farzher/fuzzysort

Fast SublimeText-like fuzzy search for JavaScript.

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Summary Information

Updated 31 minutes ago
Added to GitGenius on September 16th, 2026
Created on August 18th, 2017
Open Issues & Pull Requests: 7 (+0)
GitHub issues: Enabled
Number of forks: 160
Total Stargazers: 4,350 (+0)
Total Subscribers: 37 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 12.1 hours
Mean response time: 36.9 days
90th percentile: 173.7 days
Tracked items: 25

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Issue Activity (beta)

Open issues: 3
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 1,251 days
Stale 30+ days: 3
Stale 90+ days: 2

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

fuzzysort is a JavaScript library that provides fast fuzzy search matching with a SublimeText-like algorithm.

The library solves the problem of efficiently filtering and ranking items based on fuzzy string matching, where users can find results by typing partial, non-contiguous characters. It implements a scoring algorithm that prioritizes matches where the typed characters appear consecutively or early in the target string, mimicking the behavior developers expect from SublimeText's search functionality. The approach focuses on speed, making it suitable for real-time search across large datasets without noticeable latency.

Developers should choose this tool when building search interfaces that need to feel responsive and intuitive, particularly for autocomplete fields, command palettes, or filtering lists of items. It works well in scenarios where users expect SublimeText-style fuzzy matching behavior. The library is language-agnostic in application despite being written in JavaScript, making it suitable for browser-based applications, Node.js projects, or any environment where JavaScript runs.

The project shows consistent maintenance with regular updates addressing performance and correctness. Development activity demonstrates responsiveness to issues and pull requests, with fixes and improvements being integrated steadily. The codebase receives attention to edge cases and algorithm refinements, indicating active stewardship of the tool's core functionality.