The List.fold_left
and List.fold_right
functions are higher-order functions that implement the outer logic of list aggregation. Aggregating a list, sometimes also referred to as reducing a list, means computing a value derived from the sequential inspection of all items in that list.
The documentation of the List module states that
List.fold_left f a [b1; ...; bn]
is f (... (f (f a b1) b2) ...) bn
.List.fold_right f [a1; ...; an] b
is f a1 (f a2 (... (f an b) ...))
. (This latter function is not tail-recursive.)In plain English computing List.fold_left f a [b1; ...; bn]
amounts to running through the list [b1; ...; bn]
keeping track of an accumulator initially set to a
: each time we see an item in the list, we use f
to update the value of the accumulator, and when we are done, the accumulator is the final value of our computation. The List.fold_right
function is similar.
Here are a few practical examples:
List.fold_left ( + ) 0 lst
let average lst =
let (sum, n) =
List.fold_left (fun (sum, n) x -> (sum +. x, n + 1)) (0.0, 0) lst
in
sum /. (float_of_int n)
The functions List.fold_left
and List.fold_right
are so general that they can be used to implement almost every other functions from the list module:
let list_length lst = (* Alternative implementation to List.length *)
List.fold_left ( + ) 0 lst
let list_filter predicate lst = (* Alternative implementation to List.filter *)
List.fold_right (fun a b -> if predicate a then a :: b else b) lst []
It is even possible to reimplement the List.iter
function, remember that ()
is the global state of the program to interpret this code as a further example of list aggregation:
let list_iter f lst = (* Alternation implementation to List.iter *)
List.fold_left (fun () b -> f b) () lst
These examples are meant to be learning material, these implementations have no virtue over the corresponding functions from the standard library.