flesch-kincaid
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2.0.1 • Public • Published

flesch-kincaid

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Formula to detect the grade level of text according to the Flesch–Kincaid grade level.

Contents

What is this?

This package exposes an algorithm to detect ease of reading of English texts.

When should I use this?

You’re probably dealing with natural language, and know you need this, if you’re here!

This algorithm is based on syllables, whereas some others are not, which means it’s tougher to get right and slower to calculate. See syllable for detecting syllables.

Install

This package is ESM only. In Node.js (version 14.14+, 16.0+), install with npm:

npm install flesch-kincaid

In Deno with esm.sh:

import {fleschKincaid} from 'https://esm.sh/flesch-kincaid@2'

In browsers with esm.sh:

<script type="module">
  import {fleschKincaid} from 'https://esm.sh/flesch-kincaid@2?bundle'
</script>

Use

import {fleschKincaid} from 'flesch-kincaid'

// For “The Australian platypus is seemingly a hybrid of a mammal and reptilian
// creature.” (1 sentence, 13 words, 26 syllables).
fleschKincaid({sentence: 1, word: 13, syllable: 26})
// => 13.08

API

This package exports the identifier fleschKincaid. There is no default export.

fleschKincaid(counts)

Given an object containing the number of words (word), the number of sentences (sentence), and the number of syllables (syllable) in a document, returns the U.S. grade level associated with the document.

counts

Counts from input document.

counts.sentence

Number of sentences (number, required).

counts.word

Number of words (number, required).

counts.syllable

Number of syllables (number, required).

Returns

Grade level associated with the document (number).

👉 Note: values can theoretically start at -3.40 and end at Infinity.

Types

This package is fully typed with TypeScript. It exports the additional type Counts.

Compatibility

This package is at least compatible with all maintained versions of Node.js. As of now, that is Node.js 14.14+ and 16.0+. It also works in Deno and modern browsers.

Related

  • automated-readability — uses character count instead of error-prone syllable parser
  • coleman-liau — uses letter count instead of an error-prone syllable parser
  • dale-chall-formula — uses a dictionary; suited for higher reading levels
  • flesch — uses syllable count
  • gunning-fog — uses syllable count, needs POS-tagging and NER
  • smog-formula — like gunning-fog-index, without needing advanced NLP
  • spache-formula — uses a dictionary, suited for lower reading levels

Contribute

Yes please! See How to Contribute to Open Source.

Security

This package is safe.

License

MIT © Titus Wormer

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Install

npm i flesch-kincaid

Weekly Downloads

740

Version

2.0.1

License

MIT

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Collaborators

  • wooorm
  • zeke