Duplicate functionality?
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Date:   (:) 
From:  Brian Hurt <bhurt@s...> 
Subject:  Re: [Camllist] Duplicate functionality? 
On Fri, 21 Oct 2005, Stephen Brackin wrote: > My biggest initial question is why OCaml has both a modules system and > objects: Aren't they different ways of accomplishing the same things? No. And this is one of the most misunderstood things about Ocaml modules that they are NOT just a weird and broken implementation of objects. A better point of reference would probably be C++ templates (although Ocaml modules fix the complaints I have with C++ templates). Modules are used for code that is "based on" other code. An example makes this clearer. Let's consider Newton's method for root find. This is an incredibly powerfull algorithm that can be applied to a huge number of different number systems. For example, it works on reals, it works on complexs, it works on quaterions, it works on integers, and it works on systems of nonlinear equations (vectors and matricies). And when I say it works on reals, I mean it works on all representations of reals it works on IEEE floating point, it works on arbitrary precision rationals, it works on arbitrary precision floats, it works on fixed precision floats, etc. All we need to implement Newton's method is a small set of basic operations. We need subtraction, we need to be able to solve Ax = b given A and b (which is just x = b/A in most number systems, but we express it this way as it's more "natural" if A is the Jacobian matrix of partial derivitives and b is the vector residual), and we need some way to say we're "close enough" to the solution that we can stop. With modules, we might write: module type Req = sig type t (* the basic type of the number system *) type dt (* the type of derivitives generally, this will be the same * as t, but in the case of vectors/matricies, t is a vector * while dt is a matrix. *) type et (* The type of the error value. Often times this will be * the same as t above, but for "constructed" types * like complexes and vectors, type et will be whatever * real type they are made out of. *) val sub : t > t > t (* subtraction *) val solve : et > dt > t > t (* Solve Ax = b to within epsilon. * Generally epsilon will be ignored, * and the solution will just be * x = b/A. *) val default_epsilon : et val within_epsilon : et > t > t > bool (* Returns true if the two value differ by a factor of less * than epsilon. *) end;; module Make(Alg: Req) = struct exception Max_iters_reached of Alg.t let meth ?(epsilon = Alg.default_epsilon) ?(max_iters = max_int) f df x = (* Find a root to f given f and it's derivitive df starting * at an initial guess of x. *) let rec loop i x = if i > max_iters then raise (Max_iters_reached x) else let x' = Alg.sub x (Alg.solve epsilon (df x) (f x)) in if Alg.within_epsilon epsilon x x' then x' else loop (i+1) x' in loop 0 x end;; Now, we could probably implement something like this in objects Newtons would be a base class calling out to virtual functions like solve and sub which would be implemented in concrete subclasses. But there are several large advantages to using modules in this case. The first one is types. Note that were I to implement Newtons with floating point numbers, like: module Float = struct type t = float type dt = float type et = float let sub = ( . ) let solve (_: et) a b = b /. a let default_epsilon = 1.e14;; let within_epsilon e x y = ((abs_float ((x . y) /. x)) < e)  ((abs_float (x . y)) < e) end;; module FloatNewtons = Make(Float);; Ocaml figures out the t, dt, and et are "all the same type", and I have a function with the right signature. This is doable with dynamic type checking and objects, but not static. Or at least I've never seen it done in a static language. Another advantage of modules over structures in the type arena is to be able to express the "these two objects need to be of the same implementation" as a type constraint. An example of this is the compare function in Map or Set. The compare function wants to gaurentee that the two maps or sets you are comparing have the same ordering. They can do that using modules and functors. Another advantage of modules and functors is, with ocamldefun, the ability to remove the layer of vituralization, and actually have myself a highperformance Newton's method implementation. Another advantage is that it allows objects to be objects, and stop having to be things they're not, like name spaces. Ocaml objects have a hard time implementing the Singleton pattern, for example. Of course they do you should be using modules for that. Brian