Blazing fast library for fuzzy filtering, matching, and other fuzzy things!

Zadeh

Zadeh is a blazing fast library for fuzzy filtering, matching, and other fuzzy things. Zadeh is a multi-threaded library written in C++ with the goal to search through a dataset with 1M entries in a few hundred milliseconds.

features

• fuzzy filter through an array of candidates (StringArrayFilterer)
• fuzzy filter through a nested tree-like objects (TreeFilterer)
• Special treatment for strings that have separators (space , hyphen -, underline_)
• Special treatment for path-like strings (string separated by \ or //)
• give an array of indices at which the query matches the given string (match)
• score the given string against the given query (score)
• give an HTML/Markdown string that highlights the range for which the match happens (wrap)
• Allows setting the candidates only once using StringArrayFilterer and TreeFilterer classes, and then, perform filter multiple times, which is much more efficient than calling the filter or filterTree functions directly every time.
• Bindings for Nodejs (more to come)

Usage

Usage from C++

This is a header only library. Include ./src/zadeh.h and build it in your application.

examples/example1.cpp:

#include "../src/zadeh.h"  // include zadeh.h
#include <string>
#include <iostream>

using namespace std;

int main() {
  // the data to fuzzy search on
  auto data = vector<string>{"eye", "why", "bi"};

  // setup StringArrayFilterer
  auto strArrFilterer = zadeh::StringArrayFilterer<vector<string>, string>{};
  strArrFilterer.set_candidates(data);

  // filter the indices that match the query
  auto filtered_indices = strArrFilterer.filter_indices("ye");

  // print the filtered data
  for (auto ind: filtered_indices) {
    cout << data[ind] << '\n';
  }
}

Cmake file:

cmake_minimum_required(VERSION 3.17)

project(example1 LANGUAGES CXX)
add_executable(example1 ./examples/example1.cpp)
target_compile_features(example1 PRIVATE cxx_std_17)

Build:

cmake -S . -B ./build && cmake --build ./build --config Debug

Usage from Nodejs

Installation:

npm install zadeh

To import all the functions:

import * as zadeh from "zadeh"

or

const zadeh = require("zadeh")

StringArrayFilterer

StringArrayFilterer is a class that allows to set the candidates only once and perform filtering on them multiple times. This is much more efficient than calling the filter function directly.

export class StringArrayFilterer {
  /**
   * Make a `StringArrayFilterer` for the candidates that are going to be filtered.
   *
   * @param candidates An array of strings.
   */
  constructor(candidates?: Array<string>)

  /**
   * Filter the already set array of strings
   *
   * @param query A string query to match each candidate against.
   * @param options Options
   * @returns Returns an array of candidates sorted by best match against the query.
   */
  filter(query: string, options: StringArrayFilterOptions = {}): Array<string>

  /**
   * Filter the already set array of objects and get the indices of the chosen candidate
   *
   * @param query A string query to match the dataKey of each candidate against.
   * @param options Options
   * @returns Returns an array of numbers indicating the index of the chosen candidate sorted by best match against the query.
   */
  filterIndices(query: string, options: StringArrayFilterOptions = {}): Array<number>

  /**
   * Allows to set the candidates (if changed or not set in the constructor).
   *
   * @param candidates An array of strings.
   */
  setCandidates(candidates: Array<string>)
}

Example:

const { StringArrayFilterer } = require("zadeh")

// create class
const strArrFilterer = new StringArrayFilterer()

// set the candidates
strArrFilterer.setCandidates(["Call", "Me", "Maybe"])

// call filter multiple times
strArrFilterer.filter("me")
strArrFilterer.filter("all")

ObjectArrayFilterer

ObjectArrayFilterer is a class that performs filtering on an array of objects based on a string stored in the given dataKey for each object

export class ObjectArrayFilterer<DataKey extends string | number = string> {
  /**
   * Make a `ObjectArrayFilterer` for the candidates that are going to be filtered.
   *
   * @param candidates An array of objects.
   * @param dataKey The key which is indexed for each object, and filtering is done based on the resulting string
   */
  constructor(candidates?: Array<ObjectWithKey<DataKey>>, dataKey?: DataKey)

  /**
   * Filter the already set objects
   *
   * @param query A string query to match the dataKey of each candidate against.
   * @param options Options
   * @returns Returns an array of objects sorted by best match against the query.
   */
  filter(query: string, options: ObjectArrayFilterOptions = {}): Array<ObjectWithKey>

  /**
   * Filter the already set array of strings and get the indices of the chosen candidate
   *
   * @param query A string query to match each candidate against.
   * @param options Options
   * @returns Returns an array of numbers indicating the index of the chosen candidate sorted by best match against the query.
   */
  filterIndices(query: string, options: StringArrayFilterOptions = {}): Array<number>

  /**
   * Allows to set the candidates (if changed or not set in the constructor).
   *
   * @param candidates An array of objects.
   * @param dataKey The key which is indexed for each object, and filtering is done based on the resulting string
   */
  setCandidates(candidates: Array<ObjectWithKey<DataKey>>, dataKey: DataKey)
}

Example:

const { ObjectArrayFilterer } = require("zadeh")

const candidates = [
  { name: "Call", id: 1 },
  { name: "Me", id: 2 },
  { name: "Maybe", id: 3 },
]

// create a class and set the candidates
const objArrFilterer = new ObjectArrayFilterer(candidates, "name") // filter based on their name

// call filter multiple times
objArrFilterer.filter("me") // [{ name: 'Me', id: 2 }, { name: 'Maybe', id: 3}] // finds two objects
objArrFilterer.filter("all") // [{ name: 'Call', id: 1 }]

TreeFilterer

TreeFilterer is a filters the given query in the nodes of the given array of trees, and returns an array of filtered trees (or the indices of the filter candidates). A tree object is an object in which each entry stores the data in its dataKey and it has (may have) some children (with a similar structure) in its childrenKey

export class TreeFilterer<DataKey extends string, ChildrenKey extends string> {
  /**
   * The method to set an array of trees that are going to be filtered
   *
   * @param candidates An array of tree objects.
   * @param dataKey The key of the object (and its children) which holds the data (defaults to `"data"`)
   * @param childrenKey The key of the object (and its children) which hold the children (defaults to `"children"`)
   */
  constructor(
    candidates?: Tree<DataKey, ChildrenKey>[],
    dataKey: DataKey = "data",
    childrenKey: ChildrenKey = "children"
  )

  /**
   * The method to set an array of trees that are going to be filtered
   *
   * @param candidates An array of tree objects.
   * @param dataKey The key of the object (and its children) which holds the data (defaults to `"data"`)
   * @param childrenKey The key of the object (and its children) which hold the children (defaults to `"children"`)
   */
  setCandidates(
    candidates: Tree<DataKey, ChildrenKey>[],
    dataKey: DataKey = "data",
    childrenKey: ChildrenKey = "children"
  )

  /**
   * Filter the already set trees
   *
   * @param query A string query to match the dataKey of each candidate against.
   * @param options Options
   * @returns {Tree[]} An array of filtered trees. In a tree, the filtered data is at the last level (if it has
   *   children, they are not included in the filered tree)
   */
  filter(query: string, options: TreeFilterOptions = {}): Tree<DataKey, ChildrenKey>[]

  /**
   * The method to perform the filtering on the already set candidates
   *
   * @param query A string query to match the dataKey of each candidate against.
   * @param options Options
   * @returns {TreeFilterIndicesResult[]} An array candidate objects in form of `{data, index, parentIndices}` sorted by
   *   best match against the query. Each objects has the address of the object in the tree using `index` and `parent_indices`
   */
  filterIndices(query: string, options: TreeFilterOptions = {}): TreeFilterIndicesResult[]
}

Example:

const { TreeFilterer } = require("zadeh")

const treeFilterer = new TreeFilterer()

const candidates = [
  { data: "bye1", children: [{ data: "hello" }] },
  { data: "Bye2", children: [{ data: "_bye4" }, { data: "hel" }] },
  { data: "eye" },
]
treeFilterer.setCandidates(candidates, "data", "children")

treeFilterer.filter("hel")

returns

;[
  { data: "Bye2", children: [{ data: "hel" }] },
  { data: "bye1", children: [{ data: "hello" }] },
]

treeFilterer.filter("bye")

returns

;[
  { data: "bye1", children: [] },
  { data: "Bye2", children: [{ data: "_bye4" }] },
  { data: "Bye2", children: [] },
]

treeFilterer.filterIndices("bye")

returns

;[
  { data: "bye1", index: 0, parent_indices: [] },
  { data: "_bye4", index: 0, parent_indices: [1] },
  { data: "Bye2", index: 1, parent_indices: [] },
]

score

score(string, query, options = {})

Score the given string against the given query.

• string - The string the score.
• query - The query to score the string against.

const { score } = require('zadeh')

score('Me', 'me')    # 0.17099999999999999
score('Maybe', 'me') # 0.0693

match

match(string, query, options = {})

Gives an array of indices at which the query matches the given string

const { match } = require("zadeh")

match("Hello World", "he") // [0, 1]
match("Hello World", "wor") // [6, 7, 8]
match("Hello World", "elwor") // [1, 2, 6, 7, 8]

wrap

wrap (string, query, options = {})

Gives an HTML/Markdown string that highlights the range for which the match happens

wrap("helloworld", "he")

helloworld

wrap("Hello world", "he")

Hello world

options

In all the above functions, you can pass an optional object with the following keys

{
    /** only for `filter` function */
    /** The key to use when candidates is an object */
    key?: T extends string ? never : keyof T

    /** only for `filter` function */
    maxResults?: number

    /** @default false */
    allowErrors?: boolean

    /** @default true */
    usePathScoring?: boolean

    /** @default false */
    useExtensionBonus?: boolean

    pathSeparator?: '/' | '\\' | string
}

Deprecated functions

These deprecated functions are provided to support the API of fuzzaldrin and fuzzaldrin-plus. However, you should replace their usage with StringArrayFilterer or ObjectArrayFilterer classes that allow setting the candidates only once and perform filtering on those candidates multiple times. This is much more efficient than filter or filterTree functions.

filter

filter(candidates, query, options = {})

Sort and filter the given candidates by matching them against the given query.

• candidates - An array of strings or objects.
• query - A string query to match each candidate against.
• options options. You should provide a key in the options if an array of objects are passed.

Returns an array of candidates sorted by best match against the query.

const { filter } = require("zadeh")

// With an array of strings
let candidates = ["Call", "Me", "Maybe"]
let results = filter(candidates, "me") // ['Me', 'Maybe']

// With an array of objects
const candidates = [
  { name: "Call", id: 1 },
  { name: "Me", id: 2 },
  { name: "Maybe", id: 3 },
]

results = filter(candidates, "me", { key: "name" }) // [{name: 'Me', id: 2}, {name: 'Maybe', id: 3}]

Deprecation Note: use StringArrayFilterer or ObjectArrayFilterer class instead. filter internally uses this class and in each call, it sets the candidates from scratch which can slow down the process.

Comparison with other libraries

Zadeh vs fuzzaldrin and fuzzaldrin-plus

API is backward compatible with Fuzzaldrin and Fuzzaldrin-plus. Additional functions are provided to achieve better performance that could suit your needs

Zadeh achieves 10x-20x performance improvement over Fuzzaldrin plus for chromium project with 300K files. This high performance is achieved using the following techniques.

• Uses native C++ bindings that provides ~4x performance benefit.
• Use multiple threads to parallelize computation to achieve another ~4x performance benefit.
• Some miscellaneous improvements provide additional benefit.

This project potentially solves the following Atom fuzzy-finder issues if used. https://github.com/atom/fuzzy-finder/issues/271 and https://github.com/atom/fuzzy-finder/issues/88