Learn Graphql, Microsoft and Python

One of the most well-known GraphQL features is that it lets you do things like replacing multiple REST calls with a single query. You might have done some query experimentation with demo APIs or working on a Gatsby site. 

But there's more to GraphQL than just making queries.

For example, with mutations and subscriptions, GraphQL can smooth out the process of implementing real-time features in your web applications.

In this new course, you'll get practice with these features as egghead's own Ian Jones guides you through building a real-time chat app that's backed by GitHub Issues.

The tools used for the course are OneGraph and Formidable Labs' urql client.

OneGraph is great because it allows you to expose a single GraphQL endpoint that can access data from multiple services including GitHub, Stripe, Airtable, and more. It handles things like authentication for us as well, as you'll see in the course.

At Formidable Labs, the team released urql as a lighter weight alternative to Apollo or Relay that supports the most common interactions with a GraphQL server through their handy React Hooks. 

The course starts with a fresh Create-React-App and touches upon topics like using GraphQL query variables, working with Hooks, handling authentication with React Context, and setting up & consuming the GraphQL subscription.

Along the way, Ian also works through debugging some common errors that you may encounter when developing your own GraphQL apps in the future!

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.

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React Real-Time Messaging with GraphQL using urql and OneGraph

_Note: this course is being published and released as it is recorded, and is still incomplete. It is slated to be around a dozen videos._

Learn how to build PlaylistHunt, a fully featured app with authentication, authorization, a GraphQL API, and more, using up and coming modern tools, including:

- Gatsby
- Hasura
- Heroku
- Auth0
- Chakra UI

[View the demo](https://playlisthunt.netlify.app/) live online!

Most tools used are open source, with the exception of Auth0 and Heroku, which offers a generous enough free tier for hobby apps to be developed without any problems.

## Modern techniques

In the process, implement techniques to make your app experience dynamic on some portions, and static in others. 

Learn to how to build for Gatsby's vast and powerful plugin ecosystem by creating 3 of your own custom plugins in the process.

Use the latest and greatest of Gatsby, like the brand new [file-system routing APIs](https://www.gatsbyjs.com/docs/file-system-page-creation/). 

## Who is this course for?

Intermediate developers with some existing knowledge of React and web development are best suited for this course. The pace is a little quicker and aims at showing how all the pieces connect together to make a modern JAMstack app.

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.

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Build a full-stack JAMstack application with Gatsby, Hasura, and Auth0

GraphQL brings joy to using APIs. Even though it's based on a type system, GraphQL in many ways is more flexible than REST.

But the flexibility that makes GraphQL a joy to work with can have its downsides if you aren't careful.

Schema design is an area where one small oversight at the beginning can get you stuck having to deal with weird naming, bloated duplicates, and other annoying workarounds.

It doesn't have to be like this!

Nik Graf has extensive experience designing GraphQL schemas, for a variety of business applications.

In this course, Nik has prepared several examples following different design patterns. Through exploration and comparison, you'll come away with actionable knowledge for designing and extending schemas.

Follow Nik, and avoid making Schema mistakes that will come back to bite you later.

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.

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Designing GraphQL Schemas

GraphQL is gaining traction as one of the most popular ways to create an API. Regardless of which GraphQL implementation you pick, you’ll use the QL in GraphQL — the query language — to query data, change data with mutations, and listen for data changes with subscriptions.

You need to know the Query Language regardless of the server-side implementation.  In this course, we will learn the GraphQL query language by sending an assortment of GraphQL operations to an existing API. 

To start, we’ll learn how to write queries to obtain all the data needed for an app in one response. As the course progresses, we’ll use mutations to add and change data. To wrap up, we’ll investigate GraphQL subscriptions and realtime data. 

After the course, you’ll be ready to communicate with a GraphQL API regardless of server-side implementation using the GraphQL query language.

GraphQL Query Language

A short list of screencasts to cover essentials of [Gatsby](https://www.gatsbyjs.org/) to get started and have enough knowledge to become dangerous. 

The content comes from multiple instructors that have each covered different essentials, this cherry picks some of the most important concepts.

Videos in this collection cover these topics:
- installing plugins
- creating pages
- navigating between pages
- adding optimized images
- theming your styles
- deploying your site

Up and Running with Gatsby

In this playlist, we are going to go over how to set up and use urql as a GraphQL client. 

You will learn how to set up an Urql `Provider` component so that all of your React components have access to urql. Then you will learn how to use 3 of urql's React Hooks:

- useQuery
- useMutation
- useSubscription

Each of these lessons covers their corresponding GraphQL topic: Queries, Mutations, and Subscription.

Visual Studio Code is an integrated development environment (IDE) built and maintained by Microsoft. It is offered free of charge.

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Introduction to Urql: A React GraphQL Client

Learn how to add optimized images to your Gatsby site with the `gatsby-image` plugin.

These videos dive into:

- installing and configuring plugin options
- sourcing images to be queried via GraphQL
- displaying traced-svg or "blurred-up" images
- different image types supported by `gatsby-image`
- as well as alternatives for using images in Gatsby

Image Loading and Optimization in Gatsby with gatsby-image

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.

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

WordPress is the most popular content management system in the world. Content creators are able to easily customize nearly everything about WordPress from their admin dashboard, providing a really pleasant content management experience. Using Gatsby as a frontend for your WordPress sites makes the experience of developing the site and visiting the site just as pleasant.

Moving your WordPress frontend to the Jamstack means you keep the convenience of using WordPress’s custom backend for creating and editing content while _also_ avoiding some of WordPress’s biggest downsides.

Historically, WordPress has many downsides, including:

- **Security** — because it’s the most popular content management system in the world, hackers work hard to find and exploit security holes in WordPress sites.
Performance — through a combination of legacy code, community plugins, and other challenges, WordPress sites can easily become slow to load.
- **Scale** — if a WordPress site suddenly becomes very popular (a great thing!) it can overload servers and cause the website to go down (a not-so-great thing!) without complex scaling techniques.
- **Cost** — a WordPress site requires always-on hosting, and specialized hosting can be expensive. Adding support to handle massive scale adds significant cost, too.

Switching to the Jamstack helps mitigate — and even eliminate! — these downsides:

- **More secure** — Jamstack sites don’t connect to the server or database after they’re built. This makes it much harder to hack the site.
- **More performant** — by doing less work for each request and leveraging modern tools, Jamstack sites tend to outperform WordPress sites out of the box, and can be very fast with a bit of extra effort.
- **More resilient** — because Jamstack sites ship to a content delivery network (CDN) by default, a sudden surge of site visitors won’t take your site down.
- **More affordable** — many Jamstack hosting solutions have generous free tiers that are plenty for most small to medium sites, and upgraded accounts typically cost less than specialized WordPress hosting.

Switching to the Jamstack gives you all of the benefits of WordPress and helps you avoid the downsides!

In this collection, we walk through the full process of migrating a WordPress site to the Jamstack, which keeps all the flexibility and power of WordPress’s admin dashboards while adding all the benefits of the Jamstack.

Migrate a WordPress Site to the Jamstack Using Gatsby

Neural networks, with Keras, bring powerful machine learning to Python applications. They can answer questions like “How much traffic will hit my website tonight?” or answer classification questions like “Will this customer buy our product?” or “Will the stock price go up or down tomorrow?”

In this course, we’ll build a fully connected neural network with Keras. This is the most basic type of neural network you can create, but it’s powerful in application and can jumpstart your exploration of other frameworks. 

We’ll start the course by creating the primary network. Then we’ll:

- build and configure the network, then evaluate and test the accuracy of each
- save the model and learn how to load it and use it to make predictions in the future
- expose the model as part of a tiny web application that can be used to make predictions

You don’t need to know a lot of Python for this course, but some basic Python knowledge will be helpful. Enjoy!

Python is a widely used dynamically typed programming language. It allows for many different programming paradigms including object-oriented, imperative, functional programming, and procedural styles.

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Fully Connected Neural Networks with Keras

With GraphQL, you can define the shape of your data in a schema, and GraphQL will fulfill the request with the precise data you need. When you need it. This doesn't come without a cost. GraphQL adds a lot of complexity to your application by requiring you to define your schemas through types, mutations, and resolvers.

AppSync is a fully managed serverless GraphQL service that fast-tracks your API development. You can define a single type, and AppSync auto-generates a schema, queries, mutators, and subscriptions for you.

In this course, Nader Dabit will show you how to:

- build a production-ready GraphQL API through AWS AppSync
- create and modify data through the AWS AppSync console
- connect a React application to the GraphQL API
- execute queries, mutations, and subscriptions for data through the API in React

Scalable Offline-Ready GraphQL Applications with AWS AppSync & React

GraphQL is a fan favorite for good reason. It lets a client make specific, complex, and/or aggregate queries for data, and it’s user-friendly to boot.

If you’ve been meaning to learn GraphQL and start harnessing its powers, this is a great place to start.

This course is for GraphQL newbies with a basic understanding of React. It focuses on the client-side implementation of GraphQL usage using the Apollo client.

We’ll start with a guide on how to add the Apollo client to an existing project, then move on using the Query and Mutation components to fetch and manipulate data using a GraphQL API.

GraphQL Data in React with Apollo Client

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 Introduction to Python, we will start at the beginning: Installing python 3 and using virtual environments. With a working environment, we will learn how to manipulate strings and numbers, and gain working knowledge of data structures and flow control. We will build on that by introducing modules and classes and learn how to interact with our python applications using command line switches, console input and files.

At the end of this course, you’ll have a great working knowledge of Python, fully capable of creating your own Python projects from scratch or jumping into an existing application with the capability to read, understand, and contribute to the application.

Check out these [**community notes for this course on Github**](https://github.com/eggheadio-projects/introduction-to-the-python-3-programming-language-notes).

Introduction to the Python 3 Programming Language

Introduced in React 16.8, Hooks are a new way to write stateful components while avoiding the pitfalls of classes. 

As a result, GraphQL developers everywhere wanted to use them for their Apollo Client components, instead of relying on render props pattern. In August of 2019 things have changed and Apollo Client now has official support for React hooks, by providing `useQuery`, `useLazyQuery`, `useMutation` and `useSubscription` hooks.

If you'd like to learn how to use them, this playlist is for you!

Learn Apollo Client Hooks

Artificial intelligence. Machine learning. Bots. Computers learning and communicating with us to do our bidding. But, where do you start? How do you get a machine to even begin to understand what you speak or type at it? There are several common machine learning algorithms that will help us begin to answer these questions.

In this course we’ll learn about common machine learning algorithms that don’t require implementing a neural network. We will not be going too much into the math behind them, but instead learn what each algorithm is good for, and how to train them. We'll also learn about a few metrics for evaluating models.

We’ll implement these in Python using `scikit-learn` using `scikit-learn`’s built-in data sets. The focus of this course is on implementation and a high-level understanding of these algorithms. 

We'll look at a few ways to evaluate our models, for both classification and regression models. We'll touch on mean squared error and coefficient of determination (for regression), and accuracy score, logarithmic loss, confusion matrices, and classification reports (for classification). 

Python 2.7 is used in the lesson videos but the code provided has Python 3 available. The only breaking change is the `print` statement API.

For additional information on installation, vocabulary, and common errors visit the `README.md` to the course code attached to each lesson.

Simple and efficient tools for data mining and data analysis

scikit-learn

Introductory Machine Learning Algorithms in Python with scikit-learn

AWS Amplify allows developers to create, configure, and deploy Serverless APIs and functions directly from their front-end environment.In this collection, you'll learn how to deploy various types of APIs and functions using the Amplify CLI. You'll also learn how to share code among various functions using Lambda layers and schedule functions to run at an interval to implement Serverless cron jobs.

JavaScript® (often shortened to JS) is a lightweight, interpreted, object-oriented language with first-class functions, most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic, and supports object-oriented, imperative, and functional programming styles.

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Up and Running with AWS Amplify Functions

In this course, we take a look at a new data query language and runtime called GraphQL. GraphQL was designed and built at Facebook to help product developers request and receive the data they need for their mobile and web applications. GraphQL sits on top of your application’s data access layer, providing clients with the ability to explicitly specify their data requirements and the guarantee that this data won’t change.

GraphQL manages these kinds of guarantees through a mixture of its Type System and Query semantics, both of which are pieces of GraphQL that we’ll look at in this series. We’ll also take a look at Mutations, and how to make our GraphQL Servers Relay-compliant using Nodes, Edges, and Connections.

Build a GraphQL Server

This collection of videos teaches you how to use [KeystoneJS](https://v5.keystonejs.com) to build a CRUD-ready GraphQL API, coming with an automatically generated Admin UI. 

Starting with a blank file, we will create an API by:
- defining "Lists" as content types
- adding fields (Select, Text, Checkbox, ...) to our lists
- customising access control to define what users can (and cannot!) do with our API.

Build a CRUD-ready GraphQL API + Admin UI with KeystoneJS

Learn how to create tuples in Python. The videos in this collection will also cover more advanced features of tuples

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