简单地说，函子或函数对象是可以像函数一样调用的类对象。

在c++中:

这就是写函数的方法

void foo()
{
    cout << "Hello, world! I'm a function!";
}

这就是写函子的方法

class FunctorClass
{
    public:
    void operator ()
    {
        cout << "Hello, world! I'm a functor!";
    }
};

现在你可以这样做:

foo(); //result: Hello, World! I'm a function!

FunctorClass bar;
bar(); //result: Hello, World! I'm a functor!

这样做的好处是可以将state保存在类中——想象一下，如果您想询问一个函数被调用了多少次。没有办法以简洁、封装的方式做到这一点。对于函数对象，它就像任何其他类一样:你有一些实例变量，你在operator()中增加它，还有一些方法来检查这个变量，一切都很整齐。

有三种不同的意思，没有太大的联系!

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);;

您现在可以快速添加许多可能的顺序，形成新顺序的方法，轻松地对它们进行二进制或线性搜索。泛型编程。

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

因此，这是一种特殊的类型构造函数，与Ocaml中的函子关系不大!

在命令式语言中，它是指向函数的指针。

“函子”这个词来自范畴论，范畴论是数学中一个非常普遍、非常抽象的分支。函数式语言的设计者至少以两种不同的方式借用了它。

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.

像往常一样，人们继续发明新的、有用的抽象，您可能想要研究应用函子，对此最好的参考可能是Conor McBride和Ross Paterson撰写的一篇名为《带效果的应用编程》的论文。

这里的其他答案是完整的，但我将尝试另一种解释FP使用函子。我们来做个类比:

函子是类型为A的容器，当它受到从A→b映射的函数的作用时，将产生类型为b的容器。

与c++中使用的抽象函数指针不同，这里函子不是函数;相反，它是一种在受到某个函数影响时表现一致的东西。

在Inria网站上的O'Reilly OCaml书中有一个很好的例子(不幸的是，在写这篇文章时，它被删除了)。我在加州理工学院使用的这本书中找到了一个非常相似的例子:OCaml介绍(pdf链接)。相关的部分是关于函子的章节(书中139页，PDF中149页)。

在书中，他们有一个名为MakeSet的函子，它创建了一个由列表组成的数据结构，以及添加元素、确定元素是否在列表中以及查找元素的函数。用于确定它是否在集合中的比较函数已被参数化(这是使MakeSet成为函子而不是模块的原因)。

它们还有一个实现比较函数的模块，这样就可以进行不区分大小写的字符串比较。

使用函子函数和实现比较的模块，它们可以在一行中创建一个新模块:

module SSet = MakeSet(StringCaseEqual);;

这将为使用不区分大小写比较的一组数据结构创建一个模块。如果您想创建一个使用区分大小写比较的集合，那么您只需要实现一个新的比较模块，而不是一个新的数据结构模块。

Tobu将函子与c++中的模板进行了比较，我认为这是非常恰当的。

你回答了不少不错的问题。我将加入:

函子，在数学意义上，是代数上一种特殊的函数。它是将一个代数映射到另一个代数的最小函数。“极简性”用函子定律来表示。

有两种方式来看待这个问题。例如，列表是某些类型的函子。也就是说，给定类型为“a”的代数，您可以生成包含类型为“a”的列表的兼容代数。(例如:将一个元素带到包含它的单元素列表的映射:f(a) = [a])同样，兼容性的概念是由函子定律表示的。

另一方面,鉴于函子f / a型,(也就是说,f是应用函子的结果f的代数a型),从g和功能:- > b,我们可以计算一个新的函子f = (fmap g)映射f a到f b。简而言之,fmap是f的一部分映射“函子零件”“函子零件”,和g函数的一部分,“代数”映射到“代数部分”。它接受一个函数，一个函子，一旦完成，它也是一个函子。

看起来不同的语言使用不同的函子概念，但事实并非如此。它们只是在不同的代数上使用函子。OCamls有一个模块代数，这个代数上的函子允许您以一种“兼容”的方式将新声明附加到模块。

Haskell函子不是类型类。它是一个具有满足类型类的自由变量的数据类型。如果您愿意深入挖掘数据类型的精髓(没有自由变量)，您可以通过底层代数将数据类型重新解释为函子。例如:

数据F = F Int

是整型类的同构。F，作为一个值构造函数，是一个将Int映射到F Int的函数，一个等价的代数。它是一个函子。另一方面，这里的fmap不是免费的。这就是模式匹配的作用。

函子很适合以一种代数相容的方式将事物“附加”到代数元素上。