Learn Loopback, Neo4j and Sequelize

In this course we will learn some of the basics of getting data into and out of Neo4J, as well as touch on some of the libraries and tooling available in the Neo4J community ecosystem, which we will leverage to quickly create and use a full-featured GraphQL API.

We will start by learning how to run and interact with Neo4J locally. Then we will develop a graph model in which to store the data that we pull from SWAPI via REST. We will then create an Apollo GraphQL API driven by a few simple schemas which fit into this model. We will then write some simple code to crawl SWAPI and insert the data into Neo4J through our GraphQL API. Once there is data in the store, we will learn about some of the features in `neo4j-graphql-js` that make connecting and accessing our graph Nodes easier.

Neo4j delivers the lightning-fast read and write performance you need. Neo4j combines native graph storage, scalable architecture optimized for speed, and ACID compliance to ensure predictability of relationship-based queries.

neo4j

Build a Neo4J & GraphQL API

In this course the developer will learn how to create a LoopBack API and build it out to an API that can be used as a backend for apps. We will start by creating a basic LoopBack API project and gradually enhance it to a production ready API. The API we create defines a few models to persist the data and has custom functionality, validation and hooks added to those models. 

After our data structure is defined we will learn how to extend the functionality of LoopBack by using mixins and components. We will also lock our API down using ACL’s and create a mechanism to automatically define the admin and user roles and create our admin user.   

The last part of the course will show how how to filter the data stored in the API. We will make the API production-ready by adding unit tests, connecting it to MongoDB and we will show how to deploy the app to now.sh.   

LoopBack is a highly-extensible, open-source Node.js framework.

loopback

Build a Node.js REST API with LoopBack

A relation in LoopBack is a way to associate the data from multiple models with each other. LoopBack supports various types of relations each with a different use case.

In this lesson we will create a second model called Category and create a relation between the Category and the Product models. To do this we will first add a property to the Product model called `categoryId`. This will allow us to store for each Product the category it belongs to. We then move on to create the actual relationships. 

Our first relationship defines that a `Category hasMany Products` and the second one that a `Product belongsTo a Category`.

After defining these relations we will use the API Explorer to see how we can interact with this related data.

Create a relation between two LoopBack models

In this lesson we will look at the filters that can be used to retrieve and manipulate the data stored in LoopBack. 

We will use [Postman](https://www.getpostman.com/) to interact with the `/Categories` and `/Products` endpoints. 

Using the URL parameters we will apply at the various filters LoopBack has to offer: `include`, `order`, `where`, `fields`, `limit` and `offset`. 

Filter model data in LoopBack

In this lesson we look at extending the functionality of LoopBack models by defining a remote method. 

A remote method is a method on a model exposed over a custom REST endpoint. 

Using the `lb remote-method` command we will create the remote method meta-data in `product.json`. We will verify that this got created and that we see the new REST endpoint got added. Then we will create the actual method in `product.js` and enhance it so that the API will return an error if we want to buy a negative amount of products.

Define a remote method on a LoopBack model

In this lesson we will create a dynamic datasource in LoopBack. If the API is started with the environment variable `MONGODB_URL` it will use this url and the `loopback-connector-mongodb` package to store the data in MongoDB.

In the course we will use a local MongoDB instance. If you don't have MongoDB running locally you can always create a [free MongoDB Atlas database](https://egghead.io/lessons/create-a-free-database-on-mongodb-atlas).


Create a MongoDB DataSource in LoopBack

In this lesson you will learn how to persist the data from the memory connector. As the name suggests, the memory connector stores the data in memory. This means that if you restart the server, the data is gone. In development mode it can be useful to store this data in a file, so it gets persisted between server restarts, and it can be easily inspected.

Persist in-memory data to a file when developing Node.js LoopBack API's

In this lesson we will learn to create a development mode for our server. We do this by installing nodemon as a dev dependency and creating a script tag called 'dev'. 

This script tag will execute the command `nodemon server/server.js --watch common --watch server`.  

We can execute this command by running `npm run dev`. 

When running in development mode the server will be automatically restarted when there are changes detected in the `common` and `server` directories.

Setup a development mode in LoopBack API using nodemon

In this lesson we will learn how to protect our API using ACL’s. 

ACL stands for Access Control List and it's function is to control permissions of resources in the API. It does this by keeping a mapping between an API resource and a principal. An API resource as an API endpoint like a remote method or a whole model. A principal in LoopBack are users or applications that can be grouped in a role.

In order to get the API production ready we will protect a selection of our REST endpoints with ACL’s. We will look at how we can obtain an access token and how we can use that in our requests.

Finally we will write some unit tests to make sure that the ACL does what we expect. We enhance our test setup by exporting `request` with is provided by the [supertest](https://www.npmjs.com/package/supertest) library.

In our tests we use `request` to verify that our endpoints return the correct HTTP status code.  

Configure ACL’s to protect the LoopBack API

In this lesson we will look at how to deploy our LoopBack API project using [now](https://zeit.co/now). 

We will install the now client, create an account and deploy our app.

Using `now secrets` features we will store our database connection url which we get by creating a [free MongoDB Atlas database](https://egghead.io/lessons/create-a-free-database-on-mongodb-atlas).

In order to simplify following deployments we will add a `now` key to our `package.json` where we use the `name`, `alias` and `env` parameters to configure our deployments. We will add some npm scripts so we can deploy our app in the desired way using `npm run now`.

Deploy a LoopBack API project using now.sh

In this lesson we will create a free account on monogdb.com. After the account has been created we will create a group in MongoDB Atlas and in that group we create a free cluster. In order to create the cluster we need to provide a username and password. We create our user called `admin` and have the site generate our password for use. Once the cluster is created we look at where we can find the connection string.

Create a free database on MongoDB Atlas

LoopBack is a framework built on top of Express for creating APIs. It allows you to create end-to-end REST APIs that can access data from many data sources such as MondoDB, PostgreSQL, MySQL or other REST APIs.

In this lesson you will learn how to install loopback-cli and create a new LoopBack API project. After creating the basic LoopBack project through the CLI, running the server will give us access to the project and API Explorer urls. The user model will be available to us because user authentication was enabled.

Initialize a LoopBack Node.js Project through the CLI

In this lesson we will learn how to add tests to the project to make sure our API behaves as we expect. 

After installing `mocha` and `chai` as devDependencies we will add `test` and `test:watch` scripts to our `package.json`. We will create a different datasource what we will use when running the tests by copying `datasources.json` to `datasources.test.json` and prefixing our `test` command with `NODE_ENV=test`. 

We will verify that our tests run against an empty datasource. We’ll also add various tests to verify that our remote method and validation on the Product model behave as expected.

Add unit tests to a LoopBack API project

We can add validation rules to our models to make sure the data we store in our API is how we want it.

In this lesson we will add validation rules to the Product model.

We will make sure the product name has a minimal length using the `validatesLengthOf` rule and that it is unique using the `validatesUniquenessOf` rule. 

For the price property we will add a custom validation to make sure that the value entered is not a negative integer. Additionally we will show how to do an async validation using `validateAsync` . This can for instance be useful if you want the validation to depend on a value in the database or a remote system.

Add validation rules to a model in LoopBack API 

In this lesson we will learn how to add operation hooks to our models. In the Product model we will create a `before safe` observer that will check if the category we want to add the product to exists. 

In our Category model we will create a `before delete` observer to prevent categories from being deleted when they have products.

We will create a unit test to verify that both of these operation hooks work as expected.

Add Operation Hooks to a LoopBack model

In this lesson you will learn what a LoopBack model is, you will create a Product model using the LoopbBack CLI. The product model will be based off the built-in PersistedModel which gives it basic functionality like Create, Ready, Update, Delete and some more.  Using the API Explorer you can interact with the new model, store, retrieve, edit and delete the product data.

Create a model to persist data in a Node.js LoopBack API

Sequelize is a promise-based ORM for Node.js and io.js. It supports the dialects PostgreSQL, MySQL, MariaDB, SQLite and MSSQL and features solid transaction support, relations, read replication and more.

sequelize

Sequelize attribute getters and setters are a convenient way to encapsulate extra logic for model properties. In this video, we'll cover adding getters and setters to enhance and even virtualize a column.

Sequelize: Getters, Setters and Virtual Columns

Models in the Node.js ORM, Sequelize, can be expanded with both class level and instance level functions. This video will show you how to extend your models to add helpers or business logic, and explain the methods execution scope.

Sequelize: Class & Instance Methods

Javascript and database systems tend to be at odds with regard to how tables and columns should be named. Sequlize provides all the tools necessary to satisfy naming conventions in both your Node.js code and in your SQL database.

Sequelize: Model & Column Casing

There are different types of data in Neo4J: Nodes and Relationships. We will cover the ways to create each type of data: creating nodes with properties, creating nodes with relationships, and creating constraints on nodes and relationships.

Create Nodes and Relationships in Neo4J with Cypher

Once there is data in Neo4J, we need to be able to access it. We will cover the structure of a cypher query to return parts of our graph.

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