Learn Faunadb, Npm and Webstorm

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

You can’t be everywhere at once. Neither can node packages. But with a utility called npx — included in npm v5.2 and later — you can interact and run with node modules even if they’re not downloaded locally. The same is true for gists and remote branches of GitHub. As long as npm installed, your work can be wherever you are.

This course from Elijah Manor unlocks the power of the npx utility. Over 17 minutes, we will examine the npx package runner and look through various scenarios where the tool is helpful when running node packages from the command line. You’ll learn to use npm to:

- test out various versions of a package
- run packages without globally installing
- run code directly from GitHub
- make working with packages much easier

npm is the package manager for JavaScript. Find, share, and reuse packages of code from hundreds of thousands of developers — and assemble them in powerful new ways.

Execute npm Package Binaries with the npx Package Runner

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

npm is like a giant library of code building blocks. There are tons of these “blocks”, aka “packages” that we can compose together to build cool things. We can use packages by other developers, but we can also write and publish our own. 

In this course we will learn how to create, publish, and update our own packages. We will create a JavaScript utility module to filter out sensitive words from a string, including tests and development file watching. We will then cover publishing and updating our package. This same approach can be used to create and publish other types of packages too like components (React, Angular, Web Components etc.) and command line interfaces.

Publish JavaScript packages on npm

In this course we will introduce the topic of using npm scripts as a build tool. We will start simple and then continue to build a small website as we introduce new topics. By the end of the course, you'll know how to get started and what tools and techniques are needed for you to create your own set of build scripts.

How to Use npm Scripts as Your Build Tool

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"))))
```

FQL Page objects can be arguments to array functions

`Ref`s are opaque. To access the fields on a document associated with a Ref, we first need to run `Get` on our results and then we can access fields using `Select`

```
Map(
  Paginate(Match(Index("all_customers"))),
  Lambda("X", Get(Var("X")))
)
```

```
Map(
  Paginate(Match(Index("all_customers"))),
  Lambda("X", Select(["data", "firstName"], Get(Var("X"))))
)
```

Accessing fields through Refs with Select

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

Overview of the FaunaDB Query Language (FQL)

When working with FQL it's often the case that you'll encounter Refs. Refs 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"))
```

Getting fields out of Refs with Get

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"))))
```

FQL Page objects can be arguments to Array functions

Lambdas allow you to use functions like Map or Filter effectively in FQL. In this lesson we should the Lambda syntax by operating on some paginated results.

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

```
Map(
  Paginate(Match(Index("all_customers"))),
  Lambda("X", Get(Var("X")))
)
```

Using FQL Lambda in Array functions

`Ref`s are opaque. To access the fields on a document associated with a `Ref`, we first need to run `Get` on our results and then we can access fields using `Select`

```
Map(
  Paginate(Match(Index("all_customers"))),
  Lambda("X", Get(Var("X")))
)
```

```
Map(
  Paginate(Match(Index("all_customers"))),
  Lambda("X", Select(["data", "firstName"], Get(Var("X"))))
)
```

FaunaDB supports access keys with four sets of permissions, or roles. You need an access token to use a language driver like the Go driver to access FaunaDB. It is not exposed by default. The four roles are: Admin, Server, Server-ReadOnly, and Client. We'll go over what these roles are and how to choose one for your use case.

Creating an access token and choosing a role for it

You can use array and object literals to compose multiple selections into a single query, such as within a lambda.

```
Map(
  Paginate(Match(Index("all_customers"))),
  Lambda(
    "X",
    Select(["data", "firstName"], Get(Var("X")))
  )
)
```

with arrays

```
Map(
  Paginate(Match(Index("all_customers"))),
  Lambda(
    "X",
    [
      Select(["data", "firstName"], Get(Var("X"))),
      Select(["data", "lastName"], Get(Var("X")))
    ]
  )
)
```

with objects

```
Map(
  Paginate(Match(Index("all_customers"))),
  Lambda(
    "X",
    [
      Select(["data", "firstName"], Get(Var("X"))),
      Select(["data", "lastName"], Get(Var("X")))
    ]
  )
)
``````
Map(
  Paginate(Match(Index("all_customers"))),
  Lambda(
    "X",
    {
      firstName: Select(["data", "firstName"], Get(Var("X"))),
      lastName: Select(["data", "lastName"], Get(Var("X")))
    }
  )
)
```

Selecting multiple fields in an FQL query

The FaunaDB CLI is distributed on NPM and includes an interactive shell as well as the ability to send queries from a file.

```
npm i -g fauna-shell
fauna cloud-login
fauna -h
fauna list-databases
```

open a shell to a database:

```
fauna shell test-demo
```

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

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

Running queries from a file

```
fauna eval test-demo --file=./fauna.fql
```






Topics

Instructors

Content Type

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

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

Execute npm Package Binaries with the npx Package Runner

The Complete Guide to FaunaDB

Publish JavaScript packages on npm

How to Use npm Scripts as Your Build Tool

An Introduction to FaunaDB

Overview of the FaunaDB Query Language

Refs and Get in FaunaDB

FQL Page objects can be arguments to array functions

Accessing fields through Refs with Select

An Introduction to FaunaDB

Creating your first FaunaDB database

Overview of the FaunaDB Query Language (FQL)

Getting fields out of Refs with Get

FQL Page objects can be arguments to Array functions

Using FQL Lambda in Array functions

Accessing fields through Refs with Select

Creating an access token and choosing a role for it

Selecting multiple fields in an FQL query

Installing the FaunaDB CLI and using it to send queries from a local file