npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

esds

v0.6.0

Published

ES6 JS lightweight data structures (Priority Queue, Binary Search Tree (BST), Graph, Bloom Filters, Trie, Queue, Stack, Linked-List)

Downloads

90

Readme

Contributors Downloads Forks Stargazers Issues MIT License

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

Flight Routes

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

Word Prediction

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("[email protected]");
BF.add("[email protected]");
BF.add("[email protected]");
BF.add("[email protected]");
BF.add("[email protected]");

// Check individual users
console.log(BF.has("[email protected]")); // True (User may exists)
console.log(BF.has("[email protected]")); // 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