JSPM

  • ESM via JSPM
  • ES Module Entrypoint
  • Export Map
  • Keywords
  • License
  • Repository URL
  • TypeScript Types
  • README
  • Created
  • Published
  • Downloads 858
  • Score
    100M100P100Q103779F
  • License MIT

🚀 the super fast and easy didyoumean which use dice-coefficient and levenshtein

Package Exports

  • didyoumean3

This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (didyoumean3) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

didyoumean3

NPM

Greenkeeper badge Build Status Codecov David npm npm GitHub top language NPM

notice: Covers most situations and still needs to be optimized, i will do better!

Features

  • Built-in fastest levenshtein algorithm
  • Support custom return results
  • Typescript
  • Super fast
  • More flexible configuration
  • Super small (production.min.js < 2kb) and tree shaking! more info
  • Support emoji or diacritics

Usage

install

npm i didyoumean3

use case

  • base use
import didyoumean3 from 'didyoumean3'
// or
const { didyoumean3 } = require('didyoumean3');

let input = 'insargrm'
let list = [
  'facebook', 'INSTAgram', ' in stagram', 'baidu', 'twitter', 'wechat', 'instagram', 'linkedin'
]

didyoumean3(input, list)

// will output:
// {
//   winner: 'instagram',
//   matches: [
//     {
//       score: 8,
//       target: 'facebook',
//     },
//     {
//       score: 3,
//       target: 'instagram',
//     },
//     {
//       score: 7,
//       target: 'linkedin',
//     },
//     // ...
//   ],
// }
  • optional configuration

didyoumea3 has some built-in string formatting configuration items:

  • ignore: default is false, Case-insensitive
  • trim: default is true, will use string.trim format the string
  • trimAll: defalut is false, will trim with regexp /\s+/g
  • diacritics: default is false, just 'café' -> 'café'.normalize()
  • normalize: customize the formatting function by yourself

🔥If these parameters don't meet your requirements, you can customize the formatting function through normalize.

🔥When using the custom normalize function, the above string formatting configurations will fail

didyoumean3(input, target, { normalize: (s: string) => s.trim() } );
  • val: sometimes, you need to match against a list of object. you can use val to get the target string out.
let l = [
  { id: 'facebook' },
  { id: 'baidu' },
  { id: 'twitter' },
  { id: 'INSTAgram' },
  { id: ' in stagram' },
  { id: 'wechat' },
  { id: 'instagram' },
  { id: 'linkedin' },
];

didyoumean3(input, target, { val: item => item.id } );
  • result: Customize the structure of the results you want to return
type Res = null | { matches: any[], winner: string }
const result = (res: Res) => {
  if (!res) return 'nothing matched!'
  else return res
}

didyoumean3(input, target, { result } );
  • filter: You can filter the results you want, such as those with a score greater than 5
let i2 = 'insargrm';
let l2 = ['facebook', 'instagram', 'linkedin'];
expect(
  didyoumean3(i2, l2, { filter: (score: number, item: any) => score >= 7 })
    ?.matches.length
).toBe(2); 

benchmark

didyoumean x 194,593 ops/sec ±1.07% (84 runs sampled)
didyoumean2 x 311,318 ops/sec ±0.63% (90 runs sampled)
didyoumean3 x 510,067 ops/sec ±0.48% (84 runs sampled)
Fastest is didyoumean3-leven

contributors

nobody now.

Both issure and pr are welcome!

license

MIT