Related
It seems like there are a lot of functions that do the same thing, particularly relating to Monads, Functors, and Applicatives.
Examples (from most to least generic):
fmap == liftA == liftM
(<*>) == ap
liftA[2345] == liftM[2345]
pure == return
(*>) == (>>)
An example not directly based on the FAM class tree:
fmap == map
(I thought there were quite a few more with List, Foldable, Traversable, but it looks like most were made more generic some time ago, as I only see the old, less generic type signatures in old stack overflow / message board questions)
I personally find this annoying, as it means that if I need to do x, and some function such as liftM allows me to do x, then I will have made my function less generic than it could have been, and I am only going to notice that kind of thing by thoroughly reasoning about the differences between types (such as FAM, or perhaps List, Foldable, Traversable combinations as well), which is not beginner friendly at all, as while simply using those types isn't all that hard, reasoning about their properties and laws requires a lot more mental effort.
I am guessing a lot of these equivalencies come from the Applicative Monad Proposal. If that is the reason for them (and not some other reason I am missing for having less generic functions available for confusion), are they going to be deprecated / deleted ever? I can understand waiting a long time to delete them, due to breaking existing code, but surely deprecation is a good idea?
The short answers are "history" and "regularity".
Originally "map" was defined for lists. Then type-classes were introduced, with the Functor type class, so the generalised version of "map" for any functor had to be called something different, otherwise existing code would be broken. Hence "fmap".
Then monads came along. Instances of monads did not need to be functors, so "liftM" was created, along with "liftM2", "liftM3" etc. Of course if a type is an instance of both Monad and Functor then fmap = liftM.
Monads also have "ap", used in expressions like f `ap` arg1 `ap` arg2. This was very handy, but then Applicative Functors were added. (<*>) did the same job for applicative functors as 'ap', but because many applicative functors are not monads it had to be called something different. Likewise liftAx versus liftMx and "pure" versus "return".
They aren't equivalent though. equivalent things in haskell can be interchanged with no difference at all in functionality. Consider for example pure and return
EDIT: I wrote some examples down, but they were really bad since they involved Maybe a, a type that is both an applicative and a monad, so the functions could be used pretty interchangeably.
There are types that are applicatives but not monads though (see this question for examples), and by studying the type of the following expression, we can see that this could lead to some roadbumps:
pure 1 >>= pure :: (Monad m, Num b) => m b
I personally find this annoying, as it means that if I need to do x, and some function such as liftM allows me to do x, then I will have made my function less generic than it could have been
This logic is backwards.
Normally you know in advance the type of the thing you want to write, be it IO String or (Foldable f, Monoid t, Monad m) => f (m t) -> m t or whatever. Let's take the first case, getLineCapitalized :: IO String. You could write it as
getLineCapitalized = liftM (map toUpper) getLine
or
getLineCapitalized = fmap (fmap toUpper) getLine
Is the former "less generic" because it uses the specialized functions liftM and map? Of course not. This is intrinsically an IO action that produces a list. It cannot become "more generic" by changing it to the second version since those fmaps will have their types fixed to IO and [] anyways. So, there is no advantage to the second version.
By writing the first version, you provide contextual information to the reader for free. In liftM (map foo) bar, the reader knows that bar is going to be an action in some monad that returns a list. In fmap (fmap foo) bar, it could be any sort of doubly-nested structure whatsoever. If bar is something complicated rather than just getLine, then this kind of information is helpful for understanding more easily what is going on in bar.
In general, you should write a function in two steps.
Decide what the type of the function should be. Make it as general or as specific as you want. The more general the type of the function, the stronger guarantees you get on its behavior from parametricity.
Once you have decided on the type of your function, implement it using the most specific available functions. By doing so, you are providing the most information to the reader of your function. You never lose any generality or parametricity guarantees by doing so, since those only depend on the type, which you already determined in step 1.
Edit in response to comments: I was reminded of the biggest reason to use the most specific function available, which is catching bugs. The type length :: [a] -> Int is essentially the entire reason that I still use GHC 7.8. It's never happened that I wanted to take the length of an unknown Foldable structure. On the other hand, I definitely do not want to ever accidentally take the length of a pair, or take the length of foo bar baz which I think has type [a], but actually has type Maybe [a].
In the use cases for Foldable that are not already covered by the rest of the Haskell standard, lens is a vastly more powerful alternative. If I want the "length" of a Maybe t, lengthOf _Just :: Maybe t -> Int expresses my intent clearly, and the compiler can check that the program actually matches my intent; and I can go on to write lengthOf _Nothing, lengthOf _Left, etc. Explicit is better than implicit.
There are some "redundant" functions like liftM, ap, and liftA that have a very real use and taking them out would cause loss of functionality --- you can use liftM, ap, and liftA to implement your Functor or Applicative instances if all you've written is a Monad instance. It lets you be lazy and do, say:
instance Monad Foo where
return = ...
(>>=) = ...
Now you've done all of the rewarding work of defining a Monad instance, but this won't compile. Why? Because you also need a Functor and Applicative instance.
So, because you're quickly prototyping, or lazy, or can't think of a better way, you can just get a free Functor and Applicative instance:
instance Functor Foo where
fmap = liftM
instance Applicative Foo where
pure = return
(<*>) = ap
In fact, you can just copy-and-paste that chunk of code everywhere you need to quickly define a Functor or Applicative instance when you already have a Monad instance defined.
The same goes for fmapDefault from Data.Traversable. If you've implemented Traversable, you can also implement Foldable and Functor:
instance Functor Bar where
fmap = fmapDefault
no extra work required!
There are some redundant functions, however, that really have no actual usage other than being historical accidents from a time when Functor was not a superclass of Monad. These have literally zero use/point in existing...and include things like the liftM2, liftM3 etc., and (>>) and friends.
Why do we need Control.Lens.Reified? Is there some reason I can't place a Lens directly into a container? What does reify mean anyway?
We need reified lenses because Haskell's type system is predicative. I don't know the technical details of exactly what that means, but it prohibits types like
[Lens s t a b]
For some purposes, it's acceptable to use
Functor f => [(a -> f b) -> s -> f t]
instead, but when you reach into that, you don't get a Lens; you get a LensLike specialized to some functor or another. The ReifiedBlah newtypes let you hang on to the full polymorphism.
Operationally, [ReifiedLens s t a b] is a list of functions each of which takes a Functor f dictionary, while forall f . Functor f => [LensLike f s t a b] is a function that takes a Functor f dictionary and returns a list.
As for what "reify" means, well, the dictionary will say something, and that seems to translate into a rather stunning variety of specific meanings in Haskell. So no comment on that.
The problem is that, in Haskell, type abstraction and application are completely implicit; the compiler is supposed to insert them where needed. Various attempts at designing 'impredicative' extensions, where the compiler would make clever guesses where to put them, have failed; so the safest thing ends up being relying on the Haskell 98 rules:
Type abstractions occur only at the top level of a function definition.
Type applications occur immediately whenever a variable with a polymorphic type is used in an expression.
So if I define a simple lens:[1]
lensHead f [] = pure []
lensHead f (x:xn) = (:xn) <$> f x
and use it in an expression:
[lensHead]
lensHead gets automatically applied to some set of type parameters; at which point it's no longer a lens, because it's not polymorphic in the functor anymore. The take-away is: an expression always has some monomorphic type; so it's not a lens. (You'll note that the lens functions take arguments of type Getter and Setter, which are monomorphic types, for similar reasons to this. But a [Getter s a] isn't a list of lenses, because they've been specialized to only getters.)
What does reify mean? The dictionary definition is 'make real'. 'Reifying' is used in philosophy to refer to the act of regarding or treating something as real (rather than ideal or abstract). In programming, it tends to refer to taking something that normally can't be treated as a data structure and representing it as one. For example, in really old Lisps, there didn't use to be first-class functions; instead, you had to use S-Expressions to pass 'functions' around, and eval them when you needed to call the function. The S-Expressions represented the functions in a way you could manipulate in the program, which is referred to as reification.
In Haskell, we don't typically need such elaborate reification strategies as Lisp S-Expressions, partly because the language is designed to avoid needing them; but since
newtype ReifiedLens s t a b = ReifiedLens (Lens s t a b)
has the same effect of taking a polymorphic value and turning it into a true first-class value, it's referred to as reification.
Why does this work, if expressions always have monomorphic types? Well, because the Rank2Types extension adds a third rule:
Type abstractions occur at the top-level of the arguments to certain functions, with so-called rank 2 types.
ReifiedLens is such a rank-2 function; so when you say
ReifiedLens l
you get a type lambda around the argument to ReifiedLens, and then l is applied immediately to the the lambda-bound type argument. So l is effectively just eta-expanded. (Compilers are free to eta-reduce this and just use l directly).
Then, when you say
f (ReifiedLens l) = ...
on the right-hand side, l is a variable with polymorphic type, so every use of l is immediately implicitly assigned to whatever type arguments are needed for the expression to type-check. So everything works the way you expect.
The other way to think about is that, if you say
newtype ReifiedLens s t a b = ReifiedLens { unReify :: Lens s t a b }
the two functions ReifiedLens and unReify act like explicit type abstraction and application operators; this allows the compiler to identify where you want the abstractions and applications to take place well enough that the issues with impredicative type systems don't come up.
[1] In lens terminology, this is apparently called something other than a 'lens'; my entire knowledge of lenses comes from SPJ's presentation on them so I have no way to verify that. The point remains, since the polymorphism is still necessary to make it work as both a getter and a setter.
I have pretty decent intuition about types Haskell prohibits as "impredicative": namely ones where a forall appears in an argument to a type constructor other than ->. But just what is predicativity? What makes it important? How does it relate to the word "predicate"?
The central question of these type systems is: "Can you substitute a polymorphic type in for a type variable?". Predicative type systems are the no-nonsense schoolmarm answering, "ABSOLUTELY NOT", while impredicative type systems are your carefree buddy who thinks that sounds like a fun idea and what could possibly go wrong?
Now, Haskell muddies the discussion a bit because it believes polymorphism should be useful but invisible. So for the remainder of this post, I will be writing in a dialect of Haskell where uses of forall are not just allowed but required. This way we can distinguish between the type a, which is a monomorphic type which draws its value from a typing environment that we can define later, and the type forall a. a, which is one of the harder polymorphic types to inhabit. We'll also allow forall to go pretty much anywhere in a type -- as we'll see, GHC restricts its type syntax as a "fail-fast" mechanism rather than as a technical requirement.
Suppose we have told the compiler id :: forall a. a -> a. Can we later ask to use id as if it had type (forall b. b) -> (forall b. b)? Impredicative type systems are okay with this, because we can instantiate the quantifier in id's type to forall b. b, and substitute forall b. b for a everywhere in the result. Predicative type systems are a bit more wary of that: only monomorphic types are allowed in. (So if we had a particular b, we could write id :: b -> b.)
There's a similar story about [] :: forall a. [a] and (:) :: forall a. a -> [a] -> [a]. While your carefree buddy may be okay with [] :: [forall b. b] and (:) :: (forall b. b) -> [forall b. b] -> [forall b. b], the predicative schoolmarm isn't, so much. In fact, as you can see from the only two constructors of lists, there is no way to produce lists containing polymorphic values without instantiating the type variable in their constructors to a polymorphic value. So although the type [forall b. b] is allowed in our dialect of Haskell, it isn't really sensible -- there's no (terminating) terms of that type. This motivates GHC's decision to complain if you even think about such a type -- it's the compiler's way of telling you "don't bother".*
Well, what makes the schoolmarm so strict? As usual, the answer is about keeping type-checking and type-inference doable. Type inference for impredicative types is right out. Type checking seems like it might be possible, but it's bloody complicated and nobody wants to maintain that.
On the other hand, some might object that GHC is perfectly happy with some types that appear to require impredicativity:
> :set -Rank2Types
> :t id :: (forall b. b) -> (forall b. b)
{- no complaint, but very chatty -}
It turns out that some slightly-restricted versions of impredicativity are not too bad: specifically, type-checking higher-rank types (which allow type variables to be substituted by polymorphic types when they are only arguments to (->)) is relatively simple. You do lose type inference above rank-2, and principal types above rank-1, but sometimes higher rank types are just what the doctor ordered.
I don't know about the etymology of the word, though.
* You might wonder whether you can do something like this:
data FooTy a where
FooTm :: FooTy (forall a. a)
Then you would get a term (FooTm) whose type had something polymorphic as an argument to something other than (->) (namely, FooTy), you don't have to cross the schoolmarm to do it, and so the belief "applying non-(->) stuff to polymorphic types isn't useful because you can't make them" would be invalidated. GHC doesn't let you write FooTy, and I will admit I'm not sure whether there's a principled reason for the restriction or not.
(Quick update some years later: there is a good, principled reason that FooTm is still not okay. Namely, the way that GADTs are implemented in GHC is via type equalities, so the expanded type of FooTm is actually FooTm :: forall a. (a ~ forall b. b) => FooTy a. Hence to actually use FooTm, one would indeed need to instantiate a type variable with a polymorphic type. Thanks to Stephanie Weirich for pointing this out to me.)
Let me just add a point regarding the "etymology" issue, since the other answer by #DanielWagner covers much of the technical ground.
A predicate on something like a is a -> Bool. Now a predicate logic is one that can in some sense reason about predicates -- so if we have some predicate P and we can talk about, for a given a, P(a), now in a "predicate logic" (such as first-order logic) we can also say ∀a. P(a). So we can quantify over variables and discuss the behavior of predicates over such things.
Now, in turn, we say a statement is predicative if all of the things a predicate is applied to are introduced prior to it. So statements are "predicated on" things that already exist. In turn, a statement is impredicative if it can in some sense refer to itself by its "bootstraps".
So in the case of e.g. the id example above, we find that we can give a type to id such that it takes something of the type of id to something else of the type of id. So now we can give a function a type where an quantified variable (introduced by forall a.) can "expand" to be the same type as that of the entire function itself!
Hence impredicativity introduces a possibility of a certain "self reference". But wait, you might say, wouldn't such a thing lead to contradiction? The answer is: "well, sometimes." In particular, "System F" which is the polymorphic lambda calculus and the essential "core" of GHC's "core" language allows a form of impredicativity that nonetheless has two levels -- the value level, and the type level, which is allowed to quantify over itself. In this two-level stratification, we can have impredicativity and not contradiction/paradox.
Although note that this neat trick is very delicate and easy to screw up by the addition of more features, as this collection of articles by Oleg indicates: http://okmij.org/ftp/Haskell/impredicativity-bites.html
I'd like to make a comment on the etymology issue, since #sclv's answer isn't quite right (etymologically, not conceptually).
Go back in time, to the days of Russell when everything is set theory— including logic. One of the logical notions of particular import is the "principle of comprehension"; that is, given some logical predicate φ:A→2 we would like to have some principle to determine the set of all elements satisfying that predicate, written as "{x | φ(x) }" or some variation thereon. The key point to bear in mind is that "sets" and "predicates" are viewed as being fundamentally different things: predicates are mappings from objects to truth values, and sets are objects. Thus, for example, we may allow quantifying over sets but not quantifying over predicates.
Now, Russell was rather concerned by his eponymous paradox, and sought some way to get rid of it. There are numerous fixes, but the one of interest here is to restrict the principle of comprehension. But first, the formal definition of the principle: ∃S.∀x.S x ↔︎ φ(x); that is, for our particular φ there exists some object (i.e., set) S such that for every object (also a set, but thought of as an element) x, we have that S x (you can think of this as meaning "x∈S", though logicians of the time gave "∈" a different meaning than mere juxtaposition) is true just in case φ(x) is true. If we take the principle exactly as written then we end up with an impredicative theory. However, we can place restrictions on which φ we're allowed to take the comprehension of. (For example, if we say that φ must not contain any second-order quantifiers.) Thus, for any restriction R, if a set S is determined (i.e., generated via comprehension) by some R-predicate, then we say that S is "R-predicative". If every set in our language is R-predicative then we say that our language is "R-predicative". And then, as is often the case with hyphenated prefix things, the prefix gets dropped off and left implicit, whence "predicative" languages. And, naturally, languages which are not predicative are "impredicative".
That's the old school etymology. Since those days the terms have gone off and gotten lives of their own. The ways we use "predicative" and "impredicative" today are quite different, because the things we're concerned about have changed. So it can sometimes be a bit hard to see how the heck our modern usage ties back to this stuff. Honestly, I don't think knowing the etymology really helps any in terms of figuring out what the words are really about (these days).
I've come to heavily rely on haskell's type system to avoid bugs and was looking if it could also be used to ensure a (weak?) form of code correctness.
The form of code correctness I have in mind goes as follows:
A function f :: a -> b is correct if f is guaranteed to produce an output of type b for any input of type a. This clearly fails for the well known function head (head:: [a] -> a).
One way I am aware of that the type system fails to guarantee this form of correctness is when code uses error (error :: Char -> a). The error function pretty much overrides the entire type system so I would like to avoid the use of this function unless explicitly intended.
My question is two-fold:
What other functions (or haskell snippets) besides error are exceptions to Haskell's type system?
More importantly, is there a method to forbid the use of such functions within a Haskell module?
Many thanks!
You can write your own functions that never produce a value. Consider the following function:
never :: a -> b
never a = never a
It fails to terminate, so it is considered to be the value _|_ (pronounced bottom). All types in Haskell are actually the sum of the type and this special value.
You can also write a function that is only partially defined, like
undefinedForFalse :: Bool -> Bool
undefinedForFalse True = True
undefinedForFalse False is undefined, which is a special value that is semantically equivalent to _|_ except that the runtime system can stop execution, because it knows it will never finish.
error is also special function that's result is always semantically equivalent to _|_, it tells the runtime system that it can stop execution, knowing it will never finish, along with an informative error message.
Haskell is incapable of proving that a type can never take the value _|_ because it is always possible for a type to take the value _|_. Values that can never be _|_ are called "total". Functions which always produce a value other than _|_ in a finite period of time are called "total functions". Languages that can prove this are called "total languages" or "total functional programming languages". If they can prove this for all types in the language, they are necessarily Turing incomplete.
It isn't possible to prove that any arbitrary function will produce a value in a Turing complete language. You can for some specific functions though, of course. This was covered well by Cirdec, but I would like to point out a couple things with regard to using the type system to guarantee (some level) of correctness.
The relevant topic is parametricity: the fact that given a polymorphic type signature, there is often only a limited set of possible implementations (if we exclude error, undefined and other things like that).
One example of this would be (a -> b) -> a -> b. There's in fact only one possible implementation of this function.
Another example is that given an f from some type A to some type B and a function r :: [a] -> [a], it can be shown that r . map f = map f . r. This is called the "free theorem" for map. Many other polymorphic types also have free theorems.
A (sometimes more useful) result is that if you can prove that a function mapper :: (a -> b) -> F a -> F b obeys the law mapper id = id, it can be shown that mapper f . mapper g = mapper (f . g). Also, this would be the fmap implementation for the type F since those two laws are the Functor laws. This particular "fusion" law can be useful for optimization purposes.
Source: Theorems for free! http://ttic.uchicago.edu/~dreyer/course/papers/wadler.pdf
What it says in the title. If I write a type signature, is it possible to algorithmically generate an expression which has that type signature?
It seems plausible that it might be possible to do this. We already know that if the type is a special-case of a library function's type signature, Hoogle can find that function algorithmically. On the other hand, many simple problems relating to general expressions are actually unsolvable (e.g., it is impossible to know if two functions do the same thing), so it's hardly implausible that this is one of them.
It's probably bad form to ask several questions all at once, but I'd like to know:
Can it be done?
If so, how?
If not, are there any restricted situations where it becomes possible?
It's quite possible for two distinct expressions to have the same type signature. Can you compute all of them? Or even some of them?
Does anybody have working code which does this stuff for real?
Djinn does this for a restricted subset of Haskell types, corresponding to a first-order logic. It can't manage recursive types or types that require recursion to implement, though; so, for instance, it can't write a term of type (a -> a) -> a (the type of fix), which corresponds to the proposition "if a implies a, then a", which is clearly false; you can use it to prove anything. Indeed, this is why fix gives rise to ⊥.
If you do allow fix, then writing a program to give a term of any type is trivial; the program would simply print fix id for every type.
Djinn is mostly a toy, but it can do some fun things, like deriving the correct Monad instances for Reader and Cont given the types of return and (>>=). You can try it out by installing the djinn package, or using lambdabot, which integrates it as the #djinn command.
Oleg at okmij.org has an implementation of this. There is a short introduction here but the literate Haskell source contains the details and the description of the process. (I'm not sure how this corresponds to Djinn in power, but it is another example.)
There are cases where is no unique function:
fst', snd' :: (a, a) -> a
fst' (a,_) = a
snd' (_,b) = b
Not only this; there are cases where there are an infinite number of functions:
list0, list1, list2 :: [a] -> a
list0 l = l !! 0
list1 l = l !! 1
list2 l = l !! 2
-- etc.
-- Or
mkList0, mkList1, mkList2 :: a -> [a]
mkList0 _ = []
mkList1 a = [a]
mkList2 a = [a,a]
-- etc.
(If you only want total functions, then consider [a] as restricted to infinite lists for list0, list1 etc, i.e. data List a = Cons a (List a))
In fact, if you have recursive types, any types involving these correspond to an infinite number of functions. However, at least in the case above, there is a countable number of functions, so it is possible to create an (infinite) list containing all of them. But, I think the type [a] -> [a] corresponds to an uncountably infinite number of functions (again restrict [a] to infinite lists) so you can't even enumerate them all!
(Summary: there are types that correspond to a finite, countably infinite and uncountably infinite number of functions.)
This is impossible in general (and for languages like Haskell that does not even has the strong normalization property), and only possible in some (very) special cases (and for more restricted languages), such as when a codomain type has the only one constructor (for example, a function f :: forall a. a -> () can be determined uniquely). In order to reduce a set of possible definitions for a given signature to a singleton set with just one definition need to give more restrictions (in the form of additional properties, for example, it is still difficult to imagine how this can be helpful without giving an example of use).
From the (n-)categorical point of view types corresponds to objects, terms corresponds to arrows (constructors also corresponds to arrows), and function definitions corresponds to 2-arrows. The question is analogous to the question of whether one can construct a 2-category with the required properties by specifying only a set of objects. It's impossible since you need either an explicit construction for arrows and 2-arrows (i.e., writing terms and definitions), or deductive system which allows to deduce the necessary structure using a certain set of properties (that still need to be defined explicitly).
There is also an interesting question: given an ADT (i.e., subcategory of Hask) is it possible to automatically derive instances for Typeable, Data (yes, using SYB), Traversable, Foldable, Functor, Pointed, Applicative, Monad, etc (?). In this case, we have the necessary signatures as well as additional properties (for example, the monad laws, although these properties can not be expressed in Haskell, but they can be expressed in a language with dependent types). There is some interesting constructions:
http://ulissesaraujo.wordpress.com/2007/12/19/catamorphisms-in-haskell
which shows what can be done for the list ADT.
The question is actually rather deep and I'm not sure of the answer, if you're asking about the full glory of Haskell types including type families, GADT's, etc.
What you're asking is whether a program can automatically prove that an arbitrary type is inhabited (contains a value) by exhibiting such a value. A principle called the Curry-Howard Correspondence says that types can be interpreted as mathematical propositions, and the type is inhabited if the proposition is constructively provable. So you're asking if there is a program that can prove a certain class of propositions to be theorems. In a language like Agda, the type system is powerful enough to express arbitrary mathematical propositions, and proving arbitrary ones is undecidable by Gödel's incompleteness theorem. On the other hand, if you drop down to (say) pure Hindley-Milner, you get a much weaker and (I think) decidable system. With Haskell 98, I'm not sure, because type classes are supposed to be able to be equivalent to GADT's.
With GADT's, I don't know if it's decidable or not, though maybe some more knowledgeable folks here would know right away. For example it might be possible to encode the halting problem for a given Turing machine as a GADT, so there is a value of that type iff the machine halts. In that case, inhabitability is clearly undecidable. But, maybe such an encoding isn't quite possible, even with type families. I'm not currently fluent enough in this subject for it to be obvious to me either way, though as I said, maybe someone else here knows the answer.
(Update:) Oh a much simpler interpretation of your question occurs to me: you may be asking if every Haskell type is inhabited. The answer is obviously not. Consider the polymorphic type
a -> b
There is no function with that signature (not counting something like unsafeCoerce, which makes the type system inconsistent).