I'm just starting out in F# and I'm wondering how to decipher the following types and what they represent from a book example:
type subs = Map<string,exp> option
type lp = (subs->subs) ->subs->subs // A LP computation
I understand the sub type is simply a map with strings and an associated exp type... but I dont understand the use of '->' and what the lp type is assigning...
Any help on deciphering the lp type would be great
The -> represents a function. For example, string -> int represents a function that takes a string as an argument, and returns an integer.
If you chain the ->, you read it from right to left: a -> b -> c -> d is a -> (b -> (c -> d)).
Functions can take functions as arguments, so, lp is (subs -> subs) -> subs -> subs, which is also written as (subs -> subs) -> (subs -> subs). It is a function that takes a function.
If it is confusing, try to see it as fn -> (subs -> subs), where type fn = subs -> subs, a type for a function.
See also: http://en.wikipedia.org/wiki/Higher-order_function
Related
I'm following this article on catamorphism and I'm trying to define a fold function for a recursive data type like this
type Node anyType
= Leaf Id (Maybe anyType)
| Tree Id (List (Node anyType))
What i wrote is this:
foldTree fLeaf fTree acc node =
let
recurse =
foldTree fLeaf fTree
in
case node of
Leaf id v ->
let
newAcc = fLeaf acc (id, v)
in
newAcc
Tree id l ->
let
newAcc = fTree acc id
in
l |> List.foldl recurse newAcc
If i don't infer the types for foldTree the function compiles, but it seems to not be usable:
collectIds node =
let
fLeaf acc (id,v) = id :: acc
fTree acc id = id :: acc
in
foldTree fLeaf fTree [] node
throws the following:
TYPE MISMATCH - The 1st argument to `foldTree` is not what I expect:
173| foldTree fLeaf fTree [] node
#^^^^^#
This `fLeaf` value is a:
#List a# -> ( a, b ) -> #List a#
But `foldTree` needs the 1st argument to be:
#Node anyType# -> ( Id, Maybe anyType ) -> #Node anyType#
Auto inferring the types for foldTree makes it not compilable and throws the following:
-- Auto Inferred
foldTree : (c -> (Id, Maybe anyType) -> a) -> (c -> Id -> b) -> c -> Node anyType -> d
TYPE MISMATCH - Something is off with the 1st branch of this `case` expression:
126| newAcc
#^^^^^^#
This `newAcc` value is a:
#a#
But the type annotation on `foldTree` says it should be:
#d#
#Hint#: Your type annotation uses `a` and `d` as separate type variables. Your
code seems to be saying they are the same though. Maybe they should be the same
in your type annotation? Maybe your code uses them in a weird way?
and if I try to follow the hint, still does not compile
foldTree : (c -> (Id, Maybe anyType) -> a) -> (c -> Id -> b) -> c -> Node anyType -> a
TYPE MISMATCH - This function cannot handle the argument sent through the (|>) pipe:
134| l |> List.foldl recurse newAcc
#^^^^^^^^^^^^^^^^^^^^^^^^^#
The argument is:
List #(Node anyType)#
But (|>) is piping it to a function that expects:
List #c#
#Hint#: Your type annotation uses type variable `c` which means ANY type of value
can flow through, but your code is saying it specifically wants a `Node` value.
Maybe change your type annotation to be more specific? Maybe change the code to
be more general?
Read <https://elm-lang.org/0.19.1/type-annotations> for more advice!Elm
TYPE MISMATCH - The 1st argument to `foldl` is not what I expect:
134| l |> List.foldl recurse newAcc
#^^^^^^^#
This `recurse` value is a:
c -> Node anyType -> #a#
But `foldl` needs the 1st argument to be:
c -> Node anyType -> #Node anyType#
#Hint#: Your type annotation uses type variable `a` which means ANY type of value
can flow through, but your code is saying it specifically wants a `Node` value.
Maybe change your type annotation to be more specific? Maybe change the code to
be more general?
I'm stuck. Following the types on the article precisely also does not seem to work. I understand that the code on the article is F# and I'm working on Elm but I thought that in this case it would have been 100% translatable.
Where am I going wrong?
Thanks in advance!
You've flipped the arguments to List.foldl. The fold function takes the value first and the accumulator second, while your recurse function takes the accumulator first and the value second.
The simple fix to this is to eta expand the recurse function and flip the arguments when passing it to foldTree:
recurse v a = foldTree fLeaf fTree a v
Also, interestingly, annotating the type of recurse will make it compile, but obviously produces the wrong result. I didn't pursue this further to understand why, as it was wrong, but the lesson you should take from this is to always annotate your top level functions. This will give you better error messages, but also prevents your code from accidentally compiling but producing the wrong result.
I have the following excercise to do:
Code a function that will be a summation of a list of functions.
So I think that means that if a function get list of functions [f(x);g(x);h(x);...] it must return a function that is f(x)+g(x)+h(x)+...
I'm trying to do code that up for the general case and here's something I came up with:
let f_sum (h::t) = fold_left (fun a h -> (fun x -> (h x) + (a x))) h t;;
The problem is I'm using "+" operator and that means it works only when in list we have functions of type
'a -> int
So, can it be done more "generally", I mean can we write a function, that is a sum of ('a -> 'b) functions, given in a list?
yes, you can make plus function to be a parameter of your function, like
let f_sum plus fs =
let (+) = plus in
match fs with
| [] -> invalid_arg "f_sum: empty list"
| f :: fs -> fold_left ...
You can generalize even more, and ask a user to provide a zero value, so that you can return a function, returning zero if the list is empty. Also you can use records to group functions, or even first class modules (cf., Commutative_group.S in Core library).
Long story short, I came up with this funny function set, that takes a function, f : 'k -> 'v, a chosen value, k : 'k, a chosen result, v : 'v, uses f as the basis for a new function g : 'k -> 'v that is the exact same as f, except for that it now holds that, g k = v.
Here is the (pretty simple) F# code I wrote in order to make it:
let set : ('k -> 'v) -> 'k -> 'v -> 'k -> 'v =
fun f k v x ->
if x = k then v else f x
My questions are:
Does this function pose any problems?
I could imagine repeat use of the function, like this
let kvs : (int * int) List = ... // A very long list of random int pairs.
List.fold (fun f (k,v) -> set f k v) id kvs
would start building up a long list of functions on the heap. Is this something to be concerned about?
Is there a better way to do this, while still keeping the type?
I mean, I could do stuff like construct a type for holding the original function, f, a Map, setting key-value pairs to the map, and checking the map first, the function second, when using keys to get values, but that's not what interests me here - what interest me is having a function for "modifying" a single result for a given value, for a given function.
Potential problems:
The set-modified function leaks space if you override the same value twice:
let huge_object = ...
let small_object = ...
let f0 = set f 0 huge_object
let f1 = set f0 0 small_object
Even though it can never be the output of f1, huge_object cannot be garbage-collected until f1 can: huge_object is referenced by f0, which is in turn referenced by the f1.
The set-modified function has overhead linear in the number of set operations applied to it.
I don't know if these are actual problems for your intended application.
If you wish set to have exactly the type ('k -> 'v) -> 'k -> 'v -> 'k -> 'v then I don't see a better way(*). The obvious idea would be to have a "modification table" of functions you've already modified, then let set look up a given f in this table. But function types do not admit equality checking, so you cannot compare f to the set of functions known to your modification table.
(*) Reflection not withstanding.
I started learning functional programming (OCaml), but I don't understand one important topic about fp: signatures (I'm not sure if it's a proper name). When I type something and compile with ocaml, I get for example:
# let inc x = x + 1 ;;
val inc : int -> int = <fun>
This is trivial, but I don't know, why this:
let something f g a b = f a (g a b)
gives an output:
val something : (’a -> ’b -> ’c) -> (’a -> ’d -> ’b) -> ’a -> ’d -> ’c = <fun>
I suppose, that this topic is absolutely basics of fp for many of you, but I ask for help here, because I haven't found anything on the Internet about signatures in OCaml (there are some articles about signatures in Haskell, but not explanations).
If this topic somehow will survive, I post here several functions, which signatures made me confused:
# let nie f a b = f b a ;; (* flip *)
val nie : (’a -> ’b -> ’c) -> ’b -> ’a -> ’c = <fun>
# let i f g a b = f (g a b) b ;;
val i : (’a -> ’b -> ’c) -> (’d -> ’b -> ’a) -> ’d -> ’b -> ’c = <fun>
# let s x y z = x z (y z) ;;
val s : (’a -> ’b -> ’c) -> (’a -> ’b) -> ’a -> ’c = <fun>
# let callCC f k = f (fun c d -> k c) k ;;
val callCC : ((’a -> ’b -> ’c) -> (’a -> ’c) -> ’d) -> (’a -> ’c) -> ’d = <fun>
Thank you for help and explanation.
There are a couple of concepts you need to understand to make sense of this type signature and I don't know which ones you already do, so I tried my best to explain every important concept:
Currying
As you know, if you have the type foo -> bar, this describes a function taking an argument of type foo and returning a result of type bar. Since -> is right associative, the type foo -> bar -> baz is the same as foo -> (bar -> baz) and thus describes a function taking an argument of type foo and returning a value of type bar -> baz, which means the return value is a function taking a value of type bar and returning a value of type baz.
Such a function can be called like my_function my_foo my_bar, which because function application is left-associative, is the same as (my_function my_foo) my_bar, i.e. it applies my_function to the argument my_foo and then applies the function that is returned as a result to the argument my_bar.
Because it can be called like this, a function of type foo -> bar -> baz is often called "a function taking two arguments" and I will do so in the rest of this answer.
Type variables
If you define a function like let f x = x, it will have the type 'a -> 'a. But 'a isn't actually a type defined anywhere in the OCaml standard library, so what is it?
Any type that starts with a ' is a so-called type variable. A type variable can stand for any possible type. So in the example above f can be called with an int or a string or a list or anything at all - it doesn't matter.
Furthermore if the same type variable appears in a type signature more than once, it will stand for the same type. So in the example above that means, that the return type of f is the same as the argument type. So if f is called with an int, it returns an int. If it is called with a string, it returns a string and so on.
So a function of type 'a -> 'b -> 'a could take two arguments of any types (which might not be the same type for the first and second argument) and returns a value of the same type as the first argument, while a function of type 'a -> 'a -> 'a would take two arguments of the same type.
One note about type inference: Unless you explicitly give a function a type signature, OCaml will always infer the most general type possible for you. So unless a function uses any operations that only work with a given type (like + for example), the inferred type will contain type variables.
Now to explain the type...
val something : ('a -> 'b -> 'c) -> ('a -> 'd -> 'b) -> 'a -> 'd -> 'c = <fun>
This type signature tells you that something is a function taking four arguments.
The type of the first argument is 'a -> 'b -> 'c. I.e. a function taking two arguments of arbitrary and possibly different types and returning a value of an arbitrary type.
The type of the second argument is 'a -> 'd -> 'b. This is again a function with two arguments. The important thing to note here is that the first argument of the function must have the same type as the first argument of the first function and the return value of the function must have the same type as the second argument of the first function.
The type of the third argument is 'a, which is also the type of the first arguments of both functions.
Lastly, the type of the fourth argument is 'd, which is the type of the second argument of the second function.
The return value will be of type 'c, i.e. the return type of the first function.
If you're really interested in the subject (and have access to a university library), read Wadler's excellent (if somewhat dated) "Introduction to functional programming". It explains type signatures and type inference in a very nice and readable way.
Two further hints: Note that the -> arrow is right-associative, so you can bracket things from the right which sometimes helps to understand things, ie a -> b -> c is the same as a -> (b -> c). This is connected to the second hint: Higher order functions. You can do things like
let add x y = x + y
let inc = add 1
so in FP, thinking of 'add' as a function that has to take two numerical parameters and returns a numerical value is not generally the right thing to do: It can also be a function that takes one numerical argument and returns a function with type num -> num.
Understanding this will help you understand type signatures, but you can do it without. Here, quick and easy:
# let s x y z = x z (y z) ;;
val s : (’a -> ’b -> ’c) -> (’a -> ’b) -> ’a -> ’c = <fun>
Look at the right hand side. y is given one argument, so it is of type a -> b where a is the type of z. x is given two arguments, the first one of which is z, so the type of the first argument has to be a as well. The type of (y z) , the second argument, is b, and hence the type of x is (a -> b -> c). This allows you to deduce the type of s immediately.
This isn't a homework question, by the way. It got brought up in class but my teacher couldn't think of any. Thanks.
How do you define the identity functions ? If you're only considering the syntax, there are different identity functions, which all have the correct type:
let f x = x
let f2 x = (fun y -> y) x
let f3 x = (fun y -> y) (fun y -> y) x
let f4 x = (fun y -> (fun y -> y) y) x
let f5 x = (fun y z -> z) x x
let f6 x = if false then x else x
There are even weirder functions:
let f7 x = if Random.bool() then x else x
let f8 x = if Sys.argv < 5 then x else x
If you restrict yourself to a pure subset of OCaml (which rules out f7 and f8), all the functions you can build verify an observational equation that ensures, in a sense, that what they compute is the identity : for all value f : 'a -> 'a, we have that f x = x
This equation does not depend on the specific function, it is uniquely determined by the type. There are several theorems (framed in different contexts) that formalize the informal idea that "a polymorphic function can't change a parameter of polymorphic type, only pass it around". See for example the paper of Philip Wadler, Theorems for free!.
The nice thing with those theorems is that they don't only apply to the 'a -> 'a case, which is not so interesting. You can get a theorem out of the ('a -> 'a -> bool) -> 'a list -> 'a list type of a sorting function, which says that its application commutes with the mapping of a monotonous function.
More formally, if you have any function s with such a type, then for all types u, v, functions cmp_u : u -> u -> bool, cmp_v : v -> v -> bool, f : u -> v, and list li : u list, and if cmp_u u u' implies cmp_v (f u) (f u') (f is monotonous), you have :
map f (s cmp_u li) = s cmp_v (map f li)
This is indeed true when s is exactly a sorting function, but I find it impressive to be able to prove that it is true of any function s with the same type.
Once you allow non-termination, either by diverging (looping indefinitely, as with the let rec f x = f x function given above), or by raising exceptions, of course you can have anything : you can build a function of type 'a -> 'b, and types don't mean anything anymore. Using Obj.magic : 'a -> 'b has the same effect.
There are saner ways to lose the equivalence to identity : you could work inside a non-empty environment, with predefined values accessible from the function. Consider for example the following function :
let counter = ref 0
let f x = incr counter; x
You still that the property that for all x, f x = x : if you only consider the return value, your function still behaves as the identity. But once you consider side-effects, you're not equivalent to the (side-effect-free) identity anymore : if I know counter, I can write a separating function that returns true when given this function f, and would return false for pure identity functions.
let separate g =
let before = !counter in
g ();
!counter = before + 1
If counter is hidden (for example by a module signature, or simply let f = let counter = ... in fun x -> ...), and no other function can observe it, then we again can't distinguish f and the pure identity functions. So the story is much more subtle in presence of local state.
let rec f x = f (f x)
This function never terminates, but it does have type 'a -> 'a.
If we only allow total functions, the question becomes more interesting. Without using evil tricks, it's not possible to write a total function of type 'a -> 'a, but evil tricks are fun so:
let f (x:'a):'a = Obj.magic 42
Obj.magic is an evil abomination of type 'a -> 'b which allows all kinds of shenanigans to circumvent the type system.
On second thought that one isn't total either because it will crash when used with boxed types.
So the real answer is: the identity function is the only total function of type 'a -> 'a.
Throwing an exception can also give you an 'a -> 'a type:
# let f (x:'a) : 'a = raise (Failure "aaa");;
val f : 'a -> 'a = <fun>
If you restrict yourself to a "reasonable" strongly normalizing typed λ-calculus, there is a single function of type ∀α α→α, which is the identity function. You can prove it by examining the possible normal forms of a term of this type.
Philip Wadler's 1989 article "Theorems for Free" explains how functions having polymorphic types necessarily satisfy certain theorems (e.g. a map-like function commutes with composition).
There are however some nonintuitive issues when one deals with much polymorphism. For instance, there is a standard trick for encoding inductive types and recursion with impredicative polymorphism, by representing an inductive object (e.g. a list) using its recursor function. In some cases, there are terms belonging to the type of the recursor function that are not recursor functions; there is an example in §4.3.1 of Christine Paulin's PhD thesis.