What is moltyjs?
A tiny ODM for MongoDB with multy tenancy support and Elasticsearch integration.
MoltyJS allow you all what you expect from an object database modeling library plus multy tenancy support and Elasticsearch integration behind the scene.
Install
$ npm install moltyjs --save
Usage
const { connect } = require('moltys');
import { connect } from ('moltyjs');
Connect to a DB
To connect to a database use the "connect()" function passing trough 'options' payload all the settings required:
Molty.connect(options)
const { connect } = require('moltys');
const options = {
engine: 'mongodb',
uri: 'mongodb://localhost:27017/test',
max: 100,
min: 1,
connection: {
replicaSet: 'repl-s0123',
},
tenants: {
noListener: false,
returnNonCachedInstance: false,
},
elasticSearch: {
host: 'localhost:9200',
},
};
const connection = connect(options);
"connect()" will return a connection instance which will allow you to perform all the actions availables on the DB.
Options settings allowed are:
- engine: {String} By default 'mongodb', and for the time being MoltyJS only supports Mongo Databases.
- uri: {String} DB connection URI. To get more information about MongoDB connection URI take a look to the official documentation
- max: {Number} By default 100, set the maximum connection simultaneasly to the DB.
- min: {Number} Bu default 1, set the minimum connection simultaneasly to the DB.
- connection: Object to set up the connection parameters to the DB instance and the connection pool settings.
- tenants: Object to set up the db instance configuration
- noListener: {Boolean} By default false, do not make the db an event listener to the original connection. Keep it false if you are using MoltyJS in a multy tenancy architecture since MongoDB propagate all the events throug all the db instances oppened.
- returnNonCachedInstance: {Boolean} By default false, control if you want to return a cached instance or have a new one created
- elasticSearch: Object to set up the connection parameter to the Elasticsearch instance
- host: {String} Host of the Elasticsearch instance
Drop a DB
.dropDatabase(database)
const res = await connection.dropDatabase('test');
Create a new Schema
Molty Schema are based on Mongoose Schema structure with some changes on the declaration of the inherit schema options. I even keep some field options name to make the Molty integration as easier as posible in those project are currently running Mongoose.
To create a new Schema use the "Schema()" constructor passing the schema and the options:
new Schema(schema, options)
const { Schema } = require('moltys');
const newSchema = Schema(
{
email: {
type: String,
required: true,
unique: true,
maxlength: 100,
},
password: {
type: Number,
required: true,
},
name: {
type: String,
default: '',
},
age: {
type: Number,
},
tests: {
type: [Schema.types().ObjectId],
ref: 'ReferenceSchema',
},
},
{
timestamps: true,
inheritOptions: {
discriminatorKey: '__kind',
},
},
);
The schema field properties alowed are:
- type: Is the only one which is mandatory and could be a String, Number, Boolean, Buffer, Date, Array, Object, ObjectId or an array [] of any of them.
- ref: Optional and should be the Model name associated to the collection you want to refeer. The type of areference field must be ObjectId or [ObjectId].
- required: Optional and only allow Boolean values.
- unique: Optional and only allow Boolean values.
- default: Optional, only allows values of the same type which is set on the type property. You also can assigna a function to it which return a value with the correct type.
- match: Optional, allows either RegExp or String to validate the value of the field.
- enum: Optional, and must be an array of values of the same type is set on type.
- min: Optional, minimum number allowed.
- max: Optional, maximum number allowed.
- maxlength: Optional, maximum length of a String
- validate: Optional, function to perform a custom validation. Document is passing through the function arg:
const { Schema } = require('moltys');
const otherSchema = Schema({
job: {
type: String,
validate: async doc => {
if (doc.field === 'exist') return true;
return false;
},
},
});
And the schema options allowed are:
- timestamps: Optional, set automatically in the documents saved or updated in the DB the fields:
createdAt
and updatedAt
- inheritOptions: Optional, used for inherit from a parent Schema
- discriminatorKey: Required once "inheritOptions" is set
- merge: Optional, must be an array with a combination of these three values ['methods', 'preHooks', 'postHooks'], depending of what you want to merge from the parent Schema.
- mongoDBIndexes: Optional, used for set custom schema indexes in mongoDB, like multi-field index, compound indexes, etc. See [https://docs.mongodb.com/manual/reference/command/createIndexes/](mongoDB documetation) for more information.
- elasticSearchIndexes: Optional, used for set the Schema field will be indexed by the Elasticsearch server and in which type: 'text', 'keyword', 'date', 'long', 'double', 'boolean', 'ip', 'object', 'nested'
const { Schema } = require('moltys');
const schemaOptions = {
timestamps: true,
inheritOptions: {
discriminatorKey: 'kind',
},
mongoDBIndexes: [
{
key: { name: 1, age: -1 },
unique: true,
},
],
elasticSearchIndexes: {
version: {
type: 'text',
},
},
};
const elasticSearchSchema = Schema(
{
version: {
type: String,
},
counter: {
type: Number,
},
},
schemaOptions,
);
Static methods
You can extend the functionality of Document class adding static method to work with the documents instances:
newSchema.methods.comparePassword = async function(candidatePassword) {
const user = this._data;
return candidatePassword === user.password;
};
const TestModel = new Model(newSchema, 'TestModel');
newDoc = TestModel.new({
email: 'test@moltyjs.com',
password: '1321321',
name: 'Michael Scott',
});
newDoc.comparePassword('000000');
Hooks middleware
All hooks have binded the connection instance and the tenant name beside the document or the query depending of the hook.
Document middleware is supported for the following functions.
In document middleware functions, this refers to the document or to the array of documents and meta is other value info related to the transaction like the fiter payload in the updates actions.
Examples:
newSchema.pre('insertOne', function(connection, tenant, meta, next) {
console.log(this);
return next();
});
newSchema.post('insertOne', function(connection, tenant, meta, next) {
this.staticMethod();
return next();
});
newSchema.pre('insertMany', function(connection, tenant, meta, next) {
console.log(this);
return next();
});
newSchema.post('insertMany', async function(connection, tenant, meta, next) {
const newDoc = TestModel.new({
email: 'test@moltyjs.com',
password: 'ababababa',
name: 'Pam Beesley',
});
const res = await connection.insertOne('tenant_test', newDoc);
return next();
});
Query middleware is supported for the following functions.
- updateOne
- updateMany
- delete
In query middleware functions, this refers to the query and meta is other value info related to the transaction like the fiter payload in the updates actions.
Examples:
newSchema.pre('updateOne', function(connection, tenant, meta, next) {
console.log(this);
return next();
});
newSchema.post('delete', async function(connection, tenant, meta, next) {
console.log(this);
return next();
});
Create a new Model
Once we have created our schema we need to register as a model so we can start to create, find, updete and delete documents. To do this you must provide the a proper schema and a model name. The model name will be the collection name on the DB so use the criteria you want since Molty does not make any accomodation on them like auto plurilize.
new Model(schema, discriminatorName)
const { Model } = require('moltys');
const TestModel = new Model(newSchema, 'TestModel');
Create a Model discriminator
You can also create models which inherits from other models and you can decide in which fashion you want to do it. You have to make sure that the discriminator key of the child models are the same than the parents and also set what you want to merge from the parent model.
.discriminator(schema, discriminatorName)
const { Schema } = require('moltys');
const newSchemaDiscriminator = Schema(
{
job: {
type: String,
default: '',
},
position: {
type: String,
},
},
{
timestamps: true,
inheritOptions: {
discriminatorKey: '__kind',
merge: ['methods', 'preHooks', 'postHooks'],
},
},
);
TestModelDiscriminator = TestModel.discriminator(
newSchemaDiscriminator,
'TestModelDiscriminator',
);
The merge option must be an array with the element you want to merge from the parent model, those options are:
- methods: which corresponds to the static methods.
- preHooks: which corresponds to the hooks that are executed before performing actions on the DB
- postHooks: which corresponds to the hooks that are executed after performing actions on the DB
Create a new document
Once we have already set up the Schema and registered the Model with it we can start creating document from that Model as follow:
.new(payload) {Promise}
const { Model } = require('moltys');
const TestModel = new Model(newSchema, 'TestModel');
newDoc = await TestModel.new(
{
email: 'test@moltyjs.com',
password: '1321321',
name: 'Michael Scott',
},
);
Referencing Documents
MoltyJS support referencing document that later on you wil be able to populate on find queries. To make a refference to another Model just add a new field on the Schema with the type ObjectId and the "ref" propertie with the Model name referenciated.
const { Schema } = require('moltys');
const referenceSchema = new Schema(
{
email: {
type: String,
required: true,
unique: true,
maxlength: 100,
},
password: {
type: String,
required: true,
unique: true,
maxlength: 150,
default: () => crypto.randomBytes(20).toString('hex'),
},
accountExpiration: {
type: Date,
default: () =>
moment()
.add(24, 'hours')
.utc()
.format(),
},
status: {
type: String,
required: true,
enum: ['pending', 'accepted', 'error'],
default: 'pending',
},
model: {
type: Schema.types().ObjectId,
ref: 'TestModel',
},
},
{
timestamps: true,
},
);
You can use an array of ObjectId also as type ([ObjectId]). Noticed that to get the proper ObjectId type you must tu get it from the Schema.types() method object is returned.
Saving a document
insertOne(tenant, doc, options = {}) {Promise}
- {String} Tenant name
- {Document}
doc
Document instance object - {Object}
options
Optional settings
- {Boolean}
moltyClass
(true by default) True if you want the results as MoltyJs Document class
instead of MongoDB Document - {Boolean}
forceServerObjectId
(false by default: no limit) Force server to create _id fields instead of client.
const res = await connection.insertOne(newDoc);
insertMany(tenant, docs, options = {}) {Promise}
- {String} Tenant name
- [{Document}]
docs
Array of Document instances of the same model and for the same tenant - {Object}
options
Optional settings
- {Boolean}
moltyClass
(true by default) True if you want the results as MoltyJs Document class
instead of MongoDB Document - {Boolean}
forceServerObjectId
(false by default: no limit) Force server to create _id fields instead of client.
newDoc2 = TestModel.new({
email: 'test2@moltyjs.com',
password: '1321321',
name: 'Dwight Schrute',
});
const res = await connection.insertMany([newDoc, newDoc2], {moltyClass: false});
Recovering a document
find(tenant, collection, query = {}, options = {}) {Promise}
- {String}
tanant
Tenant name - {String}
collection
Collection name - {Object}
query
Query object - {Object}
options
Optional settings
- {Boolean}
moltyClass
(true by default) True if you want the results as MoltyJs Document class
instead of MongoDB Document - {Number}
limit
(0 by default: no limit) Limit the results to the amount specified - {Object}
projection
(null by default) Create a projection of a field, the projection document limits the fields to return for all matching documents
const resFind = await connection.find('tenant_test', 'TestModel',
{
name: 'Michael Scott',
},
{
limit: 1,
projection: { name: 0 }
});
Updating a document
Updating a document support all the update operators from MongoDB
updateOne(tenant, collection, filter, payload, options = {}) {Promise}
- {String}
tanant
Tenant name - {String}
collection
Collection name - {Object}
filter
Filter object used to select the document to update - {Object}
payload
Payload object used to update the document - {Object}
options
Optional settings
- {Boolean}
moltyClass
(true by default) True if you want the results as MoltyJs Document class
instead of MongoDB Document
const resUpdate = await connection.updateOne(
'tenant_test',
'TestModel',
{ name: 'Michael Scott' },
{
$set: {
name: 'Some other name',
},
},
);
updateMany(tenant, collection, filter, payload, options = {}) {Promise}
- {String}
tanant
Tenant name - {String}
collection
Collection name - {Object}
filter
Filter object used to select the document to update - {Object}
payload
Payload object used to update the document - {Object}
options
Optional settings - {Boolean}
moltyClass
(true by default) True if you want the results as MoltyJs Document class instead of MongoDB Document
const resUpdate = await connection.updateMany(
'tenant_test',
'TestModel',
_id: {
$in: [
'5aa1530d604da74824a6c170',
'5aa1530d604da74824a6c171',
'5aa1530d604da74824a6c172',
'5aa1530d604da74824a6c173',
],
},
{
$set: {
name: 'Some other name',
},
},
);
Deleting a document
deleteOne(tenant, collection, filter, options = {}) {Promise}
- {String}
tanant
Tenant name - {String}
collection
Collection name - {Object}
filter
Filter object used to select the document to delete - {Object}
options
Optional settings - {Boolean}
moltyClass
(true by default) True if you want the results as MoltyJs Document class instead of MongoDB Document
const resUpdate = await connection.deleteOne(
'tenant_test',
'TestModel',
{ name: 'Michael Scott' },
);
Aggregate
Aggregation operations group values from multiple documents together, and can perform a variety of operations on the grouped data to return a single result.
aggregate(tenant, collection, pipeline = [], options = {}) {Promise}
- {String}
tanant
Tenant name - {String}
collection
Collection name - {Object[]}
pipeline
Array containing all the aggregation framework commands for the execution.
- {Object}
options
Optional settings
- "There is no options supported yet"
const pipeline = [
{
$match: {
_id: newDoc._data._id,
},
},
{
$lookup: {
from: 'ReferenceSchema',
localField: 'tests',
foreignField: '_id',
as: 'models',
},
},
{
$project: {
_id: 0,
tests: 1,
},
},
];
const aggregate = await connection.aggregate('tenant_test', 'TestModel', pipeline, {});
Elastisearch API public
search(tenant, collection, query=[]) {Promise}
drop(tenant) {Promise}