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.
mingo
MongoDB query language for in-memory objects
Install
$ npm install mingo
Features
- Supports Dot Notation for both
<array>.<index>
and <document>.<field>
selectors - Query and Projection Operators
- Aggregation Framework Operators
- Support for adding custom operators using
mingo.addOperators
- Match against user-defined types
- Support for aggregaion variables
- ES6 module compatible
- Support integrating with custom collections via mixin
- Query filtering and aggregation streaming.
For documentation on using query operators see mongodb
Documentation
Usage
import mingo from 'mingo'
const mingo = require('mingo')
Change in 4.x.x
The $where
operator is not loaded by default and must be explicitly registered if required. See documentation for preferred alternatives.
Changes in 3.0.0
Default exports and operators
The default export of the main module only includes Aggregator
, Query
, aggregate()
, find()
, and remove()
.
Only Query and Projection operators are loaded by default when using the main module.
This is done using the side-effect module mingo/init/basic
, and also automatically includes pipeline operators $project
, $skip
, $limit
, and $sort
.
If your application uses most of the available operators or you do not care about bundle size, you can load all operators as shown below.
import 'mingo/init/system'
Or from the node CLI
node -r 'mingo/init/system' myscript.js
Custom Operators
The addOperators
function for registering custom operators and helper constants have been moved to mingo/core
.
The constants OP_XXX
have been deprecated and replace with an enum type OperatorType
also in mingo/core
.
The values defined include;
ACCUMULATOR
EXPRESSION
PIPELINE
PROJECTION
QUERY
Lastly, the function argument to addOperators(operatorType, fn)
now accepts an object with the these two internal functions;
computeValue(obj: AnyVal, expr: AnyVal, operator: string, options?: ComputeOptions): AnyVal
resolve(obj: AnyVal, selector: string, options?: ResolveOptions): AnyVal
Any extra utility may be imported directly from the specific module.
Importing submodules
Submodule imports are supported for both ES6 and ES5.
The following two examples are equivalent.
ES6
This work natively in typescript since it knows how to load commonJS modules as ES6.
You may optionally install the esm module to use this syntax.
import { $unwind } from 'mingo/operators/pipeline'
ES5
Unlike the ES6 version, it is necessary to specify the operator module in the path to avoid loading any extras
const $unwind = require('mingo/operators/pipeline/unwind').$unwind
Configuration
To support tree-shaking, you may import and register specific operators that will be used in your application.
import { useOperators, OperatorType } from 'mingo/core'
import { $trunc } from 'mingo/operators/expression'
import { $bucket } from 'mingo/operators/pipeline'
useOperators(OperatorType.EXPRESSION, { $trunc, $floor })
useOperators(OperatorType.PIPELINE, { $bucket })
Using query object to test objects
import { Query } from 'mingo'
let query = new Query({
type: "homework",
score: { $gte: 50 }
});
query.test(doc)
Searching and Filtering
import { Query } from 'mingo'
let criteria = { score: { $gt: 10 } }
let query = new Query(criteria)
let cursor = query.find(collection)
cursor.sort({student_id: 1, score: -1})
.skip(100)
.limit(100)
cursor.count()
while (cursor.hasNext()) {
console.log(cursor.next())
}
for (let value of cursor) {
console.log(value)
}
cursor.all()
Aggregation Pipeline
import { Aggregator } from 'mingo/aggregator'
import { useOperators, OperatorType } from 'mingo/core'
import { $match, $group } from 'mingo/operators/pipeline'
import { $min } from 'mingo/operators/accumulator'
useOperators(OperatorType.PIPELINE, { $match, $group })
useOperators(OperatorType.ACCUMULATOR, { $min })
let agg = new Aggregator([
{'$match': { "type": "homework"}},
{'$group': {'_id':'$student_id', 'score':{$min:'$score'}}},
{'$sort': {'_id': 1, 'score': 1}}
])
let stream = agg.stream(collection)
let result = agg.run(collection)
Benefits
- Better alternative to writing custom code for transforming collection of objects
- Quick validation of MongoDB queries without the need for a database
- MongoDB query language is among the best in the market and is well documented
Contributing
- Squash changes into one commit
- Run
npm test
to build and execute unit tests - Submit pull request
License
MIT