Video: Improve Your Website's Speed and Efficiency with Partytown

Ivan’s first attempts at performance debugging were chaotic. He would see a slow interaction, try a random optimization, see that it didn't help, and keep trying other optimizations until he found the right one (or gave up).
Back then, Ivan didn’t know how to use performance devtools well. He would do a recording in Chrome DevTools or React Profiler, poke around it, try clicking random things, and then close it in frustration a few minutes later. Now, Ivan knows exactly where and what to look for. And in this workshop, Ivan will teach you that too.
Here’s how this is going to work. We’ll take a slow app → debug it (using tools like Chrome DevTools, React Profiler, and why-did-you-render) → pinpoint the bottleneck → and then repeat, several times more. We won’t talk about the solutions (in 90% of the cases, it’s just the ol’ regular useMemo() or memo()). But we’ll talk about everything that comes before – and learn how to analyze any React performance problem, step by step.
(Note: This workshop is best suited for engineers who are already familiar with how useMemo() and memo() work – but want to get better at using the performance tools around React. Also, we’ll be covering interaction performance, not load speed, so you won’t hear a word about Lighthouse 🤐)

The addition of the hooks API to React was quite a major change. Before hooks most components had to be class based. Now, with hooks, these are often much simpler functional components. Hooks can be really simple to use. Almost deceptively simple. Because there are still plenty of ways you can mess up with hooks. And it often turns out there are many ways where you can improve your components a better understanding of how each React hook can be used.You will learn all about the pros and cons of the various hooks. You will learn when to use useState() versus useReducer(). We will look at using useContext() efficiently. You will see when to use useLayoutEffect() and when useEffect() is better.

ReactJS is wildly popular and thus wildly supported. TypeScript is increasingly popular, and thus increasingly supported.

The two together? Not as much. Given that they both change quickly, it's hard to find accurate learning materials.

React+TypeScript, with JetBrains IDEs? That three-part combination is the topic of this series. We'll show a little about a lot. Meaning, the key steps to getting productive, in the IDE, for React projects using TypeScript. Along the way we'll show test-driven development and emphasize tips-and-tricks in the IDE.

React Testing Library is a great framework for React component tests because there are a lot of questions it answers for you, so you don’t need to worry about those questions. But that doesn’t mean testing is easy. There are still a lot of questions you have to figure out for yourself: How many component tests should you write vs end-to-end tests or lower-level unit tests? How can you test a certain line of code that is tricky to test? And what in the world are you supposed to do about that persistent act() warning?
In this three-hour workshop we’ll introduce React Testing Library along with a mental model for how to think about designing your component tests. This mental model will help you see how to test each bit of logic, whether or not to mock dependencies, and will help improve the design of your components. You’ll walk away with the tools, techniques, and principles you need to implement low-cost, high-value component tests.
Table of contents- The different kinds of React application tests, and where component tests fit in- A mental model for thinking about the inputs and outputs of the components you test- Options for selecting DOM elements to verify and interact with them- The value of mocks and why they shouldn’t be avoided- The challenges with asynchrony in RTL tests and how to handle them
Prerequisites- Familiarity with building applications with React- Basic experience writing automated tests with Jest or another unit testing framework- You do not need any experience with React Testing Library- Machine setup: Node LTS, Yarn

During this workshop, participants will review the essential JavaScript patterns that every developer should know. Through hands-on exercises, real-world examples, and interactive discussions, attendees will deepen their understanding of best practices for organizing code, solving common challenges, and designing scalable architectures. By the end of the workshop, participants will gain newfound confidence in their ability to write high-quality JavaScript code that stands the test of time.
Points Covered:
1. Introduction to JavaScript Patterns2. Foundational Patterns3. Object Creation Patterns4. Behavioral Patterns5. Architectural Patterns6. Hands-On Exercises and Case Studies
How It Will Help Developers:
- Gain a deep understanding of JavaScript patterns and their applications in real-world scenarios- Learn best practices for organizing code, solving common challenges, and designing scalable architectures- Enhance problem-solving skills and code readability- Improve collaboration and communication within development teams- Accelerate career growth and opportunities for advancement in the software industry

Building instant-on web applications at scale have been elusive. Real-world sites need tracking, analytics, and complex user interfaces and interactions. We always start with the best intentions but end up with a less-than-ideal site.
QwikCity is a new meta-framework that allows you to build large-scale applications with constant startup-up performance. We will look at how to build a QwikCity application and what makes it unique. The workshop will show you how to set up a QwikCitp project. How routing works with layout. The demo application will fetch data and present it to the user in an editable form. And finally, how one can use authentication. All of the basic parts for any large-scale applications.
Along the way, we will also look at what makes Qwik unique, and how resumability enables constant startup performance no matter the application complexity.