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Efficient Binary heap (priority queue, binary tree) data structure for JavaScript / TypeScript. Includes JavaScript methods, Python's heapq module methods, and Java's PriorityQueue methods.

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README.md

Heap.js Heap.js

npm version Build Status Coverage Status Dependencies devDependency Status

Efficient Binary heap (priority queue, binary tree) data structure for JavaScript / TypeScript.

Includes JavaScript methods, Python's heapq module methods, and Java's PriorityQueue methods.

Easy to use, known interfaces, tested, and well documented JavaScript binary heap library.

Instances are integer min heap by default.

Open in Gitpod

Is it faster than sorting an array?

It depends on your usage, but for some scenarios it is much faster:

heap vs array: push + pop/unshift 50
	heap  x 72,130 ops/sec ±0.50% (93 runs sampled)
	array x 121 ops/sec ±78.09% (5 runs sampled)

heap vs array: push + peek 20
	heap  x 622,332 ops/sec ±27.93% (63 runs sampled)
	array x 207 ops/sec ±78.18% (5 runs sampled)

heap vs array: push + top(1) of 100
	heap  x 124,835 ops/sec ±40.37% (61 runs sampled)
	array x 123 ops/sec ±78.49% (5 runs sampled)

heap vs array: push + top(50) of 100
	heap  x 59,210 ops/sec ±17.66% (82 runs sampled)
	array x 125 ops/sec ±78.79% (5 runs sampled)

Changelog

2.1

  • Adds Heap.nlargest as heapq.
  • Adds Heap.nsmallest as heapq.
  • Sanitizes top / bottom input to force an integer.
  • Linted with Eslint.

2.0

The main breaking change is that now top(N) does NOT sort the output. It should not be part of the spec for a priority queue, the output should be the top N elements. It will be partially ordered with the peek at index 0 by definition, that is all.

  • top(N) is unordered, only the first element is guaranteed to be the top priority element.
  • Fixes custom heap issue #31.
  • Performance improvements.
  • More tests, including those for custom heaps.
  • Auxiliary experimental topN algorithms.
  • (wip) Benchmarks.

1.5

  • Adds Iterator interface and iterator() method.

Examples

// Basic usage example
import Heap from 'heap-js';

const minHeap = new Heap();
const maxHeap = new Heap(Heap.maxComparator);

minHeap.init([5, 18, 1]);
minHeap.push(2);
console.log(minHeap.peek()); //> 1
console.log(minHeap.pop()); //> 1
console.log(minHeap.peek()); //> 2

// Iterator
maxHeap.init([3, 4, 1, 12, 8]);
for (const value of maxHeap) {
  console.log('Next top value is', value);
}
// Priority Queue usage example
const { Heap } = require('heap-js');

const tasks = db.collection.find().toArray();
const customPriorityComparator = (a, b) => a.priority - b.priority;

const priorityQueue = new Heap(customPriorityComparator);
priorityQueue.init(tasks);

// priorityQueue === priorityQueue.iterator()
for (const task of priorityQueue) {
  // Do something
}
// Python-like static methods example
import { Heap } from 'heap-js';
const numbers = [2, 3, 7, 5];

Heap.heapify(numbers);
console.log(numbers); //> [ 2, 3, 5, 7 ]

Heap.heappush(numbers, 1);
console.log(numbers); //> [ 1, 2, 5, 7, 3 ]

Installation

yarn add heap-js # if you use yarn

npm install --save heap-js # if you use npm

Constructor

new Heap([comparator]);

Basic comparators already included:

  • Heap.minComparator Integer min heap (default)
  • Heap.maxComparator Integer max heap

Implements JavaScript style methods

  • length of the heap
  • limit amount of elements in the heap
  • pop() the top element
  • push(...elements) one or more elements to the heap
  • pushpop(element) faster than push & pop
  • replace(element) faster than pop & push
  • top(number?) most valuable elements from the heap
  • bottom(number?) least valuable elements from the heap

Implements Java's PriorityQueue interface:

  • add(element) to the heap
  • addAll([elment, element, ... ]) to the heap, faster than loop add
  • clear()
  • clone()
  • comparator()
  • contains(element, fn?)
  • element() alias of peek()
  • isEmpty()
  • iterator() returns this because it is iterable
  • offer(element) alias of add(element)
  • peek()
  • poll() alias of pop()
  • remove(element?)
  • removeAll() alias of clear()
  • size() alias of length
  • toArray()
  • toString()

To do:

  • containsAll
  • equals
  • retainAll

Implements static Python's heapq interface:

  • Heap.heapify(array, comparator?) that converts an array to an array-heap
  • Heap.heappop(heapArray, comparator?) that takes the peek of the array-heap
  • Heap.heappush(heapArray, item, comparator?) that appends elements to the array-heap
  • Heap.heappushpop(heapArray, item, comparator?) faster than heappush & heappop
  • Heap.heapreplace(heapArray, item, comparator?) faster than heappop & heappush
  • Heap.nlargest(n, iterable, comparator?) that gets the n most valuable elements of an iterable
  • Heap.nsmallest(n, iterable, comparator?) that gets the n least valuable elements of an iterable

Extras:

  • Heap.heaptop(n, heapArray, comparator?) that returns the n most valuable elements of the array-heap
  • Heap.heapbottom(n, heapArray, comparator?) that returns the n least valuable elements of the array-heap

To do:

  • merge(...iterables, comparator?)

Documentation

Extensive documentation included at ./dist/docs. It'll be published to gh-pages in a next release.

Contributing

Development of Heap.js happens in the open on GitHub, and I am grateful to the community for contributing bugfixes and improvements.

Dev setup

yarn

Tests

npm run test

Benchmarks

npm run benchmarks

License

Heap.js is BSD licensed.

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Efficient Binary heap (priority queue, binary tree) data structure for JavaScript / TypeScript. Includes JavaScript methods, Python's heapq module methods, and Java's PriorityQueue methods.

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