Last updated: 2016-08-03 14:49:53 -0700

Upstream URL: git clone http://chriswarbo.net/git/ifcxt.git


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Contents of README.md follows


This package introduces the function:

ifCxt :: IfCxt cxt => proxy cxt -> (cxt => a) -> a -> a

This function acts like an if statement where the proxy cxt parameter is the condition. If the type checker can satisfy the cxt constraint, then the second argument cxt => a is returned; otherwise, the third argument a is returned.

Before seeing more details about how ifCxt is implemented, let’s look at three examples of how to use it.

Example 1: show every type

The cxtShow function below is polymorphic over the type a. If a is an instance of Show, then cxtShow a evaluates to show a; but if a is not an instance of Show, cxtShow a evaluates to <<unshowable>>.

cxtShow :: forall a. IfCxt (Show a) => a -> String
cxtShow a = ifCxt (Proxy::Proxy (Show a))
    (show a)

In ghci:

ghci> cxtShow (1 :: Int)
ghci> cxtShow (id :: a -> a)

Example 2: make your code asymptotically efficient

The nub function removes duplicate elements from lists. It can be defined as:

nub :: Eq a => [a] -> [a]
nub []     =  []
nub (x:xs) =  x : nub (filter (x/=) xs)

This function takes time O(n^2). But if we also have an Ord constraint, we can define a much more efficient version that takes time O(n log n):

nubOrd :: Ord a => [a] -> [a]
nubOrd = go . sort
        go (x1:x2:xs)
            | x1==x2    =      go (x2:xs)
            | otherwise = x1 : go (x2:xs)
        go [x] = [x]
        go []  = []

Now, we can use the ifCxt function to define a version of nub that will automatically select the most efficient implementation for whatever type we happen to run it on:

cxtNub :: forall a. (Eq a, IfCxt (Ord a)) => [a] -> [a]
cxtNub = ifCxt (Proxy::Proxy (Ord a)) nubOrd nub

Example 3: make your code numerically stable

The simplest way to sum a list of numbers is:

sumSimple :: Num a => [a] -> a
sumSimple = foldl' (+) 0

This method has numerical stability issues on floating point representations. Kahan summation is a more accurate technique shown below:

sumKahan :: Num a => [a] -> a
sumKahan = snd . foldl' go (0,0)
        go (c,t) i = ((t'-t)-y,t')
                y = i-c
                t' = t+y

Because Kahan summation does a lot more work than simple summation, we would prefer not to run it on non-floating point types. The sumCxt function below accomplishes this:

cxtSum :: forall a. (Num a, IfCxt (Floating a)) => [a] -> a
cxtSum = ifCxt (Proxy::Proxy (Floating a)) sumKahan sumSimple

Notice that the ifCxt function is conditioning on the Floating a constraint, which isn’t actually used by the sumKahan function.

How it works

The magic of the technique is in the IfCxt class:

class IfCxt (cxt :: Constraint) where
    ifCxt :: proxy cxt -> (cxt => a) -> a -> a

(Notice that making a constraint an instance of a class requires theConstraintKinds extension, and the higher order (cxt => a) parameter requires the RankNTypes extension.)

There is a “global” instance defined as:

instance {-# OVERLAPPABLE #-} IfCxt cxt where ifCxt _ t f = f

What this says is that if no more specific instance is available, then the “global” ifCxt function will be used, which always returns the f (false) parameter.

Then for every instance of every other class, we need to define an overlapping IfCxt instance that always returns the t (true) parameter. For example, for Show Int, we define:

instance {-# OVERLAPS #-} IfCxt (Show Int) where ifCxt _ t f = t

This is a lot of boilerplate, so the template haskell function mkIfCxtInstances can be used to define these instances automatically. Unfortunately, due to a bug in template haskell we cannot enumerate all the classes currently in scope. So you must manually call mkIfCxtInstances on each class you want ifCxt to work with.