esds

ESDS

ES Javascript Data Structures (Priority Queue, Binary Search Tree (BST), Graph, Trie, Bloom Filter, Queue, Stack, Linked List)
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Table of Contents

1. Getting Started 🚦
   • Installation 💾
2. Usage 📚
   • Examples 📑
     • Priority Queue 📚
     • Binary Search Tree (BST) 🎄
     • Graph ፨
       • Undirected ↔
       • Directed →
     • Trie 🌲
     • Bloom Filter ⚘
     • Queue 📚 / Stack 🥞
     • Linked List📝
3. Roadmap 📍
4. Contributing 💪
5. License 📝
6. Contact 📧

Getting Started

To get a local copy up and running follow these simple steps.

Installation

1. Install NPM package

   npm i esds
   

Examples

Priority Queue

import { PriorityQueue } from "esds";

const minPQ = new PriorityQueue("min"); // min PQ (default if not provided)
const maxPQ = new PriorityQueue("max"); // max PQ

const arr = [20, 40, 30, 50, 15, 10, 5];

arr.forEach((element) => {
  minPQ.add(element);
  maxPQ.add(element);
});

console.log(minPQ.peek); // 5
console.log(maxPQ.peek); // 50

while (!minPQ.isEmpty) {
  console.log(minPQ.poll());
}
/*
    5
    10
    15
    20
    30
    40
    50
*/

while (!maxPQ.isEmpty) {
  console.log(maxPQ.poll());
}
/*
    50
    40
    30
    20
    15
    10
    5
*/

// Custom comparator

const comparator = (a, b) => a.age - b.age; // Using age (min)
const customPQ = new PriorityQueue("custom", comparator);
const Person = function (name, age, role) {
  this.name = name;
  this.age = age;
  this.role = role;
};

customPQ.add(new Person("Jane Doe", 26, "Software Engineer"));
customPQ.add(new Person("John Doe", 28, "Cloud Engineer"));
customPQ.add(new Person("Ordinary Joe", 42, "QA"));
customPQ.add(new Person("Janie Doe", 20, "Support Engineer"));
customPQ.add(new Person("Fred Bloggs", 19, "Intern"));

// Contains function using object
console.log(customPQ.contains(new Person("Janie Doe", 20, "Support Engineer"))); // true

// Poll
while (!customPQ.isEmpty) {
  console.log(customPQ.poll());
}
/*
{ name: 'Fred Bloggs', age: 19, role: 'Intern' }
{ name: 'Janie Doe', age: 20, role: 'Support Engineer' }
{ name: 'Jane Doe', age: 26, role: 'Software Engineer' }
{ name: 'John Doe', age: 28, role: 'Cloud Engineer' }
{ name: 'Ordinary Joe', age: 42, role: 'QA' }
*/

Binary Search Tree

import { BST, List} from "esds";


const bst = new BST();

// Add Elements
bst.add(10, "Ten");
bst.add(1, "One");
bst.add(5, "Five");
bst.add(7, "Seven");
bst.add(2, "Two");
bst.add(0, "Zero");
bst.add(8, "Eight");

console.log(bst.toArray("in-order"));
// [ 0, 1, 2, 5, 7, 8, 10 ]
console.log(bst.toArray("pre-order"));
// [ 10, 1, 0, 5, 2, 7, 8 ]
console.log(bst.toArray("post-order"));
// [ 0, 2,  8, 7, 5, 1, 10 ]
console.log(bst.toArray("reverse-in-order"));
// [ 10, 8, 7, 5, 2, 1, 0 ]

// Get Element
console.log(bst.get(7));
/*
    TreeElement {
    key: 7,
    value: 'Seven',
    left: null,
    right: TreeElement { key: 8, value: 'Eight', left: null, right: null }
    }
*/

// Update Element
bst.update(8, "はち");
console.log(bst.get(8).value); // はち

// Has
console.log(bst.has(5)); // true

// Remove Element
bst.remove(5);
console.log(bst.has(5)); // false

// Handling duplicates (Using Linked-list)
if (bst.has(7)) {   // true
  const list = new List();
  list.add(bst.get(7).value); // Added "Seven"
  list.add(["Siete", "しち", "七", "Sieben"]);
  bst.update(7, list);
}
console.log(bst.get(7).value.toArray());
// [ 'Seven', 'Siete', 'しち', '七', 'Sieben' ]

// Remove Elements using an iterator in order to prevent a significant unbalanced BST

// JS Generator function
function* iterator(arr) {
  let i = 0;
  while (true) {
    yield arr[i++];
    if (i === arr.length) i = 0;
  }
}

const removeType = iterator(["predecessor", "successor"]); // in-order predecessor, and in-order successor
[10, 1, 0, 5, 7].forEach((value) => bst.remove(value, removeType.next().value));

console.log(bst.toArray()); // Default: in-order
// [ 2, 8 ]

Graph

Undirected

import { Graph } from "esds";

const graph = new Graph(); // Creates a new undirected graph

// Add nodes (Users)
graph.addNode(1, "Randall");
graph.addNode(2, "Mellisa");
graph.addNode(3, "Cecelia");
graph.addNode(4, "Velda");
graph.addNode(5, "Rossie");

//Add Edges (Friendships)
graph.addEdge(1, 2); // Randall - Mellisa
graph.addEdge(2, 5); // Mellisa - Rossie
graph.addEdge(3, 4); // Cecelia - Velda
graph.addEdge(4, 1); // Velda - Randall
graph.addEdge(5, 1); // Rossie - Randall

// Check if connection exists (Users are friends)
console.log(graph.nodesConnected(2, 3)); // Mellisa & Cecelia: Output: false
console.log(graph.nodesConnected(1, 5)); // Randall & Rossie: Output: true

// Check distance between two nodes (Users)
console.log(graph.getWeight(2, 3)); // Mellisa & Cecelia: Output: 3rd level friends
console.log(graph.getWeight(1, 5)); // Randall & Rossie: Output: 1st level friends (Users are friends)

// Get Path between nodes (Friendship relation between two users)
console.log(graph.getPath(2, 3).map((value) => graph.getNode(value.node)));
//  [ 'Mellisa', 'Randall', 'Velda', 'Cecelia' ]
console.log(graph.getPath(1, 5).map((value) => graph.getNode(value.node)));
//  [ 'Randall', 'Rossie' ]

Directed

import { Graph } from "esds";

const graph = new Graph(true); // Creates a new directed graph

// Add Nodes (Cities)
graph.addNode(1, "City Α");
graph.addNode(2, "City β");
graph.addNode(3, "City Γ");
graph.addNode(4, "City Δ");
graph.addNode(5, "City ε");

// Add Edges (Routes between cities (one-way))
graph.addEdge(1, 3, 75); // Alpha (Α) -> Gamma (Γ), distance 75 miles
graph.addEdge(2, 5, 325); // Beta (β) -> Epsilon (ε), distance 325 miles
graph.addEdge(3, 1, 125); //  Gamma (Γ) -> Alpha (α), distance 125 miles
graph.addEdge(4, 2, 100); // Delta (Δ) -> Beta (β), distance 100 miles
graph.addEdge(5, 1, 415); // Epsilon (ε) -> Alpha (Α), distance 415 miles
graph.addEdge(5, 3, 550); // Epsilon (ε) -> Gamma (Γ), distance 550 miles

// Check if connection exists (Route between cities exists)
console.log(graph.nodesConnected(2, 3)); // Beta & Gamma: Output: false
console.log(graph.nodesConnected(5, 1)); // Epsilon & Alpha: Output: true

// Get Path between nodes (Route between two cities) by lowest number of intermediate nodes
let routeADistance = 0;
const routeA = graph.getPath(2, 3).map((value) => {
  // Between Beta (β) & Gamma (Γ)
  routeADistance += value.weight;
  return graph.getNode(value.node);
});
console.log(routeA, routeADistance);
/*
  ([Route] Total distance in miles)
  [ 'City β', 'City ε', 'City Γ' ] 875
*/

// Get Path between nodes (Route between two cities) by lowest distance (Dijkstra algorithm)
let routeB = graph.getPathWeighted(2, 3); // Between Beta (β) & Gamma (Γ)
let routeBDistance = routeB.distance;
routeB = routeB.nodes.map((value) => graph.getNode(value));
console.log(routeB, routeBDistance);
/*
  ([Route] Total distance in miles)
  [ 'City β', 'City ε', 'City Α', 'City Γ' ] 815
*/

Use cases: Social graphs, recommendation engines, navigation, supply chain, etc.

Flight Routes Example: https://bit.ly/3ApNrDA

Trie

import { Trie } from "esds";

const countries = [
  "United States of America",
  "Canada",
  "Argentina",
  "Japan",
  "Italy",
  "Germany",
  "Brazil",
  "Armenia",
  "Aruba",
];

const trie = new Trie();

countries.forEach((element) => trie.add(element)); // Add countries to the Trie

// Check if element exists
console.log(trie.contains("Argentina")); // True
console.log(trie.contains("Spain")); // False

// Update content
trie.update("Argentina", "🇦🇷");
trie.update("United States of America", "🇺🇸");

// Get content
console.log(trie.get("Argentina")); // 🇦🇷
console.log(trie.get("United States of America")); // 🇺🇸

// Retrieve Sub-Trie (DFS)
const prefix = "Ar";
const result = trie.find(prefix);

const dfs = (word, node) => {
  if (node.child?.size > 0) {
    node.child.forEach((value) => {
      dfs(`${word}${value.key}`, value);
    });
  }
  if (node.end) console.log(`${word}`);
  /*
    Argentina
    Armenia
    Aruba
  */
};
dfs(prefix, result);

// toArray()
console.log(trie.toArray());

/*
  ['United States of America','Canada', 'Argentina', 'Armenia',
   'Aruba', 'Japan', 'Italy', 'Germany','Brazil']
*/

Use cases: Auto-complete, string search, word suggestion, prefix, IP routing, etc.

Word Prediction Example: https://bit.ly/37hYhPL

Bloom Filter

A Bloom filter is a space-efficient probabilistic data structure that is used to test whether an element is a member of a set. More Info: https://bit.ly/3D9RmH8

import { BloomFilter } from "esds";

// Create BF
const BF = new BloomFilter();

// Add individual users
BF.add("[e-mail]");
BF.add("[e-mail]");
BF.add("[e-mail]");
BF.add("[e-mail]");
BF.add("[e-mail]");

// Check individual users
console.log(BF.has("[e-mail]")); // True (User may exists)
console.log(BF.has("[e-mail]")); // False

// Create second BF
const BF2 = new BloomFilter(2048, 4); // Size 2048, Num. Hash rounds 4

const users = [
  "almost",
  "dopey",
  "eritrean",
  "struggle",
  "hospitable",
  "factor",
  "quail",
];

// Add multiple users
BF2.add(users);

// Check individual users
console.log(BF2.has("struggle")); // True (User may exists)
console.log(BF2.has("house")); // False

// Check multiple values
console.log(
  BF2.has(["hospitable", "monitor", "dopey", "factor", "fan", "quail"])
);
// [ true, false, true, true, false, true ]

Bloom Filters use cases:

• Value lookup when false positives are acceptable
• Avoid expensive lookup operations against DB
• Content filtering

Queue-Stack

import {Queue, Stack} from 'esds';

const queue = new Queue();
const stack = new Stack();

queue.add([1,2,3]);
queue.add(4);
queue.add(5);

stack.push([1,2]);
stack.add(3);
stack.add([4,5]);

while (!queue.isEmpty){
    console.log(queue.poll()); // 1, 2, 3, 4, 5
}

while (!stack.isEmpty){
    console.log(stack.pop()); // 5, 4, 3, 2, 1
}

Linked List

import {List} from 'esds';

const a = new List();
a.add([1, 2, 3, 4]);
console.log(a.toArray()); // [1, 2, 3, 4]

a.add(5);
a.add("Six");
a.add({value: 7, str: "Seven"});
console.log(a.get(6).val); // "Six"

let head = a.get();
while(head){
    console.log(head.val);
    head = head.next;
}
/*
1
2
3
4
5
"Six"
{value: 7, str: "Seven"}
*/

let b = a.subList(2, 5);
console.log(b.toArray()); // [2, 3, 4, 5]

Roadmap

See the open issues for a list of proposed features (and known issues).

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Project Link: https://github.com/jayalbo/ESDS