Uvod u Mongoose za MongoDB

Mongoose je biblioteka objektnog modeliranja podataka (ODM) za MongoDB i Node.js. Upravlja odnosima između podataka, pruža provjeru valjanosti sheme i koristi se za prevođenje između objekata u kodu i predstavljanja tih objekata u MongoDB-u.

MongoDB je baza podataka NoSQL dokumenata bez sheme. To znači da u njega možete pohraniti JSON dokumente, a struktura tih dokumenata može se razlikovati jer se ne provodi poput SQL baza podataka. To je jedna od prednosti korištenja NoSQL-a jer ubrzava razvoj aplikacija i smanjuje složenost implementacija.

Ispod je primjer kako se podaci pohranjuju u Mongo u odnosu na SQL bazu podataka:

Terminologije

Zbirke

'Zbirke' u Mongu ekvivalentne su tablicama u relacijskim bazama podataka. Mogu držati više JSON dokumenata.

Dokumenti

'Dokumenti' su ekvivalentni zapisima ili redovima podataka u SQL-u. Iako se u SQL retku mogu referencirati podaci u drugim tablicama, Mongo dokumenti to obično kombiniraju u dokumentu.

Polja

'Polja' ili atributi slični su stupcima u SQL tablici.

Shema

Iako je Mongo bez sheme, SQL definira shemu putem definicije tablice. Mongooseova 'shema' je struktura podataka dokumenta (ili oblik dokumenta) koja se provodi putem aplikacijskog sloja.

Modeli

'Modeli' su konstruktori višeg reda koji uzimaju shemu i stvaraju instancu dokumenta ekvivalentnu zapisima u relacijskoj bazi podataka.

Početak rada

Mongo instalacija

Prije nego što započnemo, postavimo Mongo. Možete odabrati jednu od sljedećih opcija (za ovaj članak koristimo opciju br. 1):

  1. Preuzmite odgovarajuću verziju MongoDB za svoj operativni sustav s web stranice MongoDB i slijedite njihove upute za instalaciju
  2. Stvorite besplatnu pretplatu na bazu podataka za Sandbox na mLab
  3. Instalirajte Mongo pomoću Dockera ako više volite koristiti docker

Krenimo kroz neke od osnova Mongoosea implementirajući model koji predstavlja podatke za pojednostavljeni adresar.

Koristim Visual Studio Code, Node 8.9 i NPM 5.6. Zapalite svoj omiljeni IDE, stvorite prazan projekt i krenimo! U Nodeu ćemo koristiti ograničenu sintaksu ES6, pa nećemo konfigurirati Babel.

Instalacija NPM-a

Idemo u mapu projekta i inicijaliziramo naš projekt

npm init -y

Instalirajmo Mongoose i knjižnicu provjere valjanosti sa sljedećom naredbom:

npm install mongoose validator

Gornja naredba za instalaciju instalirat će najnoviju verziju knjižnica. Sintaksa Mongoose u ovom članku specifična je za Mongoose v5 i novije verzije.

Veza s bazom podataka

Stvorite datoteku ./src/database.jspod korijenom projekta.

Zatim ćemo dodati jednostavnu klasu s metodom koja se povezuje s bazom podataka.

Niz veze povezat će se ovisno o vašoj instalaciji.

let mongoose = require('mongoose'); const server = '127.0.0.1:27017'; // REPLACE WITH YOUR DB SERVER const database = 'fcc-Mail'; // REPLACE WITH YOUR DB NAME class Database { constructor() { this._connect() } _connect() { mongoose.connect(`mongodb://${server}/${database}`) .then(() => { console.log('Database connection successful') }) .catch(err => { console.error('Database connection error') }) } } module.exports = new Database()

The require(‘mongoose’)gornji poziv vraća Singleton objekt. To znači da prvi put kad nazovete require(‘mongoose’)stvara instancu klase Mongoose i vraća je. Na sljedećim pozivima vratit će istu instancu koja je stvorena i vraćena vam prvi put zbog načina na koji modul uvoz / izvoz radi u ES6.

Slično tome, našu smo klasu baze podataka pretvorili u jednostruku vraćanjem instance klase u module.exportsizraz jer nam je potrebna samo jedna veza s bazom podataka.

ES6 nam vrlo olakšava stvaranje jednostrukog (pojedinačnog) uzorka zbog načina na koji radi loader modula predmemoriranjem odgovora prethodno uvezene datoteke.

Shema Mongoose vs. Model

Model Mongoose je omot sheme Mongoose. Shema Mongoose definira strukturu dokumenta, zadane vrijednosti, validatore itd., Dok model Mongoose pruža sučelje bazi podataka za stvaranje, postavljanje upita, ažuriranje, brisanje zapisa itd.

Stvaranje modela Mongoose sastoji se prvenstveno od tri dijela:

1. Referenciranje Mongoosea

let mongoose = require('mongoose')

This reference will be the same as the one that was returned when we connected to the database, which means the schema and model definitions will not need to explicitly connect to the database.

2. Defining the Schema

A schema defines document properties through an object where the key name corresponds to the property name in the collection.

let emailSchema = new mongoose.Schema({ email: String })

Here we define a property called email with a schema type String which maps to an internal validator that will be triggered when the model is saved to the database. It will fail if the data type of the value is not a string type.

The following Schema Types are permitted:

  • Array
  • Boolean
  • Buffer
  • Date
  • Mixed (A generic / flexible data type)
  • Number
  • ObjectId
  • String

Mixed and ObjectId are defined under require(‘mongoose’).Schema.Types.

3. Exporting a Model

We need to call the model constructor on the Mongoose instance and pass it the name of the collection and a reference to the schema definition.

module.exports = mongoose.model('Email', emailSchema)

Let’s combine the above code into ./src/models/email.jsto define the contents of a basic email model:

let mongoose = require('mongoose') let emailSchema = new mongoose.Schema({ email: String }) module.exports = mongoose.model('Email', emailSchema)

A schema definition should be simple, but its complexity is usually based on application requirements. Schemas can be reused and they can contain several child-schemas too. In the example above, the value of the email property is a simple value type. However, it can also be an object type with additional properties on it.

We can create an instance of the model we defined above and populate it using the following syntax:

let EmailModel = require('./email') let msg = new EmailModel({ email: '[email protected]' })

Let’s enhance the Email schema to make the email property a unique, required field and convert the value to lowercase before saving it. We can also add a validation function that will ensure that the value is a valid email address. We will reference and use the validator library installed earlier.

let mongoose = require('mongoose') let validator = require('validator') let emailSchema = new mongoose.Schema({ email: { type: String, required: true, unique: true, lowercase: true, validate: (value) => { return validator.isEmail(value) } } }) module.exports = mongoose.model('Email', emailSchema)

Basic Operations

Mongoose has a flexible API and provides many ways to accomplish a task. We will not focus on the variations because that is out of scope for this article, but remember that most of the operations can be done in more than one way either syntactically or via the application architecture.

Create Record

Let’s create an instance of the email model and save it to the database:

let EmailModel = require('./email') let msg = new EmailModel({ email: '[email protected]' }) msg.save() .then(doc => { console.log(doc) }) .catch(err => { console.error(err) })

The result is a document that is returned upon a successful save:

{ _id: 5a78fe3e2f44ba8f85a2409a, email: '[email protected]', __v: 0 }

The following fields are returned (internal fields are prefixed with an underscore):

  1. The _id field is auto-generated by Mongo and is a primary key of the collection. Its value is a unique identifier for the document.
  2. The value of the email field is returned. Notice that it is lower-cased because we specified the lowercase:true attribute in the schema.
  3. __v is the versionKey property set on each document when first created by Mongoose. Its value contains the internal revision of the document.

If you try to repeat the save operation above, you will get an error because we have specified that the email field should be unique.

Fetch Record

Let’s try to retrieve the record we saved to the database earlier. The model class exposes several static and instance methods to perform operations on the database. We will now try to find the record that we created previously using the find method and pass the email as the search term.

EmailModel .find({ email: '[email protected]' // search query }) .then(doc => { console.log(doc) }) .catch(err => { console.error(err) })

The document returned will be similar to what was displayed when we created the record:

{ _id: 5a78fe3e2f44ba8f85a2409a, email: '[email protected]', __v: 0 }

Update Record

Let’s modify the record above by changing the email address and adding another field to it, all in a single operation. For performance reasons, Mongoose won’t return the updated document so we need to pass an additional parameter to ask for it:

EmailModel .findOneAndUpdate( { email: '[email protected]' // search query }, { email: '[email protected]' // field:values to update }, { new: true, // return updated doc runValidators: true // validate before update }) .then(doc => { console.log(doc) }) .catch(err => { console.error(err) })

The document returned will contain the updated email:

{ _id: 5a78fe3e2f44ba8f85a2409a, email: '[email protected]', __v: 0 }

Delete Record

We will use the findOneAndRemove call to delete a record. It returns the original document that was removed:

EmailModel .findOneAndRemove({ email: '[email protected]' }) .then(response => { console.log(response) }) .catch(err => { console.error(err) })

Helpers

We have looked at some of the basic functionality above known as CRUD (Create, Read, Update, Delete) operations, but Mongoose also provides the ability to configure several types of helper methods and properties. These can be used to further simplify working with data.

Let’s create a user schema in ./src/models/user.js with the fieldsfirstName and lastName:

let mongoose = require('mongoose') let userSchema = new mongoose.Schema({ firstName: String, lastName: String }) module.exports = mongoose.model('User', userSchema)

Virtual Property

A virtual property is not persisted to the database. We can add it to our schema as a helper to get and set values.

Let’s create a virtual property called fullName which can be used to set values on firstName and lastName and retrieve them as a combined value when read:

userSchema.virtual('fullName').get(function() { return this.firstName + ' ' + this.lastName }) userSchema.virtual('fullName').set(function(name) { let str = name.split(' ') this.firstName = str[0] this.lastName = str[1] })

Callbacks for get and set must use the function keyword as we need to access the model via the thiskeyword. Using fat arrow functions will change what this refers to.

Now, we can set firstName and lastName by assigning a value to fullName:

let model = new UserModel() model.fullName = 'Thomas Anderson' console.log(model.toJSON()) // Output model fields as JSON console.log() console.log(model.fullName) // Output the full name

The code above will output the following:

{ _id: 5a7a4248550ebb9fafd898cf, firstName: 'Thomas', lastName: 'Anderson' } Thomas Anderson

Instance Methods

We can create custom helper methods on the schema and access them via the model instance. These methods will have access to the model object and they can be used quite creatively. For instance, we could create a method to find all the people who have the same first name as the current instance.

In this example, let’s create a function to return the initials for the current user. Let’s add a custom helper method called getInitials to the schema:

userSchema.methods.getInitials = function() { return this.firstName[0] + this.lastName[0] }

This method will be accessible via a model instance:

let model = new UserModel({ firstName: 'Thomas', lastName: 'Anderson' }) let initials = model.getInitials() console.log(initials) // This will output: TA

Static Methods

Similar to instance methods, we can create static methods on the schema. Let’s create a method to retrieve all users in the database:

userSchema.statics.getUsers = function() { return new Promise((resolve, reject) => { this.find((err, docs) => { if(err) { console.error(err) return reject(err) } resolve(docs) }) }) }

Calling getUsers on the Model class will return all the users in the database:

UserModel.getUsers() .then(docs => { console.log(docs) }) .catch(err => { console.error(err) })

Adding instance and static methods is a nice approach to implement an interface to database interactions on collections and records.

Middleware

Middleware are functions that run at specific stages of a pipeline. Mongoose supports middleware for the following operations:

  • Aggregate
  • Document
  • Model
  • Query

For instance, models have pre and post functions that take two parameters:

  1. Type of event (‘init’, ‘validate’, ‘save’, ‘remove’)
  2. A callback that is executed with this referencing the model instance

Let’s try an example by adding two fields called createdAt and updatedAt to our schema:

let mongoose = require('mongoose') let userSchema = new mongoose.Schema({ firstName: String, lastName: String, createdAt: Date, updatedAt: Date }) module.exports = mongoose.model('User', userSchema)

When model.save() is called, there is a pre(‘save’, …) and post(‘save’, …) event that is triggered. For the second parameter, you can pass a function that is called when the event is triggered. These functions take a parameter to the next function in the middleware chain.

Let’s add a pre-save hook and set values for createdAt and updatedAt:

userSchema.pre('save', function (next) { let now = Date.now() this.updatedAt = now // Set a value for createdAt only if it is null if (!this.createdAt) { this.createdAt = now } // Call the next function in the pre-save chain next() })

Let’s create and save our model:

let UserModel = require('./user') let model = new UserModel({ fullName: 'Thomas Anderson' } msg.save() .then(doc => { console.log(doc) }) .catch(err => { console.error(err) })

You should see values for createdAt and updatedAt when the record that is created is printed:

{ _id: 5a7bbbeebc3b49cb919da675, firstName: 'Thomas', lastName: 'Anderson', updatedAt: 2018-02-08T02:54:38.888Z, createdAt: 2018-02-08T02:54:38.888Z, __v: 0 }

Plugins

Suppose that we want to track when a record was created and last updated on every collection in our database. Instead of repeating the above process, we can create a plugin and apply it to every schema.

Let’s create a file ./src/model/plugins/timestamp.js and replicate the above functionality as a reusable module:

module.exports = function timestamp(schema) { // Add the two fields to the schema schema.add({ createdAt: Date, updatedAt: Date }) // Create a pre-save hook schema.pre('save', function (next) { let now = Date.now() this.updatedAt = now // Set a value for createdAt only if it is null if (!this.createdAt) { this.createdAt = now } // Call the next function in the pre-save chain next() }) }

To use this plugin, we simply pass it to the schemas that should be given this functionality:

let timestampPlugin = require('./plugins/timestamp') emailSchema.plugin(timestampPlugin) userSchema.plugin(timestampPlugin)

Query Building

Mongoose has a very rich API that handles many complex operations supported by MongoDB. Consider a query where we can incrementally build query components.

In this example, we are going to:

  1. Find all users
  2. Skip the first 100 records
  3. Limit the results to 10 records
  4. Sort the results by the firstName field
  5. Select the firstName
  6. Execute that query
UserModel.find() // find all users .skip(100) // skip the first 100 items .limit(10) // limit to 10 items .sort({firstName: 1} // sort ascending by firstName .select({firstName: true} // select firstName only .exec() // execute the query .then(docs => { console.log(docs) }) .catch(err => { console.error(err) })

Closing

We have barely scratched the surface exploring some of the capabilities of Mongoose. It is a rich library full of useful and and powerful features that make it a joy to work with data models in the application layer.

While you can interact with Mongo directly using Mongo Driver, Mongoose will simplify that interaction by allowing you to model relationships between data and validate them easily.

Fun Fact:Mongoose is created by Valeri Karpovwho is an incredibly talented engineer! He coined the term The MEAN Stack.

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