Learn Dart, Jekyll and Webpack

Flutter allows you to build beautiful native apps on iOS and Android from a single codebase.

flutter

Extension methods allow you to add new methods to classes without directly changing its original interface or creating a derived class. We will explore examples of working with this feature by extending some inbuilt types.

Learn more about Extension Methods at https://medium.com/dartlang/extension-methods-2d466cd8b308

Add New Methods to inbuilt Classes and Interfaces with Extension Methods in Dart

We will learn how to work with Lists using a variety of methods made available in the **dart:core** library. We will explore the top methods for working with List type collections.

Learn more about Lists at https://api.dartlang.org/stable/2.2.0/dart-core/List-class.html

Manipulate Lists/Arrays in Dart

We will learn how to work with Strings using a variety of methods made available in the **dart:core** library. We will explore the top methods for working with String values.

Learn more about Strings at https://api.dartlang.org/stable/2.2.0/dart-core/String-class.html

Manipulate Strings in Dart

In this lesson, we will cover Interfaces and Mixins. Interfaces act as a contract containing properties and methods that a class must define once it “implements” this interface. Mixins are Dart’s way of sharing properties and methods from multiple classes, since by design Dart adopts a single-inheritance model.

Define Interfaces and Share Class Members through Mixins in Dart

Streams represent a sequence of asynchronous events. Each event is either a data event, also called an element of the stream, or an error event, which is a notification that something has failed. When a stream has emitted all its events, a single "done" event will notify the listener that the end has been reached. In this lesson, we will learn how we can capture and handle streaming data, working with various Stream classes.

Capture and Handle Data Sequences with Streams in Dart

Pub is a package management tool that makes it easy for you to install, use, share Dart libraries, command-line tools and other assets. It comes as part of the Dart SDK, and requires a dependency file called pubspec.yaml.

Manage Package Dependencies with Pub

Futures represent a computation that does not complete immediately. Where a normal function returns a result, an asynchronous function returns a Future that will eventually contain the result. These are similar to Promises in JavaScript. In this lesson, we will learn how to program asynchronously by writing logic to capture values that are returned at a later time.

Capture and Return Asynchronous Values with Futures in Dart

Dart is an object-oriented language you can use for building web applications, server-side code, and even mobile apps. It’s expressive, powerful, and has a friendly learning curve. 

In this course, we will look at the syntax and semantics of the Dart programming language. We will also cover various aspects of the Dart ecosystem, including its tools and packages that help make you a productive developer. This knowledge is applicable when developing software for client, server, and especially mobile with the Flutter framework. 

This course is beginner-friendly, but is well-suited for experience programmers as well. 

Dart is an open-source, scalable programming language, with robust libraries and runtimes, for building web, server, and mobile apps.

dart

Get Started with Dart

webpack is a tool to build JavaScript modules in your application. To start using webpack from its cli or api, follow the Installation instructions. webpack simplifies your workflow by quickly constructing a dependency graph of your application and bundling them in the right order. webpack can be configured to customise optimisations to your code, to split vendor/css/js code for production, run a development server that hot-reloads your code without page refresh and many such cool features.

webpack

As you refactor and modify applications, it's difficult to manage and keep track of files as they become unused. Keeping this "dead" code around adds noise to your application and reduces clarity. Just as ESLint can tell us when variables become unused, Webpack (with the help of the unused-files-webpack-plugin) can tell us when entire files become unused. First, we'll install the plugin with npm and save it as a devDependency. Next, we'll use npm run scripts to build a new command that will run Webpack with the plugin. Finally, we'll learn how to use Webpack environment variables to conditionally add plugins to your Webpack config. By the end of the lesson, you'll have a useful cli command you can run to check for unused modules in your Webpack build

Delete Unused Code with Webpack and unused-files-webpack-plugin

In this lesson we’ll learn how to fetch & then display data from an API over the network in a Flutter application using the http package.

Fetching & Displaying Data from an API in Flutter using the http Package

Babel has support for the latest version of JavaScript through syntax transformers. These plugins allow you to use new syntax, right now without waiting for browser support.

babel

In this lesson, we'll configure webpack to use the Babel loader for our JavaScript files, allowing us to transpile our source files and generate a bundle for deploying our application.

Configure webpack to Load JavaScript Files through Babel with babel-loader

While we're developing an application, having a local server to preview our work is a great convenience. With `webpack`, we can take advantage of `webpack-dev-server` to serve up files and automatically reload the browser when we make changes. In this lesson, we'll install and configure `webpack-dev-server` in our boilerplate project.

Serve a webpack Bundle while Developing with webpack-dev-server

We can separate our custom application code from the common libraries we leverage, such as React and ReactDOM. In this lesson we'll configure `webpack` to treat React and ReactDOM as external dependencies. Then we'll update our HTML template to conditionally include the CDN links for those libraries for production builds.

Externalize Dependencies to be Loaded via CDN with webpack

Bundle size has a huge impact on JavaScript performance. It's not just about download speed, but all the JavaScript we ship to the browser needs to be parsed and compiled before it can be executed. Keeping our bundle in check can be difficult, but it's much easier when we can see where the bloat is coming from. In this lesson, we'll add the `webpack-bundle-analyzer` plugin to inspect the output of our production build.

Analyze a Production JavaScript Bundle with webpack-bundle-analyzer

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

One approach to building high performance applications with `webpack` is to take advantage of code-splitting to only load the needed JavaScript on initial load and asynchronously load additional JavaScript bundles when needed. In this lesson, we'll create add some code-splitting to our placeholder application and configure our project to support the dynamic `import()` syntax.

Asynchronously Load webpack Bundles through Code-splitting and React Suspense

In this lesson, we'll add React and ReactDOM to our project and create an entry point for the React application. We'll also configure Babel with the React preset so Babel can transpile our JSX into JavaScript that will run in a browser.

Configure babel for React with preset-react

The `development` and `production` modes in `webpack` optimize the output in different ways. In `development` mode, the focus is on faster builds and a better developer experience. In `production` mode, the focus is on highly optimized bundles, leading to a better user experience. The good news is, we can have both. In this lesson, we'll separate our `webpack` config into two configurations and update our scripts to run the right config for our needs.

Create Separate webpack Configs for Development and Production with webpack-merge

The Chrome Developer Tools (DevTools for short), are a set of web authoring and debugging tools built into Google Chrome.

chrome-devtools

A potential downside to all the transformations our tools perform on our code is that when you need to debug your application, the code being served isn’t the code you wrote. This is where source maps save the day. We can serve transformed and bundled code, then debug in DevTools against our source code right in the browser. In this lesson we’ll take a look at the default debug experience without source maps, then we’ll configure webpack to generate source maps and look at the enhanced experience.

Generate Source Maps through webpack for a Better Debugging Experience with source-map

As of `webpack` version 4, there is a top-level configuration option called `mode`. Mode allows us optimize for build speed during development, while optimizing for runtime performance and smaller bundles for production builds. In this lesson, we'll add the mode key to our webpack configuration and look at the difference in output between the `production` and `development` settings.

Control the Output of webpack with the mode Setting

Even if it's only a simple one, we'll need to serve up an HTML file to run our JavaScript app. We can hardcode the bundle path into a script tag, but then if we want to change our bundle name, we need to update that in our webpack config and in our html file. In this lesson, we'll see how to use the `HtmlWebpackPlugin` to inject the script tag for our bundle into an HTML template file.

Inject a JavaScript bundle into HTML with the HtmlWebpackPlugin

It's inconvenient during development to have to run a script each time we make a change to our source. We can have webpack generate an updated bundle as we make changes. In this lesson, we'll create an `npm` script to run webpack in watch mode and  see it in action as we modify some source files.

Update your Bundle with each File Save with webpack's watch Mode

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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