# Data Structure Typed ![NPM](https://img.shields.io/npm/l/data-structure-typed) ![GitHub top language](https://img.shields.io/github/languages/top/zrwusa/data-structure-typed) ![npm](https://img.shields.io/npm/dw/data-structure-typed) ![eslint](https://aleen42.github.io/badges/src/eslint.svg) ![npm package minimized gzipped size (select exports)](https://img.shields.io/bundlejs/size/data-structure-typed) ![npm bundle size](https://img.shields.io/bundlephobia/min/data-structure-typed) ![npm](https://img.shields.io/npm/v/data-structure-typed) 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) [//]: # (![Branches](https://img.shields.io/badge/branches-55.47%25-red.svg?style=flat)) [//]: # (![Statements](https://img.shields.io/badge/statements-67%25-red.svg?style=flat)) [//]: # (![Functions](https://img.shields.io/badge/functions-66.38%25-red.svg?style=flat)) [//]: # (![Lines](https://img.shields.io/badge/lines-68.6%25-red.svg?style=flat)) ## 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 ```bash npm i data-structure-typed --save ``` ### yarn ```bash yarn add data-structure-typed ``` ```js import { BinaryTree, Graph, Queue, Stack, PriorityQueue, BST, Trie, DoublyLinkedList, AVLTree, MinHeap, SinglyLinkedList, DirectedGraph, TreeMultiset, DirectedVertex, AVLTreeNode } from 'data-structure-typed'; ``` ### CDN ```html ``` ```js const {Heap} = dataStructureTyped; const { BinaryTree, Graph, Queue, Stack, PriorityQueue, BST, Trie, DoublyLinkedList, AVLTree, MinHeap, SinglyLinkedList, DirectedGraph, TreeMultiset, DirectedVertex, AVLTreeNode } = dataStructureTyped; ``` ![](https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/examples/videos/webp_output/binary-tree-array-to-binary-tree.webp) ![](https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/examples/videos/webp_output/binary-tree-dfs-in-order.webp) ![](https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/examples/videos/webp_output/avl-tree-test.webp) ![](https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/examples/videos/webp_output/tree-multiset-test.webp) ![](https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/examples/videos/webp_output/matrix-cut-off-tree-for-golf.webp) ![](https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/examples/videos/webp_output/directed-graph-test.webp) ![](https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/examples/videos/webp_output/map-graph-test.webp) ## API docs & Examples [API Docs](https://data-structure-typed-docs.vercel.app) [Live Examples](https://vivid-algorithm.vercel.app) Examples Repository ## Code Snippet ### Binary Search Tree (BST) snippet #### TS ```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>(); 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 ```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 ```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 ```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 ```ts 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 ```ts 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
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	Data Structure Typed	C++ STL	java.util	Python collections
Dynamic Array	Array<E>	vector<T>	ArrayList<E>	list
Linked List	DoublyLinkedList<E>	list<T>	LinkedList<E>	deque
Singly Linked List	SinglyLinkedList<E>	-	-	-
Set	Set<E>	set<T>	HashSet<E>	set
Map	Map<K, V>	map<K, V>	HashMap<K, V>	dict
Ordered Dictionary	Map<K, V>	-	-	OrderedDict
Queue	Queue<E>	queue<T>	Queue<E>	-
Priority Queue	PriorityQueue<E>	priority_queue<T>	PriorityQueue<E>	-
Heap	Heap<V>	priority_queue<T>	PriorityQueue<E>	heapq
Stack	Stack<E>	stack<T>	Stack<E>	-
Deque	Deque<E>	deque<T>	-	-
Trie	Trie	-	-	-
Unordered Map	HashMap<K, V>	unordered_map<K, V>	HashMap<K, V>	defaultdict
Multiset	-	multiset<T>	-	-
Multimap	-	multimap<K, V>	-	-
Binary Tree	BinaryTree<K, V>	-	-	-
Binary Search Tree	BST<K, V>	-	-	-
Directed Graph	DirectedGraph<V, E>	-	-	-
Undirected Graph	UndirectedGraph<V, E>	-	-	-
Unordered Multiset	-	unordered_multiset	-	Counter
Linked Hash Set	-	-	LinkedHashSet<E>	-
Linked Hash Map	-	-	LinkedHashMap<K, V>	-
Sorted Set	AVLTree<E>	-	TreeSet<E>	-
Sorted Map	AVLTree<K, V>	-	TreeMap<K, V>	-
Tree Set	AVLTree<E>	set	TreeSet<E>	-
Unordered Multimap	-	unordered_multimap<K, V>	-	-
Bitset	-	bitset<N>	-	-
Unordered Set	-	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 [//]: # (Start of Replace Section)

avl-tree

test name	time taken (ms)	executions per sec	executed times	sample mean (secs)	sample deviation
1000 add randomly	2.21	451.50	24	0.00	9.12e-5
1000 add & delete randomly	5.02	199.23	11	0.01	6.31e-4
1000 addMany	2.96	338.41	18	0.00	2.09e-4
1000 get	2.00	499.79	26	0.00	1.89e-4

binary-tree

test name	time taken (ms)	executions per sec	executed times	sample mean (secs)	sample deviation
1000 add randomly	12.95	77.23	5	0.01	1.82e-4
1000 add & delete randomly	15.94	62.73	4	0.02	1.95e-4
1000 addMany	10.81	92.48	5	0.01	5.30e-4
1000 get	18.16	55.07	3	0.02	2.99e-4
1000 dfs	69.52	14.38	1	0.07	0.00
1000 bfs	54.84	18.24	1	0.05	7.36e-4
1000 morris	38.26	26.13	2	0.04	0.00

bst

test name	time taken (ms)	executions per sec	executed times	sample mean (secs)	sample deviation
1000 add randomly	2.22	450.51	24	0.00	6.06e-5
1000 add & delete randomly	5.04	198.59	11	0.01	2.52e-4
1000 addMany	2.14	467.96	25	0.00	6.00e-5
1000 get	2.06	486.16	25	0.00	1.15e-4

directed-graph

test name	time taken (ms)	executions per sec	executed times	sample mean (secs)	sample deviation
1000 addVertex	0.10	9726.70	496	1.03e-4	1.60e-6
1000 addEdge	6.23	160.46	9	0.01	5.60e-4
1000 getVertex	0.05	2.17e+4	1097	4.61e-5	3.68e-7
1000 getEdge	23.53	42.49	3	0.02	0.00
tarjan	216.40	4.62	1	0.22	0.01
tarjan all	218.57	4.58	1	0.22	0.00
topologicalSort	186.63	5.36	1	0.19	0.03

heap

test name	time taken (ms)	executions per sec	executed times	sample mean (secs)	sample deviation
1000 add & pop	0.34	2927.03	149	3.42e-4	3.47e-6
1000 fib add & pop	3.91	255.63	13	0.00	4.55e-5

doubly-linked-list

test name	time taken (ms)	executions per sec	executed times	sample mean (secs)	sample deviation
1000000 unshift	200.25	4.99	1	0.20	0.03
1000000 unshift & shift	183.25	5.46	1	0.18	0.05
1000 insertBefore	0.03	3.64e+4	2005	2.75e-5	8.47e-7

singly-linked-list

test name	time taken (ms)	executions per sec	executed times	sample mean (secs)	sample deviation
1000 push & pop	1.79	558.34	30	0.00	6.00e-5
1000 insertBefore	2.40	417.00	22	0.00	3.01e-4

max-priority-queue

test name	time taken (ms)	executions per sec	executed times	sample mean (secs)	sample deviation
10000 refill & poll	11.77	84.98	5	0.01	0.00

deque

test name	time taken (ms)	executions per sec	executed times	sample mean (secs)	sample deviation
1000000 push	224.48	4.45	1	0.22	0.03
1000000 shift	27.21	36.76	3	0.03	0.00

queue

test name	time taken (ms)	executions per sec	executed times	sample mean (secs)	sample deviation
1000000 push	46.46	21.52	2	0.05	0.01
1000000 push & shift	78.88	12.68	1	0.08	0.00

trie

test name	time taken (ms)	executions per sec	executed times	sample mean (secs)	sample deviation
100000 push	54.62	18.31	1	0.05	9.87e-4
100000 getWords	89.26	11.20	1	0.09	0.00

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