Collections
You are encouraged to solve this task according to the task description, using any language you may know.
Collections are abstractions to represent sets of values.
In statically-typed languages, the values are typically of a common data type.
- Task
Create a collection, and add a few values to it.
- See also
- Array
- Associative array: Creation, Iteration
- Collections
- Compound data type
- Doubly-linked list: Definition, Element definition, Element insertion, List Traversal, Element Removal
- Linked list
- Queue: Definition, Usage
- Set
- Singly-linked list: Element definition, Element insertion, List Traversal, Element Removal
- Stack
11l
11l supports arrays, tuples, dictionaries, sets, and double-ended queues as built-in collection types. See http://11l-lang.org/doc/built-in-types for further details.
68000 Assembly
(I'm probably going to use the words "array" and "collection" interchangeably, apologizing in advance here.)
Like nearly all data structures in assembly, a collection is just a sequence of values in memory. They need not share the same data type, however mixing byte data with word/long data can cause problems with alignment if the byte data is not correctly padded. Nothing is stopping you from interpreting data the "wrong" way, which can be handy for situations where you need to "deep-copy" an array of bytes and number of elements in that array just happens to be a multiple of 4 (meaning that you can treat the data as longs and copy it more quickly).
For collections of data whose elements are more than 4 bytes in size, or have varying lengths (such as strings), it's best to store a collection of pointers to those elements rather than the elements themselves. Reason being, pointers are always 4 bytes (i.e. a "long") on the 68000, regardless of the length of whatever it is they point to. This makes it much easier to find the beginning of a desired string, since you don't have to know each string's length in order to (for example) load the 5th string in the collection
In this example, we're creating a collection of strings associated with the vector table of the 68000's CPU. It's not too important what this data represents, it's more to showcase an actual application of the concept of a collection of pointers being more convenient than a collection of actual strings, so don't worry if you don't understand what these strings mean.
dc.l TrapString_Bus
dc.l TrapString_Addr
dc.l TrapString_Illegal
dc.l TrapString_Div0
dc.l TrapString_chk
dc.l TrapString_v
dc.l TrapString_priv
dc.l TrapString_trace
TrapString_Bus:
dc.b "Bus error",255
even
TrapString_Addr:
dc.b "Address error",255
even
TrapString_Illegal:
dc.b "Illegal Instruction",255
even
TrapString_Div0:
dc.b "Divide By Zero",255
even
TrapString_chk:
dc.b "CHK Failure",255
even
TrapString_v:
dc.b "Signed Overflow",255
even
TrapString_priv:
dc.b "Privilege Violation",255
even
TrapString_trace:
dc.b "Tracing",255
even
As mentioned earlier, 68000 Assembly doesn't know (or care) what types of data are stored in an array or collection, although if you try to read from an odd memory address at word or long length your CPU will suffer an alignment fault. The CPU doesn't care what types of data are actually stored in an array. It's the programmer's job to tell the CPU what the data actually means.
ABAP
REPORT z_test_rosetta_collection.
CLASS lcl_collection DEFINITION CREATE PUBLIC.
PUBLIC SECTION.
METHODS: start.
ENDCLASS.
CLASS lcl_collection IMPLEMENTATION.
METHOD start.
DATA(itab) = VALUE int4_table( ( 1 ) ( 2 ) ( 3 ) ).
cl_demo_output=>display( itab ).
ENDMETHOD.
ENDCLASS.
START-OF-SELECTION.
NEW lcl_collection( )->start( ).
Ada
Ada 95 and earlier offers arrays. Ada 2005 adds the Ada.Containers package and its children. Examples of Doubly Linked Lists and Vectors are given. Ada 2005 also provides hashed and ordered Maps and Sets (not shown).
anonymous arrays
In Ada, arrays can be indexed on any range of discrete values. The example below creates an anonymous array indexed from -3 to -1. It initializes the three elements of the array at declaration. Then it reverses their order in the array.
Anonymous arrays have no type associated with them that is accessible to the programmer. This means that anonymous arrays cannot be compared in the aggregate to other arrays (even those with the same index structure and contained type) or passed as a parameter to a subprogram. For these reasons, anonymous arrays are best used as singletons and global constants.
procedure Array_Collection is
A : array (-3 .. -1) of Integer := (1, 2, 3);
begin
A (-3) := 3;
A (-2) := 2;
A (-1) := 1;
end Array_Collection;
array types
Because of the limitations of anonymous arrays noted above, arrays are more typically defined in Ada as array types, as in the example below.
procedure Array_Collection is
type Array_Type is array (1 .. 3) of Integer;
A : Array_Type := (1, 2, 3);
begin
A (1) := 3;
A (2) := 2;
A (3) := 1;
end Array_Collection;
unconstrained arrays
Dynamic arrays can be created through the use of pointers to unconstrained arrays. While an unconstrained array's index type is defined, it does not have a pre-defined range of indices - they are specified at the time of declaration or, as would be the case in a dynamic array, at the time the memory for the array is allocated. The creation of a dynamic array is not shown here, but below is an example declaration of an unconstrained array in Ada.
procedure Array_Collection is
type Array_Type is array (positive range <>) of Integer; -- may be indexed with any positive
-- Integer value
A : Array_Type(1 .. 3); -- creates an array of three integers, indexed from 1 to 3
begin
A (1) := 3;
A (2) := 2;
A (3) := 1;
end Array_Collection;
doubly linked lists
with Ada.Containers.Doubly_Linked_Lists;
use Ada.Containers;
procedure Doubly_Linked_List is
package DL_List_Pkg is new Doubly_Linked_Lists (Integer);
use DL_List_Pkg;
DL_List : List;
begin
DL_List.Append (1);
DL_List.Append (2);
DL_List.Append (3);
end Doubly_Linked_List;
vectors
with Ada.Containers.Vectors;
use Ada.Containers;
procedure Vector_Example is
package Vector_Pkg is new Vectors (Natural, Integer);
use Vector_Pkg;
V : Vector;
begin
V.Append (1);
V.Append (2);
V.Append (3);
end Vector_Example;
Aime
Aime collections include "list"s (sequences) and "record"s (associative arrays). Both types of collections are heterogenous and resize dynamically.
Lists
Declaring a list:
list l;Adding values to it:
l_p_integer(l, 0, 7);
l_push(l, "a string");
l_append(l, 2.5);Retrieving values from a list:
l_query(l, 2)
l_head(l)
l_q_text(l, 1)
l[3]Records
Declaring a record:
record r;Adding values to it:
r_p_integer(r, "key1", 7);
r_put(r, "key2", "a string");
r["key3"] = .25;Retrieving values from a record:
r_query(r, "key1")
r_tail(r)
r["key2"]ALGOL 68
Arrays are the closest thing to collections available as standard in Algol 68. Collections could be implemented using STRUCTs but there are none as standard. Some examples of arrays:
# create a constant array of integers and set its values #
[]INT constant array = ( 1, 2, 3, 4 );
# create an array of integers that can be changed, note the size mst be specified #
# this array has the default lower bound of 1 #
[ 5 ]INT mutable array := ( 9, 8, 7, 6, 5 );
# modify the second element of the mutable array #
mutable array[ 2 ] := -1;
# array sizes are normally fixed when the array is created, however arrays can be #
# declared to be FLEXible, allowing their sizes to change by assigning a new array to them #
# The standard built-in STRING is notionally defined as FLEX[ 1 : 0 ]CHAR in the standard prelude #
# Create a string variable: #
STRING str := "abc";
# assign a longer value to it #
str := "bbc/itv";
# add a few characters to str, +=: adds the text to the beginning, +:= adds it to the end #
"[" +=: str; str +:= "]"; # str now contains "[bbc/itv]" #
# Arrays of any type can be FLEXible: #
# create an array of two integers #
FLEX[ 1 : 2 ]INT fa := ( 0, 0 );
# replace it with a new array of 5 elements #
fa := LOC[ -2 : 2 ]INT;Apex
Lists
A list is an ordered collection of elements that are distinguished by their indices Creating Lists
// Create an empty list of String
List<String> my_list = new List<String>();
// Create a nested list
List<List<Set<Integer>>> my_list_2 = new List<List<Set<Integer>>>();Access elements in a list
List<Integer> myList = new List<Integer>(); // Define a new list
myList.add(47); // Adds a second element of value 47 to the end
// of the list
Integer i = myList.get(0); // Retrieves the element at index 0
myList.set(0, 1); // Adds the integer 1 to the list at index 0
myList.clear(); // Removes all elements from the listUsing Array Notation for One-dimensional list
String[] colors = new List<String>();
List<String> colors = new String[1];
colors[0] = 'Green';Sets
A set is an unordered collection of elements that do not contain any duplicates. Defining a set:
Set<String> s1 = new Set<String>{'a', 'b + c'}; // Defines a new set with two elements
Set<String> s2 = new Set<String>(s1); // Defines a new set that contains the
// elements of the set created in the previous stepAccess elements in a set:
Set<Integer> s = new Set<Integer>(); // Define a new set
s.add(1); // Add an element to the set
System.assert(s.contains(1)); // Assert that the set contains an element
s.remove(1); // Remove the element from the setNote the following limitations on sets:
- Unlike Java, Apex developers do not need to reference the algorithm that is used to implement a set in their declarations (for example, HashSet or TreeSet). Apex uses a hash structure for all sets.
- A set is an unordered collectionβyou canβt access a set element at a specific index. You can only iterate over set elements.
- The iteration order of set elements is deterministic, so you can rely on the order being the same in each subsequent execution of the same code.
Maps
A map is a collection of key-value pairs where each unique key maps to a single value Declaring a map:
Map<String, String> country_currencies = new Map<String, String>();
Map<ID, Set<String>> m = new Map<ID, Set<String>>();
Map<String, String> MyStrings = new Map<String, String>{'a' => 'b', 'c' => 'd'.toUpperCase()};Accessing a Map:
Map<Integer, String> m = new Map<Integer, String>(); // Define a new map
m.put(1, 'First entry'); // Insert a new key-value pair in the map
m.put(2, 'Second entry'); // Insert a new key-value pair in the map
System.assert(m.containsKey(1)); // Assert that the map contains a key
String value = m.get(2); // Retrieve a value, given a particular key
System.assertEquals('Second entry', value);
Set<Integer> s = m.keySet(); // Return a set that contains all of the keys in the mapMap Considerations:
- Unlike Java, Apex developers do not need to reference the algorithm that is used to implement a map in their declarations (for example, HashMap or TreeMap). Apex uses a hash structure for all maps.
- The iteration order of map elements is deterministic. You can rely on the order being the same in each subsequent execution of the same code. However, we recommend to always access map elements by key.
- A map key can hold the null value.
- Adding a map entry with a key that matches an existing key in the map overwrites the existing entry with that key with the new entry.
Map keys of type String are case-sensitive. Two keys that differ only by the case are considered unique and have corresponding distinct Map entries.Subsequently, the Map methods, including put, get, containsKey, and remove treat these keys as distinct.
- Uniqueness of map keys of user-defined types is determined by the equals and hashCode methods, which you provide in your classes. Uniqueness of keys of all other non-primitive types, such as sObject keys, is determined by comparing the objectsβ field values.
- A Map object is serializable into JSON only if it uses one of the following data types as a key.
Boolean, Date, DateTime, Decimal, Double, Enum, Id, Integer, Long, String, Time
Arturo
Array
; initialize array
arr: ["one" 2 "three" "four"]
; add an element to the array
arr: arr ++ 5
; print it
print arr
- Output:
one 2 three four 5
Dictionary
; initialize dictionary
dict: #[
name: "john"
surname: "doe"
age: 34
preferredFood: ["fruit" "pizza"]
]
; add an element to the dictionary
dict\country: "Spain"
; print it
print dict
- Output:
[name:john surname:doe age:34 preferredFood:[fruit pizza] country:Spain]
AutoHotkey
Objects
myCol := Object()
mycol.mykey := "my value!"
mycol["mykey"] := "new val!"
MsgBox % mycol.mykey ; new val
Pseudo-arrays
Documentation: http://www.autohotkey.com/docs/misc/Arrays.htm
Loop 3
array%A_Index% := A_Index * 9
MsgBox % array1 " " array2 " " array3 ; 9 18 27
Structs
Structs are not natively supported in AutoHotkey, however they are often required in DllCalls to C++ Dlls. This shows how to retrieve values from a RECT structure in AutoHotkey (from the DllCall documentation at http://www.autohotkey.com/docs/commands/DllCall.htm)
VarSetCapacity(Rect, 16) ; A RECT is a struct consisting of four 32-bit integers (i.e. 4*4=16).
DllCall("GetWindowRect", UInt, WinExist(), UInt, &Rect) ; WinExist() returns an HWND.
MsgBox % "Left " . NumGet(Rect, 0, true) . " Top " . NumGet(Rect, 4, true)
. " Right " . NumGet(Rect, 8, true) . " Bottom " . NumGet(Rect, 12, true)
AWK
In awk, the closest thing to collections would be arrays. They are created when needed at assignment
a[0]="hello"
or by splitting a string
split("one two three",a)
Single elements are accessible with the bracket notation, like in C:
print a[0]
One can iterate over the elements of an array:
for(i in a) print i":"a[i]
Axe
1β{Lβ}
2β{Lβ+1}
3β{Lβ+2}
4β{Lβ+3}
Disp {Lβ}βΊDec,i
Disp {Lβ+1}βΊDec,i
Disp {Lβ+2}βΊDec,i
Disp {Lβ+3}βΊDec,iBBC BASIC
Arrays
In BBC BASIC the only native type of 'collection' is the array; the index starts at zero and the subscript specified in the DIM is the highest value of the index. Hence in this example an array with two elements is defined:
DIM text$(1)
text$(0) = "Hello "
text$(1) = "world!"
Arrays of structures
When the objects in the collection are not simple scalar types an array of structures may be used:
DIM collection{(1) name$, year%}
collection{(0)}.name$ = "Richard"
collection{(0)}.year% = 1952
collection{(1)}.name$ = "Sue"
collection{(1)}.year% = 1950
Linked lists
Although not a native language feature, other types of collections such as linked lists may be constructed:
DIM node{name$, year%, link%}
list% = 0
PROCadd(list%, node{}, "Richard", 1952)
PROCadd(list%, node{}, "Sue", 1950)
PROClist(list%, node{})
END
DEF PROCadd(RETURN l%, c{}, n$, y%)
LOCAL p%
DIM p% DIM(c{})-1
!(^c{}+4) = p%
c.name$ = n$
c.year% = y%
c.link% = l%
l% = p%
ENDPROC
DEF PROClist(l%, c{})
WHILE l%
!(^c{}+4) = l%
PRINT c.name$, c.year%
l% = c.link%
ENDWHILE
ENDPROC
bc
See Arrays for basic operations on arrays, the only collection type in bc.
C
See Also foreach
One thing in C language proper that can be said to be a collection is array type.
An array has a length known at compile time.
#define cSize( a ) ( sizeof(a)/sizeof(a[0]) ) /* a.size() */
int ar[10]; /* Collection<Integer> ar = new ArrayList<Integer>(10); */
ar[0] = 1; /* ar.set(0, 1); */
ar[1] = 2;
int* p; /* Iterator<Integer> p; Integer pValue; */
for (p=ar; /* for( p = ar.itereator(), pValue=p.next(); */
p<(ar+cSize(ar)); /* p.hasNext(); */
p++) { /* pValue=p.next() ) { */
printf("%d\n",*p); /* System.out.println(pValue); */
} /* } */
Please note that c built-in pointer-arithmetic support which helps this logic. An integer may be 4 bytes, and a char 1 byte: the plus operator (+) is overloaded to multiply a incement by 4 for integer pointers and by 1 for char pointers (etc).
Another construct which can be seen as a collection is a malloced array. The size of a malloced array is not known at compile time.
int* ar; /* Collection<Integer> ar; */
int arSize;
arSize = (rand() % 6) + 1;
ar = calloc(arSize, sizeof(int) ); /* ar = new ArrayList<Integer>(arSize); */
ar[0] = 1; /* ar.set(0, 1); */
int* p; /* Iterator<Integer> p; Integer pValue; */
for (p=ar; /* p=ar.itereator(); for( pValue=p.next(); */
p<(ar+arSize); /* p.hasNext(); */
p++) { /* pValue=p.next() ) { */
printf("%d\n",*p); /* System.out.println(pValue); */
} /* } */
A string is another C language construct (when looked at with its standard libraries) that behaves like a collection. A C language string is an array of char, and it's size may or may not be known at compile time, however a c string is terminated with a ASCII NUL (which may be stated as a constant, '\0' or ((char)0) in the C language). The String standard library "class" has many "methods", however instead of being called String.method(), they are usually called strmethod().
Arbitrarily complex data structures can be constructed, normally via language features struct and pointers. They are everywhere, but not provided by the C language itself per se.
C#
Arrays
// Creates and initializes a new integer Array
int[] intArray = new int[5] { 1, 2, 3, 4, 5 };
//same as
int[] intArray = new int[]{ 1, 2, 3, 4, 5 };
//same as
int[] intArray = { 1, 2, 3, 4, 5 };
//Arrays are zero-based
string[] stringArr = new string[5];
stringArr[0] = "string";
ArrayList and List
The size of ArrayList is dynamically increased as required. ArrayLists are zero-based.
//Create and initialize ArrayList
ArrayList myAl = new ArrayList { "Hello", "World", "!" };
//Create ArrayList and add some values
ArrayList myAL = new ArrayList();
myAL.Add("Hello");
myAL.Add("World");
myAL.Add("!");
The List class is the generic equivalent of the ArrayList class. A List is a strongly typed list of objects that can be accessed by index ( zero-based again).
//Create and initialize List
List<string> myList = new List<string> { "Hello", "World", "!" };
//Create List and add some values
List<string> myList2 = new List<string>();
myList2.Add("Hello");
myList2.Add("World");
myList2.Add("!");
Hashtable and Dictionary
Hashtables represent a collection of key/value pairs that are organized based on the hash code of the key. Keys must be unique.
//Create an initialize Hashtable
Hashtable myHt = new Hashtable() { { "Hello", "World" }, { "Key", "Value" } };
//Create Hashtable and add some Key-Value pairs.
Hashtable myHt2 = new Hashtable();
myHt2.Add("Hello", "World");
myHt2.Add("Key", "Value");
Dictionary is a generic class.It represents a collection of key/value pairs. Keys must be unique.
//Create an initialize Dictionary
Dictionary<string, string> dict = new Dictionary<string, string>() { { "Hello", "World" }, { "Key", "Value" } };
//Create Dictionary and add some Key-Value pairs.
Dictionary<string, string> dict2 = new Dictionary<string, string>();
dict2.Add("Hello", "World");
dict2.Add("Key", "Value");
C++
C++ has a range of different collections optimized for different use cases. Note that in C++, objects of user-defined types are mostly treated just like objects of built-in types; especially there's no different treatment for collections. Thus all collections can simply be demonstrated with the built-in type int. For user-defined types, just replace int with the user-defined type. Any type which goes into a collection must be copyable and assignable (which in general is automatically the case unless you explicitly disallow it).
Note however that C++ collections store copies of the objects given to them, so you'll lose any polymorphic behaviour. If you need polymorphism, use a collection of pointers (or smart pointers like boost::shared_ptr).
built-in array
The simplest collection in C++ is the built-in array. Built-in arrays have a fixed size, and except for POD types (i.e. basically any type you culd also write in C), the members are all initialized at array creation time (if no explicit initialization is done, the default constructr is used).
int a[5]; // array of 5 ints (since int is POD, the members are not initialized)
a[0] = 1; // indexes start at 0
int primes[10] = { 2, 3, 5, 7, 11, 13, 17, 19, 23, 29 }; // arrays can be initialized on creation
#include <string>
std::string strings[4]; // std::string is no POD, therefore all array members are default-initialized
// (for std::string this means initialized with empty strings)
vector
A vector is basically a resizable array. It is optimized for adding/removing elements on the end, and fast access to elements anywhere. Inserting elements at the beginning or in the middle is possible, but in general inefficient.
#include <vector>
std::vector<int> v; // empty vector
v.push_back(5); // insert a 5 at the end
v.insert(v.begin(), 7); // insert a 7 at the beginning
deque
A deque is optimized for appending and removing elements on both ends ofd the array. Accessing random elements is still efficient, but slightly less than with vector.
#include <deque>
std::deque<int> d; // empty deque
d.push_back(5); // insert a 5 at the end
d.push_front(7); // insert a 7 at the beginning
d.insert(v.begin()+1, 6); // insert a 6 in the middle
list
A list is optimized for insertion at an arbitrary place (provided you already have an iterator pointing to that place). Element access is efficient only in linear order.
#include <list>
std::list<int> l; // empty list
l.push_back(5); // insert a 5 at the end
l.push_front(7); // insert a 7 at the beginning
std::list::iterator i = l.begin();
++l;
l.insert(i, 6); // insert a 6 in the middle
set
A set keeps the inserted elements sorted, and also makes sure that each element occurs only once. Of course, if you want to put something into a set, it must be less-than-comparable, i.e. you must be able to compare which of two objects a and b is smaller using a<b (there's also a way to define sets with an user-defined order, in which case this restriction doesn't apply).
#include <set>
std::set<int> s; // empty set
s.insert(5); // insert a 5
s.insert(7); // insert a 7 (automatically placed after the 5)
s.insert(5); // try to insert another 5 (will not change the set)
multiset
A multiset is like a set, except the same element may occur multiple times.
#include <multiset>
std::multiset<int> m; // empty multiset
m.insert(5); // insert a 5
m.insert(7); // insert a 7 (automatically placed after the 5)
m.insert(5); // insert a second 5 (now m contains two 5s, followed by one 7)
Clojure
Clojure's collections are immutable: rather than modifying an existing collection, you create a new collection based on a previous one but with changes, for example an additional element.
Hash maps
{1 "a", "Q" 10} ; commas are treated as whitespace
(hash-map 1 "a" "Q" 10) ; equivalent to the above
(let [my-map {1 "a"}]
(assoc my-map "Q" 10)) ; "adding" an element
Lists
'(1 4 7) ; a linked list
(list 1 4 7)
(cons 1 (cons 4 '(7)))
Vectors
['a 4 11] ; somewhere between array and list
(vector 'a 4 11)
(cons ['a 4] 11) ; vectors add at the *end*
Sets
#{:pig :dog :bear}
(assoc #{:pig :bear} :dog)
(set [:pig :bear :dog])
COBOL
COBOL is very much a fixed length programming environment. Hierarchical fixed length records are the main data grouping in many COBOL applications.
Arrays are historically called tables in COBOL literature and are usually defined within a hierarchy. Tables are defined with the reserved word phrases OCCURS n TIMES, and OCCURS FROM n TO m TIMES DEPENDING ON x, (commonly referred to as ODO for short).
This example shows a small record layout inside a very small table. The last line of the output sample is a debug enabled run-time bounds check abend, caused after the table is decreased in size. The first run, without bounds check, runs to an erroneous completion; the second, with debug enabled, does not.
identification division.
program-id. collections.
data division.
working-storage section.
01 sample-table.
05 sample-record occurs 1 to 3 times depending on the-index.
10 sample-alpha pic x(4).
10 filler pic x value ":".
10 sample-number pic 9(4).
10 filler pic x value space.
77 the-index usage index.
procedure division.
collections-main.
set the-index to 3
move 1234 to sample-number(1)
move "abcd" to sample-alpha(1)
move "test" to sample-alpha(2)
move 6789 to sample-number(3)
move "wxyz" to sample-alpha(3)
display "sample-table : " sample-table
display "sample-number(1): " sample-number(1)
display "sample-record(2): " sample-record(2)
display "sample-number(3): " sample-number(3)
*> abend: out of bounds subscript, -debug turns on bounds check
set the-index down by 1
display "sample-table : " sample-table
display "sample-number(3): " sample-number(3)
goback.
end program collections.
- Output:
prompt$ cobc -xj collections.cob sample-table : abcd:1234 test:0000 wxyz:6789 sample-number(1): 1234 sample-record(2): test:0000 sample-number(3): 6789 sample-table : abcd:1234 test:0000 sample-number(3): 6789 prompt$ cobc -xj -debug collections.cob sample-table : abcd:1234 test:0000 wxyz:6789 sample-number(1): 1234 sample-record(2): test:0000 sample-number(3): 6789 sample-table : abcd:1234 test:0000 collections.cob: 33: libcob: Subscript of 'sample-number' out of bounds: 3
Common Lisp
hashing
CL-USER> (let ((list '())
(hash-table (make-hash-table)))
(push 1 list)
(push 2 list)
(push 3 list)
(format t "~S~%" (reverse list))
(setf (gethash 'foo hash-table) 42)
(setf (gethash 'bar hash-table) 69)
(maphash (lambda (key value)
(format t "~S => ~S~%" key value))
hash-table)
;; or print the hash-table in readable form
;; (inplementation-dependent)
(write hash-table :readably t)
;; or describe it
(describe hash-table)
;; describe the list as well
(describe list))
;; FORMAT on a list
(1 2 3)
;; FORMAT on a hash-table
FOO => 42
BAR => 69
;; WRITE :readably t on a hash-table
#.(SB-IMPL::%STUFF-HASH-TABLE
(MAKE-HASH-TABLE :TEST 'EQL :SIZE '16 :REHASH-SIZE '1.5
:REHASH-THRESHOLD '1.0 :WEAKNESS 'NIL)
'((BAR . 69) (FOO . 42)))
;; DESCRIBE on a hash-table
#<HASH-TABLE :TEST EQL :COUNT 2 {1002B6F391}>
[hash-table]
Occupancy: 0.1
Rehash-threshold: 1.0
Rehash-size: 1.5
Size: 16
Synchronized: no
;; DESCRIBE on a list
(3 2 1)
[list]
; No value
deque
In Lisp, a deque can be represented using two list variables which are understood to be opposite to each other. That is to say, the list links (cons cell cdr pointers) go inward into the deque from both ends. For instance the deque (1 2 3 4 5 6) can be represented using (1 2 3) and (6 5 4). Then, it is easy to push items on either end using ordinary list push operations. Popping is also simple, except when the case occurs that either piece runs out of items. A Lisp macro can be provided which takes care of this situation. The implementation below handles the underflow in one deque piece by transferring about one half of the elements from the opposite piece. This keeps the amortized cost for pushes and pops O(1), and prevents the degenerate behavior of bouncing all the elements from one side to the other when pops are requested which alternate between the two ends of the deque.
;;; Obtained from Usenet,
;;; Message-ID: <b3b1cc90-2e2b-43c3-b7d9-785ae29870e7@e23g2000prf.googlegroups.com>
;;; Posting by Kaz Kylheku, February 28, 2008.
(eval-when (:compile-toplevel :load-toplevel :execute)
(defun bisect-list (list &optional (minimum-length 0))
(do ((double-skipper (cddr list) (cddr double-skipper))
(single-skipper list (cdr single-skipper))
(length 2 (+ length (if (cdr double-skipper) 2 1))))
((null double-skipper)
(cond
((< length minimum-length)
(values list nil))
((consp single-skipper)
(multiple-value-prog1
(values list (cdr single-skipper))
(setf (cdr single-skipper) nil)))
(t (values list nil))))))
(defun pop-deque-helper (facing-piece other-piece)
(if (null facing-piece)
(multiple-value-bind (head tail) (bisect-list other-piece 10)
(let ((remaining (if tail head))
(moved (nreverse (or tail head))))
(values (first moved) (rest moved) remaining)))
(values (first facing-piece) (rest facing-piece) other-piece))))
(defmacro pop-deque (facing-piece other-piece)
(let ((result (gensym))
(new-facing (gensym))
(new-other (gensym)))
`(multiple-value-bind (,result ,new-facing ,new-other)
(pop-deque-helper ,facing-piece ,other-piece)
(psetf ,facing-piece ,new-facing
,other-piece ,new-other)
,result)))
Demo:
[1]> (defvar *front* nil) *FRONT* [2]> (defvar *back* nil) *BACK* [3]> (push 1 *front*) (1) [4]> (push 2 *front*) (2 1) [5]> (push 5 *back*) (5) [6]> (push 6 *back*) (6 5) [7]> (append *front* (reverse *back*)) ;; display the deque! (2 1 5 6) [8]> (pop-deque *front* *back*) 2 [9]> (append *front* (reverse *back*)) ;; display the deque! (1 5 6) [10]> (pop-deque *back* *front*) 6 [11]> (append *front* (reverse *back*)) ;; display the deque! (1 5) [12]> (pop-deque *back* *front*) 5 [13]> (append *front* (reverse *back*)) ;; display the deque! (1) [14]> *front* (1) [15]> *back* NIL [16]> (pop-deque *back* *front*) 1 [17]> *front* NIL [18]> *back* NIL
D
D has static arrays.
int[3] array;
array[0] = 5;
// array.length = 4; // compile-time error
D has dynamic arrays.
int[] array;
array ~= 5; // append 5
array.length = 3;
array[3] = 17; // runtime error: out of bounds. check removed in release mode.
array = [2, 17, 3];
writefln(array.sort); // 2, 3, 17
D has associative arrays.
int[int] array;
// array ~= 5; // it doesn't work that way!
array[5] = 17;
array[6] = 20;
// prints "[5, 6]" -> "[17, 20]" - although the order is not specified.
writefln(array.keys, " -> ", array.values);
assert(5 in array); // returns a pointer, by the way
if (auto ptr = 6 in array) writefln(*ptr); // 20
Delphi
Arrays
Arrays are collection of values with memory self managed, can be static (size fixed and index not need start in zero) or dynamic (size scaled by user in run time and away start index in zero).
// Creates and initializes a new integer Array
var
// Dynamics arrays can be initialized, if it's global variable in declaration scope
intArray: TArray<Integer> = [1, 2, 3, 4, 5];
intArray2: array of Integer = [1, 2, 3, 4, 5];
//Cann't initialize statics arrays in declaration scope
intArray3: array [0..4]of Integer;
intArray4: array [10..14]of Integer;
procedure
var
// Any arrays can't be initialized, if it's local variable in declaration scope
intArray5: TArray<Integer>;
begin
// Dynamics arrays can be full assigned in routine scope
intArray := [1,2,3];
intArray2 := [1,2,3];
// Dynamics arrays zero-based
intArray[0] := 1;
// Dynamics arrays must set size, if it not was initialized before
SetLength(intArray,5);
// Inline dynamics arrays can be created and initialized routine scope
// only for version after 10.3 Tokyo
var intArray6 := [1, 2, 3];
var intArray7: TArray<Integer> := [1, 2, 3];
end;
List
Lists are objects and need be release from memory after use.
var
// TLists can't be initialized or created in declaration scope
List1, List2:TList<Integer>;
begin
List1 := TList<Integer>.Create;
List1.Add(1);
list1.AddRange([2, 3]);
List1.free;
// TList can be initialized using a class derivative from TEnumerable, like it self
List1 := TList<Integer>.Create;
list1.AddRange([1,2, 3]);
List2 := TList<Integer>.Create(list1);
Writeln(List2[2]); // 3
List1.free;
List2.free;
// Inline TList can be created in routine scope
// only for version after 10.3 Tokyo
var List3:= TList<Integer>.Create;
List3.Add(2);
List3.free;
var List4: TList<Integer>:= TList<Integer>.Create;
List4.free;
end;
Dictionary
TDictionary is a generic class.It represents a collection of key/value pairs. Keys must be unique. It need be release from memory after use.
var
// TDictionary can't be initialized or created in declaration scope
Dic1: TDictionary<string, Integer>;
begin
Dic1 := TDictionary<string, Integer>.Create;
Dic1.Add('one',1);
Dic1.free;
// Inline TDictionary can be created in routine scope
// only for version after 10.3 Tokyo
var Dic2:= TDictionary<string, Integer>.Create;
Dic2.Add('one',1);
Dic2.free;
var Dic3: TDictionary<string, Integer>:= TDictionary<string, Integer>.Create.Create;
Dic3.Add('one',1);
Dic3.free;
end;
Queue
TQueue is a generic class.It represents a collection of data, stored in fist-in fist-out mode. It need be release from memory after use.
var
Queue1, Queue2: TQueue<Integer>;
List1:TList<Integer>;
begin
Queue1 := TQueue<Integer>.Create;
Queue1.Enqueue(1);
Queue1.Enqueue(2);
Writeln(Queue1.Dequeue); // 1
Writeln(Queue1.Dequeue); // 2
Queue1.free;
// TQueue can be initialized using a class derivative from TEnumerable, like TList<T>
List1 := TList<Integer>.Create;
List1.Add(3);
Queue2:= TQueue<Integer>.Create(List1);
Writeln(Queue2.Dequeue); // 3
List1.free;
Queue2.free;
// Inline TQueue can be created in routine scope
// only for version after 10.3 Tokyo
var Queue3 := TQueue<Integer>.Create;
Queue3.free;
end;
Stack
TStack is a generic class.It represents a collection of data, stored in last-in first-out mode. It need be release from memory after use.
var
Stack1, Stack2: TStack<Integer>;
List1:TList<Integer>;
begin
Stack1:= TStack<Integer>.Create;
Stack1.Push(1);
Stack1.Push(2);
Writeln(Stack1.Pop); // 2
Writeln(Stack1.Pop); // 1
Stack1.free;
// TStack can be initialized using a class derivative from TEnumerable, like TList<T>
List1 := TList<Integer>.Create;
List1.Add(3);
Stack2:= TStack<Integer>.Create(List1);
Writeln(Stack2.Pop); // 3
List1.free;
Stack2.free;
// Inline TStack can be created in routine scope
// only for version after 10.3 Tokyo
var Stack3:= TStack<Integer>.Create;
Stack3.free;
end;
Strings
String are array of chars, start index is one (not zero like almost languages). Can store ansichar (one byte char) or widechar (two bytes char), the default for newer versions is widestring;
var
Str1:String; // default WideString
Str2:WideString;
Str3:UnicodeString;
Str4:AnsiString;
Str5: PChar; //PWideChar is the same
Str6: PAnsiChar;
// Strings can be initialized, if it's global variable in declaration scope
Str4: string = 'orange';
begin
Str1 := 'apple';
// WideString and AnsiString can be converted implicitly, but in some times can lost information about char
Str4 := Str1;
// PChar is a poiter to string (WideString), must be converted using type cast
Str5 := Pchar(Str1);
// PChar not must type cast to convert back string
Str2 := Str5;
//In any string, index start in 1 and end on length of string
Writeln(Str1[1]); // 'a'
Writeln(Str1[5]); // 'e'
Writeln(Str1[length(str1)]); // the same above
end;
See #Pascal for more info.
Diego
Diego operates in the real and abstract world. In the real world, collections exist as scalars, vectors, abilities, specifications, inventories, and, non-fungible tokens:
use_namespace(rosettacode)_me();
// Real world collections
with_route(wp1-wp2)_scalar(wp1wp2Distance)_distan({m},32); // simple distance scalar
// Three dimensional vector (displacement - orientation (via quaternion) - energy consumption)
with_route(from-wp1-to-wp2)_vector(wp1Towp2Displacement)_distan({m},32)_orientatout(0.98,0.174i,0.044j,0.087k)_ergconsump({kJ},35.483);
with_robot(alif)_sensor(frontCamera)_type(camera_3d);
with_robot(alif)_abilit(frontalVision)_of[frontCamera]; // ability (1-dimensional)
with_robot(alif)_sensor(rearCamera)_type(camera_3d);
with_robot(alif)_spec(vision)_of([frontCamera],[rearCamera]); // specification (2-dimensional)
// Inventory of wheels of robot 'alif'
with_robot(alif)_invent(wheels)_compon(frontLeftWheel, frontRightWheel, rearLeftWheel, rearRightWheel)_type(wheel);
// Non-fungible token (blockchained) of robot photo (default ledger)
with_robot(beh)_camera(frontCamera)_snap(74827222-32232-22)
add_nft()_[]_chain(block);
;
// Non-fungible token (crosschained) of robot photo (default ledger)
with_robot(beh)_camera(frontCamera)_snap(74827222-32232-42)
add_nft()_[]_chain(cross);
;
reset_ns[];In the abstract world, collections exist as variables, stacks, queues, arrays, matricies, clumps, lists, dictionaries, and, hashes:
use_namespace(rosettacode)_me();
// Abstract world collections
add_var({int},wp1wp2Distance)_value(32); // variable
add_stack({int},intStack)_values(1,2,3,6,7,9); // stack
add_queue({double},intStack)_values(0.03,0.04,0.05,0.06,0.07,0.08); // queue
add_ary({str},citrusFruit)_values(lime,orange,lemon); // array
add_matrix()_subs(4,4)_identity(); // simple identity matrix
// rotation matrix
add_matrix(wp1Towp2DisplacementRotationMatrix)_row(0.981,-0.155,0.116)_row(0.186,0.924,-0.333)_row(-0.055,0.349,0.936);
add_clump()_subs(5,3,2,1); // simple clump (zero'ed)
// list (of robots) from abstract robot objects
add_list({robot},robots)_values([alif],[bah],[tah],[thah],[jim]);
// list (of robots) from SQL query
add_list({robot},robots)_sql(SELECT id, name, type FROM tbl_robot)_as(dba_admin);
// dictionary
add_dict(tanzanianBanknoteWidths)_keys(500,1000,2000,5000,10000)_values(120,125,130,135,140);
// hash of two images loaded from URIs
add_hash()_ary()_values()_img()_load(/img_027454322.jpg)_img()_load(/img_027454323.jpg);
reset_ns[];DuckDB
Apart from tables and strings, DuckDB supports these collection types: named and unnamed STRUCTs, MAPs, lists, fixed-size arrays, and JSON objects.
The ability to specify the UNIQUE constraint on a column in a table makes columns a natural choice for representing sets, especially for large sets if checking for membership in the set requires indexing for efficiency. Checking for the equality of two sets represented by two columns is also possible, e.g. using the built-in function array_agg() in conjunction with the other functions listed in the subsection on `Sets represented as Lists` below.
Strings, that is, entities of type VARCHAR, can also be viewed as an array of characters via the str_split() function, so we will not consider them further here.
Since DuckDB ensures the distinctness of the keys of JSON objects, of named STRUCTs, and of MAPs, sets in the sense of an unordered collection of distinct entities can be directly represented by any of these, though each has its own drawbacks and limitations. For example, the keys of JSON objects must be strings. Furthermore, the equality operator `=` simply does not have set-theoretic semantics for any DuckDB type. However, the equality operator when applied to sorted lists with distinct elements has set semantics, and thus we turn attention to such lists in the following subsection.
Sorted lists of distinct entities
DuckDB lists can be used to represent sets, but not without complications regarding ordering and distinctness. In practice, however, the availability of the functions list_distinct(), array_sort() and array_contains() means that sets can be conveniently represented as DuckDB lists. In this context, DuckDB's support for column constraints (`CHECK`) is relevant.
Consider therefore the following DuckDB collection of functions, followed by a transcript wherein "D " signifies the DuckDB prompt:
create or replace function toset(l) as
array_sort(list_distinct(l));
create or replace function array_intersection(a,b) as
array_filter(a, x -> array_contains(b, x));
create or replace function set_union(a,b) as
toset(toset(a) || toset(b)));
create or replace function set_intersection(a,b) as
array_intersection(toset(a),toset(b));
Transcript
# Use column constraints to enforce uniqueness and not null: D create or replace table t (l INTEGER[] NOT NULL CHECK (l = array_sort(list_distinct(l)))); D insert into t values ([1,2]); D insert into t values ([1,2,1]); Constraint Error: CHECK constraint failed: t D select array_contains(l, 1) from t; ββββββββββββββββββββββββ β array_contains(l, 1) β β boolean β ββββββββββββββββββββββββ€ β true β ββββββββββββββββββββββββ # After installing the above-defined functions: # Add the value 4 to a set D select toset([1,2] || [4]) as set; βββββββββββββ β set β β int32[] β βββββββββββββ€ β [1, 2, 4] β βββββββββββββ D select [1,2] as s1, [0, 1, 3] as s2, set_union(s1, s2) as union; βββββββββββ¬ββββββββββββ¬βββββββββββββββ β s1 β s2 β union β β int32[] β int32[] β int32[] β βββββββββββΌββββββββββββΌβββββββββββββββ€ β [1, 2] β [0, 1, 3] β [0, 1, 2, 3] β βββββββββββ΄ββββββββββββ΄βββββββββββββββ # Add 10 to the set in table t: D UPDATE t SET l = set_union(l, [10]); D from t; ββββββββββββββ β l β β int32[] β ββββββββββββββ€ β [1, 2, 10] β ββββββββββββββ
E
E has both mutable and immutable builtin collections; the common types are list (array), map (hash table), and set (hash table). This interactive session shows mutable lists and immutable collections of all three types. See also Arrays#E.
? def constList := [1,2,3,4,5]
# value: [1, 2, 3, 4, 5]
? constList.with(6)
# value: [1, 2, 3, 4, 5, 6]
? def flexList := constList.diverge()
# value: [1, 2, 3, 4, 5].diverge()
? flexList.push(6)
? flexList
# value: [1, 2, 3, 4, 5, 6].diverge()
? constList
# value: [1, 2, 3, 4, 5]
? def constMap := [1 => 2, 3 => 4]
# value: [1 => 2, 3 => 4]
? constMap[1]
# value: 2
? def constSet := [1, 2, 3, 2].asSet()
# value: [1, 2, 3].asSet()
? constSet.contains(3)
# value: trueEasyLang
EasyLang only has an array as the type of collection. Arrays can be put inside of arrays. All arrays are mutable.
array[] &= 1
array[] &= 2
array[] &= 3
arrayArray[][] &= [ 1 2 ]
arrayArray[][] &= [ 3 4 ]
arrayArray[][] &= [ 5 6 ]
print array[]
print arrayArray[][]- Output:
[ 1 2 3 ] [ [ 1 2 ] [ 3 4 ] [ 5 6 ] ]
EchoLisp
The collection will be a list, which is not unusual in EchoLisp. We add items - symbols - to the collection, and save it to local storage.
(define my-collection ' ( π± βοΈ βοΈ ))
(set! my-collection (cons 'π₯ my-collection))
(set! my-collection (cons 'π§ my-collection))
my-collection
β (π§ π₯ π± βοΈ βοΈ)
;; save it
(local-put 'my-collection)
β my-collection
Elena
ELENA 5.0:
Arrays
// Weak array
var stringArr := Array.allocate(5);
stringArr[0] := "string";
// initialized array
var intArray := new int[]{1, 2, 3, 4, 5};ArrayList and List
//Create and initialize ArrayList
var myAl := new system'collections'ArrayList().append("Hello").append("World").append("!");
//Create and initialize List
var myList := new system'collections'List().append("Hello").append("World").append("!");Dictionary
//Create a dictionary
var dict := system'collections'Dictionary.new();
dict["Hello"] := "World";
dict["Key"] := "Value";Elixir
Elixir data types are immutable. The data contents aren't changed but can get changed new data. Indexes start from zero ( It is different from Erlang ).
List
Elixir uses square brackets to specify a list of values. Values can be of any type:
empty_list = []
list = [1,2,3,4,5]
length(list) #=> 5
[0 | list] #=> [0,1,2,3,4,5]
hd(list) #=> 1
tl(list) #=> [2,3,4,5]
Enum.at(list,3) #=> 4
list ++ [6,7] #=> [1,2,3,4,5,6,7]
list -- [4,2] #=> [1,3,5]
Tuple
Elixir uses curly brackets to define tuples. Like lists, tuples can hold any value: Tuples store elements contiguously in memory. This means accessing a tuple element per index or getting the tuple size is a fast operation:
empty_tuple = {} #=> {}
tuple = {0,1,2,3,4} #=> {0, 1, 2, 3, 4}
tuple_size(tuple) #=> 5
elem(tuple, 2) #=> 2
put_elem(tuple,3,:atom) #=> {0, 1, 2, :atom, 4}
Keyword lists
In Elixir, when we have a list of tuples and the first item of the tuple (i.e. the key) is an atom, we call it a keyword list:
list = [{:a,1},{:b,2}] #=> [a: 1, b: 2]
list == [a: 1, b: 2] #=> true
list[:a] #=> 1
list ++ [c: 3, a: 5] #=> [a: 1, b: 2, c: 3, a: 5]
Keyword lists are important because they have two special characteristics:
- They keep the keys ordered, as specified by the developer.
- They allow a key to be given more than once.
Map
Whenever you need a key-value store, maps are the βgo toβ data structure in Elixir.
Compared to keyword lists, we can already see two differences:
- Maps allow any value as a key.
- Maps' keys do not follow any ordering.
empty_map = Map.new #=> %{}
kwlist = [x: 1, y: 2] # Key Word List
Map.new(kwlist) #=> %{x: 1, y: 2}
Map.new([{1,"A"}, {2,"B"}]) #=> %{1 => "A", 2 => "B"}
map = %{:a => 1, 2 => :b} #=> %{2 => :b, :a => 1}
map[:a] #=> 1
map[2] #=> :b
# If you pass duplicate keys when creating a map, the last one wins:
%{1 => 1, 1 => 2} #=> %{1 => 2}
# When all the keys in a map are atoms, you can use the keyword syntax for convenience:
map = %{:a => 1, :b => 2} #=> %{a: 1, b: 2}
map.a #=> 1
%{map | :a => 2} #=> %{a: 2, b: 2} update only
Set
empty_set = MapSet.new #=> #MapSet<[]>
set1 = MapSet.new(1..4) #=> #MapSet<[1, 2, 3, 4]>
MapSet.size(set1) #=> 4
MapSet.member?(set1,3) #=> true
MapSet.put(set1,9) #=> #MapSet<[1, 2, 3, 4, 9]>
set2 = MapSet.new([6,4,2,0]) #=> #MapSet<[0, 2, 4, 6]>
MapSet.union(set1,set2) #=> #MapSet<[0, 1, 2, 3, 4, 6]>
MapSet.intersection(set1,set2) #=> #MapSet<[2, 4]>
MapSet.difference(set1,set2) #=> #MapSet<[1, 3]>
MapSet.subset?(set1,set2) #=> false
Struct
Structs are extensions built on top of maps that provide compile-time checks and default values.
defmodule User do
defstruct name: "john", age: 27
end
john = %User{} #=> %User{age: 27, name: "john"}
john.name #=> "john"
%User{age: age} = john # pattern matching
age #=> 27
meg = %User{name: "meg"} #=> %User{age: 27, name: "meg"}
is_map(meg) #=> true
Factor
USING: assocs deques dlists lists lists.lazy sequences sets ;
! ===fixed-size sequences===
{ 1 2 "foo" 3 } ! array
[ 1 2 3 + * ] ! quotation
"Hello, world!" ! string
B{ 1 2 3 } ! byte array
?{ f t t } ! bit array
! Add an element to a fixed-size sequence
{ 1 2 3 } 4 suffix ! { 1 2 3 4 }
! Append a sequence to a fixed-size sequence
{ 1 2 3 } { 4 5 6 } append ! { 1 2 3 4 5 6 }
! Sequences are sets
{ 1 1 2 3 } { 2 5 7 8 } intersect ! { 2 }
! Strings are just arrays of code points
"Hello" { } like ! { 72 101 108 108 111 }
{ 72 101 108 108 111 } "" like ! "Hello"
! ===resizable sequences===
V{ 1 2 "foo" 3 } ! vector
BV{ 1 2 255 } ! byte vector
SBUF" Hello, world!" ! string buffer
! Add an element to a resizable sequence by mutation
V{ 1 2 3 } 4 suffix! ! V{ 1 2 3 4 }
! Append a sequence to a resizable sequence by mutation
V{ 1 2 3 } { 4 5 6 } append! ! V{ 1 2 3 4 5 6 }
! Sequences are stacks
V{ 1 2 3 } pop ! 3
! ===associative mappings===
{ { "hamburger" 150 } { "soda" 99 } { "fries" 99 } } ! alist
H{ { 1 "a" } { 2 "b" } } ! hash table
! Add a key-value pair to an assoc
3 "c" H{ { 1 "a" } { 2 "b" } } [ set-at ] keep
! H{ { 1 "a" } { 2 "b" } { "c" 3 } }
! ===linked lists===
T{ cons-state f 1 +nil+ } ! literal list syntax
T{ cons-state { car 1 } { cdr +nil+ } } ! literal list syntax
! with car 1 and cdr nil
! One method of manually constructing a list
1 2 3 4 +nil+ cons cons cons cons
1 2 2list ! convenience word for list construction
! T{ cons-state
! { car 1 }
! { cdr T{ cons-state { car 2 } { cdr +nil+ } } }
! }
{ 1 2 3 4 } sequence>list ! make a list from a sequence
0 lfrom ! a lazy list from 0 to infinity
0 [ 2 + ] lfrom-by ! a lazy list of all even numbers >= 0.
DL{ 1 2 3 } ! double linked list / deque
3 DL{ 1 2 } [ push-front ] keep ! DL{ 3 1 2 }
3 DL{ 1 2 } [ push-back ] keep ! DL{ 1 2 3 }
! Factor also comes with disjoint sets, interval maps, heaps,
! boxes, directed graphs, locked I/O buffers, trees, and more!
Fancy
array
# creating an empty array and adding values
a = [] # => []
a[0]: 1 # => [1]
a[3]: 2 # => [1, nil, nil, 2]
# creating an array with the constructor
a = Array new # => []
hash
# creating an empty hash
h = <[]> # => <[]>
h["a"]: 1 # => <["a" => 1]>
h["test"]: 2.4 # => <["a" => 1, "test" => 2.4]>
h[3]: "Hello" # => <["a" => 1, "test" => 2.4, 3 => "Hello"]>
# creating a hash with the constructor
h = Hash new # => <[]>
Forth
Array
include ffl/car.fs
10 car-create ar \ create a dynamic array with initial size 10
2 0 ar car-set \ ar[0] = 2
3 1 ar car-set \ ar[1] = 3
1 0 ar car-insert \ ar[0] = 1 ar[1] = 2 ar[2] = 3
Double linked list
include ffl/dcl.fs
dcl-create dl \ create a double linked list
3 dl dcl-append
1 dl dcl-prepend
2 1 dl dcl-insert \ dl[0] = 1 dl[1] = 2 dl[2] = 3
Hashtable
include ffl/hct.fs
10 hct-create ht \ create a hashtable with initial size 10
1 s" one" ht hct-insert \ ht["one"] = 1
2 s" two" ht hct-insert \ ht["two"] = 2
3 s" three" ht hct-insert \ ht["three"] = 3
Fortran
Standard
The only facility for a collection more organised than a collection of separately-named variables (even if with a system for the names) is the array, which is a collection of items of identical type, indexed by an integer only, definitely not by a text as in say Snobol. Thus
REAL A(36) !Declares a one-dimensional array A(1), A(2), ... A(36)
A(1) = 1 !Assigns a value to the first element.
A(2) = 3*A(1) + 5 !The second element gets 8.
With F90 came a large expansion in the facilities for manipulating arrays. They can now have any lower bound, as in REAL A(-6:+12) and their size can be defined at run time, not just compile time. Further, programmer-defined data aggregates can be defined via the TYPE statement, and arrays of such types can be manipulated. However, type-matching remains rigid: all elements of an array must be of the same type. So,
TYPE(MIXED) !Name the "type".
INTEGER COUNTER !Its content is listed.
REAL WEIGHT,DEPTH
CHARACTER*28 MARKNAME
COMPLEX PATH(6) !The mixed collection includes an array.
END TYPE MIXED
TYPE(MIXED) TEMP,A(6) !Declare some items of that type.
would define a collection of variables constituting a "type", then a simple variable TEMP whose parts would be accessed via the likes of TEMP.DEPTH or TEMP%DEPTH, and an array of such aggregates where A(3).PATH(1) = (2.7,3.1) assigns a complex number to the first step of the PATH of the third element of array A. The indexing must be associated with the item having an array aspect, but in pl/i A.PATH(3,1) - or other groupings - would be acceptable.
There is a sense in which the CHARACTER type is flexible, in that multiple and different types can be represented as texts so that "Pi, 3.14159, 4*atan(1)" might be considered a collection of three items (yet be contained in one, possibly large variable) and be processed in various ways, or one might prepare a battery of variables and arrays referring to each other and disc files in such a way as to present a database containing a collection of information.
Coarray
Fortran normally uses only ( ) with no appeal to {[ ]} usage even for complex formulae. The co-array concept of the 1990s that was standardised in F2008 extends the syntax to use [k] to specify the k'th "image" executing in parallel. Loosely, if X is a variable, manipulated as in normal statements, a reference to X[3] would be to that X value held by the third running "image", while X would be in each image a reference to that image's own X value. In other words, there is a collection of X variables.
FreeBASIC
Although it's possible to build any type of collection (vectors, linked lists, stacks, queues, hashtables etc.) using FreeBASIC's object oriented features, the only collection type which is built into the language is the array.
This can be fixed size or dynamic, have arbitrary lower and upper bounds, have up to 8 dimensions and any kind of element type (including user defined types). Here are some simple examples:
' FB 1.05.0 Win64
'create fixed size array of integers
Dim a(1 To 5) As Integer = {1, 2, 3, 4, 5}
Print a(2), a(4)
'create empty dynamic array of doubles
Dim b() As Double
' add two elements by first redimensioning the array to hold this number of elements
Redim b(0 To 1)
b(0) = 3.5 : b(1) = 7.1
Print b(0), b(1)
'create 2 dimensional fixed size array of bytes
Dim c(1 To 2, 1 To 2) As Byte = {{1, 2}, {3, 4}}
Print c(1, 1), c(2,2)
Sleep
- Output:
2 4 3.5 7.1 1 4
FutureBasic
include "NSLog.incl"
void local fn Array
CFArrayRef array = @[@"Alpha",@"Bravo",@"Charlie",@"Delta"]
NSLog(@"Array:%@\n",array)
end fn
void local fn Dictionary
CFDictionaryRef dict = @{@"Key1":@"Value1",@"Key2":@"Value2",@"Key3":@"Value3"}
NSLog(@"Dictionary:%@\n",dict)
end fn
void local fn Set
CFSetRef set = fn SetWithArray( @[@"Echo",@"Echo",@"FutureBasic",@"Golf",@"Hotel",@"India"] )
NSLog(@"Set:%@\n",set)
end fn
void local fn IndexPath
long indexes(3)
indexes(0) = 1 : indexes(1) = 4 : indexes(2) = 3 : indexes(3) = 2
IndexPathRef indexPath = fn IndexPathWithIndexes( @indexes(0), 4 )
NSLog(@"IndexPath:%@\n",indexPath)
end fn
void local fn IndexSet
IndexSetRef indexSet = fn IndexSetWithIndexesInRange( fn CFRangeMake( 12, 5 ) )
NSLog(@"IndexSet:%@\n",indexSet)
end fn
void local fn CountedSet
CountedSetRef countedSet = fn CountedSetWithArray( @[@"Juliet",@"Lima",@"Mike",@"Lima",@"Kilo",@"Lima",@"Juliet",@"Mike",@"Lima"] )
NSLog(@"CountedSet:%@\n",countedSet)
end fn
void local fn OrderedSet
OrderedSetRef orderedSet = fn OrderedSetWithObjects( @"November", @"Oscar", @"Papa", NULL )
NSLog(@"OrderedSet:%@\n",orderedSet)
end fn
fn Array
fn Dictionary
fn Set
fn IndexPath
fn IndexSet
fn CountedSet
fn OrderedSet
HandleEvents- Output:
Array:(
Alpha,
Bravo,
Charlie,
Delta
)
Dictionary:{
Key1 = Value1;
Key2 = Value2;
Key3 = Value3;
}
Set:{(
India,
Echo,
Hotel,
FutureBasic,
Golf
)}
IndexPath:<NSIndexPath: 0x93855b96cef033ba> {length = 4, path = 1 - 4 - 3 - 2}
IndexSet:<NSIndexSet: 0x600000318cc0>[number of indexes: 5 (in 1 ranges), indexes: (12-16)]
CountedSet:<NSCountedSet: 0x60000031aa60> (Mike [2], Lima [4], Juliet [2], Kilo [1])
OrderedSet:{(
November,
Oscar,
Papa
)}
Gambas
Click this link to run this code
Public Sub Main()
Dim siCount As Short
Dim cCollection As Collection = ["0": "zero", "1": "one", "2": "two", "3": "three", "4": "four",
"5": "five", "6": "six", "7": "seven", "8": "eight", "9": "nine"]
For siCount = 0 To 9
Print cCollection[Str(siCount)]
Next
End
Output:
zero one two three four five six seven eight nine
Go
Built in, resizable
- Slices
- Maps
Built in resizable collections are slices and maps. The value type for these collections can be any Go type, including interface. An empty interface can reference an object of any type, providing a kind of polymorphic collection. Here the variable a is a slice of interface{} objects.
package main
import "fmt"
func main() {
var a []interface{}
a = append(a, 3)
a = append(a, "apples", "oranges")
fmt.Println(a)
}
- Output:
[3 apples oranges]
Built in, less conventional
- Go has arrays that can be used as collections, but arrays are declared with constant size and cannot be resized.
- Strings are a special case of slice. Strings are immutable and are handled specially in other ways.
- A struct with a number of members might be considered a collection in some sense.
- A buffered channel might be closer to the familiar concept of a collection, as it represents a FIFO queue. Buffered channels have a fixed size and cannot be resized after creation.
Library
- The container directory of the standard library has the packages heap, list, and ring.
- Anything that implements bufio.ReadWriter can be used as a FIFO queue. This includes bytes.Buffer, which makes a useful in-memory collection.
- The sort package also contains search functions which perform a binary search on a sorted collection. For these functions the collection implementation is abstracted through sort.Interface. It is typically a slice, but could be anything that is indexable with an integer index.
Groovy
Lists are just variable-length, integer-indexed arrays.
def emptyList = []
assert emptyList.isEmpty() : "These are not the items you're looking for"
assert emptyList.size() == 0 : "Empty list has size 0"
assert ! emptyList : "Empty list evaluates as boolean 'false'"
def initializedList = [ 1, "b", java.awt.Color.BLUE ]
assert initializedList.size() == 3
assert initializedList : "Non-empty list evaluates as boolean 'true'"
assert initializedList[2] == java.awt.Color.BLUE : "referencing a single element (zero-based indexing)"
assert initializedList[-1] == java.awt.Color.BLUE : "referencing a single element (reverse indexing of last element)"
def combinedList = initializedList + [ "more stuff", "even more stuff" ]
assert combinedList.size() == 5
assert combinedList[1..3] == ["b", java.awt.Color.BLUE, "more stuff"] : "referencing a range of elements"
combinedList << "even more stuff"
assert combinedList.size() == 6
assert combinedList[-1..-3] == \
["even more stuff", "even more stuff", "more stuff"] \
: "reverse referencing last 3 elements"
println ([combinedList: combinedList])
- Output:
[combinedList:[1, b, java.awt.Color[r=0,g=0,b=255], more stuff, even more stuff, even more stuff]]
Maps are just variable-length, associative arrays. They are not necessarily order preserving.
def emptyMap = [:]
assert emptyMap.isEmpty() : "These are not the items you're looking for"
assert emptyMap.size() == 0 : "Empty map has size 0"
assert ! emptyMap : "Empty map evaluates as boolean 'false'"
def initializedMap = [ count: 1, initial: "B", eyes: java.awt.Color.BLUE ]
assert initializedMap.size() == 3
assert initializedMap : "Non-empty map evaluates as boolean 'true'"
assert initializedMap["eyes"] == java.awt.Color.BLUE : "referencing a single element (array syntax)"
assert initializedMap.eyes == java.awt.Color.BLUE : "referencing a single element (member syntax)"
assert initializedMap.height == null : \
"references to non-existant keys generally evaluate to null (implementation dependent)"
def combinedMap = initializedMap \
+ [hair: java.awt.Color.BLACK, birthdate: Date.parse("yyyy-MM-dd", "1960-05-17") ]
assert combinedMap.size() == 5
combinedMap["weight"] = 185 // array syntax
combinedMap.lastName = "Smith" // member syntax
combinedMap << [firstName: "Joe"] // entry syntax
assert combinedMap.size() == 8
assert combinedMap.keySet().containsAll(
["lastName", "count", "eyes", "hair", "weight", "initial", "firstName", "birthdate"])
println ([combinedMap: combinedMap])
- Output:
[combinedMap:[count:1, initial:B, eyes:java.awt.Color[r=0,g=0,b=255], hair:java.awt.Color[r=0,g=0,b=0], birthdate:Tue May 17 00:00:00 CDT 1960, weight:185, lastName:Smith, firstName:Joe]]
Sets are unique, not indexed at all (contents can only be discovered by traversal), and are not necessarily order preserving. There is no particular special language support for denoting a Set, although a Set may be initialized from a List, and Sets share many of the same operations and methods that are available in Lists.
def emptySet = new HashSet()
assert emptySet.isEmpty() : "These are not the items you're looking for"
assert emptySet.size() == 0 : "Empty set has size 0"
assert ! emptySet : "Empty set evaluates as boolean 'false'"
def initializedSet = new HashSet([ 1, "b", java.awt.Color.BLUE ])
assert initializedSet.size() == 3
assert initializedSet : "Non-empty list evaluates as boolean 'true'"
//assert initializedSet[2] == java.awt.Color.BLUE // SYNTAX ERROR!!! No indexing of set elements!
def combinedSet = initializedSet + new HashSet([ "more stuff", "even more stuff" ])
assert combinedSet.size() == 5
combinedSet << "even more stuff"
assert combinedSet.size() == 5 : "No duplicate elements allowed!"
println ([combinedSet: combinedSet])
- Output:
[combinedSet:[1, java.awt.Color[r=0,g=0,b=255], b, even more stuff, more stuff]]
Haskell
Data.List
The list is typically the first collection type to be encountered in textbooks, but other types may tend to be more efficient, or more flexibly accessed; see the Data hierarchy of GHC's standard library. New collection types may be defined with data.
[1, 2, 3, 4, 5]
To prepend a single element to a list, use the : operator:
1 : [2, 3, 4]
To concatenate two lists, use ++:
[1, 2] ++ [3, 4]
To concatenate a whole list of lists, use concat:
concat [[1, 2], [3, 4], [5, 6, 7]]
Data.Array
Faster retrieval by index:
import Data.Array (Array, listArray, Ix, (!))
triples :: Array Int (Char, String, String)
triples =
listArray (0, 11) $
zip3
"ιΌ ηθε
ιΎθ馬ηΎη΄ιΈ‘η豬" -- ηθ shengxiao β symbolic animals
(words "shΗ niΓΊ hΗ tΓΉ lΓ³ng shΓ© mΗ yΓ‘ng hΓ³u jΔ« gΗu zhΕ«")
(words "rat ox tiger rabbit dragon snake horse goat monkey rooster dog pig")
indexedItem
:: Ix i
=> Array i (Char, String, String) -> i -> String
indexedItem a n =
let (c, w, w1) = a ! n
in c : unwords ["\t", w, w1]
main :: IO ()
main = (putStrLn . unlines) $ indexedItem triples <$> [2, 4, 6]
- Output:
θ hΗ tiger ιΎ lΓ³ng dragon 馬 mΗ horse
Data.Map
Flexible key-value indexing and efficient retrieval:
import qualified Data.Map as M
import Data.Maybe (isJust)
mapSample :: M.Map String Int
mapSample =
M.fromList
[ ("alpha", 1)
, ("beta", 2)
, ("gamma", 3)
, ("delta", 4)
, ("epsilon", 5)
, ("zeta", 6)
]
maybeValue :: String -> Maybe Int
maybeValue = flip M.lookup mapSample
main :: IO ()
main =
print $ sequence $ filter isJust (maybeValue <$> ["beta", "delta", "zeta"])
- Output:
Just [2,4,6]
Data.Set
Repertoire of efficient set operations:
import qualified Data.Set as S
setA :: S.Set String
setA = S.fromList ["alpha", "beta", "gamma", "delta", "epsilon"]
setB :: S.Set String
setB = S.fromList ["delta", "epsilon", "zeta", "eta", "theta"]
main :: IO ()
main = (print . S.toList) (S.intersection setA setB)
- Output:
["delta","epsilon"]
Icon and Unicon
Icon and Unicon have a number of different types that could be considered collections. For more information see Introduction to Icon and Unicon on Rosetta - Data Types.
Several data types could be considered collections:
Adding to these collections can be accomplished as follows:
Additionally, the following operations apply:
J
J is an array-oriented language -- it treats all data as collections and processes collections natively. Its built in (primitive) functions are specifically designed to handle collections.
J will, when possible without losing significance of the original value, implicitly convert values to a type which allows them represented in a homogeneous fashion in a collection. Heterogeneous collections are possible via "boxing" (analogous to a "variant" data type).
c =: 0 10 20 30 40 NB. A collection
c, 50 NB. Append 50 to the collection
0 10 20 30 40 50
_20 _10 , c NB. Prepend _20 _10 to the collection
_20 _10 0 10 20 30 40
,~ c NB. Self-append
0 10 20 30 40 0 10 20 30 40
,:~ c NB. Duplicate
0 10 20 30 40
0 10 20 30 40
30 e. c NB. Is 30 in the collection?
1
30 i.~c NB. Where?
3
30 80 e. c NB. Don't change anything to test multiple values -- collections are native.
1 0
2 1 4 2 { c NB. From the collection, give me items two, one, four, and two again.
20 10 40 20
|.c NB. Reverse the collection
40 30 20 10 0
1+c NB. Increment the collection
1 11 21 31 41
c%10 NB. Decimate the collection (divide by 10)
0 1 2 3 4
{. c NB. Give me the first item
0
{: c NB. And the last
40
3{.c NB. Give me the first 3 items
0 10 20
3}.c NB. Throw away the first 3 items
30 40
_3{.c NB. Give me the last 3 items
20 30 40
_3}.c NB. (Guess)
0 10
keys_map_ =: 'one';'two';'three'
vals_map_ =: 'alpha';'beta';'gamma'
lookup_map_ =: a:& $: : (dyad def ' (keys i. y) { vals,x')&boxopen
exists_map_ =: verb def 'y e. keys'&boxopen
exists_map_ 'bad key'
0
exists_map_ 'two';'bad key'
1 0
lookup_map_ 'one'
+-----+
|alpha|
+-----+
lookup_map_ 'three';'one';'two';'one'
+-----+-----+----+-----+
|gamma|alpha|beta|alpha|
+-----+-----+----+-----+
lookup_map_ 'bad key'
++
||
++
'some other default' lookup_map_ 'bad key'
+------------------+
|some other default|
+------------------+
'some other default' lookup_map_ 'two';'bad key'
+----+------------------+
|beta|some other default|
+----+------------------+
+/ c NB. Sum of collection
100
*/ c NB. Product of collection
0
i.5 NB. Generate the first 5 nonnegative integers
0 1 2 3 4
10*i.5 NB. Looks familiar
0 10 20 30 40
c = 10*i.5 NB. Test each for equality
1 1 1 1 1
c -: 10 i.5 NB. Test for identicality
1
Jakt
Array
In Jakt, arrays are of variable size.
fn main() {
mut array: [String] = []
array.push("Apple")
array.push("Banana")
println("{}", array)
}Set
fn main() {
mut set: {String} = {}
set.add("Apple")
set.add("Banana")
println("{}", set)
}Dictionary
fn main() {
mut dictionary: [i64:String] = [:]
dictionary[1] = "Apple"
dictionary[2] = "Banana"
println("{}", dictionary)
}
Java
Native collection library
When creating a List of any kind in Java (Arraylist or LinkedList), the type of the variable is a style choice. It is sometimes considered good practice to make the pointer of type List and the new object of a List subclass. Doing this will ensure two things: if you need to change the type of list you want you only need to change one line and all of your methods will still work, and you will not be able to use any methods that are specific to the List type you chose. So in this example, all instances of "ArrayList" can be changed to "LinkedList" and it will still work, but you will not be able to use a method like "ensureCapactiy()" because the variable is of type List.
List arrayList = new ArrayList();
arrayList.add(new Integer(0));
// alternative with primitive autoboxed to an Integer object automatically
arrayList.add(0);
//other features of ArrayList
//define the type in the arraylist, you can substitute a proprietary class in the "<>"
List<Integer> myarrlist = new ArrayList<Integer>();
//add several values to the arraylist to be summed later
int sum;
for(int i = 0; i < 10; i++) {
myarrlist.add(i);
}
//loop through myarrlist to sum each entry
for ( i = 0; i < myarrlist.size(); i++) {
sum += myarrlist.get(i);
}
or
for(int i : myarrlist) {
sum += i;
}
//remove the last entry in the ArrayList
myarrlist.remove(myarrlist.size()-1)
//clear the ArrayList
myarrlist.clear();
Here is a reference table for characteristics of commonly used Collections classes:
| Collection class | random access | order | iterator direction |
|---|---|---|---|
| HashMap | by key | hash | forward (separate iterators for entries, keys and values) |
| TreeMap | by key | ascending(key) | forward (separate iterators for entries, keys and values) |
| LinkedHashMap | by key | insertion | forward (separate iterators for entries, keys and values) |
| LinkedList | by index | insertion/to index | both |
| ArrayList | by index | insertion/to index (ArrayList also has a defined but expandable size) | both |
| HashSet | only remove (returns the element that was removed) | hash | forward |
| TreeSet | only remove (returns the element that was removed) | ascending(element) | forward |
Using the Scala collection classes
The Scala libraries are valid Java byte-code libraries. The collection part of these are rich because the multiple inheritance by traits. E.g. an ArrayBuffer has properties inherent of 9 traits such as Buffer[A], IndexedSeqOptimized[A, ArrayBuffer[A]], Builder[A, ArrayBuffer[A]], ResizableArray[A] and Serializable. Another collection e.g. TrieMap uses some of these and other added traits. A TrieMap -a hashmap- is the most advanced of all. It supports parallel processing without blocking.
import scala.Tuple2;
import scala.collection.concurrent.TrieMap;
import scala.collection.immutable.HashSet;
import scala.collection.mutable.ArrayBuffer;
public class Collections {
public static void main(String[] args) {
ArrayBuffer<Integer> myarrlist = new ArrayBuffer<Integer>();
ArrayBuffer<Integer> myarrlist2 = new ArrayBuffer<Integer>(20);
myarrlist.$plus$eq(new Integer(42)); // $plus$eq is Scala += operator
myarrlist.$plus$eq(13); // to add an element.
myarrlist.$plus$eq(-1);
myarrlist2 = (ArrayBuffer<Integer>) myarrlist2.$minus(-1);
for (int i = 0; i < 10; i++)
myarrlist2.$plus$eq(i);
// loop through myarrlist to sum each entry
int sum = 0;
for (int i = 0; i < myarrlist2.size(); i++) {
sum += myarrlist2.apply(i);
}
System.out.println("List is: " + myarrlist2 + " with head: "
+ myarrlist2.head() + " sum is: " + sum);
System.out.println("Third element is: " + myarrlist2.apply$mcII$sp(2));
Tuple2<String, String> tuple = new Tuple2<String, String>("US",
"Washington");
System.out.println("Tuple2 is : " + tuple);
ArrayBuffer<Tuple2<String, String>> capList = new ArrayBuffer<Tuple2<String, String>>();
capList.$plus$eq(new Tuple2<String, String>("US", "Washington"));
capList.$plus$eq(new Tuple2<String, String>("France", "Paris"));
System.out.println(capList);
TrieMap<String, String> trieMap = new TrieMap<String, String>();
trieMap.put("US", "Washington");
trieMap.put("France", "Paris");
HashSet<Character> set = new HashSet<Character>();
ArrayBuffer<Tuple2<String, String>> capBuffer = new ArrayBuffer<Tuple2<String, String>>();
trieMap.put("US", "Washington");
System.out.println(trieMap);
}
}
JavaScript
var array = [];
array.push('abc');
array.push(123);
array.push(new MyClass);
console.log( array[2] );
var obj = {};
obj['foo'] = 'xyz'; //equivalent to: obj.foo = 'xyz';
obj['bar'] = new MyClass; //equivalent to: obj.bar = new MyClass;
obj['1x; ~~:-b'] = 'text'; //no equivalent
console.log(obj['1x; ~~:-b']);
jq
jq has three native collection types: JSON objects (implemented as hash tables over strings), arrays (with index origin equal to 0), and JSON strings. Since strings in jq can be thought of as arrays of codepoints, this article will focus on objects and arrays.
Creation
Collections can be created using JSON syntax (e.g. {"a":1}) or programmatically (e.g. {} | .a = 1). One of the programmatic approaches to creating JSON objects allows the key names to be specified as unquoted strings, e.g.
{"a": 1} == {a: 1}evaluates to true. Variables can also be used, e.g. the object {"a":1} can also be created by the following pipeline:
"a" as $key | 1 as $value | {($key): $value}Equality
Two arrays are equal if and only if their lengths and respective elements are equal. Two objects are equal if and only if they have the same keys and if the values at corresponding keys are equal. Note that expressions with repeated keys are regarded as programmatic expressions: e.g. {"a":1, "a":2} is regarded as shorthand for {"a":1} + {"a":2}, which evaluates to {"a":2}. That is, "{"a":1, "a":2}" should be regarded as an expression that evaluates to a JSON object.
Immutability
Semantically, all jq data types are immutable, but it is often convenient to speak about modifying an element of a composite structure. For example, consider the following pipeline:
[0,1,2] | .[0] = 10The result (or output) of this sequence is [10,1,2], so it is convenient to speak of the operation ".[0] = 10" as simply a filter that sets the element at 0 to 10.
Julia
Julia has a wide variety of collections, including vectors, matrices, lists of Any data type, associative arrays, and bitsets. There is a slicing notation and list comprehensions similar to those in Python, but the base index is by default 1, not 0. In Julia, a collection is a just variable length array:
julia> collection = []
0-element Array{Any,1}
julia> push!(collection, 1,2,4,7)
4-element Array{Any,1}:
1
2
4
7
Kotlin
Apart from arrays whose length is immutable but content mutable, Kotlin distinguishes between mutable and immutable collection types in its standard library. Examples of each are given below. Where possible, the type parameter(s) of generic collection types are inferred from the content.
In addition, Kotlin can also access other types of Java collection such as LinkedList, Queue, Deque and Stack by simply importing the appropriate type:
import java.util.PriorityQueue
fun main(args: Array<String>) {
// generic array
val ga = arrayOf(1, 2, 3)
println(ga.joinToString(prefix = "[", postfix = "]"))
// specialized array (one for each primitive type)
val da = doubleArrayOf(4.0, 5.0, 6.0)
println(da.joinToString(prefix = "[", postfix = "]"))
// immutable list
val li = listOf<Byte>(7, 8, 9)
println(li)
// mutable list
val ml = mutableListOf<Short>()
ml.add(10); ml.add(11); ml.add(12)
println(ml)
// immutable map
val hm = mapOf('a' to 97, 'b' to 98, 'c' to 99)
println(hm)
// mutable map
val mm = mutableMapOf<Char, Int>()
mm.put('d', 100); mm.put('e', 101); mm.put('f', 102)
println(mm)
// immutable set (duplicates not allowed)
val se = setOf(1, 2, 3)
println(se)
// mutable set (duplicates not allowed)
val ms = mutableSetOf<Long>()
ms.add(4L); ms.add(5L); ms.add(6L)
println(ms)
// priority queue (imported from Java)
val pq = PriorityQueue<String>()
pq.add("First"); pq.add("Second"); pq.add("Third")
println(pq)
}
- Output:
[1, 2, 3]
[4.0, 5.0, 6.0]
[7, 8, 9]
[10, 11, 12]
{a=97, b=98, c=99}
{d=100, e=101, f=102}
[1, 2, 3]
[4, 5, 6]
[First, Second, Third]
Lingo
Lingo has 2 collection types: lists (arrays) and property lists (hashes):
-- list stuff
l = [1, 2]
l.add(3)
l.add(4)
put l
-- [1, 2, 3, 4]
-- property list stuff
pl = [#foo: 1, #bar: 2]
pl[#foobar] = 3
pl["barfoo"] = 4
put pl
-- [#foo: 1, #bar: 2, #foobar: 3, "barfoo": 4]Lingo is not statically-typed, but if needed, a collection type that only accepts a specific data type can be created by sub-classing one of the 2 available collection types and overwriting its access methods, so that those block any data type other than the one that was passed to the constructor.
Lisaac
vector
+ vector : ARRAY[INTEGER];
vector := ARRAY[INTEGER].create_with_capacity 32 lower 0;
vector.add_last 1;
vector.add_last 2;hashed set
+ set : HASHED_SET[INTEGER];
set := HASHED_SET[INTEGER].create;
set.add 1;
set.add 2;linked list
+ list : LINKED_LIST[INTEGER];
list := LINKED_LIST[INTEGER].create;
list.add_last 1;
list.add_last 2;hashed dictionary
+ dict : HASHED_DICTIONARY[INTEGER/*value*/, STRING_CONSTANT/*key*/];
dict := HASHED_DICTIONARY[INTEGER, STRING_CONSTANT].create;
dict.put 1 to "one";
dict.put 2 to "two";Logo
Logo has a list-like protocol (first, butfirst, etc.) which works on three different data types:
- members of a list: [one two three]
- items in an array: {one two three}
- characters in a word: "123
Lua
Lua has only one type of collection, the table. But Lua's table has features of both, traditional arrays and hash maps (dictionaries). You can even mix both within one table. Note, that the numeric indices of Lua's table start at 1, not at 0 as with most other languages.
collection = {0, '1'}
print(collection[1]) -- prints 0
collection = {["foo"] = 0, ["bar"] = '1'} -- a collection of key/value pairs
print(collection["foo"]) -- prints 0
print(collection.foo) -- syntactic sugar, also prints 0
collection = {0, '1', ["foo"] = 0, ["bar"] = '1'}
It is idiomatic in Lua to represent a Set data structure with a table of keys to the true value.
M2000 Interpreter
Ordered List (array)
Module Arr {
\\ array as tuple
A=(1,2,3,4,5)
Print Array(A,0)=1
Print A
\\ add two arrays
A=Cons(A, (6,))
Print Len(A)=6
Print A
\\ arrays may have arrays, inventories, stacks as items
A=((1,2,3),(4,5,6))
Print Array(Array(A, 0),2)=3
}
ArrOrdered List (stack)
A stack may have values inventories,arrays, stacks, groups
Module CheckStack {
\\ ordered collection: Stack
\\ we can add values to top or bottom,
\\ we can move values to and from top
A=Stack:=100,300,600,800,900
Print StackItem(A, 2)=300, Len(A)=5
Stack A {
\\ push to bottom (or end)
Data 2000, 4000
}
Print StackItem(A, 7)=4000, Len(A)=7
Stack A {
\\ pop from top
Read X, Y
Print X=100, Y=300
}
Print StackItem(A,5)=4000, Len(A)=5
Stack A {
\\ push to top
Push 2, 1
Stack ' display stack items
}
\\ we can make a new stack merging other stacks
A=Stack(A, stack:=5000,6000,7000)
Print Len(A)=10
Stack A {
Shift 1,-Len(A) ' Reverse order
Stack ' Display
}
Stack A {Drop 8}
Print Len(A)=2
Flush ' empty current stack
Stack A ' dump A to current stack
Print Stack.Size=2, Len(A)=0
}
CheckStackInventories as Maps
An Inventory may have values inventories,arrays, stacks, groups
Module Maps {
\\ Inventory as pairs of keys/values
\\ keys has to be unique
\\ Empty string "" can be used as key
\\ Search, Add and Delete in O(1)
\\ if we use delete we lost the order
\\ keys can be numbers or strings, either can exist in same inventory. Values can be anything (including objects)
\\ 0 can be used for string
\\ Keys must be unique
\\ a variable which hold an inventory is a pointer type
Inventory A=10:="A",20:="B",40:="C"
Print A$(10)="A", A$("20")="B"
\\ split search from retrieval, using key one time
If Exist(A,40) Then Print Eval$(A)="C"
k=Each(A)
While k {
\\ print keys as strings and values
Print Eval$(k, k^), Eval$(k)
}
\\ We can use Sort to sort as numbers or text
Append A, 5:="First"
Sort A as number
\\ Print can print an inventory using columns
Print A ' First A B C
Sort A as text
Print A ' A B C First
}
MapsInventories as Sets
Module Sets {
\\ Inventory as set of keys
\\ keys has to be unique
\\ Empty string "" can be used as key
\\ Search, Add and Delete in O(1)
\\ if we use delete we lost the order
\\ keys can be numbers or strings, either can exist in same inventory
\\ 0 can be used for string
\\ Keys must be unique
\\ a variable which hold an inventory is a pointer type
Inventory A=10,20,40
If Exist(A,20) Then Print Eval(A)=20
k=Each(A)
While k {
\\ print keys as strings and value same as key (as number here)
Print Eval$(k, k^), Eval(k)
}
\\ sort is a Quick sort
Sort Descending A as number
Print A ' 40 20 10
\\ For no unique keys
\\ we can't delete from anywhere.
\\ we can drop some keys from the end only
\\ Exist() move internal index to last of the same key
\\ we can give values also (make it as Map)
Inventory Queue B=1,1,1,2,2,6,10
Drop B 3
Print B ' prints 1 1 1 2
\\ sort is an insertion sort (stable)
}
SetsUsing a Visual Basic 6 Collection
M2000 Interpreter is a VB6 application. We can use a VB6 collection, but only until the module where we declare it end. This is what this interpreter do with COM objects, it never make a second object reference (we can make other variables as reference, using the same object, and these reference can't changed). We can pass object through stack of values, but for a call inside the M2000 interpreter. In this example we make a lambda function which hold a closure, and this closure works only if the object exist.
We can get a list
Module GetC {
declare c collection
def decimal aDecimal=3000032131231231312312
Document doc$
Print type$(c)
\\ we get an inventory list of all methods/properties of a com Object
m=param(c)
IF LEN(m)>1 THEN {
For i=0 to len(m)-1
\\ use index, not key so i! is index
Doc$=m$(i!)+{
} ' we use this block for new line
Next i
}
Report Doc$
Clipboard Doc$
\\ so now we have to use it, using Methid to call Add
Method c, "Add", 100, "Hello"
Method c, "Add", 2000, "There"
\\ add a decimal number
Method c, "Add", aDecimal, "Zero"
Method c, "count" as count
Print count =3 ' we have three members
Method C, "_NewEnum" as Item
Method c, "Item", "Zero" as ZeroItem ' we get the decimal number
Print ZeroItem
Print type$(Item)="Nothing" ' we have numbers
k=0
While Item {
k++
print k, eval(item)
}
c.item=lambda c (akey$) ->{
try ok {
method c, "item", akey$ as ret
}
If type$(Ret)="Empty" Then Error "Key not used"
=ret
}
Print c.item("Hello")
Try {
val=c.item("Hello12")
}
Print Error$
Push c
}
GetC
Read a
Print type$(a)="Collection" ' if we don't declare{Out}
Function QueryInterface(riid, ppvObj)
Function AddRef
Function Release
Function GetTypeInfoCount(pctinfo)
Function GetTypeInfo(itinfo, lcid, pptinfo)
Function GetIDsOfNames(riid, rgszNames, cNames, lcid, rgdispid)
Function Invoke(dispidMember, riid, lcid, wFlags, pdispparams, pvarResult, pexcepinfo, puArgErr)
Function Item(Index)
Function Add(Item, Key, Before, After)
Function Count
Function Remove(Index)
Function _NewEnum
True
3000032131231231312312
True
1 100
3 2000
33000032131231231312312
100
Key not used Problem in lambda in function C.ITEM(
True
Maple
Defining lists:
L1 := [3, 4, 5, 6];
L1 := [3, 4, 5, 6]
L2 := [7, 8, 9];
L2 := [7, 8, 9]Concatenating two lists:
[op(L1), op(L2)]
[3, 4, 5, 6, 7, 8, 9]Defining an Array:
A1 := Array([3, 4, 5, 6]);
A1 := [3, 4, 5, 6]Appending to a Vector:
ArrayTools:-Append(A1, 7);
A1 := [3, 4, 5, 6, 7]Mathematica / Wolfram Language
Lst = {3, 4, 5, 6}
->{3, 4, 5, 6}
PrependTo[ Lst, 2]
->{2, 3, 4, 5, 6}
PrependTo[ Lst, 1]
->{1, 2, 3, 4, 5, 6}
Lst
->{1, 2, 3, 4, 5, 6}
Insert[ Lst, X, 4]
->{1, 2, 3, X, 4, 5, 6}
MATLAB / Octave
MATLAB cell-arrays perform this function. They are indexed like arrays, but are able to hold any data type. In any cell simultaneously with any other data type. In essence they cell-arrays are sets.
Sample Usage:
>> A = {2,'TPS Report'} %Declare cell-array and initialize
A =
[2] 'TPS Report'
>> A{2} = struct('make','honda','year',2003)
A =
[2] [1x1 struct]
>> A{3} = {3,'HOVA'} %Create and assign A{3}
A =
[2] [1x1 struct] {1x2 cell}
>> A{2} %Get A{2}
ans =
make: 'honda'
year: 2003
Bold text
MiniScript
MiniScript supports both lists and maps (dictionaries). This task demonstrates lists.
seq = [0, "foo", pi]
seq.push 42
seq = seq + [1, 2, 3]
print seq
- Output:
[0, "foo", 3.141593, 42, 1, 2, 3]
MS SmallBasic
Only with LD extension
ll=LDList.CreateFromValues("")
LDList.Add(ll "Cars")
LDList.Add(ll "Toys")
LDList.Print(ll)result:
List1
1 : Cars
2 : Toys
NetRexx
NetRexx can take advantage of Java's Collection classes. This example uses the Set interface backed by a HashSet:
/* NetRexx */
options replace format comments java crossref symbols nobinary
myVals = [ 'zero', 'one', 'two', 'three', 'four', 'five' ]
mySet = Set
mySet = HashSet()
loop val over myVals
mySet.add(val)
end val
loop val over mySet
say val
end val
return
Nim
Array
Length is known at compile time
var a = [1,2,3,4,5,6,7,8,9]
var b: array[128, int]
b[9] = 10
b[0..8] = a
var c: array['a'..'d', float] = [1.0, 1.1, 1.2, 1.3]
c['b'] = 10000
Seq
Variable length sequences
var d = @[1,2,3,5,6,7,8,9]
d.add(10)
d.add([11,12,13,14])
d[0] = 0
var e: seq[float] = @[]
e.add(15.5)
var f = newSeq[string]()
f.add("foo")
f.add("bar")
Tuple
Fixed length, named
var g = (13, 13, 14)
g[0] = 12
var h: tuple[key: string, val: int] = ("foo", 100)
# A sequence of key-val tuples:
var i = {"foo": 12, "bar": 13}
Set
Bit vector of ordinals
var j: set[char]
j.incl('X')
var k = {'a'..'z', '0'..'9'}
j = j + k
Tables
Hash tables (there are also ordered hash tables and counting hash tables)
import tables
var l = initTable[string, int]()
l["foo"] = 12
l["bar"] = 13
var m = {"foo": 12, "bar": 13}.toTable
m["baz"] = 14Sets
Hash sets (also ordered hash sets)
import sets
var n = initSet[string]()
n.incl("foo")
var o = ["foo", "bar", "baz"].toSet
o.incl("foobar")Double queues
import deques
var p = initDeque[int]()
p.addLast(12)
p.addFirst(13)
echo p.popFirst()
echo p.popLast()Objeck
vector
values := IntVector->New();
values->AddBack(7);
values->AddBack(3);
values->AddBack(10);linked list
values := IntList->New();
values->AddBack(7);
values->AddBack(3);
values->AddBack(10);hash
values := StringHash->New();
values->Insert("seven", IntHolder->New(7));
values->Insert("three", IntHolder->New(3));
values->Insert("ten", IntHolder->New(10));stack
values := IntStack->New();
values->Push(7);
values->Push(3);
values->Push(10);Objective-C
OpenStep (and derivates like GNUstep and Cocoa) has several collection classes; here we show
- a set: a collection of unique elements (like mathematical set). Possible operations on a set are not shown;
- a counted set (also known as bag): each elements have a counter that says how many time that element appears;
- a dictionary: pairs key-value.
Arrays (indexed by an integer), which are also collections, are not shown here.
#import <Foundation/Foundation.h>
void show_collection(id coll)
{
for ( id el in coll )
{
if ( [coll isKindOfClass: [NSCountedSet class]] ) {
NSLog(@"%@ appears %lu times", el, [coll countForObject: el]);
} else if ( [coll isKindOfClass: [NSDictionary class]] ) {
NSLog(@"%@ -> %@", el, coll[el]);
} else {
NSLog(@"%@", el);
}
}
printf("\n");
}
int main()
{
@autoreleasepool {
// create an empty set
NSMutableSet *set = [[NSMutableSet alloc] init];
// populate it
[set addObject: @"one"];
[set addObject: @10];
[set addObjectsFromArray: @[@"one", @20, @10, @"two"] ];
// let's show it
show_collection(set);
// create an empty counted set (a bag)
NSCountedSet *cset = [[NSCountedSet alloc] init];
// populate it
[cset addObject: @"one"];
[cset addObject: @"one"];
[cset addObject: @"two"];
// show it
show_collection(cset);
// create a dictionary
NSMutableDictionary *dict = [[NSMutableDictionary alloc] init];
// populate it
dict[@"four"] = @4;
dict[@"eight"] = @8;
// show it
show_collection(dict);
}
return EXIT_SUCCESS;
}- Output:
(stripped the left-sided log info)
two 20 10 one two appears 1 times one appears 2 times eight -> 8 four -> 4
OCaml
Lists are written like so:
[1; 2; 3; 4; 5]To prepend a single element to a list, use the :: operator:
1 :: [2; 3; 4; 5]To concatenate two lists, use @:
[1; 2] @ [3; 4; 5]To concatenate a whole list of lists, use List.flatten:
# List.flatten [[1; 2]; [3; 4]; [5; 6; 7]] ;;
- : int list = [1; 2; 3; 4; 5; 6; 7]Being a functional programming language, the list is one of the most important collection type. And being an impure functional programming language there are also imperative collection type, as for example, arrays:
[| 1; 2; 3; 4; 5 |]The extlib also provides a type Enum.t.
Oforth
Collection is a class. Into the lang package, subclasses are :
Buffer A collection of bytes
Mem A mutable collection of bytes
Interval A first value, a last value and a step.
Pair A collection of 2 elements (with key/value features).
List A collection of n elements
ListBuffer A mutable collection of n elements that can grow when necessary
String A collection of n characters
Symbol A collection of n characters that are identity (if they are equal, they are the same object).
StringBuffer A mutable collection of n charaters that can grow when necessary
There is no Array collection : an immutable array is a list (which is immutable) an a mutable array is a ListBuffer.
A List (or a Pair) can be created using the following syntax :
[ 1, 1.2, "abcd", [ 1, 2, 3 ] ]In order to add values to a collection, you have to use a ListBuffer (a mutable collection) :
ListBuffer new dup add(10) dup add("aaa") dup add(Date now) dup add(1.3) println- Output:
[10, aaa, 2015-02-02 14:02:17,047, 1.3]
ooRexx
ooRexx has multiple classes that are collections of other objects with different access and storage characteristics.
- Arrays
ooRexx arrays are sequential lists of object references. The index values are the numeric position (1-based) within the array. A given array may be sparse and arrays will be automatically expanded as needed.
a = .array~new(4) -- creates an array of 4 items, with all slots empty
say a~size a~items -- size is 4, but there are 0 items
a[1] = "Fred" -- assigns a value to the first item
a[5] = "Mike" -- assigns a value to the fifth slot, expanding the size
say a~size a~items -- size is now 5, with 2 items- Lists
Lists are non-sparse sequential lists of object references. Item can be inserted or deleted at any position and the positions will be adjusted accordingly. Lists are indexed using index cookies that are assigned when an entry is added to the list and can be used to access entries or traverse through the list.
l = .list~new -- lists have no inherent size
index = l~insert('123') -- adds an item to this list, returning the index
l~insert('Fred', .nil) -- inserts this at the beginning
l~insert('Mike') -- adds this to the end
l~insert('Rick', index) -- inserts this after '123'
l[index] = l[index] + 1 -- the original item is now '124'
do item over l -- iterate over the items, displaying them in order
say item
end- Output:
Fred 124 Rick Mike
- Queues
Queues are non-sparse sequential lists of object references. The index values are by numeric position (1-based), although access to items is traditionally done by pushing or popping objects.
q = .queue~of(2,4,6) -- creates a queue containing 3 items
say q[1] q[3] -- displays "2 6"
i = q~pull -- removes the first item
q~queue(i) -- adds it to the end
say q[1] q[3] -- displays "4 2"
q[1] = q[1] + 1 -- updates the first item
say q[1] q[3] -- displays "5 2"- Tables
Tables are collections that create a one-to-one relationship between an index object and a referenced object. Although frequently used with string indexes, the index object can be of any class, with index identity determined by the "==" method.
t = .table~new
t['abc'] = 1
t['def'] = 2
say t['abc'] t['def'] -- displays "1 2"- Relations
Relation collections create one-to-many data relationships. An addition to the collection will always create a new entry.
t = .table~new -- a table example to demonstrate the difference
t['abc'] = 1 -- sets an item at index 'abc'
t['abc'] = 2 -- updates that item
say t~items t['abc'] -- displays "1 2"
r = .relation~new
r['abc'] = 1 -- sets an item at index 'abc'
r['abc'] = 2 -- adds an additional item at the same index
say r~items r['abc'] -- displays "2 2" this has two items in it now
do item over r~allAt('abc') -- retrieves all items at the index 'abc'
say item
end- Directories
Directory objects are like tables, but the index values must always be string objects.
d = .directory~new
d['abc'] = 1
d['def'] = 2
say d['abc'] d['def'] -- displays "1 2"Directory objects also support an UNKNOWN method that map messages to directory index entries. This allows values to be set as if they were object attributes. The following example is another way of doing the same as the first example:
d = .directory~new
d~abc = 1
d~def = 2
say d~abc d~def -- displays "1 2"Note that the index entries created in the example are the uppercase 'ABC' and 'DEF'.
- Sets
Sets are unordered collections where the items added to the collection are unique values. Duplicate additions are collapsed to just a single item. Sets are useful for collecting unique occurrences of items.
s = .set~new
text = "the quick brown fox jumped over the lazy dog"
do word over text~makearray(' ')
s~put(word)
end
say "text has" text~words", but only" s~items "unique words"Oz
The most important collection types are lists, records, dictionaries and arrays:
declare
%% Lists (immutable, recursive)
Xs = [1 2 3 4]
%% Add element at the front (cons)
Xs0 = 0|Xs
{Show {Length Xs}} %% output: 4
%% Records (immutable maps with a label)
Rec = label(1:2 symbol:3)
{Show Rec} %% output: label(2 symbol:3)
{Show Rec.1} %% output: 2
%% create a new record with an added field
Rec2 = {AdjoinAt Rec 2 value}
{Show Rec2} %% output: label(2 value symbol:3)
%% Dictionaries (mutable maps)
Dict = {Dictionary.new}
Dict.1 := 1
Dict.symbol := 3
{Show Dict.1} %% output: 1
%% Arrays (mutable with integer keys)
Arr = {Array.new 1 10 initValue}
Arr.1 := 3
{Show Arr.1} %% output: 3There are also tuples (records with consecutive integer keys starting with 1), weak dictionaries, queues and stacks.
PARI/GP
Pari has vectors, column vectors, matrices, sets, lists, small vectors, and maps.
v = vector(0);
v = [];
cv = vectorv(0);
cv = []~;
m = matrix(1,1);
s = Set(v);
l = List(v);
vs = vectorsmall(0);
M = Map()Adding members:
listput(l, "hello world")
v=concat(v, [1,2,3]);
v=concat(v, 4);
mapput(M, "key", "value");Pascal
Different implementations of Pascal have various containers.
Array
var
MyArray: array[1..5] of real;
begin
MyArray[1] := 4.35;
end;Dynamic Array
var
MyArray: array of integer;
begin
setlength (MyArray, 10);
MyArray[4] := 99;
end;Record
var
MyRecord: record
x, y, z: real;
presence: boolean;
end;
begin
MyRecord.x := 0.3;
MyRecord.y := 3.2;
MyRecord.z := -4.0;
MyRecord.presence := true;
end;Set
type
days = (Mon, Tue, Wed, Thu, Fri, Sat, Sun);
var
workDays, week, weekendDays: set of days;
begin
workdays := [Mon, Tue, Wed, Thu, Fri];
week := workdays + [Sat, Sun];
weekendDays := week - workdays;
end;String
var
MyString: String;
begin
MyString:= 'Some Text';
end;List
program ListDemo;
uses
classes;
var
MyList: TList;
a, b, c: integer;
i: integer;
begin
a := 1;
b := 2;
c := 3;
MyList := TList.Create;
MyList.Add(@a);
MyList.Add(@c);
MyList.Insert(1, @b);
for i := MyList.IndexOf(MyList.First) to MyList.IndexOf(MyList.Last) do
writeln (integer(MyList.Items[i]^));
MyList.Destroy;
end.- Output:
% ./ListDemo 1 2 3
Collection
Example from the documentation of the FreePascal runtime library.
Program ex34;
{ Program to demonstrate the TCollection.AtInsert method }
Uses Objects, MyObject; { For TMyObject definition and registration }
Var C : PCollection;
M : PMyObject;
I : Longint;
Procedure PrintField (Dummy : Pointer; P : PMyObject);
begin
Writeln ('Field : ',P^.GetField);
end;
begin
Randomize;
C:=New(PCollection, Init(120, 10));
Writeln ('Inserting 100 records at random places.');
For I:=1 to 100 do
begin
M:=New(PMyObject, Init);
M^.SetField(I-1);
If I=1 then
C^.Insert(M)
else
With C^ do
AtInsert(Random(Count), M);
end;
Writeln ('Values : ');
C^.Foreach(@PrintField);
Dispose(C, Done);
end.PascalABC.NET
begin
// build-in array
var a: array of integer := new integer[5] (1,2,3,4,5);
// build-in multidimensional array
var aa: array [,] of integer := new integer[4,3]((1,2,3),(4,5,6),(7,8,9),(1,2,3));
// List is a resizable array
var lst := new List<integer>(a);
lst.Add(1);
lst.AddRange(|2,3|);
// HashSet is an unordered set, SortedSet is ordered
var hs := new HashSet<integer>;
var ss := new SortedSet<integer>;
hs.Add(1); ss.Add(2);
// Dictionary is an unordered map, SortedDictionary is ordered
var d := new Dictionary<string,integer>;
d['str1'] := 1; d['str2'] := 3;
var sd := new SortedDictionary<string,integer>;
sd['str1'] := 1; sd['str2'] := 3;
// Stack and Queue
var s := new Stack<integer>;
s.Push(1); s.Push(2); s.Push(3);
var q := new Queue<integer>;
q.Enqueue(1); q.Enqueue(2); q.Enqueue(3);
end.Perl
Perl has array and hashes.
use strict;
my @c = (); # create an empty "array" collection
# fill it
push @c, 10, 11, 12;
push @c, 65;
# print it
print join(" ",@c) . "\n";
# create an empty hash
my %h = ();
# add some pair
$h{'one'} = 1;
$h{'two'} = 2;
# print it
foreach my $i ( keys %h ) {
print $i . " -> " . $h{$i} . "\n";
}Phix
Collections can simply be stored as sequences
with javascript_semantics sequence collection = {} collection = append(collection,"one") collection = prepend(collection,2) ? collection -- {2,"one"}
If you want uniqueness, you could simply use a dictionary with values of 0:
with javascript_semantics setd("one",0) setd(2,0) function visitor(object key, object /*data*/, object /*user_data*/) ?key return 1 end function traverse_dict(routine_id("visitor")) -- shows 2, "one"
PHP
PHP has associative arrays as collection
<?php
$a = array();
# add elements "at the end"
array_push($a, 55, 10, 20);
print_r($a);
# using an explicit key
$a['one'] = 1;
$a['two'] = 2;
print_r($a);
?>- Output:
Array
(
[0] => 55
[1] => 10
[2] => 20
)
Array
(
[0] => 55
[1] => 10
[2] => 20
[one] => 1
[two] => 2
)
Picat
Lists
go =>
L = [1,2,3,4],
L2 = L ++ [[5,6,7]], % adding a list
L3 = ["a string"] ++ L2, % adding a string
% Prolog way
append([0],L,[5],L4).Arrays
Array are often used instead of lists for speed. The array literal use {...} (instead of the lists [...]).
go2 =>
L = {1,2,3,4},
L2 = {0} ++ L ++ {5},
% multi dimensional arrays
M = new_array(4,4),
bind_vars(M,0). % initialize to 0Maps
Associative arrays/Dictionaries.
go3 =>
Map = new_map(),
Map.put(a,1),
Map.put(b,2),
% Initialize map with values
Map2 = new_map([c=3,d="some value"]).Sets
A set is a map where every key is associated with the atom 'not_a_value'. All of the built-ins for maps can be applied to sets.
go4 =>
S = new_set([1,2,3,4,5,"picat"]),
S.put(1),
S.put(21).Structures
A structure takes the form $s(t1,...,tn), where s is an atom, and n is called the arity of the
structure. The dollar symbol is used to distinguish a structure from a function call.
go5 =>
S = new_struct(a_struct,5),
S[2] = 4, % place 4 at position 2
arg(3,S,"string"). % place "string" at position 3Heaps
A heap is a complete binary tree represented as an array. A heap can be a min-heap or a max-heap. In a min-heap, the value at the root of each subtree is the minimum among all the values in the subtree. In a max-heap, the value at the root of each subtree is the maximum among all the values in the subtree.
go6 =>
L = [1,3,2,4,5,3,6],
H = new_min_heap(L),
H.heap_push(-123).
PicoLisp
The direct way in PicoLisp is a linear list (other possibilities could involve index trees or property lists).
: (setq Lst (3 4 5 6))
-> (3 4 5 6)
: (push 'Lst 2)
-> 2
: (push 'Lst 1)
-> 1
: Lst
-> (1 2 3 4 5 6)
: (insert 4 Lst 'X)
-> (1 2 3 X 4 5 6)PL/I
declare countries character (20) varying controlled;
allocate countries initial ('Britain');
allocate countries initial ('America');
allocate countries initial ('Argentina');PowerShell
The most common collection types in PowerShell are arrays and hash tables.
Array
The array index is zero based.
# Create an Array by separating the elements with commas:
$array = "one", 2, "three", 4
# Using explicit syntax:
$array = @("one", 2, "three", 4)
# Send the values back into individual variables:
$var1, $var2, $var3, $var4 = $array
# An array of several integer ([int]) values:
$array = 0, 1, 2, 3, 4, 5, 6, 7
# Using the range operator (..):
$array = 0..7
# Strongly typed:
[int[]] $stronglyTypedArray = 1, 2, 4, 8, 16, 32, 64, 128
# An empty array:
$array = @()
# An array with a single element:
$array = @("one")
# I suppose this would be a jagged array:
$jaggedArray = @((11, 12, 13),
(21, 22, 23),
(31, 32, 33))
$jaggedArray | Format-Wide {$_} -Column 3 -Force
$jaggedArray[1][1] # returns 22
# A Multi-dimensional array:
$multiArray = New-Object -TypeName "System.Object[,]" -ArgumentList 6,6
for ($i = 0; $i -lt 6; $i++)
{
for ($j = 0; $j -lt 6; $j++)
{
$multiArray[$i,$j] = ($i + 1) * 10 + ($j + 1)
}
}
$multiArray | Format-Wide {$_} -Column 6 -Force
$multiArray[2,2] # returns 33Hash Table
Hash tables come in two varieties: normal and ordered, where of course, the order of entry is retained.
# An empty Hash Table:
$hash = @{}
# A Hash table populated with some values:
$nfcCentralDivision = @{
Packers = "Green Bay"
Bears = "Chicago"
Lions = "Detroit"
}
# Add items to a Hash Table:
$nfcCentralDivision.Add("Vikings","Minnesota")
$nfcCentralDivision.Add("Buccaneers","Tampa Bay")
# Remove an item from a Hash Table:
$nfcCentralDivision.Remove("Buccaneers")
# Searching for items
$nfcCentralDivision.ContainsKey("Packers")
$nfcCentralDivision.ContainsValue("Green Bay")
# A bad value...
$hash1 = @{
One = 1
Two = 3
}
# Edit an item in a Hash Table:
$hash1.Set_Item("Two",2)
# Combine Hash Tables:
$hash2 = @{
Three = 3
Four = 4
}
$hash1 + $hash2
# Using the ([ordered]) accelerator the items in the Hash Table retain the order in which they were input:
$nfcCentralDivision = [ordered]@{
Bears = "Chicago"
Lions = "Detroit"
Packers = "Green Bay"
Vikings = "Minnesota"
}Other Collection Types
PowerShell is a .NET language so all of the collection types in .NET are available to PowerShell. The most commonly used would probably be [System.Collections.ArrayList].
$list = New-Object -TypeName System.Collections.ArrayList -ArgumentList 1,2,3
# or...
$list = [System.Collections.ArrayList]@(1,2,3)
$list.Add(4) | Out-Null
$list.RemoveAt(2)Prolog
Traditionally Prolog supports only lists.
% create a list
L = [a,b,c,d],
% prepend to the list
L2 = [before_a|L],
% append to the list
append(L2, ['Hello'], L3),
% delete from list
exclude(=(b), L3, L4).Output:
L = [a, b, c, d], L2 = [before_a, a, b, c, d], L3 = [before_a, a, b, c, d, 'Hello'], L4 = [before_a, a, c, d, 'Hello'].
SWI-Prolog supports some other collection types as built in libraries, the most notable is the Dict. Dicts can be accessed using a special notation and can be added and removed from in an immutable way.
% create an empty dict call 'point'
D1 = point{},
% add a value
D2 = D1.put(x, 20).put(y, 30).put(z, 20),
% update a value
D3 = D2.put([x=25]),
% remove a value
del_dict(z, D3, _, D4),
% access a value randomly
format('x = ~w, y = ~w~n', [D4.x, D4.y]).Output:
x = 25, y = 30
D1 = point{},
D2 = point{x:20, y:30, z:20},
D3 = point{x:25, y:30, z:20},
D4 = point{x:25, y:30}.
PureBasic
Arrays
Creating an Array of 10 strings (could be any type). PureBasic starts the index with element 0.
Dim Text.s(9)
Text(3)="Hello"
Text(7)="World!"Linked Lists
Create a Linked List for strings (could be any type), then add two elements.
NewList Cars.s()
AddElement(Cars()): Cars()="Volvo"
AddElement(Cars()): Cars()="BMV"Hash table
Create a Map, e.g. a hash table that could be any type. The size of the dictionary can be defined as needed, otherwise a default value is used.
NewMap Capitals.s()
Capitals("USA") = "Washington"
Capitals("Sweden")= "Stockholm"Python
Python supports lists, tuples, dictionaries and now sets as built-in collection types. See http://docs.python.org/tut/node7.html for further details.
collection = [0, '1'] # Lists are mutable (editable) and can be sorted in place
x = collection[0] # accessing an item (which happens to be a numeric 0 (zero)
collection.append(2) # adding something to the end of the list
collection.insert(0, '-1') # inserting a value into the beginning
y = collection[0] # now returns a string of "-1"
collection.extend([2,'3']) # same as [collection.append(i) for i in [2,'3']] ... but faster
collection += [2,'3'] # same as previous line
collection[2:6] # a "slice" (collection of the list elements from the third up to but not including the sixth)
len(collection) # get the length of (number of elements in) the collection
collection = (0, 1) # Tuples are immutable (not editable)
collection[:] # ... slices work on these too; and this is equivalent to collection[0:len(collection)]
collection[-4:-1] # negative slices count from the end of the string
collection[::2] # slices can also specify a stride --- this returns all even elements of the collection
collection="some string" # strings are treated as sequences of characters
x = collection[::-1] # slice with negative step returns reversed sequence (string in this case).
collection[::2] == "some string"[::2] # True, literal objects don't need to be bound to name/variable to access slices or object methods
collection.__getitem__(slice(0,len(collection),2)) # same as previous expressions.
collection = {0: "zero", 1: "one"} # Dictionaries (Hash)
collection['zero'] = 2 # Dictionary members accessed using same syntax as list/array indexes.
collection = set([0, '1']) # sets (Hash)In addition Python classes support a number of methods allowing them to implement indexing, slicing, and attribute management features as collections. Thus many modules in the Python standard libraries allow one to treat files contents, databases, and other data using the same syntax as the native collection types. Some Python modules (such as Numeric and NumPy) provide low-level implementations of additional collections (such as efficient n-dimensional arrays).
R
R has several types that can be considered collections.
Vectors
Numeric (floating point)
numeric(5)
1:10
c(1, 3, 6, 10, 7 + 8, sqrt(441))[1] 0 0 0 0 0 [1] 1 2 3 4 5 6 7 8 9 10 [1] 1 3 6 10 15 21
Integer
integer(5)
c(1L, -2L, 99L);[1] 0 0 0 0 0 [1] 1 -2 99
Logical
logical(5)
c(TRUE, FALSE)[1] FALSE FALSE FALSE FALSE FALSE [1] TRUE FALSE
Character
character(5)
c("abc", "defg", "")[1] "" "" "" "" "" [1] "abc" "defg" ""
Arrays and Matrices
These are essentially vectors with a dimension attribute. Matrices are just arrays with two dimensions (and a different class).
matrix(1:12, nrow=3)
array(1:24, dim=c(2,3,4)) #output not shown[,1] [,2] [,3] [,4] [1,] 1 4 7 10 [2,] 2 5 8 11 [3,] 3 6 9 12
Lists
Lists are collections of other variables (that can include other lists).
list(a=123, b="abc", TRUE, 1:5, c=list(d=runif(5), e=5+6))$a
[1] 123
$b
[1] "abc"
[[3]]
[1] TRUE
[[4]]
[1] 1 2 3 4 5
$c
$c$d
[1] 0.6013157 0.5011909 0.7106448 0.3882265 0.1274939
$c$e
[1] 11Data Frames
Data frames are like a cross between a list and a matrix. Each row represents one "record", or a collection of variables.
data.frame(name=c("Alice", "Bob", "Carol"), age=c(23, 35, 17))name age 1 Alice 23 2 Bob 35 3 Carol 17
Racket
As in other lisps, the simple kind of linked lists are the most common collection-of-values type.
#lang racket
;; create a list
(list 1 2 3 4)
;; create a list of size N
(make-list 100 0)
;; add an element to the front of a list (non-destructively)
(cons 1 (list 2 3 4))Racket comes with about 7000 additional types that can be considered as a collection of values, but it's not clear whether this entry is supposed to be a laundry list...
Raku
(formerly Perl 6)
Raku has both mutable and immutable containers of various sorts. Here are some of the most common ones:
Mutable
# Array
my @array = 1,2,3;
@array.push: 4,5,6;
# Hash
my %hash = 'a' => 1, 'b' => 2;
%hash<c d> = 3,4;
%hash.push: 'e' => 5, 'f' => 6;
# SetHash
my $s = SetHash.new: <a b c>;
$s βͺ= <d e f>;
# BagHash
my $b = BagHash.new: <b a k l a v a>;
$b β= <a b c>;Immutable
# List
my @list := 1,2,3;
my @newlist := |@list, 4,5,6; # |@list will slip @list into the surrounding list instead of creating a list of lists
# Set
my $set = set <a b c>;
my $newset = $set βͺ <d e f>;
# Bag
my $bag = bag <b a k l a v a>;
my $newbag = $bag β <b e e f>;Pair list (cons list)
my $tail = d => e => f => Nil;
my $new = a => b => c => $tail;P6opaque object (immutable in structure)
class Something { has $.foo; has $.bar };
my $obj = Something.new: foo => 1, bar => 2;
my $newobj = $obj but role { has $.baz = 3 } # anonymous mixinRaven
Numerically indexed List:
[ 1 2 3 'abc' ] as a_list
a_list print
list (4 items)
0 => 1
1 => 2
2 => 3
3 => "abc"String key indexed Hash:
{ 'a' 1 'b' 2 } as a_hash
a_hash print
hash (2 items)
a => 1
b => 2Set items:
17 a_list 1 set # set second item
42 a_hash 'b' set # set item with key 'b'
42 a_hash:b # shorthandGet items:
a_list 1 get # get second item
a_hash 'b' get # get item with key 'b'
a_hash.b # shorthandOther stuff:
42 a_list push # append an item
a_list pop # remove last item
42 a_list shove # prepend an item
a_list shift # remove first item
42 a_list 1 insert # insert item second, shuffling others down
a_list 1 remove # retrieve second item, shuffling others upREXX
There are several methods to store collections in REXX:
- stemmed arrays (or simply, arrays)
- lists or vectors
- sparse stemmed arrays; (or simply, sparse arrays)
A collection can be numbers (integer or floating point numbers), or any character strings (including nulls).
Indeed, even numbers in REXX are stored as characters.
stemmed arrays
To store (say) a collection of numbers (or anything, for that matter) into a stemmed array:
pr. = /*define a default for all elements for the array*/
pr.1 = 2 /*note that this array starts at 1 (one). */
pr.2 = 3
pr.3 = 5
pr.4 = 7
pr.5 = 11
pr.6 = 13
pr.7 = 17
pr.8 = 19
pr.9 = 23
pr.10 = 29
pr.11 = 31
pr.12 = 37
pr.13 = 41
pr.14 = 43
pr.15 = 47
y. = 0 /*define a default for all years (Y) to be zero*/
y.1985 = 6020
y.1986 = 7791
y.1987 = 8244
y.1988 = 10075
x = y.2012 /*the variable X will have a value of zero (0).*/
fib.0 = 0 /*this stemmed arrays will start with zero (0). */
fib.1 = 1
fib.2 = 1
fib.3 = 2
fib.4 = 3
fib.5 = 5
fib.6 = 8
fib.7 = 17
do n=-5 to 5 /*define a stemmed array from -5 to 5 */
sawtooth.n = n /*the sawtooth array is, well, a sawtooth curve*/
end /*n*/ /*note that eleven elements will be defined. */Most often, programmers will assign the zero entry to the number of elements in the stemmed array.
This means that any index of the stemmed array must be positive to be useful for storing numbers.
pr.0= 15 /*number of (data) entries in the stemmed array. */Programmatically, a simple test could be performed to detect the end of the array (if there aren't any null values):
do j=1 while pr.j\==''
say 'prime' j "is" pr.j
end /*j*/
/*at this point, J=16 (because of the DO */
/*loop incrementing the index. */
j= j-1 /*J now has the count of primes stored. */lists or vectors
To store (say) a collection of numbers (or anything, for that matter) into a list:
primeList = '2 3 5 7 11 13 17 19 23 29 31 37 41 43' /* or Β·Β·Β· */
primeList = 2 3 5 7 11 13 17 19 23 29 31 37 41 43
/*in this case, the quotes (') can be elided.*/
primes= words(primeList) /*the WORDS BIF counts the number of blankβ */
/*separated words (in this case, prime numbers)*/
/*in the value of the variable "primeList".*/
do j=1 for primes /*can also be coded as: do j=1 to primes */
say 'prime' j "is" word(primeList, j)
/*this method (using the WORD BIF) isn't */
/*very efficient for very large arrays (those */
/*with many many thousands of elements). */
end /*j*/The use of lists (in the above manner) is suitable for words (or numbers) that do not have
leading, embedded, or
trailing blanks as part of their value.
One workaround is to use some other unique character (such as an
underbar/underscore _ character) that
that can be substituted, and then later, be translated to a true blank.
sparse stemmed arrays
To store (for instance) a collection of numbers (or anything, for that matter) into a sparse stemmed array:
pr. = 0 /*define a default for all elements for the array.*/
pr.2 = 1
pr.3 = 1
pr.5 = 1
pr.7 = 1
pr.11 = 1
pr.13 = 1
pr.17 = 1
pr.19 = 1
pr.23 = 1
pr.29 = 1
pr.31 = 1
pr.37 = 1
pr.41 = 1
pr.43 = 1
pr.47 = 1
/*ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ*/
primes=0
do j=1 for 10000 /*this method isn't very efficient. */
if \pr.j then iterate /*Not prime? Then skip this element. */
primes = primes + 1 /*bump the number of primes (counter).*/
end /*j*/
/*note that the 10000 is a small "β".*/
say '# of primes in list:' primes
/*ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ*/
#primes=0
do j=1 for 10000 /*this method is not very efficient. */
if pr.j\==0 then #primes = #primes + 1 /*Not zero? Bump the number of primes.*/
end /*j*/ /* [β] not as idiomatic as 1st program*/
say '# of primes in the list:' #primes
/*ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ*/
Ps=0
do k=1 for 10000 /*and yet another inefficient method. */
if pr.k==0 then iterate /*Not a prime? Then skip this element.*/
Ps = Ps + 1 /*bump the counter for the # of primes.*/
say 'prime' Ps "is:" k /*might as well echo this prime number.*/
end /*k*/
say 'The number of primes found in the list is ' Ps
/*ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ*/
pr.0 = 47 /*hardcode the highest prime in array. */
# = 0
do k=2 to pr.0 /*and much more efficient method. */
if \pr.k then iterate /*Not a prime? Then skip this element.*/
# = # + 1 /*bump the counter for the # of primes.*/
say 'prime' Ps "is:" k /*might as well echo this prime number.*/
end /*k*/
say 'The number of primes found in the list is: ' #
Ring
text = list(2)
text[1] = "Hello "
text[2] = "world!"
see text[1] + text[2] + nlOutput:
Hello world!
Ruby
Array
Arrays are ordered, integer-indexed collections of any object.
# creating an empty array and adding values
a = [] #=> []
a[0] = 1 #=> [1]
a[3] = "abc" #=> [1, nil, nil, "abc"]
a << 3.14 #=> [1, nil, nil, "abc", 3.14]
# creating an array with the constructor
a = Array.new #=> []
a = Array.new(3) #=> [nil, nil, nil]
a = Array.new(3, 0) #=> [0, 0, 0]
a = Array.new(3){|i| i*2} #=> [0, 2, 4]Hash
A Hash is a dictionary-like collection of unique keys and their values. Also called associative arrays, they are similar to Arrays, but where an Array uses integers as its index, a Hash allows you to use any object type.
# creating an empty hash
h = {} #=> {}
h["a"] = 1 #=> {"a"=>1}
h["test"] = 2.4 #=> {"a"=>1, "test"=>2.4}
h[3] = "Hello" #=> {"a"=>1, "test"=>2.4, 3=>"Hello"}
h = {a:1, test:2.4, World!:"Hello"}
#=> {:a=>1, :test=>2.4, :World!=>"Hello"}
# creating a hash with the constructor
h = Hash.new #=> {} (default value : nil)
p h[1] #=> nil
h = Hash.new(0) #=> {} (default value : 0)
p h[1] #=> 0
p h #=> {}
h = Hash.new{|hash, key| key.to_s}
#=> {}
p h[123] #=> "123"
p h #=> {}
h = Hash.new{|hash, key| hash[key] = "foo#{key}"}
#=> {}
p h[1] #=> "foo1"
p h #=> {1=>"foo1"}Struct
A Struct is a convenient way to bundle a number of attributes together, using accessor methods, without having to write an explicit class.
# creating a struct
Person = Struct.new(:name, :age, :sex)
a = Person.new("Peter", 15, :Man)
p a[0] #=> "Peter"
p a[:age] #=> 15
p a.sex #=> :Man
p a.to_a #=> ["Peter", 15, :Man]
p a.to_h #=> {:name=>"Peter", :age=>15, :sex=>:Man}
b = Person.new
p b #=> #<struct Person name=nil, age=nil, sex=nil>
b.name = "Margaret"
b["age"] = 18
b[-1] = :Woman
p b.values #=> ["Margaret", 18, :Woman]
p b.members #=> [:name, :age, :sex]
p b.size #=> 3
c = Person["Daniel", 22, :Man]
p c.to_h #=> {:name=>"Daniel", :age=>22, :sex=>:Man}Set
Set implements a collection of unordered values with no duplicates. This is a hybrid of Array's intuitive inter-operation facilities and Hash's fast lookup.
require 'set'
# different ways of creating a set
p s1 = Set[1, 2, 3, 4] #=> #<Set: {1, 2, 3, 4}>
p s2 = [8, 6, 4, 2].to_set #=> #<Set: {8, 6, 4, 2}>
p s3 = Set.new(1..4) {|x| x*2} #=> #<Set: {2, 4, 6, 8}>
# Union
p s1 | s2 #=> #<Set: {1, 2, 3, 4, 8, 6}>
# Intersection
p s1 & s2 #=> #<Set: {4, 2}>
# Difference
p s1 - s2 #=> #<Set: {1, 3}>
p s1 ^ s2 #=> #<Set: {8, 6, 1, 3}>
p s2 == s3 #=> true
p s1.add(5) #=> #<Set: {1, 2, 3, 4, 5}>
p s1 << 0 #=> #<Set: {1, 2, 3, 4, 5, 0}>
p s1.delete(3) #=> #<Set: {1, 2, 4, 5, 0}>Matrix and Vector
The Matrix and Vector class represents a mathematical matrix and vector.
require 'matrix'
# creating a matrix
p m0 = Matrix.zero(3) #=> Matrix[[0, 0, 0], [0, 0, 0], [0, 0, 0]]
p m1 = Matrix.identity(3) #=> Matrix[[1, 0, 0], [0, 1, 0], [0, 0, 1]]
p m2 = Matrix[[11, 12], [21, 22]]
#=> Matrix[[11, 12], [21, 22]]
p m3 = Matrix.build(3) {|row, col| row - col}
#=> Matrix[[0, -1, -2], [1, 0, -1], [2, 1, 0]]
p m2[0,0] #=> 11
p m1 * 5 #=> Matrix[[5, 0, 0], [0, 5, 0], [0, 0, 5]]
p m1 + m3 #=> Matrix[[1, -1, -2], [1, 1, -1], [2, 1, 1]]
p m1 * m3 #=> Matrix[[0, -1, -2], [1, 0, -1], [2, 1, 0]]
# creating a Vector
p v1 = Vector[1,3,5] #=> Vector[1, 3, 5]
p v2 = Vector[0,1,2] #=> Vector[0, 1, 2]
p v1[1] #=> 3
p v1 * 2 #=> Vector[2, 6, 10]
p v1 + v2 #=> Vector[1, 4, 7]
p m1 * v1 #=> Vector[1, 3, 5]
p m3 * v1 #=> Vector[-13, -4, 5]OpenStruct
An OpenStruct is a data structure, similar to a Hash, that allows the definition of arbitrary attributes with their accompanying values.
require 'ostruct'
# creating a OpenStruct
ab = OpenStruct.new
p ab #=> #<OpenStruct>
ab.foo = 25
p ab.foo #=> 25
ab[:bar] = 2
p ab["bar"] #=> 2
p ab #=> #<OpenStruct foo=25, bar=2>
ab.delete_field("foo")
p ab.foo #=> nil
p ab #=> #<OpenStruct bar=2>
p son = OpenStruct.new({ :name => "Thomas", :age => 3 })
#=> #<OpenStruct name="Thomas", age=3>
p son.name #=> "Thomas"
p son[:age] #=> 3
son.age += 1
p son.age #=> 4
son.items = ["candy","toy"]
p son.items #=> ["candy","toy"]
p son #=> #<OpenStruct name="Thomas", age=4, items=["candy", "toy"]Rust
Rust has quite a few collections built in.
Stack-allocated collections
Array
Arrays ([T]) are stack allocated, fixed size collections of items of the same type.
let a = [1u8,2,3,4,5]; // a is of type [u8; 5];
let b = [0;256] // Equivalent to `let b = [0,0,0,0,0,0... repeat 256 times]`Slice
Slices (&[T]) are dynamically sized views into contiguous sequences (arrays, vectors, strings)
let array = [1,2,3,4,5];
let slice = &array[0..2]
println!("{:?}", slice);- Output:
[1,2]
String slice
String slices are (str) are slices of Unicode characters. Plain strs are almost never seen in Rust. Instead either heap-allocated Strings or borrowed string slices (&str which is basically equivalent to a slice of bytes: &[u8]) are more often used. It should be noted that strings are not indexable as they are UTF-8 (meaning that characters are not necessarily of a fixed size) however iterators can be created over codepoints or graphemes.
Heap-allocated collections
Vector
Vectors (Vec<T>) are a growable list type. According to the Rust documentation, you want to use a Vector if:
- You want to collect items up to be processed or sent elsewhere later, and don't care about any properties of the actual values being stored.
- You want a sequence of elements in a particular order, and will only be appending to (or near) the end.
- You want a stack.
- You want a resizable array.
- You want a heap-allocated array.
let mut v = Vec::new();
v.push(1);
v.push(2);
v.push(3);
// Or (mostly) equivalently via a convenient macro in the standard library
let v = vec![1,2,3];String
Strings are growable strings stored as a UTF-8 buffer which are just Vec<u8>s under the hood. Like strs, they are not indexable (for the same reasons) but iterators can be created over the graphemes, codepoints or bytes therein.
let x = "abc"; // x is of type &str (a borrowed string slice)
let s = String::from(x);
// or alternatively
let s = x.to_owned();VecDequeue
A growable ring buffer. According to the Rust documentation you should use VecDequeue<T> when:
- You want a Vec that supports efficient insertion at both ends of the sequence.
- You want a queue.
- You want a double-ended queue (deque).
Linked List
A doubly-linked list. According to the Rust documentation, you should use it when:
- You want a Vec or VecDeque of unknown size, and can't tolerate amortization.
- You want to efficiently split and append lists.
- You are absolutely certain you really, truly, want a doubly linked list.
HashMap
A hash map implementation which uses linear probing with Robin Hood bucket stealing. According to the Rust documentation, you should use it when:
- You want to associate arbitrary keys with an arbitrary value.
- You want a cache.
- You want a map, with no extra functionality.
BTreeMap
A map based on a B-Tree. According to the Rust documentation, you should use it when:
- You're interested in what the smallest or largest key-value pair is.
- You want to find the largest or smallest key that is smaller or larger than something.
- You want to be able to get all of the entries in order on-demand.
- You want a sorted map.
HashSet/BTreeSet
Set implementations that use an empty tuple () as the value of their respective maps (and implement different methods). They should be used when:
- You just want to remember which keys you've seen.
- There is no meaningful value to associate with your keys.
- You just want a set.
BinaryHeap
A priority queue implemented with a binary heap. You should use it when
- You want to store a bunch of elements, but only ever want to process the "biggest" or "most important" one at any given time.
- You want a priority queue.
Scala
Scala has in his run-time library a rich set set of collections. Due to use of traits is this library easily realized and consistent. Collections provide the same operations on any type where it makes sense to do so. For instance, a string is conceptually a sequence of characters. Consequently, in Scala collections, strings support all sequence operations. The same holds for arrays.
The collections are available in two flavors; immutable (these have no methods to modify or update) and mutable. With these properties they are also available in concurrent version for parallel processing. Switching between sequential and parallel can easily be done by adding a .seq or .par post-fix.
These examples were taken from a Scala REPL session. The second lines are the REPL responces.
Windows PowerShell
Copyright (C) 2012 Microsoft Corporation. All rights reserved.
PS C:\Users\FransAdm> scala
Welcome to Scala version 2.10.1 (Java HotSpot(TM) 64-Bit Server VM, Java 1.7.0_25).
Type in expressions to have them evaluated.
Type :help for more information.
scala> // Immutable collections do not and cannot change the instantiated object
scala> // Lets start with Lists
scala> val list = Nil // Empty List
list: scala.collection.immutable.Nil.type = List()
scala> val list2 = List("one", "two") // List with two elements (Strings)
list2: List[String] = List(one, two)
scala> val list3 = 3 :: list2 // prepend 3 to list2, using a special operator
list3: List[Any] = List(3, one, two)
scala> // The result was a mixture with a Int and Strings, so the common superclass Any is used.
scala> // Let test the Set collection
scala> val set = Set.empty[Char] // Empty Set of Char type
set: scala.collection.immutable.Set[Char] = Set()
scala> val set1 = set + 'c' // add an element
set1: scala.collection.immutable.Set[Char] = Set(c)
scala> val set2 = set + 'a' + 'c' + 'c' // try to add another and the same element twice
set2: scala.collection.immutable.Set[Char] = Set(a, c)
scala> // Let's look at the most universal map: TrieMap (Cache-aware lock-free concurrent hash trie)
scala> val capital = collection.concurrent.TrieMap("US" -> "Washington", "France" -> "Paris") // This map is mutable
capital: scala.collection.concurrent.TrieMap[String,String] = TrieMap(US -> Washington, France -> Paris)
scala> capital - "France" // This is only an expression, does not modify the map itself
res0: scala.collection.concurrent.TrieMap[String,String] = TrieMap(US -> Washington)
scala> capital += ("Tokio" -> "Japan") // Adding an element, object is changed - not the val capital
res1: capital.type = TrieMap(US -> Washington, Tokio -> Japan, France -> Paris)
scala> capital // Check what we have sofar
res2: scala.collection.concurrent.TrieMap[String,String] = TrieMap(US -> Washington, Tokio -> Japan, France -> Paris)
scala> val queue = new scala.collection.mutable.Queue[String]
queue: scala.collection.mutable.Queue[String] = Queue()
scala> queue += "first"
res17: queue.type = Queue("first")
scala> queue += "second"
res19: queue.type = Queue("first", "second")
scala> import collection.concurrent.TrieMap
// super concurrent mutable hashmap
val map = TrieMap("Amsterdam" -> "Netherlands",
"New York" -> "USA",
"Heemstede" -> "Netherlands")
map("Laussanne") = "Switzerland" // 2 Ways of updating
map += ("Tokio" -> "Japan")
assert(map("New York") == "USA")
assert(!map.isDefinedAt("Gent")) // isDefinedAt is false
assert(map.isDefinedAt("Laussanne")) // true
val hash = new TrieMap[Int, Int]
hash(1) = 2
hash += (1 -> 2) // same as hash(1) = 2
hash += (3 -> 4, 5 -> 6, 44 -> 99)
hash(44) // 99
hash.contains(33) // false
hash.isDefinedAt(33) // same as contains
hash.contains(44) // true
// iterate over key/value
// hash.foreach { case (key, val) => println( "key " + e._1 + " value " + e._2) } // e is a 2 element Tuple
// same with for syntax
for ((k, v) <- hash) println("key " + k + " value " + v)
// // items in map where the key is greater than 3
map.filter { k => k._1 > 3 } // Map(5 -> 6, 44 -> 99)
// // same with for syntax
for ((k, v) <- map; if k > 3) yield (k, v)Scheme
list
(list obj ...)returns a newly allocated list of its arguments.
Example:
(display (list 1 2 3))
(newline)
(display (list))
(newline)- Output:
(1 2 3) ()
cons
(cons obj lst)returns a newly allocated list consisting of obj prepended to lst.
Example:
(display (cons 0 (list 1 2 3)))
(newline)- Output:
(0 1 2 3)
append
(append lst ...)returns a newly allocated list consisting of the elements of lst followed by the elements of the other lists.
Example:
(display (append (list 1 2 3) (list 4 5 6)))
(newline)- Output:
(1 2 3 4 5 6)
Seed7
set
$ include "seed7_05.s7i";
enable_output(set of string);
const proc: main is func
local
var set of string: aSet is {"iron", "copper"};
begin
writeln(aSet);
incl(aSet, "silver");
writeln(aSet);
end func;array
$ include "seed7_05.s7i";
const proc: main is func
local
var array string: anArray is [] ("iron", "copper");
var string: element is "";
begin
for element range anArray do
write(element <& " ");
end for;
writeln;
anArray &:= "silver";
for element range anArray do
write(element <& " ");
end for;
writeln;
end func;hash
$ include "seed7_05.s7i";
const type: aHashType is hash [string] string;
const proc: main is func
local
var aHashType: aHash is aHashType.value;
var string: aValue is "";
var string: aKey is "";
begin
aHash @:= ["gold"] "metal";
aHash @:= ["helium"] "noble gas";
for aValue key aKey range aHash do
writeln(aKey <& ": " <& aValue);
end for;a
end func;Setl4
Set
set = new('set 5 10 15 20 25 25')
add(set,30)
show(set)
show.eval('member(set,5)')
show.eval('member(set,6)')
show.eval("exists(set,'eq(this,10)')")
show.eval("forall(set,'eq(this,40)')")Iter
iter = new('iter 1 10 2')
show(iter)
show.eval("eq(set.size(iter),5)")
show.eval('member(iter,5)')Map
map = new('map one:1 two:2 ten:10 forty:40 hundred:100 thousand:1000')
show(map)
show.eval("eq(get(map,'one'),1)")
show.eval("eq(get(map,'one'),6)")
show.eval("exists(map,'eq(get(map,this),2)')")
show.eval("forall(map,'eq(get(map,this),2)')")Sidef
Array
Arrays are ordered, integer-indexed collections of any object.
# creating an empty array and adding values
var a = [] #=> []
a[0] = 1 #=> [1]
a[3] = "abc" #=> [1, nil, nil, "abc"]
a << 3.14 #=> [1, nil, nil, "abc", 3.14]Hash
A Hash is a dictionary-like collection of unique keys and their values. Also called associative arrays, they are similar to Arrays, but where an Array uses integers as its index, a Hash allows you to use any object type, which is automatically converted into a String.
# creating an empty hash
var h = Hash() #=> Hash()
h{:foo} = 1 #=> Hash("foo"=>1)
h{:bar} = 2.4 #=> Hash("foo"=>1, "bar"=>2.4)
h{:bar} += 3 #=> Hash("foo"=>1, "bar"=>5.4)Pair
A Pair is an array-like collection, but restricted only to two elements.
# create a simple pair
var p = Pair('a', 'b')
say p.first; #=> 'a'
say p.second; #=> 'b'
# create a pair of pairs
var pair = 'foo':'bar':'baz':(); # => Pair('foo', Pair('bar', Pair('baz', nil)))
# iterate over the values of a pair of pairs
loop {
say pair.first; #=> 'foo', 'bar', 'baz'
pair = pair.second;
pair == nil && break;
}Struct
A Struct is a convenient way to bundle a number of attributes together.
# creating a struct
struct Person {
String name,
Number age,
String sex
}
var a = Person("John Smith", 41, :man)
a.age += 1 # increment age
a.name = "Dr. #{a.name}" # update name
say a.name #=> "Dr. John Smith"
say a.age #=> 42
say a.sex #=> "man"Slate
{1. 2. 3. 4. 5} collect: [|:x| x + 1]. "--> {2. 3. 4. 5. 6}"
{1. 2. 3. 4. 5} select: #isOdd `er. "--> {1. 3. 5}"
({3. 2. 7} collect: #+ `er <- 3) sort. "--> {"SortedArray traitsWindow" 5. 6. 10}"
ExtensibleArray new `>> [addLast: 3. addFirst: 4. ]. "--> {"ExtensibleArray traitsWindow" 4. 3}"Smalltalk
Smalltalk has several collection classes (indeed the class Collection is the parent of a long list of subclasses), being the word collection rather generic (an array indexed by integers is a collection too, and in some languages it's the only primitive collection available).
In this code I show how to add elements (which for each collection kind can be mixed) to five kind of Smalltalk collection:
- OrderedCollection: elements are kept in the order they are added;
- Bag: for each element, a count of how many times it appears is kept. So objects appear only once, but we can know how many we added in the bag;
- Set: a set. Elements appear only once, adding an existing object won't change the set; if we want to know if we added the same object several time, we use a Bag;
- SortedCollection: elements-objects are sorted (every comparable object can be added, and if we want different sorting criteria, we can give our custom comparator through sortBlock);
- Dictionary: objects are indexed by an arbitrary key, e.g. a string
|anOrdered aBag aSet aSorted aSorted2 aDictionary|
anOrdered := OrderedCollection new.
anOrdered add: 1; add: 5; add: 3.
anOrdered printNl.
aBag := Bag new.
aBag add: 5; add: 5; add: 5; add: 6.
aBag printNl.
aSet := Set new.
aSet add: 10; add: 5; add: 5; add: 6; add: 10.
aSet printNl.
aSorted := SortedCollection new.
aSorted add: 10; add: 9; add: 8; add: 5.
aSorted printNl.
"another sorted with custom comparator: let's sort
the other collections according to their size (number of
elements)"
aSorted2 := SortedCollection sortBlock: [ :a :b |
(a size) < (b size) ].
aSorted2 add: anOrdered; add: aBag; add: aSet; add: aSorted.
aSorted2 printNl.
aDictionary := Dictionary new.
aDictionary at: 'OrderedCollection' put: anOrdered;
at: 'Bag' put: aBag;
at: 'Set' put: aSet;
at: 'SortedCollection' put: { aSorted. aSorted2 }.
aDictionary printNl.Output:
OrderedCollection (1 5 3 )
Bag(5:3 6:1 )
Set (10 5 6 )
SortedCollection (5 8 9 10 )
SortedCollection (Set (10 5 6 ) OrderedCollection (1 5 3 ) Bag(5:3 6:1 ) SortedCollection (5 8 9 10 ) )
Dictionary (
'SortedCollection'->(SortedCollection (5 8 9 10 ) SortedCollection (Set (10 5 6 ) OrderedCollection (1 5 3 ) Bag(5:3 6:1 ) SortedCollection (5 8 9 10 ) ) )
'OrderedCollection'->OrderedCollection (1 5 3 )
'Set'->Set (10 5 6 )
'Bag'->Bag(5:3 6:1 )
)
Tcl
Tcl has 3 fundamental collection types: list, array and dictionary.
A Tcl list is called an array in other languages (an integer-indexed list of values).
set c [list] ;# create an empty list
# fill it
lappend c 10 11 13
set c [linsert $c 2 "twelve goes here"]
# iterate over it
foreach elem $c {puts $elem}
# pass to a proc
proc show_size {l} {
puts [llength $l]
}
show_size $cA Tcl array is an associative array (aka hash). Arrays are collections of variables indexable by name, and not collections of values. An array cannot be passed to a procedure be value: it must either be passed by name or by its serialized representation. Tcl arrays also are strictly one-dimensional: arrays cannot be nested. However, multi-dimensional arrays can be simulated with cleverly constructed key strings.
# create an empty array
array set h {}
# add some pair
set h(one) 1
set h(two) 2
# add more data
array set h {three 3 four 4 more {5 6 7 8}}
# iterate over it in a couple of ways
foreach key [array names h] {puts "$key -> $h($key)"}
foreach {key value} [array get h] {puts "$key -> $value"}
# pass by name
proc numkeys_byname {arrayName} {
upvar 1 $arrayName arr
puts "array $arrayName has [llength [array names arr]] keys"
}
numkeys_byname h
# pass serialized
proc numkeys_bycopy {l} {
array set arr $l
puts "array has [llength [array names arr]] keys"
}
numkeys_bycopy [array get h]A Tcl dictionary is an associative array value that contains other values. Hence dictionaries can be nested and arbitrarily deep data structures can be created.
# create an empty dictionary
set d [dict create]
dict set d one 1
dict set d two 2
# create another
set e [dict create three 3 four 4]
set f [dict merge $d $e]
dict set f nested [dict create five 5 more [list 6 7 8]]
puts [dict get $f nested more] ;# ==> 6 7 8TUSCRIPT
$$ MODE TUSCRIPT
collection=*
DATA apple
DATA banana
DATA orange
morestuff=*
DATA peaches
DATA apple
collection=APPEND(collection,morestuff)
TRACE *collectionOutput:
collection = *
1 = apple
2 = banana
3 = orange
4 = peaches
5 = apple
UNIX Shell
"Advanced" unix shells have indexed array and associative array collections.
Indexed arrays
a_index=(one two three) # create an array with a few elements
a_index+=(four five) # append some elements
a_index[9]=ten # add a specific index
for elem in "${a_index[@]}"; do # interate over the elements
echo "$elem"
done
for idx in "${!a_index[@]}"; do # interate over the array indices
printf "%d\t%s\n" $idx "${a_index[idx]}"
doneAssociative arrays
declare -A a_assoc=([one]=1 [two]=2 [three]=3) # create an array with a few elements
a_assoc+=([four]=4 [five]=5) # add some elements
a_assoc[ten]=10
for value in "${a_assoc[@]}"; do # interate over the values
echo "$value"
done
for key in "${!a_assoc[@]}"; do # interate over the array indices
printf "%s\t%s\n" "$key" "${a_assoc[$key]}"
doneChange
declare -Ato
typeset -AUrsala
There are several kinds of collections in Ursala that are supported by having their own operators and type constructors associated with them. All storage is immutable, but one may "add" to a collection by invoking a function that returns a new collection from it. The examples shown below populate the collections with primitive types expressed literally, but they could also be aggregate or abstract types, functions, symbolic names or expressions.
Lists
Lists are written as comma-separated sequences enclosed in angle brackets, or with the head and tail separated by a colon.
x = <1,5,6>
y = <'foo','bar'>
z = 3:<6,8>This function takes a pair of a new head and an existing list, and returns one that has the new head "added" to it.
foo ("newhead","existing-list") = "newhead":"existing-list"Sets
Sets are comma separated sequences enclosed in braces. The order and multiplicities of elements are ignored, so that the followng declarations are equivalent.
x = {'a','b'}
y = {'b','a'}
z = {'a','b','a'}Modules
Modules are lists in a particular form used to represent key:value pairs, with the key being a character string.
m = <'foo': 1,'bar': 2,'baz': 3>A module or any list of pairs can be reified into a function (a.k.a., a hash or finite map) and used in any context where a function is usable, assuming the keys are mutually distinct.
Trees
Trees are written in the form ^:,
where is the root and is a list of subtrees, which can
be of any length.
x =
'z'^: <
'x'^: <
'7'^: <>,
'?'^: <'D'^: <>>>,
'a'^: <'E'^: <>,'j'^: <>>,
'b'^: <'i'^: <>>,
'c'^: <>>A-trees
A-trees allow faster access than trees by using a different representation wherein data are stored only in the leaves at a constant depth.
x =
[
4:0: 'foo',
4:1: 'bar',
4:2: 'baz',
4:3: 'volta',
4:4: 'pramim']Grids
Grids are similar to lists of A-trees satisfying certain additional invariants. They represent a rooted, directed graph in which the nodes are partitioned by levels and edges exist only between nodes in consecutive levels. This type of data structure is ubiquitous in financial derivatives applications.
This example shows a grid of floating point numbers. The colon separated numbers (e.g., 4:10) are used in grids of any type as addresses, with each node including a list of the addresses of its descendents in the next level.
g =
<
[0:0: -9.483639e+00^: <4:10,4:14>],
[
4:14: -9.681900e+00^: <4:15>,
4:10: 2.237330e+00^: <4:7>],
[
4:15: -2.007562e+00^: <5:5>,
4:7: 2.419021e+00^: <5:5,5:15>],
[
5:15: 8.215451e+00^: <11:118>,
5:5: 4.067704e+00^: <11:741>],
[
11:741: -7.608967e+00^: <8:68>,
11:118: -1.552837e+00^: <8:68,8:208>],
[
8:208: 5.348115e+00^: <4:7,4:9,4:12>,
8:68: -9.066821e+00^: <4:9,4:12>],
[
4:12: -3.460494e+00^: <>,
4:9: 2.840319e+00^: <>,
4:7: -2.181140e+00^: <>]>V
A quote is used for the same purpose in V
[4 3 2 1] 5 swap cons
=[5 4 3 2 1]VBA
VBA has a built in collection type
Dim coll As New Collection
coll.Add "apple"
coll.Add "banana"Vim Script
Vim Script has two collection types: List and Dictionary.
See Arrays for basic operations on a List and Associative_array/Creation for basic operations on a Dictionary.
Visual Basic .NET
Dim toys As New List(Of String)
toys.Add("Car")
toys.Add("Boat")
toys.Add("Train")Visual FoxPro
Visual FoxPro has a built in Collection class.
LOCAL loColl As Collection, o, a1, a2, a3
a1 = CREATEOBJECT("animal", "dog", 4)
a2 = CREATEOBJECT("animal", "chicken", 2)
a3 = CREATEOBJECT("animal", "snake", 0)
loColl = NEWOBJECT("Collection")
loColl.Add(a1)
loColl.Add(a2)
loColl.Add(a3)
FOR EACH o IN loColl FOXOBJECT
? o.Name, o.Legs
ENDFOR
DEFINE CLASS animal As Custom
Legs = 0
PROCEDURE Init(tcName, tnLegs)
THIS.Name = tcName
THIS.Legs = tnLegs
ENDPROC
ENDDEFINEWren
Wren has only Map(hash) and List(array).
var list = [] // Empty Array
list = [1, 2, 3, 4]
list.add(5)
list.clear()
list = [0] * 10
list.count // 10
var map = {}
map["key"] = "value"
map[3] = 31
map.count // 2
map.clear()
for (e in map.keys) {
// Do stuff
}Z80 Assembly
The Z80 can support collections of any type but the responsibility of memory management lies with the programmer, making some of them much more difficult to implement than others. Functions such as "append," etc. aren't implemented by default and differ for each data type. Most implementations of collections are very similar. We'll use lists as an example, but most of the same concepts, techniques, and limitations apply to other types of collections.
A list is just a consecutive section of memory. Lists are mutable if they are in RAM, and are immutable if they are in ROM. Whether they are located in RAM or in ROM depends mostly on the hardware that uses the Z80 CPU. (Typically, programs that are run from CD-ROM or floppy disks can create mutable lists using the method below, but ROM cartridges cannot, even if those cartridges have internal RAM.)
List:
byte 1,2,3,4,5To append to a list you need to know where it ends, unfortunately the CPU can't know this without some sort of metadata placed at the beginning of a list. In addition, it is important to have enough free space after a list to append to it successfully. Otherwise you'll "clobber" whatever is stored after the list, which could be other data or executable code. (The Z80 has no segfaults or memory protection of any kind; writes to ROM are silently ignored, and executable code in RAM is overwritten like any other mutable data.)
List:
byte 5 ;size byte
byte 1,2,3,4,5 ;the actual list
byte 0,0,0,0,0 ;free space
;NOTE: separating the above list into different rows is just for visual clarity - it makes no difference to the CPU!
AppendList:
;input: A = the value you wish to append. β
βld hl,List
ld a,(HL) ;get the size byte
ld b,a ;store in B to use as loop counter for DJNZ
inc hl ;increment HL past the "size byte" to the actual data.
βpush hl ;save this pointer for later
push af ;save the value we want to append for later.
GotoEndOfList:
βinc hl
βdjnz GotoEndOfList
;now, HL points to the first "free" byte.
pop af
ld (HL),a ;store at the end of the list
pop hl ;go back to beginning of the list.
inc (hl) ;add 1 to the size byte.
ret
zkl
Lists: L(1,2,3).append(4); //-->L(1,2,3,4), mutable list
Read only list: ROList(1,2,3).append(4); // creates two lists
Bit bucket: Data(0,Int,1,2,3) // three bytes
The "Int" means treat contents as a byte stream
Data(0,Int,"foo ","bar") //-->7 bytes
Data(0,Int,"foo ").append("bar") //ditto
Data(0,Int,"foo\n","bar").readln() //-->"foo\n"
Data(0,String,"foo ","bar") //-->9 bytes (2 \0s)
Data(0,String,"foo ").append("bar").readln() //-->"foo "- Programming Tasks
- Basic language learning
- Data Structures
- Clarified and Needing Review
- 11l
- 68000 Assembly
- ABAP
- Ada
- Ada.Containers.Doubly Linked Lists
- Ada.Containers.Vectors
- Aime
- ALGOL 68
- Apex
- Arturo
- AutoHotkey
- AWK
- Axe
- BBC BASIC
- Bc
- C
- C sharp
- C++
- Clojure
- COBOL
- Common Lisp
- D
- Delphi
- Diego
- DuckDB
- E
- EasyLang
- EchoLisp
- Elena
- Elixir
- Factor
- Fancy
- Forth
- Forth Foundation Library
- Fortran
- FreeBASIC
- FutureBasic
- Gambas
- Go
- Groovy
- Haskell
- Icon
- Unicon
- J
- Jakt
- Java
- JavaScript
- Jq
- Julia
- Kotlin
- Lingo
- Lisaac
- Logo
- Lua
- M2000 Interpreter
- Maple
- Mathematica
- Wolfram Language
- MATLAB
- Octave
- MiniScript
- MS SmallBasic
- NetRexx
- Nim
- Objeck
- Objective-C
- OCaml
- Oforth
- OoRexx
- Oz
- PARI/GP
- Pascal
- Classes
- Objects
- PascalABC.NET
- Perl
- Phix
- PHP
- Picat
- PicoLisp
- PL/I
- PowerShell
- Prolog
- PureBasic
- Python
- R
- Racket
- Raku
- Raven
- REXX
- Ring
- Ruby
- Rust
- Scala
- Scheme
- Seed7
- Setl4
- Sidef
- Slate
- Smalltalk
- Tcl
- TUSCRIPT
- UNIX Shell
- Ursala
- V
- VBA
- Vim Script
- Visual Basic .NET
- Visual FoxPro
- Wren
- Z80 Assembly
- Zkl
- Pages with too many expensive parser function calls