 18.927 | 23.529 > BayerPrimes | 3.999 | 8.895 | 18.003 | 22.977 | 38.053 I wrote this as an experiment in coding data structures in Haskell's lazy evaluation model, rather than as explicit data. The majority of the work done by this code is done by "merge"; the multiples of each prime percolate up through a tournament consisting of a balanced tree of suspended "merge" function calls. In order to create an infinite lazy balanced tree of lists, the datatype > data List a = A a (List a) | B [a] is used as scaffolding. One thinks of the root of the infinite tree as starting at the leftmost child, and crawling up the left spine as necessary. What I'm calling a "venturi" > venturi :: Ord a => [[a]] -> [a] merges an infinite list of infinite lists into one list, under the assumption that each list, and the heads of the lists, are in increasing order. This could be a generally useful function. If one can think of a better way to write "venturi", swapping in your code would in particular yield a faster prime sieve. I found that a tertiary merge tree was faster than a binary merge tree, because this leads to fewer suspensions. One can speed this code up a bit by interleaving strict and lazy calls, but I prefer to leave the code short and readable. It is bizarre that > trim p = let f m x = mod x m /= 0 in filter (f p) lurks in the prime sieve code, but it is only used with primes of size up to the square root of the largest output prime. I tried more thoughtful alternatives, and they all slowed down the sieve. Sometimes dumb is beautiful. Thanks to apfelmus for various helpful remarks that lead me to think of this approach. Here is the code: > module BayerPrimes (venturi,primes) where > > -- Code for venturi :: Ord a => [[a]] -> [a] > > merge :: Ord a => [a] -> [a] -> [a] -> [a] > merge xs@(x:xt) ys@(y:yt) zs@(z:zt) > | x <= y = if x <= z > then x : (merge xt ys zs) > else z : (merge xs ys zt) > | otherwise = if y <= z > then y : (merge xs yt zs) > else z : (merge xs ys zt) > merge _ _ _ = undefined > > data List a = A a (List a) | B [a] > > mergeA :: Ord a => List a -> List a -> List a -> List a > mergeA (A x xt) ys zs = A x (mergeA xt ys zs) > mergeA (B xs) ys zs = mergeB xs ys zs > > mergeB :: Ord a => [a] -> List a -> List a -> List a > mergeB xs@(x:xt) ys@(A y yt) zs = case compare x y of > LT -> A x (mergeB xt ys zs) > EQ -> A x (mergeB xt yt zs) > GT -> A y (mergeB xs yt zs) > mergeB xs (B ys) zs = mergeC xs ys zs > mergeB _ _ _ = undefined > > mergeC :: Ord a => [a] -> [a] -> List a -> List a > mergeC xs@(x:xt) ys@(y:yt) zs@(A z zt) > | x < y = if x < z > then A x (mergeC xt ys zs) > else A z (mergeC xs ys zt) > | otherwise = if y < z > then A y (mergeC xs yt zs) > else A z (mergeC xs ys zt) > mergeC xs ys (B zs) = B $ merge xs ys zs > mergeC _ _ _ = undefined > > root :: Ord a => List a -> [List a] -> [a] > root (A x xt) yss = x : (root xt yss) > root (B xs) (ys:zs:yst) = root (mergeB xs ys zs) yst > root _ _ = undefined > > wrap :: [a] -> List a > wrap [] = B [] > wrap (x:xt) = A x $ B xt > > triple :: Ord a => [List a] -> [List a] > triple (x:y:z:xs) = mergeA x y z : (triple xs) > triple _ = undefined > > group :: Ord a => [List a] -> [List a] > group (x:y:xt) = x : y : (group $ triple xt) > group _ = undefined > > venturi :: Ord a => [[a]] -> [a] > venturi (x:xt) = root (wrap x) $ group $ map wrap xt > venturi _ = undefined > > -- Code for primes :: Integral a => [a] > > diff :: Ord a => [a] -> [a] -> [a] > diff xs@(x:xt) ys@(y:yt) = case compare x y of > LT -> x : (diff xt ys) > EQ -> (diff xt yt) > GT -> (diff xs yt) > diff _ _ = undefined > > trim :: Integral a => a -> [a] -> [a] > trim p = let f m x = mod x m /= 0 in filter (f p) > > seed :: Integral a => [a] > seed = [2,3,5,7,11,13,17] > > wheel :: Integral a => [a] > wheel = drop 1 [ m*j + k | j <- [0..], k <- ws ] > where m = foldr1 (*) seed > ws = foldr trim [1..m] seed > > multiples :: Integral a => [a] -> [[a]] > multiples ws = map fst $ tail $ iterate g ([], ws) > where g (_,ps@(p:pt)) = ([ m*p | m <- ps ], trim p pt) > g _ = undefined > > primes :: Integral a => [a] > primes = seed ++ (diff wheel $ venturi $ multiples wheel)

6 8