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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.
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 } ]
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 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 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.
JavaScript implementation of MongoDB query language
$ npm install mingo
In browser
<script type="text/javascript" src="./mingo-min.js"></script>
var Mingo = require('mingo');
// or just access *Mingo* global in browser
var Mingo = require('mingo');
// 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: { $gte: 50 }
});
// filter collection with find()
var cursor = query.find(collection);
// shorthand with query criteria
// cursor = Mingo.find(collection, criteria);
// sort, skip and limit by chaining
cursor.sort({student_id: 1, score: -1})
.skip(100)
.limit(100);
// count matches
cursor.count();
// iterate cursor
// iteration is forward only
while (cursor.hasNext()) {
console.log(cursor.next());
}
// use first(), last() and all() to retrieve matched objects
cursor.first();
cursor.last();
cursor.all();
// Filter non-matched objects
var result = query.remove(collection);
a.pipe(query).pipe(process.stdout);
var agg = new Mingo.Aggregator([
{'$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}}
]
);
var JSONStream = require('JSONStream'),
fs = require('fs'),
Mingo = require('mingo');
var query = Mingo.compile({
scores: { $elemMatch: {type: "exam", score: {$gt: 90}} }
}, {name: 1});
// ex. [
// { "_id" : 11, "name" : "Marcus Blohm", "scores" : [
// { "type" : "exam", "score" : 78.42617835651868 },
// { "type" : "quiz", "score" : 82.58372817930675 },
// { "type" : "homework", "score" : 87.49924733328717 },
// { "type" : "homework", "score" : 15.81264595052612 } ]
// },
// ...
// ]
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);
// 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();
For documentation on using query operators see mongodb
Creates a Mingo.Query
object with the given query criteria
test(obj)
Returns true if the object passes the query criteria, otherwise false.find(collection, [projection])
Performs a query on a collection and returns a Mingo.Cursor
object.remove(collection)
Remove matching documents from the collection and return the remainderstream()
Return a Mingo.Stream
to filter and transform JSON objects from a readable stream. NodeJS onlyCreates a Mingo.Aggregator
object with a collection of aggregation pipeline expressions
run()
Apply the pipeline operations over the collection by order of the sequence addedCreates a Mingo.Cursor
object which holds the result of applying the query over the collection
all()
Returns all the matched documents in a cursor as a collection.first()
Returns the first documents in a cursor.last()
Returns the last document in a cursorcount()
Returns a count of the documents in a cursor.limit(n)
Constrains the size of a cursor's result set.skip(n)
Returns a cursor that begins returning results only after passing or skipping a number of documents.sort(modifier)
Returns results ordered according to a sort specification.next()
Returns the next document in a cursor.hasNext()
Returns true if the cursor has documents and can be iterated.max(expression)
Specifies an exclusive upper index bound for a cursormin(expression)
Specifies an inclusive lower index bound for a cursor.map(callback)
Applies a function to each document in a cursor and collects the return values in an array.forEach(callback)
Applies a JavaScript function for every document in a cursor.A Transform stream that can be piped from/to any readable/writable JSON stream.
A mixin object for Backbone.Collection
which adds query()
and aggregate()
methods
query(criteria)
Performs a query on the collection and returns a Mingo.Cursor
object.aggregate(expressions)
Performs aggregation operation using the aggregation pipeline.Performs a query on a collection and returns a Mingo.Cursor
object.
Returns the non-matched objects as a collection from executing a Mingo.Query
with the given criteria
Performs aggregation operation using the aggregation pipeline.
MIT
FAQs
MongoDB query language for in-memory objects
The npm package mingo receives a total of 95,920 weekly downloads. As such, mingo popularity was classified as popular.
We found that mingo demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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