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

kled

v0.1.6

Published

Fuzzy Matching Library with Levenshtein Edit Distance, Tailored for Korean Language Support

Downloads

12

Readme

kled.js

Fuzzy Matching Library with Levenshtein Edit Distance, Tailored for Korean Language Support

Also available in: 한국어

APIs

distance(a: string, b: string, caseSensitive: bool): number

Calculate the Levenshtein distance between two strings.

Parameters

  • a: a string
  • b: another string
  • caseSensitive: optional parameter (default: false), determines whether to consider case sensitivity.

Returns

The Levenshtein distance between the input strings.

matches(needle: string, haystack: string, caseSensitive: bool): number

Calculate the similarity score between two strings, providing a numerical value between 0 and 1. If the "haystack" does not contain the "needle," the function returns 0.

It also supports partial Korean letter matching. For example, "ㅇㄴ" and "아녀" matches "안녕" with a slightly lower score than "안녕", which exactly matches the haystack.

Parameters

  • needle: a string to search for
  • haystack: a string to search in
  • caseSensitive: optional parameter (default: false), determines whether to consider case sensitivity.

Returns

A similarity score between the input strings, where 0 indicates no similarity, and 1 indicates a perfect match based on the number of matched letters and their positions.

Usage

import { distance, matches } from 'kled';

const levenshteinDistance = distance('hello', 'hola');
console.log(`Levenshtein Distance: ${levenshteinDistance}`);

const similarityScore = matches('abc', 'abCde');
console.log(`Similarity Score: ${similarityScore}`);

Reporting Issues

Please report issues here if you find any.

License

MIT