Learn A11y, Bash and Faunadb

Dive into the world of real-time web development with this hands-on course! You’ll learn how to build a dynamic chat application using Fauna Streams and Next.js 14, focusing on the essentials and best practices.

**What You’ll Learn:**
- **Next.js Best Practices:** Master Next.js best practices for building fast, maintainable apps.
- **Server-Side Rendering (SSR):** Learn SSR techniques and master features like server actions, server side form submission etc.
- **Database Access Patterns:** Efficiently connect and retrieve data using Fauna.
- **Real-Time Updates:** Implement real-time updates with Fauna Streams.
- **Basic Authentication:** Secure your chat app with simple authentication methods.

**Course Highlights:**
- Practical, project-based learning.
- Clear, step-by-step instructions.
- Focus on modern, real-time web development.
- Tips and tricks for optimizing performance.

By the end of this course, you’ll have a working real-time chat app and a solid grasp of the tools and techniques used to build it.


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

Build a Real-time Next.js 14 Chat App with Fauna 

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

Now that we have user information available to us, we want to connect messages created to the users that are sending them. When we add `read` privileges to the `User` model, we can call `User.identity()` to get the user data we need to set for messages. 

Update Fauna Messages Collection with Authors

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

For user signin, we'll implement a proper server action by creating a `actions.js` file where our server actions can live. In our login page, we'll set the component to be a client component to hold some state. This way we can use the new `useFormState` hook from `react-dom` and pass in our login server action.

Within the action we'll call our `UserLogin` function from Fauna and set a cookie with the secret we get back that we can use throughout our application.

Implement Fauna Signin with Next.js Server Actions and useFormState React Hook

Now it's time to actually sign users up for our appliaction.

We'll implement the `doSignup` function that we created earlier. This function will run on the server with the `'use server'` directive so we can instantiate a fauna client and call `UserRegistration` within this function.

From there we'll redirect the user to the `/signin` page which will error out because it's not implemented yet.

Implement Signup Functionality through Fauna with Next.js 14 Server Actions

To have actual users in our application we need to represent those users in our database. Fauna has quite a few ways you can do user authentication but we'll be creating our own using a few built-in Fauna helpers.

We'll start by setting up the necessary Fauna logic for users. We'll add a `User` collection as well as a `functions.fsl` file that we'll expose user sign up and log in. Here we'll see how Fauna gives us a built in `Credentials` document to handle email and password for a user. It also has a login function that it exposes to make that easy for us which will generate a token for a user on login.

After setting up our functions, we'll add an `UnAuthRole` as well as an `AuthRole` and give proper actions for each role.

Add Fauna User Authentication to a Next.js App

To stream messages, we'll implement logic very similar to how we stream the creation of rooms from earlier.

First, we need to convert `MessageList` into a client component. We'll get an interesting error saying that only plain objects can be passed to client components from server components. This happens because the response we get back from Fauna is pretty complex. To fix this error we'll create a simple messages array and pass that down to the `MessageList` component.

In the `MessageList` component we'll create a `useEffect` that will initiate a Fauna stream within a ref and push new messages into state that we are holding in the component.

Stream Chat Messages in Real-time in Next.js from Fauna

Now it's time to actually create messages and display them in rooms within our application.

We'll start by creating a `MessageForm` component that will send a `Message.create` query to Fauna on form submission.

Next, we'll display these messages by updating our room query to also get all the messages for that room. You'll see that we can still just perform one query because we pass in the room id and call `Message.where(.room == room)` to the query.

One note here is if you console log your messages in your page component, you'll notice that the logs show up in the terminal and not the browser. This is because we are using a server component.

Create and Display Messages using Fauna within a Room in Next.js

We'll take a moment to explore how Fauna handles one-to-many relationships inside the fauna shell. 

First we'll create a `Message` collection.

Then we'll connect to the cloud database by running `fauna shell`, because I'm logged and configured this connects to the database I'm working with.

In the terminal we'll see how to create multiple messages that are associated with a room and query for those messages by room.

Explore Faunas one-to-many Relationships between Collections in the Terminal

With rooms being created and displayed on the index page, it's now time to create dynamic routes for each room so that when you click on a room name, you are actually navigated to that room.

We'll do this by using Next.js dynamic route syntax `/rooms/[...id]/page.js`. This will render a page on any `/rooms/:id` passing the component we define the `:id` as params.

Here we'll take that id and fetch the room data from fauna with a `Room.byId` query.

Create Dynamic Routes in Next.js for Chat Rooms

We can add rooms but our application does not update and display rooms when a room is added. This should happen in real-time.

To fix this we'll add a useEffect that will query for all our rooms and use fauna's `client.stream` API to ensure that this happens in real-time.

List Available Chat Rooms in Real-time in Next.js from Fauna

The first step to building a chat app is to have rooms to chat in. We'll need to create a Room collection (or table) in Fauna that we'll be adding to.

In our Next Application we'll create a simple form that has a submit handler that will create those rooms in Fauna. We need to hold some state in our component so we'll turn the page into a client component with `'use client'`.

There will be a little bit more Fauna set up to get things working. We need to create a key for our application to interact with our database so we'll create a key by running `Key.create` in our `fauna shell`. Then we'll install the `fauna` client and make a `client.query` to create the room.

Create a Fauna Room Collection in Next.js with the fauna Client

The first step is to install and configure our database that will be backing our Next.js application. We'll be using Fauna so we head over to the Fauna website and create a database.

Back in our terminal we will install `fauna-shell` so we can interact and manage our database from within our project. After some initializing steps from the CLI we'll be set up to build the app out.

Initialize and Configure a Fauna Database inside a Next.js project with fauna-shell

“a11y” stands for “accessibility.” It is a numeronym, with 11 representing the count of letters between the letter a and the letter y.

Accessibility is broken down into 4 categories of disability: visual, cognitive, auditory, motor. 

Regardless of the category of disability, accessibilities aim in web development is to make applications and websites usable for everyone.

a11y

In this course, we'll be focusing on building an accessible component by using a built-in browser API with React to implement best practices in accessibility custom features. 

Everyone is responsible for accessibility, and we need to start creating features and websites with that in mind. The goal of this course is for you to exploit your understanding of HTML and aria, and be able to look at any common features and identify the different accessibility patterns. 

With this course you won't only learn about accessibility, but also will learn about `HTMLMediaElement` API, and state management in React. 


 





Introduction to Creating a Custom Accessible Audio Player with React

React's `forwardRef` function allows a component to receive a ref that has been created outside of it. This can be useful in cases where you want to have a specific part of your component, such as a section of a long transcript or a specific part of an audio recording, referenced from outside the component.

One example of when this might be useful is if you have a "listicle" type of audio, such as "5 things your tech resume needs", and you want to allow users to jump to specific parts of the audio. By converting the component to a forwarded ref component, you can create a ref in the parent component (in this case, the "App" component) and pass it into the audio component. This allows you to create a few buttons in the parent component that can control the audio ref and jump to specific audio sections.

To convert a component to a forwarded ref component, you can use React's `forwardRef` function to wrap the component, and then remove the audio ref and replace all instances with the new ref.

By doing this, you can now control the audio component, like play, pause and jump to a specific time, by interacting with the `audioRef` ref object created in the parent component and passed into the audio component.

**Think about:** What ways to control the audio outside the component could help with accessibility?

Using a forwardRef to Create External Controls

We are creating an accessible popup menu for a web application. It covers various concepts, including handling keyboard events, creating a new dropdown component for reuse, using arrow keys to navigate through buttons, using the Tab key to close the menu and go to the next item in the tab order, using the Escape key to close the menu and focus on the button that closes it, using the `aria-expanded` attribute to communicate whether the menu is open or closed, and the difference between the tab index values of 0 and -1. 

**Think about:**
- Why tabindex -1?
- Why would you use arrows versus tab key to navigate through the dropdown?

Create a Dropdown Menu for Rates

In this lesson, we are using HTML, accessibility concepts, and ARIA attributes to improve the time scrubber feature of an audio player. 

The goal is to make it accessible to users of screen readers so that the time scrubber announces the actual time (e.g. 12 minutes and 15 seconds) rather than just the value (e.g. 735). 

We are also creating a new folder called "helpers" in the "src" folder and a new file called "format time.js" within it to hold a function called "format human read time" that takes time as a parameter and returns the human-readable equivalent of that time. Additionally, the author debugs the code and uses console.log to check the variable.

**Think about:** Why does a human-readable name help?

Create a Human Readable Time Formatter

I suggest using the previously learned approach but keep in mind that it may lead to an overly complex markup. We also use the `aria-label` attribute, which can be used to override the text within a label element.

**Think about:** Why would you use an `aria-label` instead of creating a visually hidden span?

Using Aria-Label as a Solution for Overly Complex Markup

We create an input range with a label, where the range is between 0 and 1 with a step of 0 - 1. The input's value should be determined by a ternary statement that checks if the volume is muted and sets it to 0 or to the current volume if not muted. 

An `onVolumeScrubberChange` function is also added that sets the volume to the event target value when the input value changes and updates the volume in the state and an audio reference. The `onVolumeChange` function does not need to be used and the logic needs to be adjusted to ensure that the volume can be updated and that it mutes when the volume reaches 0.

**Think about:** Why do we have to add `audioRef.current.volume === 0` in addition to `audioRef.current.muted`?

Implementing a Volume Range with an onChange Event

We are creating a toggle button for muting and unmuting an audio element using React hooks `useState` and `useRef`. It destructures `isMuted` from the `useState` hook and sets the initial state to false. 

The button's inner text is dependent on the state of `isMuted`, and a `toggleMute` function is created which sets `isMuted` to the opposite of its current state and also sets the `audioRef.current.muted` property to the opposite of `isMuted`. 

A `onVolumeChange` function is added to the audio element that sets the `isMuted` state based on the value of `audioRef.current.muted`. This allows the `isMuted` state to change even when the mute button on the audio element itself is pressed.

**Think about:** 
- Why do we have to add `onVolumeChange` for instead of `onMuted`? 
- How can we use `onVolumeChange` to check for things being muted?

Creating a Toggle Button for Muting and Unmuting an Audio Element in React

We are creating a playback rate button in a React application. An array of rates is created, and each element of the array is mapped to a button. Each button is given an onClick handler that calls an anonymous function called `changeRate`. 

`changeRate` sets the playback rate of an audio element to the rate passed as an argument. When the button is pressed in the browser, it shows the new playback rate.

**Think about:** We have all these states for volume, media time etc, why don't we have one for rate?

Creating a Playback Rate Button

We will create two buttons labeled "rewind 15 seconds" and "fast forward 15 seconds." Then, we created two functions, `onRewind` and `onFastForward`, to adjust the current time of a media by 15 seconds. The `onRewind` function will use `Math.max` to ensure that the time does not go into negative, and the `onFastForward` function will use `Math.min` to set a max limit. These functions will be added to the click events of the corresponding buttons. Finally, it sets the new time for the media state and the audio reference.

**Think about:** Why do you need the second parameter for `math.max` and `math.min`?

Add Fast-Forward and Rewind 15 Second Buttons

You will learn how to create and manage complex, nested schemas using a real world example (room bookings with guest details) used throughout all lessons. All created schemas are tested against potential bugs and we verify error messages.

The course covers topics such as:

- Utilizing Zod's shape and unwrap features to perform partial validations without losing the overall schema structure.
- Managing optional, nullable and nullish properties.
- Implementing unions and intersections to handle different types of data.
- Ensuring type safety with sets and maps, including custom validation logic for primitive values.
- Creating custom error messages for improved user feedback.

Get a solid understanding of how to leverage Zod to enhance runtime data validation in JavaScript/TypeScript applications 🔥

Tomasz Ducin

Advanced Type Checks with Zod

Get a solid understanding of how to leverage Zod to enhance runtime data validation in JavaScript or TypeScript applications

Get started with MongoDB and Docker really quick 🔥 even if you have no backend/fullstack experience.

This lesson guides you through installing Docker Desktop and setting up a MongoDB image.

We explain Docker images and containers, and their roles in providing isolated software environments.

We run a MongoDB image in 2 ways: using the terminal and Docker Desktop

We demonstrates configuring port settings for a container and accessing the MongoDB shell (`mongosh`) to interact with the database.

We learn how to manage Docker containers, configure settings, and run commands inside the container.

Grab the CLI command: 🔥 `docker run --name some-mongo -d mongo:latest` 🔥

Install Docker to run local MongoDB Container

Learn to install Docker Desktop, set up a MongoDB image, and manage containers. Configure ports and access the Mongo shell

[https://github.com/johnlindquist/mcp-cursor-tool-starter/tree/main](https://github.com/johnlindquist/mcp-cursor-tool-starter/tree/main)

Cursor's AI is powerful, but it can't do everything. What if you could give it the ability to interact with your specific workflows, tools, and data? This lesson shows you how to do exactly that by building a custom MCP tool – and we'll do it in under two minutes!

We'll leverage the Model Context Protocol (MCP), an open standard that bridges the gap between AI agents (like Cursor's Composer) and your custom code. By creating an MCP tool, you're essentially giving Cursor a new skill.

Here's the breakdown:

Understanding MCP: We'll briefly cover what the Model Context Protocol (MCP) is and why it's the key to extending Cursor's functionality. In short, it enables communication between the AI and your tools in a standardized way.

Fast Track Setup: We'll use a ready-made starter project (a single TypeScript file and package.json) to skip the boilerplate and get straight to the core concepts.

Step-by-Step Integration: We'll walk through the simple process of:

Cloning the starter project.

Installing dependencies with pnpm install.

Running the starter server.

Adding the tool to Cursor's MCP settings (under Features > MCP).

Verifying that your tool is working

Real-World Example: We'll demonstrate the tool in action, using Cursor's Composer to create a new GitHub issue using the gh CLI, all driven by our custom MCP tool.

This lesson is about more than just building one tool; it's about understanding how to extend Cursor's capabilities to fit your unique development needs. You'll learn the foundational steps to create a whole ecosystem of AI-powered tools.

Build Your First MCP Tool in Cursor in Just 2 Minutes

Displaying data in tables has been notoriously hard to implement. Naive implementations of data tables will leave your app slow and janky and many table libraries out there are restricted to a few select UI frameworks they use or aren't very customizable.

Tanstack Table is a 'headless' option meaning you have complete control of the presentation while taking advantage of the data side of the equation.

You'll be able to fetch and display remote data, handle pagination, and implement row virtualization for better performance.

Once you've implemented basic functionality you can take your tables to the next level customizing cells with your own JSX components, adding features like toggling column visibility, and ensuring your table is mobile-friendly with CSS pseudo-elements.

By the end, you'll have the skills to create efficient, user-friendly tables that elevate your applications. You can take what you learn here (using React) to any of the popular modern UI frameworks that fit your project requirements.

Ian Jones

Headless, Mobile-friendly Data Tables with Tanstack Table and React

Learn to display, paginate, and virtualize data effectively in a table with Tanstack table and React 19.

Install `ghx` with `npm i -g @johnlindquist/ghx`

https://github.com/johnlindquist/ghx

You've copied and pasted code, set up your project, and... *error*.  "Stream is not readable."  Sound familiar?  Generic Google searches and outdated Stack Overflow answers often leave you more confused than when you started.  You need more than just documentation; you need *context*.  You need to see how real developers solve this *exact* problem.

This lesson shows you a better way to debug, using real-world GitHub examples and the power of Cursor's Composer.

Here's the workflow we'll cover:

1.  **Identify the Error:** You've already done this!  You have a specific error message ("Stream is not readable") and the code that's causing it.
2.  **Find Real-World Solutions with `ghx`:** We'll use `ghx`, a tool for searching GitHub, to find *actual projects* that have encountered (and solved!) this same issue.  No more generic advice – you'll see working code.
3.  **Consolidate and Analyze:**  `ghx` brings those relevant code snippets into a single, easy-to-read file.
4.  **Leverage Cursor's Composer:** We'll use Cursor's Composer to directly interact with the examples and your problematic code.  Paste in your error, reference the `ghx`-generated file, and ask targeted questions like:
    *   "Based on these examples, how should I modify my code to fix the 'stream is not readable' error?"
    *   "What's the common cause of this error in the context of an MCP server?"
    *   "Show me the specific lines in the examples that handle stream readability correctly."
5. **Fix the Error:** Implement the solution using this workflow.

Instead of guessing, you'll learn directly from proven solutions.  You'll gain a deeper understanding of your issue and how to troubleshoot it effectively.  This approach transforms debugging from a frustrating hunt into a targeted learning experience.

Fix Real-World Coding Errors with GitHub Context through ghx and Cursor Composer

Learn how to test custom ESLint rules with Vitest and RuleTester.

In the [previous video](https://egghead.io/set-up-a-custom-es-lint-rule~kq49h), we created a custom eslint rule that gives us a warning when some of the class names don’t start with a lowercase letter.

Here, I'll show you how to test this or any other custom ESLint rule using unit tests without manually restarting the ESLint server or modifying production code to check if the rules work correctly. We'll look at the structure in which correct and incorrect code samples should be specific to RuleTester.

We'll also learn how to make our rule fixable and verify that the applied fix works as expected.

Test Custom ESLint Rules with Vitest and RuleTester

Learn to test a Custom ESLint Rule using Vitest and RuleTester.

AI is amazing for generating code, but often leaves us staring at functions and libraries we've never seen before. This creates a huge problem: When things break (and they will break), we're lost. We don't understand the individual pieces, let alone how they interact. Knowing one part isn't enough; we need to see how unfamiliar components work together.

The solution? Real-world examples.

This lesson introduces ghx, a tool I built to do exactly that. ghx searches GitHub, finding actual code examples that use the specific combinations of functions and libraries that are tripping you up. Instead of generic documentation, you get concrete implementations. You can find the ghx repository at https://github.com/johnlindquist/ghx.

Here's the workflow we cover:

Identify the Unknown: Pinpoint the AI-generated code you don't understand – specific functions, libraries, or their interactions.

Search with ghx: Use ghx to search GitHub for examples using those terms together. ghx finds repos where those elements co-exist.

Consolidate Examples: ghx combines the relevant code snippets from those examples into a single, digestible file.

Ask the AI (Again, but Better!): Feed this consolidated code to an AI (like a coding-focused model in an AI studio). Now, instead of asking general questions, you can ask targeted questions based on real-world usage:

"Explain how these functions are used together in these examples."

"What are some common use cases for this combination of libraries?"

"Show me alternative code snippets that achieve the same result."

"Can you identify potential problems or areas for improvement, based on these examples?"

Iterate. Use your improved understanding to make changes, and then repeat the process to debug.

By leveraging ghx and targeted AI prompting, we transform from being lost in a sea of unfamiliar code to actively learning from how others have solved similar problems. We gain a deeper understanding of our AI-generated codebase, making debugging, modification, and future development far more manageable. This gives you the tools to understand, debug and improve your own code.

How to Work with AI-Generated Code You Don't Understand with ghx and Gemini

In this less we create a custom Zod schema using `z.custom`.

The example case covers room numbers validation: it must start with an uppercase letter followed by three digits. `z.custom` allows the creation of a brand new custom schema with a callback function that returns a boolean indicating validity.

We highlight a challenge with type inference in Zod's custom schemas: callback parameter types don't get aligned automatically - type-safety must be explicitly defined using type parameters.

We run tests against various room numbers and demonstrate how to effectively validate inputs and manage error messages.


Create Custom Zod Schemas and Validate project-specific data

Create custom validation logic in Zod using z.custom, for primitive values, ensuring type safety and proper error messages for room numbers.


In this lesson we make use of partial validation of large and nested schemas in Zod.

Instead of creating many small schemas, which can complicate maintenance, Zod allows for the extraction of specific parts of a schema using the concept of ".shape". It "unwraps" the object schema, enabling access to sub-schemas within specific properties.

Additionally, we can use the `.unwrap` to get into element schemas of altered schemas such as `.optional` or `.array`.

Simplify working with complex schemas without the need to break them into hundreds of small schemas.

Use Zod Schemas partially using shape and unwrap

Manage large and nested Zod Schemas by extracting partial validations using shape and unwrap utilities

In this lesson we cover implementing sets and maps in Zod.

Using `z.set`, a schema for string-based amenities is created. We demonstrate how validation works by intentionally introducing errors and customizing error messages for better clarity.

Next, a map is created for existing guestDetails schema using `z.map`, with string keys and an existing `z.object`-based schema. The validation process is shown again by deliberately breaking the schema, such as omitting the age property, which triggers appropriate error messages.


Validate maps and sets using Zod schemas

Use sets and maps in Zod for schema validation, ensuring type safety for both keys and values.

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