This article includes a list of general references, but it remains largely unverified because it lacks sufficient corresponding inline citations. (September 2013) |
In mathematics and computer science, a higher-order function is a function that does at least one of the following:
All other functions are first-order functions. In mathematics higher-order functions are also termed operators or functionals. The differential operator in calculus is a common example, since it maps a function to its derivative, also a function. Higher-order functions should not be confused with other uses of the word "functor" throughout mathematics, see Functor (disambiguation).
In the untyped lambda calculus, all functions are higher-order; in a typed lambda calculus, from which most functional programming languages are derived, higher-order functions that take one function as argument are values with types of the form .
map
function, found in many functional programming languages, is one example of a higher-order function. It takes as arguments a function f and a collection of elements, and as the result, returns a new collection with f applied to each element from the collection.qsort
is an example of this.It has been suggested that this article be split into a new article titled Comparison of programming languages (higher-order functions). (Discuss) (May 2016) |
The examples are not intended to compare and contrast programming languages, but to serve as examples of higher-order function syntax
In the following examples, the higher-order function twice
takes a function, and applies the function to some value twice. If twice
has to be applied several times for the same f
it preferably should return a function rather than a value. This is in line with the "don't repeat yourself" principle.
twice←{⍺⍺ ⍺⍺ ⍵}
plusthree←{⍵+3}
g←{plusthree twice ⍵}
g 7
13
Or in a tacit manner:
twice←⍣2
plusthree←+∘3
g←plusthree twice
g 7
13
Using std::function
in C++11:
#include <iostream>
#include <functional>
auto twice = [](const std::function<int(int)>& f)
{
return [&f](int x) {
return f(f(x));
};
};
auto plus_three = [](int i)
{
return i + 3;
};
int main()
{
auto g = twice(plus_three);
std::cout << g(7) << '\n'; // 13
}
Or, with generic lambdas provided by C++14:
#include <iostream>
auto twice = [](const auto& f)
{
return [&f](int x) {
return f(f(x));
};
};
auto plus_three = [](int i)
{
return i + 3;
};
int main()
{
auto g = twice(plus_three);
std::cout << g(7) << '\n'; // 13
}
Using just delegates:
using System;
public class Program
{
public static void Main(string[] args)
{
Func<Func<int, int>, Func<int, int>> twice = f => x => f(f(x));
Func<int, int> plusThree = i => i + 3;
var g = twice(plusThree);
Console.WriteLine(g(7)); // 13
}
}
Or equivalently, with static methods:
using System;
public class Program
{
private static Func<int, int> Twice(Func<int, int> f)
{
return x => f(f(x));
}
private static int PlusThree(int i) => i + 3;
public static void Main(string[] args)
{
var g = Twice(PlusThree);
Console.WriteLine(g(7)); // 13
}
}
(defn twice [f]
(fn [x] (f (f x))))
(defn plus-three [i]
(+ i 3))
(def g (twice plus-three))
(println (g 7)) ; 13
twice = function(f) {
return function(x) {
return f(f(x));
};
};
plusThree = function(i) {
return i + 3;
};
g = twice(plusThree);
writeOutput(g(7)); // 13
import std.stdio : writeln;
alias twice = (f) => (int x) => f(f(x));
alias plusThree = (int i) => i + 3;
void main()
{
auto g = twice(plusThree);
writeln(g(7)); // 13
}
In Elixir, you can mix module definitions and anonymous functions
defmodule Hof do
def twice(f) do
fn(x) -> f.(f.(x)) end
end
end
plus_three = fn(i) -> 3 + i end
g = Hof.twice(plus_three)
IO.puts g.(7) # 13
Alternatively, we can also compose using pure anonymous functions.
twice = fn(f) ->
fn(x) -> f.(f.(x)) end
end
plus_three = fn(i) -> 3 + i end
g = twice.(plus_three)
IO.puts g.(7) # 13
or_else([], _) -> false;
or_else([F | Fs], X) -> or_else(Fs, X, F(X)).
or_else(Fs, X, false) -> or_else(Fs, X);
or_else(Fs, _, {false, Y}) -> or_else(Fs, Y);
or_else(_, _, R) -> R.
or_else([fun erlang:is_integer/1, fun erlang:is_atom/1, fun erlang:is_list/1], 3.23).
In this Erlang example, the higher-order function or_else/2
takes a list of functions (Fs
) and argument (X
). It evaluates the function F
with the argument X
as argument. If the function F
returns false then the next function in Fs
will be evaluated. If the function F
returns {false, Y}
then the next function in Fs
with argument Y
will be evaluated. If the function F
returns R
the higher-order function or_else/2
will return R
. Note that X
, Y
, and R
can be functions. The example returns false
.
let twice f = f >> f
let plus_three = (+) 3
let g = twice plus_three
g 7 |> printf "%A" // 13
package main
import "fmt"
func twice(f func(int) int) func(int) int {
return func(x int) int {
return f(f(x))
}
}
func main() {
plusThree := func(i int) int {
return i + 3
}
g := twice(plusThree)
fmt.Println(g(7)) // 13
}
Notice a function literal can be defined either with an identifier (twice
) or anonymously (assigned to variable plusThree
).
twice :: (Int -> Int) -> (Int -> Int)
twice f = f . f
plusThree :: Int -> Int
plusThree = (+3)
main :: IO ()
main = print (g 7) -- 13
where
g = twice plusThree
Explicitly,
twice=. adverb : 'u u y'
plusthree=. verb : 'y + 3'
g=. plusthree twice
g 7
13
or tacitly,
twice=. ^:2
plusthree=. +&3
g=. plusthree twice
g 7
13
Using just functional interfaces:
import java.util.function.*;
class Main {
public static void main(String[] args) {
Function<IntUnaryOperator, IntUnaryOperator> twice = f -> f.andThen(f);
IntUnaryOperator plusThree = i -> i + 3;
var g = twice.apply(plusThree);
System.out.println(g.applyAsInt(7)); // 13
}
}
Or equivalently, with static methods:
import java.util.function.*;
class Main {
private static IntUnaryOperator twice(IntUnaryOperator f) {
return f.andThen(f);
}
private static int plusThree(int i) {
return i + 3;
}
public static void main(String[] args) {
var g = twice(Main::plusThree);
System.out.println(g.applyAsInt(7)); // 13
}
}
"use strict";
const twice = f => x => f(f(x));
const plusThree = i => i + 3;
const g = twice(plusThree);
console.log(g(7)); // 13
julia> function twice(f)
function result(x)
return f(f(x))
end
return result
end
twice (generic function with 1 method)
julia> plusthree(i) = i + 3
plusthree (generic function with 1 method)
julia> g = twice(plusthree)
(::var"#result#3"{typeof(plusthree)}) (generic function with 1 method)
julia> g(7)
13
fun twice(f: (Int) -> Int): (Int) -> Int {
return { f(f(it)) }
}
fun plusThree(i: Int) = i + 3
fun main() {
val g = twice(::plusThree)
println(g(7)) // 13
}
local function twice(f)
return function (x)
return f(f(x))
end
end
local function plusThree(i)
return i + 3
end
local g = twice(plusThree)
print(g(7)) -- 13
function result = twice(f)
result = @inner
function val = inner(x)
val = f(f(x));
end
end
plusthree = @(i) i + 3;
g = twice(plusthree)
disp(g(7)); % 13
let twice f x =
f (f x)
let plus_three =
(+) 3
let () =
let g = twice plus_three in
print_int (g 7); (* 13 *)
print_newline ()
<?php
declare(strict_types=1);
function twice(callable $f): Closure {
return function (int $x) use ($f): int {
return $f($f($x));
};
}
function plusThree(int $i): int {
return $i + 3;
}
$g = twice('plusThree');
echo $g(7), "\n"; // 13
or with all functions in variables:
<?php
declare(strict_types=1);
$twice = fn(callable $f): Closure => fn(int $x): int => $f($f($x));
$plusThree = fn(int $i): int => $i + 3;
$g = $twice($plusThree);
echo $g(7), "\n"; // 13
Note that arrow functions implicitly capture any variables that come from the parent scope,[1] whereas anonymous functions require the use
keyword to do the same.
{$mode objfpc}
type fun = function(x: Integer): Integer;
function twice(f: fun; x: Integer): Integer;
begin
result := f(f(x));
end;
function plusThree(i: Integer): Integer;
begin
result := i + 3;
end;
begin
writeln(twice(@plusThree, 7)); { 13 }
end.
use strict;
use warnings;
sub twice {
my ($f) = @_;
sub {
$f->($f->(@_));
};
}
sub plusThree {
my ($i) = @_;
$i + 3;
}
my $g = twice(\&plusThree);
print $g->(7), "\n"; # 13
or with all functions in variables:
use strict;
use warnings;
my $twice = sub {
my ($f) = @_;
sub {
$f->($f->(@_));
};
};
my $plusThree = sub {
my ($x) = @_;
$x + 3;
};
my $g = $twice->($plusThree);
print $g->(7), "\n"; # 13
>>> def twice(f):
... def result(x):
... return f(f(x))
... return result
>>> plusthree = lambda i: i + 3
>>> g = twice(plusthree)
>>> g(7)
13
Python decorator syntax is often used to replace a function with the result of passing that function through a higher-order function. E.g., the function g
could be implemented equivalently:
>>> @twice
... def g(i):
... return i + 3
>>> g(7)
13
twice <- function(f) {
return(function(x) {
f(f(x))
})
}
plusThree <- function(i) {
return(i + 3)
}
g <- twice(plusThree)
> print(g(7))
[1] 13
sub twice(Callable:D $f) {
return sub { $f($f($^x)) };
}
sub plusThree(Int:D $i) {
return $i + 3;
}
my $g = twice(&plusThree);
say $g(7); # 13
In Raku, all code objects are closures and therefore can reference inner "lexical" variables from an outer scope because the lexical variable is "closed" inside of the function. Raku also supports "pointy block" syntax for lambda expressions which can be assigned to a variable or invoked anonymously.
def twice(f)
->(x) { f.call f.call(x) }
end
plus_three = ->(i) { i + 3 }
g = twice(plus_three)
puts g.call(7) # 13
fn twice(f: impl Fn(i32) -> i32) -> impl Fn(i32) -> i32 {
move |x| f(f(x))
}
fn plus_three(i: i32) -> i32 {
i + 3
}
fn main() {
let g = twice(plus_three);
println!("{}", g(7)) // 13
}
object Main {
def twice(f: Int => Int): Int => Int =
f compose f
def plusThree(i: Int): Int =
i + 3
def main(args: Array[String]): Unit = {
val g = twice(plusThree)
print(g(7)) // 13
}
}
(define (add x y) (+ x y))
(define (f x)
(lambda (y) (+ x y)))
(display ((f 3) 7))
(display (add 3 7))
In this Scheme example, the higher-order function (f x)
is used to implement currying. It takes a single argument and returns a function. The evaluation of the expression ((f 3) 7)
first returns a function after evaluating (f 3)
. The returned function is (lambda (y) (+ 3 y))
. Then, it evaluates the returned function with 7 as the argument, returning 10. This is equivalent to the expression (add 3 7)
, since (f x)
is equivalent to the curried form of (add x y)
.
func twice(_ f: @escaping (Int) -> Int) -> (Int) -> Int {
return { f(f($0)) }
}
let plusThree = { $0 + 3 }
let g = twice(plusThree)
print(g(7)) // 13
set twice {{f x} {apply $f [apply $f $x]}}
set plusThree {{i} {return [expr $i + 3]}}
# result: 13
puts [apply $twice $plusThree 7]
Tcl uses apply command to apply an anonymous function (since 8.6).
The XACML standard defines higher-order functions in the standard to apply a function to multiple values of attribute bags.
rule allowEntry{
permit
condition anyOfAny(function[stringEqual], citizenships, allowedCitizenships)
}
The list of higher-order functions in XACML can be found here.
declare function local:twice($f, $x) {
$f($f($x))
};
declare function local:plusthree($i) {
$i + 3
};
local:twice(local:plusthree#1, 7) (: 13 :)
Function pointers in languages such as C and C++ allow programmers to pass around references to functions. The following C code computes an approximation of the integral of an arbitrary function:
#include <stdio.h>
double square(double x)
{
return x * x;
}
double cube(double x)
{
return x * x * x;
}
/* Compute the integral of f() within the interval [a,b] */
double integral(double f(double x), double a, double b, int n)
{
int i;
double sum = 0;
double dt = (b - a) / n;
for (i = 0; i < n; ++i) {
sum += f(a + (i + 0.5) * dt);
}
return sum * dt;
}
int main()
{
printf("%g\n", integral(square, 0, 1, 100));
printf("%g\n", integral(cube, 0, 1, 100));
return 0;
}
The qsort function from the C standard library uses a function pointer to emulate the behavior of a higher-order function.
Macros can also be used to achieve some of the effects of higher-order functions. However, macros cannot easily avoid the problem of variable capture; they may also result in large amounts of duplicated code, which can be more difficult for a compiler to optimize. Macros are generally not strongly typed, although they may produce strongly typed code.
In other imperative programming languages, it is possible to achieve some of the same algorithmic results as are obtained via higher-order functions by dynamically executing code (sometimes called Eval or Execute operations) in the scope of evaluation. There can be significant drawbacks to this approach:
In object-oriented programming languages that do not support higher-order functions, objects can be an effective substitute. An object's methods act in essence like functions, and a method may accept objects as parameters and produce objects as return values. Objects often carry added run-time overhead compared to pure functions, however, and added boilerplate code for defining and instantiating an object and its method(s). Languages that permit stack-based (versus heap-based) objects or structs can provide more flexibility with this method.
An example of using a simple stack based record in Free Pascal with a function that returns a function:
program example;
type
int = integer;
Txy = record x, y: int; end;
Tf = function (xy: Txy): int;
function f(xy: Txy): int;
begin
Result := xy.y + xy.x;
end;
function g(func: Tf): Tf;
begin
result := func;
end;
var
a: Tf;
xy: Txy = (x: 3; y: 7);
begin
a := g(@f); // return a function to "a"
writeln(a(xy)); // prints 10
end.
The function a()
takes a Txy
record as input and returns the integer value of the sum of the record's x
and y
fields (3 + 7).
Defunctionalization can be used to implement higher-order functions in languages that lack first-class functions:
// Defunctionalized function data structures
template<typename T> struct Add { T value; };
template<typename T> struct DivBy { T value; };
template<typename F, typename G> struct Composition { F f; G g; };
// Defunctionalized function application implementations
template<typename F, typename G, typename X>
auto apply(Composition<F, G> f, X arg) {
return apply(f.f, apply(f.g, arg));
}
template<typename T, typename X>
auto apply(Add<T> f, X arg) {
return arg + f.value;
}
template<typename T, typename X>
auto apply(DivBy<T> f, X arg) {
return arg / f.value;
}
// Higher-order compose function
template<typename F, typename G>
Composition<F, G> compose(F f, G g) {
return Composition<F, G> {f, g};
}
int main(int argc, const char* argv[]) {
auto f = compose(DivBy<float>{ 2.0f }, Add<int>{ 5 });
apply(f, 3); // 4.0f
apply(f, 9); // 7.0f
return 0;
}
In this case, different types are used to trigger different functions via function overloading. The overloaded function in this example has the signature auto apply
.
By: Wikipedia.org
Edited: 2021-06-18 15:16:21
Source: Wikipedia.org