@imranbarbhuiya/mongoose-fuzzy-searching

v3.0.5

Published

2 years ago

Mongoose fuzzy searching plugin

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imranbarbhuiya

mongoose fuzzy searching search plugin mongo mongodb

Mongoose Fuzzy Searching

Note

*Notice: This is a fork of the original Mongoose Fuzzy Searching

As that project is no longer maintained, So I'm going to work on it for my personal use. I'll recommend use the original one. Also if VassilisPallas starts maintaining the original project, I'll use that instead.

mongoose-fuzzy-searching is simple and lightweight plugin that enables fuzzy searching in documents in MongoDB. This code is based on this article.

npm: npm docs: docs

Mongoose Fuzzy Searching

Features

Creates Ngrams for the selected keys in the collection
Add fuzzySearch method on model
Work with pre-existing data

Install

Install using npm

npm i @imranbarbhuiya/mongoose-fuzzy-searching

or using yarn

yarn add @imranbarbhuiya/mongoose-fuzzy-searching

Getting started

Initialize plugin

const mongoose = require("mongoose");

return mongoose.connect(URL);

In the below example, we have a User collection and we want to make fuzzy searching in firstName and lastName.

const { Schema } = require("mongoose");
const mongoose_fuzzy_searching = require("@imranbarbhuiya/mongoose-fuzzy-searching");

const UserSchema = new Schema({
  firstName: String,
  lastName: String,
  email: String,
  age: Number,
});

UserSchema.plugin(mongoose_fuzzy_searching, {
  fields: ["firstName", "lastName"],
});
const User = mongoose.model("User", UserSchema);
module.exports = { User };

const user = new User({
  firstName: "Joe",
  lastName: "Doe",
  email: "[email protected]",
  age: 30,
});

try {
  await user.save(); // mongodb: { ..., firstName_fuzzy: [String], lastName_fuzzy: [String] }
  const users = await User.fuzzySearch("jo");

  console.log(users);
  // each user object will not contain the fuzzy keys:
  // Eg.
  // {
  //   "firstName": "Joe",
  //   "lastName": "Doe",
  //   "email": "[email protected]",
  //   "age": 30,
  //   "confidenceScore": 34.3 ($text meta score)
  // }
} catch (e) {
  console.error(e);
}

The results are sorted by the confidenceScore key. You can override this option.

try {
  const users = await User.fuzzySearch("jo").sort({ age: -1 }).exec();
  console.log(users);
} catch (e) {
  console.error(e);
}

Example with typescript

import mongoose_fuzzy_searching, {MongoosePluginModel} from "@imranbarbhuiya/mongoose-fuzzy-searching";

export interface IUser extends mongoose.Document{
  firstName: string;
  lastName: string;
}

const UserSchema<IUser> = new Schema({
  firstName: String,
  lastName: String,
});

UserSchema.plugin(mongoose_fuzzy_searching, {
  fields: ["firstName"],
});

const UserModel = mongoose.model<IUser>("User", UserSchema) as MongoosePluginModel<IUser>

Plugin options

Options can contain fields and middlewares.

Fields

Fields attribute is mandatory and should be either an array of Strings or an array of Objects.

String field

If you want to use the default options for all your fields, you can just pass them as a string.

const mongoose_fuzzy_searching = require("@imranbarbhuiya/mongoose-fuzzy-searching");

const UserSchema = new Schema({
  firstName: String,
  lastName: String,
  email: String,
});

UserSchema.plugin(mongoose_fuzzy_searching, {
  fields: ["firstName", "lastName"],
});

Object field

In case you want to override any of the default options for your arguments, you can add them as an object and override any of the values you wish. The below table contains the expected keys for this object.

| key | type | default | description | | ----------------------- | ----------------- | ----------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | name | String | null | Collection key name | | minSize | Integer | 2 | N-grams min size. Learn more about N-grams | | weight | Integer | 1 | Denotes the significance of the field relative to the other indexed fields in terms of the text search score. Learn more about index weights | | prefixOnly | Boolean | false | Only return ngrams from start of word. (It gives more precise results) | | escapeSpecialCharacters | Boolean | true | Remove special characters from N-grams. | | keys | Array[String] | null | If the type of the collection attribute is Object or [Object] (see example), you can define which attributes will be used for fuzzy searching |

Example:

const mongoose_fuzzy_searching = require('mongoose-fuzzy-searching');

const UserSchema = new Schema({
  firstName: String,
  lastName: String,
  email: String,
  content: {
      en: String,
      de: String,
      it: String
  }
  text: [
    {
      title: String,
      description: String,
      language: String,
    },
  ],
});

UserSchema.plugin(mongoose_fuzzy_searching, {
  fields: [
    {
      name: 'firstName',
      minSize: 2,
      weight: 5,
    },
    {
      name: 'lastName',
      minSize: 3,
      prefixOnly: true,
    },
    {
      name: 'email',
      escapeSpecialCharacters: false,
    },
    {
      name: 'content',
      keys: ['en', 'de', 'it'],
    },
    {
      name: 'text',
      keys: ['title', 'language'],
    },
  ],
});

Middlewares

Middlewares is an optional Object that can contain custom pre middlewares. This plugin is using these middlewares in order to create or update the fuzzy elements. That means that if you add pre middlewares, they will never get called since the plugin overrides them. To avoid that problem you can pass your custom midlewares into the plugin. Your middlewares will be called first. The middlewares you can pass are:

preSave
- stands for schema.pre("save", ...)
preInsertMany
- stands for schema.pre("insertMany", ...)
preUpdateOne
- stands for schema.pre("updateOne", ...)
preFindOneAndUpdate
- stands for schema.pre("findOneAndUpdate", ...)
preUpdateMany
- stands for schema.pre("updateMany", ...)

If you want to add any of the middlewares above, you can add it directly on the plugin.

const mongoose_fuzzy_searching = require("@imranbarbhuiya/mongoose-fuzzy-searching");

const UserSchema = new Schema({
  firstName: String,
  lastName: String,
});

UserSchema.plugin(mongoose_fuzzy_searching, {
  fields: ["firstName"],
  middlewares: {
    preSave: function () {
      // do something before the object is saved
    },
  },
});

Middlewares can also be asynchronous functions:

const mongoose_fuzzy_searching = require('mongoose-fuzzy-searching');

const UserSchema = new Schema({
  firstName: String,
  lastName: String,
});

UserSchema.plugin(mongoose_fuzzy_searching, {
  fields: ['firstName'],
  middlewares: {
    preUpdateOne: async function {
      // do something before the object is updated (asynchronous)
    }
  }
});

Query parameters

The fuzzy search query can be used either as static function, or as a helper, which let's you to chain multiple queries together. The function name in either case is surprise, surprise, fuzzySearch.

Instance method

Instance method can accept up to three parameters. The first one is the query, which can either be either a String or an Object. This parameter is required. The second parameter can either be eiter an Object that contains any additional queries (e.g. age: { $gt: 18 }), or a callback function. If the second parameter is the queries, then the third parameter is the callback function. If you don't set a callback function, the results will be returned inside a Promise.

The below table contains the expected keys for the first parameter (if is an object)

| key | type | deafult | description | | ---------- | ----------- | ----------- | --------------------------------------------------------------------------------- | | query | String | null | String to search | | minSize | Integer | 2 | N-grams min size. | | prefixOnly | Boolean | false | Only return ngrams from start of word. (It gives more precise results) the prefix | | exact | Boolean | false | Matches on a phrase, as opposed to individual terms |

Example:

/* With string that returns a Promise */
User.fuzzySearch("jo").then(console.log).catch(console.error);

/* With additional options that returns a Promise */
User.fuzzySearch({ query: "jo", prefixOnly: true, minSize: 4 })
  .then(console.log)
  .catch(console.error);

/* With additional queries that returns a Promise */
User.fuzzySearch("jo", { age: { $gt: 18 } })
  .then(console.log)
  .catch(console.error);

/* With string and a callback */
User.fuzzySearch("jo", (err, doc) => {
  if (err) {
    console.error(err);
  } else {
    console.log(doc);
  }
});

/* With additional queries and callback */
User.fuzzySearch("jo", { age: { $gt: 18 } }, (err, doc) => {
  if (err) {
    console.error(err);
  } else {
    console.log(doc);
  }
});

Working with pre-existing data

The plugin creates indexes for the selected fields. In the below example the new indexes will be firstName_fuzzy and lastName_fuzzy. Also, each document will have the fields firstName_fuzzy[String] and lastName_fuzzy[String]. These arrays will contain the anagrams for the selected fields.

const mongoose_fuzzy_searching = require("@imranbarbhuiya/mongoose-fuzzy-searching");

const UserSchema = new Schema({
  firstName: String,
  lastName: String,
  email: String,
  age: Number,
});

UserSchema.plugin(mongoose_fuzzy_searching, {
  fields: ["firstName", "lastName"],
});

In other words, this plugin creates anagrams when you create or update a document. All the pre-existing documents won't contain these fuzzy arrays, so fuzzySearch function, will not be able to find them.

Update all pre-existing documents with ngrams

In order to create anagrams for pre-existing documents, you should update each document. The below example, updates the firstName attribute to every document on the collection User.

const cursor = Model.find().cursor();
cursor.next(function (error, doc) {
  const obj = attrs.reduce((acc, attr) => ({ ...acc, [attr]: doc[attr] }), {});
  return Model.findByIdAndUpdate(doc._id, obj);
});

Delete old ngrams from all documents

In the previous example, we set firstName and lastName as the fuzzy attributes. If you remove the firstName from the fuzzy fields, the firstName_fuzzy array will not be removed by the collection. If you want to remove the array on each document you have to unset that value.

const cursor = Model.find().cursor();
cursor.next(function (error, doc) {
  const $unset = attrs.reduce(
    (acc, attr) => ({ ...acc, [`${attr}_fuzzy`]: 1 }),
    {}
  );
  return Model.findByIdAndUpdate(
    data._id,
    { $unset },
    { new: true, strict: false }
  );
});

Testing and code coverage

All tests

We use jest for all of our unit and integration tests.

npm test

Note: this will run all suites serially to avoid mutliple concurrent connection on the db.

This will run the tests using a memory database. If you wish for any reason to run the tests using an actual connection on a mongo instance, add the environment variable MONGO_DB:

docker run --name mongo_fuzzy_test -p 27017:27017 -d mongo
MONGO_DB=true npm test

Available test suites

unit tests

npm run test:unit

Integration tests

npm run test:integration

License

MIT License

Credit

Credit goes to the original package owner VassilisPallas