Data Structure Typed: Optimize JavaScript Structures

Data-structure-typed


Why

Do you envy C++ with STL (std::), Python with collections, and Java with java.util ? Well, no need to envy anymore! JavaScript and TypeScript now have data-structure-typed.Benchmark compared with C++ STL. API standards aligned with ES6 and Java. Usability is comparable to Python

We provide data structures that are not available in JS/TS

Heap, Binary Tree, RedBlack Tree, Linked List, Deque, Trie, Directed Graph, Undirected Graph, BST, AVL Tree, Priority Queue, Queue, Tree Multiset, Linked List.

Performance surpasses that of native JS/TS

MethodTime Taken (ms)ScaleBelongs To
Queue.push & shift5.83100,000data-structure-typed
Array.push & shift2829.59100,000Native JS
Deque.unshift & shift2.44100,000data-structure-typed
Array.unshift & shift4750.37100,000Native JS
HashMap.set122.511,000,000data-structure-typed
Map.set223.801,000,000Native JS
Set.add185.061,000,000Native JS

Installation and Usage

Now you can use it in Node.js and browser environments

CommonJS:require export.modules =

ESModule:   import export

Typescript:   import export

UMD:           var Deque = dataStructureTyped.Deque

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, TreeMultimap,
  DirectedVertex, AVLTreeNode
} from 'data-structure-typed';

CDN

Copy the line below into the head tag in an HTML document.

development

<script src='https://cdn.jsdelivr.net/npm/data-structure-typed/dist/umd/data-structure-typed.js'></script>

production

<script src='https://cdn.jsdelivr.net/npm/data-structure-typed/dist/umd/data-structure-typed.min.js'></script>

Copy the code below into the script tag of your HTML, and you're good to go with your development.

const {Heap} = dataStructureTyped;
const {
  BinaryTree, Graph, Queue, Stack, PriorityQueue, BST, Trie, DoublyLinkedList,
  AVLTree, MinHeap, SinglyLinkedList, DirectedGraph, TreeMultimap,
  DirectedVertex, AVLTreeNode
} = dataStructureTyped;

Vivid Examples

Binary Tree

Try it out, or you can run your own code using our visual tool

Binary Tree DFS

Try it out

AVL Tree

Try it out

Tree Multi Map

Try it out

Matrix

Try it out

Directed Graph

Try it out

Map Graph

Try it out

Code Snippets

Binary Search Tree (BST) snippet

TS

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

const bst = new BST<number>();
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.getNode(6);   // BSTNode
bst.getHeight(6) === 2;         // true
bst.getHeight() === 5;          // true
bst.getDepth(6) === 3;          // true

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

bst.delete(6);
bst.get(6);                     // undefined
bst.isAVLBalanced();            // true
bst.bfs()[0] === 11;            // true
bst.print()
//       ______________11_____           
//      /                     \          
//   ___3_______            _13_____
//  /           \          /        \    
//  1_     _____8____     12      _15__
//    \   /          \           /     \ 
//    2   4_       _10          14    16
//          \     /                      
//          5_    9
//            \                          
//            7

const objBST = new BST<number, {height: number, age: number}>();

objBST.add(11, { "name": "Pablo", "age": 15 });
objBST.add(3, { "name": "Kirk", "age": 1 });

objBST.addMany([15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5], [
    { "name": "Alice", "age": 15 },
    { "name": "Bob", "age": 1 },
    { "name": "Charlie", "age": 8 },
    { "name": "David", "age": 13 },
    { "name": "Emma", "age": 16 },
    { "name": "Frank", "age": 2 },
    { "name": "Grace", "age": 6 },
    { "name": "Hannah", "age": 9 },
    { "name": "Isaac", "age": 12 },
    { "name": "Jack", "age": 14 },
    { "name": "Katie", "age": 4 },
    { "name": "Liam", "age": 7 },
    { "name": "Mia", "age": 10 },
    { "name": "Noah", "age": 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.getNode(6);
bst.getHeight(6) === 2;         // true
bst.getHeight() === 5;          // true
bst.getDepth(6) === 3;          // true
const leftMost = bst.getLeftMost();
leftMost?.key === 1;            // true

bst.delete(6);
bst.get(6);                     // undefined
bst.isAVLBalanced();            // true or false
const bfsIDs = bst.bfs();
bfsIDs[0] === 11;               // true

AVLTree snippet

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

const avlTree = new AVLTree<number>();
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

RedBlackTree snippet

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

const rbTree = new RedBlackTree<number>();
rbTree.addMany([11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5])
rbTree.isAVLBalanced();    // true
rbTree.delete(10);
rbTree.isAVLBalanced();    // true
rbTree.print()
//         ___6________
//        /            \
//      ___4_       ___11________
//     /     \     /             \
//    _2_    5    _8_       ____14__
//   /   \       /   \     /        \
//   1   3       7   9    12__     15__
//                            \        \
//                           13       16

Directed Graph simple snippet

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

const graph = new DirectedGraph<string>();

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

Undirected Graph snippet

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

const graph = new UndirectedGraph<string>();
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.key) // ['A', 'B', 'D']

Free conversion between data structures.

const orgArr = [6, 1, 2, 7, 5, 3, 4, 9, 8];
const orgStrArr = ["trie", "trial", "trick", "trip", "tree", "trend", "triangle", "track", "trace", "transmit"];
const entries = [[6, 6], [1, 1], [2, 2], [7, 7], [5, 5], [3, 3], [4, 4], [9, 9], [8, 8]];

const queue = new Queue(orgArr);
queue.print();      
// [6, 1, 2, 7, 5, 3, 4, 9, 8]

const deque = new Deque(orgArr);
deque.print();      
// [6, 1, 2, 7, 5, 3, 4, 9, 8]

const sList = new SinglyLinkedList(orgArr);
sList.print();      
// [6, 1, 2, 7, 5, 3, 4, 9, 8]

const dList = new DoublyLinkedList(orgArr);
dList.print();      
// [6, 1, 2, 7, 5, 3, 4, 9, 8]

const stack = new Stack(orgArr);
stack.print();      
// [6, 1, 2, 7, 5, 3, 4, 9, 8]

const minHeap = new MinHeap(orgArr);
minHeap.print();    
// [1, 5, 2, 7, 6, 3, 4, 9, 8]

const maxPQ = new MaxPriorityQueue(orgArr);
maxPQ.print();      
// [9, 8, 4, 7, 5, 2, 3, 1, 6]

const biTree = new BinaryTree(entries);
biTree.print();
//         ___6___
//        /       \
//     ___1_     _2_
//    /     \   /   \
//   _7_    5   3   4
//  /   \
//  9   8

const bst = new BST(entries);
bst.print();
//     _____5___
//    /         \
//   _2_       _7_
//  /   \     /   \
//  1   3_    6   8_
//        \         \
//        4         9


const rbTree = new RedBlackTree(entries);
rbTree.print();
//     ___4___
//    /       \
//   _2_     _6___
//  /   \   /     \
//  1   3   5    _8_
//              /   \
//              7   9


const avl = new AVLTree(entries);
avl.print();
//     ___4___
//    /       \
//   _2_     _6___
//  /   \   /     \
//  1   3   5    _8_
//              /   \
//              7   9

const treeMulti = new TreeMultimap(entries);
treeMulti.print();
//     ___4___
//    /       \
//   _2_     _6___
//  /   \   /     \
//  1   3   5    _8_
//              /   \
//              7   9

const hm = new HashMap(entries);
hm.print()    
// [[6, 6], [1, 1], [2, 2], [7, 7], [5, 5], [3, 3], [4, 4], [9, 9], [8, 8]]

const rbTreeH = new RedBlackTree(hm);
rbTreeH.print();
//     ___4___
//    /       \
//   _2_     _6___
//  /   \   /     \
//  1   3   5    _8_
//              /   \
//              7   9

const pq = new MinPriorityQueue(orgArr);
pq.print();   
// [1, 5, 2, 7, 6, 3, 4, 9, 8]

const bst1 = new BST(pq);
bst1.print();
//     _____5___
//    /         \
//   _2_       _7_
//  /   \     /   \
//  1   3_    6   8_
//        \         \
//        4         9

const dq1 = new Deque(orgArr);
dq1.print();    
// [6, 1, 2, 7, 5, 3, 4, 9, 8]
const rbTree1 = new RedBlackTree(dq1);
rbTree1.print();
//    _____5___
//   /         \
//  _2___     _7___
// /     \   /     \
// 1    _4   6    _9
//      /         /
//      3         8


const trie2 = new Trie(orgStrArr);
trie2.print();    
// ['trie', 'trial', 'triangle', 'trick', 'trip', 'tree', 'trend', 'track', 'trace', 'transmit']
const heap2 = new Heap(trie2, { comparator: (a, b) => Number(a) - Number(b) });
heap2.print();    
// ['transmit', 'trace', 'tree', 'trend', 'track', 'trial', 'trip', 'trie', 'trick', 'triangle']
const dq2 = new Deque(heap2);
dq2.print();      
// ['transmit', 'trace', 'tree', 'trend', 'track', 'trial', 'trip', 'trie', 'trick', 'triangle']
const entries2 = dq2.map((el, i) => [i, el]);
const avl2 = new AVLTree(entries2);
avl2.print();
//     ___3_______
//    /           \
//   _1_       ___7_
//  /   \     /     \
//  0   2    _5_    8_
//          /   \     \
//          4   6     9

API docs & Examples

API Docs

Live Examples

Examples Repository

Data Structures

Data StructureUnit TestPerformance TestAPI Docs
Binary TreeView
Binary Search Tree (BST)View
AVL TreeView
Red Black TreeView
Tree MultimapView
HeapView
Priority QueueView
Max Priority QueueView
Min Priority QueueView
TrieView
GraphView
Directed GraphView
Undirected GraphView
QueueView
DequeView
Hash MapView
Linked ListView
Singly Linked ListView
Doubly Linked ListView
StackView
Segment Tree View
Binary Indexed Tree View

Standard library data structure comparison

Data Structure TypedC++ STLjava.utilPython collections
Heap<E>priority_queue<T>PriorityQueue<E>heapq
Deque<E>deque<T>ArrayDeque<E>deque
Queue<E>queue<T>Queue<E>-
HashMap<K, V>unordered_map<K, V>HashMap<K, V>defaultdict
DoublyLinkedList<E>list<T>LinkedList<E>-
SinglyLinkedList<E>---
BinaryTree<K, V>---
BST<K, V>---
RedBlackTree<E>set<T>TreeSet<E>-
RedBlackTree<K, V>map<K, V>TreeMap<K, V>-
TreeMultimap<K, V>multimap<K, V>--
TreeMultimap<E>multiset<T>--
Trie---
DirectedGraph<V, E>---
UndirectedGraph<V, E>---
PriorityQueue<E>priority_queue<T>PriorityQueue<E>-
Array<E>vector<T>ArrayList<E>list
Stack<E>stack<T>Stack<E>-
HashMap<E>unordered_set<T>HashSet<E>set
-unordered_multiset-Counter
LinkedHashMap<K, V>-LinkedHashMap<K, V>OrderedDict
-unordered_multimap<K, V>--
-bitset<N>--

Built-in classic algorithms

AlgorithmFunction DescriptionIteration Type
Binary Tree DFSTraverse a binary tree in a depth-first manner, starting from the root node, first visiting the left subtree, and then the right subtree, using recursion.Recursion + Iteration
Binary Tree BFSTraverse a binary tree in a breadth-first manner, starting from the root node, visiting nodes level by level from left to right.Iteration
Graph DFSTraverse a graph in a depth-first manner, starting from a given node, exploring along one path as deeply as possible, and backtracking to explore other paths. Used for finding connected components, paths, etc.Recursion + Iteration
Binary Tree MorrisMorris traversal is an in-order traversal algorithm for binary trees with O(1) space complexity. It allows tree traversal without additional stack or recursion.Iteration
Graph BFSTraverse a graph in a breadth-first manner, starting from a given node, first visiting nodes directly connected to the starting node, and then expanding level by level. Used for finding shortest paths, etc.Recursion + Iteration
Graph Tarjan's AlgorithmFind strongly connected components in a graph, typically implemented using depth-first search.Recursion
Graph Bellman-Ford AlgorithmFinding the shortest paths from a single source, can handle negative weight edgesIteration
Graph Dijkstra's AlgorithmFinding the shortest paths from a single source, cannot handle negative weight edgesIteration
Graph Floyd-Warshall AlgorithmFinding the shortest paths between all pairs of nodesIteration
Graph getCyclesFind all cycles in a graph or detect the presence of cycles.Recursion
Graph getCutVertexesFind cut vertices in a graph, which are nodes that, when removed, increase the number of connected components in the graph.Recursion
Graph getSCCsFind strongly connected components in a graph, which are subgraphs where any two nodes can reach each other.Recursion
Graph getBridgesFind bridges in a graph, which are edges that, when removed, increase the number of connected components in the graph.Recursion
Graph topologicalSortPerform topological sorting on a directed acyclic graph (DAG) to find a linear order of nodes such that all directed edges go from earlier nodes to later nodes.Recursion

Software Engineering Design Standards

PrincipleDescription
PracticalityFollows ES6 and ESNext standards, offering unified and considerate optional parameters, and simplifies method names.
ExtensibilityAdheres to OOP (Object-Oriented Programming) principles, allowing inheritance for all data structures.
ModularizationIncludes data structure modularization and independent NPM packages.
EfficiencyAll methods provide time and space complexity, comparable to native JS performance.
MaintainabilityFollows open-source community development standards, complete documentation, continuous integration, and adheres to TDD (Test-Driven Development) patterns.
TestabilityAutomated and customized unit testing, performance testing, and integration testing.
PortabilityPlans for porting to Java, Python, and C++, currently achieved to 80%.
ReusabilityFully decoupled, minimized side effects, and adheres to OOP.
SecurityCarefully designed security for member variables and methods. Read-write separation. Data structure software does not need to consider other security aspects.
ScalabilityData structure software does not involve load issues.

Benchmark

avl-tree

test nametime taken (ms)executions per secsample deviation
10,000 add randomly51.2219.520.00
10,000 add & delete randomly110.409.060.00
10,000 addMany58.3917.136.35e-4
10,000 get50.5919.773.87e-4

binary-tree

test nametime taken (ms)executions per secsample deviation
1,000 add randomly13.8372.291.19e-4
1,000 add & delete randomly21.4946.542.34e-4
1,000 addMany15.9362.781.27e-4
1,000 get18.1954.981.79e-4
1,000 has18.2054.931.71e-4
1,000 dfs161.796.187.45e-4
1,000 bfs56.6817.644.77e-4
1,000 morris262.643.810.00

bst

test nametime taken (ms)executions per secsample deviation
10,000 add randomly51.5119.418.70e-4
10,000 add & delete randomly114.098.769.66e-4
10,000 addMany47.8620.902.77e-4
10,000 get51.9319.266.56e-4

rb-tree

test nametime taken (ms)executions per secsample deviation
100,000 add86.6311.540.00
100,000 add & delete randomly218.884.570.01
100,000 getNode261.163.830.00
100,000 add & iterator117.648.500.00

comparison

test nametime taken (ms)executions per secsample deviation
SRC PQ 10,000 add0.146949.201.53e-6
CJS PQ 10,000 add0.146943.681.74e-6
MJS PQ 10,000 add0.571758.406.26e-6
SRC PQ 10,000 add & pop3.40293.943.50e-5
CJS PQ 10,000 add & pop3.42292.695.34e-5
MJS PQ 10,000 add & pop3.30303.013.97e-5

directed-graph

test nametime taken (ms)executions per secsample deviation
1,000 addVertex0.109930.741.11e-6
1,000 addEdge6.13163.191.84e-4
1,000 getVertex0.052.15e+45.00e-7
1,000 getEdge23.5742.430.00
tarjan252.053.970.03
tarjan all221.154.520.00
topologicalSort181.075.520.00

hash-map

test nametime taken (ms)executions per secsample deviation
1,000,000 set122.908.140.04
Native Map 1,000,000 set215.974.630.02
Native Set 1,000,000 add179.115.580.02
1,000,000 set & get123.108.120.04
Native Map 1,000,000 set & get271.803.680.02
Native Set 1,000,000 add & has176.655.660.02
1,000,000 ObjKey set & get341.972.920.07
Native Map 1,000,000 ObjKey set & get316.863.160.04
Native Set 1,000,000 ObjKey add & has285.143.510.06

heap

test nametime taken (ms)executions per secsample deviation
100,000 add & pop80.3712.440.00
100,000 add & dfs36.2027.630.00
10,000 fib add & pop362.242.760.00

doubly-linked-list

test nametime taken (ms)executions per secsample deviation
1,000,000 push216.094.630.06
1,000,000 unshift220.684.530.02
1,000,000 unshift & shift172.935.780.04
1,000,000 insertBefore332.253.010.08

singly-linked-list

test nametime taken (ms)executions per secsample deviation
1,000,000 push & shift222.994.480.10
10,000 push & pop214.824.660.01
10,000 insertBefore251.243.980.01

max-priority-queue

test nametime taken (ms)executions per secsample deviation
10,000 refill & poll8.91112.191.57e-4

priority-queue

test nametime taken (ms)executions per secsample deviation
100,000 add & pop101.709.830.00

deque

test nametime taken (ms)executions per secsample deviation
1,000,000 push13.8072.471.56e-4
1,000,000 push & pop22.7244.022.02e-4
100,000 push & shift2.35425.675.80e-5
Native Array 100,000 push & shift2511.140.400.36
100,000 unshift & shift2.23447.893.30e-4
Native Array 100,000 unshift & shift4140.230.240.33

queue

test nametime taken (ms)executions per secsample deviation
1,000,000 push43.6522.910.01
100,000 push & shift4.99200.289.54e-5
Native Array 100,000 push & shift2335.630.430.33
Native Array 100,000 push & pop4.39227.810.00

stack

test nametime taken (ms)executions per secsample deviation
1,000,000 push45.3822.040.01
1,000,000 push & pop49.5220.190.01

trie

test nametime taken (ms)executions per secsample deviation
100,000 push42.9923.260.00
100,000 getWords89.7811.140.00

English | 简体中文


Download Details:

Author: zrwusa
Source Code: https://github.com/zrwusa/data-structure-typed 
License: MIT license

#javascript #data #type #typescript #graph 

Data Structure Typed: Optimize JavaScript Structures
1.55 GEEK