PhongPham
c65cc97a33
✨ MAJOR FEATURES: • Auto-zoom intelligence với smart bounds fitting • Enhanced 3D GPS markers với pulsing effects • Professional route display với 6-layer rendering • Status-based parking icons với availability indicators • Production-ready build optimizations 🗺️ AUTO-ZOOM FEATURES: • Smart bounds fitting cho GPS + selected parking • Adaptive padding (50px) cho visual balance • Max zoom control (level 16) để tránh quá gần • Dynamic centering khi không có selection 🎨 ENHANCED VISUALS: • 3D GPS marker với multi-layer pulse effects • Advanced parking icons với status colors • Selection highlighting với animation • Dimming system cho non-selected items 🛣️ ROUTE SYSTEM: • OpenRouteService API integration • Multi-layer route rendering (glow, shadow, main, animated) • Real-time distance & duration calculation • Visual route info trong popup 📱 PRODUCTION READY: • SSR safe với dynamic imports • Build errors resolved • Global deployment via Vercel • Optimized performance 🌍 DEPLOYMENT: • Vercel: https://whatever-ctk2auuxr-phong12hexdockworks-projects.vercel.app • Bundle size: 22.8 kB optimized • Global CDN distribution • HTTPS enabled 💾 VERSION CONTROL: • MapView-v2.0.tsx backup created • MAPVIEW_VERSIONS.md documentation • Full version history tracking
fast-levenshtein - Levenshtein algorithm in Javascript
An efficient Javascript implementation of the Levenshtein algorithm with locale-specific collator support.
Features
- Works in node.js and in the browser.
- Better performance than other implementations by not needing to store the whole matrix (more info).
- Locale-sensitive string comparisions if needed.
- Comprehensive test suite and performance benchmark.
- Small: <1 KB minified and gzipped
Installation
node.js
Install using npm:
$ npm install fast-levenshtein
Browser
Using bower:
$ bower install fast-levenshtein
If you are not using any module loader system then the API will then be accessible via the window.Levenshtein object.
Examples
Default usage
var levenshtein = require('fast-levenshtein');
var distance = levenshtein.get('back', 'book'); // 2
var distance = levenshtein.get('我愛你', '我叫你'); // 1
Locale-sensitive string comparisons
It supports using Intl.Collator for locale-sensitive string comparisons:
var levenshtein = require('fast-levenshtein');
levenshtein.get('mikailovitch', 'Mikhaïlovitch', { useCollator: true});
// 1
Building and Testing
To build the code and run the tests:
$ npm install -g grunt-cli
$ npm install
$ npm run build
Performance
Thanks to Titus Wormer for encouraging me to do this.
Benchmarked against other node.js levenshtein distance modules (on Macbook Air 2012, Core i7, 8GB RAM):
Running suite Implementation comparison [benchmark/speed.js]...
>> levenshtein-edit-distance x 234 ops/sec ±3.02% (73 runs sampled)
>> levenshtein-component x 422 ops/sec ±4.38% (83 runs sampled)
>> levenshtein-deltas x 283 ops/sec ±3.83% (78 runs sampled)
>> natural x 255 ops/sec ±0.76% (88 runs sampled)
>> levenshtein x 180 ops/sec ±3.55% (86 runs sampled)
>> fast-levenshtein x 1,792 ops/sec ±2.72% (95 runs sampled)
Benchmark done.
Fastest test is fast-levenshtein at 4.2x faster than levenshtein-component
You can run this benchmark yourself by doing:
$ npm install
$ npm run build
$ npm run benchmark
Contributing
If you wish to submit a pull request please update and/or create new tests for any changes you make and ensure the grunt build passes.
See CONTRIBUTING.md for details.
License
MIT - see LICENSE.md