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https://github.com/foray1010/didyoumean2
a library for matching human-quality input to a list of potential matches using the Levenshtein distance algorithm
https://github.com/foray1010/didyoumean2
edit-distance fuzzy-search levenshtein-distance spelling-correction typescript
Last synced: about 2 months ago
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a library for matching human-quality input to a list of potential matches using the Levenshtein distance algorithm
- Host: GitHub
- URL: https://github.com/foray1010/didyoumean2
- Owner: foray1010
- License: mit
- Created: 2016-01-02T08:45:12.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2024-04-13T05:06:37.000Z (5 months ago)
- Last Synced: 2024-04-13T22:19:35.621Z (5 months ago)
- Topics: edit-distance, fuzzy-search, levenshtein-distance, spelling-correction, typescript
- Language: TypeScript
- Homepage:
- Size: 8.09 MB
- Stars: 95
- Watchers: 4
- Forks: 5
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
README
# didyoumean2
[](https://circleci.com/gh/foray1010/didyoumean2/tree/master)
[](https://codecov.io/gh/foray1010/didyoumean2)
[](https://www.npmjs.com/package/didyoumean2)
[](https://www.npmjs.com/package/didyoumean2)
[](https://www.npmjs.com/package/didyoumean2)
`didyoumean2` is a library for matching human-quality input to a list of potential matches using the [Levenshtein distance algorithm](https://en.wikipedia.org/wiki/Levenshtein_distance).
It is inspired by [didyoumean.js](https://github.com/dcporter/didyoumean.js).
## Why reinventing the wheel
1. Based on [fastest-levenshtein](https://github.com/ka-weihe/fastest-levenshtein), the fastest JS implementation of the [Levenshtein distance algorithm](https://en.wikipedia.org/wiki/Levenshtein_distance)
1. ~100% faster than [didyoumean.js](https://github.com/dcporter/didyoumean.js)
1. Well tested with 100% coverage
1. Static type checking with [TypeScript](https://github.com/Microsoft/TypeScript)
1. More control on what kind of matches you want to return
1. Support matching object's `path` instead of just `key`
## Installation
```sh
npm install didyoumean2
```
```js
const didYouMean = require('didyoumean2').default
// or if you are using TypeScript or ES module
import didYouMean from 'didyoumean2'
// you can also access to Enums via:
const {
default: didYouMean,
ReturnTypeEnums,
ThresholdTypeEnums,
} = require('didyoumean2')
// or
import didYouMean, { ReturnTypeEnums, ThresholdTypeEnums } from 'didyoumean2'
```
## Development Setup
We are using [corepack](https://nodejs.org/api/corepack.html) to manage the `yarn` version
```bash
corepack enable
```
## Usage
```js
didYouMean(input, matchList[, options])
```
- `input {string}`: A string that you are not sure and want to match with `matchList`
- `matchList {Object[]|string[]}`: A List for matching with `input`
- `options {Object}`(optional): An options that allows you to modify the behavior
- `@return {Array|null|Object|string}`: A list of or single matched result(s), return object if `match` is `{Object[]}`
### Options
#### `caseSensitive {boolean}`
- default: `false`
- Perform case-sensitive matching
#### `deburr {boolean}`
- default: `true`
- Perform [combining diacritical marks](https://en.wikipedia.org/wiki/Combining_Diacritical_Marks) insensitive matching
- Refer to [lodash \_.deburr](https://lodash.com/docs#deburr) for how it works
#### `matchPath {Array}`
- default: `[]`
- If your `matchList` is an array of object, you must use `matchPath` to point to the string that you want to match
- Refer to [ramda R.path](https://ramdajs.com/docs/#path) for how to define the path, e.g. `['obj', 'array', 0, 'key']`
#### `returnType {string}`
- default: `ReturnTypeEnums.FIRST_CLOSEST_MATCH`
| returnType | Description |
| ------------------------------------- | ----------------------------------------------------------------- |
| `ReturnTypeEnums.ALL_CLOSEST_MATCHES` | Return all matches with the closest value to the `input` in array |
| `ReturnTypeEnums.ALL_MATCHES` | Return all matches in array |
| `ReturnTypeEnums.ALL_SORTED_MATCHES` | Return all matches in array, sorted from closest to furthest |
| `ReturnTypeEnums.FIRST_CLOSEST_MATCH` | Return first match from `ReturnTypeEnums.ALL_CLOSEST_MATCHES` |
| `ReturnTypeEnums.FIRST_MATCH` | Return first match (**FASTEST**) |
#### `threshold {integer|number}`
- depends on `thresholdType`
- type: `{number}` (`similarity`) or `{integer}` (`edit-distance`)
- default: `0.4` (`similarity`) or `20` (`edit-distance`)
- If the result is larger (`similarity`) or smaller (`edit-distance`) than or equal to the `threshold`, that result is matched
#### `thresholdType {string}`
- default: `ThresholdTypeEnums.SIMILARITY`
| thresholdType | Description |
| ---------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------ |
| `ThresholdTypeEnums.EDIT_DISTANCE` | Refer to [Levenshtein distance algorithm](https://en.wikipedia.org/wiki/Levenshtein_distance), must be `integer`, lower value means more similar |
| `ThresholdTypeEnums.SIMILARITY` | `l = max(input.length, matchItem.length), similarity = (l - editDistance) / l`, `number` from `0` to `1`, higher value means more similar |
#### `trimSpaces {boolean}`
- default: `true`
- Remove noises when matching
- Trim all starting and ending spaces, and concatenate all continuous spaces to one space
## Test
**_Before all:_**
```sh
npm install -g yarn
yarn install
```
Unit test and coverage:
```sh
yarn test
```
Linter:
```sh
yarn lint
```