Learn D3, Jekyll and Recoil

D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG and CSS. D3’s emphasis on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework, combining powerful visualization components and a data-driven approach to DOM manipulation.

In this lesson, we'll clean up some of our placeholder elements. We'll then look at D3's ordinal scale to create a color scale that maps our regions to colors. We'll apply the colors based on region to our data points via the SVG `g`(group) element to apply the color to both our bars and their corresponding inline labels.

Create a Color Scale with D3's scaleOrdinal

Looking at our bars against each other with the x-axis as a guide gives us some relative information, but doesn't deliver the most precise values. In this lesson, we'll add additional labels to show the exact values of each data point in the context of the individual bars.

Clarify Data in D3 with Additional Labels and Rounded Domain Values

In this lesson, we'll see how we can add labels down the y-axis using our band scale. We'll see how to render the labels in React and how we can precisely position the labels based on values calculated by D3 and our scales.

Render a Y Axis for a Bar Chart with D3 and React

In this lesson, we'll take advantage of our `xScale` and the bottom margin to create an axis to start giving our data meaning. We'll access `ticks` from the scale and then use React to render and position the SVG `rect` and `text` elements to create the x-axis for our chart.

Render an X Axis for a Bar Chart with D3 and React

When applying scales to data elements in D3, it's common to combine the scale with an accessor function in order to apply the scale to the appropriate key on a data object. In this lesson, we'll create scaled accessors to refactor and tighten up some existing code.

Create Scaled Accessor Functions from D3 Scales

A band scale allows us to map a discrete set of values to a continuous range. In this lesson, we'll use a band scale in D3 to take the distinct "region" keys in our sample data and map those to evenly spaced and sized elements on our y-axis. We'll use this band scale to show a bar in the bar chart for each region, setting their size and position based on this scale.

Layout SVG Elements on a Y Axis with a D3 Band Scale in React

Drawing data accurately requires a consistent and precise mechanism for mapping data values to pixels on the screen. We can accomplish this mapping in D3 using scales. There are various scales available in D3, depending on your needs. In this lesson we'll using a linear scale to map a data domain of continuous values to continuous range of pixel values. We'll render a new SVG element, setting its width from our scale.

Set an SVG Element's Width Based on a D3 Linear Scale in React

When you want to add data visualizations to your web app, D3 is pretty much the accepted standard.

In this course, we'll start from scratch and build out a bar chart for some sample data using D3's utilities to wrangle the data and then we'll handle the rendering with React.

We'll start by laying out the SVG element that will hold everything, then we'll move on to creating scales that will give us the information we need to render our data as well as axes to give our data some meaning.

Along the way, we'll cover accessor functions, linear scales, band scales and finally, we'll use an ordinal scale to map data objects to colors.

This course certainly won't cover all of D3, but we'll cover enough of the fundamentals to give you a solid jumping off point for future D3 and React data visualization work.

Introduction to Create a Bar Chart with React and D3

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

Recoil offers several hooks to use for consuming state in React, and this lesson looks at how to choose which hook to use, and what happens when you don't use the right hook (hint: **extra renders**).

The three basic RecoilJS hooks are:

1. `useRecoilState`, which is great for reading and writing state,
2. `useRecoilValue`, ideal for reading state, and
3. `useSetRecoilState`, the primary candidate when you just need to write state.

Choose the Right Hook for Your Recoil State

When consuming asynchronous selectors in Recoil, you're going to need to tell React what to render while the API is fetching its data. 

One way to solve this issue is by setting a fallback value using React `Suspense`. But there's another option that gives you fine-grained control, and that's by preventing the selectors from returning a promise in the first place.

In this lesson we're going to have our selectors return Recoil's `Loadable` object, which always contains the current selector value (`contents`) and what state the selector is in (`state`). By consuming this with the `useRecoilValueLoadable` hook rather than the regular `useRecoilValue` hook, we can manually define whatever we want React to render in each of the 3 states: `hasError`, `hasValue`, and `loading`.

Handle Recoil Asynchronous Selectors using Loadables in React

Selectors are great for automatically triggering API calls with Recoil because they are automatically run as soon as any dependencies are updated, and because selectors are shared across your application.

Be aware that Recoil will cache your selector values, so asynchronous selectors are best utilized when the data is not meant to change throughout the life-cycle of an application. Fetching a user's avatar would be a good use case.

When writing asynchronous selectors, one thing to keep in mind is that React must always know what to render - even while your data is being fetched. One solution for this is to use Suspense, a React component that allows you to supply a fallback value to render until your data returns. In this lesson, we'll look at how to call APIs inside selectors and handle situations where selectors return promises.

Use Recoil Selectors to Make API Calls in React

In this lesson, we're going to learn how to create Recoil selectors that accept arguments. These are made possible using the `selectorFamily` utility function.

We'll start with an existing application that uses a regular `selector` to display a sorted array of Todo items, and then we'll refactor it so that we're able to supply the sort type (`ascending` or `descending`) in the React component itself.

For more information on `selectorFamily`, have a look at the official RecoilJS docs: https://recoiljs.org/docs/api-reference/utils/selectorFamily


Use selectorFamily to take arguments in your Recoil selectors

Learn how to set state in Recoil using the `useRecoilState` hook. 

Sound familiar? It should, because it works very similarly to React's built-in `useState` hook (the functional component equivalent of `setState`).

In this lesson, we'll practice removing and adding items from an array that we keep in state using a Recoil atom. We'll create new immutable functions, and then call our setter functions in order to update the state.

Update Recoil State in React using useRecoilState

In this lesson, we're going to show how RecoilJS selectors are used to display computed data in React. While atoms are the go-to state objects in Recoil, selectors are the ideal choice when data can be computed based on existing state - like displaying the price of a restaurant order. And your selector output always remains up to date - just subscribe to it using one of the RecoilJS hooks.

Display Computed Data Using Recoil Selectors in React

Recoil is a new (experimental!) library from facebook that can handle complex shared data across a large react app.

In this collection, we'll create a simple game with React using Recoil, to explore how you can share and update state across an app. 

Recoil is similar to (but different than) Context, Redux, or other shared state libraries (like MobX), but is designed to handle large (and variable) numbers of state that can update without re-rendering your entire app's component tree.

A state management library for React.

Recoil works and thinks like React. Add some to your app and get fast and flexible shared state.

recoil

Getting Started with Recoil in React

[Recoil](https://recoiljs.org/) is a brand new state management library for React, developed by Facebook.

Recoil works and thinks like React. Add some to your app and get fast and flexible shared state.

This quick collection will get you up and running with Recoil, you're going to learn how to:

* add Recoil to your React project
* create a Recoil atom and use it to store a piece of state
* use `useRecoilState` hook to update an atom
* use `useRecoilValue` to access value stored in an atom in a read-only fashion
* use 🔥`selectors`🔥 in order to calculate derived data based on state stored within atoms (this is *really* powerful!) 

Sync State Across Components with Recoil in React

Recoil allows us to use atoms in order to store pieces of state. More often than not in our apps we need to use data that derives from our application state (for instance to multiply height and width stored within a state to calculate area of an element).

Luckily Recoil provides us with a powerful tool to automatically re-calculate derived state value whenever an piece of state changes - selectors.

A [selector](https://recoiljs.org/docs/introduction/core-concepts#selectors) is a pure function that accepts atoms or other selectors as input. When these upstream atoms or selectors are updated, the selector function will be re-evaluated.

In this quick lesson we're going to learn how to use a selector in order to automatically calculate a square of a number whenever a value stored within an atom is going to change

Use Selectors to Calculate Derived Data Based on State Stored within a Recoil Atom

Not every component is going to modify a 'global' state stored in a Recoil atom - in some cases a component just needs to be able to read the value.

In this quick lesson we're going to learn how to use a `useRecoilValue` hook to ensure that a component will be able to read a number stored in a Recoil atom in a read-only fashion. 

Use useRecoilValue Hook to Read a Value From a Recoil Atom

[Recoil](https://twitter.com/recoiljs/status/1260965007954591744) is a brand new state management library for React developed by Facebook.

In this quick lesson we're going to learn how to add it to a React app and how to use a Recoil atom in order to share state between two React components using `useRecoilState` hook

 

Use a Recoil Atom to Share State Between Two React Components

Jekyll is a parsing engine bundled as a ruby gem used to build static websites from dynamic components such as templates, partials, liquid code, markdown, etc. Jekyll is known as "a simple, blog aware, static site generator".

jekyll

[Jekyll](https://jekyllrb.com/) is a static site generator built in [Ruby](https://www.ruby-lang.org/en/) and available to generate and host websites on [GitHub Pages](https://pages.github.com/). In this course, you'll install the Jekyll gem, use the command line tool to generate a new project, inspect the scaffolded project, and finally, serve the starter website.

Install Jekyll and generate initial, scaffolded website

In this lesson we'll take a look at how to render a basic line graph using D3, and VX. We'll move on to analyzing how to add some interactivity that will render a line where ever the user hovers using `bisect` from D3. Then we'll show how to render another line path using the scales and manipulating our data. Finally we'll add another line split so we're rendering 2 line paths.

Create an Interactive Line Graph with a Hover Line Highlight using VX and D3

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` 🔥

Tomasz Ducin

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

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.

Ákos Kőműves

Test Custom ESLint Rules with Vitest and RuleTester

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

This course is designed to make you proficient in building dynamic data tables in React using TanStack Table. 

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

The lessons guide you through customizing table cells with your own JSX components, adding features like toggling column visibility to enhance user interaction, and create mobile-friendly tables with CSS pseudo-elements. 

By the end, you'll have the skills to create efficient, user-friendly tables that elevate your React applications.

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.

John Lindquist

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

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.


Excessive properties refer to any additional attributes that are not explicitly listed in an object schema. When creating an object based on a schema, it is important to ensure that only the defined properties are included.

In TypeScript, if an object is created with an extra property that isn't defined in the schema, TypeScript will not raise an error unless the type is explicitly annotated. When the type is annotated, TypeScript will issue an error indicating that the extra property is not allowed.

Zod provides a strict utility to enforce similar checks. This feature ensures that only specified properties are allowed in an object schema. When unnecessary properties are added at both the top level and within nested schemas, Zod will throw errors indicating unrecognized keys.

Adding an unrecognized property to a Zod schema results in an error message that specifies which keys are not recognized. Applying strict checks on nested schemas ensures that all levels of the data structure are validated correctly.


Make Excessive Object Properties Fail on Zod Validation

Prevent excessive properties in TypeScript and Zod schemas using strict checks for better data validation

In this lesson we discuss how Zod works with TypeScript to handle special types like `undefined`, `null`, `any`, `unknown`, `never` and `void`.

We modify our room booking schema to demonstrate the use of `optional` and `nullable` Zod utilities.

By using `.optional`, we allow a property to be either its _original type_ or `undefined`. With `.nullable`, we allow it to be either its _original type_ or `null`. Finally, `.nullish` allows a value to be either its _original type_, `null`, or `undefined`.

For all cases, we run tests to show how these schemas work in practice, as well as how TypeScript infers types.


Declare Lack of Value in zod (optional, nullable and nullish)

use Zod for TypeScript schemas, including handling undefined, null, and special types like optional and nullable values, as well as any, unknown never and void

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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