mingo

What is mingo?

Mingo is a JavaScript library that provides MongoDB-like query and aggregation capabilities for in-memory data processing. It allows you to filter, sort, group, and transform data collections using a syntax similar to MongoDB queries.

What are mingo's main functionalities?

Querying

This feature allows you to perform complex queries on your data collections. The example demonstrates how to filter a list of people to find those older than 26.

const mingo = require('mingo');
const data = [
  { name: 'John', age: 25 },
  { name: 'Jane', age: 30 },
  { name: 'Jim', age: 27 }
];
const query = new mingo.Query({ age: { $gt: 26 } });
const result = query.find(data).all();
console.log(result); // Output: [ { name: 'Jane', age: 30 }, { name: 'Jim', age: 27 } ]

Aggregation

This feature allows you to perform aggregation operations on your data collections. The example demonstrates how to calculate the average salary of people older than 26.

const mingo = require('mingo');
const data = [
  { name: 'John', age: 25, salary: 50000 },
  { name: 'Jane', age: 30, salary: 60000 },
  { name: 'Jim', age: 27, salary: 55000 }
];
const pipeline = [
  { $match: { age: { $gt: 26 } } },
  { $group: { _id: null, averageSalary: { $avg: '$salary' } } }
];
const result = mingo.aggregate(data, pipeline);
console.log(result); // Output: [ { _id: null, averageSalary: 57500 } ]

Projection

This feature allows you to project specific fields from your data collections. The example demonstrates how to retrieve only the 'name' and 'age' fields from a list of people.

const mingo = require('mingo');
const data = [
  { name: 'John', age: 25, salary: 50000 },
  { name: 'Jane', age: 30, salary: 60000 },
  { name: 'Jim', age: 27, salary: 55000 }
];
const query = new mingo.Query({});
const result = query.find(data).project({ name: 1, age: 1 }).all();
console.log(result); // Output: [ { name: 'John', age: 25 }, { name: 'Jane', age: 30 }, { name: 'Jim', age: 27 } ]

Other packages similar to mingo

lodash

Lodash is a JavaScript utility library that provides a wide range of functions for manipulating arrays, objects, and other data structures. While it does not offer MongoDB-like query syntax, it provides similar functionalities for filtering, sorting, and transforming data collections.

underscore

Underscore is another JavaScript utility library similar to Lodash. It provides a set of utility functions for working with arrays, objects, and other data types. Like Lodash, it does not offer MongoDB-like query syntax but provides similar data manipulation capabilities.

json-query

json-query is a library for querying JSON data structures using a simple query language. It provides functionalities for filtering and transforming JSON data, similar to Mingo, but with a different query syntax.

README

Mingo

JavaScript implementation of MongoDB query language

Mingo harnesses the power of MongoDB-style queries and allows direct querying of in-memory javascript objects in both client and server-side environments.

Dependencies

underscore

Installing

$ npm install mingo

In browser

<!-- DO NOT FORGET Underscore -->
<script type="text/javascript" src="./underscore-min.js"></script>
<script type="text/javascript" src="./mingo.min.js"></script>

Features

• Supports Dot Notation for both '<array>.<index>' and '<document>.<field>' selectors
• Query and Projection Operators
  • Array Operators ($all, $elemMatch, $size)
  • Comparisons Operators ($gt, $gte, $lt, $lte, $ne, $nin, $in)
  • Element Operators ($exists, $type)
  • Evaluation Operators ($regex, $mod, $where)
  • Logical Operators ($and, $or, $nor, $not)
• Aggregation Framework Operators
  • Pipeline Operators ($group, $match, $project, $sort, $limit, $unwind, $skip)
  • Group Operators ($addToSet, $sum, $max, $min, $avg, $push, $first, $last)
  • Projection Operators ($elemMatch, $slice)
  • Arithmetic Operators ($add, $divide, $mod, $multiply, $subtract)
  • Array Operators ($size)
  • Boolean Operators ($and, $or, $not)
  • Comparisons Operators ($cmp, $gt, $gte, $lt, $lte, $ne, $nin, $in)
  • Conditional Operators ($cond, $ifNull)
  • Date Operators ($dayOfYear, $dayOfMonth, $dayOfWeek, $year, $month, $week, $hour, $minute, $second, $millisecond, $dateToString)
  • Literal Operators ($literal)
  • Set Operators ($setEquals, $setIntersection, $setDifference, $setUnion, $setIsSubset, $anyElementTrue, $allElementsTrue)
  • String Operators ($strcasecmp, $concat, $substr, $toLower, $toUpper)
  • Variable Operators ($map, $let)
• Support for custom operators
• BackboneJS Integration
• Match against user-defined types
• JSON stream filtering and projection. NodeJS only

For documentation on using query operators see mongodb

Usage

var Mingo = require('mingo');
// or just access *Mingo* global in browser

// setup the key field for your collection
Mingo.setup({
    key: '_id' // default
});

// create a query with criteria
// find all grades for homework with score >= 50
var query = new Mingo.Query({
    type: "homework",
    score: { $gte: 50 }
});

Searching and Filtering

// filter collection with find()
var cursor = query.find(collection);

// shorthand with query criteria
// cursor = Mingo.find(collection, criteria);

// sort, skip and limit by chaining
cursor.sort({student_id: 1, score: -1})
    .skip(100)
    .limit(100);

// count matches
cursor.count();

// iterate cursor
// iteration is forward only
while (cursor.hasNext()) {
    console.log(cursor.next());
}

// use first(), last() and all() to retrieve matched objects
cursor.first();
cursor.last();
cursor.all();

// Filter non-matched objects (
var result = query.remove(collection);

Aggregation Pipeline

var agg = new Mingo.Aggregator([
    {'$match': { "type": "homework"}},
    {'$group':{'_id':'$student_id', 'score':{$min:'$score'}}},
    {'$sort':{'_id': 1, 'score': 1}}
]);

var result = agg.run(collection);

// shorthand
result = Mingo.aggregate(
    collection,
    [
        {'$match': { "type": "homework"}},
        {'$group':{'_id':'$student_id', 'score':{$min:'$score'}}},
        {'$sort':{'_id': 1, 'score': 1}}
    ]
);

Stream Filtering

var JSONStream = require('JSONStream'),
    fs = require('fs'),
    Mingo = require('mingo');

var query = new Mingo.Query({
  scores: { $elemMatch: {type: "exam", score: {$gt: 90}} }
}, {name: 1});

file = fs.createReadStream('./students.json');

var qs = query.stream();
qs.on('data', function (data) {
    console.log(data); // log filtered outputs
    // ex. { name: 'Dinah Sauve', _id: 49 }
});

file.pipe(JSONStream.parse("*")).pipe(qs);

Backbone Integration

// using with Backbone
var Grades = Backbone.Collection.extend(Mingo.CollectionMixin);

var grades = new Grades(collection);

// find students with grades less than 50 in homework or quiz
// sort by score ascending and type descending
cursor = grades.query({
    $or: [{type: "quiz", score: {$lt: 50}}, {type: "homework", score: {$lt: 50}}]
}).sort({score: 1, type: -1}).limit(10);

// print grade with the lowest score
cursor.first();

Documentation

• API
• Custom Operators

TODO

• Geospatial Query Operators ($geoWithin, $geoIntersects, $near, $nearSphere)
• Geometry Specifiers ($geometry, $maxDistance, $center, $centerSphere, $box, $polygon)

License

MIT

Changelog

v0.6.4 / 2016-05-19

• Support matching against user-defined types. See #22