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46 lines
1.6 KiB
46 lines
1.6 KiB
3 years ago
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# fuzzysearch
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> Tiny and blazing-fast fuzzy search in JavaScript
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Fuzzy searching allows for flexibly matching a string with partial input, useful for filtering data very quickly based on lightweight user input.
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# Demo
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To see `fuzzysearch` in action, head over to [bevacqua.github.io/horsey][3], which is a demo of an autocomplete component that uses `fuzzysearch` to filter out results based on user input.
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# Install
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From `npm`
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```shell
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npm install --save fuzzysearch
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```
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# `fuzzysearch(needle, haystack)`
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Returns `true` if `needle` matches `haystack` using a fuzzy-searching algorithm. Note that this program doesn't implement _[levenshtein distance][2]_, but rather a simplified version where **there's no approximation**. The method will return `true` only if each character in the `needle` can be found in the `haystack` and occurs after the preceding character.
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```js
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fuzzysearch('twl', 'cartwheel') // <- true
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fuzzysearch('cart', 'cartwheel') // <- true
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fuzzysearch('cw', 'cartwheel') // <- true
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fuzzysearch('ee', 'cartwheel') // <- true
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fuzzysearch('art', 'cartwheel') // <- true
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fuzzysearch('eeel', 'cartwheel') // <- false
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fuzzysearch('dog', 'cartwheel') // <- false
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```
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An exciting application for this kind of algorithm is to filter options from an autocomplete menu, check out [horsey][3] for an example on how that might look like.
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# But! _`RegExp`s...!_
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![chart showing abysmal performance for regexp-based implementation][1]
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# License
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MIT
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[1]: https://cloud.githubusercontent.com/assets/934293/6495796/106a61a6-c2ac-11e4-945d-3d1bb066a76e.png
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[2]: http://en.wikipedia.org/wiki/Levenshtein_distance
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[3]: http://bevacqua.github.io/horsey
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