Priority queue: Difference between revisions

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{{draft task}}
A [[wp:Priority queue|priority queue]] is somewhat similar to a [[Queue|queue]], with an important distinction: each item is added to a priority queue with a priority level, and will be later removed from the queue with the highest priority element first. That is, the items are (conceptually) stored in the queue in priority order instead of in insertion order.
 
 
'''Task:''' Create a priority queue. The queue must support at least two operations:
;Task:
# Insertion. An element is added to the queue with a priority (a numeric value).
Create a priority queue.   The queue must support at least two operations:
# Top item removal. Deletes the element or one of the elements with the current top priority and return it.
:#   Insertion.   An element is added to the queue with a priority (a numeric value).
:#   Top item removal.   Deletes the element or one of the elements with the current top priority and return it.
 
 
Optionally, other operations may be defined, such as peeking (find what current top priority/top element is), merging (combining two priority queues into one), etc.
 
To test your implementation, insert a number of elements into the queue, each with some random priority. Then dequeue them sequentially; now the elements should be sorted by priority. You can use the following task/priority items as input data:
'''Priority''' '''Task'''
3 Clear drains
4 Feed cat
5 Make tea
1 Solve RC tasks
2 Tax return
 
To test your implementation, insert a number of elements into the queue, each with some random priority.
The implementation should try to be efficient. A typical implementation has O(log n) insertion and extraction time, where n is the number of items in the queue. You may choose to impose certain limits such as small range of allowed priority levels, limited capacity, etc. If so, discuss the reasons behind it.
 
Then dequeue them sequentially; now the elements should be sorted by priority.
 
You can use the following task/priority items as input data:
'''Priority''' '''Task'''
══════════ ════════════════
3 Clear drains
4 Feed cat
5 Make tea
1 Solve RC tasks
2 Tax return
 
 
The implementation should try to be efficient.   A typical implementation has   '''O(log n)'''   insertion and extraction time,   where   '''n'''   is the number of items in the queue.
 
You may choose to impose certain limits such as small range of allowed priority levels, limited capacity, etc.   If so, discuss the reasons behind it.
<br><br>
=={{header|11l}}==
{{trans|Python}}
 
<syntaxhighlight lang="11l">V items = [(3, ‘Clear drains’), (4, ‘Feed cat’), (5, ‘Make tea’), (1, ‘Solve RC tasks’), (2, ‘Tax return’)]
minheap:heapify(&items)
L !items.empty
print(minheap:pop(&items))</syntaxhighlight>
 
{{out}}
<pre>
(1, Solve RC tasks)
(2, Tax return)
(3, Clear drains)
(4, Feed cat)
(5, Make tea)
</pre>
 
=={{header|AArch64 Assembly}}==
{{works with|as|Raspberry Pi 3B version Buster 64 bits}}
<syntaxhighlight lang="aarch64 assembly">
/* ARM assembly AARCH64 Raspberry PI 3B */
/* program priorQueue64.s */
/*******************************************/
/* Constantes file */
/*******************************************/
/* for this file see task include a file in language AArch64 assembly*/
.include "../includeConstantesARM64.inc"
.equ NBMAXIELEMENTS, 100
/*******************************************/
/* Structures */
/********************************************/
/* example structure item */
.struct 0
item_priority: // priority
.struct item_priority + 8
item_address: // string address
.struct item_address + 8
item_fin:
/* example structure heap */
.struct 0
heap_size: // heap size
.struct heap_size + 8
heap_items: // structure of items
.struct heap_items + (item_fin * NBMAXIELEMENTS)
heap_fin:
/*********************************/
/* Initialized data */
/*********************************/
.data
szMessEmpty: .asciz "Empty queue. \n"
szMessNotEmpty: .asciz "Not empty queue. \n"
szMessError: .asciz "Error detected !!!!. \n"
szMessResult: .asciz "Priority : @ : @ \n" // message result
szString1: .asciz "Clear drains"
szString2: .asciz "Feed cat"
szString3: .asciz "Make tea"
szString4: .asciz "Solve RC tasks"
szString5: .asciz "Tax return"
szCarriageReturn: .asciz "\n"
/*********************************/
/* UnInitialized data */
/*********************************/
.bss
.align 4
sZoneConv: .skip 24
Queue1: .skip heap_fin // queue memory place
/*********************************/
/* code section */
/*********************************/
.text
.global main
main: // entry of program
ldr x0,qAdrQueue1 // queue structure address
bl isEmpty
cbz x0,1f
ldr x0,qAdrszMessEmpty
bl affichageMess // display message empty
b 2f
1:
ldr x0,qAdrszMessNotEmpty
bl affichageMess // display message not empty
2:
// init item 1
ldr x0,qAdrQueue1 // queue structure address
mov x1,#3 // priority
ldr x2,qAdrszString1
bl pushQueue // add item in queue
cmp x0,#-1 // error ?
beq 99f
ldr x0,qAdrQueue1 // queue structure address
bl isEmpty
cbz x0,3f // not empty
ldr x0,qAdrszMessEmpty
bl affichageMess // display message empty
b 4f
3:
ldr x0,qAdrszMessNotEmpty
bl affichageMess // display message not empty
4:
// init item 2
ldr x0,qAdrQueue1 // queue structure address
mov x1,#4 // priority
ldr x2,qAdrszString2
bl pushQueue // add item in queue
cmp x0,#-1 // error ?
beq 99f
// init item 3
ldr x0,qAdrQueue1 // queue structure address
mov x1,#5 // priority
ldr x2,qAdrszString3
bl pushQueue // add item in queue
cmp x0,#-1 // error ?
beq 99f
// init item 4
ldr x0,qAdrQueue1 // queue structure address
mov x1,#1 // priority
ldr x2,qAdrszString4
bl pushQueue // add item in queue
cmp x0,#-1 // error ?
beq 99f
// init item 5
ldr x0,qAdrQueue1 // queue structure address
mov x1,#2 // priority
ldr x2,qAdrszString5
bl pushQueue // add item in queue
cmp x0,#-1 // error ?
beq 99f
5:
ldr x0,qAdrQueue1 // queue structure address
bl popQueue // return item
cmp x0,#-1 // end ?
beq 100f
mov x2,x1 // save string address
ldr x1,qAdrsZoneConv // conversion priority
bl conversion10 // decimal conversion
ldr x0,qAdrszMessResult
ldr x1,qAdrsZoneConv
bl strInsertAtCharInc
mov x1,x2 // string address
bl strInsertAtCharInc
bl affichageMess // display message
b 5b // loop
99: // error
ldr x0,qAdrszMessError
bl affichageMess
100: // standard end of the program
mov x0, #0 // return code
mov x8, #EXIT // request to exit program
svc #0 // perform the system call
qAdrQueue1: .quad Queue1
qAdrszString1: .quad szString1
qAdrszString2: .quad szString2
qAdrszString3: .quad szString3
qAdrszString4: .quad szString4
qAdrszString5: .quad szString5
qAdrszMessError: .quad szMessError
qAdrszMessEmpty: .quad szMessEmpty
qAdrszMessNotEmpty: .quad szMessNotEmpty
qAdrszMessResult: .quad szMessResult
qAdrszCarriageReturn: .quad szCarriageReturn
//qAdrsMessPriority: .quad sMessPriority
qAdrsZoneConv: .quad sZoneConv
/******************************************************************/
/* test if queue empty */
/******************************************************************/
/* x0 contains the address of queue structure */
isEmpty:
stp x1,lr,[sp,-16]! // save registres
ldr x1,[x0,#heap_size] // heap size
cmp x1,#0
cset x0,eq
ldp x1,lr,[sp],16 // restaur des 2 registres
ret
/******************************************************************/
/* add item in queue */
/******************************************************************/
/* x0 contains the address of queue structure */
/* x1 contains the priority of item */
/* x2 contains the string address */
pushQueue:
stp x1,lr,[sp,-16]! // save registres
stp x2,x3,[sp,-16]! // save registres
stp x4,x5,[sp,-16]! // save registres
stp x6,x7,[sp,-16]! // save registres
stp x8,x9,[sp,-16]! // save registres
ldr x3,[x0,#heap_size] // heap size
cbnz x3,1f // heap empty ?
add x4,x0,#heap_items // address of item structure
str x1,[x4,#item_priority] // store in first item
str x2,[x4,#item_address]
mov x3,#1 // heap size
str x3,[x0,#heap_size] // new heap size
b 100f
1:
mov x4,x3 // maxi index
lsr x5,x4,#1 // current index = maxi / 2
mov x8,x1 // save priority
mov x9,x2 // save string address
2: // insertion loop
cmp x4,#0 // end loop ?
ble 3f
mov x6,#item_fin // item size
madd x6,x5,x6,x0 // item shift
add x6,x6,#heap_items // compute address item
ldr x7,[x6,#item_priority] // load priority
cmp x7,x8 // compare priority
ble 3f // <= end loop
mov x1,x4 // last index
mov x2,x5 // current index
bl exchange
mov x4,x5 // last index = current index
lsr x5,x5,#1 // current index / 2
b 2b
3: // store item at last index find
mov x6,#item_fin // item size
madd x6,x4,x6,x0 // item shift
add x6,x6,#heap_items // item address
str x8,[x6,#item_priority]
str x9,[x6,#item_address]
add x3,x3,#1 // increment heap size
cmp x3,#NBMAXIELEMENTS // maxi ?
bge 99f // yes -> error
str x3,[x0,#heap_size] // store new size
b 100f
99:
mov x0,#-1 // error
100:
ldp x8,x9,[sp],16 // restaur des 2 registres
ldp x6,x7,[sp],16 // restaur des 2 registres
ldp x4,x5,[sp],16 // restaur des 2 registres
ldp x2,x3,[sp],16 // restaur des 2 registres
ldp x1,lr,[sp],16 // restaur des 2 registres
ret
/******************************************************************/
/* swap two elements of table */
/******************************************************************/
/* x0 contains the address of table */
/* x1 contains the first index */
/* x2 contains the second index */
exchange:
stp x1,lr,[sp,-16]! // save registres
stp x2,x3,[sp,-16]! // save registres
stp x4,x5,[sp,-16]! // save registres
stp x6,x7,[sp,-16]! // save registres
add x5,x0,#heap_items // address items begin
mov x3,#item_fin // item size
madd x4,x1,x3,x5 // compute item 1 address
madd x6,x2,x3,x5 // compute item 2 address
ldr x5,[x4,#item_priority] // exchange
ldr x3,[x6,#item_priority]
str x3,[x4,#item_priority]
str x5,[x6,#item_priority]
ldr x5,[x4,#item_address]
ldr x3,[x6,#item_address]
str x5,[x6,#item_address]
str x3,[x4,#item_address]
100:
ldp x6,x7,[sp],16 // restaur des 2 registres
ldp x4,x5,[sp],16 // restaur des 2 registres
ldp x2,x3,[sp],16 // restaur des 2 registres
ldp x1,lr,[sp],16 // restaur des 2 registres
ret
/******************************************************************/
/* move one element of table */
/******************************************************************/
/* x0 contains the address of table */
/* x1 contains the origin index */
/* x2 contains the destination index */
moveItem:
stp x1,lr,[sp,-16]! // save registres
stp x2,x3,[sp,-16]! // save registres
stp x4,x5,[sp,-16]! // save registres
stp x6,x7,[sp,-16]! // save registres
add x5,x0,#heap_items // address items begin
mov x3,#item_fin // item size
madd x4,x1,x3,x5 // compute item 1 address
madd x6,x2,x3,x5 // compute item 2 address
ldr x5,[x4,#item_priority] // exchange
str x5,[x6,#item_priority]
ldr x5,[x4,#item_address]
str x5,[x6,#item_address]
100:
ldp x6,x7,[sp],16 // restaur des 2 registres
ldp x4,x5,[sp],16 // restaur des 2 registres
ldp x2,x3,[sp],16 // restaur des 2 registres
ldp x1,lr,[sp],16 // restaur des 2 registres
ret
/******************************************************************/
/* pop queue */
/******************************************************************/
/* x0 contains the address of queue structure */
/* x0 return priority */
/* x1 return string address */
popQueue:
stp x10,lr,[sp,-16]! // save registres
stp x2,x3,[sp,-16]! // save registres
stp x4,x5,[sp,-16]! // save registres
stp x6,x7,[sp,-16]! // save registres
stp x8,x9,[sp,-16]! // save registres
mov x1,x0 // save address queue
bl isEmpty // control if empty queue
cmp x0,#1 // yes -> error
beq 99f
 
mov x0,x1 // restaur address queue
add x4,x0,#heap_items // address of item structure
ldr x8,[x4,#item_priority] // save priority first item
ldr x9,[x4,#item_address] // save address string first item
ldr x3,[x0,#heap_size] // heap size
sub x7,x3,#1 // last item
mov x1,x7
mov x2,#0 // first item
bl moveItem // move last item in first item
cmp x7,#1 // one only item ?
beq 10f // yes -> end
mov x4,#0 // first index
1:
cmp x4,x7 // = last index
bge 10f // yes -> end
mov x5,x7 // last index
cmp x4,#0 // init current index
mov x6,#1 // = 1
lsl x1,x4,#1 // else = first index * 2
csel x6,x6,x1,eq
cmp x6,x7 // current index > last index
bgt 2f // yes
// no compar priority current item last item
mov x1,#item_fin
madd x1,x6,x1,x0
add x1,x1,#heap_items // address of current item structure
ldr x1,[x1,#item_priority]
mov x10,#item_fin
madd x10,x5,x10,x0
add x10,x10,#heap_items // address of last item structure
ldr x10,[x10,#item_priority]
cmp x1,x10
csel x5,x6,x5,lt
2:
add x10,x6,#1 // increment current index
cmp x10,x7 // end ?
bgt 3f // yes
mov x1,#item_fin // no compare priority
madd x1,x10,x1,x0
add x1,x1,#heap_items // address of item structure
ldr x1,[x1,#item_priority]
mov x2,#item_fin
madd x2,x5,x2,x0
add x2,x2,#heap_items // address of item structure
ldr x2,[x2,#item_priority]
cmp x1,x2
csel x5,x10,x5,lt
3:
mov x1,x5 // move item
mov x2,x4
bl moveItem
mov x4,x5
b 1b // and loop
10:
sub x3,x3,#1
str x3,[x0,#heap_size] // new heap size
mov x0,x8 // return priority
mov x1,x9 // return string address
b 100f
99:
mov x0,#-1 // error
100:
ldp x8,x9,[sp],16 // restaur des 2 registres
ldp x6,x7,[sp],16 // restaur des 2 registres
ldp x4,x5,[sp],16 // restaur des 2 registres
ldp x2,x3,[sp],16 // restaur des 2 registres
ldp x10,lr,[sp],16 // restaur des 2 registres
ret
/********************************************************/
/* File Include fonctions */
/********************************************************/
/* for this file see task include a file in language AArch64 assembly */
.include "../includeARM64.inc"
</syntaxhighlight>
{{Output}}
<pre>
Empty queue.
Not empty queue.
Priority : 1 : Solve RC tasks
Priority : 2 : Tax return
Priority : 3 : Clear drains
Priority : 4 : Feed cat
Priority : 5 : Make tea
</pre>
 
=={{header|Action!}}==
The user must type in the monitor the following command after compilation and before running the program!<pre>SET EndProg=*</pre>
{{libheader|Action! Tool Kit}}
<syntaxhighlight lang="action!">CARD EndProg ;required for ALLOCATE.ACT
 
INCLUDE "D2:ALLOCATE.ACT" ;from the Action! Tool Kit. You must type 'SET EndProg=*' from the monitor after compiling, but before running this program!
 
DEFINE PTR="CARD"
DEFINE NODE_SIZE="5"
TYPE QueueNode=[
BYTE priority
PTR data ;CHAR ARRAY
PTR nxt]
 
QueueNode POINTER queueFront,queueRear
 
BYTE FUNC IsEmpty()
IF queueFront=0 THEN
RETURN (1)
FI
RETURN (0)
 
PROC Push(BYTE p CHAR ARRAY d)
QueueNode POINTER node,curr,prev
 
node=Alloc(NODE_SIZE)
node.priority=p
node.data=d
node.nxt=0
 
IF IsEmpty() THEN
queueFront=node
queueRear=node
RETURN
FI
 
curr=queueFront
prev=0
WHILE curr#0 AND curr.priority<=p
DO
prev=curr
curr=curr.nxt
OD
 
IF prev=0 THEN
queueFront=node
ELSEIF curr=0 THEN
queueRear.nxt=node
queueRear=node
ELSE
prev.nxt=node
FI
node.nxt=curr
RETURN
 
PTR FUNC Pop()
QueueNode POINTER node
IF IsEmpty() THEN
PrintE("Error: queue is empty!")
Break()
FI
 
node=queueFront
queueFront=node.nxt
RETURN (node)
 
PROC TestIsEmpty()
IF IsEmpty() THEN
PrintE("Queue is empty")
ELSE
PrintE("Queue is not empty")
FI
RETURN
 
PROC TestPush(BYTE p CHAR ARRAY d)
PrintF("Push priority=%B task=%S%E",p,d)
Push(p,d)
RETURN
 
PROC TestPop()
QueueNode POINTER node
 
node=Pop()
PrintF("Pop priority=%B task=%S%E",node.priority,node.data)
Free(node,NODE_SIZE)
RETURN
 
PROC Main()
AllocInit(0)
queueFront=0
queueRear=0
 
Put(125) PutE() ;clear screen
 
TestIsEmpty()
TestPush(3,"Clear drains")
TestPush(4,"Feed cat")
TestPush(5,"Make tea")
TestPush(1,"Solve RC tasks")
TestPush(2,"Tax return")
TestIsEmpty()
TestPop()
TestPop()
TestPop()
TestPop()
TestPop()
TestIsEmpty()
RETURN</syntaxhighlight>
{{out}}
[https://gitlab.com/amarok8bit/action-rosetta-code/-/raw/master/images/Priority_queue.png Screenshot from Atari 8-bit computer]
<pre>
Queue is empty
Push priority=3 task=Clear drains
Push priority=4 task=Feed cat
Push priority=5 task=Make tea
Push priority=1 task=Solve RC tasks
Push priority=2 task=Tax return
Queue is not empty
Pop priority=1 task=Solve RC tasks
Pop priority=2 task=Tax return
Pop priority=3 task=Clear drains
Pop priority=4 task=Feed cat
Pop priority=5 task=Make tea
Queue is empty
</pre>
 
=={{header|Ada}}==
{{works with|Ada 2012}}
Ada 2012 includes container classes for priority queues.
 
<syntaxhighlight lang="ada">with Ada.Containers.Synchronized_Queue_Interfaces;
with Ada.Containers.Unbounded_Priority_Queues;
with Ada.Strings.Unbounded;
with Ada.Text_IO;
 
procedure Priority_Queues is
use Ada.Containers;
use Ada.Strings.Unbounded;
type Queue_Element is record
Priority : Natural;
Content : Unbounded_String;
end record;
function Get_Priority (Element : Queue_Element) return Natural is
begin
return Element.Priority;
end Get_Priority;
function Before (Left, Right : Natural) return Boolean is
begin
return Left > Right;
end Before;
package String_Queues is new Synchronized_Queue_Interfaces
(Element_Type => Queue_Element);
package String_Priority_Queues is new Unbounded_Priority_Queues
(Queue_Interfaces => String_Queues,
Queue_Priority => Natural);
 
My_Queue : String_Priority_Queues.Queue;
begin
My_Queue.Enqueue (New_Item => (Priority => 3, Content => To_Unbounded_String ("Clear drains")));
My_Queue.Enqueue (New_Item => (Priority => 4, Content => To_Unbounded_String ("Feed cat")));
My_Queue.Enqueue (New_Item => (Priority => 5, Content => To_Unbounded_String ("Make tea")));
My_Queue.Enqueue (New_Item => (Priority => 1, Content => To_Unbounded_String ("Solve RC tasks")));
My_Queue.Enqueue (New_Item => (Priority => 2, Content => To_Unbounded_String ("Tax return")));
 
declare
Element : Queue_Element;
begin
while My_Queue.Current_Use > 0 loop
My_Queue.Dequeue (Element => Element);
Ada.Text_IO.Put_Line (Natural'Image (Element.Priority) & " => " & To_String (Element.Content));
end loop;
end;
end Priority_Queues;</syntaxhighlight>
 
{{out}}
<pre>
5 => Make tea
4 => Feed cat
3 => Clear drains
2 => Tax return
1 => Solve RC tasks
</pre>
 
=={{header|ARM Assembly}}==
{{works with|as|Raspberry Pi}}
<syntaxhighlight lang="arm assembly">
/* ARM assembly Raspberry PI */
/* program priorqueue.s */
 
/* Constantes */
.equ STDOUT, 1 @ Linux output console
.equ EXIT, 1 @ Linux syscall
.equ WRITE, 4 @ Linux syscall
 
.equ NBMAXIELEMENTS, 100
 
/*******************************************/
/* Structures */
/********************************************/
/* example structure item */
.struct 0
item_priority: @ priority
.struct item_priority + 4
item_address: @ string address
.struct item_address + 4
item_fin:
/* example structure heap */
.struct 0
heap_size: @ heap size
.struct heap_size + 4
heap_items: @ structure of items
.struct heap_items + (item_fin * NBMAXIELEMENTS)
heap_fin:
 
 
/*********************************/
/* Initialized data */
/*********************************/
.data
szMessEmpty: .asciz "Empty queue. \n"
szMessNotEmpty: .asciz "Not empty queue. \n"
szMessError: .asciz "Error detected !!!!. \n"
szMessResult: .ascii "Priority : " @ message result
sMessPriority: .fill 11, 1, ' '
.asciz " : "
 
szString1: .asciz "Clear drains"
szString2: .asciz "Feed cat"
szString3: .asciz "Make tea"
szString4: .asciz "Solve RC tasks"
szString5: .asciz "Tax return"
szCarriageReturn: .asciz "\n"
/*********************************/
/* UnInitialized data */
/*********************************/
.bss
.align 4
Queue1: .skip heap_fin @ queue memory place
/*********************************/
/* code section */
/*********************************/
.text
.global main
main: @ entry of program
ldr r0,iAdrQueue1 @ queue structure address
bl isEmpty
cmp r0,#0
beq 1f
ldr r0,iAdrszMessEmpty
bl affichageMess @ display message empty
b 2f
1:
ldr r0,iAdrszMessNotEmpty
bl affichageMess @ display message not empty
2:
@ init item 1
ldr r0,iAdrQueue1 @ queue structure address
mov r1,#3 @ priority
ldr r2,iAdrszString1
bl pushQueue @ add item in queue
cmp r0,#-1 @ error ?
beq 99f
 
ldr r0,iAdrQueue1 @ queue structure address
bl isEmpty
cmp r0,#0 @ not empty
beq 3f
ldr r0,iAdrszMessEmpty
bl affichageMess @ display message empty
b 4f
3:
ldr r0,iAdrszMessNotEmpty
bl affichageMess @ display message not empty
 
4:
@ init item 2
ldr r0,iAdrQueue1 @ queue structure address
mov r1,#4 @ priority
ldr r2,iAdrszString2
bl pushQueue @ add item in queue
cmp r0,#-1 @ error ?
beq 99f
@ init item 3
ldr r0,iAdrQueue1 @ queue structure address
mov r1,#5 @ priority
ldr r2,iAdrszString3
bl pushQueue @ add item in queue
cmp r0,#-1 @ error ?
beq 99f
@ init item 4
ldr r0,iAdrQueue1 @ queue structure address
mov r1,#1 @ priority
ldr r2,iAdrszString4
bl pushQueue @ add item in queue
cmp r0,#-1 @ error ?
beq 99f
@ init item 5
ldr r0,iAdrQueue1 @ queue structure address
mov r1,#2 @ priority
ldr r2,iAdrszString5
bl pushQueue @ add item in queue
cmp r0,#-1 @ error ?
beq 99f
5:
ldr r0,iAdrQueue1 @ queue structure address
bl popQueue @ return item
cmp r0,#-1 @ end ?
beq 100f
mov r2,r1 @ save string address
ldr r1,iAdrsMessPriority @ conversion priority
bl conversion10 @ decimal conversion
ldr r0,iAdrszMessResult
bl affichageMess @ display message
mov r0,r2 @ string address
bl affichageMess @ display message
ldr r0,iAdrszCarriageReturn
bl affichageMess
 
b 5b @ loop
99:
@ error
ldr r0,iAdrszMessError
bl affichageMess
100: @ standard end of the program
mov r0, #0 @ return code
mov r7, #EXIT @ request to exit program
svc #0 @ perform the system call
 
iAdrQueue1: .int Queue1
iAdrszString1: .int szString1
iAdrszString2: .int szString2
iAdrszString3: .int szString3
iAdrszString4: .int szString4
iAdrszString5: .int szString5
iAdrszMessError: .int szMessError
iAdrszMessEmpty: .int szMessEmpty
iAdrszMessNotEmpty: .int szMessNotEmpty
iAdrszMessResult: .int szMessResult
iAdrszCarriageReturn: .int szCarriageReturn
iAdrsMessPriority: .int sMessPriority
 
/******************************************************************/
/* test if queue empty */
/******************************************************************/
/* r0 contains the address of queue structure */
isEmpty:
push {r1,lr} @ save registres
ldr r1,[r0,#heap_size] @ heap size
cmp r1,#0
moveq r0,#1 @ empty queue
movne r0,#0 @ not empty
pop {r1,lr} @ restaur registers
bx lr @ return
/******************************************************************/
/* add item in queue */
/******************************************************************/
/* r0 contains the address of queue structure */
/* r1 contains the priority of item */
/* r2 contains the string address */
pushQueue:
push {r1-r9,lr} @ save registres
ldr r3,[r0,#heap_size] @ heap size
cmp r3,#0 @ heap empty ?
bne 1f
add r4,r0,#heap_items @ address of item structure
str r1,[r4,#item_priority] @ store in first item
str r2,[r4,#item_address]
mov r3,#1 @ heap size
str r3,[r0,#heap_size] @ new heap size
b 100f
1:
mov r4,r3 @ maxi index
lsr r5,r4,#1 @ current index = maxi / 2
mov r8,r1 @ save priority
mov r9,r2 @ save string address
2: @ insertion loop
cmp r4,#0 @ end loop ?
ble 3f
mov r6,#item_fin @ item size
mul r6,r5,r6 @ item shift
add r6,r0
add r6,#heap_items @ compute address item
ldr r7,[r6,#item_priority] @ load priority
cmp r7,r8 @ compare priority
ble 3f @ <= end loop
mov r1,r4 @ last index
mov r2,r5 @ current index
bl exchange
mov r4,r5 @ last index = current index
lsr r5,#1 @ current index / 2
b 2b
3: @ store item at last index find
mov r6,#item_fin @ item size
mul r6,r4,r6 @ item shift
add r6,r0
add r6,#heap_items @ item address
str r8,[r6,#item_priority]
str r9,[r6,#item_address]
add r3,#1 @ increment heap size
cmp r3,#NBMAXIELEMENTS @ maxi ?
movge r0,#-1 @ yes -> error
bge 100f
str r3,[r0,#heap_size] @ store new size
100:
pop {r1-r9,lr} @ restaur registers
bx lr @ return
/******************************************************************/
/* swap two elements of table */
/******************************************************************/
/* r0 contains the address of table */
/* r1 contains the first index */
/* r2 contains the second index */
exchange:
push {r3-r6,lr} @ save registers
add r5,r0,#heap_items @ address items begin
mov r3,#item_fin @ item size
mul r4,r1,r3 @ compute item 1 shift
add r4,r5 @ compute item 1 address
mul r6,r2,r3 @ compute item 2 shift
add r6,r5 @ compute item 2 address
ldr r5,[r4,#item_priority] @ exchange
ldr r3,[r6,#item_priority]
str r3,[r4,#item_priority]
str r5,[r6,#item_priority]
ldr r5,[r4,#item_address]
ldr r3,[r6,#item_address]
str r5,[r6,#item_address]
str r3,[r4,#item_address]
 
100:
pop {r3-r6,lr}
bx lr @ return
/******************************************************************/
/* move one element of table */
/******************************************************************/
/* r0 contains the address of table */
/* r1 contains the origin index */
/* r2 contains the destination index */
moveItem:
push {r3-r6,lr} @ save registers
add r5,r0,#heap_items @ address items begin
mov r3,#item_fin @ item size
mul r4,r1,r3 @ compute item 1 shift
add r4,r5 @ compute item 1 address
mul r6,r2,r3 @ compute item 2 shift
add r6,r5 @ compute item 2 address
ldr r5,[r4,#item_priority] @ exchange
str r5,[r6,#item_priority]
ldr r5,[r4,#item_address]
str r5,[r6,#item_address]
 
100:
pop {r3-r6,lr}
bx lr @ return
 
 
/******************************************************************/
/* pop queue */
/******************************************************************/
/* r0 contains the address of queue structure */
/* r0 return priority */
/* r1 return string address */
popQueue:
push {r2-r10,lr} @ save registres
mov r1,r0 @ save address queue
bl isEmpty @ control if empty queue
cmp r0,#1 @ yes -> error
moveq r0,#-1
beq 100f
@ save données à retourner
mov r0,r1 @ restaur address queue
add r4,r0,#heap_items @ address of item structure
ldr r8,[r4,#item_priority] @ save priority first item
ldr r9,[r4,#item_address] @ save address string first item
ldr r3,[r0,#heap_size] @ heap size
sub r7,r3,#1 @ last item
mov r1,r7
mov r2,#0 @ first item
bl moveItem @ move last item in first item
 
cmp r7,#1 @ one only item ?
beq 10f @ yes -> end
mov r4,#0 @ first index
1:
cmp r4,r7 @ = last index
bge 10f @ yes -> end
mov r5,r7 @ last index
cmp r4,#0 @ init current index
moveq r6,#1 @ = 1
lslne r6,r4,#1 @ else = first index * 2
cmp r6,r7 @ current index > last index
bgt 2f @ yes
@ no compar priority current item last item
mov r1,#item_fin
mul r1,r6,r1
add r1,r0
add r1,#heap_items @ address of current item structure
ldr r1,[r1,#item_priority]
mov r10,#item_fin
mul r10,r5,r10
add r10,r0
add r10,#heap_items @ address of last item structure
ldr r10,[r10,#item_priority]
cmp r1,r10
movlt r5,r6
2:
add r10,r6,#1 @ increment current index
cmp r10,r7 @ end ?
bgt 3f @ yes
mov r1,#item_fin @ no compare priority
mul r1,r10,r1
add r1,r0
add r1,#heap_items @ address of item structure
ldr r1,[r1,#item_priority]
mov r2,#item_fin
mul r2,r5,r2
add r2,r0
add r2,#heap_items @ address of item structure
ldr r2,[r2,#item_priority]
cmp r1,r2
movlt r5,r10
3:
mov r1,r5 @ move item
mov r2,r4
bl moveItem
mov r4,r5
b 1b @ and loop
10:
sub r3,#1
str r3,[r0,#heap_size] @ new heap size
mov r0,r8 @ return priority
mov r1,r9 @ return string address
100:
pop {r2-r10,lr} @ restaur registers
bx lr @ return
/******************************************************************/
/* display text with size calculation */
/******************************************************************/
/* r0 contains the address of the message */
affichageMess:
push {r0,r1,r2,r7,lr} @ save registres
mov r2,#0 @ counter length
1: @ loop length calculation
ldrb r1,[r0,r2] @ read octet start position + index
cmp r1,#0 @ if 0 its over
addne r2,r2,#1 @ else add 1 in the length
bne 1b @ and loop
@ so here r2 contains the length of the message
mov r1,r0 @ address message in r1
mov r0,#STDOUT @ code to write to the standard output Linux
mov r7, #WRITE @ code call system "write"
svc #0 @ call systeme
pop {r0,r1,r2,r7,lr} @ restaur registers */
bx lr @ return
/******************************************************************/
/* Converting a register to a decimal */
/******************************************************************/
/* r0 contains value and r1 address area */
.equ LGZONECAL, 10
conversion10:
push {r1-r4,lr} @ save registers
mov r3,r1
mov r2,#LGZONECAL
1: @ start loop
bl divisionpar10 @ r0 <- dividende. quotient ->r0 reste -> r1
add r1,#48 @ digit
strb r1,[r3,r2] @ store digit on area
cmp r0,#0 @ stop if quotient = 0
subne r2,#1 @ previous position
bne 1b @ else loop
@ end replaces digit in front of area
mov r4,#0
2:
ldrb r1,[r3,r2]
strb r1,[r3,r4] @ store in area begin
add r4,#1
add r2,#1 @ previous position
cmp r2,#LGZONECAL @ end
ble 2b @ loop
mov r1,#' '
3:
strb r1,[r3,r4]
add r4,#1
cmp r4,#LGZONECAL @ end
ble 3b
100:
pop {r1-r4,lr} @ restaur registres
bx lr @return
/***************************************************/
/* division par 10 signé */
/* Thanks to http://thinkingeek.com/arm-assembler-raspberry-pi/*
/* and http://www.hackersdelight.org/ */
/***************************************************/
/* r0 dividende */
/* r0 quotient */
/* r1 remainder */
divisionpar10:
/* r0 contains the argument to be divided by 10 */
push {r2-r4} @ save registers */
mov r4,r0
mov r3,#0x6667 @ r3 <- magic_number lower
movt r3,#0x6666 @ r3 <- magic_number upper
smull r1, r2, r3, r0 @ r1 <- Lower32Bits(r1*r0). r2 <- Upper32Bits(r1*r0)
mov r2, r2, ASR #2 @ r2 <- r2 >> 2
mov r1, r0, LSR #31 @ r1 <- r0 >> 31
add r0, r2, r1 @ r0 <- r2 + r1
add r2,r0,r0, lsl #2 @ r2 <- r0 * 5
sub r1,r4,r2, lsl #1 @ r1 <- r4 - (r2 * 2) = r4 - (r0 * 10)
pop {r2-r4}
bx lr @ return
</syntaxhighlight>
{{out}}
<pre>
Empty queue.
Not empty queue.
Priority : 1 : Solve RC tasks
Priority : 2 : Tax return
Priority : 3 : Clear drains
Priority : 4 : Feed cat
Priority : 5 : Make tea
</pre>
 
=={{header|Arturo}}==
 
<syntaxhighlight lang="arturo">define :item [priority, value][
print: [
~"(|this\priority|, |this\value|)"
]
]
define :queue [items][
init: [
this\items: arrange this\items 'it -> it\priority
]
]
 
empty?: function [this :queue][
zero? this\items
]
 
push: function [this :queue, item][
this\items: this\items ++ item
this\items: arrange this\items 'it -> it\priority
]
 
pop: function [this :queue][
ensure -> not? empty? this
result: this\items\0
this\items: remove.index this\items 0
return result
]
 
Q: to :queue @[to [:item] [
[3 "Clear drains"]
[4 "Feed cat"]
[5 "Make tea"]
[1 "Solve RC tasks"]
]]
 
push Q to :item [2 "Tax return"]
 
print ["queue is empty?" empty? Q]
print ""
 
while [not? empty? Q]->
print ["task:" pop Q]
 
print ""
print ["queue is empty?" empty? Q]</syntaxhighlight>
 
{{out}}
 
<pre>queue is empty? false
 
task: (1, Solve RC tasks)
task: (2, Tax return)
task: (3, Clear drains)
task: (4, Feed cat)
task: (5, Make tea)
 
queue is empty? true</pre>
 
=={{header|ATS}}==
 
I am treating more positive numbers as higher in priority, because that way the list of "Tasks" comes out in a plausible order. It is simple to reverse that order. (In fact, the direction of priorities could easily be made configurable by the template mechanism.)
 
Any value of type '''int''' may be used as a priority number.
 
<syntaxhighlight lang="ats">
(* NOTE: Others are treating more negative numbers as the higher
priority, but I think it is pretty clear that making tea and
feeding the cat are higher in priority than solving RC tasks.
So I treat more positive numbers as higher priority.
But see a note below on how easy it is to reverse that. *)
 
#include "share/atspre_staload.hats"
staload UN = "prelude/SATS/unsafe.sats"
 
(* For the sake of the task, use a heap implementation that comes with
the ATS distribution. *)
staload H = "libats/ATS1/SATS/funheap_binomial.sats"
 
(* #include instead of anonymous staload, to work around an
inconvenience in the distributed code: funheap_is_empty and
funheap_isnot_empty are functions rather than template
functions. One could instead compile funheap_binomial.dats
separately. Or one could copy and modify the distributed code to
one's own taste. (The heap code is GPL-3+) *)
#include "libats/ATS1/DATS/funheap_binomial.dats"
 
#define NIL list_nil ()
#define :: list_cons
 
abstype pqueue (a : t@ype+) = ptr
 
extern fn {}
pqueue_make_empty :
{a : t@ype}
() -<> pqueue a
 
extern fn {}
pqueue_is_empty :
{a : t@ype}
pqueue (INV(a)) -<> [b : bool] bool
 
extern fn {}
pqueue_isnot_empty :
{a : t@ype}
pqueue (INV(a)) -<> [b : bool] bool
 
extern fn {a : t@ype}
pqueue_size :
pqueue (INV(a)) -<> [n : nat] size_t n
 
extern fn {a : t@ype}
pqueue_insert :
(&pqueue (INV(a)) >> _, int, a) -< !wrt > void
 
extern fn {a : t@ype}
pqueue_delete :
(&pqueue (INV(a)) >> _) -< !wrt > Option a
 
extern fn {a : t@ype}
pqueue_peek :
(pqueue (INV(a))) -< !wrt > Option a
 
extern fn {a : t@ype}
pqueue_merge :
(pqueue (INV(a)), pqueue a) -< !wrt > pqueue a
 
local
 
typedef heap_elt (a : t@ype+) =
'{
(* The "priority" field must come first. We take advantage of
the layout of a '{..} being that of a C struct. *)
priority = int,
value = a
}
 
fn {a : t@ype}
heap_elt_get_priority (elt : heap_elt a)
:<> int =
let
typedef prio_t = '{ priority = int }
val prio = $UN.cast{prio_t} elt
in
prio.priority
end
 
extern castfn
pqueue2heap :
{a : t@ype}
pqueue a -<> $H.heap (heap_elt a)
 
extern castfn
heap2pqueue :
{a : t@ype}
$H.heap (heap_elt a) -<> pqueue a
 
macdef p2h = pqueue2heap
macdef h2p = heap2pqueue
 
macdef comparison_cloref =
lam (x, y) =<cloref>
let
val px = heap_elt_get_priority x
and py = heap_elt_get_priority y
in
(* NOTE: Reverse the order of the arguments, if you want more
negative numbers to represent higher priorities. *)
compare (py, px)
end
 
fn {a : t@ype}
funheap_getmin_opt (heap : $H.heap (INV(a)),
cmp : $H.cmp a)
:<!wrt> Option_vt a =
let
var result : a?
val success = $H.funheap_getmin<a> (heap, cmp, result)
in
if success then
let
prval () = opt_unsome{a} result
in
Some_vt{a} result
end
else
let
prval () = opt_unnone{a} result
in
None_vt{a} ()
end
end
 
in
 
implement {}
pqueue_make_empty {a} () =
h2p{a} ($H.funheap_make_nil {heap_elt a} ())
 
implement {}
pqueue_is_empty {a} pq =
$H.funheap_is_empty {heap_elt a} (p2h{a} pq)
 
implement {}
pqueue_isnot_empty {a} pq =
$H.funheap_isnot_empty {heap_elt a} (p2h{a} pq)
 
implement {a}
pqueue_size pq =
$H.funheap_size<heap_elt a> (p2h{a} pq)
 
implement {a}
pqueue_insert (pq, priority, x) =
let
val elt =
'{
priority = priority,
value = x
} : heap_elt a
and compare = comparison_cloref
var heap = p2h{a} pq
val () = $H.funheap_insert (heap, elt, compare)
in
pq := h2p{a} heap
end
 
implement {a}
pqueue_delete pq =
let
typedef t = heap_elt a
val compare = comparison_cloref
var heap = p2h{a} pq
val elt_opt = $H.funheap_delmin_opt<heap_elt a> (heap, compare)
in
pq := h2p{a} heap;
case+ elt_opt of
| ~ Some_vt elt => Some (elt.value)
| ~ None_vt () => None ()
end
 
implement {a}
pqueue_peek pq =
let
typedef t = heap_elt a
val compare = comparison_cloref
and heap = p2h{a} pq
val elt_opt = funheap_getmin_opt<heap_elt a> (heap, compare)
in
case+ elt_opt of
| ~ Some_vt elt => Some (elt.value)
| ~ None_vt () => None ()
end
 
implement {a}
pqueue_merge (pq1, pq2) =
let
val heap1 = p2h{a} pq1
and heap2 = p2h{a} pq2
and compare = comparison_cloref
in
h2p{a} ($H.funheap_merge<heap_elt a> (heap1, heap2, compare))
end
 
overload iseqz with pqueue_is_empty
overload isneqz with pqueue_isnot_empty
overload size with pqueue_size
overload insert with pqueue_insert
overload delete with pqueue_delete
overload peek with pqueue_peek
overload merge with pqueue_merge
 
end
 
implement
main0 () =
let
var pq = pqueue_make_empty{string} ()
val () = print! (" ", iseqz pq)
val () = print! (" ", isneqz pq)
val () = print! (" ", "size:", size pq)
val () = insert (pq, 3, "3")
val () = insert (pq, 4, "4")
val () = insert (pq, 2, "2")
val () = insert (pq, 5, "5")
val () = insert (pq, 1, "1")
val () = print! (" ", iseqz pq)
val () = print! (" ", isneqz pq)
val () = print! (" ", "size:", size pq)
 
var pq2 = pqueue_make_empty{string} ()
val () = insert (pq, 6, "6")
val () = insert (pq, 4, "4a")
 
val () = pq := merge (pq, pq2)
val () = print! (" ", iseqz pq)
val () = print! (" ", isneqz pq)
val () = print! (" ", "size:", size pq)
 
val- Some x = peek pq
val () = print! (" ", x)
val- Some x = peek pq
val () = print! (" ", x)
val- Some x = peek pq
val () = print! (" ", x)
val- Some x = peek pq
val () = print! (" ", x)
val- Some x = delete pq
val () = print! (" ", x)
val- Some x = delete pq
val () = print! (" ", x)
val- Some x = peek pq
val () = print! (" ", x)
val- Some x = peek pq
val () = print! (" ", x)
val- Some x = delete pq
val () = print! (" ", x)
val- Some x = peek pq
val () = print! (" ", x)
val- Some x = peek pq
val () = print! (" ", x)
val- Some x = peek pq
val () = print! (" ", x)
val- Some x = peek pq
val () = print! (" ", x)
val- Some x = delete pq
val () = print! (" ", x)
val- Some x = delete pq
val () = print! (" ", x)
val- Some x = delete pq
val () = print! (" ", x)
val- Some x = delete pq
val () = print! (" ", x)
val- None () = delete pq
 
val () = println! ()
 
var pq2 = pqueue_make_empty{string} ()
val () = insert (pq2, 3, "Clear drains")
val () = insert (pq2, 4, "Feed cat")
val () = insert (pq2, 5, "Make tea")
val () = insert (pq2, 1, "Solve RC tasks")
val () = insert (pq2, 2, "Tax return")
val- Some x = delete pq2
val () = println! ("|", x, "|")
val- Some x = delete pq2
val () = println! ("|", x, "|")
val- Some x = delete pq2
val () = println! ("|", x, "|")
val- Some x = delete pq2
val () = println! ("|", x, "|")
val- Some x = delete pq2
val () = println! ("|", x, "|")
in
end
</syntaxhighlight>
 
{{out}}
<pre>$ patscc -O3 -DATS_MEMALLOC_GCBDW priority-queue.dats -lgc && ./a.out
true false size:0 false true size:5 false true size:7 6 6 6 6 6 5 4a 4a 4a 4 4 4 4 4 3 2 1
|Make tea|
|Feed cat|
|Clear drains|
|Tax return|
|Solve RC tasks|
</pre>
 
=={{header|AutoHotkey}}==
<syntaxhighlight lang="autohotkey">;-----------------------------------
PQ_TopItem(Queue,Task:=""){ ; remove and return top priority item
TopPriority := PQ_TopPriority(Queue)
for T, P in Queue
if (P = TopPriority) && ((T=Task)||!Task)
return T , Queue.Remove(T)
return 0
}
;-----------------------------------
PQ_AddTask(Queue,Task,Priority){ ; insert and return new task
for T, P in Queue
if (T=Task) || !(Priority && Task)
return 0
return Task, Queue[Task] := Priority
}
;-----------------------------------
PQ_DelTask(Queue, Task){ ; delete and return task
for T, P in Queue
if (T = Task)
return Task, Queue.Remove(Task)
}
;-----------------------------------
PQ_Peek(Queue){ ; peek and return top priority task(s)
TopPriority := PQ_TopPriority(Queue)
for T, P in Queue
if (P = TopPriority)
PeekList .= (PeekList?"`n":"") "`t" T
return PeekList
}
;-----------------------------------
PQ_Check(Queue,Task){ ; check task and return its priority
for T, P in Queue
if (T = Task)
return P
return 0
}
;-----------------------------------
PQ_Edit(Queue,Task,Priority){ ; Update task priority and return its new priority
for T, P in Queue
if (T = Task)
return Priority, Queue[T]:=Priority
return 0
}
;-----------------------------------
PQ_View(Queue){ ; view current Queue
for T, P in Queue
Res .= P " : " T "`n"
Sort, Res, FMySort
return "Priority Queue=`n" Res
}
MySort(a,b){
RegExMatch(a,"(\d+) : (.*)", x), RegExMatch(b,"(\d+) : (.*)", y)
return x1>y1?1:x1<y1?-1: x2>y2?1:x2<y2?-1: 0
}
;-----------------------------------
PQ_TopPriority(Queue){ ; return queue's top priority
for T, P in Queue
TopPriority := TopPriority?TopPriority:P , TopPriority := TopPriority<P?TopPriority:P
return, TopPriority
}</syntaxhighlight>
Examples:<syntaxhighlight lang="autohotkey">data =
(
3 Clear drains
1 test
4 Feed cat
5 Make tea
1 Solve RC tasks
2 Tax return
)
PQ:=[] ; Create Priority Queue PQ[Task, Priority]
loop, parse, data, `n, `r
F:= StrSplit(A_LoopField, "`t") , PQ[F[2]] := F[1]
PQ_View(PQ)
MsgBox, 262208,, % "Top Priority item(s)=`n" PQ_Peek(PQ) "`n`n" PQ_View(PQ)
MsgBox, 262208,, % "Add : " PQ_AddTask(PQ, "AutoHotkey", 2) "`n`n" PQ_View(PQ)
MsgBox, 262208,, % "Remove Top Item : " PQ_TopItem(PQ) "`n`n" PQ_View(PQ)
MsgBox, 262208,, % "Remove specific top item : " PQ_TopItem(PQ,"test") "`n`n" PQ_View(PQ)
MsgBox, 262208,, % "Delete Item : " PQ_DelTask(PQ, "Clear drains") "`n`n" PQ_View(PQ)
MsgBox, 262208,, % (Task:="Tax return") " new priority = " PQ_Edit(PQ,task, 7) "`n`n" PQ_View(PQ)
MsgBox, 262208,, % (Task:="Feed cat") " priority = " PQ_Check(PQ,task)"`n`n" PQ_View(PQ)
^Esc::
ExitApp</syntaxhighlight>
 
=={{header|Axiom}}==
Axiom already has a heap domain for ordered sets.
We define a domain for ordered key-entry pairs and then define a priority queue using the heap domain over the pairs:
<syntaxhighlight lang="axiom">)abbrev Domain ORDKE OrderedKeyEntry
OrderedKeyEntry(Key:OrderedSet,Entry:SetCategory): Exports == Implementation where
Exports == OrderedSet with
construct: (Key,Entry) -> %
elt: (%,"key") -> Key
elt: (%,"entry") -> Entry
Implementation == add
Rep := Record(k:Key,e:Entry)
x,y: %
construct(a,b) == construct(a,b)$Rep @ %
elt(x,"key"):Key == (x@Rep).k
elt(x,"entry"):Entry == (x@Rep).e
x < y == x.key < y.key
x = y == x.key = y.key
hash x == hash(x.key)
if Entry has CoercibleTo OutputForm then
coerce(x):OutputForm == bracket [(x.key)::OutputForm,(x.entry)::OutputForm]
)abbrev Domain PRIORITY PriorityQueue
S ==> OrderedKeyEntry(Key,Entry)
PriorityQueue(Key:OrderedSet,Entry:SetCategory): Exports == Implementation where
Exports == PriorityQueueAggregate S with
heap : List S -> %
setelt: (%,Key,Entry) -> Entry
Implementation == Heap(S) add
setelt(x:%,key:Key,entry:Entry) ==
insert!(construct(key,entry)$S,x)
entry</syntaxhighlight>For an example:<syntaxhighlight lang="axiom">pq := empty()$PriorityQueue(Integer,String)
pq(3):="Clear drains";
pq(4):="Feed cat";
pq(5):="Make tea";
pq(1):="Solve RC tasks";
pq(2):="Tax return";
[extract!(pq) for i in 1..#pq]</syntaxhighlight>
{{out}}
<pre>
[[5,"Make tea"], [4,"Feed cat"], [3,"Clear drains"], [2,"Tax return"],
[1,"Solve RC tasks"]]
Type: List(OrderedKeyEntry(Integer,String))</pre>
 
=={{header|BASIC}}==
==={{header|FreeBASIC}}===
{{trans|VBA}}
<syntaxhighlight lang="freebasic">Type Tupla
Prioridad As Integer
Tarea As String
End Type
Dim Shared As Tupla a()
Dim Shared As Integer n 'número de eltos. en la matriz, el último elto. es n-1
 
Function Izda(i As Integer) As Integer
Izda = 2 * i + 1
End Function
 
Function Dcha(i As Integer) As Integer
Dcha = 2 * i + 2
End Function
 
Function Parent(i As Integer) As Integer
Parent = (i - 1) \ 2
End Function
 
Sub Intercambio(i As Integer, j As Integer)
Dim t As Tupla
t = a(i)
a(i) = a(j)
a(j) = t
End Sub
 
Sub bubbleUp(i As Integer)
Dim As Integer p = Parent(i)
Do While i > 0 And a(i).Prioridad < a(p).Prioridad
Intercambio i, p
i = p
p = Parent(i)
Loop
End Sub
 
Sub Annadir(fPrioridad As Integer, fTarea As String)
n += 1
If n > Ubound(a) Then Redim Preserve a(2 * n)
a(n - 1).Prioridad = fPrioridad
a(n - 1).Tarea = fTarea
bubbleUp (n - 1)
End Sub
 
Sub trickleDown(i As Integer)
Dim As Integer j, l, r
Do
j = -1
r = Dcha(i)
If r < n And a(r).Prioridad < a(i).Prioridad Then
l = Izda(i)
If a(l).Prioridad < a(r).Prioridad Then
j = l
Else
j = r
End If
Else
l = Izda(i)
If l < n And a(l).Prioridad < a(i).Prioridad Then j = l
End If
If j >= 0 Then Intercambio i, j
i = j
Loop While i >= 0
End Sub
 
Function Remove() As Tupla
Dim As Tupla x = a(0)
a(0) = a(n - 1)
n = n - 1
trickleDown 0
If 3 * n < Ubound(a) Then Redim Preserve a(Ubound(a) \ 2)
Remove = x
End Function
 
 
Redim a(4)
Annadir (3, "Clear drains")
Annadir (4, "Feed cat")
Annadir (5, "Make tea")
Annadir (1, "Solve RC tasks")
Annadir (2, "Tax return")
Dim t As Tupla
Do While n > 0
t = Remove
Print t.Prioridad; " "; t.Tarea
Loop
Sleep</syntaxhighlight>
{{out}}
<pre>
Igual que la entrada de VBA.
</pre>
 
=={{header|Batch File}}==
Batch has only a data structure, the environment that incidentally sorts itself automatically by key. The environment has a limit of 64K
<syntaxhighlight lang="batch file">
@echo off
setlocal enabledelayedexpansion
 
call :push 10 "item ten"
call :push 2 "item two"
call :push 100 "item one hundred"
call :push 5 "item five"
 
call :pop & echo !order! !item!
call :pop & echo !order! !item!
call :pop & echo !order! !item!
call :pop & echo !order! !item!
call :pop & echo !order! !item!
 
goto:eof
 
 
:push
set temp=000%1
set queu%temp:~-3%=%2
goto:eof
 
:pop
set queu >nul 2>nul
if %errorlevel% equ 1 (set order=-1&set item=no more items & goto:eof)
for /f "tokens=1,2 delims==" %%a in ('set queu') do set %%a=& set order=%%a& set item=%%~b& goto:next
:next
set order= %order:~-3%
goto:eof</syntaxhighlight>
{{out}}
<pre>
002 item two
005 item five
010 item ten
100 item one hundred
-1 no more items
</pre>
 
=={{header|C}}==
Using a dynamic array as a binary heap. Stores integer priority and a void datacharacter pointer. There's no limit on heap size besides integer overflow, although a very large heap will cause a lot of page faults. Supports insert, extraction, peeking at top element, mergingpush and clearingpop.
<langsyntaxhighlight lang="c">#include <stdio.h>
#include <stdlib.h>
 
typedef struct { void * data; int pri; } q_elem_t;
int priority;
typedef struct { q_elem_t *buf; int n, alloc; } pri_queue_t, *pri_queue;
char *data;
} node_t;
 
typedef struct {
#define priq_purge(q) (q)->n = 1
node_t *nodes;
#define priq_size(q) ((q)->n - 1)
int len;
/* first element in array not used to simplify indices */
pri_queue priq_new( int size);
} heap_t;
{
if (size < 4) size = 4;
 
void push (heap_t *h, int priority, char *data) {
pri_queue q = malloc(sizeof(pri_queue_t));
q if (h->buflen =+ malloc(sizeof(q_elem_t)1 *>= h->size); {
q h->allocsize = h->size ? h->size * 2 : 4;
h->nodes = (node_t *)realloc(h->nodes, h->size * sizeof (node_t));
q->n = 1;
}
int i = h->len + 1;
int j = i / 2;
while (i > 1 && h->nodes[j].priority > priority) {
h->nodes[i] = h->nodes[j];
i = j;
j = j / 2;
}
h->nodes[i].priority = priority;
h->nodes[i].data = data;
h->len++;
}
 
char *pop (heap_t *h) {
return q;
int i, j, k;
if (!h->len) {
return NULL;
}
char *data = h->nodes[1].data;
h->nodes[1] = h->nodes[h->len];
h->len--;
i = 1;
while (i!=h->len+1) {
k = h->len+1;
j = 2 * i;
if (j <= h->len && h->nodes[j].priority < h->nodes[k].priority) {
k = j;
}
if (j + 1 <= h->len && h->nodes[j + 1].priority < h->nodes[k].priority) {
k = j + 1;
}
h->nodes[i] = h->nodes[k];
i = k;
}
return data;
}
 
int main () {
void priq_push(pri_queue q, void *data, int pri)
heap_t *h = (heap_t *)calloc(1, sizeof (heap_t));
{
push(h, 3, "Clear drains");
q_elem_t *b;
push(h, 4, "Feed cat");
int n, m;
push(h, 5, "Make tea");
push(h, 1, "Solve RC tasks");
push(h, 2, "Tax return");
int i;
for (i = 0; i < 5; i++) {
printf("%s\n", pop(h));
}
return 0;
}
</syntaxhighlight>
{{output}}
<pre>Solve RC tasks
Tax return
Clear drains
Feed cat
Make tea</pre>
=== Pairing heap w/ generic data types ===
header file:
<syntaxhighlight lang="c">
typedef struct _pq_node_t {
long int key;
struct _pq_node_t *next, *down;
} pq_node_t, *heap_t;
 
extern heap_t heap_merge(heap_t, heap_t);
if (q->n >= q->alloc) {
extern heap_t heap_pop(heap_t);
q->alloc *= 2;
b = q->buf = realloc(q->buf, sizeof(q_elem_t) * q->alloc);
} else
b = q->buf;
 
#define NEW_PQ_ELE(p, k) \
n = q->n++;
do { \
/* append at end, then up heap */
(p) = (typeof(p)) malloc(sizeof(*p)); \
while ((m = n / 2) && pri < b[m].pri) {
((pq_node_t *) (p))->next = ((pq_node_t *) (p))->down = NULL; \
b[n] = b[m];
((pq_node_t *) (p))->key = (k); \
n = m;
} while (0)
}
 
b[n].data = data;
#define HEAP_PUSH(p, k, h) \
b[n].pri = pri;
NEW_PQ_ELE(p, k); \
*(h) = heap_merge(((pq_node_t *) (p)), *(h))
</syntaxhighlight>
implementation:
<syntaxhighlight lang="c">
#include <stdlib.h>
#include "pairheap.h"
 
/* ---------------------------------------------------------------------------
* Pairing heap implementation
* --------------------------------------------------------------------------- */
 
static heap_t add_child(heap_t h, heap_t g) {
if (h->down != NULL)
g->next = h->down;
h->down = g;
}
 
heap_t heap_merge(heap_t a, heap_t b) {
/* remove top item. returns 0 if empty. *pri can be null. */
if (a == NULL) return b;
void * priq_pop(pri_queue q, int *pri)
if (b == NULL) return a;
{
if (a->key < b->key) {
void *out;
add_child(a, b);
if (q->n == 1) return 0;
return a;
} else {
add_child(b, a);
return b;
}
}
 
/* NOTE: caller should have pointer to top of heap, since otherwise it won't
q_elem_t *b = q->buf;
* be reclaimed. (we do not free the top.)
*/
heap_t two_pass_merge(heap_t h) {
if (h == NULL || h->next == NULL)
return h;
else {
pq_node_t
*a = h,
*b = h->next,
*rest = b->next;
a->next = b->next = NULL;
return heap_merge(heap_merge(a, b), two_pass_merge(rest));
}
}
 
heap_t heap_pop(heap_t h) {
out = b[1].data;
return two_pass_merge(h->down);
if (pri) *pri = b[1].pri;
}
</syntaxhighlight>
usage:
<syntaxhighlight lang="c">
#include <stdio.h>
#include <string.h>
#include <stdlib.h>
#include "pairheap.h"
 
struct task {
/* pull last item to top, then down heap. */
pq_node_t hd;
--q->n;
char task[40];
};
 
void main() {
int n = 1, m;
heap_t heap = NULL;
while ((m = n * 2) < q->n) {
struct task *new;
if (m + 1 < q->n && b[m].pri > b[m + 1].pri) m++;
 
HEAP_PUSH(new, 3, &heap);
if (b[q->n].pri <= b[m].pri) break;
strcpy(new->task, "Clear drains.");
b[n] = b[m];
n = m;
}
 
HEAP_PUSH(new, 4, &heap);
b[n] = b[q->n];
strcpy(new->task, "Feed cat.");
if (q->n < q->alloc / 2 && q->n >= 16)
q->buf = realloc(q->buf, (q->alloc /= 2) * sizeof(b[0]));
 
HEAP_PUSH(new, 5, &heap);
return out;
strcpy(new->task, "Make tea.");
 
HEAP_PUSH(new, 1, &heap);
strcpy(new->task, "Solve RC tasks.");
 
HEAP_PUSH(new, 2, &heap);
strcpy(new->task, "Tax return.");
 
while (heap != NULL) {
struct task *top = (struct task *) heap;
printf("%s\n", top->task);
heap = heap_pop(heap);
free(top);
}
}
</syntaxhighlight>
{{Out}}
<pre>
Solve RC tasks.
Tax return.
Clear drains.
Feed cat.
Make tea.
</pre>
 
=={{header|C sharp}}==
/* get the top element without removing it from queue */
 
void* priq_top(pri_queue q, int *pri)
===.NET 6 solution===
<syntaxhighlight lang="csharp">using System;
using System.Collections.Generic;
 
namespace PriorityQueueExample
{
class Program
if (q->n == 1) return 0;
{
if (pri) *pri = q->buf[1].pri;
static void Main(string[] args)
return q->buf[1].data;
{
// Starting with .NET 6.0 preview 2 (released March 11th, 2021), there's a built-in priority queue
var p = new PriorityQueue<string, int>();
p.Enqueue("Clear drains", 3);
p.Enqueue("Feed cat", 4);
p.Enqueue("Make tea", 5);
p.Enqueue("Solve RC tasks", 1);
p.Enqueue("Tax return", 2);
while (p.TryDequeue(out string task, out int priority))
{
Console.WriteLine($"{priority}\t{task}");
}
}
}
}
 
/* Output:
/* this is O(n log n), but probably not the best */
void priq_combine(pri_queue q, pri_queue q2)
1 Solve RC tasks
{
2 Tax return
int i;
3 Clear drains
q_elem_t *e = q2->buf + 1;
4 Feed cat
5 Make tea
*/</syntaxhighlight>
 
===Pre-.NET 6 solution===
for (i = q2->n - 1; i >= 1; i--, e++)
<syntaxhighlight lang="csharp">using System;
priq_push(q, e->data, e->pri);
priq_purge(q2);
}
 
namespace PriorityQueue
int main()
{
class Program
int i, p;
{
char *c, *tasks[] ={
static void Main(string[] args)
"Clear drains", "Feed cat", "Make tea", "Solve RC tasks", "Tax return" };
int pri[] = { 3, 4, 5, 1, 2 };{
PriorityQueue PQ = new PriorityQueue();
PQ.push(3, "Clear drains");
PQ.push(4, "Feed cat");
PQ.push(5, "Make tea");
PQ.push(1, "Solve RC tasks");
PQ.push(2, "Tax return");
 
while (!PQ.Empty)
/* make two queues */
{
pri_queue q = priq_new(0), q2 = priq_new(0);
var Val = PQ.pop();
Console.WriteLine(Val[0] + " : " + Val[1]);
}
Console.ReadKey();
}
}
 
class PriorityQueue
/* push all 5 tasks into q */
{
for (i = 0; i < 5; i++)
private System.Collections.SortedList PseudoQueue;
priq_push(q, tasks[i], pri[i]);
 
public bool Empty
/* pop them and print one by one */
{
while ((c = priq_pop(q, &p)))
get
printf("%d: %s\n", p, c);
{
return PseudoQueue.Count == 0;
}
}
 
public PriorityQueue()
/* put a million random tasks in each queue */
for (i = 0; i < 1 << 20; i++) {
PseudoQueue = new System.Collections.SortedList();
p = rand() / ( RAND_MAX / 5 );
}
priq_push(q, tasks[p], pri[p]);
 
public void push(object Priority, object Value)
p = rand() / ( RAND_MAX / 5 );
{
priq_push(q2, tasks[p], pri[p]);
PseudoQueue.Add(Priority, Value);
}
}
 
public object[] pop()
printf("\nq has %d items, q2 has %d items\n", priq_size(q), priq_size(q2));
{
object[] ReturnValue = { null, null };
if (PseudoQueue.Count > 0)
{
ReturnValue[0] = PseudoQueue.GetKey(0);
ReturnValue[1] = PseudoQueue.GetByIndex(0);
 
PseudoQueue.RemoveAt(0);
/* merge q2 into q; q2 is empty */
}
priq_combine(q, q2);
return ReturnValue;
printf("After merge, q has %d items, q2 has %d items\n",
}
priq_size(q), priq_size(q2));
}
}</syntaxhighlight>
 
'''Min Heap Priority Queue'''
/* pop q until it's empty */
for (i = 0; (c = priq_pop(q, 0)); i++);
printf("Popped %d items out of q\n", i);
 
{{works with|C sharp|C#|3.0+/DotNet 3.5+}}
return 0;
The above code is not really a true Priority Queue as it does not allow duplicate keys; also, the SortedList on which it is based does not have O(log n) insertions and removals for random data as a true Priority Queue does. The below code implements a true Min Heap Priority Queue:
}</lang>output<lang>1: Solve RC tasks
<syntaxhighlight lang="csharp">namespace PriorityQ {
2: Tax return
using KeyT = UInt32;
3: Clear drains
using System;
4: Feed cat
using System.Collections.Generic;
5: Make tea
using System.Linq;
class Tuple<K, V> { // for DotNet 3.5 without Tuple's
public K Item1; public V Item2;
public Tuple(K k, V v) { Item1 = k; Item2 = v; }
public override string ToString() {
return "(" + Item1.ToString() + ", " + Item2.ToString() + ")";
}
}
class MinHeapPQ<V> {
private struct HeapEntry {
public KeyT k; public V v;
public HeapEntry(KeyT k, V v) { this.k = k; this.v = v; }
}
private List<HeapEntry> pq;
private MinHeapPQ() { this.pq = new List<HeapEntry>(); }
private bool mt { get { return pq.Count == 0; } }
private int sz {
get {
var cnt = pq.Count;
return (cnt == 0) ? 0 : cnt - 1;
}
}
private Tuple<KeyT, V> pkmn {
get {
if (pq.Count == 0) return null;
else {
var mn = pq[0];
return new Tuple<KeyT, V>(mn.k, mn.v);
}
}
}
private void psh(KeyT k, V v) { // add extra very high item if none
if (pq.Count == 0) pq.Add(new HeapEntry(UInt32.MaxValue, v));
var i = pq.Count; pq.Add(pq[i - 1]); // copy bottom item...
for (var ni = i >> 1; ni > 0; i >>= 1, ni >>= 1) {
var t = pq[ni - 1];
if (t.k > k) pq[i - 1] = t; else break;
}
pq[i - 1] = new HeapEntry(k, v);
}
private void siftdown(KeyT k, V v, int ndx) {
var cnt = pq.Count - 1; var i = ndx;
for (var ni = i + i + 1; ni < cnt; ni = ni + ni + 1) {
var oi = i; var lk = pq[ni].k; var rk = pq[ni + 1].k;
var nk = k;
if (k > lk) { i = ni; nk = lk; }
if (nk > rk) { ni += 1; i = ni; }
if (i != oi) pq[oi] = pq[i]; else break;
}
pq[i] = new HeapEntry(k, v);
}
private void rplcmin(KeyT k, V v) {
if (pq.Count > 1) siftdown(k, v, 0);
}
private void dltmin() {
var lsti = pq.Count - 2;
if (lsti <= 0) pq.Clear();
else {
var lkv = pq[lsti];
pq.RemoveAt(lsti); siftdown(lkv.k, lkv.v, 0);
}
}
private void reheap(int i) {
var lfti = i + i + 1;
if (lfti < sz) {
var rghti = lfti + 1; reheap(lfti); reheap(rghti);
var ckv = pq[i]; siftdown(ckv.k, ckv.v, i);
}
}
private void bld(IEnumerable<Tuple<KeyT, V>> sq) {
var sqm = from e in sq
select new HeapEntry(e.Item1, e.Item2);
pq = sqm.ToList<HeapEntry>();
var sz = pq.Count;
if (sz > 0) {
var lkv = pq[sz - 1];
pq.Add(new HeapEntry(KeyT.MaxValue, lkv.v));
reheap(0);
}
}
private IEnumerable<Tuple<KeyT, V>> sq() {
return from e in pq
where e.k != KeyT.MaxValue
select new Tuple<KeyT, V>(e.k, e.v); }
private void adj(Func<KeyT, V, Tuple<KeyT, V>> f) {
var cnt = pq.Count - 1;
for (var i = 0; i < cnt; ++i) {
var e = pq[i];
var r = f(e.k, e.v);
pq[i] = new HeapEntry(r.Item1, r.Item2);
}
reheap(0);
}
public static MinHeapPQ<V> empty { get { return new MinHeapPQ<V>(); } }
public static bool isEmpty(MinHeapPQ<V> pq) { return pq.mt; }
public static int size(MinHeapPQ<V> pq) { return pq.sz; }
public static Tuple<KeyT, V> peekMin(MinHeapPQ<V> pq) { return pq.pkmn; }
public static MinHeapPQ<V> push(KeyT k, V v, MinHeapPQ<V> pq) {
pq.psh(k, v); return pq; }
public static MinHeapPQ<V> replaceMin(KeyT k, V v, MinHeapPQ<V> pq) {
pq.rplcmin(k, v); return pq; }
public static MinHeapPQ<V> deleteMin(MinHeapPQ<V> pq) { pq.dltmin(); return pq; }
public static MinHeapPQ<V> merge(MinHeapPQ<V> pq1, MinHeapPQ<V> pq2) {
return fromSeq(pq1.sq().Concat(pq2.sq())); }
public static MinHeapPQ<V> adjust(Func<KeyT, V, Tuple<KeyT, V>> f, MinHeapPQ<V> pq) {
pq.adj(f); return pq; }
public static MinHeapPQ<V> fromSeq(IEnumerable<Tuple<KeyT, V>> sq) {
var pq = new MinHeapPQ<V>(); pq.bld(sq); return pq; }
public static Tuple<Tuple<KeyT, V>, MinHeapPQ<V>> popMin(MinHeapPQ<V> pq) {
var rslt = pq.pkmn; if (rslt == null) return null;
pq.dltmin(); return new Tuple<Tuple<KeyT, V>, MinHeapPQ<V>>(rslt, pq); }
public static IEnumerable<Tuple<KeyT, V>> toSeq(MinHeapPQ<V> pq) {
for (; !pq.mt; pq.dltmin()) yield return pq.pkmn; }
public static IEnumerable<Tuple<KeyT, V>> sort(IEnumerable<Tuple<KeyT, V>> sq) {
return toSeq(fromSeq(sq)); }
}
}</syntaxhighlight>
 
The above class code offers a full set of static methods and properties:
1. "empty" to create a new empty queue,
2. "isEmpty" to test if a queue is empty,
3. "size" to get the number of elements in the queue,
4. "peekMin" to retrieve the lowest priority key/value pair entry as a Tuple (possibly null for empty queues),
5. "push" to insert an entry,
6. "deleteMin" to remove the lowest priority entry,
7. "replaceMin" to replace the lowest priority and adjust the queue according to the value (faster than a "deleteMin" followed by a "push"),
8. "adjust" to apply a function to every key/value entry pair and reheapify the result,
9. "merge" to merge two queues into a single reheapified result,
10. "fromSeq" to build a queue from a sequence of key/value pair tuples,
11. "popMin" which is a convenience function combining a "peekMin" with a "deleteMin", returning null if the queue is empty and a tuple of the result otherwise,
12. "toSeq" to output an ordered sequence of the queue contents as Tuple's of the key/value pairs, and
13. "sort" which is a convenience function combining "fromSeq" followed by "toSeq".
 
The first four are all O(1) and the remainder O(log n) except "adjust" and "fromSeq" are O(n), "merge" is O(m + n) where m and n are the sizes of the two queues, and "toSeq" and "sort" are O(n log n); "replaceMin" is still O(log n) but faster than a "deleteMin" followed by a "push" by a constant factor.
 
Note that the Key type "KeyT" is not generic in order to give better comparison efficiency than using generic comparison using the IComparible interface but can be changed to different numeric types using the "using KeyT = ???" type alias.
 
The above code can be tested as per the page specification by the following code:
<syntaxhighlight lang="csharp"> static void Main(string[] args) {
Tuple<uint, string>[] ins = { new Tuple<uint,string>(3u, "Clear drains"),
new Tuple<uint,string>(4u, "Feed cat"),
new Tuple<uint,string>(5u, "Make tea"),
new Tuple<uint,string>(1u, "Solve RC tasks"),
new Tuple<uint,string>(2u, "Tax return") };
 
var spq = ins.Aggregate(MinHeapPQ<string>.empty, (pq, t) => MinHeapPQ<string>.push(t.Item1, t.Item2, pq));
foreach (var e in MinHeapPQ<string>.toSeq(spq)) Console.WriteLine(e); Console.WriteLine();
 
foreach (var e in MinHeapPQ<string>.sort(ins)) Console.WriteLine(e); Console.WriteLine();
 
var npq = MinHeapPQ<string>.fromSeq(ins);
foreach (var e in MinHeapPQ<string>.toSeq(MinHeapPQ<string>.merge(npq, npq)))
Console.WriteLine(e); Console.WriteLine();
 
var npq = MinHeapPQ<string>.fromSeq(ins);
foreach (var e in MinHeapPQ<string>.toSeq(MinHeapPQ<string>.merge(npq, npq)))
Console.WriteLine(e);
 
foreach (var e in MinHeapPQ<string>.toSeq(MinHeapPQ<string>.adjust((k, v) => new Tuple<uint,string>(6u - k, v), npq)))
Console.WriteLine(e); Console.WriteLine();
}</syntaxhighlight>
 
It tests building the queue the slow way using repeated "push"'s - O(n log n), the faster "fromSeq" (included in the "sort") - O(n), and also tests the "merge" and "adjust" methods.
 
The output of the above test is as follows:
{{output}}
<pre>(1, Solve RC tasks)
(2, Tax return)
(3, Clear drains)
(4, Feed cat)
(5, Make tea)
 
(1, Solve RC tasks)
(2, Tax return)
(3, Clear drains)
(4, Feed cat)
(5, Make tea)
 
(1, Solve RC tasks)
(1, Solve RC tasks)
(2, Tax return)
(2, Tax return)
(3, Clear drains)
(3, Clear drains)
(4, Feed cat)
(4, Feed cat)
(5, Make tea)
(5, Make tea)
 
(1, Make tea)
q has 1048576 items, q2 has 1048576 items
(2, Feed cat)
After merge, q has 2097152 items, q2 has 0 items
(3, Clear drains)
Popped 2097152 items out of q</lang>
(4, Tax return)
(5, Solve RC tasks)</pre>
 
=={{header|C++}}==
The C++ standard library contains the <code>std::priority_queue</code> opaque data structure. It implements a max-heap.
 
<langsyntaxhighlight lang="cpp">#include <iostream>
#include <string>
#include <queue>
Line 182 ⟶ 2,207:
 
return 0;
}</langsyntaxhighlight>
 
{{out}}
output:
<pre>
5, Make tea
Line 193 ⟶ 2,218:
</pre>
 
Alternately, you can use a pre-existing container of yours and use the heap operations to manipulate it:
and use the heap operations to manipulate it:
 
<langsyntaxhighlight lang="cpp">#include <iostream>
#include <string>
#include <vector>
Line 224 ⟶ 2,250:
 
return 0;
}</langsyntaxhighlight>
 
{{out}}
output:
<pre>
5, Make tea
Line 233 ⟶ 2,259:
2, Tax return
1, Solve RC tasks
</pre>
 
=={{header|Clojure}}==
 
<syntaxhighlight lang="clojure">user=> (use 'clojure.data.priority-map)
 
; priority-map can be used as a priority queue
user=> (def p (priority-map "Clear drains" 3, "Feed cat" 4, "Make tea" 5, "Solve RC tasks" 1))
#'user/p
user=> p
{"Solve RC tasks" 1, "Clear drains" 3, "Feed cat" 4, "Make tea" 5}
 
; You can use assoc or conj to add items
user=> (assoc p "Tax return" 2)
{"Solve RC tasks" 1, "Tax return" 2, "Clear drains" 3, "Feed cat" 4, "Make tea" 5}
 
; peek to get first item, pop to give you back the priority-map with the first item removed
user=> (peek p)
["Solve RC tasks" 1]
 
; Merge priority-maps together
user=> (into p [["Wax Car" 4]["Paint Fence" 1]["Sand Floor" 3]])
{"Solve RC tasks" 1, "Paint Fence" 1, "Clear drains" 3, "Sand Floor" 3, "Wax Car" 4, "Feed cat" 4, "Make tea" 5}</syntaxhighlight>
 
=={{header|CLU}}==
This is a priority queue based on a binary heap. It uses CLU's dynamic
array to store the data.
 
There are no intrinsic limits on what kind of data can be used for the
priority or the values themselves, except that the priority datatype
must support the less-than operator.
 
<syntaxhighlight lang="clu">prio_queue = cluster [P, T: type] is new, empty, push, pop
where P has lt: proctype (P,P) returns (bool)
item = struct[prio: P, val: T]
rep = array[item]
new = proc () returns (cvt)
return (rep$create(0))
end new
empty = proc (pq: cvt) returns (bool)
return (rep$empty(pq))
end empty
parent = proc (k: int) returns (int)
return ((k-1)/2)
end parent
left = proc (k: int) returns (int)
return (2*k + 1)
end left
right = proc (k: int) returns (int)
return (2*k + 2)
end right
swap = proc (pq: rep, a: int, b: int)
temp: item := pq[a]
pq[a] := pq[b]
pq[b] := temp
end swap
min_heapify = proc (pq: rep, k: int)
l: int := left(k)
r: int := right(k)
smallest: int := k
if l < rep$size(pq) cand pq[l].prio < pq[smallest].prio then
smallest := l
end
if r < rep$size(pq) cand pq[r].prio < pq[smallest].prio then
smallest := r
end
if smallest ~= k then
swap(pq, k, smallest)
min_heapify(pq, smallest)
end
end min_heapify
push = proc (pq: cvt, prio: P, val: T)
rep$addh(pq, item${prio: prio, val: val})
i: int := rep$high(pq)
while i ~= 0 cand pq[i].prio < pq[parent(i)].prio do
swap(pq, i, parent(i))
i := parent(i)
end
end push
pop = proc (pq: cvt) returns (P, T) signals (empty)
if empty(up(pq)) then signal empty end
if rep$size(pq) = 1 then
i: item := rep$remh(pq)
return (i.prio, i.val)
end
root: item := pq[0]
pq[0] := rep$remh(pq)
min_heapify(pq, 0)
return (root.prio, root.val)
end pop
end prio_queue
start_up = proc ()
% use ints for priority and strings for data
prioq = prio_queue[int,string]
% make the priority queue
pq: prioq := prioq$new()
% add some tasks
prioq$push(pq, 3, "Clear drains")
prioq$push(pq, 4, "Feed cat")
prioq$push(pq, 5, "Make tea")
prioq$push(pq, 1, "Solve RC tasks")
prioq$push(pq, 2, "Tax return")
% print them all out in order
po: stream := stream$primary_output()
while ~prioq$empty(pq) do
prio: int task: string
prio, task := prioq$pop(pq)
stream$putl(po, int$unparse(prio) || ": " || task)
end
end start_up</syntaxhighlight>
{{out}}
<pre>1: Solve RC tasks
2: Tax return
3: Clear drains
4: Feed cat
5: Make tea</pre>
 
=={{header|COBOL}}==
 
===IBM Enterprise COBOL solution===
 
Note that the logic of this implementation follows the C solution above for "Pairing heap w/ generic data types" except that the "generic type" (the TASK record defintion) is sized and allocated in the calling test program instead of in the priority queue subroutines.
 
Note also that each subroutine is declared RECURSIVE though they do not all need it.
 
The subroutines each pass back a return value in their last parameter. The most recent release of the IBM Enterprise COBOL compiler (V6.4 as of the date of this contribution) does, in fact, support user-defined functions, which would make some of this implementation a little easier to write and read, but since many IBM shops are not yet up to the most recent level, this version is offered as one that will work with down-level compiler versions.
 
In the "two pass merge" subroutine (PTYQ2PMG), the final three lines are needed because the COBOL CALL statement does not allow for expressions as arguments, so the arguments to the outer call to the "merge" subroutine must be executed first, and the results of those two calls become the arguments to the final "merge" call.
 
Note also that the subroutines call each other using "PIC X(8)" pseudonyms because the actually recursive subroutines cannot use the "same name" as both the PROGRAM-ID and as a variable name. This could be resolved by simply using "constant" calls (like <code>CALL "PTYQ2PMG" USING . . . </code> but using the pseudonyms allows each of the subroutines to also be separately compiled into an executable module and then dynamically loaded at run time. Many IBM shops will prefer that method to this purely "static" solution.
 
<syntaxhighlight lang="COBOL">
PROCESS NOSEQ,DS(S),AR(E),TEST(SO),CP(1047)
IDENTIFICATION DIVISION.
PROGRAM-ID. PTYQTEST
ENVIRONMENT DIVISION.
CONFIGURATION SECTION.
* UNCOMMENT WITH DEBUGGING CLAUSE FOR DEBUG LINES TO EXECUTE.
SOURCE-COMPUTER.
Z-SYSTEM
* WITH DEBUGGING MODE
.
 
DATA DIVISION.
WORKING-STORAGE SECTION.
01 PTYQ-PGMNAMES.
05 PTYQPUSH PIC X(8) VALUE "PTYQPUSH".
05 PTYQPOP PIC X(8) VALUE "PTYQPOP".
 
01 TASK-PTR POINTER.
 
01 TOP-PTR POINTER.
 
01 LINK-KEY PIC S9(8) COMP-5.
 
01 HEAP-PTR POINTER VALUE NULL.
 
01 PUSHD-PTR POINTER VALUE NULL.
 
01 POPPD-PTR POINTER VALUE NULL.
 
LINKAGE SECTION.
01 TASK.
05 TASK-NODE.
10 TASK-KEY PIC S9(8) COMP-5.
10 TASK-NEXT POINTER.
10 TASK-DOWN POINTER.
05 TASK-NAME PIC X(40).
 
PROCEDURE DIVISION.
ALLOCATE TASK RETURNING TASK-PTR
MOVE "EAT SCONES." TO TASK-NAME
MOVE +6 TO LINK-KEY
CALL PTYQPUSH USING TASK-PTR, LINK-KEY, HEAP-PTR, PUSHD-PTR
SET HEAP-PTR TO PUSHD-PTR
 
ALLOCATE TASK RETURNING TASK-PTR
MOVE "CLEAR DRAINS." TO TASK-NAME
MOVE +3 TO LINK-KEY
CALL PTYQPUSH USING TASK-PTR, LINK-KEY, HEAP-PTR, PUSHD-PTR
SET HEAP-PTR TO PUSHD-PTR
 
ALLOCATE TASK RETURNING TASK-PTR
MOVE "FEED CAT." TO TASK-NAME
MOVE +4 TO LINK-KEY
CALL PTYQPUSH USING TASK-PTR, LINK-KEY, HEAP-PTR, PUSHD-PTR
SET HEAP-PTR TO PUSHD-PTR
 
ALLOCATE TASK RETURNING TASK-PTR
MOVE "MAKE TEA." TO TASK-NAME
MOVE +5 TO LINK-KEY
CALL PTYQPUSH USING TASK-PTR, LINK-KEY, HEAP-PTR, PUSHD-PTR
SET HEAP-PTR TO PUSHD-PTR
 
ALLOCATE TASK RETURNING TASK-PTR
MOVE "SOLVE RC TASKS." TO TASK-NAME
MOVE +1 TO LINK-KEY
CALL PTYQPUSH USING TASK-PTR, LINK-KEY, HEAP-PTR, PUSHD-PTR
SET HEAP-PTR TO PUSHD-PTR
 
ALLOCATE TASK RETURNING TASK-PTR
MOVE "TAX RETURN." TO TASK-NAME
MOVE +2 TO LINK-KEY
CALL PTYQPUSH USING TASK-PTR, LINK-KEY, HEAP-PTR, PUSHD-PTR
SET HEAP-PTR TO PUSHD-PTR
 
PERFORM WITH TEST BEFORE UNTIL HEAP-PTR = NULL
SET TOP-PTR TO HEAP-PTR
SET ADDRESS OF TASK TO TOP-PTR
DISPLAY TASK-KEY " " TASK-NAME
CALL PTYQPOP USING HEAP-PTR, POPPD-PTR
SET HEAP-PTR TO POPPD-PTR
FREE TOP-PTR
END-PERFORM
GOBACK.
END PROGRAM PTYQTEST.
PROCESS NOSEQ,DS(S),AR(E),TEST(SO),CP(1047)
IDENTIFICATION DIVISION.
PROGRAM-ID. PTYQMERG RECURSIVE.
ENVIRONMENT DIVISION.
CONFIGURATION SECTION.
* UNCOMMENT WITH DEBUGGING CLAUSE FOR DEBUG LINES TO EXECUTE.
SOURCE-COMPUTER.
Z-SYSTEM
* WITH DEBUGGING MODE
.
 
DATA DIVISION.
 
LINKAGE SECTION.
01 HEAP-PTRA POINTER.
 
01 HEAP-PTRB POINTER.
 
01 MERGD-PTR POINTER.
 
01 HEAPA.
05 HEAPA-KEY PIC S9(8) COMP-5 VALUE +0.
05 HEAPA-NEXT POINTER.
05 HEAPA-DOWN POINTER.
 
01 HEAPB.
05 HEAPB-KEY PIC S9(8) COMP-5 VALUE +0.
05 HEAPB-NEXT POINTER.
05 HEAPB-DOWN POINTER.
 
PROCEDURE DIVISION USING HEAP-PTRA, HEAP-PTRB, MERGD-PTR.
EVALUATE TRUE
WHEN HEAP-PTRA = NULL
SET MERGD-PTR TO HEAP-PTRB
WHEN HEAP-PTRB = NULL
SET MERGD-PTR TO HEAP-PTRA
WHEN OTHER
SET ADDRESS OF HEAPA TO HEAP-PTRA
SET ADDRESS OF HEAPB TO HEAP-PTRB
IF HEAPA-KEY < HEAPB-KEY
IF HEAPA-DOWN NOT = NULL
SET HEAPB-NEXT TO HEAPA-DOWN
END-IF
SET HEAPA-DOWN TO HEAP-PTRB
SET MERGD-PTR TO HEAP-PTRA
ELSE
IF HEAPB-DOWN NOT = NULL
SET HEAPA-NEXT TO HEAPB-DOWN
END-IF
SET HEAPB-DOWN TO HEAP-PTRA
SET MERGD-PTR TO HEAP-PTRB
END-IF
END-EVALUATE
GOBACK.
END PROGRAM PTYQMERG.
PROCESS NOSEQ,DS(S),AR(E),TEST(SO),CP(1047)
IDENTIFICATION DIVISION.
PROGRAM-ID. PTYQ2PMG RECURSIVE.
ENVIRONMENT DIVISION.
CONFIGURATION SECTION.
* UNCOMMENT WITH DEBUGGING CLAUSE FOR DEBUG LINES TO EXECUTE.
SOURCE-COMPUTER.
Z-SYSTEM
* WITH DEBUGGING MODE
.
 
DATA DIVISION.
WORKING-STORAGE SECTION.
01 PGMQMERG PIC X(8) VALUE "PTYQMERG".
01 PGMQ2PMG PIC X(8) VALUE "PTYQ2PMG".
 
LOCAL-STORAGE SECTION.
01 HEAP-PTRA POINTER.
 
01 HEAP-PTRB POINTER.
 
01 HEAP-REST POINTER.
 
01 MERG1-PTR POINTER.
 
01 MERG2-PTR POINTER.
 
LINKAGE SECTION.
01 HEAP-PTR POINTER.
 
01 MERGD-PTR POINTER.
 
01 HEAP.
05 HEAP-KEY PIC S9(8) COMP-5 VALUE +0.
05 HEAP-NEXT POINTER.
05 HEAP-DOWN POINTER.
 
01 HEAPA.
05 HEAPA-KEY PIC S9(8) COMP-5 VALUE +0.
05 HEAPA-NEXT POINTER.
05 HEAPA-DOWN POINTER.
 
01 HEAPB.
05 HEAPB-KEY PIC S9(8) COMP-5 VALUE +0.
05 HEAPB-NEXT POINTER.
05 HEAPB-DOWN POINTER.
 
01 REST.
05 REST-KEY PIC S9(8) COMP-5 VALUE +0.
05 REST-NEXT POINTER.
05 REST-DOWN POINTER.
 
PROCEDURE DIVISION USING HEAP-PTR, MERGD-PTR.
SET ADDRESS OF HEAP TO HEAP-PTR
EVALUATE TRUE
WHEN HEAP-PTR = NULL
SET MERGD-PTR TO HEAP-PTR
WHEN HEAP-NEXT = NULL
SET MERGD-PTR TO HEAP-PTR
WHEN OTHER
SET HEAP-PTRA TO HEAP-PTR
SET ADDRESS OF HEAPA TO HEAP-PTRA
SET HEAP-PTRB TO HEAP-NEXT
SET ADDRESS OF HEAPB TO HEAP-PTRB
SET HEAP-REST TO HEAPB-NEXT
SET ADDRESS OF REST TO HEAP-REST
SET HEAPA-NEXT TO NULL
SET HEAPB-NEXT TO NULL
CALL PGMQMERG USING HEAP-PTRA, HEAP-PTRB, MERG1-PTR
CALL PGMQ2PMG USING HEAP-REST, MERG2-PTR
CALL PGMQMERG USING MERG1-PTR, MERG2-PTR, MERGD-PTR
END-EVALUATE
GOBACK.
END PROGRAM PTYQ2PMG.
PROCESS NOSEQ,DS(S),AR(E),TEST(SO),CP(1047)
IDENTIFICATION DIVISION.
PROGRAM-ID. PTYQPUSH RECURSIVE.
ENVIRONMENT DIVISION.
CONFIGURATION SECTION.
* UNCOMMENT WITH DEBUGGING CLAUSE FOR DEBUG LINES TO EXECUTE.
SOURCE-COMPUTER.
Z-SYSTEM
* WITH DEBUGGING MODE
.
 
DATA DIVISION.
WORKING-STORAGE SECTION.
01 PTYQMERG PIC X(8) VALUE "PTYQMERG".
 
LINKAGE SECTION.
01 NODE-PTR POINTER.
 
01 LINK-KEY PIC S9(8) COMP-5.
 
01 HEAP-PTR POINTER.
 
01 PUSHD-PTR POINTER.
 
01 HEAP.
05 HEAP-KEY PIC S9(8) COMP-5.
05 HEAP-NEXT POINTER.
05 HEAP-DOWN POINTER.
 
01 NODE.
05 NODE-KEY PIC S9(8) COMP-5.
05 NODE-NEXT POINTER.
05 NODE-DOWN POINTER.
 
PROCEDURE DIVISION USING NODE-PTR, LINK-KEY, HEAP-PTR, PUSHD-PTR.
SET ADDRESS OF NODE TO NODE-PTR
SET ADDRESS OF HEAP TO HEAP-PTR
SET NODE-NEXT TO NULL
SET NODE-DOWN TO NULL
MOVE LINK-KEY TO NODE-KEY
CALL PTYQMERG USING NODE-PTR, HEAP-PTR, PUSHD-PTR
GOBACK.
END PROGRAM PTY2PUSH.
PROCESS NOSEQ,DS(S),AR(E),TEST(SO),CP(1047)
IDENTIFICATION DIVISION.
PROGRAM-ID. PTYQPOP RECURSIVE.
ENVIRONMENT DIVISION.
CONFIGURATION SECTION.
* UNCOMMENT WITH DEBUGGING CLAUSE FOR DEBUG LINES TO EXECUTE.
SOURCE-COMPUTER.
Z-SYSTEM
* WITH DEBUGGING MODE
.
 
DATA DIVISION.
WORKING-STORAGE SECTION.
01 PTYQ2PMG PIC X(8) VALUE "PTYQ2PMG".
 
LINKAGE SECTION.
01 HEAP-PTR POINTER.
 
01 POPPD-PTR POINTER.
 
01 HEAP.
05 HEAP-KEY PIC S9(8) COMP-5 VALUE +0.
05 HEAP-NEXT POINTER.
05 HEAP-DOWN POINTER.
 
PROCEDURE DIVISION USING HEAP-PTR, POPPD-PTR.
SET ADDRESS OF HEAP TO HEAP-PTR
CALL PTYQ2PMG USING HEAP-DOWN, POPPD-PTR
GOBACK.
END PROGRAM PTYQPOP.
</syntaxhighlight>
 
{{out}}
<pre>
+0000000001 SOLVE RC TASKS.
+0000000002 TAX RETURN.
+0000000003 CLEAR DRAINS.
+0000000004 FEED CAT.
+0000000005 MAKE TEA.
+0000000006 EAT SCONES.
</pre>
 
=={{header|CoffeeScript}}==
<syntaxhighlight lang="coffeescript">
PriorityQueue = ->
# Use closure style for object creation (so no "new" required).
# Private variables are toward top.
h = []
better = (a, b) ->
h[a].priority < h[b].priority
swap = (a, b) ->
[h[a], h[b]] = [h[b], h[a]]
sift_down = ->
max = h.length
n = 0
while n < max
c1 = 2*n + 1
c2 = c1 + 1
best = n
best = c1 if c1 < max and better(c1, best)
best = c2 if c2 < max and better(c2, best)
return if best == n
swap n, best
n = best
sift_up = ->
n = h.length - 1
while n > 0
parent = Math.floor((n-1) / 2)
return if better parent, n
swap n, parent
n = parent
# now return the public interface, which is an object that only
# has functions on it
self =
size: ->
h.length
 
push: (priority, value) ->
elem =
priority: priority
value: value
h.push elem
sift_up()
pop: ->
throw Error("cannot pop from empty queue") if h.length == 0
value = h[0].value
last = h.pop()
if h.length > 0
h[0] = last
sift_down()
value
 
# test
do ->
pq = PriorityQueue()
pq.push 3, "Clear drains"
pq.push 4, "Feed cat"
pq.push 5, "Make tea"
pq.push 1, "Solve RC tasks"
pq.push 2, "Tax return"
 
while pq.size() > 0
console.log pq.pop()
# test high performance
for n in [1..100000]
priority = Math.random()
pq.push priority, priority
v = pq.pop()
console.log "First random element was #{v}"
while pq.size() > 0
new_v = pq.pop()
throw Error "Queue broken" if new_v < v
v = new_v
console.log "Final random element was #{v}"
</syntaxhighlight>
 
output
 
<syntaxhighlight lang="text">
> coffee priority_queue.coffee
Solve RC tasks
Tax return
Clear drains
Feed cat
Make tea
First random element was 0.00002744467929005623
Final random element was 0.9999718656763434
</syntaxhighlight>
 
=={{header|Common Lisp}}==
In this task were implemented to versions of the functions, the non-destructive ones that will not change the state of the priority queue and the destructive ones that will change. The destructive ones work very similarly to the 'pop' and 'push' functions.
<syntaxhighlight lang="lisp">
;priority-queue's are implemented with association lists
(defun make-pq (alist)
(sort (copy-alist alist) (lambda (a b) (< (car a) (car b)))))
;
;Will change the state of pq
;
(define-modify-macro insert-pq (pair)
(lambda (pq pair) (sort-alist (cons pair pq))))
 
(define-modify-macro remove-pq-aux () cdr)
 
(defmacro remove-pq (pq)
`(let ((aux (copy-alist ,pq)))
(REMOVE-PQ-AUX ,pq)
(car aux)))
;
;Will not change the state of pq
;
(defun insert-pq-non-destructive (pair pq)
(sort-alist (cons pair pq)))
 
(defun remove-pq-non-destructive (pq)
(cdr pq))
;testing
(defparameter a (make-pq '((1 . "Solve RC tasks") (3 . "Clear drains") (2 . "Tax return") (5 . "Make tea"))))
(format t "~a~&" a)
(insert-pq a '(4 . "Feed cat"))
(format t "~a~&" a)
(format t "~a~&" (remove-pq a))
(format t "~a~&" a)
(format t "~a~&" (remove-pq a))
(format t "~a~&" a)
</syntaxhighlight>
{{out}}
<pre>
((1 . Solve RC tasks) (2 . Tax return) (3 . Clear drains) (5 . Make tea))
((1 . Solve RC tasks) (2 . Tax return) (3 . Clear drains) (4 . Feed cat) (5 . Make tea))
(1 . Solve RC tasks)
((2 . Tax return) (3 . Clear drains) (4 . Feed cat) (5 . Make tea))
(2 . Tax return)
((3 . Clear drains) (4 . Feed cat) (5 . Make tea))
</pre>
 
=={{header|Component Pascal}}==
BlackBox Component Builder
<syntaxhighlight lang="oberon2">
MODULE PQueues;
IMPORT StdLog,Boxes;
 
TYPE
Rank* = POINTER TO RECORD
p-: LONGINT; (* Priority *)
value-: Boxes.Object
END;
PQueue* = POINTER TO RECORD
a: POINTER TO ARRAY OF Rank;
size-: LONGINT;
END;
PROCEDURE NewRank*(p: LONGINT; v: Boxes.Object): Rank;
VAR
r: Rank;
BEGIN
NEW(r);r.p := p;r.value := v;
RETURN r
END NewRank;
PROCEDURE NewPQueue*(cap: LONGINT): PQueue;
VAR
pq: PQueue;
BEGIN
NEW(pq);pq.size := 0;
NEW(pq.a,cap);pq.a[0] := NewRank(MIN(INTEGER),NIL);
RETURN pq
END NewPQueue;
PROCEDURE (pq: PQueue) Push*(r:Rank), NEW;
VAR
i: LONGINT;
BEGIN
INC(pq.size);
i := pq.size;
WHILE r.p < pq.a[i DIV 2].p DO
pq.a[i] := pq.a[i DIV 2];i := i DIV 2
END;
pq.a[i] := r
END Push;
PROCEDURE (pq: PQueue) Pop*(): Rank,NEW;
VAR
r,y: Rank;
i,j: LONGINT;
ok: BOOLEAN;
BEGIN
r := pq.a[1]; (* Priority object *)
y := pq.a[pq.size]; DEC(pq.size); i := 1; ok := FALSE;
WHILE (i <= pq.size DIV 2) & ~ok DO
j := i + 1;
IF (j < pq.size) & (pq.a[i].p > pq.a[j + 1].p) THEN INC(j) END;
IF y.p > pq.a[j].p THEN pq.a[i] := pq.a[j]; i := j ELSE ok := TRUE END
END;
pq.a[i] := y;
RETURN r
END Pop;
PROCEDURE (pq: PQueue) IsEmpty*(): BOOLEAN,NEW;
BEGIN
RETURN pq.size = 0
END IsEmpty;
PROCEDURE Test*;
VAR
pq: PQueue;
r: Rank;
PROCEDURE ShowRank(r:Rank);
BEGIN
StdLog.Int(r.p);StdLog.String(":> ");StdLog.String(r.value.AsString());StdLog.Ln;
END ShowRank;
BEGIN
pq := NewPQueue(128);
pq.Push(NewRank(3,Boxes.NewString("Clear drains")));
pq.Push(NewRank(4,Boxes.NewString("Feed cat")));
pq.Push(NewRank(5,Boxes.NewString("Make tea")));
pq.Push(NewRank(1,Boxes.NewString("Solve RC tasks")));
pq.Push(NewRank(2,Boxes.NewString("Tax return")));
ShowRank(pq.Pop());
ShowRank(pq.Pop());
ShowRank(pq.Pop());
ShowRank(pq.Pop());
ShowRank(pq.Pop());
END Test;
END PQueues.
</syntaxhighlight>
Interface extracted from the implementation
<syntaxhighlight lang="oberon2">
DEFINITION PQueues;
 
IMPORT Boxes;
 
TYPE
PQueue = POINTER TO RECORD
size-: LONGINT;
(pq: PQueue) IsEmpty (): BOOLEAN, NEW;
(pq: PQueue) Pop (): Rank, NEW;
(pq: PQueue) Push (r: Rank), NEW
END;
 
Rank = POINTER TO RECORD
p-: LONGINT;
value-: Boxes.Object
END;
 
PROCEDURE NewPQueue (cap: LONGINT): PQueue;
PROCEDURE NewRank (p: LONGINT; v: Boxes.Object): Rank;
PROCEDURE Test;
 
END PQueues.
</syntaxhighlight>
Execute: ^Q PQueues.Test<br/>
Output:
<pre>
1:> Solve RC tasks
2:> Tax return
3:> Clear drains
4:> Feed cat
5:> Make tea
</pre>
 
=={{header|D}}==
<syntaxhighlight lang="d">import std.stdio, std.container, std.array, std.typecons;
 
void main() {
alias tuple T;
auto heap = heapify([T(3, "Clear drains"),
T(4, "Feed cat"),
T(5, "Make tea"),
T(1, "Solve RC tasks"),
T(2, "Tax return")]);
 
while (!heap.empty) {
writeln(heap.front);
heap.removeFront();
}
}</syntaxhighlight>
{{out}}
<pre>Tuple!(int,string)(5, "Make tea")
Tuple!(int,string)(4, "Feed cat")
Tuple!(int,string)(3, "Clear drains")
Tuple!(int,string)(2, "Tax return")
Tuple!(int,string)(1, "Solve RC tasks")</pre>
=={{header|Delphi}}==
{{libheader| System.SysUtils}}
{{libheader| Boost.Generics.Collection}}
Boost.Generics.Collection is part of [https://github.com/MaiconSoft/DelphiBoostLib DelphiBoostLib]
<syntaxhighlight lang="delphi">program Priority_queue;
 
{$APPTYPE CONSOLE}
 
uses
System.SysUtils, Boost.Generics.Collection;
 
var
Queue: TPriorityQueue<String>;
 
begin
Queue := TPriorityQueue<String>.Create(['Clear drains', 'Feed cat',
'Make tea', 'Solve RC tasks', 'Tax return'], [3, 4, 5, 1, 2]);
 
while not Queue.IsEmpty do
with Queue.DequeueEx do
Writeln(Priority, ', ', value);
end.</syntaxhighlight>
{{out}}
<pre>1, Solve RC tasks
2, Tax return
3, Clear drains
4, Feed cat
5, Make tea</pre>
 
=={{header|EchoLisp}}==
We use the built-in binary tree library. Each tree node has a datum (key . value). The functions (bin-tree-pop-first tree) and (bin-tree-pop-last tree) allow to extract the node with highest or lowest priority.
<syntaxhighlight lang="lisp">
(lib 'tree)
(define tasks (make-bin-tree 3 "Clear drains"))
(bin-tree-insert tasks 2 "Tax return")
(bin-tree-insert tasks 5 "Make tea")
(bin-tree-insert tasks 1 "Solve RC tasks")
(bin-tree-insert tasks 4 "Feed 🐡")
 
(bin-tree-pop-first tasks) → (1 . "Solve RC tasks")
(bin-tree-pop-first tasks) → (2 . "Tax return")
(bin-tree-pop-first tasks) → (3 . "Clear drains")
(bin-tree-pop-first tasks) → (4 . "Feed 🐡")
(bin-tree-pop-first tasks) → (5 . "Make tea")
(bin-tree-pop-first tasks) → null
 
;; similarly
(bin-tree-pop-last tasks) → (5 . "Make tea")
(bin-tree-pop-last tasks) → (4 . "Feed 🐡")
; etc.
</syntaxhighlight>
 
=={{header|Elixir}}==
{{trans|Erlang}}
<syntaxhighlight lang="elixir">defmodule Priority do
def create, do: :gb_trees.empty
def insert( element, priority, queue ), do: :gb_trees.enter( priority, element, queue )
def peek( queue ) do
{_priority, element, _new_queue} = :gb_trees.take_smallest( queue )
element
end
def task do
items = [{3, "Clear drains"}, {4, "Feed cat"}, {5, "Make tea"}, {1, "Solve RC tasks"}, {2, "Tax return"}]
queue = Enum.reduce(items, create, fn({priority, element}, acc) -> insert( element, priority, acc ) end)
IO.puts "peek priority: #{peek( queue )}"
Enum.reduce(1..length(items), queue, fn(_n, q) -> write_top( q ) end)
end
def top( queue ) do
{_priority, element, new_queue} = :gb_trees.take_smallest( queue )
{element, new_queue}
end
defp write_top( q ) do
{element, new_queue} = top( q )
IO.puts "top priority: #{element}"
new_queue
end
end
 
Priority.task</syntaxhighlight>
 
{{out}}
<pre>
peek priority: Solve RC tasks
top priority: Solve RC tasks
top priority: Tax return
top priority: Clear drains
top priority: Feed cat
top priority: Make tea
</pre>
 
=={{header|Erlang}}==
Using built in gb_trees module, with the suggested interface for this task.
<syntaxhighlight lang="erlang">
-module( priority_queue ).
 
-export( [create/0, insert/3, peek/1, task/0, top/1] ).
 
create() -> gb_trees:empty().
 
insert( Element, Priority, Queue ) -> gb_trees:enter( Priority, Element, Queue ).
 
peek( Queue ) ->
{_Priority, Element, _New_queue} = gb_trees:take_smallest( Queue ),
Element.
 
task() ->
Items = [{3, "Clear drains"}, {4, "Feed cat"}, {5, "Make tea"}, {1, "Solve RC tasks"}, {2, "Tax return"}],
Queue = lists:foldl( fun({Priority, Element}, Acc) -> insert( Element, Priority, Acc ) end, create(), Items ),
io:fwrite( "peek priority: ~p~n", [peek( Queue )] ),
lists:foldl( fun(_N, Q) -> write_top( Q ) end, Queue, lists:seq(1, erlang:length(Items)) ).
 
top( Queue ) ->
{_Priority, Element, New_queue} = gb_trees:take_smallest( Queue ),
{Element, New_queue}.
 
 
 
write_top( Q ) ->
{Element, New_queue} = top( Q ),
io:fwrite( "top priority: ~p~n", [Element] ),
New_queue.
</syntaxhighlight>
{{out}}
<pre>
12> priority_queue:task().
peek priority: "Solve RC tasks"
top priority: "Solve RC tasks"
top priority: "Tax return"
top priority: "Clear drains"
top priority: "Feed cat"
top priority: "Make tea"
</pre>
 
=={{header|F Sharp}}==
 
The below codes all provide the standard priority queue functions of "peekMin", "push", and "deleteMin"; as well, "replaceMin" which can be much more efficient that a "deleteMin" followed by a "push" for some types of queues), "popMin" (generally a convenience function for "peekMin" followed by "deleteMin"), "adjust" for applying a function to all queue entries and reheapifying, "fromSeq" for building a queue from a sequence, "toSeq" for outputting a sorted sequence of the queue contents, and "sort" which is a convenience function combining the latter two functions are provided. Finally, the queue's all provide a "merge" function to combine two queues into one, and an "adjust" function which applies a function to every heap element and reheapifies.
===Functional===
 
'''Binomial Heap Priority Queue'''
 
The following Binomial Heap Priority Queue code has been adapted [http://cs.hubfs.net/topic/None/56608 from a version by "DeeJay"] updated for changes in F# over the intervening years, and implementing the O(1) "peekMin" mentioned in that post; in addition to the above standard priority queue functions, it also implements the "merge" function for which the Binomial Heap is particularly suited, taking O(log n) time rather than the usual O(n) (or worse) time:
<syntaxhighlight lang="fsharp">[<RequireQualifiedAccess>]
module PriorityQ =
 
// type 'a treeElement = Element of uint32 * 'a
type 'a treeElement = struct val k:uint32 val v:'a new(k,v) = { k=k;v=v } end
 
type 'a tree = Node of uint32 * 'a treeElement * 'a tree list
 
type 'a heap = 'a tree list
 
[<CompilationRepresentation(CompilationRepresentationFlags.UseNullAsTrueValue)>]
[<NoEquality; NoComparison>]
type 'a outerheap = | HeapEmpty | HeapNotEmpty of 'a treeElement * 'a heap
 
let empty = HeapEmpty
 
let isEmpty = function | HeapEmpty -> true | _ -> false
 
let inline private rank (Node(r,_,_)) = r
 
let inline private root (Node(_,x,_)) = x
 
exception Empty_Heap
 
let peekMin = function | HeapEmpty -> None
| HeapNotEmpty(min, _) -> Some (min.k, min.v)
 
let rec private findMin heap =
match heap with | [] -> raise Empty_Heap //guarded so should never happen
| [node] -> root node,[]
| topnode::heap' ->
let min,subheap = findMin heap' in let rtn = root topnode
match subheap with
| [] -> if rtn.k > min.k then min,[] else rtn,[]
| minnode::heap'' ->
let rmn = root minnode
if rtn.k <= rmn.k then rtn,heap
else rmn,minnode::topnode::heap''
 
let private mergeTree (Node(r,kv1,ts1) as tree1) (Node (_,kv2,ts2) as tree2) =
if kv1.k > kv2.k then Node(r+1u,kv2,tree1::ts2)
else Node(r+1u,kv1,tree2::ts1)
 
let rec private insTree (newnode: 'a tree) heap =
match heap with
| [] -> [newnode]
| topnode::heap' -> if (rank newnode) < (rank topnode) then newnode::heap
else insTree (mergeTree newnode topnode) heap'
 
let push k v = let kv = treeElement(k,v) in let nn = Node(0u,kv,[])
function | HeapEmpty -> HeapNotEmpty(kv,[nn])
| HeapNotEmpty(min,heap) -> let nmin = if k > min.k then min else kv
HeapNotEmpty(nmin,insTree nn heap)
 
let rec private merge' heap1 heap2 = //doesn't guaranty minimum tree node as head!!!
match heap1,heap2 with
| _,[] -> heap1
| [],_ -> heap2
| topheap1::heap1',topheap2::heap2' ->
match compare (rank topheap1) (rank topheap2) with
| -1 -> topheap1::merge' heap1' heap2
| 1 -> topheap2::merge' heap1 heap2'
| _ -> insTree (mergeTree topheap1 topheap2) (merge' heap1' heap2')
 
let merge oheap1 oheap2 = match oheap1,oheap2 with
| _,HeapEmpty -> oheap1
| HeapEmpty,_ -> oheap2
| HeapNotEmpty(min1,heap1),HeapNotEmpty(min2,heap2) ->
let min = if min1.k > min2.k then min2 else min1
HeapNotEmpty(min,merge' heap1 heap2)
 
let rec private removeMinTree = function
| [] -> raise Empty_Heap // will never happen as already guarded
| [node] -> node,[]
| t::ts -> let t',ts' = removeMinTree ts
if (root t).k <= (root t').k then t,ts else t',t::ts'
 
let deleteMin =
function | HeapEmpty -> HeapEmpty
| HeapNotEmpty(_,heap) ->
match heap with
| [] -> HeapEmpty // should never occur: non empty heap with no elements
| [Node(_,_,heap')] -> match heap' with
| [] -> HeapEmpty
| _ -> let min,_ = findMin heap'
HeapNotEmpty(min,heap')
| _::_ -> let Node(_,_,ts1),ts2 = removeMinTree heap
let nheap = merge' (List.rev ts1) ts2 in let min,_ = findMin nheap
HeapNotEmpty(min,nheap)
 
let replaceMin k v pq = push k v (deleteMin pq)
 
let fromSeq sq = Seq.fold (fun pq (k, v) -> push k v pq) empty sq
 
let popMin pq = match peekMin pq with
| None -> None
| Some(kv) -> Some(kv, deleteMin pq)
 
let toSeq pq = Seq.unfold popMin pq
 
let sort sq = sq |> fromSeq |> toSeq
 
let adjust f pq = pq |> toSeq |> Seq.map (fun (k, v) -> f k v) |> fromSeq</syntaxhighlight>
 
"isEmpty", "empty", and "peekMin" all have O(1) performance, "push" is O(1) amortized performance with O(log n) worst case, and the rest are O(log n) except for "fromSeq" (and thus "sort" and "adjust") which have O(n log n) performance since they use repeated "deleteMin" with one per entry.
 
No "size" function is provided, but it would be implemented by summing the total size of all the nested tree lists, which each have a "Count" property and thus would be quite fast.
 
Note that the current "adjust" function is horribly inefficient as it outputs the original queue as a sorted sequence (O(n log n) time complexity), maps the adjusting function to each element, and rebuilds the queue be repeated "push" operations of the resulting sequence. This could be improved by re-writing to output the sequence in unsorted order (using an internal function that doesn't use repeated "deleteMin" operations) and then rebuilding from the adjusted sequence; doing this would make the "adjust" operation take O(n) amortized time.
 
The "sort" function also uses a similar technique of building a queue from a sequence by repeated "push" operations (however, those only take O(n) amortized time for the Binomial Heap), then outputting a sorted sequence by repeated "popMin" operations for a combined O(n log n) time complexity.
 
'''Min Heap Priority Queue'''
 
The following code implementing a Min Heap Priority Queue is adapted from the [http://www.cl.cam.ac.uk/~lp15/MLbook/programs/sample4.sml ML PRIORITY_QUEUE code by Lawrence C. Paulson] including separating the key/value pairs as separate entries in the data structure for better comparison efficiency; it implements an efficient "fromSeq" function using reheapify for which the Min Heap is particularly suited as it has only O(n) instead of O(n log n) computational time complexity, which method is also used for the "adjust" and "merge" functions:
<syntaxhighlight lang="fsharp">[<RequireQualifiedAccess>]
module PriorityQ =
 
type HeapEntry<'V> = struct val k:uint32 val v:'V new(k,v) = {k=k;v=v} end
[<CompilationRepresentation(CompilationRepresentationFlags.UseNullAsTrueValue)>]
[<NoEquality; NoComparison>]
type PQ<'V> =
| Mt
| Br of HeapEntry<'V> * PQ<'V> * PQ<'V>
 
let empty = Mt
 
let isEmpty = function | Mt -> true
| _ -> false
 
// Return number of elements in the priority queue.
// /O(log(n)^2)/
let rec size = function
| Mt -> 0
| Br(_, ll, rr) ->
let n = size rr
// rest n p q, where n = size ll, and size ll - size rr = 0 or 1
// returns 1 + size ll - size rr.
let rec rest n pl pr =
match pl with
| Mt -> 1
| Br(_, pll, plr) ->
match pr with
| Mt -> 2
| Br(_, prl, prr) ->
let nm1 = n - 1 in let d = nm1 >>> 1
if (nm1 &&& 1) = 0
then rest d pll prl // subtree sizes: (d or d+1), d; d, d
else rest d plr prr // subtree sizes: d+1, (d or d+1); d+1, d
2 * n + rest n ll rr
 
let peekMin = function | Br(kv, _, _) -> Some(kv.k, kv.v)
| _ -> None
 
let rec push wk wv =
function | Mt -> Br(HeapEntry(wk, wv), Mt, Mt)
| Br(vkv, ll, rr) ->
if wk <= vkv.k then
Br(HeapEntry(wk, wv), push vkv.k vkv.v rr, ll)
else Br(vkv, push wk wv rr, ll)
 
let inline private siftdown wk wv pql pqr =
let rec sift pl pr =
match pl with
| Mt -> Br(HeapEntry(wk, wv), Mt, Mt)
| Br(vkvl, pll, plr) ->
match pr with
| Mt -> if wk <= vkvl.k then Br(HeapEntry(wk, wv), pl, Mt)
else Br(vkvl, Br(HeapEntry(wk, wv), Mt, Mt), Mt)
| Br(vkvr, prl, prr) ->
if wk <= vkvl.k && wk <= vkvr.k then Br(HeapEntry(wk, wv), pl, pr)
elif vkvl.k <= vkvr.k then Br(vkvl, sift pll plr, pr)
else Br(vkvr, pl, sift prl prr)
sift pql pqr
 
let replaceMin wk wv = function | Mt -> Mt
| Br(_, ll, rr) -> siftdown wk wv ll rr
 
let deleteMin = function
| Mt -> Mt
| Br(_, ll, Mt) -> ll
| Br(vkv, ll, rr) ->
let rec leftrem = function | Mt -> vkv, Mt // should never happen
| Br(kvd, Mt, _) -> kvd, Mt
| Br(vkv, Br(kvd, _, _), Mt) ->
kvd, Br(vkv, Mt, Mt)
| Br(vkv, pl, pr) -> let kvd, pqd = leftrem pl
kvd, Br(vkv, pr, pqd)
let (kvd, pqd) = leftrem ll
siftdown kvd.k kvd.v rr pqd;
 
let adjust f pq =
let rec adj = function
| Mt -> Mt
| Br(vkv, ll, rr) -> let nk, nv = f vkv.k vkv.v
siftdown nk nv (adj ll) (adj rr)
adj pq
 
let fromSeq sq =
if Seq.isEmpty sq then Mt
else let nmrtr = sq.GetEnumerator()
let rec build lvl = if lvl = 0 || not (nmrtr.MoveNext()) then Mt
else let ck, cv = nmrtr.Current
let lft = lvl >>> 1
let rght = (lvl - 1) >>> 1
siftdown ck cv (build lft) (build rght)
build (sq |> Seq.length)
 
let merge (pq1:PQ<_>) (pq2:PQ<_>) = // merges without using a sequence
match pq1 with
| Mt -> pq2
| _ ->
match pq2 with
| Mt -> pq1
| _ ->
let rec zipper lvl pq rest =
if lvl = 0 then Mt, pq, rest else
let lft = lvl >>> 1 in let rght = (lvl - 1) >>> 1
match pq with
| Mt ->
match rest with
| [] | Mt :: _ -> Mt, pq, [] // Mt in list never happens
| Br(kv, ll, Mt) :: tl ->
let pl, pql, rstl = zipper lft ll tl
let pr, pqr, rstr = zipper rght pql rstl
siftdown kv.k kv.v pl pr, pqr, rstr
| Br(kv, ll, rr) :: tl ->
let pl, pql, rstl = zipper lft ll (rr :: tl)
let pr, pqr, rstr = zipper rght pql rstl
siftdown kv.k kv.v pl pr, pqr, rstr
| Br(kv, ll, Mt) ->
let pl, pql, rstl = zipper lft ll rest
let pr, pqr, rstr = zipper rght pql rstl
siftdown kv.k kv.v pl pr, pqr, rstr
| Br(kv, ll, rr) ->
let pl, pql, rstl = zipper lft ll (rr :: rest)
let pr, pqr, rstr = zipper rght pql rstl
siftdown kv.k kv.v pl pr, pqr, rstr
let sz = size pq1 + size pq2
let pq, _, _ = zipper sz pq1 [pq2] in pq
 
let popMin pq = match peekMin pq with
| None -> None
| Some(kv) -> Some(kv, deleteMin pq)
 
let toSeq pq = Seq.unfold popMin pq
 
let sort sq = sq |> fromSeq |> toSeq</syntaxhighlight>
 
The above code implements a "merge" function so that no internal sequence generation is necessary as generation of sequence iterators is quite inefficient in F# for a combined O(n) computational time complexity but a considerable reduction in the constant factor overhead.
 
Other than the "merge" function, the Min Heap Priority Queue has the same time complexity as for the Binomial Heap Priority Queue above except that "push" has O(log n) performance rather than the amortized O(1) performance; however, the Binomial Heap Priority Queue is generally a constant factor slower due to more complex operations. The Binomial Heap Priority Queue is generally more suited when used where merging of large queues or frequent "push" operations are used; the Min Heap Priority Queue is more suitable for use when replacing the value at the minimum entry of the queue is frequently required, especially when the adjusted value is not displaced very far down the queue on average.
 
===Imperative===
 
'''Min Heap Priority Queue'''
 
As the Min Heap is usually implemented as a [http://opendatastructures.org/versions/edition-0.1e/ods-java/10_1_BinaryHeap_Implicit_Bi.html mutable array binary heap] after a genealogical tree based model invented by [https://en.wikipedia.org/wiki/Michael_Eytzinger Michael Eytzinger] over 400 years ago, the following "ugly imperative" code implements the Min Heap Priority Queue this way; note that the code could be implemented not using "ugly" mutable state variables other than the contents of the array (DotNet List which implements a growable array) but in this case the code would be considerably slower as in not much faster or slower than the functional version since using mutable side effects greatly reduces the number of operations:
<syntaxhighlight lang="fsharp">[<RequireQualifiedAccess>]
module PriorityQ =
 
type HeapEntry<'T> = struct val k:uint32 val v:'T new(k,v) = { k=k;v=v } end
type MinHeapTree<'T> = ResizeArray<HeapEntry<'T>>
 
let empty<'T> = MinHeapTree<HeapEntry<'T>>()
 
let isEmpty (pq: MinHeapTree<_>) = pq.Count = 0
 
let size (pq: MinHeapTree<_>) = let cnt = pq.Count
if cnt = 0 then 0 else cnt - 1
 
let peekMin (pq:MinHeapTree<_>) = if pq.Count > 1 then let kv = pq.[0]
Some (kv.k, kv.v) else None
 
let push k v (pq:MinHeapTree<_>) =
if pq.Count = 0 then pq.Add(HeapEntry(0xFFFFFFFFu,v)) //add an extra entry so there's always a right max node
let mutable nxtlvl = pq.Count in let mutable lvl = nxtlvl <<< 1 //1 past index of value added times 2
pq.Add(pq.[nxtlvl - 1]) //copy bottom entry then do bubble up while less than next level up
while ((lvl <- lvl >>> 1); nxtlvl <- nxtlvl >>> 1; nxtlvl <> 0) do
let t = pq.[nxtlvl - 1] in if t.k > k then pq.[lvl - 1] <- t else lvl <- lvl <<< 1; nxtlvl <- 0 //causes loop break
pq.[lvl - 1] <- HeapEntry(k,v); pq
 
let inline private siftdown k v ndx (pq: MinHeapTree<_>) =
let mutable i = ndx in let mutable ni = i in let cnt = pq.Count - 1
while (ni <- ni + ni + 1; ni < cnt) do
let lk = pq.[ni].k in let rk = pq.[ni + 1].k in let oi = i
let k = if k > lk then i <- ni; lk else k in if k > rk then ni <- ni + 1; i <- ni
if i <> oi then pq.[oi] <- pq.[i] else ni <- cnt //causes loop break
pq.[i] <- HeapEntry(k,v)
 
let replaceMin k v (pq:MinHeapTree<_>) = siftdown k v 0 pq; pq
 
let deleteMin (pq:MinHeapTree<_>) =
let lsti = pq.Count - 2
if lsti <= 0 then pq.Clear(); pq else
let lstkv = pq.[lsti]
pq.RemoveAt(lsti)
siftdown lstkv.k lstkv.v 0 pq; pq
 
let adjust f (pq:MinHeapTree<_>) = //adjust all the contents using the function, then re-heapify
let cnt = pq.Count - 1
let rec adj i =
let lefti = i + i + 1 in let righti = lefti + 1
let ckv = pq.[i] in let (nk, nv) = f ckv.k ckv.v
if righti < cnt then adj righti
if lefti < cnt then adj lefti; siftdown nk nv i pq
else pq.[i] <- HeapEntry(nk, nv)
adj 0; pq
 
let fromSeq sq =
if Seq.isEmpty sq then empty
else let pq = new MinHeapTree<_>(sq |> Seq.map (fun (k, v) -> HeapEntry(k, v)))
let sz = pq.Count in let lkv = pq.[sz - 1]
pq.Add(HeapEntry(UInt32.MaxValue, lkv.v))
let rec build i =
let lefti = i + i + 1
if lefti < sz then
let righti = lefti + 1 in build lefti; build righti
let ckv = pq.[i] in siftdown ckv.k ckv.v i pq
build 0; pq
 
let merge (pq1:MinHeapTree<_>) (pq2:MinHeapTree<_>) =
if pq2.Count = 0 then pq1 else
if pq1.Count = 0 then pq2 else
let pq = empty
pq.AddRange(pq1); pq.RemoveAt(pq.Count - 1)
pq.AddRange(pq2)
let sz = pq.Count - 1
let rec build i =
let lefti = i + i + 1
if lefti < sz then
let righti = lefti + 1 in build lefti; build righti
let ckv = pq.[i] in siftdown ckv.k ckv.v i pq
build 0; pq
 
let popMin pq = match peekMin pq with
| None -> None
| Some(kv) -> Some(kv, deleteMin pq)
 
let toSeq pq = Seq.unfold popMin pq
 
let sort sq = sq |> fromSeq |> toSeq</syntaxhighlight>
 
The comments for the above code are the same as for the functional version; the main difference is that the imperative code takes about two thirds of the time on average.
 
All of the above codes can be tested under the F# REPL using the following:
<syntaxhighlight lang="fsharp">> let testseq = [| (3u, "Clear drains");
(4u, "Feed cat");
(5u, "Make tea");
(1u, "Solve RC tasks");
(2u, "Tax return") |] |> Array.toSeq
let testpq = testseq |> MinHeap.fromSeq
testseq |> Seq.fold (fun pq (k, v) -> MinHeap.push k v pq) MinHeap.empty
|> MinHeap.toSeq |> Seq.iter (printfn "%A") // test slow build
printfn ""
testseq |> MinHeap.fromSeq |> MinHeap.toSeq // test fast build
|> Seq.iter (printfn "%A")
printfn ""
testseq |> MinHeap.sort |> Seq.iter (printfn "%A") // convenience function
printfn ""
MinHeap.merge testpq testpq // test merge
|> MinHeap.toSeq |> Seq.iter (printfn "%A")
printfn ""
testpq |> MinHeap.adjust (fun k v -> uint32 (MinHeap.size testpq) - k, v)
|> MinHeap.toSeq |> Seq.iter (printfn "%A") // test adjust;;</syntaxhighlight>
 
to produce the following output:
{{output}}
<pre>(1u, "Solve RC tasks")
(2u, "Tax return")
(3u, "Clear drains")
(4u, "Feed cat")
(5u, "Make tea")
 
(1u, "Solve RC tasks")
(2u, "Tax return")
(3u, "Clear drains")
(4u, "Feed cat")
(5u, "Make tea")
 
(1u, "Solve RC tasks")
(2u, "Tax return")
(3u, "Clear drains")
(4u, "Feed cat")
(5u, "Make tea")
 
(1u, "Solve RC tasks")
(1u, "Solve RC tasks")
(2u, "Tax return")
(2u, "Tax return")
(3u, "Clear drains")
(3u, "Clear drains")
(4u, "Feed cat")
(4u, "Feed cat")
(5u, "Make tea")
(5u, "Make tea")
 
(0u, "Make tea")
(1u, "Feed cat")
(2u, "Clear drains")
(3u, "Tax return")
(4u, "Solve RC tasks")
val it : unit = ()</pre>
 
Note that the code using "fromSeq" instead of repeated "push" operations to build a queue is considerably faster for large random-order entry sequences.
 
Also note that the imperative version modifies the state of the "testpq" binding for modification operations such as "push" and "deleteMin" or operations derived from those; this means that if the last two tests were reversed then the "merge" would be passed zero sized queues since the "testpq" would have been reduced by the "toSeq" operation (which effectively uses repeated "deleteMin" functions).
 
=={{header|Factor}}==
Factor has priority queues implemented in the library: documentation is available at http://docs.factorcode.org/content/article-heaps.html (or by typing "heaps" help interactively in the listener).
<syntaxhighlight lang="factor"><min-heap> [ {
{ 3 "Clear drains" }
{ 4 "Feed cat" }
{ 5 "Make tea" }
{ 1 "Solve RC tasks" }
{ 2 "Tax return" }
} swap heap-push-all
] [
[ print ] slurp-heap
] bi</syntaxhighlight>
 
output:
<syntaxhighlight lang="factor">Solve RC tasks
Tax return
Clear drains
Feed cat
Make tea</syntaxhighlight>
 
=={{header|Forth}}==
{{works with|gforth|0.7.3}}
<br>
<syntaxhighlight lang="forth">#! /usr/bin/gforth
 
\ Priority queue
 
10 CONSTANT INITIAL-CAPACITY
 
\ creates a new empty queue
: new-queue ( -- addr )
2 INITIAL-CAPACITY 3 * + cells allocate throw
INITIAL-CAPACITY over !
0 over cell + !
;
 
\ deletes a queue
: delete-queue ( addr -- )
free throw
;
 
: queue-capacity ( addr -- n )
@
;
 
\ the number of elements in the queue
: queue-size ( addr -- n )
cell + @
;
 
: resize-queue ( addr -- addr )
dup queue-capacity 2 * dup >r 3 * 2 + cells resize throw
r> over !
;
 
: ix->addr ( addr ix -- addr )
3 * 2 + cells +
;
 
: ix! ( p x y addr ix -- )
ix->addr
tuck 2 cells + !
tuck cell + !
!
;
 
: ix@ ( addr ix -- p x y )
ix->addr
dup @ swap
cell + dup @ swap
cell + @
;
 
: ix->priority ( addr ix -- p )
ix->addr @
;
 
: ix<->ix ( addr ix ix' -- )
-rot over swap ( ix' addr addr ix ) ( )
2over swap 2>r ( ix' addr addr ix ) ( addr ix' )
2dup ix@ 2>r >r ( ix' addr addr ix ) ( addr ix' x y p )
2>r ( ix' addr ) ( addr ix' x y p addr ix )
swap ix@ ( p' x' y' ) ( addr ix' x y p addr ix )
2r> ix! ( ) ( addr ix' x y p )
r> 2r> 2r> ix! ( ) ( )
;
 
: ix-parent ( ix -- ix' )
dup 0> IF
1- 2/
THEN
;
 
: ix-left-son ( ix -- ix' )
2* 1+
;
 
: ix-right-son ( ix -- ix' )
2* 2 +
;
 
: swap? ( addr ix ix' -- f )
rot >r ( ix ix' ) ( addr )
2dup ( ix ix' ix ix' ) ( addr )
r> tuck swap ( ix ix' ix addr addr ix' ) ( )
ix->priority >r ( ix ix' ix addr ) ( p' )
tuck swap ( ix ix' addr addr ix ) ( p' )
ix->priority r> ( ix ix' addr p p' ) ( )
> IF
-rot ix<->ix
true
ELSE
2drop drop
false
THEN
;
 
: ix? ( addr ix -- f )
swap queue-size <
;
 
: bubble-up ( addr ix -- )
2dup dup ix-parent swap ( addr ix addr ix' ix )
swap? IF ( addr ix )
ix-parent recurse
ELSE
2drop
THEN
;
 
: bubble-down ( addr ix -- )
2dup ix-right-son ix? IF
2dup ix-left-son ix->priority >r
2dup ix-right-son ix->priority r> < IF
2dup dup ix-right-son swap? IF
ix-right-son recurse
ELSE
2drop
THEN
ELSE
2dup dup ix-left-son swap? IF
ix-left-son recurse
ELSE
2drop
THEN
THEN
ELSE
2dup ix-left-son ix? IF
2dup dup ix-left-son swap? IF
ix-left-son recurse
ELSE
2drop
THEN
ELSE
2drop
THEN
THEN
;
 
\ enqueues an element with priority p and payload x y into queue addr
: >queue ( p x y addr -- addr )
dup queue-capacity over queue-size =
IF
resize-queue
THEN
dup >r
dup queue-size
ix!
r>
1 over cell + +!
dup dup queue-size 1- bubble-up
;
 
\ dequeues the element with highest priority
: queue> ( addr -- p x y )
dup queue-size 0= IF
1 throw
THEN
dup 0 ix@ 2>r >r dup >r
dup dup queue-size 1- ix@ r> 0 ix!
dup cell + -1 swap +!
0 bubble-down
r> 2r>
;
 
\ dequeues elements and prints them until the queue is empty
: drain-queue ( addr -- )
dup queue-size 0> IF
dup queue>
rot
. ." - " type cr
recurse
ELSE
drop
THEN
;
 
 
\ example
 
new-queue
>r 3 s" Clear drains" r> >queue
>r 4 s" Feed cat" r> >queue
>r 5 s" Make tea" r> >queue
>r 1 s" Solve RC tasks" r> >queue
>r 2 s" Tax return" r> >queue
 
drain-queue</syntaxhighlight>
 
{{out}}
<pre>
1 - Solve RC tasks
2 - Tax return
3 - Clear drains
4 - Feed cat
5 - Make tea
</pre>
 
=={{header|Fortran}}==
<syntaxhighlight lang="fortran">module priority_queue_mod
implicit none
 
type node
character (len=100) :: task
integer :: priority
end type
 
type queue
type(node), allocatable :: buf(:)
integer :: n = 0
contains
procedure :: top
procedure :: enqueue
procedure :: siftdown
end type
 
contains
 
subroutine siftdown(this, a)
class (queue) :: this
integer :: a, parent, child
associate (x => this%buf)
parent = a
do while(parent*2 <= this%n)
child = parent*2
if (child + 1 <= this%n) then
if (x(child+1)%priority > x(child)%priority ) then
child = child +1
end if
end if
if (x(parent)%priority < x(child)%priority) then
x([child, parent]) = x([parent, child])
parent = child
else
exit
end if
end do
end associate
end subroutine
 
function top(this) result (res)
class(queue) :: this
type(node) :: res
res = this%buf(1)
this%buf(1) = this%buf(this%n)
this%n = this%n - 1
call this%siftdown(1)
end function
 
subroutine enqueue(this, priority, task)
class(queue), intent(inout) :: this
integer :: priority
character(len=*) :: task
type(node) :: x
type(node), allocatable :: tmp(:)
integer :: i
x%priority = priority
x%task = task
this%n = this%n +1
if (.not.allocated(this%buf)) allocate(this%buf(1))
if (size(this%buf)<this%n) then
allocate(tmp(2*size(this%buf)))
tmp(1:this%n-1) = this%buf
call move_alloc(tmp, this%buf)
end if
this%buf(this%n) = x
i = this%n
do
i = i / 2
if (i==0) exit
call this%siftdown(i)
end do
end subroutine
end module
 
program main
use priority_queue_mod
 
type (queue) :: q
type (node) :: x
 
call q%enqueue(3, "Clear drains")
call q%enqueue(4, "Feed cat")
call q%enqueue(5, "Make Tea")
call q%enqueue(1, "Solve RC tasks")
call q%enqueue(2, "Tax return")
 
do while (q%n >0)
x = q%top()
print "(g0,a,a)", x%priority, " -> ", trim(x%task)
end do
 
end program
 
! Output:
! 5 -> Make Tea
! 4 -> Feed cat
! 3 -> Clear drains
! 2 -> Tax return
! 1 -> Solve RC tasks
</syntaxhighlight>
 
=={{header|Frink}}==
This uses Frink's ability to call arbitrary Java code and uses Java's PriorityQueue implementation, defining our own comparator function.
<syntaxhighlight lang="frink">pq = newJava["java.util.PriorityQueue", new Comparator[byColumn[0]]]
 
pq.add[[3, "Clear Drains"]]
pq.add[[4, "Feed cat"]]
pq.add[[5, "Make tea"]]
pq.add[[1, "Solve RC tasks"]]
pq.add[[2, "Tax return"]]
 
while ! pq.isEmpty[]
println[pq.poll[]]</syntaxhighlight>
{{out}}
<pre>
[1, Solve RC tasks]
[2, Tax return]
[3, Clear Drains]
[4, Feed cat]
[5, Make tea]
</pre>
 
=={{header|FunL}}==
<syntaxhighlight lang="funl">import util.ordering
native scala.collection.mutable.PriorityQueue
 
data Task( priority, description )
 
def comparator( Task(a, _), Task(b, _) )
| a > b = -1
| a < b = 1
| otherwise = 0
q = PriorityQueue( ordering(comparator) )
 
q.enqueue(
Task(3, 'Clear drains'),
Task(4, 'Feed cat'),
Task(5, 'Make tea'),
Task(1, 'Solve RC tasks'),
Task(2, 'Tax return')
)
 
while not q.isEmpty()
println( q.dequeue() )</syntaxhighlight>
 
{{out}}
 
<pre>
Task(1, Solve RC tasks)
Task(2, Tax return)
Task(3, Clear drains)
Task(4, Feed cat)
Task(5, Make tea)
</pre>
 
=={{header|Go}}==
Go's standard library contains the <code>container/heap</code> package, which which provides operations to operate as a heap any data structure that contains the <code>Push</code>, <code>Pop</code>, <code>Len</code>, <code>Less</code>, and <code>Swap</code> methods, the easiest of which is the <code>Vector</code> type in <code>container/vector</code>.
 
<syntaxhighlight lang="go">package main
 
<lang go>package main
import (
"fmt"
"container/vector"
"container/heap"
)
Line 247 ⟶ 3,939:
type Task struct {
priority int
name string
}
 
type TaskPQ []Task
func (self Task) Less(other interface{}) bool {
 
return self.priority < other.(Task).priority
func (self TaskPQ) Len() int { return len(self) }
func (self TaskPQ) Less(i, j int) bool {
return self[i].priority < self[j].priority
}
func (self TaskPQ) Swap(i, j int) { self[i], self[j] = self[j], self[i] }
func (self *TaskPQ) Push(x interface{}) { *self = append(*self, x.(Task)) }
func (self *TaskPQ) Pop() (popped interface{}) {
popped = (*self)[len(*self)-1]
*self = (*self)[:len(*self)-1]
return
}
 
func main() {
pq := &vector.VectorTaskPQ{ Task { 3, "Clear drains" },
Task { 4, "Feed cat" },
Task { 5, "Make tea" },
Task { 1, "Solve RC tasks" } }
 
// heapify
Line 264 ⟶ 3,966:
 
// enqueue
heap.Push(pq, Task { 2, "Tax return" } )
 
for pq.Len() != 0 {
// dequeue
fmt.Println(heap.Pop(pq))
}
}</syntaxhighlight>
}
</lang>
 
output:
Line 280 ⟶ 3,981:
{4 Feed cat}
{5 Make tea}
</pre>
 
=={{header|Groovy}}==
Groovy can use the built in java PriorityQueue class
<syntaxhighlight lang="groovy">import groovy.transform.Canonical
 
@Canonical
class Task implements Comparable<Task> {
int priority
String name
int compareTo(Task o) { priority <=> o?.priority }
}
 
new PriorityQueue<Task>().with {
add new Task(priority: 3, name: 'Clear drains')
add new Task(priority: 4, name: 'Feed cat')
add new Task(priority: 5, name: 'Make tea')
add new Task(priority: 1, name: 'Solve RC tasks')
add new Task(priority: 2, name: 'Tax return')
 
while (!empty) { println remove() }
}</syntaxhighlight>
 
Output:
<pre>Task(1, Solve RC tasks)
Task(2, Tax return)
Task(3, Clear drains)
Task(4, Feed cat)
Task(5, Make tea)</pre>
 
=={{header|Haskell}}==
One of the best Haskell implementations of priority queues (of which there are many) is [http://hackage.haskell.org/package/pqueue pqueue], which implements a binomial heap.
<syntaxhighlight lang="haskell">import Data.PQueue.Prio.Min
 
main = print (toList (fromList [(3, "Clear drains"),(4, "Feed cat"),(5, "Make tea"),(1, "Solve RC tasks"), (2, "Tax return")]))</syntaxhighlight>
 
Although Haskell's standard library does not have a dedicated priority queue structure, one can (for most purposes) use the built-in <code>Data.Set</code> data structure as a priority queue, as long as no two elements compare equal (since Set does not allow duplicate elements). This is the case here since no two tasks should have the same name. The complexity of all basic operations is still O(log n) although that includes the "elemAt 0" function to retrieve the first element of the ordered sequence if that were required; "fromList" takes O(n log n) and "toList" takes O(n) time complexity. Alternatively, a <code>Data.Map.Lazy</code> or <code>Data.Map.Strict</code> can be used in the same way with the same limitations.
<syntaxhighlight lang="haskell">import qualified Data.Set as S
 
main = print (S.toList (S.fromList [(3, "Clear drains"),(4, "Feed cat"),(5, "Make tea"),(1, "Solve RC tasks"), (2, "Tax return")]))</syntaxhighlight>
{{out}}
<pre>[(1,"Solve RC tasks"),(2,"Tax return"),(3,"Clear drains"),(4,"Feed cat"),(5,"Make tea")]</pre>
 
Alternatively, a homemade min heap implementation:
<syntaxhighlight lang="haskell">data MinHeap a = Nil | MinHeap { v::a, cnt::Int, l::MinHeap a, r::MinHeap a }
deriving (Show, Eq)
 
hPush :: (Ord a) => a -> MinHeap a -> MinHeap a
hPush x Nil = MinHeap {v = x, cnt = 1, l = Nil, r = Nil}
hPush x h = if x < vv -- insert element, try to keep the tree balanced
then if hLength (l h) <= hLength (r h)
then MinHeap { v=x, cnt=cc, l=hPush vv ll, r=rr }
else MinHeap { v=x, cnt=cc, l=ll, r=hPush vv rr }
else if hLength (l h) <= hLength (r h)
then MinHeap { v=vv, cnt=cc, l=hPush x ll, r=rr }
else MinHeap { v=vv, cnt=cc, l=ll, r=hPush x rr }
where (vv, cc, ll, rr) = (v h, 1 + cnt h, l h, r h)
 
hPop :: (Ord a) => MinHeap a -> (a, MinHeap a)
hPop h = (v h, pq) where -- just pop, heed not the tree balance
pq | l h == Nil = r h
| r h == Nil = l h
| v (l h) <= v (r h) = let (vv,hh) = hPop (l h) in
MinHeap {v = vv, cnt = hLength hh + hLength (r h),
l = hh, r = r h}
| otherwise = let (vv,hh) = hPop (r h) in
MinHeap {v = vv, cnt = hLength hh + hLength (l h),
l = l h, r = hh}
 
hLength :: (Ord a) => MinHeap a -> Int
hLength Nil = 0
hLength h = cnt h
 
hFromList :: (Ord a) => [a] -> MinHeap a
hFromList = foldl (flip hPush) Nil
 
hToList :: (Ord a) => MinHeap a -> [a]
hToList = unfoldr f where
f Nil = Nothing
f h = Just $ hPop h
 
main = mapM_ print $ hToList $ hFromList [
(3, "Clear drains"),
(4, "Feed cat"),
(5, "Make tea"),
(1, "Solve RC tasks"),
(2, "Tax return")]</syntaxhighlight>
 
The above code is a Priority Queue but isn't a [https://en.wikipedia.org/wiki/Binary_heap Min Heap based on a Binary Heap] for the following reasons: 1) it does not preserve the standard tree structure of the binary heap and 2) the tree balancing can be completely destroyed by some combinations of "pop" operations. The following code is a true purely functional Min Heap implementation and as well implements the extra optional features of Min Heap's that it can build a new Min Heap from a list in O(n) amortized time rather than the O(n log n) amortized time (for a large number of randomly ordered entries) by simply using repeated "push" operations; as well as the standard "push", "peek", "delete" and "pop" (combines the previous two). As well as the "fromList", "toList", and "sort" functions (the last combines the first two), it also has an "isEmpty" function to test for the empty queue, an "adjust" function that applies a function to every entry in the queue and reheapifies in O(n) amortized time and also the "replaceMin" function which is about twice as fast on the average as combined "delete" followed by "push" operations:
<syntaxhighlight lang="haskell">data MinHeap kv = MinHeapEmpty
| MinHeapLeaf !kv
| MinHeapNode !kv {-# UNPACK #-} !Int !(MinHeap a) !(MinHeap a)
deriving (Show, Eq)
 
emptyPQ :: MinHeap kv
emptyPQ = MinHeapEmpty
 
isEmptyPQ :: PriorityQ kv -> Bool
isEmptyPQ Mt = True
isEmptyPQ _ = False
sizePQ :: (Ord kv) => MinHeap kv -> Int
sizePQ MinHeapEmpty = 0
sizePQ (MinHeapLeaf _) = 1
sizePQ (MinHeapNode _ cnt _ _) = cnt
peekMinPQ :: MinHeap kv -> Maybe kv
peekMinPQ MinHeapEmpty = Nothing
peekMinPQ (MinHeapLeaf v) = Just v
peekMinPQ (MinHeapNode v _ _ _) = Just v
 
pushPQ :: (Ord kv) => kv -> MinHeap kv -> MinHeap kv
pushPQ kv pq = insert kv 0 pq where -- insert element, keeping the tree balanced
insert kv _ MinHeapEmpty = MinHeapLeaf kv
insert kv _ (MinHeapLeaf vv) = if kv <= vv
then MinHeapNode kv 2 (MinHeapLeaf vv) MinHeapEmpty
else MinHeapNode vv 2 (MinHeapLeaf kv) MinHeapEmpty
insert kv msk (MinHeapNode vv cc ll rr) = if kv <= vv
then if nmsk >= 0
then MinHeapNode kv nc (insert vv nmsk ll) rr
else MinHeapNode kv nc ll (insert vv nmsk rr)
else if nmsk >= 0
then MinHeapNode vv nc (insert kv nmsk ll) rr
else MinHeapNode vv nc ll (insert kv nmsk rr)
where nc = cc + 1
nmsk = if msk /= 0 then msk `shiftL` 1 -- walk path to next
else let s = floor $ (log $ fromIntegral nc) / log 2 in
(nc `shiftL` ((finiteBitSize cc) - s)) .|. 1 --never 0 again
 
siftdown :: (Ord kv) => kv -> Int -> MinHeap kv -> MinHeap kv -> MinHeap kv
siftdown kv cnt lft rght = replace cnt lft rght where
replace cc ll rr = case rr of -- adj to put kv in current left/right
MinHeapEmpty -> -- means left is a MinHeapLeaf
case ll of { (MinHeapLeaf vl) ->
if kv <= vl
then MinHeapNode kv 2 ll MinHeapEmpty
else MinHeapNode vl 2 (MinHeapLeaf kv) MinHeapEmpty }
MinHeapLeaf vr ->
case ll of
MinHeapLeaf vl -> if vl <= vr
then if kv <= vl then MinHeapNode kv cc ll rr
else MinHeapNode vl cc (MinHeapLeaf kv) rr
else if kv <= vr then MinHeapNode kv cc ll rr
else MinHeapNode vr cc ll (MinHeapLeaf kv)
MinHeapNode vl ccl lll rrl -> if vl <= vr
then if kv <= vl then MinHeapNode kv cc ll rr
else MinHeapNode vl cc (replace ccl lll rrl) rr
else if kv <= vr then MinHeapNode kv cc ll rr
else MinHeapNode vr cc ll (MinHeapLeaf kv)
MinHeapNode vr ccr llr rrr -> case ll of
(MinHeapNode vl ccl lll rrl) -> -- right is node, so is left
if vl <= vr then
if kv <= vl then MinHeapNode kv cc ll rr
else MinHeapNode vl cc (replace ccl lll rrl) rr
else if kv <= vr then MinHeapNode kv cc ll rr
else MinHeapNode vr cc ll (replace ccr llr rrr)
 
replaceMinPQ :: (Ord kv) => a -> MinHeap kv -> MinHeap kv
replaceMinPQ _ MinHeapEmpty = MinHeapEmpty
replaceMinPQ kv (MinHeapLeaf _) = MinHeapLeaf kv
replaceMinPQ kv (MinHeapNode _ cc ll rr) = siftdown kv cc ll rr where
 
deleteMinPQ :: (Ord kv) => MinHeap kv -> MinHeap kv
deleteMinPQ MinHeapEmpty = MinHeapEmpty -- remove min keeping tree balanced
deleteMinPQ pq = let (dkv, npq) = delete 0 pq in
replaceMinPQ dkv npq where
delete _ (MinHeapLeaf vv) = (vv, MinHeapEmpty)
delete msk (MinHeapNode vv cc ll rr) =
if rr == MinHeapEmpty -- means left is MinHeapLeaf
then case ll of (MinHeapLeaf vl) -> (vl, MinHeapLeaf vv)
else if nmsk >= 0 -- means only deal with left
then let (dv, npq) = delete nmsk ll in
(dv, MinHeapNode vv (cc - 1) npq rr)
else let (dv, npq) = delete nmsk rr in
(dv, MinHeapNode vv (cc - 1) ll npq)
where nmsk = if msk /= 0 then msk `shiftL` 1 -- walk path to last
else let s = floor $ (log $ fromIntegral cc) / log 2 in
(cc `shiftL` ((finiteBitSize cc) - s)) .|. 1 --never 0 again
 
adjustPQ :: (Ord kv) => (kv -> kv) -> MinHeap kv -> MinHeap kv
adjustPQ f pq = adjust pq where -- applies function to every element and reheapifies
adjust MinHeapEmpty = MinHeapEmpty
adjust (MinHeapLeaf v) = MinHeapLeaf (f v)
adjust (MinHeapNode vv cc ll rr) = siftdown (f vv) cc (adjust ll) (adjust rr)
 
fromListPQ :: (Ord kv) => [kv] -> MinHeap kv
-- fromListPQ = foldl (flip pushPQ) MinHeapEmpty -- O(n log n) time; slow
fromListPQ [] = MinHeapEmpty -- O(n) time using "adjust id" which is O(n)
fromListPQ xs = let (_, pq) = build 1 xs in pq where
sz = length xs
szd2 = sz `div` 2
build _ [] = ([], MinHeapEmpty)
build lvl (x:xs') = if lvl > szd2 then (xs', MinHeapLeaf x)
else let nlvl = lvl + lvl in
let (xrl, pql) = build nlvl xs' in
let (xrr, pqr) = if nlvl >= sz
then (xrl, MinHeapEmpty) -- no right leaf
else build (nlvl + 1) xrl in
let cnt = sizePQ pql + sizePQ pqr + 1 in
(xrr, siftdown x cnt pql pqr)
popMinPQ :: (Ord kv) => MinHeap kv -> Maybe (kv, MinHeap kv)
popMinPQ pq = case peekMinPQ pq of
Nothing -> Nothing
Just v -> Just (v, deleteMinPQ pq)
toListPQ :: (Ord kv) => MinHeap kv -> [kv]
toListPQ = unfoldr f where
f MinHeapEmpty = Nothing
f pq = popMinPQ pq
 
sortPQ :: (Ord kv) => [kv] -> [kv]
sortPQ ls = toListPQ $ fromListPQ ls</syntaxhighlight>
 
If one is willing to forgo the fast O(1) "size" function and to give up strict conformance to the Heap tree structure (where rather than building each new level until each left node is full to that level before increasing level to the right, a new level is built by promoting leaves to branches only containing left leaves until all branches have left leaves before filling any right leaves of that level) although having even better tree balancing and therefore at least as high efficiency, one can use the following code adapted from the [http://www.cl.cam.ac.uk/~lp15/MLbook/programs/sample4.sml ''ML'' PRIORITY_QUEUE code by Lawrence C. Paulson] including separating the key/value pairs as separate entries in the data structure for better comparison efficiency; as noted in the code comments, a "size" function to output the number of elements in the queue (fairly quickly in O((log n)^2)), an "adjust" function to apply a function to all elements and reheapify in O(n) time, and a "merge" function to merge two queues has been added to the ML code:
<syntaxhighlight lang="haskell">data PriorityQ k v = Mt
| Br !k v !(PriorityQ k v) !(PriorityQ k v)
deriving (Eq, Ord, Read, Show)
 
emptyPQ :: PriorityQ k v
emptyPQ = Mt
 
isEmptyPQ :: PriorityQ k v -> Bool
isEmptyPQ Mt = True
isEmptyPQ _ = False
 
-- The size function isn't from the ML code, but an implementation was
-- suggested by Bertram Felgenhauer on Haskell Cafe, so it is included.
 
-- Return number of elements in the priority queue.
-- /O(log(n)^2)/
sizePQ :: PriorityQ k v -> Int
sizePQ Mt = 0
sizePQ (Br _ _ pl pr) = 2 * n + rest n pl pr where
n = sizePQ pr
-- rest n p q, where n = sizePQ q, and sizePQ p - sizePQ q = 0 or 1
-- returns 1 + sizePQ p - sizePQ q.
rest :: Int -> PriorityQ k v -> PriorityQ k v -> Int
rest 0 Mt _ = 1
rest 0 _ _ = 2
rest n (Br _ _ ll lr) (Br _ _ rl rr) = case r of
0 -> rest d ll rl -- subtree sizes: (d or d+1), d; d, d
1 -> rest d lr rr -- subtree sizes: d+1, (d or d+1); d+1, d
where m1 = n - 1
d = m1 `shiftR` 1
r = m1 .&. 1
 
peekMinPQ :: PriorityQ k v -> Maybe (k, v)
peekMinPQ Mt = Nothing
peekMinPQ (Br k v _ _) = Just (k, v)
 
pushPQ :: Ord k => k -> v -> PriorityQ k v -> PriorityQ k v
pushPQ wk wv Mt = Br wk wv Mt Mt
pushPQ wk wv (Br vk vv pl pr)
| wk <= vk = Br wk wv (pushPQ vk vv pr) pl
| otherwise = Br vk vv (pushPQ wk wv pr) pl
siftdown :: Ord k => k -> v -> PriorityQ k v -> PriorityQ k v -> PriorityQ k v
siftdown wk wv Mt _ = Br wk wv Mt Mt
siftdown wk wv (pl @ (Br vk vv _ _)) Mt
| wk <= vk = Br wk wv pl Mt
| otherwise = Br vk vv (Br wk wv Mt Mt) Mt
siftdown wk wv (pl @ (Br vkl vvl pll plr)) (pr @ (Br vkr vvr prl prr))
| wk <= vkl && wk <= vkr = Br wk wv pl pr
| vkl <= vkr = Br vkl vvl (siftdown wk wv pll plr) pr
| otherwise = Br vkr vvr pl (siftdown wk wv prl prr)
replaceMinPQ :: Ord k => k -> v -> PriorityQ k v -> PriorityQ k v
replaceMinPQ wk wv Mt = Mt
replaceMinPQ wk wv (Br _ _ pl pr) = siftdown wk wv pl pr
 
deleteMinPQ :: (Ord k) => PriorityQ k v -> PriorityQ k v
deleteMinPQ Mt = Mt
deleteMinPQ (Br _ _ pr Mt) = pr
deleteMinPQ (Br _ _ pl pr) = let (k, v, npl) = leftrem pl in
siftdown k v pr npl where
leftrem (Br k v Mt Mt) = (k, v, Mt)
leftrem (Br vk vv (Br k v _ _) Mt) = (k, v, Br vk vv Mt Mt)
leftrem (Br vk vv pl pr) = let (k, v, npl) = leftrem pl in
(k, v, Br vk vv pr npl)
 
-- the following function has been added to the ML code to apply a function
-- to all the entries in the queue and reheapify in O(n) time
adjustPQ :: (Ord k) => (k -> v -> (k, v)) -> PriorityQ k v -> PriorityQ k v
adjustPQ f pq = adjust pq where -- applies function to every element and reheapifies
adjust Mt = Mt
adjust (Br vk vv pl pr) = let (k, v) = f vk vv in
siftdown k v (adjust pl) (adjust pr)
 
fromListPQ :: (Ord k) => [(k, v)] -> PriorityQ k v
-- fromListPQ = foldl (flip pushPQ) Mt -- O(n log n) time; slow
fromListPQ [] = Mt -- O(n) time using adjust-from-bottom which is O(n)
fromListPQ xs = let (pq, _) = build (length xs) xs in pq where
build 0 xs = (Mt, xs)
build lvl ((k, v):xs') = let (pl, xrl) = build (lvl `shiftR` 1) xs'
(pr, xrr) = build ((lvl - 1) `shiftR` 1) xrl in
(siftdown k v pl pr, xrr)
 
-- the following function has been added to merge two queues in O(m + n) time
-- where m and n are the sizes of the two queues
mergePQ :: (Ord k) => PriorityQ k v -> PriorityQ k v -> PriorityQ k v
mergePQ pq1 Mt = pq1 -- from concatenated "dumb" list
mergePQ Mt pq2 = pq2 -- in O(m + n) time where m,n are sizes pq1,pq2
mergePQ pq1 pq2 = fromListPQ (zipper pq1 $ zipper pq2 []) where
zipper (Br wk wv Mt _) appndlst = (wk, wv) : appndlst
zipper (Br wk wv pl Mt) appndlst = (wk, wv) : zipper pl appndlst
zipper (Br wk wv pl pr) appndlst = (wk, wv) : zipper pl (zipper pr appndlst)
 
popMinPQ :: (Ord k) => PriorityQ k v -> Maybe ((k, v), PriorityQ k v)
popMinPQ pq = case peekMinPQ pq of
Nothing -> Nothing
Just kv -> Just (kv, deleteMinPQ pq)
 
toListPQ :: (Ord k) => PriorityQ k v -> [(k, v)]
toListPQ Mt = [] -- unfoldr popMinPQ
toListPQ pq @ (Br vk vv _ _) = (vk, vv) : (toListPQ $ deleteMinPQ pq)
 
sortPQ :: (Ord k) => [(k, v)] -> [(k, v)]
sortPQ ls = toListPQ $ fromListPQ ls</syntaxhighlight>
 
The above codes compile but do not run with GHC Haskell version 7.8.3 using the LLVM back end with LLVM version 3.4 and full optimization turned on under Windows 32; they were tested under Windows 64 and 32 using the Native Code Generator back end with full optimization. With GHC Haskell version 7.10.1 they compile and run with or without LLVM 3.5.1 for 32-bit Windows (64-bit GHC Haskell under Windows does not run with LLVM for version 7.10.1), with a slight execution speed advantage to using LLVM.
 
Min Heaps are faster than Priority Queue's based on Binomial Heaps (or Leftist or Skewed Heaps) when one mainly requires fast replacement of the head of the queue without many fresh "push" operations; Binomial Heap based versions (or Leftist or Skewed Heap based versions) are faster for merging of a series of large queues into one and for algorithms that have a lot of "push" operations of random entries. Both have O(log n) average "push" and "pop" time complexity with O(1) for "peek", but Binomial Heap based queues (and the others) tend to be somewhat slower by a constant factor due to more complex operations.
 
Min Heaps are also faster than the use of balanced tree Set's or Map's where many references are made to the next element in the queue (O(1) complexity rather than O(log n)) or where frequent modification and reinsertion of the next element in the queue is required (still O(log n) but faster by a constant factor greater than two on average) and generally faster by a constant factor as operations near the top of the queue don't have to traverse the entire tree structure; O(log n) is worst case time complexity for "replace" operations not average.
 
The above codes when tested with the following "main" function (with a slight modification for the first test when the combined kv entry is used):
<syntaxhighlight lang="haskell">testList = [ (3, "Clear drains"),
(4, "Feed cat"),
(5, "Make tea"),
(1, "Solve RC tasks"),
(2, "Tax return") ]
 
testPQ = fromListPQ testList
 
main = do -- slow build
mapM_ print $ toListPQ $ foldl (\pq (k, v) -> pushPQ k v pq) emptyPQ testList
putStrLn "" -- fast build
mapM_ print $ toListPQ $ fromListPQ testList
putStrLn "" -- combined fast sort
mapM_ print $ sortPQ testList
putStrLn "" -- test merge
mapM_ print $ toListPQ $ mergePQ testPQ testPQ
putStrLn "" -- test adjust
mapM_ print $ toListPQ $ adjustPQ (\x y -> (x * (-1), y)) testPQ</syntaxhighlight>
 
has the output as follows:
{{output}}
<pre>(1,"Solve RC tasks")
(2,"Tax return")
(3,"Clear drains")
(4,"Feed cat")
(5,"Make tea")
 
(1,"Solve RC tasks")
(2,"Tax return")
(3,"Clear drains")
(4,"Feed cat")
(5,"Make tea")
 
(1,"Solve RC tasks")
(2,"Tax return")
(3,"Clear drains")
(4,"Feed cat")
(5,"Make tea")
 
(1,"Solve RC tasks")
(1,"Solve RC tasks")
(2,"Tax return")
(2,"Tax return")
(3,"Clear drains")
(3,"Clear drains")
(4,"Feed cat")
(4,"Feed cat")
(5,"Make tea")
(5,"Make tea")
 
(-5,"Make tea")
(-4,"Feed cat")
(-3,"Clear drains")
(-2,"Tax return")
(-1,"Solve RC tasks")</pre>
 
but the first method uses the slower way of building a queue.
 
=={{header|Icon}} and {{header|Unicon}}==
This solution uses classes provided by the UniLib package.
<tt>Heap</tt> is an implementation of a priority queue and
<tt>Closure</tt> is used to allow the queue to order lists based on
their first element. The solution only works in Unicon.
<syntaxhighlight lang="unicon">import Utils # For Closure class
import Collections # For Heap (dense priority queue) class
 
procedure main()
pq := Heap(, Closure("[]",Arg,1) )
pq.add([3, "Clear drains"])
pq.add([4, "Feed cat"])
pq.add([5, "Make tea"])
pq.add([1, "Solve RC tasks"])
pq.add([2, "Tax return"])
 
while task := pq.get() do write(task[1]," -> ",task[2])
end
</syntaxhighlight>
Output when run:
<pre>
1 -> Solve RC tasks
2 -> Tax return
3 -> Clear drains
4 -> Feed cat
5 -> Make tea
</pre>
 
Line 286 ⟶ 4,398:
Implementation:
 
<langsyntaxhighlight lang="j">coclass 'priorityQueue'
 
PRI=: ''
Line 308 ⟶ 4,420:
QUE=: y}.QUE
r
)</langsyntaxhighlight>
 
Efficiency is obtained by batching requests. Size of batch for insert is determined by size of arguments. Size of batch for topN is its right argument.
Line 314 ⟶ 4,426:
Example:
 
<langsyntaxhighlight lang="j"> Q=: conew'priorityQueue'
3 4 5 1 2 insert__Q 'clear drains';'feed cat';'make tea';'solve rc task';'tax return'
>topN__Q 1
Line 322 ⟶ 4,434:
clear drains
tax return
solve rc task</langsyntaxhighlight>
 
=={{header|Java}}==
Java has a <code>PriorityQueue</code> class. It requires either the elements implement <code>Comparable</code>, or you give it a custom <code>Comparator</code> to compare the elements.
 
<langsyntaxhighlight lang="java">import java.util.PriorityQueue;
 
class Task implements Comparable<Task> {
Line 346 ⟶ 4,458:
}
 
public static final void main(String[] args) {
PriorityQueue<Task> pq = new PriorityQueue<Task>();
pq.add(new Task(3, "Clear drains"));
Line 357 ⟶ 4,469:
System.out.println(pq.remove());
}
}</langsyntaxhighlight>
{{out}}
 
output:
<pre>
1, Solve RC tasks
Line 367 ⟶ 4,478:
5, Make tea
</pre>
 
=={{header|jq}}==
Since jq is a functional language, the priority queue must be represented explicitly as data; in the following, we use a JSON object with keys as priorities (strings). Since a given priority level may have more than task, we use arrays to hold the values.
 
The special key "priorities" is used to store the priorities in a sorted array. Since "sort" is fast we will use that rather than optimizing insertion in the priorities array.
 
We assume that if an item of a given priority is already in the priority queue, there is no need to add it again.<syntaxhighlight lang="jq"># In the following, pq stands for "priority queue".
 
# Add an item with the given priority (an integer,
# or a string representing an integer)
# Input: a pq
def pq_add(priority; item):
(priority|tostring) as $p
| if .priorities|index($p) then
if (.[$p] | index(item)) then . else .[$p] += [item] end
else .[$p] = [item] | .priorities = (.priorities + [$p] | sort)
end ;
 
# emit [ item, pq ]
# Input: a pq
def pq_pop:
.priorities as $keys
| if ($keys|length) == 0 then [ null, . ]
else
if (.[$keys[0]] | length) == 1
then .priorities = .priorities[1:]
else .
end
| [ (.[$keys[0]])[0], (.[$keys[0]] = .[$keys[0]][1:]) ]
end ;
 
# Emit the item that would be popped, or null if there is none
# Input: a pq
def pq_peep:
.priorities as $keys
| if ($keys|length) == 0 then null
else (.[$keys[0]])[0]
end ;
 
# Add a bunch of tasks, presented as an array of arrays
# Input: a pq
def pq_add_tasks(list):
reduce list[] as $pair (.; . + pq_add( $pair[0]; $pair[1]) ) ;
 
# Pop all the tasks, producing a stream
# Input: a pq
def pq_pop_tasks:
pq_pop as $pair
| if $pair[0] == null then empty
else $pair[0], ( $pair[1] | pq_pop_tasks )
end ;
 
# Input: a bunch of tasks, presented as an array of arrays
def prioritize:
. as $list | {} | pq_add_tasks($list) | pq_pop_tasks ;
</syntaxhighlight>
The specific task:
<syntaxhighlight lang="jq">
[ [3, "Clear drains"],
[4, "Feed cat"],
[5, "Make tea"],
[1, "Solve RC tasks"],
[2, "Tax return"]
] | prioritize
</syntaxhighlight>
{{Out}}
"Solve RC tasks"
"Tax return"
"Clear drains"
"Feed cat"
"Make tea"
 
=={{header|Julia}}==
Julia has built-in support for priority queues, though the <code>PriorityQueue</code> type is not exported by default. Priority queues are a specialization of the <code>Dictionary</code> type having ordered values, which serve as the priority. In addition to all of the methods of standard dictionaries, priority queues support: <code>enqueue!</code>, which adds an item to the queue, <code>dequeue!</code> which removes the lowest priority item from the queue, returning its key, and <code>peek</code>, which returns the (key, priority) of the lowest priority entry in the queue. The ordering behavior of the queue, which by default is its value sort order (typically low to high), can be set by passing an order directive to its constructor. For this task, <code>Base.Order.Reverse</code> is used to set-up the <code>task</code> queue to return tasks from high to low priority.
<syntaxhighlight lang="julia">
using Base.Collections
 
test = ["Clear drains" 3;
"Feed cat" 4;
"Make tea" 5;
"Solve RC tasks" 1;
"Tax return" 2]
 
task = PriorityQueue(Base.Order.Reverse)
for i in 1:size(test)[1]
enqueue!(task, test[i,1], test[i,2])
end
 
println("Tasks, completed according to priority:")
while !isempty(task)
(t, p) = peek(task)
dequeue!(task)
println(" \"", t, "\" has priority ", p)
end</syntaxhighlight>
 
{{out}}
<pre>Tasks, completed according to priority:
"Make tea" has priority 5
"Feed cat" has priority 4
"Clear drains" has priority 3
"Tax return" has priority 2
"Solve RC tasks" has priority 1
</pre>
 
=={{header|Kotlin}}==
{{trans|Java}}
<syntaxhighlight lang="scala">import java.util.PriorityQueue
 
internal data class Task(val priority: Int, val name: String) : Comparable<Task> {
override fun compareTo(other: Task) = when {
priority < other.priority -> -1
priority > other.priority -> 1
else -> 0
}
}
 
private infix fun String.priority(priority: Int) = Task(priority, this)
 
fun main(args: Array<String>) {
val q = PriorityQueue(listOf("Clear drains" priority 3,
"Feed cat" priority 4,
"Make tea" priority 5,
"Solve RC tasks" priority 1,
"Tax return" priority 2))
while (q.any()) println(q.remove())
}</syntaxhighlight>
{{out}}
<pre>Task(priority=1, name=Solve RC tasks)
Task(priority=2, name=Tax return)
Task(priority=3, name=Clear drains)
Task(priority=4, name=Feed cat)
Task(priority=5, name=Make tea)</pre>
 
=={{header|Lasso}}==
<syntaxhighlight lang="lasso">define priorityQueue => type {
data
store = map,
cur_priority = void
 
public push(priority::integer, value) => {
local(store) = .`store`->find(#priority)
 
if(#store->isA(::array)) => {
#store->insert(#value)
return
}
.`store`->insert(#priority=array(#value))
 
.`cur_priority`->isA(::void) or #priority < .`cur_priority`
? .`cur_priority` = #priority
}
 
public pop => {
.`cur_priority` == void
? return void
 
local(store) = .`store`->find(.`cur_priority`)
local(retVal) = #store->first
 
#store->removeFirst&size > 0
? return #retVal
// Need to find next priority
.`store`->remove(.`cur_priority`)
 
if(.`store`->size == 0) => {
.`cur_priority` = void
else
// There are better / faster ways to do this
// The keys are actually already sorted, but the order of
// storage in a map is not actually defined, can't rely on it
.`cur_priority` = .`store`->keys->asArray->sort&first
}
 
return #retVal
}
 
public isEmpty => (.`store`->size == 0)
 
}
 
local(test) = priorityQueue
 
#test->push(2,`e`)
#test->push(1,`H`)
#test->push(5,`o`)
#test->push(2,`l`)
#test->push(5,`!`)
#test->push(4,`l`)
 
while(not #test->isEmpty) => {
stdout(#test->pop)
}</syntaxhighlight>
 
{{out}}
<pre>Hello!</pre>
 
=={{header|Logtalk}}==
 
Logtalk comes with a [https://github.com/LogtalkDotOrg/logtalk3/tree/master/library/heaps heap implementation] out of the box. As such it by definition also has a priority queue. It can be used at the toplevel like this (with some formatting changes for clarity, and <code>%</code> marking comments that would not be in the output):
 
<syntaxhighlight lang="logtalk">?- logtalk_load(heaps(loader)). % also `{heaps(loader)}.` on most back-ends
% output varies by settings and what's already been loaded
?- heap(<)::new(H0), % H0 contains an empty heap
heap(<)::insert(3, 'Clear drains', H0, H1), % as with Prolog, variables are in the mathematical
% sense: immutable, so we make a new heap from the empty one
heap(<)::insert(4, 'Feed cat',H1, H2), % with each insertion a new heap
heap(<)::top(H2, K2, V2), % K2=3, V2='Clear drains',
% H2=t(2, [], t(3, 'Clear drains', t(4, 'Feed cat', t, t), t))
heap(<)::insert_all(
[
5-'Make tea',
1-'Solve RC tasks',
2-'Tax return'
], H2, H3), % it's easier and more efficient to add items in K-V pairs
heap(<)::top(H3, K3, V3), % K3=1, V3='Solve RC tasks',
% H3=t(5, [], t(1, 'Solve RC tasks', t(3, 'Clear drains',
% t(4, 'Feed cat', t, t), t), t(2, 'Tax return',
% t(5, 'Make tea', t, t), t))),
heap(<)::delete(H3, K3, V3, H4), % K3=1, V3='Solve RC tasks',
% H4=t(4, [5], t(2, 'Tax return', t(3, 'Clear drains',
% t(4, 'Feed cat', t, t), t), t(5, 'Make tea', t, t))),
heap(<)::top(H4, K4, V4). % K4=2, V4='Tax return'</syntaxhighlight>
 
Since <code>heap(Ordering)</code> is a parametrized object in Logtalk, with the parameter being the ordering predicate, we actually use <code>heap(<)</code> object to get min ordering. There are two objects provided in Logtalk that eliminate the unnecessary replication of the two most common orderings:
 
<syntaxhighlight lang="logtalk">:- object(minheap,
extends(heap(<))).
 
:- info([
version is 1:0:0,
author is 'Paulo Moura.',
date is 2010-02-19,
comment is 'Min-heap implementation. Uses standard order to compare keys.'
]).
 
:- end_object.
 
 
:- object(maxheap,
extends(heap(>))).
 
:- info([
version is 1:0:0,
author is 'Paulo Moura.',
date is 2010-02-19,
comment is 'Max-heap implementation. Uses standard order to compare keys.'
]).
 
:- end_object.</syntaxhighlight>
 
Given the presence of these two objects, all of the example code above could have <code>heap(<)</code> replaced with <code>minheap</code> for identical results (including identical performance). It also illustrates how quickly and easily other orderings could be provided at need.
 
=={{header|Lua}}==
 
This implementation uses a table with priorities as keys and queues as values. Queues for each priority are created when putting items as needed and are shrunk as necessary when popping items and removed when they are empty. Instead of using a plain array table for each queue, the technique shown in the Lua implementation from the [[Queue/Definition#Lua | Queue]] task is used. This avoids having to use <code>table.remove(t, 1)</code> to get and remove the first queue element, which is rather slow for big tables.
 
<syntaxhighlight lang="lua">PriorityQueue = {
__index = {
put = function(self, p, v)
local q = self[p]
if not q then
q = {first = 1, last = 0}
self[p] = q
end
q.last = q.last + 1
q[q.last] = v
end,
pop = function(self)
for p, q in pairs(self) do
if q.first <= q.last then
local v = q[q.first]
q[q.first] = nil
q.first = q.first + 1
return p, v
else
self[p] = nil
end
end
end
},
__call = function(cls)
return setmetatable({}, cls)
end
}
 
setmetatable(PriorityQueue, PriorityQueue)
 
-- Usage:
pq = PriorityQueue()
 
tasks = {
{3, 'Clear drains'},
{4, 'Feed cat'},
{5, 'Make tea'},
{1, 'Solve RC tasks'},
{2, 'Tax return'}
}
 
for _, task in ipairs(tasks) do
print(string.format("Putting: %d - %s", unpack(task)))
pq:put(unpack(task))
end
 
for prio, task in pq.pop, pq do
print(string.format("Popped: %d - %s", prio, task))
end</syntaxhighlight>
 
'''Output:'''
 
Putting: 3 - Clear drains
Putting: 4 - Feed cat
Putting: 5 - Make tea
Putting: 1 - Solve RC tasks
Putting: 2 - Tax return
Popped: 1 - Solve RC tasks
Popped: 2 - Tax return
Popped: 3 - Clear drains
Popped: 4 - Feed cat
Popped: 5 - Make tea
 
The implementation is faster than the Python implementations below using <code>queue.PriorityQueue</code> or <code>heapq</code>, even when comparing the standard Lua implementation against [[PyPy]] and millions of tasks are added to the queue. With LuaJIT it is yet faster. The following code measures the time needed to add 10<sup>7</sup> tasks with a random priority between 1 and 1000 and to retrieve them from the queue again in order.
 
<syntaxhighlight lang="lua">-- Use socket.gettime() for benchmark measurements
-- since it has millisecond precision on most systems
local socket = require("socket")
 
n = 10000000 -- number of tasks added (10^7)
m = 1000 -- number different priorities
 
local pq = PriorityQueue()
 
print(string.format("Adding %d tasks with random priority 1-%d ...", n, m))
start = socket.gettime()
 
for i = 1, n do
pq:put(math.random(m), i)
end
 
print(string.format("Elapsed: %.3f ms.", (socket.gettime() - start) * 1000))
 
print("Retrieving all tasks in order...")
start = socket.gettime()
 
local pp = 0
local pv = 0
 
for i = 1, n do
local p, task = pq:pop()
 
-- check that tasks are popped in ascending priority
assert(p >= pp)
 
if pp == p then
-- check that tasks within one priority maintain the insertion order
assert(task > pt)
end
 
pp = p
pt = task
end
 
print(string.format("Elapsed: %.3f ms.", (socket.gettime() - start) * 1000))</syntaxhighlight>
 
=={{header|M2000 Interpreter}}==
For these three examples, we can use same priorities, so if a priority exist then the new insertion not alter the top item (which we pop or peek from queue).
 
===Using unordered array===
<syntaxhighlight lang="m2000 interpreter">
Module UnOrderedArray {
Class PriorityQueue {
Private:
Dim Item()
many=0, level=0, first
cmp = lambda->0
Module Reduce {
if .many<.first*2 then exit
if .level<.many/2 then .many/=2 : Dim .Item(.many)
}
Public:
Module Clear {
Dim .Item() \\ erase all
.many<=0 \\ default
.Level<=0
}
Module Add {
if .level=.many then
if .many=0 then Error "Define Size First"
Dim .Item(.many*2)
.many*=2
end if
Read Item
if .level=0 then
.Item(0)=Item
else.If .cmp(.Item(0), Item)=-1 then \\ Item is max
.Item(.level)=Item
swap .Item(0), .Item(.level)
else
.Item(.level)=Item
end if
.level++
}
Function Peek {
if .level=0 then error "empty"
=.Item(0)
}
Function Poll {
if .level=0 then error "empty"
=.Item(0)
if .level=2 then
swap .Item(0), .Item(1)
.Item(1)=0
.Level<=1
else.If .level>2 then
.Level--
Swap .Item(.level), .Item(0)
.Item(.level)=0
for I=.level-1 to 1
if .cmp(.Item(I), .Item(I-1))=1 then Swap .Item(I), .Item(I-1)
next
else
.level<=0 : .Item(0)=0
end if
.Reduce
}
Module Remove {
if .level=0 then error "empty"
Read Item
k=true
if .cmp(.Item(0), Item)=0 then
Item=.Poll()
K~ \\ k=false
else.If .Level>1 then
I2=.Level-1
for I=1 to I2
if k then
if .cmp(.Item(I), Item)=0 then
if I<I2 then Swap .Item(I), .Item(I2)
.Item(I2)=0
k=false
end if
else
exit
end if
next
.Level--
end if
if k then Error "Not Found"
.Reduce
}
Function Size {
if .many=0 then Error "Define Size First"
=.Level
}
Class:
Module PriorityQueue {
if .many>0 then Error "Clear List First"
Read .many, .cmp
.first<=.many
Dim .Item(.many)
}
}
Class Item { X, S$
Class: // constructor as temporary definition
Module Item {Read .X, .S$}
}
Queue=PriorityQueue(100, Lambda -> {Read A,B : =Compare(A.X,B.X)})
Queue.Add Item(3, "Clear drains") : Gosub PrintTop()
Queue.Add Item(4 ,"Feed cat") : PrintTop()
Queue.Add Item(5 ,"Make tea") : PrintTop()
Queue.Add Item(1 ,"Solve RC tasks") : PrintTop()
Queue.Add Item(2 ,"Tax return") : PrintTop()
Print "remove items"
While true
MM=Queue.Poll() :Print MM.X, MM.S$,,"Size="; Queue.Size()
if Queue.Size()=0 then exit
PrintTop()
End While
Sub PrintTop()
M=Queue.Peek() : Print "Item ";M.X, M.S$
End Sub
}
UnOrderedArray
</syntaxhighlight>
 
===Using a stack with arrays as elements===
Every insertion push item using binary search in proper position. Pop is very fast. Cons() used for demo purposes, make a new array from a series of arrays (a=cons(a,a) add to a an a . Variable a is a pointer to array (a tuple)
 
<syntaxhighlight lang="m2000 interpreter">
Module PriorityQueue {
a= ((3, "Clear drains"), (4 ,"Feed cat"), ( 5 , "Make tea"))
a=cons(a, ((1 ,"Solve RC tasks"), ( 2 , "Tax return")))
b=stack
comp=lambda (a, b) -> array(a, 0)<array(b, 0)
module InsertPQ (a, n, &comp) {
if len(a)=0 then stack a {data n} : exit
if comp(n, stackitem(a)) then stack a {push n} : exit
stack a {
push n
t=2: b=len(a)
m=b
while t<=b
t1=m
m=(b+t) div 2
if m=0 then m=t1 : exit
If comp(stackitem(m),n) then t=m+1: continue
b=m-1
m=b
end while
if m>1 then shiftback m
}
}
n=each(a)
while n
InsertPq b, array(n), &comp
end while
n1=each(b)
while n1
m=stackitem(n1)
print array(m, 0), array$(m, 1)
end while
\\ Peek topitem (without popping)
print Array$(stackitem(b), 1)
\\ Pop item
Stack b {
Read old
}
print Array$(old, 1)
def Peek$(a)=Array$(stackitem(a), 1)
Function Pop$(a) {
stack a {
=Array$(stackitem(), 1)
drop
}
}
print Peek$(b)
print Pop$(b)
def IsEmpty(a)=len(a)=0
while not IsEmpty(b)
print pop$(b)
end while
}
PriorityQueue
</syntaxhighlight>
 
===Using a stack with Groups as elements===
This is the same as previous but now we use a group (a user object for M2000). InsertPQ is the same as before. Lambda comp has change only. We didn't use pointers to groups. All groups here works as values, so when we get a peek we get a copy of group in top position. All members of a group may not values, so if we have a pointer to group then we get a copy of that pointer, but then we can make changes and that changes happen for the group which we get the copy.
 
<syntaxhighlight lang="m2000 interpreter">
// class definitions are global
// if there aren't defintions in a class
global countmany=0&
class obj {
x, s$
property toString$ {
value (sp=8) {
link parent x, s$ to x, s$
value$=format$("{0::-5}"+string$(" ", sp)+"{1:20}", x, s$)
}
}
remove {
countmany--
}
class:
module obj (.x, .s$) {countmany++}
}
Module PriorityQueueForGroups {
Flush ' empty current stack
Data obj(3, "Clear drains"), obj(4 ,"Feed cat"), obj( 5 , "Make tea")
Data obj( 1 ,"Solve RC tasks"), obj( 2 , "Tax return")
ObjectCount()
b=stack
while not empty
InsertPQ(b) // top of stack is b then objects follow
end while
ObjectCount()
Print "Using Peek to Examine Priority Queue"
n1=each(b)
Header()
while n1
Print @Peek$(n1)
end while
ObjectCount()
Header()
while not @isEmpty(b)
Print @Pop(b)=>tostring$
end while
ObjectCount()
// here are the subs/simple functions
// these are static parts of module
sub Header()
Print " Priority Task"
Print "========== ================"
end sub
sub ObjectCount()
Print "There are ";countmany;" objects of type obj"
end sub
sub InsertPQ(a, n)
Print "Insert:";n.tostring$(1)
if len(a)=0 then stack a {data n} : exit sub
if @comp(n, stackitem(a)) then stack a {push n} : exit sub
stack a {
push n
local t=2, b=len(a)
local m=b
while t<=b
t1=m
m=(b+t) div 2
if m=0 then m=t1 : exit
If @comp(stackitem(m),n) then t=m+1: continue
b=m-1
m=b
end while
if m>1 then shiftback m
}
end sub
function comp(a, b)
=a.x<b.x
end function
function Peek$(a as stack)
=stackitem(a)=>toString$
countmany++
end function
function IsEmpty(a)
=len(a)=0
end function
Function Pop(a)
// Group make a copy
stack a {=Group:countmany++}
end function
}
PriorityQueueForGroups
</syntaxhighlight>
 
===Using a stack with pointers to Groups as elements (with Merge Function)===
Now we use pointer to group, and use of Subs and simple Functions (called using @ prefix). Also we have a global countmany (is a long type, see 0&) to check how many objects exist. We have use "as *obj" to declare a parameter to stay as pointer and to check the type (here is obj). The remove method of object called when object has to be removed. The constructor module obj called once and not exist in the final object obj (it is a part under Class: label, and this part define things for construction time only). Property toString$ is a group which return value (a string value), and we can use it with or without parameter. Because it is a group, we have to link parent properties/functions (but not modules) to get access.
 
Added Merge function. We can choose if we leave the second queue untouched or erase each item as we merge it to the first queue, using the third parameter.
 
<syntaxhighlight lang="m2000 interpreter">
global countmany=0&
class obj {
x, s$
property toString$ {
value (sp=8) {
link parent x, s$ to x, s$
value$=format$("{0::-5}"+string$(" ", sp)+"{1:20}", x, s$)
}
}
function Copy {
countmany++
z=this
=pointer((z))
}
remove {
countmany--
}
class:
module obj (.x, .s$) {countmany++}
}
// obj() return object as value (using a special pointer)
function global g(priority, task$) {
// here we return an object using nonrmal pointer
// try to change -> to = to see the error
->obj(priority, task$)
}
Module PriorityQueueForGroups {
Flush ' empty current stack
Data g(3, "Clear drains"),g(4 ,"Feed cat"), g( 5 , "Make tea")
Data g( 1 ,"Solve RC tasks")
ObjectCount()
pq=stack
zz=stack
while not empty
InsertPQ(pq) // top of stack is pq then objects follow
end while
Pen 15 {
data g(2 , "Tax return"), g(1 ,"Solve RC tasks#2")
while not empty: InsertPq(zz): End While
n1=each(zz,-1,1)
Header()
while n1
Print @Peek$(stackitem(n1))
end while
}
MergePq(pq, zz, false)
InsertPq(pq, g(1 ,"Solve RC tasks#3"))
ObjectCount()
Print "Using Peek to Examine Priority Queue"
n1=each(pq,-1, 1)
Header()
while n1
Print @Peek$(stackitem(n1))
end while
ObjectCount()
Header()
while not @isEmpty(pq)
Print @Pop(pq)=>tostring$
end while
ObjectCount()
Header()
while not @isEmpty(zz)
Print @Pop(zz)=>tostring$
end while
ObjectCount()
// here are the subs/simple functions
// these are static parts of module
sub Header()
Print " Priority Task"
Print "========== ================"
end sub
sub ObjectCount()
Print "There are ";countmany;" objects of type obj"
end sub
sub MergePq(a, pq, emptyqueue)
local n1=each(pq, -1, 1), z=pointer()
while n1
if emptyqueue then
stack pq {
shiftback len(pq)
InsertPQ(a, Group)
}
else
z=stackitem(n1)
InsertPQ(a, z=>copy())
end if
end while
end sub
sub InsertPQ(a, n as *obj)
Print "Insert:";n=>tostring$(1)
if len(a)=0 then stack a {data n} : exit sub
if @comp(n, stackitem(a)) then stack a {push n} : exit sub
stack a {
push n
local t=2, pq=len(a), t1=0
local m=pq
while t<=pq
t1=m
m=(pq+t) div 2
if m=0 then m=t1 : exit
If @comp(stackitem(m),n) then t=m+1: continue
pq=m-1
m=pq
end while
if m>1 then shiftback m
}
end sub
function comp(a as *obj, pq as *obj)
=a=>x>pq=>x
end function
function Peek$(a as *obj)
=a=>toString$
end function
function IsEmpty(a)
=len(a)=0
end function
function Pop(a)
// Group make a copy (but here is a pointer of group)
stack a {shift stack.size
=Group}
end function
}
PriorityQueueForGroups
</syntaxhighlight>
 
===Using ordered list (plus merge function)===
<syntaxhighlight lang="m2000 interpreter">
form 80, 42
Module OrdrerQueue (filename$) {
// f=-2 or use empty filename for screen
open filename$ for output as #f
zz=list
pq=List
flush
// subs can read from module's stack
println("Add items to pq queue")
Data 4 ,"Feed cat",5 , "Make tea", 3, "Clear drains",1 , "Solve RC tasks"
AddItems(pq)
println("Add items to zz queue")
AddItems(zz, 2 , "Tax return", 1 ,"Solve RC tasks#2")
println("Peek top from zz queue")
PeekTop(zz) // Solve RC tasks#2
println("Merge two priority lists")
merge(pq, zz, false)
println("Peek top from pq queue")
PeekTop(pq) // Solve RC tasks
println("Add items to pq queue")
AddItems(pq, 1 ,"Solve RC tasks#3")
println("Peek top from pq queue")
PeekTop(pq) // Solve RC tasks
println("Pop one from pq until empty queue")
while len(pq)>0
PopOne(pq)
end while
println("Pop one from zz until empty queue")
while len(zz)>0
PopOne(zz)
end while
close #f
sub AddItems(pq)
local s, z
while not empty
read z
if not exist(pq, z) then s=stack:append pq, z:=s else s=eval(pq)
read what$: stack s {data what$}
stack new {println( "add item",z,what$)}
end while
sort descending pq as number
Println()
end sub
sub merge(pq, qp, emptyqueue)
local needsort=false
local kqp=each(qp, -1, 1), k$, t, p
while kqp
t=eval(kqp)
k$= eval$(kqp!)
if not exist(pq, eval$(kqp!)) then
p=stack
append pq, val(eval$(kqp!)):=p
needsort=true
else
p=eval(pq)
end if
stack p {
if emptyqueue then
data !t
delete qp,eval$(kqp!)
else
data !stack(t)
end if
}
end while
if needsort then sort descending pq as number
end sub
sub PeekTop(pq)
Local k=len(pq)
if k=0 then exit sub
k=val(eval$(pq, k-1))
if exist(pq, k) then local s=eval(pq): println( k,stackitem$(s, 1))
End sub
Sub PopOne(pq)
Local k=len(pq)
if k<0 then exit sub
k=val(eval$(pq, k-1))
if exist(pq, k) then
local s=eval(pq)
println( k,stackitem$(s, 1))
if len(s)=1 then
delete pq, k
else
stack s {drop}
end if
end if
end sub
Sub println()
if empty then print #f, "": exit sub
while not empty
if islet then print #f, letter$;
if empty else print #f, " ";
if isnum then print #f, number;
if empty else print #f, " ";
end while
if f=-2 and pos=0 then exit sub
print #f, ""
end sub
}
OrdrerQueue ""
</syntaxhighlight>
 
{{out}}
<pre>Add items to pq queue
add item 4 Feed cat
add item 5 Make tea
add item 3 Clear drains
add item 1 Solve RC tasks
 
Add items to zz queue
add item 2 Tax return
add item 1 Solve RC tasks#2
 
Peek top from zz queue
1 Solve RC tasks#2
Merge two priority lists
Peek top from pq queue
1 Solve RC tasks
Add items to pq queue
add item 1 Solve RC tasks#3
 
Peek top from pq queue
1 Solve RC tasks
Pop one from pq until empty queue
1 Solve RC tasks
1 Solve RC tasks#2
1 Solve RC tasks#3
2 Tax return
3 Clear drains
4 Feed cat
5 Make tea
Pop one from zz until empty queue
1 Solve RC tasks#2
2 Tax return
</pre>
 
=={{header|Mathematica}}/{{header|Wolfram Language}}==
<syntaxhighlight lang="mathematica">push = Function[{queue, priority, item},
queue = SortBy[Append[queue, {priority, item}], First], HoldFirst];
pop = Function[queue,
If[Length@queue == 0, Null,
With[{item = queue[[-1, 2]]}, queue = Most@queue; item]],
HoldFirst];
peek = Function[queue,
If[Length@queue == 0, Null, Max[queue[[All, 1]]]], HoldFirst];
merge = Function[{queue1, queue2},
SortBy[Join[queue1, queue2], First], HoldAll];</syntaxhighlight>
 
Example:
 
<syntaxhighlight lang="mathematica">queue = {};
push[queue, 3, "Clear drains"];
push[queue, 4, "Feed cat"];
push[queue, 5, "Make tea"];
push[queue, 1, "Solve RC tasks"];
push[queue, 2, "Tax return"];
Print[peek[queue]];
Print[pop[queue]];
queue1 = {};
push[queue1, 6, "Drink tea"];
Print[merge[queue, queue1]];</syntaxhighlight>
 
Output:
 
<pre>5
 
Make tea
 
{{1,Solve RC tasks},{2,Tax return},{3,Clear drains},{4,Feed cat},{6,Drink tea}}</pre>
 
=={{header|Maxima}}==
<syntaxhighlight lang="maxima">/* Naive implementation using a sorted list of pairs [key, [item[1], ..., item[n]]].
The key may be any number (integer or not). Items are extracted in FIFO order. */
 
defstruct(pqueue(q = []))$
 
/* Binary search */
 
find_key(q, p) := block(
[i: 1, j: length(q), k, c],
if j = 0 then false
elseif (c: q[i][1]) >= p then
(if c = p then i else false)
elseif (c: q[j][1]) <= p then
(if c = p then j else false)
else catch(
while j >= i do (
k: quotient(i + j, 2),
if (c: q[k][1]) = p then throw(k)
elseif c < p then i: k + 1 else j: k - 1
),
false
)
)$
 
pqueue_push(pq, x, p) := block(
[q: pq@q, k],
k: find_key(q, p),
if integerp(k) then q[k][2]: endcons(x, q[k][2])
else pq@q: sort(cons([p, [x]], q)),
'done
)$
pqueue_pop(pq) := block(
[q: pq@q, v, x],
if emptyp(q) then 'fail else (
p: q[1][1],
v: q[1][2],
x: v[1],
if length(v) > 1 then q[1][2]: rest(v) else pq@q: rest(q),
x
)
)$
 
pqueue_print(pq) := block([t], while (t: pqueue_pop(pq)) # 'fail do disp(t))$
 
 
/* An example */
 
a: new(pqueue)$
 
pqueue_push(a, "take milk", 4)$
pqueue_push(a, "take eggs", 4)$
pqueue_push(a, "take wheat flour", 4)$
pqueue_push(a, "take salt", 4)$
pqueue_push(a, "take oil", 4)$
pqueue_push(a, "carry out crepe recipe", 5)$
pqueue_push(a, "savour !", 6)$
pqueue_push(a, "add strawberry jam", 5 + 1/2)$
pqueue_push(a, "call friends", 5 + 2/3)$
pqueue_push(a, "go to the supermarket and buy food", 3)$
pqueue_push(a, "take a shower", 2)$
pqueue_push(a, "get dressed", 2)$
pqueue_push(a, "wake up", 1)$
pqueue_push(a, "serve cider", 5 + 3/4)$
pqueue_push(a, "buy also cider", 3)$
 
pqueue_print(a);
"wake up"
"take a shower"
"get dressed"
"go to the supermarket and buy food"
"buy also cider"
"take milk"
"take butter"
"take flour"
"take salt"
"take oil"
"carry out recipe"
"add strawberry jam"
"call friends"
"serve cider"
"savour !"</syntaxhighlight>
 
=={{header|Mercury}}==
Mercury comes with an efficient, albeit simple, priority queue in its standard library. The build_pqueue/2 predicate in the code below inserts the test data in arbitrary order. display_pqueue/3, in turn, removes one K/V pair at a time, displaying the value. Compiling and running the supplied program results in all tasks being displayed in priority order as expected.
 
<syntaxhighlight lang="mercury">:- module test_pqueue.
 
:- interface.
 
:- import_module io.
 
:- pred main(io::di, io::uo) is det.
 
:- implementation.
 
:- import_module int.
:- import_module list.
:- import_module pqueue.
:- import_module string.
 
:- pred build_pqueue(pqueue(int,string)::in, pqueue(int,string)::out) is det.
build_pqueue(!PQ) :-
pqueue.insert(3, "Clear drains", !PQ),
pqueue.insert(4, "Feed cat", !PQ),
pqueue.insert(5, "Make tea", !PQ),
pqueue.insert(1, "Solve RC tasks", !PQ),
pqueue.insert(2, "Tax return", !PQ).
 
:- pred display_pqueue(pqueue(int, string)::in, io::di, io::uo) is det.
display_pqueue(PQ, !IO) :-
( pqueue.remove(K, V, PQ, PQO) ->
io.format("Key = %d, Value = %s\n", [i(K), s(V)], !IO),
display_pqueue(PQO, !IO)
;
true
).
 
main(!IO) :-
build_pqueue(pqueue.init, PQO),
display_pqueue(PQO, !IO).</syntaxhighlight>
 
=={{header|Nim}}==
{{trans|C}}
<syntaxhighlight lang="nim">type
PriElem[T] = tuple
data: T
pri: int
 
PriQueue[T] = object
buf: seq[PriElem[T]]
count: int
 
# first element not used to simplify indices
proc initPriQueue[T](initialSize = 4): PriQueue[T] =
result.buf.newSeq(initialSize)
result.buf.setLen(1)
result.count = 0
 
proc add[T](q: var PriQueue[T], data: T, pri: int) =
var n = q.buf.len
var m = n div 2
q.buf.setLen(n + 1)
 
# append at end, then up heap
while m > 0 and pri < q.buf[m].pri:
q.buf[n] = q.buf[m]
n = m
m = m div 2
 
q.buf[n] = (data, pri)
q.count = q.buf.len - 1
 
proc pop[T](q: var PriQueue[T]): PriElem[T] =
assert q.buf.len > 1
result = q.buf[1]
 
var qn = q.buf.len - 1
var n = 1
var m = 2
while m < qn:
if m + 1 < qn and q.buf[m].pri > q.buf[m+1].pri:
inc m
 
if q.buf[qn].pri <= q.buf[m].pri:
break
 
q.buf[n] = q.buf[m]
n = m
m = m * 2
 
q.buf[n] = q.buf[qn]
q.buf.setLen(q.buf.len - 1)
q.count = q.buf.len - 1
 
var p = initPriQueue[string]()
p.add("Clear drains", 3)
p.add("Feed cat", 4)
p.add("Make tea", 5)
p.add("Solve RC tasks", 1)
p.add("Tax return", 2)
 
while p.count > 0:
echo p.pop()</syntaxhighlight>
{{out}}
<pre>(data: Solve RC tasks, pri: 1)
(data: Tax return, pri: 2)
(data: Clear drains, pri: 3)
(data: Feed cat, pri: 4)
(data: Make tea, pri: 5)</pre>
 
''' Using Nim HeapQueue'''
<syntaxhighlight lang="nim">import HeapQueue
 
var pq = newHeapQueue[(int, string)]()
 
pq.push((3, "Clear drains"))
pq.push((4, "Feed cat"))
pq.push((5, "Make tea"))
pq.push((1, "Solve RC tasks"))
pq.push((2, "Tax return"))
 
while pq.len() > 0:
echo pq.pop()</syntaxhighlight>
 
{{out}}
<pre>(Field0: 1, Field1: "Solve RC tasks")
(Field0: 2, Field1: "Tax return")
(Field0: 3, Field1: "Clear drains")
(Field0: 4, Field1: "Feed cat")
(Field0: 5, Field1: "Make tea")</pre>
 
''' Using Nim tables'''
<syntaxhighlight lang="nim">import tables
 
var
pq = initTable[int, string]()
 
proc main() =
pq.add(3, "Clear drains")
pq.add(4, "Feed cat")
pq.add(5, "Make tea")
pq.add(1, "Solve RC tasks")
pq.add(2, "Tax return")
 
for i in countUp(1,5):
if pq.hasKey(i):
echo i, ": ", pq[i]
pq.del(i)
main()</syntaxhighlight>
{{out}}
<pre>1: Solve RC tasks
2: Tax return
3: Clear drains
4: Feed cat
5: Make tea</pre>
 
=={{header|Objective-C}}==
Line 372 ⟶ 5,662:
The priority queue used in this example is not actually written in Objective-C. It is part of Apple's (C-based) Core Foundation library, which is included with in Cocoa on Mac OS X and iOS. Its interface is a C function interface, which makes the code very ugly. Core Foundation is not included in GNUStep or other Objective-C APIs.
 
<langsyntaxhighlight lang="objc">#import <Foundation/Foundation.h>
 
const void *PQRetain(CFAllocatorRef allocator, const void *ptr) {
return [(__bridge_retained const void *)(__bridge id)ptr retain];
}
void PQRelease(CFAllocatorRef allocator, const void *ptr) {
[(void)(__bridge_transfer id)ptr release];
}
CFComparisonResult PQCompare(const void *ptr1, const void *ptr2, void *unused) {
return [(__bridge id)ptr1 compare:(__bridge id)ptr2];
}
 
Line 388 ⟶ 5,678:
NSString *name;
}
- (idinstancetype)initWithPriority:(int)p andName:(NSString *)n;
- (NSComparisonResult)compare:(Task *)other;
@end
 
@implementation Task
- (idinstancetype)initWithPriority:(int)p andName:(NSString *)n {
if ((self = [super init])) {
priority = p;
Line 399 ⟶ 5,689:
}
return self;
}
- (void)dealloc {
[name release];
[super dealloc];
}
- (NSString *)description {
Line 418 ⟶ 5,704:
 
int main (int argc, const char *argv[]) {
@autoreleasepool {
NSAutoreleasePool * pool = [[NSAutoreleasePool alloc] init];
 
CFBinaryHeapCallBacks callBacks = {0, PQRetain, PQRelease, NULL, PQCompare};
CFBinaryHeapRef pq = CFBinaryHeapCreate(NULL, 0, &callBacks, NULL);
 
CFBinaryHeapAddValue(pq, [[[Task alloc] initWithPriority:3 andName:@"Clear drains"] autorelease]);
CFBinaryHeapAddValue(pq, [[[Task alloc] initWithPriority:4 andName:@"Feed cat"] autorelease]);
CFBinaryHeapAddValue(pq, [[[Task alloc] initWithPriority:5 andName:@"Make tea"] autorelease]);
CFBinaryHeapAddValue(pq, [[[Task alloc] initWithPriority:1 andName:@"Solve RC tasks"] autorelease]);
CFBinaryHeapAddValue(pq, [[[Task alloc] initWithPriority:2 andName:@"Tax return"] autorelease]);
 
while (CFBinaryHeapGetCount(pq) != 0) {
Task *task = (id)CFBinaryHeapGetMinimum(pq);
NSLog(@"%@", task);
CFBinaryHeapRemoveMinimumValue(pq);
}
 
CFRelease(pq);
 
}
[pool drain];
return 0;
}</syntaxhighlight>
}
</lang>
 
log:
Line 453 ⟶ 5,738:
=={{header|OCaml}}==
 
TheHolger Arnold's [http://holgerarnold.net/software/ OCaml base library] provides a [http://holgerarnold.net/software/ocaml/doc/base/PriorityQueue.html PriorityQueue] module.
 
<langsyntaxhighlight lang="ocaml">module PQ = Base.PriorityQueue
 
let () =
Line 471 ⟶ 5,756:
PQ.remove_first pq;
print_endline task
done</langsyntaxhighlight>
 
testing:
Line 482 ⟶ 5,767:
 
Although OCaml's standard library does not have a dedicated priority queue structure, one can (for most purposes) use the built-in Set data structure as a priority queue, as long as no two elements compare equal (since Set does not allow duplicate elements). This is the case here since no two tasks should have the same name. Note that Set is a functional, persistent data structure, so we derive new priority queues from the old ones functionally, rather than modifying them imperatively; the complexity is still O(log n).
{{works with|OCaml|4.02+}}
 
<langsyntaxhighlight lang="ocaml">module PQSet = Set.Make
(struct
type t = int * string (* pair of priority and task name *)
Line 497 ⟶ 5,782:
2, "Tax return";
] in
let pq = List.fold_right PQSet.addof_list tasks PQSet.empty in
let rec aux pq' =
if not (PQSet.is_empty pq') then begin
Line 504 ⟶ 5,789:
aux (PQSet.remove task pq')
end
in aux pq</langsyntaxhighlight>
{{out}}
 
<pre>
testing:
<pre>$ ocaml pq.ml
1, Solve RC tasks
2, Tax return
Line 513 ⟶ 5,797:
4, Feed cat
5, Make tea
</pre>
=={{header|OxygenBasic}}==
<syntaxhighlight lang="text">
'PRIORITY QUEUE WITH 16 LEVELS
 
uses console
 
% pl 16 'priority levels
 
===================
Class PriorityQueue
===================
 
indexbase 1
bstring buf[pl] 'buffers to hold priority queues content
int bg[pl] 'buffers base offset
int i[pl] 'indexers
int le[pl] 'length of buffer
 
method constructor()
====================
int p
for p=1 to pl
buf[p]=""
le[p]=0
bg[p]=0
i=[p]=0
next
end method
 
method destructor()
===================
int p
for p=1 to pl
del (buf[p])
le[p]=0
bg[p]=0
i=[p]=0
next
end method
method Encodelength(int ls,p)
=============================
int ll at i[p]+strptr(buf[p])
ll=ls
i[p]+=sizeof int
end method
 
method limit(int*p)
===================
if p>pl
p=pl
endif
if p<1
p=1
endif
end method
method push(string s,int p)
=============================
limit p
int ls
ls=len s
if i[p]+ls+8 > le[p] then
int e=8000+(ls*2) 'extra buffer bytes
buf[p]=buf[p]+nuls e 'extend buf
le[p]=len buf[p]
end if
EncodeLength ls,p 'length of input s
mid buf[p],i[p]+1,s 'patch in s
i[p]+=ls
end method
 
method popLength(int p) as int
==============================
if bg[p]>=i[p]
return -1 'buffer empty
endif
int ll at (bg[p]+strptr buf[p])
bg[p]+=sizeof int
return ll
end method
method pop(string *s, int *p=1, lpl=0) as int
=============================================
limit p
int ls
do
ls=popLength p
if ls=-1
if not lpl 'lpl: lock priority level
p++ 'try next priority level
if p<=pl
continue do
endif
endif
s=""
return ls 'empty buffers
endif
exit do
loop
s=mid buf[p],bg[p]+1,ls
bg[p]+=ls
'cleanup buffer
if bg[p]>1e6 then
buf[p]=mid buf[p],bg[p]+1 'remove old popped data
le[p]=len buf[p]
i[p]-=bg[p] 'shrink buf
bg[p]=0
end if
end method
method clear()
==============
constructor
end method
 
end class 'PriorityQueue
 
 
'====
'DEMO
'====
new PriorityQueue medo()
string s
 
def inp
medo.push %2,%1
end def
 
' Priority Task
' ══════════ ════════════════
inp 3 "Clear drains"
inp 4 "Feed cat"
inp 5 "Make tea"
inp 1 "Solve RC tasks"
inp 2 "Tax return"
inp 4 "Plant beans"
'
int er
int p
print "Priority Task" cr
print "=================" cr
do
er=medo.pop s,p
if er=-1
print "(buffer empty)"
exit do
endif
print p tab s cr
loop
pause
del medo
 
/*
RESULTS:
Priority Task
=================
1 Solve RC tasks
2 Tax return
3 Clear drains
4 Feed cat
4 Plant beans
5 Make tea
(buffer empty)
*/
</syntaxhighlight>
 
=={{header|Pascal}}==
<syntaxhighlight lang="pascal">
program PriorityQueueTest;
 
uses Classes;
 
Type
TItem = record
Priority:Integer;
Value:string;
end;
PItem = ^TItem;
TPriorityQueue = class(Tlist)
procedure Push(Priority:Integer;Value:string);
procedure SortPriority();
function Pop():String;
function Empty:Boolean;
end;
 
{ TPriorityQueue }
 
procedure TPriorityQueue.Push(Priority:Integer;Value:string);
var
Item: PItem;
begin
new(Item);
Item^.Priority := Priority;
Item^.Value := Value;
inherited Add(Item);
SortPriority();
end;
 
procedure TPriorityQueue.SortPriority();
var
i,j:Integer;
begin
if(Count < 2) Then Exit();
for i:= 0 to Count-2 do
for j:= i+1 to Count-1 do
if ( PItem(Items[i])^.Priority > PItem(Items[j])^.Priority)then
Exchange(i,j);
end;
 
function TPriorityQueue.Pop():String;
begin
if count = 0 then
Exit('');
result := PItem(First)^.value;
Dispose(PItem(First));
Delete(0);
end;
 
function TPriorityQueue.Empty:Boolean;
begin
Result := Count = 0;
end;
 
var
Queue : TPriorityQueue;
begin
Queue:= TPriorityQueue.Create();
Queue.Push(3,'Clear drains');
Queue.Push(4,'Feed cat');
Queue.Push(5,'Make tea');
Queue.Push(1,'Solve RC tasks');
Queue.Push(2,'Tax return');
while not Queue.Empty() do
writeln(Queue.Pop());
Queue.free;
end.
</syntaxhighlight>
====Advanced version====
{{works with|FPC}}
A maximizing priority queue based on a binary heap with the ability to update keys using a special handle. User is responsible for keeping track of when the handle becomes invalid. Comparing elements requires a regular boolean function of the form:
<syntaxhighlight lang="pascal">
type
TComparer<T> = function(const L, R: T): Boolean;
</syntaxhighlight>
which should return True if the first argument is less than the second. It seems that all operations should be performed in O(LogN).
<syntaxhighlight lang="pascal">
unit PQueue;
{$mode objfpc}{$h+}{$b-}
interface
uses
SysUtils;
 
type
EPqError = class(Exception);
 
generic TPriorityQueue<T> = class
public
type
TComparer = function(const L, R: T): Boolean;
THandle = type SizeInt;
const
NULL_HANDLE = THandle(-1);
strict private
type
TNode = record
Data: T;
HeapIndex: SizeInt;
end;
const
INIT_SIZE = 16;
NULL_INDEX = SizeInt(-1);
SEUndefComparer = 'Undefined comparer';
SEInvalidHandleFmt = 'Invalid handle value(%d)';
SEAccessEmpty = 'Cannot access an empty queue item';
var
FNodes: array of TNode;
FHeap: array of SizeInt;
FCount,
FStackTop: SizeInt;
FCompare: TComparer;
procedure CheckEmpty;
procedure Expand;
function NodeAdd(const aValue: T; aIndex: SizeInt): SizeInt;
function NodeRemove(aIndex: SizeInt): T;
function StackPop: SizeInt;
procedure StackPush(aIdx: SizeInt);
procedure PushUp(Idx: SizeInt);
procedure SiftDown(Idx: SizeInt);
function DoPop: T;
public
constructor Create(c: TComparer);
function IsEmpty: Boolean;
procedure Clear;
function Push(const v: T): THandle;
function Pop: T;
function TryPop(out v: T): Boolean;
function Peek: T;
function TryPeek(out v: T): Boolean;
function GetValue(h: THandle): T;
procedure Update(h: THandle; const v: T);
property Count: SizeInt read FCount;
end;
 
implementation
 
procedure TPriorityQueue.CheckEmpty;
begin
if Count = 0 then raise EPqError.Create(SEAccessEmpty);
end;
 
procedure TPriorityQueue.Expand;
begin
if Length(FHeap) < INIT_SIZE then begin
SetLength(FHeap, INIT_SIZE);
SetLength(FNodes, INIT_SIZE)
end
else begin
SetLength(FHeap, Length(FHeap) * 2);
SetLength(FNodes, Length(FNodes) * 2);
end;
end;
 
function TPriorityQueue.NodeAdd(const aValue: T; aIndex: SizeInt): SizeInt;
begin
if FStackTop <> NULL_INDEX then
Result := StackPop
else
Result := FCount;
FNodes[Result].Data := aValue;
FNodes[Result].HeapIndex := aIndex;
Inc(FCount);
end;
 
function TPriorityQueue.NodeRemove(aIndex: SizeInt): T;
begin
StackPush(aIndex);
Result := FNodes[aIndex].Data;
end;
 
function TPriorityQueue.StackPop: SizeInt;
begin
Result := FStackTop;
if Result <> NULL_INDEX then begin
FStackTop := FNodes[Result].HeapIndex;
FNodes[Result].HeapIndex := NULL_INDEX;
end;
end;
 
procedure TPriorityQueue.StackPush(aIdx: SizeInt);
begin
FNodes[aIdx].HeapIndex := FStackTop;
FStackTop := aIdx;
end;
 
procedure TPriorityQueue.PushUp(Idx: SizeInt);
var
Prev, Curr: SizeInt;
begin
Prev := (Idx - 1) shr 1;
Curr := FHeap[Idx];
while(Idx > 0) and FCompare(FNodes[FHeap[Prev]].Data, FNodes[Curr].Data) do begin
FHeap[Idx] := FHeap[Prev];
FNodes[FHeap[Prev]].HeapIndex := Idx;
Idx := Prev;
Prev := (Prev - 1) shr 1;
end;
FHeap[Idx] := Curr;
FNodes[Curr].HeapIndex := Idx;
end;
 
procedure TPriorityQueue.SiftDown(Idx: SizeInt);
var
Next, Sifted: SizeInt;
begin
if Count < 2 then exit;
Next := Idx*2 + 1;
Sifted := FHeap[Idx];
while Next < Count do begin
if(Next+1 < Count)and FCompare(FNodes[FHeap[Next]].Data, FNodes[FHeap[Next+1]].Data)then Inc(Next);
if not FCompare(FNodes[Sifted].Data, FNodes[FHeap[Next]].Data) then break;
FHeap[Idx] := FHeap[Next];
FNodes[FHeap[Next]].HeapIndex := Idx;
Idx := Next;
Next := Next*2 + 1;
end;
FHeap[Idx] := Sifted;
FNodes[Sifted].HeapIndex := Idx;
end;
 
function TPriorityQueue.DoPop: T;
begin
Result := NodeRemove(FHeap[0]);
Dec(FCount);
if Count > 0 then begin
FHeap[0] := FHeap[Count];
SiftDown(0);
end;
end;
 
constructor TPriorityQueue.Create(c: TComparer);
begin
if c = nil then raise EPqError.Create(SEUndefComparer);
FCompare := c;
FStackTop := NULL_INDEX;
end;
 
function TPriorityQueue.IsEmpty: Boolean;
begin
Result := Count = 0;
end;
 
procedure TPriorityQueue.Clear;
begin
FNodes := nil;
FHeap := nil;
FCount := 0;
FStackTop := NULL_INDEX;
end;
 
function TPriorityQueue.Push(const v: T): THandle;
var
InsertPos: SizeInt;
begin
if Count = Length(FHeap) then Expand;
InsertPos := Count;
Result := NodeAdd(v, InsertPos);
FHeap[InsertPos] := Result;
if InsertPos > 0 then PushUp(InsertPos);
end;
 
function TPriorityQueue.Pop: T;
begin
CheckEmpty;
Result := DoPop;
end;
 
function TPriorityQueue.TryPop(out v: T): Boolean;
begin
if Count = 0 then exit(False);
v := DoPop;
Result := True;
end;
 
function TPriorityQueue.Peek: T;
begin
CheckEmpty;
Result := FNodes[FHeap[0]].Data;
end;
 
function TPriorityQueue.TryPeek(out v: T): Boolean;
begin
if Count = 0 then exit(False);
v := FNodes[FHeap[0]].Data;
Result := True;
end;
 
function TPriorityQueue.GetValue(h: THandle): T;
begin
if SizeUInt(h) < SizeUInt(Length(FHeap)) then
Result := FNodes[h].Data
else
raise EPqError.CreateFmt(SEInvalidHandleFmt, [h]);
end;
 
procedure TPriorityQueue.Update(h: THandle; const v: T);
begin
if SizeUInt(h) < SizeUInt(Length(FHeap)) then begin
if FCompare(FNodes[h].Data, v) then begin
FNodes[h].Data := v;
PushUp(FNodes[h].HeapIndex);
end else
if FCompare(v, FNodes[h].Data) then begin
FNodes[h].Data := v;
SiftDown(FNodes[h].HeapIndex);
end;
end else
raise EPqError.CreateFmt(SEInvalidHandleFmt, [h]);
end;
 
end.
</syntaxhighlight>
Usage:
<syntaxhighlight lang="pascal">
program PqDemo;
{$mode delphi}
uses
SysUtils, PQueue;
 
type
TTask = record
Name: string; Prio: Integer;
end;
 
const
Tasks: array of TTask = [
(Name: 'Clear drains'; Prio: 3), (Name: 'Feed cat'; Prio: 4),
(Name: 'Make tea'; Prio: 5), (Name: 'Solve RC tasks'; Prio: 1),
(Name: 'Tax return'; Prio: 2)];
 
function TaskCmp(const L, R: TTask): Boolean;
begin
Result := L.Prio < R.Prio;
end;
 
var
q: TPriorityQueue<TTask>;
h: q.THandle = q.NULL_HANDLE;
t: TTask;
MaxPrio: Integer = Low(Integer);
begin
Randomize;
q := TPriorityQueue<TTask>.Create(@TaskCmp);
for t in Tasks do begin
if t.Prio > MaxPrio then MaxPrio := t.Prio;
if Pos('cat', t.Name) > 0 then
h := q.Push(t)
else
q.Push(t);
end;
if (h <> q.NULL_HANDLE) and Boolean(Random(2)) then begin
WriteLn('Cat is angry!');
t := q.GetValue(h);
t.Prio := Succ(MaxPrio);
q.Update(h, t);
end;
WriteLn('Task list:');
while q.TryPop(t) do
WriteLn(' ', t.Prio, ' ', t.Name);
q.Free;
end.
</syntaxhighlight>
{{out}}
<pre>
Cat is angry!
Task list:
6 Feed cat
5 Make tea
3 Clear drains
2 Tax return
1 Solve RC tasks
</pre>
 
=={{header|Perl}}==
===Using a Module===
There are a few implementations on CPAN. Following uses <code>Heap::Priority</code>[http://search.cpan.org/~fwojcik/Heap-Priority-0.11/Priority.pm]
<langsyntaxhighlight lang="perl">use 5.10.0strict;
use strictwarnings;
use feature 'say';
use Heap::Priority;
 
my $h = new Heap::Priority->new;
 
$h->highest_first(); # higher or lower number is more important
$h->add(@$_) for ["Clear drains", 3],
["Feed cat", 4],
["Make tea", 5],
["Solve RC tasks", 1],
["Tax return", 2];
 
say while ($_ = $h->pop);</langsyntaxhighlight>output<lang>Make tea
{{out}}
<pre>
Make tea
Feed cat
Clear drains
Tax return
Solve RC tasks</lang>
</pre>
 
===IBM card sorter version===
=={{header|Perl 6}}==
<syntaxhighlight lang="perl">use strict;
This is a rather simple implementation. It requires the priority to be a positive integer value, with lower values being higher priority. There isn't a hard limit on how many priority levels you can have, though more than a few dozen is probably not practical.
use warnings; # in homage to IBM card sorters :)
 
my $data = <<END;
The tasks are stored internally as an array of FIFO buffers, so multiple tasks of the same priority level will be returned in the order they were stored.
Priority Task
3 Clear drains
4 Feed cat
5 Make tea
1 Solve RC tasks
2 Tax return
4 Feed dog
END
 
insert( $1, $2 ) while $data =~ /(\d+)\h+(.*)/g; # insert all data
<lang perl6>class PriorityQueue {
has @!tasks is rw;
 
while( my $item = method insert top_item_removal() Int) $priority# whereget {in $priority >= 0 }, $task ) {order
{
@!tasks[$priority] //= [];
print "$item\n";
@!tasks[$priority].push: $task;
}
 
######################################################################
method get { @!tasks.first({$^_}).shift }
 
my @bins; # priorities limited to small (<1e6 maybe?) non-negative integers
method is_empty { !?@!tasks.first({$^_}) }
}
 
sub insert { push @{ $bins[shift] }, pop } # O(1)
my $pq = PriorityQueue.new;
 
sub top_item_removal # O(1) (sort of, maybe?)
for (
{
3, 'Clear drains',
delete $bins[-1] while @bins and @{ $bins[-1] // [] } == 0;
4, 'Feed cat',
shift @{ $bins[-1] // [] };
5, 'Make tea',
}</syntaxhighlight>
9, 'Sleep',
{{out}}
3, 'Check email',
<pre>
1, 'Solve RC tasks',
Make tea
9, 'Exercise',
Feed cat
2, 'Do taxes'
Feed dog
) -> $priority, $task {
Clear drains
$pq.insert( $priority, $task );
Tax return
Solve RC tasks
</pre>
 
=={{header|Phix}}==
Dictionary based solution. Allows duplicate tasks, FIFO within priority, and uses a callback-style method of performing tasks.<br>
Assumes 5 is the highest priority and should be done first, for 1 first just delete the ",true" on traverse_dict calls.
<!--<syntaxhighlight lang="phix">(phixonline)-->
<span style="color: #008080;">with</span> <span style="color: #008080;">javascript_semantics</span>
<span style="color: #008080;">constant</span> <span style="color: #000000;">tasklist</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">new_dict</span><span style="color: #0000FF;">()</span>
<span style="color: #008080;">procedure</span> <span style="color: #000000;">add_task</span><span style="color: #0000FF;">(</span><span style="color: #004080;">integer</span> <span style="color: #000000;">priority</span><span style="color: #0000FF;">,</span> <span style="color: #004080;">string</span> <span style="color: #000000;">desc</span><span style="color: #0000FF;">)</span>
<span style="color: #004080;">integer</span> <span style="color: #000000;">k</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">getd_index</span><span style="color: #0000FF;">(</span><span style="color: #000000;">priority</span><span style="color: #0000FF;">,</span><span style="color: #000000;">tasklist</span><span style="color: #0000FF;">)</span>
<span style="color: #008080;">if</span> <span style="color: #000000;">k</span><span style="color: #0000FF;">=</span><span style="color: #000000;">0</span> <span style="color: #008080;">then</span>
<span style="color: #7060A8;">putd</span><span style="color: #0000FF;">(</span><span style="color: #000000;">priority</span><span style="color: #0000FF;">,{</span><span style="color: #000000;">desc</span><span style="color: #0000FF;">},</span><span style="color: #000000;">tasklist</span><span style="color: #0000FF;">)</span>
<span style="color: #008080;">else</span>
<span style="color: #004080;">sequence</span> <span style="color: #000000;">descs</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">getd_by_index</span><span style="color: #0000FF;">(</span><span style="color: #000000;">k</span><span style="color: #0000FF;">,</span><span style="color: #000000;">tasklist</span><span style="color: #0000FF;">)</span>
<span style="color: #7060A8;">putd</span><span style="color: #0000FF;">(</span><span style="color: #000000;">priority</span><span style="color: #0000FF;">,</span><span style="color: #7060A8;">append</span><span style="color: #0000FF;">(</span><span style="color: #000000;">descs</span><span style="color: #0000FF;">,</span><span style="color: #000000;">desc</span><span style="color: #0000FF;">),</span><span style="color: #000000;">tasklist</span><span style="color: #0000FF;">)</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">if</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">procedure</span>
<span style="color: #008080;">function</span> <span style="color: #000000;">list_task_visitor</span><span style="color: #0000FF;">(</span><span style="color: #004080;">integer</span> <span style="color: #000000;">priority</span><span style="color: #0000FF;">,</span> <span style="color: #004080;">sequence</span> <span style="color: #000000;">descs</span><span style="color: #0000FF;">,</span> <span style="color: #004080;">integer</span> <span style="color: #000080;font-style:italic;">/*user_data*/</span><span style="color: #0000FF;">)</span>
<span style="color: #0000FF;">?{</span><span style="color: #000000;">priority</span><span style="color: #0000FF;">,</span><span style="color: #000000;">descs</span><span style="color: #0000FF;">}</span>
<span style="color: #008080;">return</span> <span style="color: #004600;">true</span> <span style="color: #000080;font-style:italic;">-- continue</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">function</span>
<span style="color: #008080;">procedure</span> <span style="color: #000000;">list_tasks</span><span style="color: #0000FF;">()</span>
<span style="color: #7060A8;">traverse_dict</span><span style="color: #0000FF;">(</span><span style="color: #000000;">list_task_visitor</span><span style="color: #0000FF;">,</span> <span style="color: #000000;">0</span><span style="color: #0000FF;">,</span> <span style="color: #000000;">tasklist</span><span style="color: #0000FF;">,</span> <span style="color: #004600;">true</span><span style="color: #0000FF;">)</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">procedure</span>
<span style="color: #008080;">function</span> <span style="color: #000000;">pop_task_visitor</span><span style="color: #0000FF;">(</span><span style="color: #004080;">integer</span> <span style="color: #000000;">priority</span><span style="color: #0000FF;">,</span> <span style="color: #004080;">sequence</span> <span style="color: #000000;">descs</span><span style="color: #0000FF;">,</span> <span style="color: #004080;">integer</span> <span style="color: #000000;">rid</span><span style="color: #0000FF;">)</span>
<span style="color: #004080;">string</span> <span style="color: #000000;">desc</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">descs</span><span style="color: #0000FF;">[</span><span style="color: #000000;">1</span><span style="color: #0000FF;">]</span>
<span style="color: #000000;">descs</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">descs</span><span style="color: #0000FF;">[</span><span style="color: #000000;">2</span><span style="color: #0000FF;">..$]</span>
<span style="color: #008080;">if</span> <span style="color: #7060A8;">length</span><span style="color: #0000FF;">(</span><span style="color: #000000;">descs</span><span style="color: #0000FF;">)=</span><span style="color: #000000;">0</span> <span style="color: #008080;">then</span>
<span style="color: #7060A8;">deld</span><span style="color: #0000FF;">(</span><span style="color: #000000;">priority</span><span style="color: #0000FF;">,</span><span style="color: #000000;">tasklist</span><span style="color: #0000FF;">)</span>
<span style="color: #008080;">else</span>
<span style="color: #7060A8;">putd</span><span style="color: #0000FF;">(</span><span style="color: #000000;">priority</span><span style="color: #0000FF;">,</span><span style="color: #000000;">descs</span><span style="color: #0000FF;">,</span><span style="color: #000000;">tasklist</span><span style="color: #0000FF;">)</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">if</span>
<span style="color: #000000;">rid</span><span style="color: #0000FF;">(</span><span style="color: #000000;">priority</span><span style="color: #0000FF;">,</span><span style="color: #000000;">desc</span><span style="color: #0000FF;">)</span>
<span style="color: #008080;">return</span> <span style="color: #004600;">false</span> <span style="color: #000080;font-style:italic;">-- stop</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">function</span>
<span style="color: #008080;">procedure</span> <span style="color: #000000;">pop_task</span><span style="color: #0000FF;">(</span><span style="color: #004080;">integer</span> <span style="color: #000000;">rid</span><span style="color: #0000FF;">)</span>
<span style="color: #008080;">if</span> <span style="color: #7060A8;">dict_size</span><span style="color: #0000FF;">(</span><span style="color: #000000;">tasklist</span><span style="color: #0000FF;">)!=</span><span style="color: #000000;">0</span> <span style="color: #008080;">then</span>
<span style="color: #7060A8;">traverse_dict</span><span style="color: #0000FF;">(</span><span style="color: #000000;">pop_task_visitor</span><span style="color: #0000FF;">,</span> <span style="color: #000000;">rid</span><span style="color: #0000FF;">,</span> <span style="color: #000000;">tasklist</span><span style="color: #0000FF;">,</span> <span style="color: #004600;">true</span><span style="color: #0000FF;">)</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">if</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">procedure</span>
<span style="color: #000000;">add_task</span><span style="color: #0000FF;">(</span><span style="color: #000000;">3</span><span style="color: #0000FF;">,</span><span style="color: #008000;">"Clear drains"</span><span style="color: #0000FF;">)</span>
<span style="color: #000000;">add_task</span><span style="color: #0000FF;">(</span><span style="color: #000000;">4</span><span style="color: #0000FF;">,</span><span style="color: #008000;">"Feed cat"</span><span style="color: #0000FF;">)</span>
<span style="color: #000000;">add_task</span><span style="color: #0000FF;">(</span><span style="color: #000000;">5</span><span style="color: #0000FF;">,</span><span style="color: #008000;">"Make tea"</span><span style="color: #0000FF;">)</span>
<span style="color: #000000;">add_task</span><span style="color: #0000FF;">(</span><span style="color: #000000;">1</span><span style="color: #0000FF;">,</span><span style="color: #008000;">"Solve RC tasks"</span><span style="color: #0000FF;">)</span>
<span style="color: #000000;">add_task</span><span style="color: #0000FF;">(</span><span style="color: #000000;">2</span><span style="color: #0000FF;">,</span><span style="color: #008000;">"Tax return"</span><span style="color: #0000FF;">)</span>
<span style="color: #008080;">procedure</span> <span style="color: #000000;">do_task</span><span style="color: #0000FF;">(</span><span style="color: #004080;">integer</span> <span style="color: #000000;">priority</span><span style="color: #0000FF;">,</span> <span style="color: #004080;">string</span> <span style="color: #000000;">desc</span><span style="color: #0000FF;">)</span>
<span style="color: #0000FF;">?{</span><span style="color: #000000;">priority</span><span style="color: #0000FF;">,</span><span style="color: #000000;">desc</span><span style="color: #0000FF;">}</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">procedure</span>
<span style="color: #000000;">list_tasks</span><span style="color: #0000FF;">()</span>
<span style="color: #0000FF;">?</span><span style="color: #008000;">"==="</span>
<span style="color: #000000;">pop_task</span><span style="color: #0000FF;">(</span><span style="color: #000000;">do_task</span><span style="color: #0000FF;">)</span>
<span style="color: #0000FF;">?</span><span style="color: #008000;">"==="</span>
<span style="color: #000000;">list_tasks</span><span style="color: #0000FF;">()</span>
<!--</syntaxhighlight>-->
{{out}}
<pre>
{5,{"Make tea"}}
{4,{"Feed cat"}}
{3,{"Clear drains"}}
{2,{"Tax return"}}
{1,{"Solve RC tasks"}}
"==="
{5,"Make tea"}
"==="
{4,{"Feed cat"}}
{3,{"Clear drains"}}
{2,{"Tax return"}}
{1,{"Solve RC tasks"}}
</pre>
=== trans nim ===
{{trans|Nim}}
(I needed this for [[Taxicab_numbers#Phix|Taxicab_numbers]])<br>
The bulk of this code now forms builtins/pqueue.e (not properly documented at the time, but now is, see below)
<!--<syntaxhighlight lang="phix">(phixonline)-->
<span style="color: #008080;">with</span> <span style="color: #008080;">javascript_semantics</span>
<span style="color: #004080;">sequence</span> <span style="color: #000000;">pq</span> <span style="color: #0000FF;">=</span> <span style="color: #0000FF;">{}</span>
<span style="color: #008080;">constant</span> <span style="color: #000000;">PRIORITY</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">2</span>
<span style="color: #008080;">procedure</span> <span style="color: #000000;">pqAdd</span><span style="color: #0000FF;">(</span><span style="color: #004080;">sequence</span> <span style="color: #000000;">item</span><span style="color: #0000FF;">)</span>
<span style="color: #000080;font-style:italic;">-- item is {object data, object priority}</span>
<span style="color: #004080;">integer</span> <span style="color: #000000;">n</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">length</span><span style="color: #0000FF;">(</span><span style="color: #000000;">pq</span><span style="color: #0000FF;">)+</span><span style="color: #000000;">1</span><span style="color: #0000FF;">,</span>
<span style="color: #000000;">m</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">floor</span><span style="color: #0000FF;">(</span><span style="color: #000000;">n</span><span style="color: #0000FF;">/</span><span style="color: #000000;">2</span><span style="color: #0000FF;">)</span>
<span style="color: #000000;">pq</span> <span style="color: #0000FF;">&=</span> <span style="color: #000000;">0</span>
<span style="color: #000080;font-style:italic;">-- append at end, then up heap</span>
<span style="color: #008080;">while</span> <span style="color: #000000;">m</span><span style="color: #0000FF;">></span><span style="color: #000000;">0</span> <span style="color: #008080;">and</span> <span style="color: #000000;">item</span><span style="color: #0000FF;">[</span><span style="color: #000000;">PRIORITY</span><span style="color: #0000FF;">]<</span><span style="color: #000000;">pq</span><span style="color: #0000FF;">[</span><span style="color: #000000;">m</span><span style="color: #0000FF;">][</span><span style="color: #000000;">PRIORITY</span><span style="color: #0000FF;">]</span> <span style="color: #008080;">do</span>
<span style="color: #000000;">pq</span><span style="color: #0000FF;">[</span><span style="color: #000000;">n</span><span style="color: #0000FF;">]</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">pq</span><span style="color: #0000FF;">[</span><span style="color: #000000;">m</span><span style="color: #0000FF;">]</span>
<span style="color: #000000;">n</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">m</span>
<span style="color: #000000;">m</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">floor</span><span style="color: #0000FF;">(</span><span style="color: #000000;">m</span><span style="color: #0000FF;">/</span><span style="color: #000000;">2</span><span style="color: #0000FF;">)</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">while</span>
<span style="color: #000000;">pq</span><span style="color: #0000FF;">[</span><span style="color: #000000;">n</span><span style="color: #0000FF;">]</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">item</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">procedure</span>
<span style="color: #008080;">function</span> <span style="color: #000000;">pqPop</span><span style="color: #0000FF;">()</span>
<span style="color: #004080;">sequence</span> <span style="color: #000000;">result</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">pq</span><span style="color: #0000FF;">[</span><span style="color: #000000;">1</span><span style="color: #0000FF;">]</span>
<span style="color: #004080;">integer</span> <span style="color: #000000;">qn</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">length</span><span style="color: #0000FF;">(</span><span style="color: #000000;">pq</span><span style="color: #0000FF;">),</span>
<span style="color: #000000;">n</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">1</span><span style="color: #0000FF;">,</span>
<span style="color: #000000;">m</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">2</span>
<span style="color: #008080;">while</span> <span style="color: #000000;">m</span><span style="color: #0000FF;"><</span><span style="color: #000000;">qn</span> <span style="color: #008080;">do</span>
<span style="color: #008080;">if</span> <span style="color: #000000;">m</span><span style="color: #0000FF;">+</span><span style="color: #000000;">1</span><span style="color: #0000FF;"><</span><span style="color: #000000;">qn</span> <span style="color: #008080;">and</span> <span style="color: #000000;">pq</span><span style="color: #0000FF;">[</span><span style="color: #000000;">m</span><span style="color: #0000FF;">][</span><span style="color: #000000;">PRIORITY</span><span style="color: #0000FF;">]></span><span style="color: #000000;">pq</span><span style="color: #0000FF;">[</span><span style="color: #000000;">m</span><span style="color: #0000FF;">+</span><span style="color: #000000;">1</span><span style="color: #0000FF;">][</span><span style="color: #000000;">PRIORITY</span><span style="color: #0000FF;">]</span> <span style="color: #008080;">then</span>
<span style="color: #000000;">m</span> <span style="color: #0000FF;">+=</span> <span style="color: #000000;">1</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">if</span>
<span style="color: #008080;">if</span> <span style="color: #000000;">pq</span><span style="color: #0000FF;">[</span><span style="color: #000000;">qn</span><span style="color: #0000FF;">][</span><span style="color: #000000;">PRIORITY</span><span style="color: #0000FF;">]<=</span><span style="color: #000000;">pq</span><span style="color: #0000FF;">[</span><span style="color: #000000;">m</span><span style="color: #0000FF;">][</span><span style="color: #000000;">PRIORITY</span><span style="color: #0000FF;">]</span> <span style="color: #008080;">then</span> <span style="color: #008080;">exit</span> <span style="color: #008080;">end</span> <span style="color: #008080;">if</span>
<span style="color: #000000;">pq</span><span style="color: #0000FF;">[</span><span style="color: #000000;">n</span><span style="color: #0000FF;">]</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">pq</span><span style="color: #0000FF;">[</span><span style="color: #000000;">m</span><span style="color: #0000FF;">]</span>
<span style="color: #000000;">n</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">m</span>
<span style="color: #000000;">m</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">m</span> <span style="color: #0000FF;">*</span> <span style="color: #000000;">2</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">while</span>
<span style="color: #000000;">pq</span><span style="color: #0000FF;">[</span><span style="color: #000000;">n</span><span style="color: #0000FF;">]</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">pq</span><span style="color: #0000FF;">[</span><span style="color: #000000;">qn</span><span style="color: #0000FF;">]</span>
<span style="color: #000000;">pq</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">pq</span><span style="color: #0000FF;">[</span><span style="color: #000000;">1</span><span style="color: #0000FF;">..$-</span><span style="color: #000000;">1</span><span style="color: #0000FF;">]</span>
<span style="color: #008080;">return</span> <span style="color: #000000;">result</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">function</span>
<span style="color: #7060A8;">set_rand</span><span style="color: #0000FF;">(</span><span style="color: #008080;">iff</span><span style="color: #0000FF;">(</span><span style="color: #7060A8;">platform</span><span style="color: #0000FF;">()=</span><span style="color: #004600;">JS</span><span style="color: #0000FF;">?</span><span style="color: #000000;">5749</span><span style="color: #0000FF;">:</span> <span style="color: #000080;font-style:italic;">-- (optional!)</span>
<span style="color: #008080;">iff</span><span style="color: #0000FF;">(</span><span style="color: #7060A8;">machine_bits</span><span style="color: #0000FF;">()=</span><span style="color: #000000;">32</span><span style="color: #0000FF;">?</span><span style="color: #000000;">4601</span><span style="color: #0000FF;">:</span><span style="color: #000000;">97</span><span style="color: #0000FF;">)))</span>
<span style="color: #008080;">constant</span> <span style="color: #000000;">set</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">shuffle</span><span style="color: #0000FF;">({{</span><span style="color: #008000;">"Clear drains"</span><span style="color: #0000FF;">,</span> <span style="color: #000000;">3</span><span style="color: #0000FF;">},</span>
<span style="color: #0000FF;">{</span><span style="color: #008000;">"Feed cat"</span><span style="color: #0000FF;">,</span> <span style="color: #000000;">4</span><span style="color: #0000FF;">},</span>
<span style="color: #0000FF;">{</span><span style="color: #008000;">"Make tea"</span><span style="color: #0000FF;">,</span> <span style="color: #000000;">5</span><span style="color: #0000FF;">},</span>
<span style="color: #0000FF;">{</span><span style="color: #008000;">"Solve RC tasks"</span><span style="color: #0000FF;">,</span> <span style="color: #000000;">1</span><span style="color: #0000FF;">},</span>
<span style="color: #0000FF;">{</span><span style="color: #008000;">"Tax return"</span><span style="color: #0000FF;">,</span> <span style="color: #000000;">2</span><span style="color: #0000FF;">}})</span>
<span style="color: #008080;">for</span> <span style="color: #000000;">i</span><span style="color: #0000FF;">=</span><span style="color: #000000;">1</span> <span style="color: #008080;">to</span> <span style="color: #7060A8;">length</span><span style="color: #0000FF;">(</span><span style="color: #000000;">set</span><span style="color: #0000FF;">)</span> <span style="color: #008080;">do</span>
<span style="color: #000000;">pqAdd</span><span style="color: #0000FF;">(</span><span style="color: #000000;">set</span><span style="color: #0000FF;">[</span><span style="color: #000000;">i</span><span style="color: #0000FF;">])</span>
<span style="color: #000000;">pqAdd</span><span style="color: #0000FF;">(</span><span style="color: #000000;">set</span><span style="color: #0000FF;">[</span><span style="color: #7060A8;">rand</span><span style="color: #0000FF;">(</span><span style="color: #7060A8;">length</span><span style="color: #0000FF;">(</span><span style="color: #000000;">set</span><span style="color: #0000FF;">))])</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">for</span>
<span style="color: #004080;">sequence</span> <span style="color: #000000;">res</span> <span style="color: #0000FF;">=</span> <span style="color: #0000FF;">{}</span>
<span style="color: #008080;">while</span> <span style="color: #7060A8;">length</span><span style="color: #0000FF;">(</span><span style="color: #000000;">pq</span><span style="color: #0000FF;">)</span> <span style="color: #008080;">do</span>
<span style="color: #0000FF;">?</span><span style="color: #000000;">pqPop</span><span style="color: #0000FF;">()</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">while</span>
<!--</syntaxhighlight>-->
{{out}}
The optional initial set_rand() makes it slightly more amusing.<br>
<small>As shown set_rand() achieves consistency per-platform, not cross-platform, the numbers above were found using a brute-force outer loop stopping on the desired result, since deleted.</small>
<pre>
{"Solve RC tasks",1}
{"Tax return",2}
{"Clear drains",3}
{"Feed cat",4}
{"Feed cat",4}
{"Feed cat",4}
{"Feed cat",4}
{"Feed cat",4}
{"Feed cat",4}
{"Make tea",5}
</pre>
 
=== builtin ===
If you omit MAX_HEAP or (same thing) specify MIN_HEAP, the output'll be 1..5
<!--<syntaxhighlight lang="phix">(phixonline)-->
<span style="color: #008080;">with</span> <span style="color: #008080;">javascript_semantics</span>
<span style="color: #008080;">constant</span> <span style="color: #000000;">tasklist</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">pq_new</span><span style="color: #0000FF;">(</span><span style="color: #004600;">MAX_HEAP</span><span style="color: #0000FF;">)</span>
<span style="color: #7060A8;">pq_add</span><span style="color: #0000FF;">({</span><span style="color: #008000;">"Clear drains"</span><span style="color: #0000FF;">,</span><span style="color: #000000;">3</span><span style="color: #0000FF;">},</span><span style="color: #000000;">tasklist</span><span style="color: #0000FF;">)</span>
<span style="color: #7060A8;">pq_add</span><span style="color: #0000FF;">({</span><span style="color: #008000;">"Feed cat"</span><span style="color: #0000FF;">,</span><span style="color: #000000;">4</span><span style="color: #0000FF;">},</span><span style="color: #000000;">tasklist</span><span style="color: #0000FF;">)</span>
<span style="color: #7060A8;">pq_add</span><span style="color: #0000FF;">({</span><span style="color: #008000;">"Make tea"</span><span style="color: #0000FF;">,</span><span style="color: #000000;">5</span><span style="color: #0000FF;">},</span><span style="color: #000000;">tasklist</span><span style="color: #0000FF;">)</span>
<span style="color: #7060A8;">pq_add</span><span style="color: #0000FF;">({</span><span style="color: #008000;">"Solve RC tasks"</span><span style="color: #0000FF;">,</span><span style="color: #000000;">1</span><span style="color: #0000FF;">},</span><span style="color: #000000;">tasklist</span><span style="color: #0000FF;">)</span>
<span style="color: #7060A8;">pq_add</span><span style="color: #0000FF;">({</span><span style="color: #008000;">"Tax return"</span><span style="color: #0000FF;">,</span><span style="color: #000000;">2</span><span style="color: #0000FF;">},</span><span style="color: #000000;">tasklist</span><span style="color: #0000FF;">)</span>
<span style="color: #008080;">while</span> <span style="color: #7060A8;">pq_size</span><span style="color: #0000FF;">(</span><span style="color: #000000;">tasklist</span><span style="color: #0000FF;">)</span> <span style="color: #008080;">do</span>
<span style="color: #0000FF;">{</span><span style="color: #004080;">string</span> <span style="color: #000000;">task</span><span style="color: #0000FF;">,</span> <span style="color: #004080;">integer</span> <span style="color: #000000;">priority</span><span style="color: #0000FF;">}</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">pq_pop</span><span style="color: #0000FF;">(</span><span style="color: #000000;">tasklist</span><span style="color: #0000FF;">)</span>
<span style="color: #7060A8;">printf</span><span style="color: #0000FF;">(</span><span style="color: #000000;">1</span><span style="color: #0000FF;">,</span><span style="color: #008000;">"%d: %s\n"</span><span style="color: #0000FF;">,{</span><span style="color: #000000;">priority</span><span style="color: #0000FF;">,</span><span style="color: #000000;">task</span><span style="color: #0000FF;">})</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">while</span>
<!--</syntaxhighlight>-->
{{out}}
<pre>
5: Make tea
4: Feed cat
3: Clear drains
2: Tax return
1: Solve RC tasks
</pre>
 
=={{header|Phixmonti}}==
<syntaxhighlight lang="phixmonti">/# Rosetta Code problem: http://rosettacode.org/wiki/Priority_queue
by Galileo, 05/2022 #/
 
include ..\Utilitys.pmt
 
( )
( 3 "Clear drains" ) 0 put ( 4 "Feed cat" ) 0 put ( 5 "Make tea" ) 0 put ( 1 "Solve RC tasks" ) 0 put ( 2 "Tax return" ) 0 put
sort pop swap print pstack
</syntaxhighlight>
{{out}}
<pre>[1, "Solve RC tasks"]
[[[2, "Tax return"], [3, "Clear drains"], [4, "Feed cat"], [5, "Make tea"]]]
 
=== Press any key to exit ===</pre>
 
=={{header|PHP}}==
{{works with|PHP|5.3+}}
PHP's <code>SplPriorityQueue</code> class implements a max-heap. PHP also separately has <code>SplHeap</code>, <code>SplMinHeap</code>, and <code>SplMaxHeap</code> classes.
<syntaxhighlight lang="php"><?php
$pq = new SplPriorityQueue;
 
$pq->insert('Clear drains', 3);
$pq->insert('Feed cat', 4);
$pq->insert('Make tea', 5);
$pq->insert('Solve RC tasks', 1);
$pq->insert('Tax return', 2);
 
// This line causes extract() to return both the data and priority (in an associative array),
// Otherwise it would just return the data
$pq->setExtractFlags(SplPriorityQueue::EXTR_BOTH);
 
while (!$pq->isEmpty()) {
print_r($pq->extract());
}
?></syntaxhighlight>
 
Output:
say $pq.get until $pq.is_empty;</lang>
<pre>
Array
(
[data] => Make tea
[priority] => 5
)
Array
(
[data] => Feed cat
[priority] => 4
)
Array
(
[data] => Clear drains
[priority] => 3
)
Array
(
[data] => Tax return
[priority] => 2
)
Array
(
[data] => Solve RC tasks
[priority] => 1
)
</pre>
 
{{works with|PHP|5.3+}}
The difference between <code>SplHeap</code> and <code>SplPriorityQueue</code> is that <code>SplPriorityQueue</code> takes the data and the priority as two separate arguments, and the comparison is only made on the priority; whereas <code>SplHeap</code> takes only one argument (the element), and the comparison is made on that directly. In all of these classes it is possible to provide a custom comparator by subclassing the class and overriding its <code>compare</code> method.
<syntaxhighlight lang="php"><?php
$pq = new SplMinHeap;
$pq->insert(array(3, 'Clear drains'));
$pq->insert(array(4, 'Feed cat'));
$pq->insert(array(5, 'Make tea'));
$pq->insert(array(1, 'Solve RC tasks'));
$pq->insert(array(2, 'Tax return'));
 
while (!$pq->isEmpty()) {
print_r($pq->extract());
}
?></syntaxhighlight>
 
Output:
<pre>Solve RC tasks
Array
Do taxes
(
Clear drains
[0] => 1
Check email
[1] => Solve RC tasks
Feed cat
)
Make tea
Array
Sleep
(
Exercise</pre>
[0] => 2
[1] => Tax return
)
Array
(
[0] => 3
[1] => Clear drains
)
Array
(
[0] => 4
[1] => Feed cat
)
Array
(
[0] => 5
[1] => Make tea
)
</pre>
 
=={{header|Picat}}==
Picat has built-in support for min and max heaps.
<syntaxhighlight lang="picat">main =>
Tasks = [[3,"Clear drains"],
[4,"Feed cat"],
[5,"Make tea"],
[1,"Solve RC tasks"],
[2,"Tax return"]],
Heap = new_min_heap([]),
foreach(Task in Tasks)
Heap.heap_push(Task),
println(top=Heap.heap_top())
end,
nl,
println(Heap),
println(size=Heap.heap_size),
nl,
println("Pop the elements from the queue:"),
println([Heap.heap_pop() : _ in 1..Heap.heap_size]).</syntaxhighlight>
 
{{out}}
<pre>top = [3,Clear drains]
top = [3,Clear drains]
top = [3,Clear drains]
top = [1,Solve RC tasks]
top = [1,Solve RC tasks]
 
_$heap(5,{[1,Solve RC tasks],[2,Tax return],[5,Make tea],[4,Feed cat],[3,Clear drains],_33c8},min)
size = 5
 
Pop the elements from the queue:
[[1,Solve RC tasks],[2,Tax return],[3,Clear drains],[4,Feed cat],[5,Make tea]]</pre>
 
The heaps creation functions can take the task list as argument:
<syntaxhighlight lang="picat"> Tasks = [[3,"Clear drains"],
[4,"Feed cat"],
[5,"Make tea"],
[1,"Solve RC tasks"],
[2,"Tax return"]],
Heap = new_min_heap(Tasks),
println([Heap.heap_pop() : _ in 1..Heap.heap_size]).</syntaxhighlight>
 
 
=={{header|PicoLisp}}==
The following implementation imposes no limits. It uses a [http://software-lab.de/doc/refI.html#idx binary tree] for storage. The priority levels may be numeric, or of any other type.
<langsyntaxhighlight PicoLisplang="picolisp"># Insert item into priority queue
(de insertPQ (Queue Prio Item)
(idx Queue (cons Prio Item) T) )
Line 600 ⟶ 6,770:
# Merge second queue into first
(de mergePQ (Queue1 Queue2)
(balance Queue1 (sort (conc (idx Queue1) (idx Queue2)))) )</langsyntaxhighlight>
Test:
<langsyntaxhighlight PicoLisplang="picolisp"># Two priority queues
(off Pq1 Pq2)
 
Line 619 ⟶ 6,789:
# Remove and print all items from first queue
(while Pq1
(println (removePQ 'Pq1)) )</langsyntaxhighlight>
Output:
<pre>(Solve RC tasks)
Line 626 ⟶ 6,796:
(Feed cat)
(Make tea)</pre>
=== Alternative version using a pairing heap: ===
<syntaxhighlight lang="picolisp">
(de heap-first (H) (car H))
 
(de heap-merge (H1 H2)
(cond
((= H1 NIL) H2)
((= H2 NIL) H1)
((< (car H1) (car H2))
(cons (car H1) (cons H2 (cdr H1))))
(T
(cons (car H2) (cons H1 (cdr H2))))))
 
(de heap-insert (Item Heap)
(heap-merge (list Item) Heap))
 
(de "merge-pairs" (H)
(if (= (cdr H) NIL)
(car H) # also handles NIL (H = NIL -> NIL)
(heap-merge
(heap-merge (car H) (cadr H))
("merge-pairs" (cddr H)))))
 
(de heap-rest (H)
("merge-pairs" (cdr H)))
</syntaxhighlight>
Test:
<syntaxhighlight lang="picolisp">
(setq H NIL)
(for
Task '(
(3 . "Clear drains.")
(4 . "Feed cat.")
(5 . "Make tea.")
(1 . "Solve RC tasks.")
(2 . "Tax Return."))
(setq H (heap-insert Task H)))
 
(while H
(prinl (caar H) ". " (cdar H))
(setq H (heap-rest H)))
 
(bye)
</syntaxhighlight>
{{Out}}
<pre>
1. Solve RC tasks.
2. Tax Return.
3. Clear drains.
4. Feed cat.
5. Make tea.
</pre>
 
=={{header|Prolog}}==
SWI-Prolog has a library <b>heaps.pl</b>, written by <b>Lars Buitinck</b> that implements priority queues.<br>
Informations here : http://www.swi-prolog.org/pldoc/doc/swi/library/heaps.pl
 
Example of use :
<syntaxhighlight lang="prolog">priority-queue :-
TL0 = [3-'Clear drains',
4-'Feed cat'],
 
% we can create a priority queue from a list
list_to_heap(TL0, Heap0),
% alternatively we can start from an empty queue
% get from empty_heap/1.
% now we add the other elements
add_to_heap(Heap0, 5, 'Make tea', Heap1),
add_to_heap(Heap1, 1, 'Solve RC tasks', Heap2),
add_to_heap(Heap2, 2, 'Tax return', Heap3),
 
% we list the content of the heap:
heap_to_list(Heap3, TL1),
writeln('Content of the queue'), maplist(writeln, TL1),
nl,
 
% now we retrieve the minimum-priority pair
get_from_heap(Heap3, Priority, Key, Heap4),
format('Retrieve top of the queue : Priority ~w, Element ~w~n', [Priority, Key]),
nl,
 
% we list the content of the heap:
heap_to_list(Heap4, TL2),
writeln('Content of the queue'), maplist(writeln, TL2).
</syntaxhighlight>
The output :
<pre>1 ?- priority-queue.
Content of the queue
1-Solve RC tasks
2-Tax return
3-Clear drains
4-Feed cat
5-Make tea
 
Retrieve top of the queue : Priority 1, Element Solve RC tasks
 
Content of the queue
2-Tax return
3-Clear drains
4-Feed cat
5-Make tea
true.
</pre>
 
=={{header|PureBasic}}==
The priority queue is implemented using a binary heap array and a map.
The map stores the elements of a given priority in a FIFO list.
Priorities can be any signed 32 value.
<syntaxhighlight lang="purebasic">Structure taskList
List description.s() ;implements FIFO queue
EndStructure
 
Structure task
*tl.tList ;pointer to a list of task descriptions
Priority.i ;tasks priority, lower value has more priority
EndStructure
 
Structure priorityQueue
maxHeapSize.i ;increases as needed
heapItemCount.i ;number of elements currently in heap
Array heap.task(0) ;elements hold FIFO queues ordered by priorities, lowest first
map heapMap.taskList() ;holds lists of tasks with the same priority that are FIFO queues
EndStructure
 
Procedure insertPQ(*PQ.priorityQueue, description.s, p)
If FindMapElement(*PQ\heapMap(), Str(p))
LastElement(*PQ\heapMap()\description())
AddElement(*PQ\heapMap()\description())
*PQ\heapMap()\description() = description
Else
Protected *tl.taskList = AddMapElement(*PQ\heapMap(), Str(p))
AddElement(*tl\description())
*tl\description() = description
Protected pos = *PQ\heapItemCount
*PQ\heapItemCount + 1
If *PQ\heapItemCount > *PQ\maxHeapSize
Select *PQ\maxHeapSize
Case 0
*PQ\maxHeapSize = 128
Default
*PQ\maxHeapSize * 2
EndSelect
Redim *PQ\heap.task(*PQ\maxHeapSize)
EndIf
While pos > 0 And p < *PQ\heap((pos - 1) / 2)\Priority
*PQ\heap(pos) = *PQ\heap((pos - 1) / 2)
pos = (pos - 1) / 2
Wend
*PQ\heap(pos)\tl = *tl
*PQ\heap(pos)\Priority = p
EndIf
EndProcedure
 
Procedure.s removePQ(*PQ.priorityQueue)
Protected *tl.taskList = *PQ\heap(0)\tl, description.s
FirstElement(*tl\description())
description = *tl\description()
If ListSize(*tl\description()) > 1
DeleteElement(*tl\description())
Else
DeleteMapElement(*PQ\heapMap(), Str(*PQ\heap(0)\Priority))
*PQ\heapItemCount - 1
*PQ\heap(0) = *PQ\heap(*PQ\heapItemCount)
Protected pos
Repeat
Protected child1 = 2 * pos + 1
Protected child2 = 2 * pos + 2
If child1 >= *PQ\heapItemCount
Break
EndIf
Protected smallestChild
If child2 >= *PQ\heapItemCount
smallestChild = child1
ElseIf *PQ\heap(child1)\Priority <= *PQ\heap(child2)\Priority
smallestChild = child1
Else
smallestChild = child2
EndIf
If (*PQ\heap(smallestChild)\Priority >= *PQ\heap(pos)\Priority)
Break
EndIf
Swap *PQ\heap(pos)\tl, *PQ\heap(smallestChild)\tl
Swap *PQ\heap(pos)\Priority, *PQ\heap(smallestChild)\Priority
pos = smallestChild
ForEver
EndIf
ProcedureReturn description
EndProcedure
 
Procedure isEmptyPQ(*PQ.priorityQueue) ;returns 1 if empty, otherwise returns 0
If *PQ\heapItemCount
ProcedureReturn 0
EndIf
ProcedureReturn 1
EndProcedure
 
If OpenConsole()
Define PQ.priorityQueue
insertPQ(PQ, "Clear drains", 3)
insertPQ(PQ, "Answer Phone 1", 8)
insertPQ(PQ, "Feed cat", 4)
insertPQ(PQ, "Answer Phone 2", 8)
insertPQ(PQ, "Make tea", 5)
insertPQ(PQ, "Sleep", 9)
insertPQ(PQ, "Check email", 3)
insertPQ(PQ, "Solve RC tasks", 1)
insertPQ(PQ, "Answer Phone 3", 8)
insertPQ(PQ, "Exercise", 9)
insertPQ(PQ, "Answer Phone 4", 8)
insertPQ(PQ, "Tax return", 2)
While Not isEmptyPQ(PQ)
PrintN(removePQ(PQ))
Wend
Print(#CRLF$ + #CRLF$ + "Press ENTER to exit"): Input()
CloseConsole()
EndIf</syntaxhighlight>
{{out}}
<pre>Solve RC tasks
Tax return
Clear drains
Check email
Feed cat
Make tea
Answer Phone 1
Answer Phone 2
Answer Phone 3
Answer Phone 4
Sleep
Exercise</pre>
 
=={{header|Python}}==
Line 632 ⟶ 7,044:
 
The data structures in the "queue" module are synchronized multi-producer, multi-consumer queues for multi-threaded use. They can however handle this task:
<langsyntaxhighlight lang="python">>>> import queue
>>> pq = queue.PriorityQueue()
>>> for item in ((3, "Clear drains"), (4, "Feed cat"), (5, "Make tea"), (1, "Solve RC tasks"), (2, "Tax return")):
pq.put(item)
 
>>> while not pq.empty():
print(pq.get_nowait())
 
(1, 'Solve RC tasks')
(2, 'Tax return')
Line 647 ⟶ 7,059:
(4, 'Feed cat')
(5, 'Make tea')
>>> </langsyntaxhighlight>
 
;Help text for queue.PriorityQueue:
<langsyntaxhighlight lang="python">>>> import queue
>>> help(queue.PriorityQueue)
Help on class PriorityQueue in module queue:
Line 756 ⟶ 7,168:
| list of weak references to the object (if defined)
 
>>> </langsyntaxhighlight>
 
===Using heapq===
Line 762 ⟶ 7,174:
 
Although one can use the heappush method to add items individually to a heap similar to the method used in the PriorityQueue example above, we will instead transform the list of items into a heap in one go then pop them off one at a time as before.
<langsyntaxhighlight lang="python">>>> from heapq import heappush, heappop, heapify
>>> items = [(3, "Clear drains"), (4, "Feed cat"), (5, "Make tea"), (1, "Solve RC tasks"), (2, "Tax return")]
>>> heapify(items)
>>> while items:
print(heappop(items))
 
(1, 'Solve RC tasks')
(2, 'Tax return')
Line 774 ⟶ 7,186:
(4, 'Feed cat')
(5, 'Make tea')
>>> </langsyntaxhighlight>
 
;Help text for module heapq:
<langsyntaxhighlight lang="python">>>> help('heapq')
Help on module heapq:
 
Line 865 ⟶ 7,277:
 
 
>>> </langsyntaxhighlight>
 
 
=={{header|Quackery}}==
 
For more examples uf usage, see [[Sorting algorithms/Heapsort#Quackery]] and [[Huffman coding#Quackery]]
 
<syntaxhighlight lang="quackery">( ***** priotity queue ***** )
 
[ stack ] is heap.pq ( --> s )
 
[ stack ] is comp.pq ( --> s )
 
[ unpack
comp.pq put heap.pq put ] is pq->stacks ( p --> )
 
[ heap.pq take comp.pq take
2 pack ] is stacks->pq ( --> p )
 
[ heap.pq share swap peek ] is heapeek ( n --> x )
 
[ heap.pq take
swap poke heap.pq put ] is heapoke ( n x --> )
 
[ 1 - 1 >> ] is parent ( n --> n )
 
[ 0 > ] is has-parent ( n --> b )
 
[ 1 << 1+ ] is child ( n --> n )
 
[ child heap.pq share size < ] is has-child ( n --> b )
 
[ 1+ ] is sibling ( n --> n )
 
[ sibling
heap.pq share size < ] is has-sibling ( n --> b )
 
[ comp.pq share do ] is compare ( x x --> b )
 
[ 0 peek size ] is pqsize ( p --> n )
 
[ swap pq->stacks
heap.pq take tuck size
rot 0 join heap.pq put
[ dup has-parent while
dup parent
rot over heapeek
2dup compare iff
[ 2swap unrot heapoke ]
again
rot 2drop swap ]
heapoke
stacks->pq ] is topq ( p x --> p )
 
[ dup heapeek swap
[ dup has-child while
dup child
dup has-sibling if
[ dup sibling heapeek
over heapeek
compare if sibling ]
dip over dup heapeek
rot dip dup compare iff
[ rot heapoke ] again
2drop ]
heapoke ] is heapify.pq ( n --> )
 
[ dup pqsize 0 = if
[ $ "Unexpectedly empty priority queue."
fail ]
pq->stacks heap.pq share
behead
over [] = iff
[ swap heap.pq replace ]
else
[ swap -1 split
swap join heap.pq put
0 heapify.pq ]
stacks->pq swap ] is frompq ( p --> p x )
 
[ ]'[ 2 pack pq->stacks
heap.pq share
size 1 >> times
[ i heapify.pq ]
stacks->pq ] is pqwith ( [ --> p )
 
( ***** task ***** )
 
[ 2 pack topq ] is insert ( p n $ --> p )
 
[ frompq unpack ] is dequeue ( p --> p n $ )
 
[] pqwith [ 0 peek dip [ 0 peek ] < ]
 
3 $ "Clear drains" insert
4 $ "Feed cat" insert
5 $ "Make tea" insert
1 $ "Solve RC tasks" insert
2 $ "Tax return" insert
 
5 times
[ dequeue
swap echo say ": "
echo$ cr ]
drop</syntaxhighlight>
 
{{out}}
 
<pre>1: Solve RC tasks
2: Tax return
3: Clear drains
4: Feed cat
5: Make tea
</pre>
 
=={{header|R}}==
Using closures:
<syntaxhighlight lang="r">PriorityQueue <- function() {
keys <- values <- NULL
insert <- function(key, value) {
ord <- findInterval(key, keys)
keys <<- append(keys, key, ord)
values <<- append(values, value, ord)
}
pop <- function() {
head <- list(key=keys[1],value=values[[1]])
values <<- values[-1]
keys <<- keys[-1]
return(head)
}
empty <- function() length(keys) == 0
environment()
}
 
pq <- PriorityQueue()
pq$insert(3, "Clear drains")
pq$insert(4, "Feed cat")
pq$insert(5, "Make tea")
pq$insert(1, "Solve RC tasks")
pq$insert(2, "Tax return")
while(!pq$empty()) {
with(pq$pop(), cat(key,":",value,"\n"))
}</syntaxhighlight>With output:<syntaxhighlight lang="r">1 : Solve RC tasks
2 : Tax return
3 : Clear drains
4 : Feed cat
5 : Make tea</syntaxhighlight>A similar implementation using R5 classes:<syntaxhighlight lang="r">PriorityQueue <-
setRefClass("PriorityQueue",
fields = list(keys = "numeric", values = "list"),
methods = list(
insert = function(key,value) {
insert.order <- findInterval(key, keys)
keys <<- append(keys, key, insert.order)
values <<- append(values, value, insert.order)
},
pop = function() {
head <- list(key=keys[1],value=values[[1]])
keys <<- keys[-1]
values <<- values[-1]
return(head)
},
empty = function() length(keys) == 0
))</syntaxhighlight>The only change in the example would be in the instantiation:<syntaxhighlight lang="r">pq <- PriorityQueue$new()</syntaxhighlight>.
 
=={{header|Racket}}==
This solution implements priority queues on top of heaps.
<syntaxhighlight lang="racket">
#lang racket
(require data/heap)
 
(define pq (make-heap (λ(x y) (<= (second x) (second y)))))
 
(define (insert! x pri)
(heap-add! pq (list pri x)))
 
(define (remove-min!)
(begin0
(first (heap-min pq))
(heap-remove-min! pq)))
 
(insert! 3 "Clear drains")
(insert! 4 "Feed cat")
(insert! 5 "Make tea")
(insert! 1 "Solve RC tasks")
(insert! 2 "Tax return")
 
(remove-min!)
(remove-min!)
(remove-min!)
(remove-min!)
(remove-min!)
</syntaxhighlight>
Output:
<syntaxhighlight lang="racket">
"Solve RC tasks"
"Tax return"
"Clear drains"
"Feed cat"
"Make tea"
</syntaxhighlight>
 
=={{header|Raku}}==
(formerly Perl 6)
This is a rather simple implementation. It requires the priority to be a positive integer value, with lower values being higher priority. There isn't a hard limit on how many priority levels you can have, though more than a few dozen is probably not practical.
 
The tasks are stored internally as an array of FIFO buffers, so multiple tasks of the same priority level will be returned in the order they were stored.
 
<syntaxhighlight lang="raku" line>class PriorityQueue {
has @!tasks;
 
method insert (Int $priority where * >= 0, $task) {
@!tasks[$priority].push: $task;
}
 
method get { @!tasks.first(?*).shift }
 
method is-empty { ?none @!tasks }
}
 
my $pq = PriorityQueue.new;
for (
3, 'Clear drains',
4, 'Feed cat',
5, 'Make tea',
9, 'Sleep',
3, 'Check email',
1, 'Solve RC tasks',
9, 'Exercise',
2, 'Do taxes'
) -> $priority, $task {
$pq.insert( $priority, $task );
}
say $pq.get until $pq.is-empty;</syntaxhighlight>
 
{{out}}
<pre>Solve RC tasks
Do taxes
Clear drains
Check email
Feed cat
Make tea
Sleep
Exercise</pre>
 
=={{header|REXX}}==
===version 1===
Programming note: &nbsp; this REXX version allows any number (with or without decimals, say, '''5.7''') for the priority, including negative numbers.
<syntaxhighlight lang="rexx">/*REXX program implements a priority queue with insert/display/delete the top task.*/
#=0; @.= /*0 tasks; nullify the priority queue.*/
say '══════ inserting tasks.'; call .ins 3 "Clear drains"
call .ins 4 "Feed cat"
call .ins 5 "Make tea"
call .ins 1 "Solve RC tasks"
call .ins 2 "Tax return"
call .ins 6 "Relax"
call .ins 6 "Enjoy"
say '══════ showing tasks.'; call .show
say '══════ deletes top task.'; say .del() /*delete the top task. */
exit /*stick a fork in it, we're all done. */
/*──────────────────────────────────────────────────────────────────────────────────────*/
.del: procedure expose @. #; arg p; if p='' then p=.top(); y=@.p; @.p=; return y
.ins: procedure expose @. #; #=#+1; @.#=arg(1); return # /*entry, P, task.*/
.show: procedure expose @. #; do j=1 for #; _=@.j; if _\=='' then say _; end; return
/*──────────────────────────────────────────────────────────────────────────────────────*/
.top: procedure expose @. #; top=; top#=
do j=1 for #; _=word(@.j, 1); if _=='' then iterate
if top=='' | _>top then do; top=_; top#=j; end
end /*j*/
return top#</syntaxhighlight>
{{out|output}}
<pre>
══════ inserting tasks.
══════ showing tasks.
3 Clear drains
4 Feed cat
5 Make tea
1 Solve RC tasks
2 Tax return
6 Relax
6 Enjoy
══════ deletes top task.
6 Relax
</pre>
 
===version 2===
<syntaxhighlight lang="rexx">/*REXX pgm implements a priority queue; with insert/show/delete top task*/
n=0
task.=0 /* for the sake of task.0done.* */
say '------ inserting tasks.'; call ins_task 3 'Clear drains'
call ins_task 4 'Feed cat'
call ins_task 5 'Make tea'
call ins_task 1 'Solve RC tasks'
call ins_task 2 'Tax return'
call ins_task 6 'Relax'
call ins_task 6 'Enjoy'
say '------ Showing tasks.'; call show_tasks
say '------ Show and delete top task.'
todo=n /* tasks to be done */
do While todo>0
Say top()
End
exit
 
ins_task: procedure expose n task.
n=n+1
Parse Arg task.0pri.n task.0txt.n
Return
 
show_tasks: procedure expose task. n
do i=1 To n
Say task.0pri.i task.0txt.i
End
Return
 
top: procedure expose n task. todo /* get top task and mark it 'done' */
high=0
Do i=1 To n
If task.0pri.i>high &,
task.0done.i=0 Then Do
j=i
high=task.0pri.i
End
End
res=task.0pri.j task.0txt.j
task.0done.j=1
todo=todo-1
return res</syntaxhighlight>
{{out}}
<pre>------ inserting tasks.
------ Showing tasks.
3 Clear drains
4 Feed cat
5 Make tea
1 Solve RC tasks
2 Tax return
6 Relax
6 Enjoy
------ Show and delete top task.
6 Relax
6 Enjoy
5 Make tea
4 Feed cat
3 Clear drains
2 Tax return
1 Solve RC tasks</pre>
 
=={{header|Ruby}}==
A naive, inefficient implementation
<syntaxhighlight lang="ruby">class PriorityQueueNaive
def initialize(data=nil)
@q = Hash.new {|h, k| h[k] = []}
data.each {|priority, item| @q[priority] << item} if data
@priorities = @q.keys.sort
end
def push(priority, item)
@q[priority] << item
@priorities = @q.keys.sort
end
def pop
p = @priorities[0]
item = @q[p].shift
if @q[p].empty?
@q.delete(p)
@priorities.shift
end
item
end
def peek
unless empty?
@q[@priorities[0]][0]
end
end
def empty?
@priorities.empty?
end
def each
@q.each do |priority, items|
items.each {|item| yield priority, item}
end
end
def dup
@q.each_with_object(self.class.new) do |(priority, items), obj|
items.each {|item| obj.push(priority, item)}
end
end
def merge(other)
raise TypeError unless self.class == other.class
pq = dup
other.each {|priority, item| pq.push(priority, item)}
pq # return a new object
end
def inspect
@q.inspect
end
end
 
test = [
[6, "drink tea"],
[3, "Clear drains"],
[4, "Feed cat"],
[5, "Make tea"],
[6, "eat biscuit"],
[1, "Solve RC tasks"],
[2, "Tax return"],
]
 
pq = PriorityQueueNaive.new
test.each {|pr, str| pq.push(pr, str) }
until pq.empty?
puts pq.pop
end
 
puts
test2 = test.shift(3)
p pq1 = PriorityQueueNaive.new(test)
p pq2 = PriorityQueueNaive.new(test2)
p pq3 = pq1.merge(pq2)
puts "peek : #{pq3.peek}"
until pq3.empty?
puts pq3.pop
end
puts "peek : #{pq3.peek}"</syntaxhighlight>
 
{{out}}
<pre>
Solve RC tasks
Tax return
Clear drains
Feed cat
Make tea
drink tea
eat biscuit
 
{5=>["Make tea"], 6=>["eat biscuit"], 1=>["Solve RC tasks"], 2=>["Tax return"]}
{6=>["drink tea"], 3=>["Clear drains"], 4=>["Feed cat"]}
{5=>["Make tea"], 6=>["eat biscuit", "drink tea"], 1=>["Solve RC tasks"], 2=>["Tax return"], 3=>["Clear drains"], 4=>["Feed cat"]}
peek : Solve RC tasks
Solve RC tasks
Tax return
Clear drains
Feed cat
Make tea
eat biscuit
drink tea
peek :
</pre>
 
=={{header|Run BASIC}}==
<syntaxhighlight lang="runbasic">sqliteconnect #mem, ":memory:"
#mem execute("CREATE TABLE queue (priority float,descr text)")
 
' --------------------------------------------------------------
' Insert items into the que
' --------------------------------------------------------------
#mem execute("INSERT INTO queue VALUES (3,'Clear drains')")
#mem execute("INSERT INTO queue VALUES (4,'Feed cat')")
#mem execute("INSERT INTO queue VALUES (5,'Make tea')")
#mem execute("INSERT INTO queue VALUES (1,'Solve RC tasks')")
#mem execute("INSERT INTO queue VALUES (2,'Tax return')")
 
'--------------- insert priority between 4 and 5 -----------------
#mem execute("INSERT INTO queue VALUES (4.5,'My Special Project')")
 
what$ = " -------------- Find first priority ---------------------"
mem$ = "SELECT * FROM queue ORDER BY priority LIMIT 1"
gosub [getQueue]
 
what$ = " -------------- Find last priority ---------------------"
mem$ = "SELECT * FROM queue ORDER BY priority desc LIMIT 1"
gosub [getQueue]
 
what$ = " -------------- Delete Highest Priority ---------------------"
mem$ = "DELETE FROM queue WHERE priority = (select max(q.priority) FROM queue as q)"
#mem execute(mem$)
 
what$ = " -------------- List Priority Sequence ---------------------"
mem$ = "SELECT * FROM queue ORDER BY priority"
gosub [getQueue]
end
 
 
[getQueue]
print what$
#mem execute(mem$)
rows = #mem ROWCOUNT()
print "Priority Description"
for i = 1 to rows
#row = #mem #nextrow()
priority = #row priority()
descr$ = #row descr$()
print priority;" ";descr$
next i
RETURN</syntaxhighlight>
{{out}}
<pre> -------------- Find first priority ---------------------
Priority Description
1.0 Solve RC tasks
-------------- Find last priority ---------------------
Priority Description
5.0 Make tea
-------------- List Priority Sequence ---------------------
Priority Description
1.0 Solve RC tasks
2.0 Tax return
3.0 Clear drains
4.0 Feed cat
4.5 My Special Project</pre>
 
=={{header|Rust}}==
<syntaxhighlight lang="rust">use std::collections::BinaryHeap;
use std::cmp::Ordering;
use std::borrow::Cow;
 
#[derive(Eq, PartialEq)]
struct Item<'a> {
priority: usize,
task: Cow<'a, str>, // Takes either borrowed or owned string
}
 
impl<'a> Item<'a> {
fn new<T>(p: usize, t: T) -> Self
where T: Into<Cow<'a, str>>
{
Item {
priority: p,
task: t.into(),
}
}
}
 
// Manually implpement Ord so we have a min heap
impl<'a> Ord for Item<'a> {
fn cmp(&self, other: &Self) -> Ordering {
other.priority.cmp(&self.priority)
}
}
 
// PartialOrd is required by Ord
impl<'a> PartialOrd for Item<'a> {
fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
Some(self.cmp(other))
}
}
 
 
fn main() {
let mut queue = BinaryHeap::with_capacity(5);
queue.push(Item::new(3, "Clear drains"));
queue.push(Item::new(4, "Feed cat"));
queue.push(Item::new(5, "Make tea"));
queue.push(Item::new(1, "Solve RC tasks"));
queue.push(Item::new(2, "Tax return"));
 
for item in queue {
println!("{}", item.task);
}
}</syntaxhighlight>
{{out}}
<pre>Solve RC tasks
Tax return
Make tea
Feed cat
Clear drains</pre>
 
=={{header|SAS}}==
Using macros in a SAS data step:
<syntaxhighlight lang="sas">%macro HeapInit(size=1000,nchar=20);
do;
_len = 0;
_size = &size;
array _times(&size) _temporary_ ;
array _kinds(&size) $ &nchar _temporary_;
drop _size _len;
end;
%mend;
%macro HeapSwapItem(index1, index2);
do;
_tempN = _times[&index1]; _times[&index1] = _times[&index2]; _times[&index2] = _tempN;
_tempC = _kinds[&index1]; _kinds[&index1] = _kinds[&index2]; _kinds[&index2]= _tempC;
drop _tempN _tempC;
end;
%mend;
%macro HeapEmpty;
(_len=0)
%mend;
%macro HeapCompare(index1, index2);
(_times[&index1] < _times[&index2])
%mend;
%macro HeapSiftdown(index);
do;
_parent = &index;
_done = 0;
do while (_parent*2 <= _len & ^_done);
_child = _parent*2;
if (_child+1 <= _len and %HeapCompare(_child+1,_child)) then
_child = _child + 1;
if %HeapCompare(_child,_parent) then do;
%HeapSwapItem(_child,_parent);
_parent = _child;
end;
else _done = 1;
end;
drop _done _parent _child;
end;
%mend;
%macro HeapSiftup(index);
do;
_child = &index;
_done = 0;
do while(_child>1 and ^_done);
_parent = floor(_child/2);
if %HeapCompare(_parent,_child) then
_done = 1;
else do;
%HeapSwapItem(_child,_parent);
_tempN = _child;
_child = _parent;
_parent = _tempN;
end;
end;
drop _parent _child _done _tempN;
end;
%mend;
%macro HeapPush(time, kind);
do;
if _len >= _size then do;
put "ERROR: exceeded size of heap. Consider changing size argument to %HeapInit.";
stop;
end;
_len = _len + 1;
_times[_len] = &time;
_kinds[_len] = &kind;
%HeapSiftup(_len);
end;
%mend;
%macro HeapPop;
do;
_len = _len - 1;
if (_len>0) then do;
_times[1] = _times[_len+1];
_kinds[1] = _kinds[_len+1];
%HeapSiftdown(1);
end;
end;
%mend;
%macro HeapPeek;
time = _times[1];
kind = _kinds[1];
put time kind;
%mend;
data _null_;
%HeapInit;
%HeapPush(3, "Clear drains");
%HeapPush(4, "Feed cat");
%HeapPush(5, "Make tea");
%HeapPush(1, "Solve RC tasks");
%HeapPush(2, "Tax return");
do while(^%HeapEmpty);
%HeapPeek;
%HeapPop;
end;
run;</syntaxhighlight>
{{output}}
<pre>1 Solve RC tasks
2 Tax return
3 Clear drains
4 Feed cat
5 Make tea</pre>
 
An implementation using <code>proc ds2</code> may be more structured:
<syntaxhighlight lang="sas">proc ds2;
package Heap / overwrite=yes;
dcl int _entryorder _size _len _entryOrders[1000];
dcl double _times[1000];
dcl varchar(20) _kinds[1000];
method init();
_entryOrder = 1;
_size = 1000;
_len = 0;
end;
method empty() returns int;
return(_len=0);
end;
method compare(int index1, int index2) returns int;
return(_times[index1] < _times[index2] or (_times[index1] = _times[index2] and _entryOrders[index1] < _entryOrders[index2]));
end;
method SetItem(int index, double _time, int entryOrder, varchar(20) kind);
_times[index] = _time;
_entryOrders[index] = entryOrder;
_kinds[index] = kind;
end;
method CopyItem(int ito, int ifrom);
_times[ito] = _times[ifrom];
_entryOrders[ito] = _entryOrders[ifrom];
_kinds[ito] = _kinds[ifrom];
end;
method SwapItem(int index1, int index2);
dcl double tempD;
dcl int tempI;
dcl varchar(20) tempC;
tempD = _times[index1]; _times[index1] = _times[index2]; _times[index2]= tempD;
tempI = _entryorders[index1]; _entryorders[index1] = _entryorders[index2]; _entryorders[index2]= tempI;
tempC = _kinds[index1]; _kinds[index1] = _kinds[index2]; _kinds[index2]= tempC;
end;
method Siftdown(int index);
dcl int parent done child;
parent = index;
done = 0;
do while (parent*2 <= _len and ^done);
child = parent*2;
if (child+1 <= _len and Compare(child+1,child)) then
child = child + 1;
if Compare(child,parent) then do;
SwapItem(child,parent);
parent = child;
end;
else done = 1;
end;
end;
method Siftup(int index);
dcl int parent child done tempI;
child = index;
done = 0;
do while(child>1 and ^done);
parent = floor(child/2);
if Compare(parent,child) then
done = 1;
else do;
SwapItem(child,parent);
tempI = child;
child = parent;
parent = tempI;
end;
end;
end;
method Pop();
_len = _len - 1;
if (_len>0) then do;
CopyItem(1,_len+1);
Siftdown(1);
end;
end;
method PeekTime() returns double;
return _times[1];
end;
method PeekKind() returns varchar(20);
return _kinds[1];
end;
method Push(double _time, varchar(20) kind);
if _len >= _size then do;
put 'ERROR: exceeded size of heap.';
stop;
end;
_len = _len + 1;
_entryOrder = _entryOrder + 1;
SetItem(_len, _time, _entryOrder, kind);
Siftup(_len);
end;
endpackage;
run;
data _null_;
dcl package Heap h();
method init();
dcl double _time;
dcl varchar(20) _kind;
h.init();
h.Push(3, 'Clear drains');
h.Push(4, 'Feed cat');
h.Push(5, 'Make tea');
h.Push(1, 'Solve RC tasks');
h.Push(2, 'Tax return');
do while(^h.empty());
_time = h.PeekTime();
_kind = h.PeekKind();
put _time _kind;
h.Pop();
end;
end;
enddata;
run;</syntaxhighlight>
 
=={{header|Scala}}==
Scala has a class PriorityQueue in its standard library.
<syntaxhighlight lang="scala">import scala.collection.mutable.PriorityQueue
case class Task(prio:Int, text:String) extends Ordered[Task] {
def compare(that: Task)=that.prio compare this.prio
}
 
//test
var q=PriorityQueue[Task]() ++ Seq(Task(3, "Clear drains"), Task(4, "Feed cat"),
Task(5, "Make tea"), Task(1, "Solve RC tasks"), Task(2, "Tax return"))
while(q.nonEmpty) println(q dequeue)</syntaxhighlight>
Output:
<pre>Task(1,Solve RC tasks)
Task(2,Tax return)
Task(3,Clear drains)
Task(4,Feed cat)
Task(5,Make tea)</pre>
Instead of deriving the class from Ordering an implicit conversion could be provided.
<syntaxhighlight lang="scala">case class Task(prio:Int, text:String)
implicit def taskOrdering=new Ordering[Task] {
def compare(t1:Task, t2:Task):Int=t2.prio compare t1.prio
}</syntaxhighlight>
 
=={{header|SenseTalk}}==
We use New to create an object instance -- in this case (for simplicity) based on the script itself, which is named PriorityQueue. The Tell command or dot notation are then used to send messages directly to that object.
<syntaxhighlight lang="sensetalk">
// PriorityQueue.script
set Tasks to a new PriorityQueue
 
tell Tasks to add 3,"Clear drains"
tell Tasks to add 4,"Feed cat"
tell Tasks to add 5,"Make tea"
tell Tasks to add 1,"Solve RC tasks"
tell Tasks to add 2,"Tax return"
 
put "Initial tasks:"
put Tasks.report & return
 
put Tasks.getTop into topItem
put "Top priority: " & topItem & return
 
put "Remaining:" & return & Tasks.report
 
------
properties
queue:[]
end properties
 
to add newPriority, newTask
repeat with each item of my queue
if newPriority comes before the priority of it then
insert {priority:newPriority, task:newTask} before item the counter of my queue
return
end if
end repeat
insert {priority:newPriority, task:newTask} into my queue -- add at end if last priority
end add
 
to getTop
pull my queue into firstItem
return firstItem
end getTop
 
to report
return (priority of each && task of each for each item of my queue) joined by return
end report
</syntaxhighlight>
{{out}}
<pre>
Initial tasks:
1 Solve RC tasks
2 Tax return
3 Clear drains
4 Feed cat
5 Make tea
 
Top priority: {priority:1, task:"Solve RC tasks"}
 
Remaining:
2 Tax return
3 Clear drains
4 Feed cat
5 Make tea
</pre>
 
=={{header|Sidef}}==
{{trans|Raku}}
<syntaxhighlight lang="ruby">class PriorityQueue {
has tasks = []
 
method insert (Number priority { _ >= 0 }, task) {
for n in range(tasks.len, priority) {
tasks[n] = []
}
tasks[priority].append(task)
}
 
method get { tasks.first { !.is_empty } -> shift }
method is_empty { tasks.all { .is_empty } }
}
 
var pq = PriorityQueue()
 
[
[3, 'Clear drains'],
[4, 'Feed cat'],
[5, 'Make tea'],
[9, 'Sleep'],
[3, 'Check email'],
[1, 'Solve RC tasks'],
[9, 'Exercise'],
[2, 'Do taxes'],
].each { |pair|
pq.insert(pair...)
}
 
say pq.get while !pq.is_empty</syntaxhighlight>
 
{{out}}
<pre>
Solve RC tasks
Do taxes
Clear drains
Check email
Feed cat
Make tea
Sleep
Exercise
</pre>
 
=={{header|Standard ML}}==
Line 871 ⟶ 8,202:
Note: this is a max-heap
 
<langsyntaxhighlight lang="sml">structure TaskPriority = struct
type priority = int
val compare = Int.compare
Line 888 ⟶ 8,219:
(1, "Solve RC tasks"),
(2, "Tax return")]
val pq = foldrfoldl PQ.insert PQ.empty tasks
(* or val pq = PQ.fromList tasks *)
fun aux pq' =
Line 899 ⟶ 8,230:
in
aux pq
end</langsyntaxhighlight>
 
testing:
Line 908 ⟶ 8,239:
2, Tax return
1, Solve RC tasks
</pre>
 
=={{header|Stata}}==
{{trans|Fortran}}
 
Using <code>mata</code>, which has 1-based arrays:
<syntaxhighlight lang="stata">mata
struct Node {
real scalar time
transmorphic data
}
class Heap {
public:
struct Node rowvector nodes
real scalar len
real scalar size
real scalar minHeap
void new()
void push()
void siftup()
void siftdown()
struct Node scalar pop()
real scalar empty()
real scalar compare()
}
real scalar Heap::compare(a,b) {
struct Node scalar left, right
left = nodes[a]
right = nodes[b]
return(minHeap ? left.time<right.time : left.time>right.time)
}
void Heap::new() {
len = 0
size = 4
nodes = Node(1,size)
minHeap = 1 // defaults to min heap
}
real scalar Heap::empty() {
return(len==0)
}
void Heap::siftdown(real scalar index) {
parent = index
while (parent*2 <= len) {
child = parent*2
if (child+1 <= len ? compare(child+1,child) : 0) {
child++
}
if (compare(child,parent)) {
nodes[(child,parent)] = nodes[(parent,child)]
parent = child
} else break
}
}
void Heap::siftup(real scalar index) {
child = index
while(child>1) {
parent = floor(child/2)
if (compare(parent,child)) {
break
}
nodes[(child,parent)] = nodes[(parent,child)]
temp = child
child = parent
parent = temp
}
}
void Heap::push (real scalar time, transmorphic data) {
if (len + 1 >= size) {
nodes = (nodes, nodes)
size = size*2
}
len++
nodes[len].time = time
nodes[len].data = data
siftup(len)
}
struct Node scalar Heap::pop () {
if (len==0) {
_error(3000,"empty heap")
}
len--
struct Node scalar newnode
newnode.time = nodes[1].time
newnode.data = nodes[1].data
if (len>0) {
nodes[1] = nodes[len+1]
siftdown(1)
}
return(newnode)
}
void testHeap(real scalar minHeap) {
class Heap scalar h
struct Node scalar node
h = Heap()
h.minHeap = minHeap
h.push(3, "Clear drains")
h.push(4, "Feed cat")
h.push(5, "Make tea")
h.push(1, "Solve RC tasks")
h.push(2, "Tax return")
while (!h.empty()) {
node = h.pop()
printf("%f -> %s\n", node.time, node.data)
}
}
testHeap(1)
testHeap(0)
end
</syntaxhighlight>
{{out}}
<pre>
: testHeap(1)
1 -> Solve RC tasks
2 -> Tax return
3 -> Clear drains
4 -> Feed cat
5 -> Make tea
 
: testHeap(0)
5 -> Make tea
4 -> Feed cat
3 -> Clear drains
2 -> Tax return
1 -> Solve RC tasks
</pre>
 
Note: the Fortran version was simpler and did not use the <code>siftup()</code> method.
 
=={{header|Swift}}==
You can use <code>CFBinaryHeap</code> from Core Foundation, but it is super ugly due to the fact that <code>CFBinaryHeap</code> operates on generic pointers, and you need to convert back and forth between that and objects.
{{works with|Swift|2.x}}
<syntaxhighlight lang="swift">class Task : Comparable, CustomStringConvertible {
var priority : Int
var name: String
init(priority: Int, name: String) {
self.priority = priority
self.name = name
}
var description: String {
return "\(priority), \(name)"
}
}
func ==(t1: Task, t2: Task) -> Bool {
return t1.priority == t2.priority
}
func <(t1: Task, t2: Task) -> Bool {
return t1.priority < t2.priority
}
 
struct TaskPriorityQueue {
let heap : CFBinaryHeapRef = {
var callBacks = CFBinaryHeapCallBacks(version: 0, retain: {
UnsafePointer(Unmanaged<Task>.fromOpaque(COpaquePointer($1)).retain().toOpaque())
}, release: {
Unmanaged<Task>.fromOpaque(COpaquePointer($1)).release()
}, copyDescription: nil, compare: { (ptr1, ptr2, _) in
let t1 : Task = Unmanaged<Task>.fromOpaque(COpaquePointer(ptr1)).takeUnretainedValue()
let t2 : Task = Unmanaged<Task>.fromOpaque(COpaquePointer(ptr2)).takeUnretainedValue()
return t1 == t2 ? CFComparisonResult.CompareEqualTo : t1 < t2 ? CFComparisonResult.CompareLessThan : CFComparisonResult.CompareGreaterThan
})
return CFBinaryHeapCreate(nil, 0, &callBacks, nil)
}()
var count : Int { return CFBinaryHeapGetCount(heap) }
mutating func push(t: Task) {
CFBinaryHeapAddValue(heap, UnsafePointer(Unmanaged.passUnretained(t).toOpaque()))
}
func peek() -> Task {
return Unmanaged<Task>.fromOpaque(COpaquePointer(CFBinaryHeapGetMinimum(heap))).takeUnretainedValue()
}
mutating func pop() -> Task {
let result = Unmanaged<Task>.fromOpaque(COpaquePointer(CFBinaryHeapGetMinimum(heap))).takeUnretainedValue()
CFBinaryHeapRemoveMinimumValue(heap)
return result
}
}
 
var pq = TaskPriorityQueue()
 
pq.push(Task(priority: 3, name: "Clear drains"))
pq.push(Task(priority: 4, name: "Feed cat"))
pq.push(Task(priority: 5, name: "Make tea"))
pq.push(Task(priority: 1, name: "Solve RC tasks"))
pq.push(Task(priority: 2, name: "Tax return"))
 
while pq.count != 0 {
print(pq.pop())
}</syntaxhighlight>
 
{{out}}
<pre>
1, Solve RC tasks
2, Tax return
3, Clear drains
4, Feed cat
5, Make tea
</pre>
 
=={{header|Tcl}}==
{{tcllib|struct::prioqueue}}
<langsyntaxhighlight lang="tcl">package require struct::prioqueue
 
set pq [struct::prioqueue]
Line 929 ⟶ 8,455:
# Remove the front-most item from the priority queue
puts [$pq get]
}</langsyntaxhighlight>
Which produces this output:
<pre>
Line 937 ⟶ 8,463:
Tax return
Solve RC tasks
</pre>
 
=={{header|uBasic/4tH}}==
This implementation inserts items using a binary search. Hence, no sorting is required, since all entries are always in order of priority. It also allows for listing of valid entries.
<syntaxhighlight lang="text">b = -1 ' b points to last entry on the queue
 
q = FUNC(_Grab) ' now grab the top value
' and display it
Print Peek(q, 0) - Ord("0"), Show(Chop(q, 1))
Print
 
Proc _Insert(3, "Clear drains") ' insert the whole bunch
Proc _Insert(4, "Feed cat")
Proc _Insert(5, "Make tea")
Proc _Insert(1, "Solve RC tasks")
Proc _Insert(2, "Tax return")
 
For x = 0 To b: Proc _List(x) : Next ' list all entries
 
q = FUNC(_Grab) ' now grab the top value
 
Print ' and display it
Print Peek(q, 0) - Ord("0"), Show(Chop(q, 1))
Print
 
For x = 0 To b: Proc _List(x) : Next ' list all entries
End
 
_Grab ' return and remove top entry
Local (2)
' return dummy on error
If b < 0 Then Return ("0No such entry")
a@ = @(0)) ' save the top entry
For b@ = 0 To Set(b, b - 1) : @(b@) = @(b@+1): Next
Return (a@)
 
_List ' list any (valid) position on queue
Param (1)
If (a@ > b) = 0 Then Print Peek(@(a@), 0) - Ord("0"), Show(Chop(@(a@), 1))
Return
 
_Insert ' insert an entry
Param (2) ' priority, task
Local (1)
c@ = FUNC(_binarySearch(a@, 0, b)) ' search the position
Proc _MakeRoom (c@) ' make room
@(c@) = Join(Str(a@), b@) ' assign the entry
Return
 
_binarySearch ' perform a binary search
Param(3) ' value, start index, end index
Local(1) ' The middle of the array
' Ok, signal we didn't find it
If c@ < b@ Then Return (b@) ' first entry on start
 
d@ = SHL(b@ + c@, -1) ' prevent overflow (LOL!)
If a@ < Peek(@(d@), 0) - Ord("0") Then Return (FUNC(_binarySearch (a@, b@, d@-1)))
If a@ > Peek(@(d@), 0) - Ord("0") Then Return (FUNC(_binarySearch (a@, d@+1, c@)))
If a@ = Peek(@(d@), 0) - Ord("0") Then Return (d@)
Return (-1) ' -1 on error
 
_MakeRoom ' make some space
Param (1) ' starting position
Local (1)
' from bottom to top
For b@ = Set(b, b+1) To a@ + 1 Step -1: @(b@) = @(b@-1) : Next
Return
</syntaxhighlight>
{{Out}}
First an entry is dequeued from an empty queue. Then all entries are inserted and listed. Finally, another entry is dequeued and the remainder of the entries is listed again.
<pre>0 No such entry
 
1 Solve RC tasks
2 Tax return
3 Clear drains
4 Feed cat
5 Make tea
 
1 Solve RC tasks
 
2 Tax return
3 Clear drains
4 Feed cat
5 Make tea
 
0 OK, 0:750
</pre>
 
=={{header|VBA}}==
<syntaxhighlight lang="vb">Type Tuple
Priority As Integer
Data As String
End Type
Dim a() As Tuple
Dim n As Integer 'number of elements in array, last element is n-1
Private Function Left(i As Integer) As Integer
Left = 2 * i + 1
End Function
Private Function Right(i As Integer) As Integer
Right = 2 * i + 2
End Function
Private Function Parent(i As Integer) As Integer
Parent = (i - 1) \ 2
End Function
Private Sub Add(fPriority As Integer, fData As String)
n = n + 1
If n > UBound(a) Then ReDim Preserve a(2 * n)
a(n - 1).Priority = fPriority
a(n - 1).Data = fData
bubbleUp (n - 1)
End Sub
Private Sub Swap(i As Integer, j As Integer)
Dim t As Tuple
t = a(i)
a(i) = a(j)
a(j) = t
End Sub
Private Sub bubbleUp(i As Integer)
Dim p As Integer
p = Parent(i)
Do While i > 0 And a(i).Priority < a(p).Priority
Swap i, p
i = p
p = Parent(i)
Loop
End Sub
Private Function Remove() As Tuple
Dim x As Tuple
x = a(0)
a(0) = a(n - 1)
n = n - 1
trickleDown 0
If 3 * n < UBound(a) Then ReDim Preserve a(UBound(a) \ 2)
Remove = x
End Function
Private Sub trickleDown(i As Integer)
Dim j As Integer, l As Integer, r As Integer
Do
j = -1
r = Right(i)
If r < n And a(r).Priority < a(i).Priority Then
l = Left(i)
If a(l).Priority < a(r).Priority Then
j = l
Else
j = r
End If
Else
l = Left(i)
If l < n And a(l).Priority < a(i).Priority Then j = l
End If
If j >= 0 Then Swap i, j
i = j
Loop While i >= 0
End Sub
Public Sub PQ()
ReDim a(4)
Add 3, "Clear drains"
Add 4, "Feed cat"
Add 5, "Make tea"
Add 1, "Solve RC tasks"
Add 2, "Tax return"
Dim t As Tuple
Do While n > 0
t = Remove
Debug.Print t.Priority, t.Data
Loop
End Sub</syntaxhighlight>{{out}}<pre>1 Solve RC tasks
2 Tax return
3 Clear drains
4 Feed cat
5 Make tea
</pre>
 
=={{header|VBScript}}==
I wrote this priority queue in a class. It uses a dynamic array to implement the class. Function out_of_order must be adapted to the data. Run it with CScript.
<syntaxhighlight lang="vb">
option explicit
Class prio_queue
private size
private q
'adapt this function to your data
private function out_of_order(f1,f2): out_of_order = f1(0)>f2(0):end function
function peek
peek=q(1)
end function
property get qty
qty=size
end property
 
property get isempty
isempty=(size=0)
end property
function remove
dim x
x=q(1)
q(1)=q(size)
size=size-1
sift_down
remove=x
end function
sub add (x)
size=size+1
if size>ubound(q) then redim preserve q(ubound(q)*1.1)
q(size)=x
sift_up
end sub
Private sub swap (i,j)
dim x
x=q(i):q(i)=q(j):q(j)=x
end sub
private sub sift_up
dim h,p
h=size
p=h\2
if p=0 then exit sub
while out_of_order(q(p),q(h))
swap h,p
h=p
p=h\2
if p=0 then exit sub
wend
end sub
end sub
private sub sift_down
dim p,h
p=1
do
if p>=size then exit do
h =p*2
if h >size then exit do
if h+1<=size then if out_of_order(q(h),q(h+1)) then h=h+1
if out_of_order(q(p),q(h)) then swap h,p
p=h
loop
end sub
'Al instanciar objeto con New
Private Sub Class_Initialize( )
redim q(100)
size=0
End Sub
 
'When Object is Set to Nothing
Private Sub Class_Terminate( )
erase q
End Sub
End Class
'-------------------------------------
'test program
'---------------------------------
dim tasks:tasks=array(_
array(3,"Clear drains"),_
array(4,"Feed cat"),_
array(5,"Make tea"),_
array(1,"Solve RC tasks"),_
array(2,"Tax return"))
 
dim queue,i,x
set queue=new prio_queue
for i=0 to ubound(tasks)
queue.add(tasks(i))
next
 
wscript.echo "Done: " & queue.qty() &" items in queue. "& queue.peek()(1)& " is at the top." & vbcrlf
 
while not queue.isempty()
x=queue.remove()
wscript.echo x(0),x(1)
wend
set queue= nothing
 
</syntaxhighlight>
Output:
<pre>
Done: 5 items in queue. Item Solve RC tasks is at the top.
 
1 Solve RC tasks
2 Tax return
3 Clear drains
4 Feed cat
5 Make tea
</pre>
 
=={{header|Wren}}==
{{libheader|Wren-queue}}
The above module contains a PriorityQueue class. Unlike some other languages here, the higher the number, the higher the priority. So the 'Make tea' task has the highest priority and, thankfully, the cat has a good chance of being fed!
<syntaxhighlight lang="wren">import "./queue" for PriorityQueue
 
var tasks = PriorityQueue.new()
tasks.push("Clear drains", 3)
tasks.push("Feed cat", 4)
tasks.push("Make tea", 5)
tasks.push("Solve RC tasks", 1)
tasks.push("Tax return", 2)
while (!tasks.isEmpty) {
var t = tasks.pop()
System.print(t)
}</syntaxhighlight>
 
{{out}}
<pre>
[Make tea, 5]
[Feed cat, 4]
[Clear drains, 3]
[Tax return, 2]
[Solve RC tasks, 1]
</pre>
 
=={{header|XLISP}}==
 
It does not seem necessary that <i>every</i> queue should support arbitrarily many distinct priority levels, so long as <i>each particular</i> queue supports as many levels as the user anticipates needing. We therefore store a priority queue as a fixed-length vector of queues and allow the user to pass the least urgent level needed (counting from 0 as the most urgent) as a parameter when a new priority queue is instantiated.
 
A vector can be efficiently indexed into, and we can eliminate a lot of searching by providing for each priority queue to know its most urgent priority level at any given time. The <code>'POP</code> method can then return the first item stored at that level, without needing to search. If this operation leaves that level empty, however, it does need to search for the next non-empty level. The worst case would be popping from a queue that contained only one item, at the most urgent priority level: the program would have to search down all the levels looking for one that wasn't empty. In the nature of a priority queue, however, this case is probably unusual.
 
The <code>'PUSH</code> method never needs to search down the levels. The efficiency bottleneck here is probably the implementation of <code>NCONC</code> (used for adding the new item to the end of the queue at the relevant level). A priority <i>stack</i>, with first in / last out at each priority level rather than first in / first out, would be faster.
 
<syntaxhighlight lang="lisp">(define-class priority-queue
(instance-variables queue lowest-priority most-urgent) )
 
(define-method (priority-queue 'initialize limit)
(defun setup (x)
(vector-set! queue x nil)
(if (< x limit)
(setup (+ x 1)) ) )
(setq lowest-priority limit)
(setq most-urgent limit)
(setq queue (make-vector (+ limit 1)))
(setup 0)
self )
 
(define-method (priority-queue 'push item priority)
(if (and (integerp priority) (>= priority 0) (<= priority lowest-priority))
(progn
(setq most-urgent (min priority most-urgent))
(vector-set! queue priority (nconc (vector-ref queue priority) (cons item nil))) ) ) )
 
(define-method (priority-queue 'pop)
(defun find-next (q)
(if (or (= q lowest-priority) (not (null (vector-ref queue q))))
q
(find-next (+ q 1)) ) )
(define item (car (vector-ref queue most-urgent)))
(vector-set! queue most-urgent (cdr (vector-ref queue most-urgent)))
(setq most-urgent (find-next most-urgent))
item )
 
(define-method (priority-queue 'peek)
(car (vector-ref queue most-urgent)) )
 
(define-method (priority-queue 'emptyp)
(and (= most-urgent lowest-priority) (null (vector-ref queue most-urgent))) )</syntaxhighlight>
 
The example uses strings, but the data items stored in the priority queue can be of any type (including the empty list—or even other priority queues).
<syntaxhighlight lang="lisp">(define pq (priority-queue 'new 5))
 
(pq 'push "Clear drains" 3)
(pq 'push "Feed cat" 4)
(pq 'push "Make tea" 5)
(pq 'push "Solve RC tasks" 1)
(pq 'push "Tax return" 2)</syntaxhighlight>
{{out}}
Items are popped beginning from the most urgent:
<syntaxhighlight lang="lisp">[1] (pq 'pop)
 
"Solve RC tasks"
[2] (pq 'pop)
 
"Tax return"</syntaxhighlight>
Within each priority level, new items are pushed onto the end and popped from the beginning of the list (a queue is a first in / first out data structure):
<syntaxhighlight lang="lisp">[3] (pq 'push "Answer emails" 4)
 
("Feed cat" "Answer emails")</syntaxhighlight>
Attempting to push with an invalid priority value returns the empty list, i.e. false:
<syntaxhighlight lang="lisp">[4] (pq 'push "Weed garden" 17)
 
()</syntaxhighlight>
<code>'EMPTYP</code> returns false if the priority queue is not empty:
<syntaxhighlight lang="lisp">[5] (pq 'emptyp)
 
()</syntaxhighlight>
<code>'PEEK</code> non-destructively returns the item that would be popped if you called <code>'POP</code>:
<syntaxhighlight lang="lisp">[6] (pq 'peek)
 
"Clear drains"</syntaxhighlight>
If you want to examine a whole priority queue, the built-in <code>'SHOW</code> method allows you to do so:
<syntaxhighlight lang="scheme">[7] (pq 'show)
 
Object is #<Object:PRIORITY-QUEUE #x4e2cba8>, Class is #<Class:PRIORITY-QUEUE #x4e254c8>
Instance variables:
QUEUE = #(() () () ("Clear drains") ("Feed cat" "Answer emails") ("Make tea"))
LOWEST-PRIORITY = 5
MOST-URGENT = 3
#<Object:PRIORITY-QUEUE #x4e2cba8></syntaxhighlight>
Once all the items have been popped, the priority queue is empty and <code>'EMPTYP</code> then returns true:
<syntaxhighlight lang="lisp">[8] (pq 'pop)
 
"Clear drains"
[9] (pq 'pop)
 
"Feed cat"
[10] (pq 'pop)
 
"Answer emails"
[11] (pq 'pop)
 
"Make tea"
[12] (pq 'emptyp)
 
#T</syntaxhighlight>
Attempting to pop from an empty priority queue returns false:
<syntaxhighlight lang="lisp">[13] (pq 'pop)
 
()</syntaxhighlight>
 
=={{header|XPL0}}==
The highest priority item is the one with the minimum number, as in 1st priority.
<syntaxhighlight lang "XPL0">def PQSize = 10; \Maximum number of items priority queue can hold
int PQ(PQSize*2), PQI;
 
func Remove; \Remove and return item with highest priority
int Min, I, MinI, Item;
[if PQI <= 0 then return 0;
Min:= -1>>1; I:= PQI;
while I > 0 do
[I:= I-2;
if PQ(I) < Min then
[Min:= PQ(I);
MinI:= I;
];
];
Item:= PQ(MinI+1); \get highest priority Item
PQI:= PQI-2;
PQ(MinI):= PQ(PQI); \replace that Item with last item
PQ(MinI+1):= PQ(PQI+1);
return Item;
];
 
proc Insert(Priority, Item); \Insert item into priority queue
int Priority, Item;
[if PQI >= PQSize*2 then return;
PQ(PQI):= Priority;
PQ(PQI+1):= Item;
PQI:= PQI+2;
];
 
int Items, I;
[Items:= [
[3, "Clear drains"],
[4, "Feed cat"],
[5, "Make tea"],
[1, "Solve RC tasks"],
[2, "Tax return"] ];
PQI:= 0;
for I:= 0 to 5-1 do
Insert(Items(I,0), Items(I,1));
while PQI > 0 do
[Text(0, Remove); CrLf(0)];
]</syntaxhighlight>
{{out}}
<pre>
Solve RC tasks
Tax return
Clear drains
Feed cat
Make tea
</pre>
 
=={{header|Zig}}==
 
Zig's standard library has a built-in implementation of the Priority Queue data structure.
 
Save the following code as <code>priority_queue.zig</code>, and run the tests using <code>zig test priority_queue.zig</code>.
 
<syntaxhighlight lang="zig">
const std = @import("std");
const PriorityQueue = std.PriorityQueue;
const Allocator = std.mem.Allocator;
const testing = std.testing;
 
/// wrapper for the task - stores task priority
/// along with the task name
const Task = struct {
const Self = @This();
 
priority: i32,
name: []const u8,
 
pub fn init(priority: i32, name: []const u8) Self {
return Self{
.priority = priority,
.name = name,
};
}
};
 
/// Simple wrapper for the comparator function.
/// Each comparator function has the following signature:
///
/// fn(T, T) bool
const Comparator = struct {
fn maxCompare(_: void, a: Task, b: Task) std.math.Order {
return std.math.order(a.priority, b.priority);
}
 
fn minCompare(_: void, a: Task, b: Task) std.math.Order {
return std.math.order(a.priority, b.priority);
}
};
 
test "priority queue (max heap)" {
var arena = std.heap.ArenaAllocator.init(std.heap.page_allocator);
defer arena.deinit();
const allocator = arena.allocator();
var pq = PriorityQueue(Task, void, Comparator.maxCompare).init(allocator, {});
defer pq.deinit();
 
try pq.add(Task.init(3, "Clear drains"));
try pq.add(Task.init(4, "Feed Cat"));
try pq.add(Task.init(5, "Make tea"));
try pq.add(Task.init(1, "Solve RC tasks"));
try pq.add(Task.init(2, "Tax returns"));
try testing.expectEqual(pq.count(), 5);
 
std.debug.print("\n", .{});
 
// execute the tasks in decreasing order of priority
while (pq.count() != 0) {
const task = pq.remove();
std.debug.print("Executing: {s} (priority {d})\n", .{ task.name, task.priority });
}
std.debug.print("\n", .{});
}
 
test "priority queue (min heap)" {
var arena = std.heap.ArenaAllocator.init(std.heap.page_allocator);
defer arena.deinit();
const allocator = arena.allocator();
var pq = PriorityQueue(Task, void, Comparator.minCompare).init(allocator, {});
defer pq.deinit();
 
try pq.add(Task.init(3, "Clear drains"));
try pq.add(Task.init(4, "Feed Cat"));
try pq.add(Task.init(5, "Make tea"));
try pq.add(Task.init(1, "Solve RC tasks"));
try pq.add(Task.init(2, "Tax returns"));
try testing.expectEqual(pq.count(), 5);
 
std.debug.print("\n", .{});
 
// execute the tasks in increasing order of priority
while (pq.count() != 0) {
const task = pq.remove();
std.debug.print("Executing: {s} (priority {d})\n", .{ task.name, task.priority });
}
std.debug.print("\n", .{});
}
</syntaxhighlight>
 
Sample output:
 
<syntaxhighlight lang="zig">
$ zig test priority_queue.zig
Test [1/2] test "priority queue (max heap)"...
Executing: Make tea (priority 5)
Executing: Feed Cat (priority 4)
Executing: Clear drains (priority 3)
Executing: Tax returns (priority 2)
Executing: Solve RC tasks (priority 1)
 
Test [2/2] test "priority queue (min heap)"...
Executing: Solve RC tasks (priority 1)
Executing: Tax returns (priority 2)
Executing: Clear drains (priority 3)
Executing: Feed Cat (priority 4)
Executing: Make tea (priority 5)
 
All 2 tests passed.
</syntaxhighlight>
 
=={{header|zkl}}==
This solution uses a [hopefully small] fixed number of priorities, each of which has an unordered list of tasks. This allows O(1) insertions, O(p) for retrievals (p is the number of priorities).
<syntaxhighlight lang="zkl">class PQ{
fcn init(numLevels=10){ // 0..numLevels, bigger # == lower priorty
var [const] queue=(1).pump(numLevels+1,List.createLong(numLevels).write,L().copy);
}
fcn add(item,priorty){ queue[priorty].append(item); }
fcn peek{ if(q:=queue.filter1()) return(q[-1]); Void }// -->Void if empty
fcn pop { if(q:=queue.filter1()) return(q.pop()); Void }// -->Void if empty
var [private] state=L();
fcn [private] next{ // iterate
qi,ii:=state;
foreach n in ([qi..queue.len()-1]){
q:=queue[n];
if(ii>=q.len()) ii=0;
else{ state.clear().append(n,ii+1); return(q[ii]) }
}
Void.Stop
}
fcn walker{ state.clear().append(0,0); Walker(next) } // iterator front end
fcn toString{ "PQ(%d) items".fmt(queue.reduce(fcn(sum,q){ sum+q.len() },0)) }
}</syntaxhighlight>
<syntaxhighlight lang="zkl">pq:=PQ();
foreach x in
(T("Clear drains",3, "Feed cat",4, "Make tea",5, "Solve RC tasks",1, "Tax return",2,
"Clean room",10,"Wash cat",10)){
pq.add(x,__xWalker.next())
}
pq.println();
println("Number 1 thing to do: ",pq.peek());
println("Top 2 things to do: ",pq.walker().walk(2));
println("Do this next year: ",pq.walker().walk()[-1]);
println("ToDo list:");
foreach item in (pq){ item.println() }
pq.println();</syntaxhighlight>
{{out}}
<pre>
PQ(7) items
Number 1 thing to do: Solve RC tasks
Top 2 things to do: L("Solve RC tasks","Tax return")
Do this next year: Wash cat
ToDo list:
Solve RC tasks
Tax return
Clear drains
Feed cat
Make tea
Clean room
Wash cat
PQ(7) items
</pre>