fuzzysearch

WebJar for fuzzysearch

License

License

MIT
Categories

Categories

Search Business Logic Libraries
GroupId

GroupId

org.webjars.npm
ArtifactId

ArtifactId

fuzzysearch
Last Version

Last Version

1.0.3
Release Date

Release Date

Type

Type

jar
Description

Description

fuzzysearch
WebJar for fuzzysearch
Project URL

Project URL

http://webjars.org
Source Code Management

Source Code Management

https://github.com/bevacqua/fuzzysearch

Download fuzzysearch

How to add to project

<!-- https://jarcasting.com/artifacts/org.webjars.npm/fuzzysearch/ -->
<dependency>
    <groupId>org.webjars.npm</groupId>
    <artifactId>fuzzysearch</artifactId>
    <version>1.0.3</version>
</dependency>
// https://jarcasting.com/artifacts/org.webjars.npm/fuzzysearch/
implementation 'org.webjars.npm:fuzzysearch:1.0.3'
// https://jarcasting.com/artifacts/org.webjars.npm/fuzzysearch/
implementation ("org.webjars.npm:fuzzysearch:1.0.3")
'org.webjars.npm:fuzzysearch:jar:1.0.3'
<dependency org="org.webjars.npm" name="fuzzysearch" rev="1.0.3">
  <artifact name="fuzzysearch" type="jar" />
</dependency>
@Grapes(
@Grab(group='org.webjars.npm', module='fuzzysearch', version='1.0.3')
)
libraryDependencies += "org.webjars.npm" % "fuzzysearch" % "1.0.3"
[org.webjars.npm/fuzzysearch "1.0.3"]

Dependencies

There are no dependencies for this project. It is a standalone project that does not depend on any other jars.

Project Modules

There are no modules declared in this project.

fuzzysearch

Tiny and blazing-fast fuzzy search in JavaScript

Fuzzy searching allows for flexibly matching a string with partial input, useful for filtering data very quickly based on lightweight user input.

Demo

To see fuzzysearch in action, head over to bevacqua.github.io/horsey, which is a demo of an autocomplete component that uses fuzzysearch to filter out results based on user input.

Install

From npm

npm install --save fuzzysearch

fuzzysearch(needle, haystack)

Returns true if needle matches haystack using a fuzzy-searching algorithm. Note that this program doesn't implement levenshtein distance, 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 matches.

fuzzysearch('twl', 'cartwheel') // <- true
fuzzysearch('cart', 'cartwheel') // <- true
fuzzysearch('cw', 'cartwheel') // <- true
fuzzysearch('ee', 'cartwheel') // <- true
fuzzysearch('art', 'cartwheel') // <- true
fuzzysearch('eeel', 'cartwheel') // <- false
fuzzysearch('dog', 'cartwheel') // <- false

An exciting application for this kind of algorithm is to filter options from an autocomplete menu, check out horsey for an example on how that might look like.

But! RegExps...!

chart showing abysmal performance for regexp-based implementation

The current implementation uses the algorithm suggested by Mr. Aleph, a crazy russian compiler engineer working at V8.

License

MIT

Versions

Version
1.0.3