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Monads as containers - HaskellWiki - 0 views

  • A monad is a container type together with a few methods defined on it.
  • all the elements which a monadic container holds at any one time must be the same type (it is homogeneous).
  • map (fmap), return and join,
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  • map, (but called fmap in Haskell 98) actually comes from the definition of a functor
  • That is, if f is a functor, and we are given a function of type (a -> b), and a container of type (f a), we can get a new container of type (f b). This is expressed in the type of fmap: fmap :: (Functor f) => (a -> b) -> f a -> f b If you will give me a blueberry for each apple I give you (a -> b), and I have a box of apples (f a), then I can get a box of blueberries (f b). Every monad is a functor.
  • The second method, return, is specific to monads. If m is a monad, then return takes an element of type a, and gives a container of type (m a) with that element in it. So, its type in Haskell is return :: (Monad m) => a -> m a If I have an apple (a) then I can put it in a box (m a).
  • takes a container of containers m (m a), and combines them into one m a in some sensible fashion. Its Haskell type is join :: (Monad m) => m (m a) -> m a
  • If I have a box of boxes of apples (m (m a)) then I can take the apples from each, and put them in a new box (m a).
  • bind or extend, which is commonly given the symbol (>>=)
  • liftM :: (Monad m) => (a -> b) -> m a -> m b liftM f xs = xs >>= (return . f) -- take a container full of a's, to each, apply f, -- put the resulting value of type b in a new container, -- and then join all the containers together.
  • The function that does this for any monad in Haskell is called liftM -- it can be written in terms of return and bind as follows:
  • Well, in Haskell, IO is a monad.
  • Lists are most likely the simplest, most illustrative example
  • The reason that bind is so important is that it serves to chain computations on monadic containers together.
  • You might notice a similarity here between bind and function application or composition, and this is no coincidence.
  • What bind does is to take a container of type (m a) and a function of type (a -> m b). It first maps the function over the container, (which would give an m (m b)) and then applies join to the result to get a container of type (m b). Its type and definition in Haskell is the
  • xs >>= f = join (fmap f xs)
  • bind (>>=)
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99 questions/1 to 10 - HaskellWiki - 0 views

  • data NestedList a = Elem a | List [NestedList a]   flatten :: NestedList a -> [a] flatten (Elem x) = [x] flatten (List x) = concatMap flatten x
  • compress :: Eq a => [a] -> [a] compress = map head . group We simply group equal values together (group), then take the head of each. Note that (with GHC) we must give an explicit type to compress otherwise we get:
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Bluish Coder: Dynamic Compilation and Loading of Modules in Haskell - 0 views

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    The Haskell system GHC has libraries that provide the ability to compile Haskell code and dynamically load it into a running Haskell program. A library that provides this functionality is hs-plugins. Unfortunately hs-plugins doesn't work with the latest GHC release, 6.10.1.
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Existential type - HaskellWiki - 0 views

  • First of all, it is now impossible for a function to demand a Worker having a specific type of buffer. Second, the type of foo can now be derived automatically without needing an explicit type signature. (No monomorphism restriction.) Thirdly, since code now has no idea what type the buffer function returns, you are more limited in what you can do to it.
  • This illustrates creating a heterogeneous list, all of whose members implement "Show", and progressing through that list to show these items: data Obj = forall a. (Show a) => Obj a   xs :: [Obj] xs = [Obj 1, Obj "foo", Obj 'c']   doShow :: [Obj] -> String doShow [] = "" doShow ((Obj x):xs) = show x ++ doShow xs With output: doShow xs ==> "1\"foo\"'c'"
  • Existential types in conjunction with type classes can be used to emulate the dynamic dispatch mechanism of object oriented programming languages. To illustrate this concept I show how a classic example from object oriented programming can be encoded in Haskell.
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Programming errors in traversal programs over structured data - 0 views

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    Traversal strategies `a la Stratego (also `a la Strafunski and 'Scrap Your Boilerplate') provide an exceptionally versatile and uniform means of querying and transforming deeply nested and heterogeneously structured data including terms in functional programming and rewriting, objects in OO programming, and XML documents in XML programming. However, the resulting traversal programs are prone to programming errors. We are specifically concerned with errors that go beyond conservative type errors; examples we examine include divergent traversals, prematurely terminated traversals, and traversals with dead code. Based on an inventory of possible programming errors we explore options of static typing and static analysis so that some categories of errors can be avoided. This exploration generates suggestions for improvements to strategy libraries as well as their underlyingq programming languages. Haskell is used for illustrations and specifications with sufficient explanations to make the presentation comprehensible to the non-specialist. The overall ideas are language-agnostic and they are summarized accordingly.
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Hoogle - 0 views

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    Hoogle is a Haskell API search engine, which allows you to search many standard Haskell libraries by either function name, or by approximate type signature.
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The Haskell 98 Library Report: Arrays - 0 views

  • 16.2  Incremental Array Updates The operator (//) takes an array and a list of pairs and returns an array identical to the left argument except that it has been updated by the associations in the right argument. (As with the array function, the indices in the association list must be unique for the updated elements to be defined.) For example, if m is a 1-origin, n by n matrix, then m//[((i,i), 0) | i <- [1..n]] is the same matrix, except with the diagonal zeroed.
  • -- A rectangular subarray subArray :: (Ix a) => (a,a) -> Array a b -> Array a b subArray bnds = ixmap bnds (\i->i) -- A row of a matrix row :: (Ix a, Ix b) => a -> Array (a,b) c -> Array b c row i x = ixmap (l',u') (\j->(i,j)) x where ((_,l'),(_,u')) = bounds x -- Diagonal of a matrix (assumed to be square) diag :: (Ix a) => Array (a,a) b -> Array a b diag x = ixmap (l,u) (\i->(i,i)) x        where           ((l,_),(u,_)) = bounds x -- Projection of first components of an array of pairs firstArray :: (Ix a) => Array a (b,c) -> Array a b firstArray = fmap (\(x,y)->x)
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A Neighborhood of Infinity: Haskell Monoids and their Uses - 0 views

  • The Writer MonadYou can think of monoids as being accumulators. Given a running total, n, we can add in a new value a to get a new running total n' = n `mappend` a. Accumulating totals is a very common design pattern in real code so it's useful to abstract this idea. This is exactly what the Writer monad allows. We can write monadic code that accumulates values as a "side effect". The function to perform the accumulation is (somewhat confusingly) called tell. Here's an example where we're logging a trace of what we're doing.
  • This is an implementation of the factorial function that tells us what it did.
  • We use runWriter to extract the results back out. If we run> ex1 = runWriter (fact1 10)we get back both 10! and a list of what it took to compute this.
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  • and the monoid for addition is Sum
  • but there is a big advantage to using the Writer version. It has type signature f :: Integer -> Writer (Sum Integer) Integer. We can immediately read from this that our function has a side effect that involves accumulating a number in a purely additive way.
  • This is the Bool type with the disjunction operator, better known as ||.
  • "tell my caller if any value of r is ever 120"
  • One last application to mention is the Data.Foldable library. This provides a generic approach to walking through a datastructure, accumulating values as we go. The foldMap function applies a function to each element of our structure and then accumulates the return values of each of these applications. An implementation of foldMap for a tree structure might be
  • Suppose we want to accumulate two side effects at the same time. For example, maybe we want to both count instructions and leave a readable trace of our computation. We could use monad transformers to combine two writer monads. But there is a slightly easier way - we can combine two monoids into one 'product' monoid. It's defined like this:instance (Monoid a,Monoid b) => Monoid (a,b) where mempty = (mempty,mempty) mappend (u,v) (w,x) = (u `mappend` w,v `mappend` x)
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