CSS

The Evolution of CSS: From Early Days to Flexbox & Grid with Kevin Powell

Published Sep 24, 2024

Updated Dec 11, 2024

2 min read

In this episode of the Modern Web Podcast, CSS expert Kevin Powell discusses the evolution of CSS, from the early days of CSS3 to the rapid advancements with Flexbox, Grid, and the latest innovations. Kevin explains how CSS is making strides to integrate features that previously required JavaScript, like scroll-driven animations and popovers, simplifying development and improving performance. He also touches on the importance of understanding the fundamentals of CSS, debugging techniques, and the future of tools like Tailwind and Sass.

Chapters

Here are the timestamped chapters for the episode:

00:00 - Introduction and Technical Setup Issues
01:05 - Guest Introduction: Kevin Powell
02:00 - Kevin's Journey into CSS and Content Creation
03:21 - Evolution of CSS: From CSS3 to Modern Features
05:46 - The Role of JavaScript in CSS and New Features
08:08 - Popovers, Anchor Positioning, and Progressive Enhancement in CSS
10:26 - Discussion on SAS, Tailwind, and CSS Tools
12:35 - Challenges with Tailwind and Over-Componentization
14:57 - The Importance of Learning Core CSS Principles
16:56 - The "CSS is Hard" Memes and Overcoming CSS Frustration
19:12 - Formatting Contexts and Advanced CSS Concepts
21:31 - Opportunities for Junior Developers to Master CSS
23:54 - Browser Discrepancies and the Future of Web Standards
26:14 - Refactoring CSS for Performance and Best Practices
27:50 - Favorite CSS Resources and Conferences
28:26 - Imposter Syndrome and Kevin's Speaking Journey
29:55 - Closing Remarks and Where to Find Kevin Powell Online

Follow Kevin Powell on Social Media Twitter: https://x.com/KevinJPowell Github: https://github.com/kevin-powell YouTube: https://www.youtube.com/kevinpowell

How to build an AI assistant with OpenAI, Vercel AI SDK, and Ollama with Next.js

In today’s blog post, we’ll build an AI Assistant using three different AI models: Whisper and TTS from OpenAI and Llama 3.1 from Meta. While exploring AI, I wanted to try different things and create an AI assistant that works by voice. This curiosity led me to combine OpenAI’s Whisper and TTS models with Meta’s Llama 3.1 to build a voice-activated assistant. Here’s how these models will work together: * First, we’ll send our audio to the Whisper model, which will convert it from speech to text. * Next, we’ll pass that text to the Llama 3.1 model. Llama will understand the text and generate a response. * Finally, we’ll take Llama’s response and send it to the TTS model, turning the text back into speech. We’ll then stream that audio back to the client. Let’s dive in and start building this excellent AI Assistant! Getting started We will use different tools to build our assistant. To build our client side, we will use Next.js. However, you could choose whichever framework you prefer. To use our OpenAI models, we will use their TypeScript / JavaScript SDK. To use this API, we require the following environmental variable: OPENAI_API_KEY— To get this key, we need to log in to the OpenAI dashboard and find the API keys section. Here, we can generate a new key. Awesome. Now, to use our Llama 3.1 model, we will use Ollama and the Vercel AI SDK, utilizing a provider called ollama-ai-provider. Ollama will allow us to download our preferred model (we could even use a different one, like Phi) and run it locally. The Vercel SDK will facilitate its use in our Next.js project. To use Ollama, we just need to download it and choose our preferred model. For this blog post, we are going to select Llama 3.1. After installing Ollama, we can verify if it is working by opening our terminal and writing the following command: Notice that I wrote “llama3.1” because that’s my chosen model, but you should use the one you downloaded. Kicking things off It's time to kick things off by setting up our Next.js app. Let's start with this command: ` After running the command, you’ll see a few prompts to set the app's details. Let's go step by step: * Name your app. * Enable app router. The other steps are optional and entirely up to you. In my case, I also chose to use TypeScript and Tailwind CSS. Now that’s done, let’s go into our project and install the dependencies that we need to run our models: ` Building our client logic Now, our goal is to record our voice, send it to the backend, and then receive a voice response from it. To record our audio, we need to use client-side functions, which means we need to use client components. In our case, we don’t want to transform our whole page to use client capabilities and have the whole tree in the client bundle; instead, we would prefer to use Server components and import our client components to progressively enhance our application. So, let’s create a separate component that will handle the client-side logic. Inside our app folder, let's create a components folder, and here, we will be creating our component: ` Let’s go ahead and initialize our component. I went ahead and added a button with some styles in it: ` And then import it into our Page Server component: ` Now, if we run our app, we should see the following: Awesome! Now, our button doesn’t do anything, but our goal is to record our audio and send it to someplace; for that, let us create a hook that will contain our logic: ` We will use two APIs to record our voice: navigator and MediaRecorder. The navigator API will give us information about the user’s media devices like the user media audio, and the MediaRecorder will help us record the audio from it. This is how they’re going to play out together: ` Let’s explain this code step by step. First, we create two new states. The first one is for keeping track of when we are recording, and the second one stores the instance of our MediaRecorder. ` Then, we’ll create our first method, startRecording. Here, we are going to have the logic to start recording our audio. We first check if the user has media devices available thanks to the navigator API that gives us information about the browser environment of our user: If we don’t have media devices to record our audio, we just return. If they do, then let us create a stream using their audio media device. ` Finally, we go ahead and create an instance of a MediaRecorder to record this audio: ` Then we need a method to stop our recording, which will be our stopRecording. Here, we will just stop our recording in case a media recorder exists. ` We are recording our audio, but we are not storing it anywhere. Let’s add a new useEffect and ref to accomplish this. We would need a new ref, and this is where our chunks of audio data will be stored. ` In our useEffect we are going to do two main things: store those chunks in our ref, and when it stops, we are going to create a new Blob of type audio/mp3: ` It is time to wire this hook with our AudioRecorder component: ` Let’s go to the other side of the coin, the backend! Setting up our Server side We want to use our models on the server to keep things safe and run faster. Let’s create a new route and add a handler for it using route handlers from Next.js. In our App folder, let’s make an “Api” folder with the following route in it: We want to use our models on the server to keep things safe and run faster. Let’s create a new route and add a handler for it using route handlers from Next.js. In our App folder, let’s make an “Api” folder with the following route in it: ` Our route is called ‘chat’. In the route.ts file, we’ll set up our handler. Let’s start by setting up our OpenAI SDK. ` In this route, we’ll send the audio from the front end as a base64 string. Then, we’ll receive it and turn it into a Buffer object. ` It’s time to use our first model. We want to turn this audio into text and use OpenAI’s Whisper Speech-To-Text model. Whisper needs an audio file to create the text. Since we have a Buffer instead of a file, we’ll use their ‘toFile’ method to convert our audio Buffer into an audio file like this: ` Notice that we specified “mp3”. This is one of the many extensions that the Whisper model can use. You can see the full list of supported extensions here: https://platform.openai.com/docs/api-reference/audio/createTranscription#audio-createtranscription-file Now that our file is ready, let’s pass it to Whisper! Using our OpenAI instance, this is how we will invoke our model: ` That’s it! Now, we can move on to the next step: using Llama 3.1 to interpret this text and give us an answer. We’ll use two methods for this. First, we’ll use ‘ollama’ from the ‘ollama-ai-provider’ package, which lets us use this model with our locally running Ollama. Then, we’ll use ‘generateText’ from the Vercel AI SDK to generate the text. Side note: To make our Ollama run locally, we need to write the following command in the terminal: ` ` Finally, we have our last model: TTS from OpenAI. We want to reply to our user with audio, so this model will be really helpful. It will turn our text into speech: ` The TTS model will turn our response into an audio file. We want to stream this audio back to the user like this: ` And that’s all the whole backend code! Now, back to the frontend to finish wiring everything up. Putting It All Together In our useRecordVoice.tsx hook, let's create a new method that will call our API endpoint. This method will also take the response back and play to the user the audio that we are streaming from the backend. ` Great! Now that we’re getting our streamed response, we need to handle it and play the audio back to the user. We’ll use the AudioContext API for this. This API allows us to store the audio, decode it and play it to the user once it’s ready: ` And that's it! Now the user should hear the audio response on their device. To wrap things up, let's make our app a bit nicer by adding a little loading indicator: ` Conclusion In this blog post, we saw how combining multiple AI models can help us achieve our goals. We learned to run AI models like Llama 3.1 locally and use them in our Next.js app. We also discovered how to send audio to these models and stream back a response, playing the audio back to the user. This is just one of many ways you can use AI—the possibilities are endless. AI models are amazing tools that let us create things that were once hard to achieve with such quality. Thanks for reading; now, it’s your turn to build something amazing with AI! You can find the complete demo on GitHub: AI Assistant with Whisper TTS and Ollama using Next.js...

Sep 27, 2024

8 mins

AINextJSJavaScript

How to Truncate Strings Easily with CSS

You'll often need to truncate text when working with user interfaces, especially when displaying content within a limited space. CSS provides a straightforward way to handle this scenario, ensuring that long text strings are cut off gracefully without affecting the overall layout. CSS Truncation Techniques Single-Line Truncation If you want to truncate a single line of text, CSS provides a simple solution. The key properties to use here are overflow, white-space, and text-overflow. ` Explanation of properties: * white-space: nowrap: This ensures the text stays on a single line, preventing wrapping. * overflow: hidden: This hides any content that overflows the container. * text-overflow: ellipsis: This adds the ellipsis (…) at the end of the truncated text. Multi-Line Truncation While truncating a single line of text is common, sometimes you may want to display multiple lines but still cut off the text when it exceeds a certain number of lines. You can use a combination of CSS properties such as -webkit-line-clamp along with the display and overflow properties. ` Live example: Explanation of properties: * display: -webkit-box: This is a legacy flexbox-like display property that works with the -webkit-line-clamp property. * -webkit-line-clamp: Specifies the number of lines to show before truncating. * -webkit-box-orient: vertical: Ensures the box is laid out vertically for proper multi-line truncation. * overflow: hidden: Prevents content overflow. * text-overflow: ellipsis: Adds an ellipsis after the truncated content. Why Use CSS for Text Truncation Over JavaScript Techniques? While it’s possible to truncate text using JavaScript, CSS is often a better choice for this task for several reasons. Let's explore why CSS-based truncation techniques are generally preferred over JavaScript. Performance Efficiency CSS operates directly within the browser's layout engine, meaning it doesn’t require additional processing or event handling as JavaScript does. When using JavaScript to truncate text, the script needs to run on page load (or after DOM manipulation), and sometimes, it needs to listen for events such as window resizing to adjust truncation. This can introduce unnecessary overhead, especially in complex or resource-constrained environments like mobile devices. CSS, on the other hand, is declarative. Once applied, it allows the browser to handle text rendering without any further execution or processing. This leads to faster load times and a smoother user experience. Simplicity and Maintainability CSS solutions are much simpler to implement and maintain than their JavaScript counterparts. All it takes is a few lines of CSS to implement truncation. In contrast, a JavaScript solution would require you to write and maintain a function that manually trims strings, inserts ellipses, and re-adjusts the text whenever the window is resized. Here's the JavaScript Truncation Example to compare the complexity: JavaScript Truncation Example: ` At the example above, we truncated the text to 50 characters which may be 1 line on large screens and 6 lines on mobile and in that case we will need to add more code to truncate it responsively. As you can see, the CSS solution we used earlier is more concise and readable, whereas the JavaScript version is more verbose and requires managing the string length manually. Responsiveness Without Extra Code With CSS, truncation can adapt automatically to different screen sizes and layouts. You can use relative units (like percentages or vw/vh), media queries, or flexbox/grid properties to ensure the text truncates appropriately in various contexts. If you were using JavaScript, you’d need to write additional logic to detect changes in the viewport size and update the truncation manually. This would likely involve adding event listeners for window resize events, which can degrade performance and lead to more complex code. CSS Example for Responsive Truncation: ` To achieve this in JavaScript, you’d need to add more code to handle the width adjustments dynamically, making it more complex to maintain and troubleshoot. Separation of Concerns CSS handles the presentation layer of your website, while JavaScript should focus on dynamic functionality or data manipulation. By keeping truncation logic within your CSS, you're adhering to the principle of separation of concerns, where each layer of your web application has a clear, well-defined role. Using JavaScript for visual tasks like truncation mixes these concerns, making your codebase harder to maintain, debug, and scale. CSS is purpose-built for layout and visual control, and truncation is naturally a part of that domain. Browser Support and Cross-Browser Consistency Modern CSS properties like text-overflow and -webkit-line-clamp are widely supported across all major browsers. This means that CSS solutions for truncation are generally consistent and reliable. JavaScript solutions, on the other hand, may behave differently depending on the browser environment and require additional testing and handling for cross-browser compatibility. While older browsers may not support specific CSS truncation techniques (e.g., multi-line truncation), fallback options (like single-line truncation) can be easily managed through CSS alone. With JavaScript, more complex logic might be required to handle such situations. Reduced Risk of Layout Shifting JavaScript-based text truncation risks causing layout shifting, especially during initial page loads or window resizes. The browser may need to recalculate the layout multiple times, leading to content flashing or jumpy behavior as text truncation is applied. CSS-based truncation is applied as part of the browser’s natural rendering flow, eliminating this risk and ensuring a smoother experience for the user. Conclusion CSS is the optimal solution for truncating text in most cases due to its simplicity, efficiency, and responsiveness. It leverages the power of the browser’s rendering engine, avoids the overhead of JavaScript, and keeps your code clean and maintainable. While JavaScript truncation has its use cases, CSS should always be your go-to solution for truncating strings, especially in static or predictable layouts. If you like this post, check out the other CSS posts on our blog!...

Sep 13, 2024

4 mins

CSS

Introduction to Zod for Data Validation

As web developers, we're often working with data from external sources like APIs we don't control or user inputs submitted to our backends. We can't always rely on this data to take the form we expect, and we can encounter unexpected errors when it deviates from expectations. But with the Zod library, we can define what our data ought to look like and parse the incoming data against those defined schemas. This lets us work with that data confidently, or to quickly throw an error when it isn't correct. Why use Zod? TypeScript is great for letting us define the shape of our data in our code. It helps us write more correct code the first time around by warning us if we are doing something we shouldn't. But TypeScript can't do everything for us. For example, we can define a variable as a string or a number, but we can't say "a string that starts with user_id_ and is 20 characters long" or "an integer between 1 and 5". There are limits to how much TypeScript can narrow down our data for us. Also, TypeScript is a tool for us developers. When we compile our code, our types are not available to the vanilla JavaScript. JavaScript can't validate that the data we actually use in our code matches what we thought we'd get when we wrote our TypeScript types unless you're willing to manually write code to perform those checks. This is where we can reach for a tool like Zod. With Zod, we can write data schemas. These schemas, in the simplest scenarios, look very much like TypeScript types. But we can do more with Zod than we can with TypeScript alone. Zod schemas let us create additional rules for data parsing and validation. A 20-character string that starts with user_id_? It's z.string().startsWith('user_id_').length(20). An integer between 1 and 5 inclusive? It's z.number().int().gte(1).lte(5). Zod's primitives give us many extra functions to be more specific about *exactly* what data we expect. Unlike TypeScript, Zod schemas aren't removed on compilation to JavaScript—we still have access to them! If our app receives some data, we can verify that it matches the expected shape by passing it to your Zod schema's parse function. You'll either get back your data in exactly the shape you defined in your schema, or Zod will give you an error to tell you what was wrong. Zod schemas aren't a replacement for TypeScript; rather, they are an excellent complement. Once we've defined our Zod schema, it's simple to derive a TypeScript type from it and to use that type as we normally would. But when we really need to be sure our data conforms to the schema, we can always parse the data with our schema for that extra confidence. Defining Data Schemas Zod schemas are the variables that define our expectations for the shape of our data, validate those expectations, and transform the data if necessary to match our desired shape. It's easy to start with simple schemas, and to add complexity as required. Zod provides different functions that represent data structures and related validation options, which can be combined to create larger schemas. In many cases, you'll probably be building a schema for a data object with properties of some primitive type. For example, here's a schema that would validate a JavaScript object representing an order for a pizza: ` Zod provides a number of primitives for defining schemas that line up with JavaScript primitives: string, number, bigint, boolean, date, symbol, undefined, and null. It also includes primitives void, any, unknown, and never for additional typing information. In addition to basic primitives, Zod can define object, array, and other native data structure schemas, as well as schemas for data structures not natively part of JavaScript like tuple and enum. The documentation contains considerable detail on the available data structures and how to use them. Parsing and Validating Data with Schemas With Zod schemas, you're not only telling your program what data should look like; you're also creating the tools to easily verify that the incoming data matches the schema definitions. This is where Zod really shines, as it greatly simplifies the process of validating data like user inputs or third party API responses. Let's say you're writing a website form to register new users. At a minimum, you'll need to make sure the new user's email address is a valid email address. For a password, we'll ask for something at least 8 characters long and including one letter, one number, and one special character. (Yes, this is not really the best way to write strong passwords; but for the sake of showing off how Zod works, we're going with it.) We'll also ask the user to confirm their password by typing it twice. First, let's create a Zod schema to model these inputs: ` So far, this schema is pretty basic. It's only making sure that whatever the user types as an email is an email, and it's checking that the password is at least 8 characters long. But it is *not* checking if password and confirmPassword match, nor checking for the complexity requirements. Let's enhance our schema to fix that! ` By adding refine with a custom validation function, we have been able to verify that the passwords match. If they don't, parsing will give us an error to let us know that the data was invalid. We can also chain refine functions to add checks for our password complexity rules: ` Here we've chained multiple refine functions. You could alternatively use superRefine, which gives you even more fine grained control. Now that we've built out our schema and added refinements for extra validation, we can parse some user inputs. Let's see two test cases: one that's bound to fail, and one that will succeed. ` There are two main ways we can use our schema to validate our data: parse and safeParse. The main difference is that parse will throw an error if validation fails, while safeParse will return an object with a success property of either true or false, and either a data property with your parsed data or an error property with the details of a ZodError explaining why the parsing failed. In the case of our example data, userInput2 will parse just fine and return the data for you to use. But userInput1 will create a ZodError listing all of the ways it has failed validation. ` ` We can use these error messages to communicate to the user how they need to fix their form inputs if validation fails. Each error in the list describes the validation failure and gives us a human readable message to go with it. You'll notice that the validation errors for checking for a valid email and for checking password length have a lot of details, but we've got three items at the end of the error list that don't really tell us anything useful: just a custom error of Invalid input. The first is from our refine checking if the passwords match, and the second two are from our refine functions checking for password complexity (numbers and special characters). Let's modify our refine functions so that these errors are useful! We'll add our own error parameters to customize the message we get back and the path to the data that failed validation. ` Now, our error messages from failures in refine are informative! You can figure out which form fields aren't validating from the path, and then display the messages next to form fields to let the user know how to remedy the error. ` By giving our refine checks a custom path and message, we can make better use of the returned errors. In this case, we can highlight specific problem form fields for the user and give them the message about what is wrong. Integrating with TypeScript Integrating Zod with TypeScript is very easy. Using z.infer<typeof YourSchema> will allow you to avoid writing extra TypeScript types that merely reflect the intent of your Zod schemas. You can create a type from any Zod schema like so: ` Using a TypeScript type derived from a Zod schema does *not* give you any extra level of data validation at the type level beyond what TypeScript is capable of. If you create a type from z.string.min(3).max(20), the TypeScript type will still just be string. And when compiled to JavaScript, even that will be gone! That's why you still need to use parse/safeParse on incoming data to validate it before proceeding as if it really does match your requirements. A common pattern with inferring types from Zod schemas is to use the same name for both. Because the schema is a variable, there's no name conflict if the type uses the same name. However, I find that this can lead to confusing situations when trying to import one or the other—my personal preference is to name the Zod schema with Schema at the end to make it clear which is which. Conclusion Zod is an excellent tool for easily and confidently asserting that the data you're working with is exactly the sort of data you were expecting. It gives us the ability to assert at runtime that we've got what we wanted, and allows us to then craft strategies to handle what happens if that data is wrong. Combined with the ability to infer TypeScript types from Zod schemas, it lets us write and run more reliable code with greater confidence....

Nov 15, 2024

7 mins

JavaScriptZod

Understanding the Difference Between `:focus` and `:focus-visible` in CSS

Understanding the Difference Between :focus and :focus-visible in CSS I have learned my fair share about the importance of keyboard accessibility, so I know that visual indication of the focused element is very important. But the well-known :focus pseudo-class is not always the best fit for this job. That's where :focus-visible comes in. Let's look at the differences between these two pseudo-classes and explore the best practices for using them effectively. What is the :focus Pseudo-Class? The :focus pseudo-class is a CSS selector that applies styles to any element that receives focus, regardless of how that focus was triggered. This includes focus events from keyboard navigation, mouse clicks, and touch interactions. Example Usage of :focus ` In this example, the button will display a blue outline whenever it is focused, whether the user clicks on it with a mouse, taps it on a touchscreen, or navigates to it using the keyboard. What is the :focus-visible Pseudo-Class? The :focus-visible pseudo-class is more specialized. It only applies styles to an element when the browser determines that the focus should be visible. This typically occurs when the user navigates via the keyboard or assistive technologies rather than through mouse or touch input. Example Usage of :focus-visible ` Here, the button will only show a blue outline when focused through keyboard navigation or another input method that usually requires visible focus indicators. Key Differences Between :focus and :focus-visible :focus - Behavior: Applies to any element that receives focus, regardless of the input method. - Use Cases: Ensures that all interactions with the element are visually indicated, whether by mouse, keyboard, or touch. :focus-visible - Behavior: Applies styles only when the focus should be visible, such as using a keyboard or assistive technology. - Use Cases: Ideal for scenarios where you want to provide focus indicators only to keyboard and assistive technology users while avoiding unnecessary outlines for mouse and touch users, typically required by design. Accessibility Implications :focus - Pros: - Guarantees that all users can see when an element is focused, which is critical for accessibility. - Cons: - Can lead to a suboptimal experience for mouse users, as focus styles may appear unnecessarily during mouse interactions. :focus-visible - Pros: - Enhances user experience by showing focus indicators only when necessary, thus keeping the interface clean for mouse and touch users. - Tailors the experience for keyboard and assistive technology users, providing them with clear visual cues. - Cons: - Additional considerations may be required to ensure that focus indicators are not accidentally omitted, especially in older browsers that do not support :focus-visible. - There may be cases where you want to show focus indicators for all users, regardless of input method. Best Practices for Using :focus and :focus-visible To achieve the best accessibility and user experience, combining both :focus and :focus-visible in your CSS is often a good idea. Combining :focus and :focus-visible ` Here is a Stackblitz example of what such styling could look like for you to try out and play with. Additional Tips - Test with Keyboard and Assistive Technology: Ensure that your web application is navigable using a keyboard (Tab, Shift + Tab, etc.) and that focus indicators are visible for those who rely on them. It's never a bad idea to include accessibility testing in your e2e testing suite. - Provide Clear Focus Indicators: Make sure that focus indicators are prominent and easy to see. A subtle or hard-to-spot focus indicator can severely impact accessibility for users who rely on keyboard navigation. Conclusion The :focus-visible pseudo-class offers a more refined way to manage focus indicators, improving accessibility and user experience, particularly for keyboard and assistive technology users. By understanding the differences between :focus and :focus-visible, and applying best practices in your CSS, you can create more accessible and user-friendly web applications. Remember, accessibility should never be an afterthought. By thoughtfully applying focus styles, you ensure that all users, regardless of how they interact with your site, can easily navigate and interact....

Nov 8, 2024

3 mins

AccessibilityCSSPlaywright

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The Evolution of CSS: From Early Days to Flexbox & Grid with Kevin Powell

Chapters

You might also like

How to build an AI assistant with OpenAI, Vercel AI SDK, and Ollama with Next.js

How to Truncate Strings Easily with CSS

Introduction to Zod for Data Validation

Understanding the Difference Between `:focus` and `:focus-visible` in CSS

Let's innovate together!

You might also like

How to build an AI assistant with OpenAI, Vercel AI SDK, and Ollama with Next.js

How to Truncate Strings Easily with CSS

Introduction to Zod for Data Validation

Understanding the Difference Between `:focus` and `:focus-visible` in CSS