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A tiny lightweight library for Fuzzy Search

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A tiny lightweight library for Fuzzy Search.

Why

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

Note

Note: The library is at a very early stage so if you want toTo help improve it, please open anissue.

Live Demo

You can check the demohere.

Installation

withyarn

yarn add fuzzify

withnpm

npm install fuzzify

Usage

importFuzzyfrom"fuzzify";constcountries=["Australia","France","Germany","Hungary","Iceland","India","Israel","Italy","Japan","Malawi","Malaysia","Maldives",];constfuzzy=newFuzzy(countries);constquery="ala";constresults=fuzzy.search(query);console.log("RESULTS",results);

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

AttributesDescription
textThe target string against which the query is matched
distanceThe 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 theindices at which characters match should be returned in the response.Eachmatch element consists of two indices -

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

Example 👇

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

In the above example 👇 matches are found

  1. charactera at0th index inala matches with characatera at5th index inAustralia
  2. characterl at1st index inala matches with characatera at6th index inAustralia
  3. charactera at2nd index inala matches with characatera at8th index inAustralia

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 of1 means an exact match, however a score of0 meansno match and those options are removed from the result.If you want to get all the options in the result, please open anissue and let's discuss.

caseSensitive

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

Set up

Install packages:

yarn

Start development playground:

yarn start

Build command:

yarn build

Contributing

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

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A tiny lightweight library for Fuzzy Search

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