Learn Faunadb, Immutable and Mocha


Next.js is one of the most popular server-side-rendered React frameworks you can use to build production-ready serverless applications in record time. 

On the other hand, Fauna is a flexible, serverless, distributed document-relational database. Fauna has a powerful GraphQL API and custom resolver support. 

Using Next.js and Fauna, you can build robust, feature-rich, production-ready full-stack applications without the hassle of managing any servers or databases.

In this course, Shadid guides you through building your very own full-stack serverless marketplace application using Next.js, GraphQL, and Fauna. 

You will learn,

- How to work with Apollo GraphQL Client in Next.js
- How to setup Fauna GraphQL
- Data modeling in Fauna
- How to write custom Fauna GraphQL Resolvers (UDFs)
- How to authenticate with Auth0?
- Stripe payment 



GraphQL is a query language for APIs and a runtime for fulfilling those queries with your existing data. GraphQL provides a complete and understandable description of the data in your API, gives clients the power to ask for exactly what they need and nothing more, makes it easier to evolve APIs over time, and enables powerful developer tools.

graphql

Full-Stack Serverless Applications with Next.js & Fauna

This application serves as an introduction to building products with a JAMStack and Serverless approach. We cover everything from the beginning:

* starting with the Gatsby client
* handling authentication with Netlify Identity
* Shipping a GraphQL server on Netlify Functions
* Building in access control with a serverless capable database

It uses tools that remove as many of the barriers as possible while also allowing upgrading in the future. Netlify Functions can grow into AWS Lambda, Netlify Identity can grow into Auth0 or Cognito, and FaunaDB can grow into DynamoDB.

Gatsby is a blazing fast static site generator built with React. Gatsby gives you all of the modern JavaScript tools you want; set up and ready to go out of the box.

gatsby

Building a Serverless JAMStack Todo app with Netlify, Gatsby, GraphQL, and FaunaDB

This collection is a sequel to the [Building a Serverless JAMStack Todo app with Netlify, Gatsby, GraphQL, and FaunaDB](https://egghead.io/playlists/building-a-serverless-jamstack-todo-app-with-netlify-gatsby-graphql-and-faunadb-53bb) collection. In this collection we take the TODO application we built and convert it to run using Netlify Identity, AWS Lambda (using the serverless framework) and DynamoDB. We cover

* Fauna vs DynamoDB and when to use each
* Setting up AWS accounts
* Creating DynamoDB tables and data modeling differences between Fauna and Dynamo
* Converting our Netlify Functions deployment to a Serverless Framework deployment
* Implementing Custom authorizer functions on AWS

It uses tools that remove as many of the barriers as possible. Netlify Functions grows into Serverless Framework adn AWS Lambda, Netlify Identity is kept around, and FaunaDB can grows into DynamoDB.



FaunaDB is a global serverless database that gives you ubiquitous, low latency access to app data, without sacrificing data correctness. It eliminates layers of app code for manually handling data anomalies, security, and scale, creating a friendlier dev experience for you and better app experience for your users.

faunadb

Converting a Serverless App to run on AWS Lambda and DynamoDB with Serverless Framework

FaunaDB is a global serverless database that gives you ubiquitous, low latency access to app data, without sacrificing data correctness. It eliminates layers of app code for manually handling data anomalies, security, and scale, creating a friendlier dev experience for you and better app experience for your users.

Fauna is inspired by [Calvin](https://blog.acolyer.org/2019/03/29/calvin-fast-distributed-transactions-for-partitioned-database-systems/), has [built-in GraphQL integration](https://docs.fauna.com/fauna/current/api/graphql/), and a query language based on lambda calculus. Be sure to check out the [Jepsen analysis](https://jepsen.io/analyses/faunadb-2.5.4) and the associated [chart of consistency models](https://jepsen.io/consistency)

The Complete Guide to FaunaDB

Immutable.js provides many Persistent Immutable data structures including: List, Stack, Map, OrderedMap, Set, OrderedSet and Record.

immutable

There are lots of techniques for accessing data kept in your Lists. In this lesson, we will compare how data stored in collections can be accessed directly in both standard Arrays and ImmutableJS Lists. We will also look at how to find data inside an Immutable List using the `findEntry` and `findIndex` methods.

Get items in an ImmutableJS List

Chai is a BDD / TDD assertion library for node and the browser that can be delightfully paired with any javascript testing framework.

chai

Every dependable library needs to have tests to ensure that you don't push accidental bugs. In this lesson, see how you can set up mocha and chai to start testing your library.

Setting up Unit Testing with Mocha and Chai

The reduce function in ImmutableJS allows you to transform and create new data from an existing data structure. In this example, we will do some math and calculate a sum based on data in an ImmutableJS Map.

Calculate a sum using reduce in ImmutableJS

Now that you've got everything set up with mocha and chai, it's time to actually write tests. In this lesson you'll learn how to use `describe` and `it` to outline your tests and make sure you don't break your library in the future.

Unit Testing with Mocha and Chai

Mocha is a feature-rich JavaScript test framework running on Node.js and in the browser, making asynchronous testing simple and fun. Mocha tests run serially, allowing for flexible and accurate reporting, while mapping uncaught exceptions to the correct test cases.

mocha

Mocha is a testing framework that provides structure for unit tests. In this lesson, we will be setting up Mocha with npm and npm scripts, writing a "Hello World" unit test, then writing the code to make the test pass (as an example of Test Driven Development (TDD), with the "red-green-refactor" workflow).

JavaScript Testing Fundamentals: Hello world unit test with Mocha (in ES6)

In this lesson, we will use Chai's request method to test our Node application's API responses.
By the end of this lesson, you will know how to:
- install the prerequisites to use mocha and chai in your application
- test for HTTP status response codes
- test for a string of text on a page
- test for a json response and validate the properties of the object
- write tests that not only verify the response of your application, but the behavior as well


Test Node RESTful API with Mocha and Chai

Writing great ES6 style Promises for Node.js is only half the battle. Your great modules must include tests as well to ensure future iterations don't break them. In this lesson, I show you a simple ES6 Promise in Node.js, then walk you through creating tests in Mocha using chai and chai-as-promised to test both resolve and reject methods.

Testing ES6 Promises in Node.js using Mocha and Chai

The key to being productive with Immutable JS is understanding how to update values that are nested. Using `setIn` you can place a new value directly into an existing or new path. If you need access to the previous value before setting the new one, you can use `updateIn` instead. `updateIn`  accepts the same path lookups as `setIn`, but gives you a callback function instead so that you can use the previous value however you wish and return an updated version.

Updating nested values with ImmutableJS

ImmutableJS reduce functions can be nested to get data out of complex data structures. In this example, we will create an Immutable List from an Immutable Map that is nested inside of an Immutable List that is itself nested inside of an Immutable Map.

Create a list with nested reduce functions in ImmutableJS

In this lesson, you will learn how to verify your API server is returning HTTP 400 responses when clients submit incorrect data. Returning HTTP 400 ensures that your clients are notified of the incorrect usage. Testing for them ensures your API returns errors instead of incorrect responses when supplied with incorrect data.

Test for HTTP 400 responses with Mocha and Chai

By utilizing immutable data structures, we can write code that is easier to reason about, avoid mutation-related bugs, reduce complexity, and even gain some performance benefits along the way.

Before diving too far into Facebook's [Immutable.js](https://facebook.github.io/immutable-js/) library, let's take a moment to examine some of the pains and obstacles that mutable data structures present. 

We'll take a brief glimpse at putting the Immutable "List" data structure to work by example. We will convert our usage of Javascript's native `Array` to use [Immutable.List](https://facebook.github.io/immutable-js/docs/#/List) in order to address a mutation-related "bug" caused by multiple objects "sharing" a mutable structure (array) by reference.

Immutable.js: Introduction - Easing the Pains of Mutability

In this lesson we'll look at some of the differences between standard JavaScript Arrays and Immutable Lists. We'll create Immutable.JS Lists from scratch, as well as by converting regular Arrays. We will also compare and contrast the `push` and `concat` methods between both types of collection.

Create an immutable List using Immutable.js

React is one of the web’s most popular frameworks for building JavaScript applications. 

If you know what you’re doing, React can drastically simplify how you build, use, and maintain code.

Whether you’re a React newbie or you’re ready for advanced techniques, you can level-up with egghead. Explore our in-depth courses, lessons, and community resources to build more powerful applications and crack open your career.

react

Sometimes our update logic is asynchronous. In this lesson we will investigate two ways in which we can write asynchronous update logic. 

…But, we will also discuss why asynchronous producers should be avoided, and how that can be done by better separating our logic. 

This lesson also demonstrates the “createDraft” and “finishDraft” APIs

Write Asynchronous Producers in Immer and Why You Shouldn’t

In this lesson we will send patches over a WebSocket to our server, and distribute them again from there.

Create a Simple WebSocket Server to Distribute Patches from Immer

We walk through creating a new Database in the FaunaDB console complete with some demo data. We do some exploration of the data, introducing concepts like Collections and Indexes, before showing an example FQL query that runs against the database. This sets us up to talk about FQL in future videos

Creating your first FaunaDB database

FaunaDB is a Calvin inspired hosted database marketed towards JAMStack and serverless users. It is geo-replicated across multiple providers (AWS, GCP, and soon Azure), uses a lambda calculus based query language (FQL) or the built-in GraphQL support, and is quick to get started with. Don't worry about the vocabulary here (Consistency, lambda calculus, etc), FaunaDB can be quickly put to work without reading any papers and without knowing what lambda calculus is.

* [Calvin Paper](http://cs.yale.edu/homes/thomson/publications/calvin-sigmod12.pdf) (warning: pdf link)
  - [Morning Paper Overview of Calvin Paper](https://blog.acolyer.org/2019/03/29/calvin-fast-distributed-transactions-for-partitioned-database-systems/) if you don't want to read the whole paper
* [jepsen report](https://jepsen.io/analyses/faunadb-2.5.4)

An Introduction to FaunaDB

FQL is the main query language for interacting with FaunaDB. It supports all JSON types, plus some additional types like Ref, Date, and Set. FQL is based in expressions and as such everything returns a value. This makes it easy to compose logic into larger queries.

Code shown in the shell:

```
Match(Index("all_customers"))
```

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