fuzzify

A tiny lightweight library for Fuzzy Search.

Why

I made this library as a result of learning about Levenshtein Distance algorithm to calculate the minimum number of single-character edits (insertions, deletions or substitutions) required to transform one word to another by Vladimir Levenshtein.

Note

Note: The library is at a very early stage so if you want to To help improve it, please open an issue.

Live Demo

You can check the demo here.

Installation

with yarn

yarn add fuzzify

with npm

npm install fuzzify

Usage

import Fuzzy from "fuzzify";

const countries = [
  "Australia",
  "France",
  "Germany",
  "Hungary",
  "Iceland",
  "India",
  "Israel",
  "Italy",
  "Japan",
  "Malawi",
  "Malaysia",
  "Maldives",
];
const fuzzy = new Fuzzy(countries);

const query = "ala";
const results = fuzzy.search(query);

console.log("RESULTS", results);

The search API gives approximate matched strings with the passed query in the below format.

Attributes	Description
text	The target string against which the query is matched
distance	The minimum number of edits (Insertion / Deletion / Substitutions) required to transform the query to target text.

[
  {
    text: "Malawi",
    distance: 3,
  },
  {
    text: "Malaysia",
    distance: 5,
  },
  {
    text: "Australia",
    distance: 6,
  },
  {
    text: "Italy",
    distance: 3,
  },
  {
    text: "Japan",
    distance: 3,
  },
  {
    text: "Iceland",
    distance: 5,
  },
  {
    text: "Maldives",
    distance: 6,
  },
  {
    text: "Israel",
    distance: 5,
  },
  {
    text: "India",
    distance: 4,
  },
  {
    text: "France",
    distance: 5,
  },
  {
    text: "Germany",
    distance: 6,
  },
  {
    text: "Hungary",
    distance: 6,
  },
];

Options

`includeMatches`

includeMatches - Determines whether the indices at which characters match should be returned in the response. Each match element consists of two indices -

The index of query string where match is found.
The index of target string where a match is found.

Example 👇

query = "ala", target string = "Australia"
matches: [
  [0, 5],
  [1, 6],
  [2, 8],
],

In the above example 👇 matches are found

character a at 0th index in ala matches with characater a at 5th index in Australia
character l at 1st index in ala matches with characater a at 6th index in Australia
character a at 2nd index in ala matches with characater a at 8th index in Australia

The complete response would be 👇

[
  {
    text: "Malawi",
    distance: 3,
    matches: [
      [0, 1],
      [1, 2],
      [2, 3],
    ],
  },
  {
    text: "Malaysia",
    distance: 5,
    matches: [
      [0, 1],
      [1, 2],
      [2, 7],
    ],
  },
  {
    text: "Australia",
    distance: 6,
    matches: [
      [0, 5],
      [1, 6],
      [2, 8],
    ],
  },
  {
    text: "Italy",
    distance: 3,
    matches: [
      [0, 2],
      [1, 3],
    ],
  },
  {
    text: "Japan",
    distance: 3,
    matches: [
      [0, 1],
      [2, 3],
    ],
  },
  {
    text: "Iceland",
    distance: 5,
    matches: [
      [1, 3],
      [2, 4],
    ],
  },
  {
    text: "Maldives",
    distance: 6,
    matches: [
      [0, 1],
      [1, 2],
    ],
  },
  {
    text: "Israel",
    distance: 5,
    matches: [
      [0, 3],
      [1, 5],
    ],
  },
  {
    text: "India",
    distance: 4,
    matches: [[2, 4]],
  },
  {
    text: "France",
    distance: 5,
    matches: [[2, 2]],
  },
  {
    text: "Germany",
    distance: 6,
    matches: [[2, 4]],
  },
  {
    text: "Hungary",
    distance: 6,
    matches: [[2, 4]],
  },
];

`includeScore`

Determines whether a score should be added in the result. A score of 1 means an exact match, however a score of 0 means no match and those options are removed from the result. If you want to get all the options in the result, please open an issue and let's discuss.

`caseSensitive`

Determines whether the query should be case-sensitive or not. By default, this option is false.

Set up

Install packages:

yarn

Start development playground:

yarn start

Build command:

yarn build

Contributing

Please open an issue so we can start discussing. Any help to improve the library is most welcome :).

ad1992/fuzzify