Code Examples

OCaml possesses an interactive system, called “toploop”, that lets you type OCaml code and have it evaluated immediately. It is a great way to learn the language and to quickly experiment with ideas. Below, we demonstrate the use of the toploop to illustrate basic capabilities of the language.

Some indications for the code below. The prompt at which you type is “#”. The code must end with “;;” (this is only an indication to the interactive system that the input has to be evaluated and is not really part of the OCaml code). The output of the system is displayed in this color.

More code examples are available on the following sites:

• Pleac
• 99 Problems (solved)
• Rosetta

Elementary functions

Let us define the square function and the recursive factorial function. Then, let us apply these functions to sample values. Unlike the majority of languages, OCaml uses parentheses for grouping but not for the arguments of a function.

# let square x = x * x;;
val square : int -> int = <fun>
# square 3;;
- : int = 9
# let rec fact x =
    if x <= 1 then 1 else x * fact (x - 1);;
val fact : int -> int = <fun>
# fact 5;;
- : int = 120
# square 120;;
- : int = 14400

Automatic memory management

All allocation and deallocation operations are fully automatic. For example, let us consider simply linked lists.

Lists are predefined in OCaml. The empty list is written []. The constructor that allows prepending an element to a list is written :: (in infix form).

# let li = 1 :: 2 :: 3 :: [];;
val li : int list = [1; 2; 3]
# [1; 2; 3];;
- : int list = [1; 2; 3]
# 5 :: li;;
- : int list = [5; 1; 2; 3]

Higher-order functions

There is no restriction on functions, which may thus be passed as arguments to other functions. Let us define a function sigma that returns the sum of the results of applying a given function f to each element of a list:

# let rec sigma f = function
    | [] -> 0
    | x :: l -> f x + sigma f l;;
val sigma : ('a -> int) -> 'a list -> int = <fun>

Anonymous functions may be defined using the fun or function construct:

# sigma (fun x -> x * x) [1; 2; 3];;
- : int = 14

Polymorphism and higher-order functions allow defining function composition in its most general form:

# let compose f g = fun x -> f (g x);;
val compose : ('a -> 'b) -> ('c -> 'a) -> 'c -> 'b = <fun>
# let square_o_fact = compose square fact;;
val square_o_fact : int -> int = <fun>
# square_o_fact 5;;
- : int = 14400

Polymorphism: sorting lists

Insertion sort is defined using two recursive functions.

# let rec sort = function
    | [] -> []
    | x :: l -> insert x (sort l)
  and insert elem = function
    | [] -> [elem]
    | x :: l -> if elem < x then elem :: x :: l
                else x :: insert elem l;;
val sort : 'a list -> 'a list = <fun>
val insert : 'a -> 'a list -> 'a list = <fun>

Note that the type of the list elements remains unspecified: it is represented by a type variable 'a. Thus, sort can be applied both to a list of integers and to a list of strings.

# sort [2; 1; 0];;
- : int list = [0; 1; 2]
# sort ["yes"; "ok"; "sure"; "ya"; "yep"];;
- : string list = ["ok"; "sure"; "ya"; "yep"; "yes"]

Imperative features

Let us encode polynomials as arrays of integer coefficients. Then, to add two polynomials, we first allocate the result array, then fill its slots using two successive for loops.

# let add_polynom p1 p2 =
    let n1 = Array.length p1
    and n2 = Array.length p2 in
    let result = Array.make (max n1 n2) 0 in
    for i = 0 to n1 - 1 do result.(i) <- p1.(i) done;
    for i = 0 to n2 - 1 do result.(i) <- result.(i) + p2.(i) done;
    result;;
val add_polynom : int array -> int array -> int array = <fun>
# add_polynom [| 1; 2 |] [| 1; 2; 3 |];;
- : int array = [|2; 4; 3|]

OCaml offers updatable memory cells, called references: ref init returns a new cell with initial contents init, !cell returns the current contents of cell, and cell := v writes the value v into cell.

We may redefine fact using a reference cell and a for loop:

# let fact n =
    let result = ref 1 in
    for i = 2 to n do
      result := i * !result
    done;
    !result;;
val fact : int -> int = <fun>
# fact 5;;
- : int = 120

The power of functions

The power of functions cannot be better illustrated than by the power function:

# let rec power f n = 
    if n = 0 then fun x -> x 
    else compose f (power f (n - 1));;
val power : ('a -> 'a) -> int -> 'a -> 'a = <fun>

The n^th derivative of a function can be computed as in mathematics by raising the derivative function to the n^th power:

# let derivative dx f = fun x -> (f (x +. dx) -. f x) /. dx;;
val derivative : float -> (float -> float) -> float -> float = <fun>
# let sin''' = power (derivative 1e-5) 3 sin;;
val sin''' : float -> float = <fun>
# let pi = 4.0 *. atan 1.0 in sin''' pi;;
- : float = 0.999998972517346263

Symbolic computation

Let us consider simple symbolic expressions made up of integers, variables, let bindings, and binary operators. Such expressions can be defined as a new data type, as follows:

# type expression =
    | Num of int
    | Var of string
    | Let of string * expression * expression
    | Binop of string * expression * expression;;
type expression =
    Num of int
  | Var of string
  | Let of string * expression * expression
  | Binop of string * expression * expression

Evaluation of these expressions involves an environment that maps identifiers to values, represented as a list of pairs.

# let rec eval env = function
    | Num i -> i
    | Var x -> List.assoc x env
    | Let (x, e1, in_e2) ->
       let val_x = eval env e1 in
       eval ((x, val_x) :: env) in_e2
    | Binop (op, e1, e2) ->
       let v1 = eval env e1 in
       let v2 = eval env e2 in
       eval_op op v1 v2
  and eval_op op v1 v2 =
    match op with
    | "+" -> v1 + v2
    | "-" -> v1 - v2
    | "*" -> v1 * v2
    | "/" -> v1 / v2
    | _ -> failwith ("Unknown operator: " ^ op);;
val eval : (string * int) list -> expression -> int = <fun>
val eval_op : string -> int -> int -> int = <fun>

As an example, we evaluate the phrase let x = 1 in x + x:

# eval [] (Let ("x", Num 1, Binop ("+", Var "x", Var "x")));;
- : int = 2

Pattern matching eases the definition of functions operating on symbolic data, by giving function definitions and type declarations similar shapes. Indeed, note the close resemblance between the definition of the eval function and that of the expression type.

Elementary debugging

To conclude, here is the simplest way of spying over functions:

let rec fib x = if x <= 1 then 1 else fib (x - 1) + fib (x - 2);;
# #trace fib;;
fib is now traced.
# fib 3;;
fib <-- 3
fib <-- 1
fib --> 1
fib <-- 2
fib <-- 0
fib --> 1
fib <-- 1
fib --> 1
fib --> 2
fib --> 3
- : int = 3

Go and try it in your browser or install it and read some tutorials.