20 KiB
id | title |
---|---|
sets-lists-tuples | Tuples, Lists, Sets |
Apart from complex data types such as maps
and records
, LIGO also
features tuples
, lists
and sets
.
Tuples
Tuples gather a given number of values in a specific order and those
values, called components, can be retrieved by their index
(position). Probably the most common tuple is the pair. For
example, if we were storing coordinates on a two dimensional grid we
might use a pair (x,y)
to store the coordinates x
and y
. There
is a specific order, so (y,x)
is not equal to (x,y)
. The number
of components is part of the type of a tuple, so, for example, we
cannot add an extra component to a pair and obtain a triple of the
same type, so, for instance, (x,y)
has always a different type from
(x,y,z)
, whereas (y,x)
might have the same type as (x,y)
.
Like records, tuple components can be of arbitrary types.
Defining Tuples
Unlike a record, tuple types do not have to be defined before they can be used. However below we will give them names by type aliasing.
type full_name is string * string // Alias
const full_name : full_name = ("Alice", "Johnson")
type full_name = string * string // Alias
let full_name : full_name = ("Alice", "Johnson") // Optional parentheses
type full_name = (string, string); // Alias
let full_name : full_name = ("Alice", "Johnson");
Accessing Components
Accessing the components of a tuple in OCaml is achieved by pattern matching. LIGO currently supports tuple patterns only in the parameters of functions, not in pattern matching. However, we can access components by their position in their tuple, which cannot be done in OCaml.
Tuple components are one-indexed like so:
const first_name : string = full_name.1;
Tuple elements are zero-indexed and accessed like so:
let first_name : string = full_name.0
Tuple components are one-indexed like so:
let first_name : string = full_name[1];
Lists
Lists are linear collections of elements of the same type. Linear means that, in order to reach an element in a list, we must visit all the elements before (sequential access). Elements can be repeated, as only their order in the collection matters. The first element is called the head, and the sub-list after the head is called the tail. For those familiar with algorithmic data structure, you can think of a list a stack, where the top is written on the left.
💡 Lists are useful when returning operations from a smart contract's entrypoint.
Defining Lists
const my_list : list (int) = list [1; 2; 2] // The head is 1
let my_list : int list = [1; 2; 2] // The head is 1
let my_list : list (int) = [1, 2, 2]; // The head is 1
Adding to Lists
Lists can be augmented by adding an element before the head (or, in terms of stack, by pushing an element on top). This operation is usually called consing in functional languages.
In PascaLIGO, the cons operator is infix and noted #
. It is not
symmetric: on the left lies the element to cons, and, on the right, a
list on which to cons. (The symbol is helpfully asymmetric to remind
you of that.)
const larger_list : list (int) = 5 # my_list // [5;1;2;2]
In CameLIGO, the cons operator is infix and noted ::
. It is not
symmetric: on the left lies the element to cons, and, on the right, a
list on which to cons.
let larger_list : int list = 5 :: my_list // [5;1;2;2]
In ReasonLIGO, the cons operator is infix and noted , ...
. It is
not symmetric: on the left lies the element to cons, and, on the
right, a list on which to cons.
let larger_list : list (int) = [5, ...my_list]; // [5,1,2,2]
💡 Lists can be iterated, folded or mapped to different values. You can find additional examples here and other built-in operators here
Functional Iteration over Lists
A functional iterator is a function that traverses a data structure and calls in turn a given function over the elements of that structure to compute some value. Another approach is possible in PascaLIGO: loops (see the relevant section).
There are three kinds of functional iterations over LIGO maps: the iterated operation, the map operation (not to be confused with the map data structure) and the fold operation.
Iterated Operation
The first, the iterated operation, is an iteration over the map with no return value: its only use is to produce side-effects. This can be useful if for example you would like to check that each value inside of a map is within a certain range, and fail with an error otherwise.
In PascaLIGO, the predefined functional iterator implementing the
iterated operation over lists is called list_iter
.
In the following example, a list is iterated to check that all its
elements (integers) are greater than 3
:
function iter_op (const l : list (int)) : unit is
block {
function iterated (const i : int) : unit is
if i > 2 then Unit else (failwith ("Below range.") : unit)
} with list_iter (iterated, l)
The iterated function must be pure, that is, it cannot mutate variables.
In CameLIGO, the predefined functional iterator implementing the
iterated operation over lists is called List.iter
.
In the following example, a list is iterated to check that all its
elements (integers) are greater than 3
:
let iter_op (l : int list) : unit =
let predicate = fun (i : int) -> assert (i > 3)
in List.iter predicate l
In ReasonLIGO, the predefined functional iterator implementing the
iterated operation over lists is called List.iter
.
In the following example, a list is iterated to check that all its
elements (integers) are greater than 3
:
let iter_op = (l : list (int)) : unit => {
let predicate = (i : int) => assert (i > 3);
List.iter (predicate, l);
};
Map Operation
We may want to change all the elements of a given list by applying to them a function. This is called a map operation, not to be confused with the map data structure.
In PascaLIGO, the predefined functional iterator implementing the map
operation over lists is called list_map
and is used as follows:
function increment (const i : int): int is i + 1
// Creates a new list with all elements incremented by 1
const plus_one : list (int) = list_map (increment, larger_list)
In CameLIGO, the predefined functional iterator implementing the map
operation over lists is called List.map
and is used as follows:
let increment (i : int) : int = i + 1
// Creates a new list with all elements incremented by 1
let plus_one : int list = List.map increment larger_list
In ReasonLIGO, the predefined functional iterator implementing the map
operation over lists is called List.map
and is used as follows:
let increment = (i : int) : int => i + 1;
// Creates a new list with all elements incremented by 1
let plus_one : list (int) = List.map (increment, larger_list);
Fold Operation
A fold operation is the most general of iterations. The folded function takes two arguments: an accumulator and the structure element at hand, with which it then produces a new accumulator. This enables having a partial result that becomes complete when the traversal of the data structure is over.
In PascaLIGO, the predefined functional iterator implementing the fold
operation over lists is called list_fold
and is used as follows:
function sum (const acc : int; const i : int): int is acc + i
const sum_of_elements : int = list_fold (sum, my_list, 0)
The folded function must be pure, that is, it cannot mutate variables.
In CameLIGO, the predefined functional iterator implementing the fold
operation over lists is called List.fold
and is used as follows:
let sum (acc, i: int * int) : int = acc + i
let sum_of_elements : int = List.fold sum my_list 0
In ReasonLIGO, the predefined functional iterator implementing the
fold operation over lists is called List.fold
and is used as follows:
let sum = ((result, i): (int, int)): int => result + i;
let sum_of_elements : int = List.fold (sum, my_list, 0);
Sets
Sets are unordered collections of values of the same type, like lists are ordered collections. Like the mathematical sets and lists, sets can be empty and, if not, elements of sets in LIGO are unique, whereas they can be repeated in a list.
Empty Sets
In PascaLIGO, the notation for sets is similar to that for lists,
except the keyword set
is used before:
const my_set : set (int) = set []
In CameLIGO, the empty set is denoted by the predefined value
Set.empty
.
let my_set : int set = Set.empty
In CameLIGO, the empty set is denoted by the predefined value
Set.empty
.
let my_set : set (int) = Set.empty;
Non-empty Sets
In PascaLIGO, the notation for sets is similar to that for lists,
except the keyword set
is used before:
const my_set : set (int) = set [3; 2; 2; 1]
You can check that 2
is not repeated in my_set
by using the LIGO
compiler like this (the output will sort the elements of the set, but
that order is not significant for the compiler):
ligo evaluate-value
gitlab-pages/docs/language-basics/src/sets-lists-tuples/sets.ligo my_set
# Outputs: { 3 ; 2 ; 1 }
In CameLIGO, there is no predefined syntactic construct for sets: you must build your set by adding to the empty set. (This is the way in OCaml.)
let my_set : int set =
Set.add 3 (Set.add 2 (Set.add 2 (Set.add 1 (Set.empty : int set))))
You can check that 2
is not repeated in my_set
by using the LIGO
compiler like this (the output will sort the elements of the set, but
that order is not significant for the compiler):
ligo evaluate-value
gitlab-pages/docs/language-basics/src/sets-lists-tuples/sets.mligo my_set
# Outputs: { 3 ; 2 ; 1 }
In ReasonLIGO, there is no predefined syntactic construct for sets: you must build your set by adding to the empty set. (This is the way in OCaml.)
let my_set : set (int) =
Set.add (3, Set.add (2, Set.add (2, Set.add (1, Set.empty : set (int)))));
You can check that 2
is not repeated in my_set
by using the LIGO
compiler like this (the output will sort the elements of the set, but
that order is not significant for the compiler):
ligo evaluate-value
gitlab-pages/docs/language-basics/src/sets-lists-tuples/sets.religo my_set
# Outputs: { 3 ; 2 ; 1 }
Set Membership
PascaLIGO features a special keyword contains
that operates like an
infix operator checking membership in a set.
const contains_3 : bool = my_set contains 3
In CameLIGO, the predefined predicate Set.mem
tests for membership
in a set as follows:
let contains_3 : bool = Set.mem 3 my_set
In ReasonLIGO, the predefined predicate Set.mem
tests for membership
in a set as follows:
let contains_3 : bool = Set.mem (3, my_set);
Cardinal
In PascaLIGO, the predefined function size
returns the number of
elements in a given set as follows:
const set_size : nat = size (my_set)
In CameLIGO, the predefined function Set.size
returns the number of
elements in a given set as follows:
let set_size : nat = Set.size my_set
In ReasonLIGO, the predefined function Set.size
returns the number
of elements in a given set as follows:
let set_size : nat = Set.size (my_set);
Updating Sets
In PascaLIGO, there are two ways to update a set, that is to add or remove from it. Either we create a new set from the given one, or we modify it in-place. First, let us consider the former way
const larger_set : set (int) = set_add (4, my_set)
const smaller_set : set (int) = set_remove (3, my_set)
If we are in a block, we can use an instruction to modify the set bound to a given variable. This is called a patch. It is only possible to add elements by means of a patch, not remove any: it is the union of two sets.
In the following example, the parameter set s
of function update
is augmented (as the with s
shows) to include 4
and 7
, that is,
this instruction is equivalent to perform the union of two sets, one
that is modified in-place, and the other given as a literal
(extensional definition).
function update (var s : set (int)) : set (int) is block {
patch s with set [4; 7]
} with s
const new_set : set (int) = update (my_set)
In CameLIGO, we update a given set by creating another one, with or without some elements.
let larger_set : int set = Set.add 4 my_set
let smaller_set : int set = Set.remove 3 my_set
In ReasonLIGO, we update a given set by creating another one, with or without some elements.
let larger_set : set (int) = Set.add (4, my_set);
let smaller_set : set (int) = Set.remove (3, my_set);
Functional Iteration over Sets
A functional iterator is a function that traverses a data structure and calls in turn a given function over the elements of that structure to compute some value. Another approach is possible in PascaLIGO: loops (see the relevant section).
There are three kinds of functional iterations over LIGO maps: the iterated operation, the map operation (not to be confused with the map data structure) and the fold operation.
Iterated Operation
The first, the iterated operation, is an iteration over the map with no return value: its only use is to produce side-effects. This can be useful if for example you would like to check that each value inside of a map is within a certain range, and fail with an error otherwise.
In PascaLIGO, the predefined functional iterator implementing the
iterated operation over sets is called set_iter
.
In the following example, a set is iterated to check that all its
elements (integers) are greater than 3
:
function iter_op (const s : set (int)) : unit is
block {
function iterated (const i : int) : unit is
if i > 2 then Unit else (failwith ("Below range.") : unit)
} with set_iter (iterated, s)
The iterated function must be pure, that is, it cannot mutate variables.
In CameLIGO, the predefined functional iterator implementing the
iterated operation over sets is called Set.iter
.
In the following example, a set is iterated to check that all its
elements (integers) are greater than 3
:
let iter_op (s : int set) : unit =
let predicate = fun (i : int) -> assert (i > 3)
in Set.iter predicate s
In ReasonLIGO, the predefined functional iterator implementing the
iterated operation over sets is called Set.iter
.
In the following example, a set is iterated to check that all its
elements (integers) are greater than 3
:
let iter_op = (s : set (int)) : unit => {
let predicate = (i : int) => assert (i > 3);
Set.iter (predicate, s);
};
Map Operation
We may want to change all the elements of a given set by applying to them a function. This is called a map operation, not to be confused with the map data structure.
In PascaLIGO, the predefined functional iterator implementing the map
operation over sets is called set_map
and is used as follows:
function increment (const i : int): int is i + 1
// Creates a new set with all elements incremented by 1
const plus_one : set (int) = set_map (increment, larger_set)
In CameLIGO, the predefined functional iterator implementing the map
operation over sets is called Set.map
and is used as follows:
let increment (i : int) : int = i + 1
// Creates a new set with all elements incremented by 1
let plus_one : int set = Set.map increment larger_set
In ReasonLIGO, the predefined functional iterator implementing the map
operation over sets is called Set.map
and is used as follows:
let increment = (i : int) : int => i + 1;
// Creates a new set with all elements incremented by 1
let plus_one : set (int) = Set.map (increment, larger_set);
Fold Operation
A fold operation is the most general of iterations. The folded function takes two arguments: an accumulator and the structure element at hand, with which it then produces a new accumulator. This enables having a partial result that becomes complete when the traversal of the data structure is over.
In PascaLIGO, the predefined functional iterator implementing the fold
operation over sets is called set_fold
and is used as follows:
function sum (const acc : int; const i : int): int is acc + i
const sum_of_elements : int = set_fold (sum, my_set, 0)
The folded function must be pure, that is, it cannot mutate variables.
It is possible to use a loop over a set as well.
function loop (const s : set (int)) : int is block {
var sum : int := 0;
for element in set s block {
sum := sum + element
}
} with sum
In CameLIGO, the predefined fold over sets is called Set.fold
.
let sum (acc, i : int * int) : int = acc + i
let sum_of_elements : int = Set.fold sum my_set 0
In ReasonLIGO, the predefined fold over sets is called Set.fold
.
let sum = ((acc, i) : (int, int)) : int => acc + i;
let sum_of_elements : int = Set.fold (sum, my_set, 0);