Fast, tiny, good fuzzy search for JavaScript.
<1ms for 13,000 files · 0 dependencies · clean ranking
Demo
https://farzher.github.io/fuzzysort/test/test.html

Install
npm i fuzzysort
import fuzzysort from 'fuzzysort'
Browser:
<script type="module">
import fuzzysort from 'https://cdn.jsdelivr.net/npm/fuzzysort@4.0.1/fuzzysort.min.js'
</script>
Quick start
const files = [
{file: 'Guide.cpp'},
{file: 'UserInterface.cpp'},
]
const results = fuzzysort.go('ui', files, {key: 'file'})
results[0].obj.file // 'UserInterface.cpp'
fuzzysort.go(search, targets, {
limit : 10, // Max results; 0 = unlimited
threshold : .5, // Minimum score; 0 = any match
key : null, // Search one property
keys : null, // Search multiple properties
scoreFn : null, // Override result scoring
})
Results
const result = fuzzysort.single('query', 'some string that contains my query.')
result.score // .80 (1 is a perfect match. 0.5 is a good match. 0 is no match.)
result.target // 'some string that contains my query.'
result.indexes // [29, 30, 31, 32, 33]
result.obj // reference to your original obj when using options.key
result.highlight('<b>', '</b>') // 'some string that contains my <b>query</b>.'
result.highlight((m, i) => <react key={i}>{m}</react>)
Advanced Usage - multiple complex keys - custom scoring
const objects = [{
title: 'Petaya Berry',
meta: {desc: 'Raises Special Attack when HP is low.'},
tags: ['berries', 'items'],
}, {
title: 'Liechi Berry',
meta: {desc: 'Raises Attack when HP is low.'},
favorite: true,
}]
const targets = fuzzysort.snapshot(objects, {
keys: ['title', 'meta.desc', obj => obj.tags?.join()],
})
const results = fuzzysort.go('attack berry', targets, {
scoreFn: r => r.score * (r.obj.favorite ? 2 : 1),
})
const result = results[0]
result[0].highlight() // 'Liechi <b>Berry</b>'
result[1].highlight() // 'Raises <b>Attack</b> when HP is low.'
result.obj.title // 'Liechi Berry'
How To Go Fast! - Performance Tips!
Filter out targets you don't need to search! Especially long ones!
let targets = [
{file: 'Guide.cpp'},
{file: 'UserInterface.cpp'},
].filter(t => t.file.length < 1000)
If your targets don't change, take an immutable snapshot() for the best performance!
targets = fuzzysort.snapshot(targets, {key: 'file'})
fuzzysort.go('gotta', targets)
fuzzysort.go('go', targets)
fuzzysort.go('fast', targets)
If you can't snapshot, provide prepared targets instead of raw strings!
targets.forEach(t => t.filePrepared = fuzzysort.prepare(t.file))
fuzzysort.go('fast', targets, {key: 'filePrepared'})
Character remapping
Searches use NFKD normalization, strip diacritics, and remap common quote, dash, slash, ellipsis, and lookalike characters.
Add or override mappings with fuzzysort.remap():
fuzzysort.remap({',': '.'}) // 12,5 = 12.5
Web Workers / cloned results
Structured cloning can remove the getters on results. For cloned results use:
fuzzysort.score(result)
fuzzysort.highlight(result)
Changelog
v4.0.0
- ESM instead of UMD
- Added
fuzzysort.snapshot()for the best search performance - Added
fuzzysort.score()andfuzzysort.highlight()for Web Worker support - Added
fuzzysort.remap()for custom normalization - Automatically remaps common lookalike characters
- Added default
thresholdandlimit - Improved multi-key highlighting
- Improved substring scoring
- Removed
options.all; empty search now returns results scoreFnnow works with all search modes