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In Functional Programming, what is a functor?

The word "functor" comes from category theory, which is a very general, very abstract branch of mathematics. It has been borrowed by designers of functional languages in at least two different ways.

  • In the ML family of languages, a functor is a module that takes one or more other modules as a parameter. It's considered an advanced feature, and most beginning programmers have difficulty with it.

    As an example of implementation and practical use, you could define your favorite form of balanced binary search tree once and for all as a functor, and it would take as a parameter a module that provides:

    • The type of key to be used in the binary tree

    • A total-ordering function on keys

    Once you've done this, you can use the same balanced binary tree implementation forever. (The type of value stored in the tree is usually left polymorphic—the tree doesn't need to look at values other than to copy them around, whereas the tree definitely needs to be able to compare keys, and it gets the comparison function from the functor's parameter.)

    Another application of ML functors is layered network protocols. The link is to a really terrific paper by the CMU Fox group; it shows how to use functors to build more complex protocol layers (like TCP) on type of simpler layers (like IP or even directly over Ethernet). Each layer is implemented as a functor that takes as a parameter the layer below it. The structure of the software actually reflects the way people think about the problem, as opposed to the layers existing only in the mind of the programmer. In 1994 when this work was published, it was a big deal.

    For a wild example of ML functors in action, you could see the paper ML Module Mania, which contains a publishable (i.e., scary) example of functors at work. For a brilliant, clear, pellucid explanation of the ML modules system (with comparisons to other kinds of modules), read the first few pages of Xavier Leroy's brilliant 1994 POPL paper Manifest Types, Modules, and Separate Compilation.

  • In Haskell, and in some related pure functional language, Functor is a type class. A type belongs to a type class (or more technically, the type "is an instance of" the type class) when the type provides certain operations with certain expected behavior. A type T can belong to class Functor if it has certain collection-like behavior:

    • The type T is parameterized over another type, which you should think of as the element type of the collection. The type of the full collection is then something like T Int, T String, T Bool, if you are containing integers, strings, or Booleans respectively. If the element type is unknown, it is written as a type parameter a, as in T a.

      Examples include lists (zero or more elements of type a), the Maybe type (zero or one elements of type a), sets of elements of type a, arrays of elements of type a, all kinds of search trees containing values of type a, and lots of others you can think of.

    • The other property that T has to satisfy is that if you have a function of type a -> b (a function on elements), then you have to be able to take that function and product a related function on collections. You do this with the operator fmap, which is shared by every type in the Functor type class. The operator is actually overloaded, so if you have a function even with type Int -> Bool, then

      fmap even
      

      is an overloaded function that can do many wonderful things:

      • Convert a list of integers to a list of Booleans

      • Convert a tree of integers to a tree of Booleans

      • Convert Nothing to Nothing and Just 7 to Just False

      In Haskell, this property is expressed by giving the type of fmap:

      fmap :: (Functor t) => (a -> b) -> t a -> t b
      

      where we now have a small t, which means "any type in the Functor class."

    To make a long story short, in Haskell a functor is a kind of collection for which if you are given a function on elements, fmap will give you back a function on collections. As you can imagine, this is an idea that can be widely reused, which is why it is blessed as part of Haskell's standard library.

As usual, people continue to invent new, useful abstractions, and you may want to look into applicative functors, for which the best reference may be a paper called Applicative Programming with Effects by Conor McBride and Ross Paterson.


Other answers here are complete, but I'll try another explanation of the FP use of functor. Take this as analogy:

A functor is a container of type a that, when subjected to a function that maps from ab, yields a container of type b.

Unlike the abstracted-function-pointer use in C++, here the functor is not the function; rather, it's something that behaves consistently when subjected to a function.


There are three different meanings, not much related!

  • In Ocaml it is a parametrized module. See manual. I think the best way to grok them is by example: (written quickly, might be buggy)

    module type Order = sig
        type t
        val compare: t -> t -> bool
    end;;
    
    
    module Integers = struct
        type t = int
        let compare x y = x > y
    end;;
    
    module ReverseOrder = functor (X: Order) -> struct
        type t = X.t
        let compare x y = X.compare y x
    end;;
    
    (* We can order reversely *)
    module K = ReverseOrder (Integers);;
    Integers.compare 3 4;;   (* this is false *)
    K.compare 3 4;;          (* this is true *)
    
    module LexicographicOrder = functor (X: Order) -> 
      functor (Y: Order) -> struct
        type t = X.t * Y.t
        let compare (a,b) (c,d) = if X.compare a c then true
                             else if X.compare c a then false
                             else Y.compare b d
    end;;
    
    (* compare lexicographically *)
    module X = LexicographicOrder (Integers) (Integers);;
    X.compare (2,3) (4,5);;
    
    module LinearSearch = functor (X: Order) -> struct
        type t = X.t array
        let find x k = 0 (* some boring code *)
    end;;
    
    module BinarySearch = functor (X: Order) -> struct
        type t = X.t array
        let find x k = 0 (* some boring code *)
    end;;
    
    (* linear search over arrays of integers *)
    module LS = LinearSearch (Integers);;
    LS.find [|1;2;3] 2;;
    (* binary search over arrays of pairs of integers, 
       sorted lexicographically *)
    module BS = BinarySearch (LexicographicOrder (Integers) (Integers));;
    BS.find [|(2,3);(4,5)|] (2,3);;
    

You can now add quickly many possible orders, ways to form new orders, do a binary or linear search easily over them. Generic programming FTW.

  • In functional programming languages like Haskell, it means some type constructors (parametrized types like lists, sets) that can be "mapped". To be precise, a functor f is equipped with (a -> b) -> (f a -> f b). This has origins in category theory. The Wikipedia article you linked to is this usage.

    class Functor f where
        fmap :: (a -> b) -> (f a -> f b)
    
    instance Functor [] where      -- lists are a functor
        fmap = map
    
    instance Functor Maybe where   -- Maybe is option in Haskell
        fmap f (Just x) = Just (f x)
        fmap f Nothing = Nothing
    
    fmap (+1) [2,3,4]   -- this is [3,4,5]
    fmap (+1) (Just 5)  -- this is Just 6
    fmap (+1) Nothing   -- this is Nothing
    

So, this is a special kind of a type constructors, and has little to do with functors in Ocaml!

  • In imperative languages, it is a pointer to function.

In OCaml, it's a parameterised module.

If you know C++, think of an OCaml functor as a template. C++ only has class templates, and functors work at the module scale.

An example of functor is Map.Make; module StringMap = Map.Make (String);; builds a map module that works with String-keyed maps.

You couldn't achieve something like StringMap with just polymorphism; you need to make some assumptions on the keys. The String module contains the operations (comparison, etc) on a totally ordered string type, and the functor will link against the operations the String module contains. You could do something similar with object-oriented programming, but you'd have method indirection overhead.


You got quite a few good answers. I'll pitch in:

A functor, in the mathematical sense, is a special kind of function on an algebra. It is a minimal function which maps an algebra to another algebra. "Minimality" is expressed by the functor laws.

There are two ways to look at this. For example, lists are functors over some type. That is, given an algebra over a type 'a', you can generate a compatible algebra of lists containing things of type 'a'. (For example: the map that takes an element to a singleton list containing it: f(a) = [a]) Again, the notion of compatibility is expressed by the functor laws.

On the other hand, given a functor f "over" a type a, (that is, f a is the result of applying the functor f to the algebra of type a), and function from g: a -> b, we can compute a new functor F = (fmap g) which maps f a to f b. In short, fmap is the part of F that maps "functor parts" to "functor parts", and g is the part of the function that maps "algebra parts" to "algebra parts". It takes a function, a functor, and once complete, it IS a functor too.

It might seem that different languages are using different notions of functors, but they're not. They're merely using functors over different algebras. OCamls has an algebra of modules, and functors over that algebra let you attach new declarations to a module in a "compatible" way.

A Haskell functor is NOT a type class. It is a data type with a free variable which satisfies the type class. If you're willing to dig into the guts of a datatype (with no free variables), you can reinterpret a data type as a functor over an underlying algebra. For example:

data F = F Int

is isomorphic to the class of Ints. So F, as a value constructor, is a function that maps Int to F Int, an equivalent algebra. It is a functor. On the other hand, you don't get fmap for free here. That's what pattern matching is for.

Functors are good for "attaching" things to elements of algebras, in an algebraically compatible way.