seanghay

seanghay / betterkhmer

Public

Regex-free, fast Khmer Encoding normalizer ported to 18 languages

c cpp csharp dart flutter
12
2
100% credibility
Found May 17, 2026 at 13 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Objective-C
AI Summary

BetterKhmer is a text normalization tool for the Khmer (Cambodian) language. It solves a subtle but important problem: the same Khmer word can be typed in multiple different ways that look identical on screen but are stored differently in the computer. This causes search engines to return wrong results, allows malicious websites to disguise themselves, and makes code review unreliable. BetterKhmer converts all these different-looking versions into one correct, consistent form. The tool has been carefully ported to work in 18 different programming languages, and all versions produce identical results, verified against over 10,000 test cases from real Khmer text.

How It Works

1
📝 You discover inconsistent Khmer text

You notice that searching for words in Khmer gives different results, or that some text looks wrong in certain apps.

2
🔍 You learn about encoding chaos

The same Khmer word can be stored in multiple ways that look identical on screen but have different byte sequences underneath.

3
✨ You find BetterKhmer

A tool that converts all those different-looking versions into one consistent, correct form that works everywhere.

4
You pick your programming language
🐍
Python, Ruby, PHP

Popular scripting languages for web and automation

⚡
Go, Rust, Swift

Fast compiled languages for performance-critical apps

☕
Java, Kotlin, C#

Enterprise languages for large business applications

🔧
C, C++, Zig

Systems languages for maximum control and speed

5
📋 You copy one file into your project

No package managers or complicated setup—just grab the single source file for your language and add it to your project.

6
🔄 You run your text through normalize()

Pass any Khmer text through the function and get back a perfectly standardized version that renders correctly everywhere.

✅ Your Khmer text works perfectly

Search finds the right results, comparisons work reliably, and your app displays Khmer text correctly for everyone.

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Star Growth

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AI-Generated Review

What is betterkhmer?

Betterkhmer is a Khmer Unicode normalizer that ensures text renders consistently regardless of how it was originally encoded. Khmer syllables are two-dimensional arrangements of marks that can be stored multiple ways in Unicode, causing search failures, security issues, and rendering problems. This library collapses all equivalent forms into one canonical byte sequence. It runs regex-free and fast, with implementations in 18 languages including Objective-C, Python, Go, Rust, Swift, Java, and more. Each port exposes a single normalize() function that you copy directly into your project.

Why is it gaining traction?

The project solves a real problem that affects search, security, and rendering for Khmer text. The approach is refreshingly simple: no dependencies, no package registry, just copy one file and call normalize(). With 18 language ports that all produce identical output (verified against 10,085 test cases), it is a solid choice for polyglot projects. The benchmark table showing Java at 85k ops/sec versus Lua at 3.5k ops/sec gives developers concrete data for performance decisions.

Who should use this?

Backend developers building search or database systems for Khmer content need this to prevent encoding mismatches. Security teams working on Khmer applications should use it to catch spoofing attempts. Anyone maintaining multilingual applications where Khmer text appears will benefit from consistent normalization.

Verdict

The library works and solves a real problem, but the 12 stars and 1.0% credibility score reflect a niche tool with low visibility. Not being published to package registries means manual integration, and documentation quality varies by language. For production Khmer text handling, this is worth evaluating, but teams should review test coverage and maintenance commitment before betting on it long-term.

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