Learn Faunadb, Jasmine and Screen-reader


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

A large number of people are unable to use the web effectively due to an impairment or disability.

As developers there are several tools and techniques we can use to make our web applications accessible, ensuring a great user experience that includes everyone.

We all agree that Accessibility is important. However, it’s a broad landscape and can be overwhelming figuring out where to start!

Erin Doyle is an expert in creating accessible React applications and has developed a course that will give you a concrete process for testing, refactoring, and building your applications with accessibility in mind.

After this course, you'll have a jump start on auditing and fixing accessibility issues in your applications and gain a better understanding of your target users and how to approach your web app design from their perspectives.


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

Develop Accessible Web Apps with React

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

screen-reader

There are many techniques for hiding content in user interfaces, and not all are created equal! Learn how different hiding techniques in HTML, CSS and ARIA impact keyboard and screen reader users in addition to visual display. As a bonus, we'll also take a look using a screen reader on a mobile device.

How Visible vs. Hidden Elements Affect Keyboard/Screen Reader Users

AngularJS is an open-source JavaScript framework, maintained by Google, that assists with running single-page applications. Its goal is to augment web-based applications with model–view–controller (MVC) capability, in an effort to make both development and testing easier.

angularjs

In this lesson Trevor looks at testing AngularJS controllers with scope inheritance with Jasmine and test spies.

Testing Controllers With Dependencies

Custom Jasmine Matchers are a great way to keep your AngularJS Unit Tests clean and tidy. We want to make expectations **readable** and express the intent of the test. Custom matchers help to accomplish this.

Custom Jasmine 1.3 Matchers

An introduction on unit testing a ReactJS component using Webpack and Jasmine. Learn how to use Webpack to package and import dependencies plus take advantage of the babel-loader to write a simple Jasmine spec using the latest ES6 syntax.

Unit testing a React component using Jasmine and Webpack

AngularJS provides helpers for convenient testing of your application. In this lesson you will learn how to test a basic controller with Jasmine and Angular.

Testing a Controller

In this lesson John shows some tricks for speeding up your test suite. He digs into some handy features of WebStorm, including the *ddescriber* plugin, as well as some alternative methods for Jasmine for selectively running your tests.

Speed Testing with WebStorm and Jasmine

One of the beautiful things about dependency injection in your AngularJS apps is the ability to replace dependencies in your unit tests. In this lesson Trevor looks at how to configure Jasmine spies as injectable replacements for dependencies for testing.

Inject Jasmine Spies With $provide

Testing is a first class citizen in AngularJS. It is at its heart and soul. This lesson demonstrates using Karma to write a simple unit test for a Filter.

Unit Testing AngularJS

Unit testing a React component using Webpack and Jasmine, can involve slow and repetitive tasks when confirming that tests are passing when your code changes. For example, manually running commands instructing webpack to compile code plus refreshing the browser. This lesson demonstrates how to speed up your development time by automating these tasks using webpack-dev-server.

Reloading React component tests using webpack-dev-server

Using Jasmine, this lesson will look at testing an AngularJS service.

Testing a Service

The Chrome Developer Tools (DevTools for short), are a set of web authoring and debugging tools built into Google Chrome.

chrome-devtools

What's in a name? In this lesson, I'll explain the concept of naming interactive elements for screen reader users, including forms, buttons, and links. You'll learn how to debug accessible names and descriptions using the Chrome Accessibility Developer Tools (previously a Canary experiment, now in Chrome), using multiple labeling techniques. We'll also listen to the effects of proper accessible names and descriptions in Voiceover and Safari.

For more information and the nitty-gritty browser implementation algorithm, refer to WAI-ARIA 1.1: 
- https://www.w3.org/TR/wai-aria-1.1/#namecalculation
- https://www.w3.org/TR/accname-1.1/

What is Accessible Name Calculation?

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"))
```

Overview of the FaunaDB Query Language

When working with FQL it's often the case that you'll encounter `Ref`s. `Ref`s don't have any fields on them though! So how do we access the fields? `Get`.

```
Collections()
```

```
Collection("customers")
```

```
Ref(Collection("customers"), "244075679454331401")
```

```
Get(Ref(Collection("customers"), "244075679454331401"))
```

```
Get(Collection("customers"))
```



Refs and Get in FaunaDB

FQL Page objects have additional fields like `before`, and `data`, that may make it seem like you need to `Select` to get at the underlying array of results. However, FQL supports passing Page objects directly to functions that operate on arrays and the function will transparently operate on the contained `data` field.

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

```
Drop(1, Paginate(Match(Index("all_customers"))))
```

```
Take(1, Paginate(Match(Index("all_customers"))))
```

Search

Search Results