synchronous-autocomplete

synchronous-autocomplete

Fast, simple autocompletion. Supports autocompletion and Levenshtein-based fuzzy search. Uses precomputed indexes to be fast.

Installing

npm install synchronous-autocomplete

Usage

Let's build a simple search for our fruit stand. We assign a weight property to each of them because some are bought more often and we want to push their ranking in the search results.

const items = [ {
	id: 'apple',
	name: 'Juicy sour Apple.',
	weight: 3
}, {
	id: 'banana',
	name: 'Sweet juicy Banana!',
	weight: 2
}, {
	id: 'pome',
	name: 'Sour Pomegranate',
	weight: 5
} ]

Let's understand the terminology used by this tool:

• item: A thing to search for. In our example, apple, banana and pomegranate each are an item.
• weight: How important an item is.
• token: A word from the fully normalized item name. For example, to find an item named Hey There!, you may process its name into the tokens hey & there.
• fragment: A word from the normalized search query, which may partially match a token. E.g. the fragment ther (from the search query Hey Ther) partially matches the token there.
• relevance: How well an item fits to the search query.
• score: A combination of an item's weight and relevance. Used to rank search results.

In order to be as fast and disk-space-efficient as possible, synchronous-autocomplete requires five indexes to be prebuilt from the list of items. Check the example code for more details on how to build them. For our example, they would look like this:

const tokens = { // internal item IDs, by token
	juicy: [0, 1],
	sour: [0, 3],
	apple: [0],
	sweet: [1],
	banana: [1],
	pomegranate: [3]
}
const weights = [ // item weights, by internal item ID
	3, // apple
	2, // banana
	5 // pome
]
const nrOfTokens = [ // nr of tokens, by internal item ID
	3, // apple
	3, // banana
	2 // pome
]
const scores = { // "uniqueness" of each token, by token
	juicy: 2 / 3, // 2 out of 3 items have the token "juicy"
	sour: 2 / 3,
	apple: 1 / 3,
	sweet: 1 / 3,
	banana: 1 / 3,
	pomegranate: 1 / 3
}
// In order to create smaller search indexes, we use numerical item IDs
// internally and maintain a mapping to their "real"/original IDs.
const originalIds = [
	'apple',
	'banana',
	'pome'
]

As the last step, we must define a function that normalizes search input into a list of fragments. Consider using this simple function:

const normalize = require('normalize-for-search')

const tokenize = (str) => {
	return normalize(str).replace(/[^\w\s]/g, '').split(/\s+/g)
}

Now, we can query our index:

const create = require('synchronous-autocomplete')

const autocomplete = create(tokens, scores, weights, nrOfTokens, originalIds, tokenize)

autocomplete('bana')
// [ {
//	id: 'banana',
//	relevance: 0.66667,
//	score: 0.83995
// } ]

autocomplete('sour')
// [ {
//	id: 'pomegranate',
//	relevance: 1.83333,
//	score: 3.13496
// }, {
//	id: 'apple',
//	relevance: 1.22222,
//	score: 1.76275
// } ]

autocomplete('aplle', 3, true) // note the typo
// [ {
//	id: 'apple',
//	relevance: 0.22222,
//	score: 0.3205
// } ]

API

const autocomplete = create(tokens, scores, weights, nrOfTokens, originalIds, tokenize)
autocomplete(query, limit = 6, fuzzy = false, completion = true)

• tokens must be an object with an array of internal item IDs per token.
• scores must be an object with a token score per token.
• weights must be an array with an item weight per internal item ID.
• nrOfTokens must be an array with the number of tokens per internal item ID.
• originalIds must be an array with the (real) item ID per internal item ID.
• tokenize must be a function that, given a search query, returns an array of fragments.

Contributing

If you have a question or have difficulties using synchronous-autocomplete, please double-check your code and setup first. If you think you have found a bug or want to propose a feature, refer to the issues page.