data-structure-typed/README.md

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Data Structure Typed

NPM GitHub top language npm eslint npm package minimized gzipped size (select exports) npm bundle size npm

Data Structures of Javascript & TypeScript.

Do you envy C++ with STL, Python with collections, and Java with java.util ? Well, no need to envy anymore! JavaScript and TypeScript now have data-structure-typed.

Now you can use this library in Node.js and browser environments in CommonJS(require export.modules = ), ESModule(import export), Typescript(import export), UMD(var Queue = dataStructureTyped.Queue)

Built-in classic algorithms

DFS(Depth-First Search), DFSIterative, BFS(Breadth-First Search), morris, Bellman-Ford Algorithm, Dijkstra's Algorithm, Floyd-Warshall Algorithm, Tarjan's Algorithm.

Installation and Usage

npm

npm i data-structure-typed --save

yarn

yarn add data-structure-typed
import {
  BinaryTree, Graph, Queue, Stack, PriorityQueue, BST, Trie, DoublyLinkedList,
  AVLTree, MinHeap, SinglyLinkedList, DirectedGraph, TreeMultiset,
  DirectedVertex, AVLTreeNode
} from 'data-structure-typed';

CDN


<script src='https://cdn.jsdelivr.net/npm/data-structure-typed/dist/umd/data-structure-typed.min.js'></script>
const {Heap} = dataStructureTyped;
const {
  BinaryTree, Graph, Queue, Stack, PriorityQueue, BST, Trie, DoublyLinkedList,
  AVLTree, MinHeap, SinglyLinkedList, DirectedGraph, TreeMultiset,
  DirectedVertex, AVLTreeNode
} = dataStructureTyped;

API docs & Examples

API Docs

Live Examples

Examples Repository

Code Snippet

Binary Search Tree (BST) snippet

TS

import {BST, BSTNode} from 'data-structure-typed';

const bst = new BST();
bst.add(11);
bst.add(3);
bst.addMany([15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5]);
bst.size === 16;                // true
bst.has(6);                     // true
const node6 = bst.get(6);       // BSTNode
bst.getHeight(6) === 2;         // true
bst.getHeight() === 5;          // true
bst.getDepth(6) === 3;          // true

bst.getLeftMost()?.id === 1;    // true

bst.delete(6);
bst.get(6);                     // null
bst.isAVLBalanced();            // true
bst.bfs()[0] === 11;            // true

const objBST = new BST<BSTNode<{id: number, keyA: number}>>();
objBST.add(11, {id: 11, keyA: 11});
objBST.add(3, {id: 3, keyA: 3});

objBST.addMany([{id: 15, keyA: 15}, {id: 1, keyA: 1}, {id: 8, keyA: 8},
  {id: 13, keyA: 13}, {id: 16, keyA: 16}, {id: 2, keyA: 2},
  {id: 6, keyA: 6}, {id: 9, keyA: 9}, {id: 12, keyA: 12},
  {id: 14, keyA: 14}, {id: 4, keyA: 4}, {id: 7, keyA: 7},
  {id: 10, keyA: 10}, {id: 5, keyA: 5}]);

objBST.delete(11);

JS

const {BST, BSTNode} = require('data-structure-typed');

const bst = new BST();
bst.add(11);
bst.add(3);
bst.addMany([15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5]);
bst.size === 16;        // true
bst.has(6);             // true
const node6 = bst.get(6);
bst.getHeight(6) === 2; // true
bst.getHeight() === 5;  // true
bst.getDepth(6) === 3;  // true
const leftMost = bst.getLeftMost();
leftMost?.id === 1;     // true
expect(leftMost?.id).toBe(1);
bst.delete(6);
bst.get(6);             // null
bst.isAVLBalanced();    // true or false
const bfsIDs = bst.bfs();
bfsIDs[0] === 11;       // true
expect(bfsIDs[0]).toBe(11);

const objBST = new BST();
objBST.add(11, {id: 11, keyA: 11});
objBST.add(3, {id: 3, keyA: 3});

objBST.addMany([{id: 15, keyA: 15}, {id: 1, keyA: 1}, {id: 8, keyA: 8},
  {id: 13, keyA: 13}, {id: 16, keyA: 16}, {id: 2, keyA: 2},
  {id: 6, keyA: 6}, {id: 9, keyA: 9}, {id: 12, keyA: 12},
  {id: 14, keyA: 14}, {id: 4, keyA: 4}, {id: 7, keyA: 7},
  {id: 10, keyA: 10}, {id: 5, keyA: 5}]);

objBST.delete(11);

const avlTree = new AVLTree();
avlTree.addMany([11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5])
avlTree.isAVLBalanced();    // true
avlTree.delete(10);
avlTree.isAVLBalanced();    // true

AVLTree snippet

TS

import {AVLTree} from 'data-structure-typed';

const avlTree = new AVLTree();
avlTree.addMany([11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5])
avlTree.isAVLBalanced();    // true
avlTree.delete(10);
avlTree.isAVLBalanced();    // true

JS

const {AVLTree} = require('data-structure-typed');

const avlTree = new AVLTree();
avlTree.addMany([11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5])
avlTree.isAVLBalanced();    // true
avlTree.delete(10);
avlTree.isAVLBalanced();    // true

Directed Graph simple snippet

TS or JS

import {DirectedGraph} from 'data-structure-typed';

const graph = new DirectedGraph();

graph.addVertex('A');
graph.addVertex('B');

graph.hasVertex('A');       // true
graph.hasVertex('B');       // true
graph.hasVertex('C');       // false

graph.addEdge('A', 'B');
graph.hasEdge('A', 'B');    // true
graph.hasEdge('B', 'A');    // false

graph.deleteEdgeSrcToDest('A', 'B');
graph.hasEdge('A', 'B');    // false

graph.addVertex('C');

graph.addEdge('A', 'B');
graph.addEdge('B', 'C');

const topologicalOrderIds = graph.topologicalSort(); // ['A', 'B', 'C']

Undirected Graph snippet

TS or JS

import {UndirectedGraph} from 'data-structure-typed';

const graph = new UndirectedGraph();
graph.addVertex('A');
graph.addVertex('B');
graph.addVertex('C');
graph.addVertex('D');
graph.deleteVertex('C');
graph.addEdge('A', 'B');
graph.addEdge('B', 'D');

const dijkstraResult = graph.dijkstra('A');
Array.from(dijkstraResult?.seen ?? []).map(vertex => vertex.id) // ['A', 'B', 'D']

Data Structures

Data Structure Unit Test Performance Test API Documentation Implemented
Binary Tree Binary Tree
Binary Search Tree (BST) BST
AVL Tree AVLTree
Red Black Tree AVLTree
Tree Multiset TreeMultiset
Segment Tree SegmentTree
Binary Indexed Tree BinaryIndexedTree
Graph AbstractGraph
Directed Graph DirectedGraph
Undirected Graph UndirectedGraph
Linked List SinglyLinkedList
Singly Linked List SinglyLinkedList
Doubly Linked List DoublyLinkedList
Queue Queue
Object Deque ObjectDeque
Array Deque ArrayDeque
Stack Stack
Coordinate Set CoordinateSet
Coordinate Map CoordinateMap
Heap Heap
Priority Queue PriorityQueue
Max Priority Queue MaxPriorityQueue
Min Priority Queue MinPriorityQueue
Trie Trie

Standard library data structure comparison

Data Structure Typed C++ STL java.util Python collections
Array<E> vector<T> ArrayList<E> list
DoublyLinkedList<E> list<T> LinkedList<E> deque
SinglyLinkedList<E> - - -
Set<E> set<T> HashSet<E> set
Map<K, V> map<K, V> HashMap<K, V> dict
Map<K, V> - - OrderedDict
Queue<E> queue<T> Queue<E> -
PriorityQueue<E> priority_queue<T> PriorityQueue<E> -
Heap<V> priority_queue<T> PriorityQueue<E> heapq
Stack<E> stack<T> Stack<E> -
Deque<E> deque<T> - -
Trie - - -
HashMap<K, V> unordered_map<K, V> HashMap<K, V> defaultdict
- multiset<T> - -
- multimap<K, V> - -
BinaryTree<K, V> - - -
BST<K, V> - - -
DirectedGraph<V, E> - - -
UndirectedGraph<V, E> - - -
- unordered_multiset - Counter
- - LinkedHashSet<E> -
- - LinkedHashMap<K, V> -
AVLTree<E> - TreeSet<E> -
AVLTree<K, V> - TreeMap<K, V> -
AVLTree<E> set TreeSet<E> -
- unordered_multimap<K, V> - -
- bitset<N> - -
- unordered_set<T> HashSet<E> -

Code design

Adhere to ES6 standard naming conventions for APIs.

Standardize API conventions by using 'add' and 'delete' for element manipulation methods in all data structures.

Opt for concise and clear method names, avoiding excessive length while ensuring explicit intent.

Object-oriented programming(OOP)

By strictly adhering to object-oriented design (BinaryTree -> BST -> AVLTree -> TreeMultiset), you can seamlessly inherit the existing data structures to implement the customized ones you need. Object-oriented design stands as the optimal approach to data structure design.

Benchmark

avl-tree
test nametime taken (ms)executions per secsample deviation
10,000 add randomly30.3332.973.56e-4
10,000 add & delete randomly66.1015.130.00
10,000 addMany39.4425.353.62e-4
10,000 get27.0636.962.52e-4
binary-tree
test nametime taken (ms)executions per secsample deviation
1,000 add randomly12.9077.521.09e-4
1,000 add & delete randomly16.1361.991.61e-4
1,000 addMany10.7493.091.00e-4
1,000 get18.0955.281.90e-4
1,000 dfs71.1214.067.83e-4
1,000 bfs57.2417.474.17e-4
1,000 morris37.2926.813.77e-4
bst
test nametime taken (ms)executions per secsample deviation
10,000 add randomly31.5831.670.00
10,000 add & delete randomly71.0914.078.99e-4
10,000 addMany29.6833.690.00
10,000 get28.5535.030.00
rb-tree
test nametime taken (ms)executions per secsample deviation
100,000 add randomly84.6411.820.01
100,000 add & 1000 delete randomly81.3212.300.01
100,000 getNode61.1816.350.00
directed-graph
test nametime taken (ms)executions per secsample deviation
1,000 addVertex0.109637.473.79e-6
1,000 addEdge6.09164.181.31e-4
1,000 getVertex0.052.14e+41.35e-6
1,000 getEdge23.9141.820.01
tarjan218.654.570.01
tarjan all221.674.510.00
topologicalSort184.345.420.02
heap
test nametime taken (ms)executions per secsample deviation
10,000 add & pop4.63215.774.49e-5
10,000 fib add & pop355.192.820.00
doubly-linked-list
test nametime taken (ms)executions per secsample deviation
1,000,000 unshift213.534.680.02
1,000,000 unshift & shift162.976.140.02
1,000,000 insertBefore335.192.980.09
singly-linked-list
test nametime taken (ms)executions per secsample deviation
10,000 push & pop231.354.320.02
10,000 insertBefore251.493.980.01
max-priority-queue
test nametime taken (ms)executions per secsample deviation
10,000 refill & poll11.4887.141.91e-4
deque
test nametime taken (ms)executions per secsample deviation
1,000,000 push215.144.650.05
1,000,000 shift25.1539.760.00
queue
test nametime taken (ms)executions per secsample deviation
1,000,000 push44.1522.650.01
1,000,000 push & shift80.8712.370.00
trie
test nametime taken (ms)executions per secsample deviation
100,000 push61.3816.290.01
100,000 getWords104.279.590.02