Manual Reference Source

MiniSearch MiniSearch

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MiniSearch is a tiny but powerful in-memory fulltext search engine for JavaScript. It is respectful of resources, and it can comfortably run both in Node and in the browser.

Try out the demo application.

Use case

MiniSearch addresses use cases where full-text search features are needed (e.g. prefix search, fuzzy search, boosting of fields), but the data to be indexed can fit locally in the process memory. While you may not index the whole Wikipedia with it, there are surprisingly many use cases that are served well by MiniSearch. By storing the index in local memory, MiniSearch can work offline, and can process queries quickly, without network latency.

A prominent use-case is search-as-you-type features in web and mobile applications, where keeping the index on the client-side enables fast and reactive UI, removing the need to make requests to a search server.



With npm:

npm install --save minisearch

With yarn:

yarn add minisearch

Then require or import it in your project.

Alternatively, to manually build the library, clone the repository and run yarn build (or yarn build-minified for a minified version + source maps). The compiled source will be created in the dist folder.


Basic usage

// A collection of documents for our examples
const documents = [
  { id: 1, title: 'Moby Dick', text: 'Call me Ishmael. Some years ago...' },
  { id: 2, title: 'Zen and the Art of Motorcycle Maintenance', text: 'I can see by my watch...' },
  { id: 3, title: 'Neuromancer', text: 'The sky above the port was...' },
  { id: 4, title: 'Zen and the Art of Archery', text: 'At first sight it must seem...' },
  // ...and more

let miniSearch = new MiniSearch({ fields: ['title', 'text'] })

// Index all documents

// Search with default options
let results ='zen art motorcycle')
// => [ { id: 2, score: 2.77258, match: { ... } }, { id: 4, score: 1.38629, match: { ... } } ]

Search options

MiniSearch supports several options for more advanced search behavior:

// Search only specific fields'zen', { fields: ['title'] })

// Boost some fields (here "title")'zen', { boost: { title: 2 } })

// Prefix search (so that 'moto' will match 'motorcycle')'moto', { prefix: true })

// Fuzzy search, in this example, with a max edit distance of 0.2 * term length,
// rounded to nearest integer. The mispelled 'ismael' will match 'ishmael'.'ismael', { fuzzy: 0.2 })

// You can set the default search options upon initialization
miniSearch = new MiniSearch({
  fields: ['title', 'text'],
  searchOptions: {
    boost: { title: 2 },
    fuzzy: 0.2

// It will now by default perform fuzzy search and boost "title":'zen and motorcycles')

Auto suggestions

MiniSearch can suggest search queries given an incomplete query:

miniSearch.autoSuggest('zen ar')
// => [ { suggestion: 'zen archery art', terms: [ 'zen', 'archery', 'art' ], score: 1.73332 },
//      { suggestion: 'zen art', terms: [ 'zen', 'art' ], score: 1.21313 } ]

The autoSuggest method takes the same options as the search method, so you can get suggestions for misspelled words using fuzzy search:

miniSearch.autoSuggest('neromancer', { fuzzy: 0.2 })
// => [ { suggestion: 'neuromancer', terms: [ 'neuromancer' ], score: 1.03998 } ]

Suggestions are ranked by the relevance of the documents that would be returned by that search.


By default, documents are tokenized by splitting on non-alphanumeric characters (accented characters and other diacritics are considered alphanumeric). The tokenization logic can be easily changed by passing a custom tokenizer function as the tokenize option:

// Tokenize splitting by hyphen
let miniSearch = new MiniSearch({
  fields: ['title', 'text'],
  tokenize: (string, _fieldName) => string.split('-')

Upon search, the same tokenization is used by default, but it is possible to pass a tokenize search option in case a different search-time tokenization is necessary:

// Tokenize splitting by hyphen
let miniSearch = new MiniSearch({
  fields: ['title', 'text'],
  tokenize: (string) => string.split('-'), // indexing tokenizer
  searchOptions: {
    tokenize: (string) => string.split(/[\s-]+/) // search query tokenizer

The default tokenizer can be obtained by calling MiniSearch.getDefault('tokenize').

Term processing

Terms are downcased by default. No stemming is performed, and no stop-word list is applied, but single-character words are excluded. To customize how the terms are processed upon indexing, for example to normalize them, filter them, or to apply stemming, the processTerm option can be used:

let stopWords = new Set(['and', 'or', 'to', 'in', 'a', 'the', /* ...and more */ ])

const removeAccents = (term) =>
  term.replace(/[àá]/, 'a')
      .replace(/[èé]/, 'e')
      .replace(/[ìí]/, 'i')
      .replace(/[òó]/, 'o')
      .replace(/[ùú]/, 'u')

// Perform custom term processing (here removing accents, downcasing, and
// discarding stop words)
let miniSearch = new MiniSearch({
  fields: ['title', 'text'],
  processTerm: (term, _fieldName) =>
    stopWords.has(term) ? null : removeAccents(term.toLowerCase())

By default, the same processing is applied to search queries. In order to apply a different processing to search queries, supply a processTerm search option:

let miniSearch = new MiniSearch({
  fields: ['title', 'text'],
  processTerm: (term) =>
    stopWords.has(term) ? null : removeAccents(term.toLowerCase()), // index term processing
  searchOptions: {
    processTerm: (term) => removeAccents(term.toLowerCase()) // search query processing

The default term processor can be obtained by calling MiniSearch.getDefault('processTerm').

API Documentation

Refer to the API documentation for details about configuration options and methods.

Browser compatibility

MiniSearch natively supports all modern browsers implementing JavaScript standards, but requires a polyfill when used in Internet Explorer, as it makes use functions like Object.entries, Array.includes, and Array.from, which are standard but not available on older browsers. The @babel/polyfill is one such polyfill that can be used to provide those functions.


Contributions to MiniSearch are welcome! Please read the contributions guidelines. Reading the design document is also useful to understand the project goals and the technical implementation.