I am studying Haskell currently and try to understand a project that uses Haskell to implement cryptographic algorithms. After reading Learn You a Haskell for Great Good online, I begin to understand the code in that project. Then I found I am stuck at the following code with the "#" symbol:
-- | Generate an #n#-dimensional secret key over #rq#.
genKey :: forall rq rnd n . (MonadRandom rnd, Random rq, Reflects n Int)
=> rnd (PRFKey n rq)
genKey = fmap Key $ randomMtx 1 $ value #n
Here the randomMtx is defined as follows:
-- | A random matrix having a given number of rows and columns.
randomMtx :: (MonadRandom rnd, Random a) => Int -> Int -> rnd (Matrix a)
randomMtx r c = M.fromList r c <$> replicateM (r*c) getRandom
And PRFKey is defined below:
-- | A PRF secret key of dimension #n# over ring #a#.
newtype PRFKey n a = Key { key :: Matrix a }
All information sources I can find say that # is the as-pattern, but this piece of code is apparently not that case. I have checked the online tutorial, blogs and even the Haskell 2010 language report at https://www.haskell.org/definition/haskell2010.pdf. There is simply no answer to this question.
More code snippets can be found in this project using # in this way too:
-- | Generate public parameters (\( \mathbf{A}_0 \) and \(
-- \mathbf{A}_1 \)) for #n#-dimensional secret keys over a ring #rq#
-- for gadget indicated by #gad#.
genParams :: forall gad rq rnd n .
(MonadRandom rnd, Random rq, Reflects n Int, Gadget gad rq)
=> rnd (PRFParams n gad rq)
genParams = let len = length $ gadget #gad #rq
n = value #n
in Params <$> (randomMtx n (n*len)) <*> (randomMtx n (n*len))
I deeply appreciate any help on this.
That #n is an advanced feature of modern Haskell, which is usually not covered by tutorials like LYAH, nor can be found the the Report.
It's called a type application and is a GHC language extension. To understand it, consider this simple polymorphic function
dup :: forall a . a -> (a, a)
dup x = (x, x)
Intuitively calling dup works as follows:
the caller chooses a type a
the caller chooses a value x of the previously chosen type a
dup then answers with a value of type (a,a)
In a sense, dup takes two arguments: the type a and the value x :: a. However, GHC is usually able to infer the type a (e.g. from x, or from the context where we are using dup), so we usually pass only one argument to dup, namely x. For instance, we have
dup True :: (Bool, Bool)
dup "hello" :: (String, String)
...
Now, what if we want to pass a explicitly? Well, in that case we can turn on the TypeApplications extension, and write
dup #Bool True :: (Bool, Bool)
dup #String "hello" :: (String, String)
...
Note the #... arguments carrying types (not values). Those are something that exists at compile time, only -- at runtime the argument does not exist.
Why do we want that? Well, sometimes there is no x around, and we want to prod the compiler to choose the right a. E.g.
dup #Bool :: Bool -> (Bool, Bool)
dup #String :: String -> (String, String)
...
Type applications are often useful in combination with some other extensions which make type inference unfeasible for GHC, like ambiguous types or type families. I won't discuss those, but you can simply understand that sometimes you really need to help the compiler, especially when using powerful type-level features.
Now, about your specific case. I don't have all the details, I don't know the library, but it's very likely that your n represents a kind of natural-number value at the type level. Here we are diving in rather advanced extensions, like the above-mentioned ones plus DataKinds, maybe GADTs, and some typeclass machinery. While I can't explain everything, hopefully I can provide some basic insight. Intuitively,
foo :: forall n . some type using n
takes as argument #n, a kind-of compile-time natural, which is not passed at runtime. Instead,
foo :: forall n . C n => some type using n
takes #n (compile-time), together with a proof that n satisfies constraint C n. The latter is a run-time argument, which might expose the actual value of n. Indeed, in your case, I guess you have something vaguely resembling
value :: forall n . Reflects n Int => Int
which essentially allows the code to bring the type-level natural to the term-level, essentially accessing the "type" as a "value". (The above type is considered an "ambiguous" one, by the way -- you really need #n to disambiguate.)
Finally: why should one want to pass n at the type level if we then later on convert that to the term level? Wouldn't be easier to simply write out functions like
foo :: Int -> ...
foo n ... = ... use n
instead of the more cumbersome
foo :: forall n . Reflects n Int => ...
foo ... = ... use (value #n)
The honest answer is: yes, it would be easier. However, having n at the type level allows the compiler to perform more static checks. For instance, you might want a type to represent "integers modulo n", and allow adding those. Having
data Mod = Mod Int -- Int modulo some n
foo :: Int -> Mod -> Mod -> Mod
foo n (Mod x) (Mod y) = Mod ((x+y) `mod` n)
works, but there is no check that x and y are of the same modulus. We might add apples and oranges, if we are not careful. We could instead write
data Mod n = Mod Int -- Int modulo n
foo :: Int -> Mod n -> Mod n -> Mod n
foo n (Mod x) (Mod y) = Mod ((x+y) `mod` n)
which is better, but still allows to call foo 5 x y even when n is not 5. Not good. Instead,
data Mod n = Mod Int -- Int modulo n
-- a lot of type machinery omitted here
foo :: forall n . SomeConstraint n => Mod n -> Mod n -> Mod n
foo (Mod x) (Mod y) = Mod ((x+y) `mod` (value #n))
prevents things to go wrong. The compiler statically checks everything. The code is harder to use, yes, but in a sense making it harder to use is the whole point: we want to make it impossible for the user to try adding something of the wrong modulus.
Concluding: these are very advanced extensions. If you're a beginner, you will need to slowly progress towards these techniques. Don't be discouraged if you can't grasp them after only a short study, it does take some time. Make a small step at a time, solve some exercises for each feature to understand the point of it. And you'll always have StackOverflow when you are stuck :-)
Related
Is there a way in haskell to get all function arguments as a list.
Let's supose we have the following program, where we want to add the two smaller numbers and then subtract the largest. Suppose, we can't change the function definition of foo :: Int -> Int -> Int -> Int. Is there a way to get all function arguments as a list, other than constructing a new list and add all arguments as an element of said list? More importantly, is there a general way of doing this independent of the number of arguments?
Example:
module Foo where
import Data.List
foo :: Int -> Int -> Int -> Int
foo a b c = result!!0 + result!!1 - result!!2 where result = sort ([a, b, c])
is there a general way of doing this independent of the number of arguments?
Not really; at least it's not worth it. First off, this entire idea isn't very useful because lists are homogeneous: all elements must have the same type, so it only works for the rather unusual special case of functions which only take arguments of a single type.
Even then, the problem is that “number of arguments” isn't really a sensible concept in Haskell, because as Willem Van Onsem commented, all functions really only have one argument (further arguments are actually only given to the result of the first application, which has again function type).
That said, at least for a single argument- and final-result type, it is quite easy to pack any number of arguments into a list:
{-# LANGUAGE FlexibleInstances #-}
class UsingList f where
usingList :: ([Int] -> Int) -> f
instance UsingList Int where
usingList f = f []
instance UsingList r => UsingList (Int -> r) where
usingList f a = usingList (f . (a:))
foo :: Int -> Int -> Int -> Int
foo = usingList $ (\[α,β,γ] -> α + β - γ) . sort
It's also possible to make this work for any type of the arguments, using type families or a multi-param type class. What's not so simple though is to write it once and for all with variable type of the final result. The reason being, that would also have to handle a function as the type of final result. But then, that could also be intepreted as “we still need to add one more argument to the list”!
With all respect, I would disagree with #leftaroundabout's answer above. Something being
unusual is not a reason to shun it as unworthy.
It is correct that you would not be able to define a polymorphic variadic list constructor
without type annotations. However, we're not usually dealing with Haskell 98, where type
annotations were never required. With Dependent Haskell just around the corner, some
familiarity with non-trivial type annotations is becoming vital.
So, let's take a shot at this, disregarding worthiness considerations.
One way to define a function that does not seem to admit a single type is to make it a method of a
suitably constructed class. Many a trick involving type classes were devised by cunning
Haskellers, starting at least as early as 15 years ago. Even if we don't understand their
type wizardry in all its depth, we may still try our hand with a similar approach.
Let us first try to obtain a method for summing any number of Integers. That means repeatedly
applying a function like (+), with a uniform type such as a -> a -> a. Here's one way to do
it:
class Eval a where
eval :: Integer -> a
instance (Eval a) => Eval (Integer -> a) where
eval i = \y -> eval (i + y)
instance Eval Integer where
eval i = i
And this is the extract from repl:
λ eval 1 2 3 :: Integer
6
Notice that we can't do without explicit type annotation, because the very idea of our approach is
that an expression eval x1 ... xn may either be a function that waits for yet another argument,
or a final value.
One generalization now is to actually make a list of values. The science tells us that
we may derive any monoid from a list. Indeed, insofar as sum is a monoid, we may turn arguments to
a list, then sum it and obtain the same result as above.
Here's how we can go about turning arguments of our method to a list:
class Eval a where
eval2 :: [Integer] -> Integer -> a
instance (Eval a) => Eval (Integer -> a) where
eval2 is i = \j -> eval2 (i:is) j
instance Eval [Integer] where
eval2 is i = i:is
This is how it would work:
λ eval2 [] 1 2 3 4 5 :: [Integer]
[5,4,3,2,1]
Unfortunately, we have to make eval binary, rather than unary, because it now has to compose two
different things: a (possibly empty) list of values and the next value to put in. Notice how it's
similar to the usual foldr:
λ foldr (:) [] [1,2,3,4,5]
[1,2,3,4,5]
The next generalization we'd like to have is allowing arbitrary types inside the list. It's a bit
tricky, as we have to make Eval a 2-parameter type class:
class Eval a i where
eval2 :: [i] -> i -> a
instance (Eval a i) => Eval (i -> a) i where
eval2 is i = \j -> eval2 (i:is) j
instance Eval [i] i where
eval2 is i = i:is
It works as the previous with Integers, but it can also carry any other type, even a function:
(I'm sorry for the messy example. I had to show a function somehow.)
λ ($ 10) <$> (eval2 [] (+1) (subtract 2) (*3) (^4) :: [Integer -> Integer])
[10000,30,8,11]
So far so good: we can convert any number of arguments into a list. However, it will be hard to
compose this function with the one that would do useful work with the resulting list, because
composition only admits unary functions − with some trickery, binary ones, but in no way the
variadic. Seems like we'll have to define our own way to compose functions. That's how I see it:
class Ap a i r where
apply :: ([i] -> r) -> [i] -> i -> a
apply', ($...) :: ([i] -> r) -> i -> a
($...) = apply'
instance Ap a i r => Ap (i -> a) i r where
apply f xs x = \y -> apply f (x:xs) y
apply' f x = \y -> apply f [x] y
instance Ap r i r where
apply f xs x = f $ x:xs
apply' f x = f [x]
Now we can write our desired function as an application of a list-admitting function to any number
of arguments:
foo' :: (Num r, Ord r, Ap a r r) => r -> a
foo' = (g $...)
where f = (\result -> (result !! 0) + (result !! 1) - (result !! 2))
g = f . sort
You'll still have to type annotate it at every call site, like this:
λ foo' 4 5 10 :: Integer
-1
− But so far, that's the best I can do.
The more I study Haskell, the more I am certain that nothing is impossible.
I have a question that I think is rather tricky.
The standard prelude contains the function
replicate :: Int -> a -> [a]
The following might seem like a reasonable definition for it
replicate n x = take n [x,x,..]
But it is actually not sufficient. Why not?
I know that the replicate function is defined as:
replicate :: Int -> a -> [a]
replicate n x = take n (repeat x)
And repeat is defined as:
repeat :: a -> [a]
repeat x = xs where xs = x:xs
Is the definition insufficient (from the question) because it uses an infinite list?
First of all there is a small syntax error in the question, it should be:
replicate n x = take n [x,x..]
-- ^ no comma
but let's not be picky.
Now when you use range syntax (i.e. x..), then x should be of a type that is an instance of Enum. Indeed:
Prelude> :t \n x -> take n [x,x..]
\n x -> take n [x,x..] :: Enum a => Int -> a -> [a]
You can argue that x,x.. will only generate x, but the Haskell compiler does not know that at compile time.
So the type in replicate (in the question) is too specific: it implies a type constraint - Enum a - that is actually not necessary.
Your own definition on the other hand is perfectly fine. Haskell has no problem with infinite lists since it uses lazy evaluation. Furthermore because you define xs with xs as tail, you actually constructed a circular linked list which also is better in terms of memory usage.
Which difference in does it make if I define a function with a lambda expression or without so when compiling the module with GHC
f :: A -> B
f = \x -> ...
vs.
f :: A -> B
f x = ...
I think I saw that it helps the compiler to inline the function but other than that can it have an impact on my code if I change from the first to the second version.
I am trying to understand someone else's code and get behind the reasoning why this function is defined in the first and not the second way.
To answer that question, I wrote a little program with both ways, and looked at the Core generated:
f1 :: Int -> Int
f1 = \x -> x + 2
{-# NOINLINE f1 #-}
f2 :: Int -> Int
f2 x = x + 2
{-# NOINLINE f2 #-}
I get the core by running ghc test.hs -ddump-simpl. The relevant part is:
f1_rjG :: Int -> Int
[GblId, Arity=1, Str=DmdType]
f1_rjG =
\ (x_alH :: Int) -> + # Int GHC.Num.$fNumInt x_alH (GHC.Types.I# 2)
f2_rlx :: Int -> Int
[GblId, Arity=1, Str=DmdType]
f2_rlx =
\ (x_amG :: Int) -> + # Int GHC.Num.$fNumInt x_amG (GHC.Types.I# 2)
The results are identical, so to answer your question: there is no impact from changing from one form to the other.
That being said, I recommend looking at leftaroundabout's answer, which deals about the cases where there actually is a difference.
First off, the second form is just more flexible (it allows you to do pattern matching, with other clauses below for alternative cases).
When there's only one clause, it's actually equivalent to a lambda... unless you have a where scope. Namely,
f = \x -> someCalculation x y
where y = expensiveConstCalculation
is more efficient than
f x = someCalculation x y
where y = expensiveConstCalculation
because in the latter, y is always recalculated when you evaluate f with a different argument. In the lambda form, y is re-used:
If the signature of f is monomorphic, then f is a constant applicative form, i.e. global constant. That means y is shared throughout your entire program, and only someCalculation needs to be re-done for each call of f. This is typically ideal performance-wise, though of course it also means that y keeps occupying memory.
If f s polymorphic, then it is in fact implicitly a function of the types you're using it with. That means you don't get global sharing, but if you write e.g. map f longList, then still y needs to be computed only once before getting mapped over the list.
That's the gist of the performance differences. Now, of course GHC can rearrange stuff and since it's guaranteed that the results are the same, it might always transform one form to the other if deemed more efficient. But normally it doesn't.
Lately I've been experimenting with the general question, what will GHC allow me to do? I was surprised to find, that it considers the following program as valid
module BrokenRecursiveType where
data FooType = Foo FooType
main = print "it compiles!"
At first I thought, how is this useful? Then I remembered that Haskell is lazy, so I could, perhaps, define a function like the following to use it
allTheFoos = Foo allTheFoos
Then I thought, so how is this useful?
Are there any valuable use cases (thought up or actually experienced) for types of similar form to FooType?
An evaluation counter
You could, hypothetically, use FooType to optionally abort a recursive function early: For example, take this code:
foo _ 0 = 1
foo (Foo x) n = n * foo x (n-1)
If you call foo allTheFoos, then you get the plain factorial function. But you can pass a different value of type FooType, e.g.
atMostFiveSteps = Foo (Foo (Foo (Foo (Foo (error "out of steps")))))
and then foo atMostFiveSteps will only work for values smaller than 6.
I’m neither saying that this is particularly useful nor that this is the best way to implement such a feature...
A void type
BTW, there is a similar construction, namely
newtype FooType' = Foo' FooType'
which is useful: It is one way to define the void type that has no values besides ⊥. You can still define
allTheFoos' = Foo' allTheFoos'
as before, but because operationally, Foo does nothing, this is equivalent to x = x and hence also ⊥.
Let's just slightly extend your data type - let's wrap the recursion into a type parameters:
data FooType f = Foo (f (FooType f))
(so your original data type would be FooType Identity).
Now we can modulate the recursive reference by any f :: * -> *. But this extended type is extremely useful! In fact, it can be used to express any recursive data type using a non-recursive one. One well kwnown package where it's defined is recursion-schemes, as Fix:
newtype Fix f = Fix (f (Fix f))
For example, if we define
data List' a r = Cons' a r | Nil'
then Fix (List' a) is isomorphic to [a]:
nil :: Fix (List' a)
nil = Fix Nil'
cons :: a -> Fix (List' a) -> Fix (List' a)
cons x xs = Fix (Cons' x xs)
Moreover, Fix allows us to define many generic operations on recursive data types such as folding/unfolding (catamorphisms/anamorphisms).
An extension of your FooType could be an abstract syntax tree. Taking a simple example language only having integers, sums and inverses, the type definition would be
data Exp = AnInt Integer
| AnInverse Exp
| ASum Exp Exp
All the following would be Exp instances:
AnInt 2 -- 2
AnInverse ( AnInt 2 ) -- 1 / 2
AnInverse ( ASum ( AnInt 2 ) ( AnInt 3 ) ) -- 1 / ( 2 + 3 )
AnInverse ( ASum 1 ( AnInverse 2 ) ) -- 1 / ( 1 + 1 / 2 )
If we removed AnInt and ASum from the Exp definition, the type would be isomorphic to your FooType (with AnInverse replacing Foo).
data FooType = Foo FooType
allTheFoos = Foo allTheFoos
I think there are two useful ways to look at this type.
First is the "moral" way—the common approach where we pretend that Haskell types don't have "bottom" (non-terminating) values. From this perspective, FooType is a unit type—a type that has only one value, just like (). This is because if you forbid bottoms, then the only value of type Foo is your allTheFoos.
From the "immoral" perspective (where bottoms are allowed), FooType is either an infinite tower of Foo constructors, or a finite tower of Foo constructors with a bottom at the bottom. This is similar to the "moral" interpretation of this type:
data Nat = Zero | Succ Nat
...but with bottom instead of zero, which means that you can't write functions like this one:
plus :: Nat -> Nat -> Nat
plus Zero y = y
plus (Succ x) y = Succ (x `plus` y)
Where does that leave us? I think the conclusion is that FooType isn't really an useful type, because:
If you look at it "morally" it's equivalent to ().
If you look at it "immorally" it's similar to Nat but any functions that tries to match a "zero" is non-terminating.
The following type:
newtype H a b = Fn {invoke :: H b a -> b}
while not exactly the same as yours but is in a similar spirit, have been shown by Launchbury, Krstic, and Sauerwein to have interesting uses regarding corouitining: https://arxiv.org/pdf/1309.5135.pdf
Many introductory texts will tell you that in Haskell type signatures are "almost always" optional. Can anybody quantify the "almost" part?
As far as I can tell, the only time you need an explicit signature is to disambiguate type classes. (The canonical example being read . show.) Are there other cases I haven't thought of, or is this it?
(I'm aware that if you go beyond Haskell 2010 there are plenty for exceptions. For example, GHC will never infer rank-N types. But rank-N types are a language extension, not part of the official standard [yet].)
Polymorphic recursion needs type annotations, in general.
f :: (a -> a) -> (a -> b) -> Int -> a -> b
f f1 g n x =
if n == (0 :: Int)
then g x
else f f1 (\z h -> g (h z)) (n-1) x f1
(Credit: Patrick Cousot)
Note how the recursive call looks badly typed (!): it calls itself with five arguments, despite f having only four! Then remember that b can be instantiated with c -> d, which causes an extra argument to appear.
The above contrived example computes
f f1 g n x = g (f1 (f1 (f1 ... (f1 x))))
where f1 is applied n times. Of course, there is a much simpler way to write an equivalent program.
Monomorphism restriction
If you have MonomorphismRestriction enabled, then sometimes you will need to add a type signature to get the most general type:
{-# LANGUAGE MonomorphismRestriction #-}
-- myPrint :: Show a => a -> IO ()
myPrint = print
main = do
myPrint ()
myPrint "hello"
This will fail because myPrint is monomorphic. You would need to uncomment the type signature to make it work, or disable MonomorphismRestriction.
Phantom constraints
When you put a polymorphic value with a constraint into a tuple, the tuple itself becomes polymorphic and has the same constraint:
myValue :: Read a => a
myValue = read "0"
myTuple :: Read a => (a, String)
myTuple = (myValue, "hello")
We know that the constraint affects the first part of the tuple but does not affect the second part. The type system doesn't know that, unfortunately, and will complain if you try to do this:
myString = snd myTuple
Even though intuitively one would expect myString to be just a String, the type checker needs to specialize the type variable a and figure out whether the constraint is actually satisfied. In order to make this expression work, one would need to annotate the type of either snd or myTuple:
myString = snd (myTuple :: ((), String))
In Haskell, as I'm sure you know, types are inferred. In other words, the compiler works out what type you want.
However, in Haskell, there are also polymorphic typeclasses, with functions that act in different ways depending on the return type. Here's an example of the Monad class, though I haven't defined everything:
class Monad m where
return :: a -> m a
(>>=) :: m a -> (a -> m b) -> m b
fail :: String -> m a
We're given a lot of functions with just type signatures. Our job is to make instance declarations for different types that can be treated as Monads, like Maybe t or [t].
Have a look at this code - it won't work in the way we might expect:
return 7
That's a function from the Monad class, but because there's more than one Monad, we have to specify what return value/type we want, or it automatically becomes an IO Monad. So:
return 7 :: Maybe Int
-- Will return...
Just 7
return 6 :: [Int]
-- Will return...
[6]
This is because [t] and Maybe have both been defined in the Monad type class.
Here's another example, this time from the random typeclass. This code throws an error:
random (mkStdGen 100)
Because random returns something in the Random class, we'll have to define what type we want to return, with a StdGen object tupelo with whatever value we want:
random (mkStdGen 100) :: (Int, StdGen)
-- Returns...
(-3650871090684229393,693699796 2103410263)
random (mkStdGen 100) :: (Bool, StdGen)
-- Returns...
(True,4041414 40692)
This can all be found at learn you a Haskell online, though you'll have to do some long reading. This, I'm pretty much 100% certain, it the only time when types are necessary.