 Courses from Guy Bedford

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

We demonstrate how to build a WebAssembly module that depends on malloc, linking in a pre-built malloc implementation at runtime, using a JS binding trick to handle the circular reference between the two WebAssembly modules. We then optimize the load process to ensure we are fetching these modules in parallel.

Malloc implementation: https://github.com/guybedford/wasm-stdlib-hack/blob/master/dist/memory.wasm

WASM Fiddle: https://wasdk.github.io/WasmFiddle/?1feerp

Demo Repo: https://github.com/guybedford/wasm-intro

Allocate Dynamic Memory in WebAssembly with Malloc

Starting from the previous example, we rebuild the program code to import its memory instead of exporting it. We then use this to simplify the application loading code.

Emscripten: https://kripken.github.io/emscripten-site/

Demo Repo: https://github.com/guybedford/wasm-intro

Create and Import a WebAssembly Memory

Using the previous JS example (with some polishing), we start the conversion by copying the JS code into a C file. Step-by-step we run through the principles of converting this JS code into valid C code that we can compile into Web Assembly, based on the same principles we learnt in the initial lessons. We paste the C code into WASM Fiddle to get the resulting WebAssembly binary, and wire it into the application.

Demo repo: https://github.com/guybedford/wasm-demo

_Note the demo is currently only supported in Chrome Canary with the Experimental Web Platform flag (chrome://flags/#enable-experimental-web-platform-feature) enabled due to the use of ES modules and WebGL 2.0._

Step-by-Step JS to WebAssembly Conversion

To improve the performance of collision detection, we need to dive into the internals of the algorithm. Here we update the JS collision detection code to use a grid for collision detection, which brings a big performance boost at the end.

Demo repo: https://github.com/guybedford/wasm-demo

_Note the demo is currently only supported in Chrome Canary with the Experimental Web Platform flag (chrome://flags/#enable-experimental-web-platform-feature) enabled due to the use of ES modules and WebGL 2.0._

Optimize Collision Detection in JS with a Grid

To write a grid collision detection optimization in C requires thinking about the data structure of the grid more than in JS. In C we can represent this with a linked list and show how to convert the JS optimization code into this structure. When we compare the final performance, the WebAssembly code is now faster than the JS code - being able to write a low-level, more efficient data structure in memory is what gives WebAssembly its best advantage over JS. For those new to the principles, a good introduction to data structures and algorithms is the CLRS Introduction to Algorithms book.

Demo repo: https://github.com/guybedford/wasm-demo

_Note the demo is currently only supported in Chrome Canary with the Experimental Web Platform flag (chrome://flags/#enable-experimental-web-platform-feature) enabled due to the use of ES modules and WebGL 2.0._

Surpass JS Performance with Optimized Collision Detection in WASM using a Linked List Grid

We use the C language instead of pure WAST to create a square root function using WASM Fiddle (https://wasdk.github.io/WasmFiddle//). We show how to run the WebAssembly in WASM Fiddle, then download and run it in the browser using a helper function to load the WebAssembly.

WASM Fiddle: https://wasdk.github.io/WasmFiddle/?t96rp

Demo Repo: https://github.com/guybedford/wasm-intro

Compile C Code into WebAssembly

We use an offset exporting function to get the address of a string in WebAssembly memory. We then create a typed array on top of the WebAssembly memory representing the raw string data, and decode that into a JavaScript string.

WASM Fiddle: https://wasdk.github.io/WasmFiddle/?6wzgh

Demo Repo: https://github.com/guybedford/wasm-intro

Read WebAssembly Memory from JavaScript

This lesson demonstrates a full build of LLVM roughly following the steps in [GettingStarted.html](http://llvm.org/docs/GettingStarted.html) (or [GettingStartedVS.html](http://llvm.org/docs/GettingStartedVS.html) for Windows), but with the experimental WebAssembly target build option. Prerequisites include cmake (which can be downloaded from [cmake.org/download](https://cmake.org/download/)), Visual Studio on windows, or Xcode command line tools on mac.

Clone and Build LLVM with the Experimental WebAssembly Target

In this lesson we cover the install process for Binaryen (http://github.com/WebAssembly/binaryen) to get the s2wasm binary and WABT (https://github.com/WebAssembly/wabt) to get the wast2wasm binary.

Prerequisites are cmake (https://cmake.org/download/), XCode CLI tools on Mac, or Visual Studio on Windows.

Install Binaryen and the WebAssembly Binary Toolkit (WABT)

We write a function that converts a string to lowercase in WebAssembly, demonstrating how to set the input string from JavaScript.

WASM Fiddle: https://wasdk.github.io/WasmFiddle/?h1s69

Demo Repo: https://github.com/guybedford/wasm-intro

Write to WebAssembly Memory from JavaScript

We introduce a black-box render function which draws circles to the screen, explaining how the position information is represented in the memory for the renderer (a typed array of [x1, y1, r1, x2, y2, r2, …]). We draw a simple circle (at [0, 0, 100]), then many random circles to get a feel for passing rendering data by directly setting Typed Array memory. The details of the renderer are not discussed at all. We set up some simple dynamics and wall bounds, and then push the circle count up over 1,000,000 renders to demonstrate the performance of dealing with raw memory and WebGL.

Demo repo: https://github.com/guybedford/wasm-demo

_Note the demo is currently only supported in Chrome Canary with the Experimental Web Platform flag (chrome://flags/#enable-experimental-web-platform-feature) enabled due to the use of ES modules and WebGL 2.0._

Typed Arrays in High Performance JavaScript

To compare the performance between JS and WebAssembly, we use an example that calculates the collisions between circles on the screen. This quickly slows down the rendering performance making the performance comparison visible. We briefly go over the same steps of converting JS into C code, and find that the JS version of the code is actually faster than the WASM version - WebAssembly improving performance is not such a simple argument.

Demo repo: https://github.com/guybedford/wasm-demo

_Note the demo is currently only supported in Chrome Canary with the Experimental Web Platform flag (chrome://flags/#enable-experimental-web-platform-feature) enabled due to the use of ES modules and WebGL 2.0._

A First Comparison of the Performance between JS and WebAssembly

We go through the command-line steps to compile C/C++ via LLVM into an intermediate S file, then use Binaryen to compile that S file into a WAST file and finally WABT to get the WASM binary. We then show an approach to clone and configure a custom std library headers for Web Assembly to build includes to the standard library.

Compiling C/C++ to WebAssembly using LLVM, Binaryen and WABT

In this introduction, we show a simple WebAssembly function that returns the square root of a number. To create this function we load up WebAssembly Explorer (https://mbebenita.github.io/WasmExplorer/), writing the native WAST code to create and export the function. We compile and download the resulting WebAssembly binary, loading this with the Fetch API and WebAssembly JavaScript API to call the function in the browser.

Demo Repo: https://github.com/guybedford/wasm-intro

Create and Run a Native WebAssembly Function

Using WASM Fiddle, we show how to write a simple number logger function that calls a consoleLog function defined in JavaScript. We then download and run the same function in a local project.

WASM Fiddle: https://wasdk.github.io/WasmFiddle/?cvrmt

Demo Repo: https://github.com/guybedford/wasm-intro

Call a JavaScript Function from WebAssembly

This course begins with some small steps for working with WebAssembly straight away using online tools wasm Explorer and wasm Fiddle to try out the examples in the browser. We start by calling a WebAssembly function from JS, then a JS function from WebAssembly, then go on to reading and writing WebAssembly memory from JS. To move beyond these online sandboxes, we show the exact steps for setting up and running a complete local WebAssembly build workflow using the experimental LLVM WebAssembly build target. We then take a demo WebGL application written in JS and show how we can optimize this with WebAssembly to get a real world example of a WebAssembly performance improvement, although it isn’t as obvious a process as we might have hoped.

Get Started Using WebAssembly (wasm)

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.

Guy Bedford

Search Results