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https://github.com/beowolx/haiku-search
Haiku-Search is a high-performance fuzzy search library designed for web applications. It is built using Rust and compiled to WebAssembly
https://github.com/beowolx/haiku-search
bitma fuzzy-search javascript n-grams rust wasm
Last synced: 17 days ago
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Haiku-Search is a high-performance fuzzy search library designed for web applications. It is built using Rust and compiled to WebAssembly
- Host: GitHub
- URL: https://github.com/beowolx/haiku-search
- Owner: beowolx
- License: mit
- Created: 2024-05-08T14:29:15.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2024-05-14T07:06:45.000Z (7 months ago)
- Last Synced: 2024-11-15T22:12:15.354Z (about 1 month ago)
- Topics: bitma, fuzzy-search, javascript, n-grams, rust, wasm
- Language: Rust
- Homepage: https://beowolx.github.io/haiku-search/
- Size: 73.2 KB
- Stars: 22
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Haiku-Search
[](https://github.com/beowolx/haiku/actions)
[](https://www.npmjs.com/package/haiku-search)
## Overview
Haiku-Search is a high-performance fuzzy search library designed for web applications. It is built using Rust and compiled to WebAssembly, providing lightning-fast search capabilities directly in the browser. This combination allows Haiku-Search to execute complex search algorithms efficiently, taking advantage of Rust's performance and safety features.
## Powered by Rust and WebAssembly
Haiku-Search leverages the power of Rust and WebAssembly to run directly in web browsers, offering significant performance improvements over traditional JavaScript search libraries. By compiling to WebAssembly, Haiku-Search provides near-native speed, making it ideal for applications requiring quick search responses on large datasets.
## Algorithms
Haiku-Search implements two primary algorithms:
- **N-gram Indexing**: This technique breaks down text into chunks (n-grams) and indexes them for quick lookup, allowing us to quickly narrow down potential matches.
- **Bitap Algorithm**: For precise matching, Haiku-Search uses the [Bitap algorithm](https://en.wikipedia.org/wiki/Bitap_algorithm), which supports a configurable number of errors. It is effective for short to medium text lengths and allows for approximate string matching.
## Installation
To install, just run:
```bash
npm install haiku-search
```
## Usage Example
Here is an example of how to use Haiku-Search without a bundler in your app:
```js
import init, {
SearchEngine,
} from "./node_modules/haiku-search/haiku_search.js";
async function demoHaikuSearch() {
// Initialize the WASM module, only needed if once and if not using a bundler
await init();
const data = ["Apple Pie", "Banana Bread", "Carrot Cake"];
const haikuEngine = new SearchEngine(data, {
ngram_size: 3,
max_distance: 1,
});
const query = "Apple";
const result = await haikuEngine.search(query);
console.log("Search result:", result[0].text);
console.log("Score result:", result[0].score);
}
demoHaikuSearch();
```
Currently, WASM modules are only supported by WebPack. So, if you want use Haiku-Search in a web application, you will have to use WebPack.
## Performance Comparison to Fuse.js
Haiku-Search is designed to be significantly faster than traditional JavaScript libraries like [Fuse.js](<[url](https://www.fusejs.io/)>). In benchmarks, Haiku-Search performs searches up to **13x faster than Fuse.js**.
You can see this chart live here: [Haiku-Search vs Fuse.js Benchmark Results](https://beowolx.github.io/haiku-search/index.html).
## Known Limitations
- **Unicode Support**: Haiku-Search does not currently support unicode characters, which may limit its use in applications requiring internationalization.
- **Pattern Length**: The Bitap algorithm used in Haiku-Search supports patterns up to 32 characters long due to limitations in handling bit masks.
## Roadmap
- Add unicode support
- Improve memory footprint
- Improve code documentation
## Contributing
Contributions to Haiku-Search are welcome! If you're looking to contribute, please:
- Check out the current issues on GitHub, especially those tagged as "good first issue".
- Fork the repository and make your changes.
- Write clear, commented code.
- Ensure your changes pass all existing tests and add new tests for added functionality.
- Submit a pull request with a detailed description of your changes.
For major changes, please open an issue first to discuss what you would like to change.
Thank you for your interest in improving Haiku-Search!