data-structure-typed

Installation and Usage

npm

1npm i data-structure-typed --save

yarn

1yarn add data-structure-typed

1import {
2  Heap, Graph, Queue, Deque, PriorityQueue, BST, Trie, DoublyLinkedList,
3  AVLTree, SinglyLinkedList, DirectedGraph, RedBlackTree, TreeMultiMap,
4  DirectedVertex, Stack, AVLTreeNode
5} from 'data-structure-typed';

If you only want to use a specific data structure independently, you can install it separately, for example, by running

1npm i @teamteanpm2024/similique-ratione-hic --save

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

Performance

Performance surpasses that of native JS/TS

Method	Time Taken	Data Scale	Belongs To	big O
Queue.push & shift	5.83 ms	100K	Ours	O(1)
Array.push & shift	2829.59 ms	100K	Native JS	O(n)
Deque.unshift & shift	2.44 ms	100K	Ours	O(1)
Array.unshift & shift	4750.37 ms	100K	Native JS	O(n)
HashMap.set	122.51 ms	1M	Ours	O(1)
Map.set	223.80 ms	1M	Native JS	O(1)
Set.add	185.06 ms	1M	Native JS	O(1)

Conciseness and uniformity

In java.utils, you need to memorize a table for all sequential data structures(Queue, Deque, LinkedList),

Java ArrayList	Java Queue	Java ArrayDeque	Java LinkedList
add	offer	push	push
remove	poll	removeLast	removeLast
remove	poll	removeFirst	removeFirst
add(0, element)	offerFirst	unshift	unshift

whereas in our data-structure-typed, you only need to remember four methods: push, pop, shift, and unshift for all sequential data structures(Queue, Deque, DoublyLinkedList, SinglyLinkedList and Array).

Data structures available

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

Data Structure	Unit Test	Perf Test	API Doc	NPM	Downloads
Binary Tree			Docs	NPM
Binary Search Tree (BST)			Docs	NPM
AVL Tree			Docs	NPM
Red Black Tree			Docs	NPM
Tree Multimap			Docs	NPM
Heap			Docs	NPM
Priority Queue			Docs	NPM
Max Priority Queue			Docs	NPM
Min Priority Queue			Docs	NPM
Trie			Docs	NPM
Graph			Docs	NPM
Directed Graph			Docs	NPM
Undirected Graph			Docs	NPM
Queue			Docs	NPM
Deque			Docs	NPM
Hash Map			Docs
Linked List			Docs	NPM
Singly Linked List			Docs	NPM
Doubly Linked List			Docs	NPM
Stack			Docs	NPM
Segment Tree			Docs
Binary Indexed Tree			Docs

Vivid Examples

AVL Tree

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

Tree Multi Map

Try it out

Directed Graph

Try it out

Map Graph

Try it out

Code Snippets

Red Black Tree snippet

TS

1import { RedBlackTree } from 'data-structure-typed';
2
3const rbTree = new RedBlackTree<number>();
4rbTree.addMany([11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5])
5rbTree.isAVLBalanced();    // true
6rbTree.delete(10);
7rbTree.isAVLBalanced();    // true
8rbTree.print()
9//         ___6________
10//        /            \
11//      ___4_       ___11________
12//     /     \     /             \
13//    _2_    5    _8_       ____14__
14//   /   \       /   \     /        \
15//   1   3       7   9    12__     15__
16//                            \        \
17//                           13       16

JS

1import { RedBlackTree } from 'data-structure-typed';
2
3const rbTree = new RedBlackTree();
4rbTree.addMany([11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5])
5rbTree.isAVLBalanced();    // true
6rbTree.delete(10);
7rbTree.isAVLBalanced();    // true
8rbTree.print()
9//         ___6________
10//        /            \
11//      ___4_       ___11________
12//     /     \     /             \
13//    _2_    5    _8_       ____14__
14//   /   \       /   \     /        \
15//   1   3       7   9    12__     15__
16//                            \        \
17//                           13       16

Free conversion between data structures.

1const orgArr = [6, 1, 2, 7, 5, 3, 4, 9, 8];
2const orgStrArr = ["trie", "trial", "trick", "trip", "tree", "trend", "triangle", "track", "trace", "transmit"];
3const entries = [[6, "6"], [1, "1"], [2, "2"], [7, "7"], [5, "5"], [3, "3"], [4, "4"], [9, "9"], [8, "8"]];
4
5const queue = new Queue(orgArr);
6queue.print();
7// [6, 1, 2, 7, 5, 3, 4, 9, 8]
8
9const deque = new Deque(orgArr);
10deque.print();
11// [6, 1, 2, 7, 5, 3, 4, 9, 8]
12
13const sList = new SinglyLinkedList(orgArr);
14sList.print();
15// [6, 1, 2, 7, 5, 3, 4, 9, 8]
16
17const dList = new DoublyLinkedList(orgArr);
18dList.print();
19// [6, 1, 2, 7, 5, 3, 4, 9, 8]
20
21const stack = new Stack(orgArr);
22stack.print();
23// [6, 1, 2, 7, 5, 3, 4, 9, 8]
24
25const minHeap = new MinHeap(orgArr);
26minHeap.print();
27// [1, 5, 2, 7, 6, 3, 4, 9, 8]
28
29const maxPQ = new MaxPriorityQueue(orgArr);
30maxPQ.print();
31// [9, 8, 4, 7, 5, 2, 3, 1, 6]
32
33const biTree = new BinaryTree(entries);
34biTree.print();
35//         ___6___
36//        /       \
37//     ___1_     _2_
38//    /     \   /   \
39//   _7_    5   3   4
40//  /   \
41//  9   8
42
43const bst = new BST(entries);
44bst.print();
45//     _____5___
46//    /         \
47//   _2_       _7_
48//  /   \     /   \
49//  1   3_    6   8_
50//        \         \
51//        4         9
52
53
54const rbTree = new RedBlackTree(entries);
55rbTree.print();
56//     ___4___
57//    /       \
58//   _2_     _6___
59//  /   \   /     \
60//  1   3   5    _8_
61//              /   \
62//              7   9
63
64
65const avl = new AVLTree(entries);
66avl.print();
67//     ___4___
68//    /       \
69//   _2_     _6___
70//  /   \   /     \
71//  1   3   5    _8_
72//              /   \
73//              7   9
74
75const treeMulti = new TreeMultiMap(entries);
76treeMulti.print();
77//     ___4___
78//    /       \
79//   _2_     _6___
80//  /   \   /     \
81//  1   3   5    _8_
82//              /   \
83//              7   9
84
85const hm = new HashMap(entries);
86hm.print()
87// [[6, "6"], [1, "1"], [2, "2"], [7, "7"], [5, "5"], [3, "3"], [4, "4"], [9, "9"], [8, "8"]]
88
89const rbTreeH = new RedBlackTree(hm);
90rbTreeH.print();
91//     ___4___
92//    /       \
93//   _2_     _6___
94//  /   \   /     \
95//  1   3   5    _8_
96//              /   \
97//              7   9
98
99const pq = new MinPriorityQueue(orgArr);
100pq.print();
101// [1, 5, 2, 7, 6, 3, 4, 9, 8]
102
103const bst1 = new BST(pq);
104bst1.print();
105//     _____5___
106//    /         \
107//   _2_       _7_
108//  /   \     /   \
109//  1   3_    6   8_
110//        \         \
111//        4         9
112
113const dq1 = new Deque(orgArr);
114dq1.print();
115// [6, 1, 2, 7, 5, 3, 4, 9, 8]
116const rbTree1 = new RedBlackTree(dq1);
117rbTree1.print();
118//    _____5___
119//   /         \
120//  _2___     _7___
121// /     \   /     \
122// 1    _4   6    _9
123//      /         /
124//      3         8
125
126
127const trie2 = new Trie(orgStrArr);
128trie2.print();
129// ['trie', 'trial', 'triangle', 'trick', 'trip', 'tree', 'trend', 'track', 'trace', 'transmit']
130const heap2 = new Heap(trie2, { comparator: (a, b) => Number(a) - Number(b) });
131heap2.print();
132// ['transmit', 'trace', 'tree', 'trend', 'track', 'trial', 'trip', 'trie', 'trick', 'triangle']
133const dq2 = new Deque(heap2);
134dq2.print();
135// ['transmit', 'trace', 'tree', 'trend', 'track', 'trial', 'trip', 'trie', 'trick', 'triangle']
136const entries2 = dq2.map((el, i) => [i, el]);
137const avl2 = new AVLTree(entries2);
138avl2.print();
139//     ___3_______
140//    /           \
141//   _1_       ___7_
142//  /   \     /     \
143//  0   2    _5_    8_
144//          /   \     \
145//          4   6     9

Binary Search Tree (BST) snippet

1import { BST, BSTNode } from 'data-structure-typed';
2
3const bst = new BST<number>();
4bst.add(11);
5bst.add(3);
6bst.addMany([15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5]);
7bst.size === 16;                // true
8bst.has(6);                     // true
9const node6 = bst.getNode(6);   // BSTNode
10bst.getHeight(6) === 2;         // true
11bst.getHeight() === 5;          // true
12bst.getDepth(6) === 3;          // true
13
14bst.getLeftMost()?.key === 1;   // true
15
16bst.delete(6);
17bst.get(6);                     // undefined
18bst.isAVLBalanced();            // true
19bst.bfs()[0] === 11;            // true
20bst.print()
21//       ______________11_____           
22//      /                     \          
23//   ___3_______            _13_____
24//  /           \          /        \    
25//  1_     _____8____     12      _15__
26//    \   /          \           /     \ 
27//    2   4_       _10          14    16
28//          \     /                      
29//          5_    9
30//            \                          
31//            7
32
33const objBST = new BST<number, { height: number, age: number }>();
34
35objBST.add(11, { "name": "Pablo", "age": 15 });
36objBST.add(3, { "name": "Kirk", "age": 1 });
37
38objBST.addMany([15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5], [
39    { "name": "Alice", "age": 15 },
40    { "name": "Bob", "age": 1 },
41    { "name": "Charlie", "age": 8 },
42    { "name": "David", "age": 13 },
43    { "name": "Emma", "age": 16 },
44    { "name": "Frank", "age": 2 },
45    { "name": "Grace", "age": 6 },
46    { "name": "Hannah", "age": 9 },
47    { "name": "Isaac", "age": 12 },
48    { "name": "Jack", "age": 14 },
49    { "name": "Katie", "age": 4 },
50    { "name": "Liam", "age": 7 },
51    { "name": "Mia", "age": 10 },
52    { "name": "Noah", "age": 5 }
53  ]
54);
55
56objBST.delete(11);

AVLTree snippet

1import { AVLTree } from 'data-structure-typed';
2
3const avlTree = new AVLTree<number>();
4avlTree.addMany([11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5])
5avlTree.isAVLBalanced();    // true
6avlTree.delete(10);
7avlTree.isAVLBalanced();    // true

Directed Graph simple snippet

1import { DirectedGraph } from 'data-structure-typed';
2
3const graph = new DirectedGraph<string>();
4
5graph.addVertex('A');
6graph.addVertex('B');
7
8graph.hasVertex('A');       // true
9graph.hasVertex('B');       // true
10graph.hasVertex('C');       // false
11
12graph.addEdge('A', 'B');
13graph.hasEdge('A', 'B');    // true
14graph.hasEdge('B', 'A');    // false
15
16graph.deleteEdgeSrcToDest('A', 'B');
17graph.hasEdge('A', 'B');    // false
18
19graph.addVertex('C');
20
21graph.addEdge('A', 'B');
22graph.addEdge('B', 'C');
23
24const topologicalOrderKeys = graph.topologicalSort(); // ['A', 'B', 'C']

Undirected Graph snippet

1import { UndirectedGraph } from 'data-structure-typed';
2
3const graph = new UndirectedGraph<string>();
4graph.addVertex('A');
5graph.addVertex('B');
6graph.addVertex('C');
7graph.addVertex('D');
8graph.deleteVertex('C');
9graph.addEdge('A', 'B');
10graph.addEdge('B', 'D');
11
12const dijkstraResult = graph.dijkstra('A');
13Array.from(dijkstraResult?.seen ?? []).map(vertex => vertex.key) // ['A', 'B', 'D']
14
15

API docs & Examples

API Docs

Live Examples

Examples Repository

Benchmark

MacBook Pro (15-inch, 2018)

Processor 2.2 GHz 6-Core Intel Core i7

Memory 16 GB 2400 MHz DDR4

Graphics Radeon Pro 555X 4 GB

Intel UHD Graphics 630 1536 MB

macOS Big Sur

Version 11.7.9

The corresponding relationships between data structures in different language standard libraries.

Data Structure Typed	C++ STL	java.util	Python collections
Heap<E>	-	-	heapq
PriorityQueue<E>	priority_queue<T>	PriorityQueue<E>	-
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

Algorithm	Function Description	Iteration Type
Binary Tree DFS	Traverse 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 BFS	Traverse a binary tree in a breadth-first manner, starting from the root node, visiting nodes level by level from left to right.	Iteration
Graph DFS	Traverse 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 Morris	Morris 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 BFS	Traverse 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 Algorithm	Find strongly connected components in a graph, typically implemented using depth-first search.	Recursion
Graph Bellman-Ford Algorithm	Finding the shortest paths from a single source, can handle negative weight edges	Iteration
Graph Dijkstra's Algorithm	Finding the shortest paths from a single source, cannot handle negative weight edges	Iteration
Graph Floyd-Warshall Algorithm	Finding the shortest paths between all pairs of nodes	Iteration
Graph getCycles	Find all cycles in a graph or detect the presence of cycles.	Recursion
Graph getCutVertices	Find cut vertices in a graph, which are nodes that, when removed, increase the number of connected components in the graph.	Recursion
Graph getSCCs	Find strongly connected components in a graph, which are subgraphs where any two nodes can reach each other.	Recursion
Graph getBridges	Find bridges in a graph, which are edges that, when removed, increase the number of connected components in the graph.	Recursion
Graph topologicalSort	Perform 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

We strictly adhere to computer science theory and software development standards. Our LinkedList is designed in the traditional sense of the LinkedList data structure, and we refrain from substituting it with a Deque solely for the purpose of showcasing performance test data. However, we have also implemented a Deque based on a dynamic array concurrently.

Principle	Description
Practicality	Follows ES6 and ESNext standards, offering unified and considerate optional parameters, and simplifies method names.
Extensibility	Adheres to OOP (Object-Oriented Programming) principles, allowing inheritance for all data structures.
Modularization	Includes data structure modularization and independent NPM packages.
Efficiency	All methods provide time and space complexity, comparable to native JS performance.
Maintainability	Follows open-source community development standards, complete documentation, continuous integration, and adheres to TDD (Test-Driven Development) patterns.
Testability	Automated and customized unit testing, performance testing, and integration testing.
Portability	Plans for porting to Java, Python, and C++, currently achieved to 80%.
Reusability	Fully decoupled, minimized side effects, and adheres to OOP.
Security	Carefully designed security for member variables and methods. Read-write separation. Data structure software does not need to consider other security aspects.
Scalability	Data structure software does not involve load issues.

supported module system

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

CDN

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

development

1
2<script src='https://cdn.jsdelivr.net/npm/data-structure-typed/dist/umd/data-structure-typed.js'></script>

production

1
2<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.

1const { Heap } = dataStructureTyped;
2const {
3  BinaryTree, Graph, Queue, Stack, PriorityQueue, BST, Trie, DoublyLinkedList,
4  AVLTree, MinHeap, SinglyLinkedList, DirectedGraph, TreeMultiMap,
5  DirectedVertex, AVLTreeNode
6} = dataStructureTyped;