Quickly integrate face, hand, and/or pose tracking to your frontend projects in a snap ✨👌

A magical full-stack framework for Django ✨

Wait, is this magic?

• Unicorn progressively enhances a normal Django view, so the initial render of components is fast and great for SEO.
• Next, Unicorn binds to the elements you specify and automatically makes AJAX calls when needed.
• Then, Unicorn dynamically updates the DOM.

The end result is that you can focus on writing regular Django templates and Python classes without needing to switch to another language or build unnecessary plumbing. Best of all, the JavaScript portion is a paltry ~8 KB gzipped.

Developers deal with technical debt every day, and they know how to prevent and manage it better than anyone else. Here’s just some of what they had to say.

Plenty of people have written about technical debt. They might be discussing it in the context of improving velocity, code churn, code refactoring, or it might just be an item on a very long to-do list that never gets prioritised.

Charts.css is an open source CSS framework for data visualization.

Visualization help end-users understand data. Charts.css help frontend developers turn data into beautiful charts and graphs using simple CSS classes.

No dependencies. 72kb file size. Less than 6kb gzipped file size!

Serving desktop-sized images to mobile devices can use 2–4x more data than needed. Instead of a "one-size-fits-all" approach to images, serve different image sizes to different devices.

Once you've implemented responsive images, you can use Lighthouse to make sure that you didn't miss any images. Run the Lighthouse Performance Audit (Lighthouse > Options > Performance) and look for the results of the Properly size images audit. These results will list the images that need to be resized.

The way you write your styles and build layouts can have a major impact on Core Web Vitals. This is particularly true for Cumulative Layout Shift (CLS) and Largest Contentful Paint (LCP).

This article covers CSS-related techniques for optimizing Web Vitals. These optimizations are broken down by different aspects of a page: layout, images, fonts, animations, and loading.

FaceSwap is a tool that utilizes deep learning to recognize and swap faces in pictures and videos.

When faceswapping was first developed and published, the technology was groundbreaking, it was a huge step in AI development. It was also completely ignored outside of academia because the code was confusing and fragmentary. It required a thorough understanding of complicated AI techniques and took a lot of effort to figure it out. Until one individual brought it together into a single, cohesive collection.

It ran, it worked, and as is so often the way with new technology emerging on the internet, it was immediately used to create inappropriate content. Despite the inappropriate uses the software was given originally, it was the first AI code that anyone could download, run and learn by experimentation without having a Ph.D. in math, computer theory, psychology, and more.

Before "deepfakes" these techniques were like black magic, only practiced by those who could understand all of the inner workings as described in esoteric and endlessly complicated books and papers.

Testing is one of those things that you either get super excited about or kinda close your eyes and walk away. Whichever camp you fall into, I’m here to tell you that front-end testing is for everyone. In fact, there are many types of tests and perhaps that is where some of the initial fear or confusion comes from.

Scroll to the end if you lack of time, the wrapping up table is great.

GSAP (Greensock Animation API) is an animation library that helps you create awesome animations. It can be used safely (back to IE6!) to create animations without jank, and it’s the only animation library (as far as I know) that handles SVG animations seamlessly.

This post will walk you through the performance tuning steps that I took to serve 1.2 million JSON "API" requests per second from a 4 vCPU AWS EC2 instance. For the purposes of this recreated quest, we will ignore most of the dead ends and dark alleyways that I had to struggle through on my solo expedition.

Instead, we will mainly stick to the happy path, moving steadily from serving 224k req/s at the start, with the default configuration, to a mind-blowing 1.2M req/s by the time we reach the end.