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

Learn Graphql

When your application communicates with multiple GraphQL services, it becomes problematic to distinguish them by operation type and name alone. Learn how to take the service's endpoint into account when intercepting GraphQL queries and mutations with Mock Service Worker.

- [`graphql.link()`](https://mswjs.io/docs/api/graphql#graphqllinkurl)

Endpoint-Based GraphQL Mocking in MSW

Let's improve our schema-first GraphQL mocks by intercepting _all_ GraphQL operations—both queries and mutations—using a single Mock Service Worker `graphql.operation()` request handler. 

- [`graphql.operation()`](https://mswjs.io/docs/api/graphql#graphloperationresolver)

Mock All GraphQL Operations in MSW

Operation-based GraphQL mocking allows you to move fast without investing time into schemas or resolvers. 

But, when integrating Mock Service Worker into an existing application, going schema-first can be advantageous. Here's how you can route every GraphQL request to be resolved against a GraphQL schema, mocked or real, and use mock resolvers to control individual types and fields. 

Resolve GraphQL Requests Against a Mock Schema in MSW

Error responses in GraphQL are a bit unique. They must still produce a "200 OK" response and list the errors in the response body instead. Let's follow the GraphQL specification to produce a valid GraphQL error response in our Mock Service Worker handlers. 

Mock GraphQL Errors in MSW

In this lesson, you will use the Mock Service Worker `graphql.mutation()` request handler to allow the users to leave reviews for the movie they've watched. 

- [`graphql` namespace](http://mswjs.io/docs/api/graphql)

Intercept and Mock GraphQL Mutations in MSW

Let's spice things up by adding GraphQL to our application. 

Since you are prototyping mock-first, you don't have to write any GraphQL schemas or define any resolvers. Instead, you will utilize Mock Service Worker to intercept valid GraphQL queries by their _type_ and _name_, and respond with the same semantic JSON responses matching the queries.

- [Describing GraphQL APIs](http://mswjs.io/docs/network-behavior/graphql)

Intercept and Mock GraphQL Queries in MSW

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.

javascript

Hi! My name is [Artem](https://kettanaito.com). In this course, I will teach you how to mock REST and GraphQL APIs with [Mock Service Worker](https://mswjs.io). Together, we will build a movie streaming application and you will learn how to intercept both server-side and client-side requests and mock responses using standard JavaScript API. This is a state-of-the-art mock-first prototyping with MSW.

- Join my [Discord server](https://kettanaito.com/discord) to go through the course with others, ask questions, and share feedback. See you there!

Introduction to Mock REST and GraphQL APIs with Mock Service Worker

Controlling the network is the key to fast prototyping, bullet-proof tests, and efficient debugging. 

Mocking the APIs you use gives you this kind of control but most methods in the client and server come up short. 

That's where Mock Service Worker does it right.

With it you can intercept and take control of requests no matter where they're being made.

In this course, you will learn how to:

* setup and your first request handler 
* mock complex flows like authentication
* describe dynamic requests
* respond with HTTP streams,
* and use schema-first GraphQL mocking

After this course you'll be more than ready to bring MSW into your app and start mocking any kind of API you're using!

Mock Service Worker is an API mocking library that allows you to write client-agnostic mocks and reuse them across any frameworks, tools, and environments. 

Controlling the network is the key to fast prototyping, bullet-proof tests, and efficient debugging. Mocking the APIs you use gives you this kind of control.

Mock REST and GraphQL APIs with Mock Service Worker

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

When a vendor manages their shops, they might want to click into the shop and mange the products associated with that shop. Let's create a page for that.

I'll create a details route that will host this information. On this page we will write a `GetShop` query that will take in the shop id that is pulled from the route. Similar to the shops page, we will iterate over the products on the shop and add buttons to manage individual products.

Create Shop Details View that uses GraphQL to Query Fauna by Shop Id

It would be great to show a list of shops that a vendor has created. To do this we will need to create a new query `getShopsByOwnerId` that accepts a string that will be our user id. Like before, we'll merge this schema change into Fauna and update our roles to make this request.

On the frontend we'll create a shop list component and pass in the user token that Auth0 gives us for the logged in user.

Query Data by Property with GraphQL and Fauna in Next.js

Fauna is a flexible database so we can update our schema without breaking any existing functionality. You'll notice that our products all have hard coded images. In this lesson, we'll update our `Product` to include an image and import those changes to Fauna.

Update the Product GraphQL Data Model and Upload Changes to Fauna

Next.js is a minimalistic framework for server-rendered React applications.

Query Data with GraphQL in Next.js from a Fauna Database

With our GraphQL schema in hand, we can create a full-fledged Fauna database. We'll import our GraphQL schema into a newly created database and explore the mutations and queries that were generated for us by creating and searching for a shop.

Upload a GraphQL Schema to Create a FaunaDB Database and Create a Shop

The next step is to model the data that we are going to use for our application, we'll have a Shop and Product. Shops will 'have many' Products. 

You'll see how to type this in a GraphQL schema with the different properties we want on Shop and Product. Additionally we will be introduced to the faunadb `@relation` directive which is similar to a foreign key constraint. 

[Read more about the @relation directive in the docs.](https://docs.fauna.com/fauna/current/api/graphql/directives/d_relation)

```typescript
# schema.graphql
type Shop {
  name: String!
  description: String!
  coverImg: String!
  products: [Product]!
  ownerID: String!
}

type Product {
  name: String!
  description: String!
  price: Float!
  category: String!
  shop: Shop! @relation
}
```

Model our Application Data with a GraphQL Schema


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 



Full-Stack Serverless Applications with Next.js & Fauna

In this course, Colby is going to do a deep dive into creating a full store for your products. You'll learn how to set up and use GraphCMS as your content management system. You'll learn about the Cloudinary UI extension and how to use it to host your images. You'll learn about Snipcart and using the useSnipcart hook to handle the cart state and the checkout. You'll learn how to implement Stripe as your payment gateway. And lastly, you'll learn how to deploy a Next js app to vercel from github with environment variables.

snipcart

Ecommerce Product Management & Storefront with GraphCMS, Snipcart, & Next.js

Apollo provides a universal GraphQL API on top of your existing services, so you can build new application features fast without waiting on backend changes.

apollo

We are going to start visualizing what our data looks like by using graphcms' Playground. Here we can query our data and explore our content API right from the dashboard. 

We are going to use Next.js getStaticProps to query our data at compile time so we don't have to make the browser wait for that request when it's getting loaded. 

To actually make our query, we are going to be using [Apollo Client](https://www.apollographql.com/docs/react/).

Query the GraphCMS GraphQL API with Apollo GraphQL

graphcms

To manage my product data, I'm going to use [graphCMS](https://graphcms.com/) which is a content management system that's going to give us a content API backed by GraphQL. You'll need to login, or register an account, with just the free version for this course. I will also run you through the initial setup for graphCMS. 

Set up GraphCMS to Manage Data with a GraphQL API

If users will be often querying the number of comments without also querying the list of comments

Then fetching the entire comment collection is wasteful. It's also not compatible with any pagination features that don't return the entire collection.

In this lesson, we will create a custom Data Loader specifically for counting items

Count the Items in a Collection with a Custom Data Loader

The simplest way to count the comments on a post is to use a Data Loader that returns all of the comments and return the length.

As long as the primary access pattern is to always fetch the number of comments along with the comments themselves, the Data Loader will batch them together and you'll get the count for free with no extra database requests.

Count the Items in a Collection By Reusing a Data Loader

One-to-many relationships are a prime candidate for scaling issues. In this lesson we'll add a new loader to fetch all the comments for a given post ID.

Fetching Many Items by Key with GraphQL DataLoaders

When comparing two visually similar websites, it can often be challenging to precisely identify the subtle differences between them. To facilitate a rapid analysis of these discrepancies, a practical technique involves leveraging Chrome's integrated developer tools to capture full-page screenshots of each site. Subsequently, these screenshots can be uploaded to a platform like AI Studio. There, the AI can analyze the images and generate a report detailing the variations. This entire process, leveraging a few quick shortcuts, can be completed in under a minute, delivering a comprehensive breakdown of the differences for efficient comparison and analysis.

Quickly Compare Two Sites Using AI Studio with Chrome Full Page Screenshots

It's fairly trivial to create a React project, but there's always a big hurdle between creating it locally and making it shareable so that someone else can run it. This lesson walks you through the process of automating creating a React project locally, creating the repository where it's going to be hosted, and creating shareable links where it can be run so that you can quickly and easily create single one-off demos and shoot them over to your friends and coworkers for sharing your code ideas in a working environment.


```bash
share-react-project() {
  if [[ -z "$1" ]]; then
    echo "Usage: share-react-project <project_name>"
    return 1
  fi

  local project_name="$1"
  local github_username=$(gh api /user --jq '.login')

  echo "Creating Vite project: $project_name"
  pnpm create vite "$project_name" --template react

  cd "$project_name"

  echo "Initializing Git repository"
  git init

  echo "Adding all files to Git"
  git add .

  echo "Creating initial commit"
  git commit -m "Initial commit"

  local codesandbox_link="https://codesandbox.io/p/github/${github_username}/${project_name}"

  echo "Adding CodeSandbox link to README.md"
  echo "" >> README.md
  echo "## CodeSandbox" >> README.md
  echo "[![Open in CodeSandbox](https://assets.codesandbox.io/github/button-edit-blue.svg)](${codesandbox_link})" >> README.md

  echo "Adding README.md to Git"
  git add README.md

  echo "Committing README.md changes"
  git commit -m "Add CodeSandbox link"

  echo "Creating GitHub repository: $github_username/$project_name"
  gh repo create "$github_username/$project_name" --public

  echo "Pushing to remote 'origin'"
  git push -u origin main

  echo "Project '$project_name' created successfully!"
  echo "GitHub repository: https://github.com/$github_username/$project_name"
  echo "CodeSandbox link: $codesandbox_link"
}
```

Automate Creating a Local React Project, GitHub Repository, and Live Hosted Demo in a Single Command

[Verdaccio](https://verdaccio.org/) is a fully featured NPM registry that you can run locally on your machine. It’s a great tool for testing your release process, running end-to-end tests, and simulating real-world scenarios like deploying packages, installing them, and verifying functionality as an end user would.

Nx includes a [generator](https://nx.dev/features/generate-code) that simplifies setting up Verdaccio. To configure it, run:

```shell
npx nx g @nx/js:setup-verdaccio   
```

This command installs the necessary NPM packages and creates a `project.json` file with a `local-registry` target. To start the local registry, open a new terminal window and run:

```shell
npx nx local-registry
```

This will:
- Launch the Verdaccio registry.
- Configure NPM to point to the local Verdaccio server at `http://localhost:4873`.

> **Note:** A `project.json` file provides an advanced way to define scripts, offering more flexibility than a traditional `package.json` for managing complex targets.

Setup local Verdaccio server to release NPM packages

Learn how to spin up a local NPM registry powered by Verdaccio to test deploy your NPM packages.

In TypeScript, developers often begin by defining the structure of their data using type definitions or interfaces, which is a powerful way to ensure type safety. However, as applications grow and become more complex, simply defining the shape of an object might not be enough to guarantee its consistent creation and behavior throughout the codebase. This often leads to situations where objects that are intended to be of a certain "type" might be missing crucial properties or have incorrect data, which can be difficult to track down and debug.

This lesson tackles the question of when and why to move beyond basic type definitions and embrace classes in TypeScript. It demonstrates how classes provide a more robust mechanism for defining object structure, enforcing type constraints, and ensuring consistent object creation. By establishing a clear blueprint for objects, classes not only improve compile-time type safety but also offer runtime benefits and better code organization, ultimately helping developers avoid common pitfalls associated with loosely structured objects in larger TypeScript projects.

Stop Avoiding Classes in TypeScript

Karabiner isn't only for your keyboard. It can also hijack your mouse buttons and enable them to be similar to layers on your keyboard, where holding down a mouse button can allow you to tap keys on your keyboard to trigger commands and macros that can completely revolutionize your workflows. For example, you can hold down the right mouse button and tap on R to go to references in VS Code. Or hold down the right mouse button and tap the left mouse button to chop up videos and Screenflow.

This completely unlocks a whole new world of possibilities and use cases for your mouse as you can hover your mouse over anywhere on the page. And just tapping keys on your keyboard allows you to trigger mouse actions, to trigger keyboard actions, or to trigger macros and applications and terminal commands. and anything that your imagination can come up with. 

Karabiner: Rethinking Right-Click as a Macro Command Center

Make an HTML table more readable on mobile devices by using the ::before pseudo-element. We add labels to each cell, so they appear like cards when the table is viewed on smaller screens. The ::before content is set using a data-label attribute for each cell to enhance mobile viewability without horizontal scrolling.



Create a mobile friendly table with the before pseudo-element

Learn to use CSS ::before pseudo-element for mobile-friendly HTML tables. Add labels to cells for enhanced readability on mobile, avoiding horizontal scroll.

Any app of a decent size has event flows and messages being passed around. At a certain point it becomes complicated to explain it through prose and you want to turn towards diagrams. Now setting aside the time to create diagrams that accurately describe what's happening in your codebase can be quite time consuming. Luckily, with today's AI tools, we can now just do basic walkthroughs with rough recordings over codebase dictating what's going on along the way and then upload that to tools like AI Studio and then ask it to generate diagrams in a text-based format such as Mermaid that will then generate the flowcharts and diagrams for us. So this video walks us through this process of recording a rough video, uploading it to AI Studio and then asking AI Studio to generate the proper Mermaid diagram syntax.

Generate Mermaid Flow Chart Diagrams with Gemini 2.0 from Rough Screen Recordings

I'm a diehard Karabiner user and anytime I start doing something repetitively I always move it into my Karabiner configuration. Sometimes I'll fall into scenarios where I want to trigger a command, but I also want to know if that command succeeded or failed. Since Karabiner can trigger any command, setting up the command is fairly straightforward, but knowing whether it succeeded or failed became much more difficult. Luckily for me there is a package called terminal-notifier that you can install from homebrew and you can pipe the output of your command to terminal-notifier. And have a seamless way of triggering your keyboard shortcut which runs a command and you can be notified of the results.

Use Karabiner to Trigger a Terminal Command and Get Notified of the Results

There are a lot of scenarios when inspecting a site in Chrome where you don't want any click events to fire and you don't want any scripts to run. Or maybe something is animating in and out of the page and you want to capture it at a certain moment. This is a great use case for pausing script execution, which is kind of using the debugger manually by going into the Chrome DevTools and the Sources tab and clicking the pause button to essentially pause the entire page. This will give you a chance to inspect any of the elements and styles you want to inspect. And you don't have to worry about fire and click events or anything that might interrupt your investigation into the elements and styles that you want to find.

Pause Script Execution in Chrome to Easily Inspect Elements

Gemini 2.0 has a context window of a million tokens, and this means that you can upload hundreds of files and allow it to inspect and analyze massive refactors across entire code bases. 

This lesson demonstrates concatenating an entire code base into a single file and then uploading it to AI Studio. Once within AI Studio, we ask it to find the types of tasks that it can evaluate for us. Then we select one of the tasks and ask it to generate instructions for that task. Once those instructions are complete, we then turn them over to Windsurf's Cascade agent, and we allow Windsurf's Cascade to do all of the work for us as we sit back, relax, and let the AI do our jobs.

GraphQL

Secure GraphQL

Securing GraphQL Backends with JWTs

Up and Running

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

Getting Started With Hasura and GraphQL

Learn Apollo Client Hooks

For Your Porfolio

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

React Real-Time Messaging with GraphQL using urql and OneGraph

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

Going Serverless with GraphQL

Scalable Offline-Ready GraphQL Applications with AWS AppSync & React

GraphQL Data in React with Apollo Client

Building Serverless Web Applications with React & AWS Amplify

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