General

Lit 2.0 Released: Building Fast and Lightweight Web Components

Published May 17, 2021

Updated Feb 14, 2023

4 min read

This article was written over 18 months ago and may contain information that is out of date. Some content may be relevant but please refer to the relevant official documentation or available resources for the latest information.

In the past months, I've been actively using Web Components to build single-page applications. It has been a great experience so far, not only because I learned a lot about the latest web standards, but also because the web applications ended up being quite fast.

The Web Component development story is not something new. In fact, it has been nearly three years since LitElement was introduced as a base class to build Web Components using JavaScript with the addition of great support from TypeScript. On the other hand, lit-html had been released almost four years ago as a way to create small and fast HTML templates in JavaScript.

As it was expected, these two worlds evolved favorably. Lit 2.0 was announced as a single library with a major update promising simple and fast Web Components.

What's New?

Lit 2.0 is coming out with a lot of great new features.

Smaller

The templating system of Lit 2.0 weights around 2.7 KB minified, and gzipped(compressed). Including the component base + reactive elements, it weights 5.8 KB.

The previous image shows the bundle size for lit@2.0.0-rc.1 from the BundlePhobia tool.

Better

This new release also includes several template improvements and a brand new class-based API for creating directives as the below example shows.

import {Directive, directive} from 'lit/directive.js';

class MyDirective extends Directive {
  render() {
    return `Hello world`;
  }
}

const hello = directive(MyDirective);
const template = html`<div>${hello()}</div>`;

Also, Lit 2.0 introduces the concept of Reactive Controllers which is a powerful primitive for code reuse and composition.

A Reactive Controller comes with the ability to "hook" into the component's lifecycle and it has its own creation API.

class MyElement extends LitElement {
  private clock = new MyReactiveController(this);
}

In the above code snippet, the component associated with the Reactive Controller instance is called the host component.

Faster

The Lit team has considered efficient rendering as one of the core values for the library since a good performance is always important when you're building for the web platform.

The library authors claim that Lit 2.0 is up to 20% faster on initial rendering and up to 15% faster on updates.

Also, it's good to know that Lit templates are efficient in keeping track of the UI, and only updates on re-rendering. These powerful features come along with interoperability in mind: they can work anywhere you use HTML with or without any framework.

Server-Side Rendering

Yes, Lit 2.0 comes with a server package for rendering Lit templates and components on the server, along with a flexible client-side "hydration".

The package name is below @lit-labs/ssr since it's a pre-release software at this time. However, it's expected to support a wide range of use cases:

App rendering frameworks built on top of web components.
Framework-specific plugins for rendering custom elements such as React or Angular.
Integration with static site generators.

You can be up-to-date about this server-side rendering support by following the news in this repository.

Connect with Lit

Lit 2.0 is not only about the cool features that are already described above, it comes along with a brand-new logo, a new website, and a welcoming community.

Why Lit?

The Web Components written with Lit are natively supported by browsers and they can be a perfect solution to share components across your application.

Also, Lit can be a useful solution to create your set of components through the Design System defined by your organization. This is even more helpful when your team uses multiple libraries and frameworks to build applications!

Community

You can be the first to know the good news about Lit and the upcoming releases. Share your ideas and projects with the community.

Join the conversations on Twitter: @buildWithLit
Send your issues or even better, help with Pull Requests on GitHub
Send your questions and help with technical issues on StackOverflow. Use lit, lit-html and lit-element as the related tags.
Finally, you can be part of lit-and-friends on Slack.

Just always remember to be nice to each other!

Playground

If you are a Developer who really enjoys and thinks through interactive examples, you cannot miss the Lit Playground website, which comes with the classic "Hello World" examples (using JavaScript and TypeScript), and others covering template concepts, directives, and more.

Conclusion

In case you were using both LitElement and lit-html (like me), it could be a great opportunity to upgrade your code to Lit 2.0. The general idea to do this involves updating the npm packages, importing paths, updating any custom directive, and using the class-based API or even adapt to minor breaking changes. Luckily, there is a guide available for upgrades.

If you're new in the world of Web Components, welcome! There is a step-by-step Lit tutorial available too.

Feel free to reach out on Twitter if you have any questions. Follow me on GitHub to see more about my work. Be ready for more articles about Lit on this blog.

This Dot is a consultancy dedicated to guiding companies through their modernization and digital transformation journeys. Specializing in replatforming, modernizing, and launching new initiatives, we stand out by taking true ownership of your engineering projects.

We love helping teams with projects that have missed their deadlines or helping keep your strategic digital initiatives on course. Check out our case studies and our clients that trust us with their engineering.

About the author(s)

Luis Aviles
Luis is a Senior Software Engineer and Google Developer Expert in Web Technologies and Angular. He is an author of online courses, technical articles, and a public speaker. He has participated in different international technology conferences, giving technical talks, workshops, and training sessions. He’s passionate about the developer community and he loves to help junior developers and professionals to improve their skills. When he’s not coding, Luis is doing photography or Astrophotography.
@luixaviles @luixaviles

Understanding Vue's Reactive Data

Introduction Web development has always been about creating dynamic experiences. One of the biggest challenges developers face is managing how data changes over time and reflecting these changes in the UI promptly and accurately. This is where Vue.js, one of the most popular JavaScript frameworks, excels with its powerful reactive data system. In this article, we dig into the heart of Vue's reactivity system. We unravel how it perfectly syncs your application UI with the underlying data state, allowing for a seamless user experience. Whether new to Vue or looking to deepen your understanding, this guide will provide a clear and concise overview of Vue's reactivity, empowering you to build more efficient and responsive Vue 3 applications. So, let’s kick off and embark on this journey to decode Vue's reactive data system. What is Vue's Reactive Data? What does it mean for data to be ”'reactive”? In essence, when data is reactive, it means that every time the data changes, all parts of the UI that rely on this data automatically update to reflect these changes. This ensures that the user is always looking at the most current state of the application. At its core, Vue's Reactive Data is like a superpower for your application data. Think of it like a mirror - whatever changes you make in your data, the user interface (UI) reflects these changes instantly, like a mirror reflecting your image. This automatic update feature is what we refer to as “reactivity”. To visualize this concept, let's use an example of a simple Vue application displaying a message on the screen: ` In this application, 'message' is a piece of data that says 'Hello Vue!'. Let's say you change this message to 'Goodbye Vue!' later in your code, like when a button is clicked. ` With Vue's reactivity, when you change your data, the UI automatically updates to 'Goodbye Vue!' instead of 'Hello Vue!'. You don't have to write extra code to make this update happen - Vue's Reactive Data system takes care of it. How does it work? Let's keep the mirror example going. Vue's Reactive Data is the mirror that reflects your data changes in the UI. But how does this mirror know when and what to reflect? That's where Vue's underlying mechanism comes into play. Vue has a behind-the-scenes mechanism that helps it stay alerted to any changes in your data. When you create a reactive data object, Vue doesn't just leave it as it is. Instead, it sends this data object through a transformation process and wraps it up in a Proxy. Proxy objects are powerful and can detect when a property is changed, updated, or deleted. Let's use our previous example: ` Consider our “message” data as a book in a library. Vue places this book (our data) within a special book cover (the Proxy). This book cover is unique - it's embedded with a tracking device that notifies Vue every time someone reads the book (accesses the data) or annotates a page (changes the data). In our example, the reactive function creates a Proxy object that wraps around our state object. When you change the 'message': ` The Proxy notices this (like a built-in alarm going off) and alerts Vue that something has changed. Vue then updates the UI to reflect this change. Let’s look deeper into what Vue is doing for us and how it transforms our object into a Proxy object. You don't have to worry about creating or managing the Proxy; Vue handles everything. ` In the example above, we encapsulate our object, in this case, “state”, converting it into a Proxy object. Note that within the second argument of the Proxy, we have two methods: a getter and a setter. The getter method is straightforward: it merely returns the value, which in this instance is “state.message” equating to 'Hello Vue!' Meanwhile, the setter method comes into play when a new value is assigned, as in the case of “state.message = ‘Hey young padawan!’”. Here, “value” becomes our new 'Hey young padawan!', prompting the property to update. This action, in turn, triggers the reactivity system, which subsequently updates the DOM. Venturing Further into the Depths If you have been paying attention to our examples above, you might have noticed that inside the Proxy method, we call the functions track and trigger to run our reactivity. Let’s try to understand a bit more about them. You see, Vue 3 reactivity data is more about Proxy objects. Let’s create a new example: ` In this example, when you click on the button, the message's value changes. This change triggers the effect function to run, as it's actively listening for any changes in its dependencies. How does the effect property know when to be called? Vue 3 has three main functions to run our reactivity: effect, track, and trigger. The effect function is like our supervisor. It steps in and takes action when our data changes – similar to our effect method, we will dive in more later. Next, we have the track function. It notes down all the important data we need to keep an eye on. In our case, this data would be state.message. Lastly, we've got the trigger function. This one is like our alarm bell. It alerts the effect function whenever our important data (the stuff track is keeping an eye on) changes. In this way, trigger, track, and effect work together to keep our Vue application reacting smoothly to changes in data. Let’s go back to them: ` Tracking (Dependency Collection) Tracking is the process of registering dependencies between reactive objects and the effects that depend on them. When a reactive property is read, it's "tracked" as a dependency of the current running effect. When we execute track(), we essentially store our effects in a Set object. But what exactly is an "effect"? If we revisit our previous example, we see that the effect method must be run whenever any property changes. This action — running the effect method in response to property changes — is what we refer to as an "Effect"! (computed property, watcher, etc.) > Note: We'll outline a basic, high-level overview of what might happen under the hood. Please note that the actual implementation is more complex and optimized, but this should give you an idea of how it works. Let’s see how it works! In our example, we have the following reactive object: ` We need a way to reference the reactive object with its effects. For that, we use a WeakMap. Which type is going to look something like this: ` We are using a WeakMap to set our object state as the target (or key). In the Vue code, they call this object targetMap. Within this targetMap object, our value is an object named depMap of Map type. Here, the keys represent our properties (in our case, that would be message and showSword), and the values correspond to their effects – remember, they are stored in a Set that in Vue 3 we refer to as dep. Huh… It might seem a bit complex, right? Let's make it more straightforward with a visual example: With the above explained, let’s see what this Track method kind of looks like and how it uses this targetMap. This method essentially is doing something like this: ` At this point, you have to be wondering, how does Vue 3 know what activeEffect should run? Vue 3 keeps track of the currently running effect by using a global variable. When an effect is executed, Vue temporarily stores a reference to it in this global variable, allowing the track function to access the currently running effect and associate it with the accessed reactive property. This global variable is called inside Vue as activeEffect. Vue 3 knows which effect is assigned to this global variable by wrapping the effects functions in a method that invokes the effect whenever a dependency changes. And yes, you guessed, that method is our effect method. ` This method behind the scenes is doing something similar to this: ` The handling of activeEffect within Vue's reactivity system is a dance of careful timing, scoping, and context preservation. Let’s go step by step on how this is working all together. When we run our Effect method for the first time, we call the get trap of the Proxy. ` When running the get trap, we have our activeEffect so we can store it as a dependency. ` This coordination ensures that when a reactive property is accessed within an effect, the track function knows which effect is responsible for that access. Trigger Method Our last method makes this Reactive system to be complete. The trigger method looks up the dependencies for the given target and key and re-runs all dependent effects. ` Conclusion Diving into Vue 3's reactivity system has been like unlocking a hidden superpower in my web development toolkit, and honestly, I've had a blast learning about it. From the rudimentary elements of reactive data and instantaneous UI updates to the intricate details involving Proxies, track and trigger functions, and effects, Vue 3's reactivity is an impressively robust framework for building dynamic and responsive applications. In our journey through Vue 3's reactivity, we've uncovered how this framework ensures real-time and precise updates to the UI. We've delved into the use of Proxies to intercept and monitor variable changes and dissected the roles of track and trigger functions, along with the 'effect' method, in facilitating seamless UI updates. Along the way, we've also discovered how Vue ingeniously manages data dependencies through sophisticated data structures like WeakMaps and Sets, offering us a glimpse into its efficient approach to change detection and UI rendering. Whether you're just starting with Vue 3 or an experienced developer looking to level up, understanding this reactivity system is a game-changer. It doesn't just streamline the development process; it enables you to create more interactive, scalable, and maintainable applications. I love Vue 3, and mastering its reactivity system has been enlightening and fun. Thanks for reading, and as always, happy coding!...

Nov 22, 2023

7 mins

VueJavaScriptTypeScriptWeb Development

A Tale of Form Autofill, LitElement and the Shadow DOM

Many web applications utilize forms in places be it for logging in, making payments, or editing a user profile. As a user of web applications, you have probably noticed that the browser is able to autofill in certain fields when a form appears so that you don't have to do it yourself. If you've ever written an application in Lit though, you may have noticed that this doesn't always work as expected. The Problem I was working on a frontend project utilizing Lit and had to implement a login form. In essence these aren’t very complicated on the frontend side of life. You just need to define a form, put some input elements inside of it with the correct type attributes assigned to it, then you hook the form up to your backend, API, or whatever you need to call to authenticate by adding a submit handler. However, there was an issue. The autocomplete doesn’t appear to be working as expected. Only the username field was being filled, but not the password. When this happened, I made sure to check documentation sites such as MDN and looked at examples. But I couldn’t find any differences between theirs and mine. At some point, I prepared a minimal reproducible example without Lit, and I was able to get the form working fine, so it had to do something with my usage of Lit. After doing a little bit of research and some testing, I found out this happened because Lit relies very heavily on something known as the Shadow DOM. I don’t believe the Shadow DOM is necessarily supposed to break this functionality. But for most major browsers, it doesn’t play nice with autocomplete for the time being. I experienced slightly different behavior in all browsers, and the autocomplete even worked under Shadow DOM with Firefox in the Lit app I was working on. The solution I ended up settling on was ensuring the form was contained inside of the Light DOM instead of the Shadow DOM, whilst also allowing the Shadow DOM to continue to be used in places where autofillable forms are not present. In this article I will show you how to implement this solution, and how to deal with any problems that might arise from it. Shadow DOM vs. Light DOM The Shadow DOM is a feature that provides a way to encapsulate your components and prevent unrelated code and components from affecting them in undesired ways. Specifically, it allows for a way to prevent outside CSS from affecting your components and vice versa by scoping them to a specific shadow root. When it comes to the Light DOM, even if you’ve never heard of the term, you’ve probably used it. If you’ve ever worked on any website before, and interacted with the standard DOM tree, that is the Light DOM. The Light DOM, and any Shadow DOMs under it for that matter, can contain Shadow DOMs inside of them attached to elements. When you add a Lit component to a page, a shadow root will get attached to it that will contain its subelements, and prevent CSS from outside of that DOM from affecting it. Using Light DOM with Certain Web Components By default, Lit attaches a shadow root to all custom elements that extend from LitElement. However, web components don’t actually require a shadow root to function. We can do away with the shadow root by overriding the createRenderRoot method, and returning the web component itself: ` Although we can just put this method in any element we want exposed into the Light DOM. We can also make a new component called LightElement that overrides this method that we can extend from instead of LitElement on our own components. This will be useful later when we tackle another problem. Uh oh, where did my CSS styling and slots go? The issue with not using a shadow root is Lit has no way to encapsulate your component stylesheets anymore. As a result, your light components will now inherit styles from the root that they are contained in. For example, if your components are directly in the body of the page, then they will inherit all global styles on the page. Similarly when your light components are inside of a shadow root, they will inherit any styles attached to that shadow root. To resolve this issue, one could simply add style tags to the HTML template returned in the render() method, and accept that other stylesheets in the same root could affect your components. You can use naming conventions such as BEM for your CSS classes to mitigate this for the most part. Although this does work and is a very pragmatic solution, this solution does pollute the DOM with multiple duplicate stylesheets if more than one instance of your component is added to the DOM. Now, with the CSS problem solved, you can now have a functional Lit web component with form autofill for passwords and other autofillable data! You can view an example using this solution here. A Better Approach using Adopted Stylesheets For a login page where only one instance of the component is in the DOM tree at any given point, the aforementioned solution is not a problem at all. However, this can become a problem if whatever element you need to use the Light DOM with is used in lots of places or repeated many times on a page. An example of this would be a custom input element in a table that contains hundreds of rows. This can potentially cause performance issues, and also pollute the CSS inspector in your devtools resulting in a suboptimal experience both for users and yourself. The better, though still imperfect, way to work around this problem is to use the adopted stylesheets feature to attach stylesheets related to the web component to the root it is connected in, and reuse that same stylesheet across all instances of the node. Below is a function that tracks stylesheets using an id and injects them in the root node of the passed in element. Do note that, with this approach, it is still possible for your component’s styles to leak to other components within the same root. And like I advised earlier, you will need to take that into consideration when writing your styles. ` This solution works for most browsers, and a fallback is included for Safari as it doesn’t support adoptedStylesheets at the time of writing this article. For Safari we inject de-duplicated style elements at the root. This accomplishes the same result effectively. Let’s go over the evictDisconnectedRoots function that was called inside of the injection function. We need to ensure we clean up global state since the injection function relies on it to keep duplication to a minimum. Our global state holds references to document nodes and shadow roots that may no longer exist in the DOM. We want these to get cleaned up so as to not leak memory. Thankfully, this is easy to iterate through and check because of the isConnected property on nodes. ` Now we need to get our Lit component to use our new style injection function. This can be done by modifying our LightElement component, and having it iterate over its statically defined stylesheets and inject them. Since our injection function contains the de-duplication logic itself, we don’t need to concern ourselves with that here. ` With all that you should be able to get an autocompletable form just like the previous example. The full example using the adopted stylesheets approach can be found here. Conclusion I hope this article was helpful for helping you figure out how to implement autofillable forms in Lit. Both examples can be viewed in our blog demos repository. The example using basic style tags can be found here, and the one using adopted stylesheets can be found here....

Jun 7, 2023

6 mins

Lit

How to Manage Breakpoints using BreakpointObserver in Angular

Defining Breakpoints is important when you start working with Responsive Design and most of the time they're created using CSS code. For example: ` By default, the text size value will be 12px, and this value will be changed to 14px when the viewport gets changed to a smaller screen (a maximum width of 600px). That solution works. However, what about if you need to _listen_ for certain breakpoints to perform changes in your application? This may be needed to configure third-party components, processing events, or any other. Luckily, Angular comes with a handy solution for these scenarios: the BreakpointObserver. Which is a utility for checking the matching state of @media queries. In this post, we will build a sample application to add the ability to configure certain breakpoints, and being able to _listen_ to them. Project Setup Prerequisites You'll need to have installed the following tools in your local environment: - Node.js. Preferably the latest LTS version. - A package manager. You can use either NPM or Yarn. This tutorial will use NPM. Creating the Angular Project Let's start creating a project from scratch using the Angular CLI tool. ` This command will initialize a base project using some configuration options: - --routing. It will create a routing module. - --prefix corp. It defines a prefix to be applied to the selectors for created components(corp in this case). The default value is app. - --style scss. The file extension for the styling files. - --skip-tests. it avoids the generations of the .spec.ts files, which are used for testing Adding Angular Material and Angular CDK Before creating the breakpoints, let's add the Angular Material components, which will install the Angular CDK library under the hood. ` Creating the Home Component We can create a brand new component to handle a couple of views to be updated while the breakpoints are changing. We can do that using the ng generate command. ` Pay attention to the output of the previous command since it will show you the auto-generated files. Update the Routing Configuration Remember we used the flag --routing while creating the project? That parameter has created the main routing configuration file for the application: app-routing.module.ts. Let's update it to be able to render the home component by default. ` Update the App Component template Remove all code except the router-outlet placeholder: ` This will allow rendering the home component by default once the routing configuration is running. Using the BreakpointObserver The application has the Angular CDK installed already, which has a layout package with some utilities to build responsive UIs that _react_ to screen-size changes. Let's update the HomeComponent, and inject the BreakpointObserver as follows. ` Once the BreakpointObserver is injected, we'll be able to evaluate media queries to determine the current screen size, and perform changes accordingly. Then, a breakpoint$ variable references an _observable_ object after a call to the observe method. The observe method gets an observable of results for the given queries, and can be used along with predetermined values defined on Breakpoints as a constant. Also, it's possible to use custom breakpoints such as (min-width: 500px). Please refer to the documentation to find more details about this. Next, you may need to _subscribe_ to the breakpoint$ observable to see the emitted values after matching the given queries. Again, let's update the home.component.ts file to do that. ` In the above code, the ngOnInit method is used to perform a _subscription_ to the breakpoint$ observable and the method breakpointChanged will be invoked every time a breakpoint match occurs. As you may note, the breakpointChanged method verifies what Breakpoint value has a match through isMatched method. In that way, the current component can perform changes after a match happened (in this case, it just updates the value for the currentBreakpoint attribute). Using Breakpoint values on the Template Now, we can set a custom template in the home.component.html file and be able to render a square according to the currentBreakpoint value. ` The previous template will render the current media query value at the top along with a rectangle according to the size: Large, Medium, Small or Custom. Live Demo and Source Code Want to play around with this code? Just open the Stackblitz editor or the preview mode in fullscreen. Find the complete angular project in this GitHub repository: breakpointobserver-example-angular. Do not forget to give it a star ⭐️ and play around with the code. Feel free to reach out on Twitter if you have any questions. Follow me on GitHub to see more about my work....

Apr 14, 2022

4 mins

AngularTypeScriptWeb Development

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

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Lit 2.0 Released: Building Fast and Lightweight Web Components

What's New?

Smaller

Better

Faster

Server-Side Rendering

Connect with Lit

Why Lit?

Community

Playground

Conclusion

Luis Aviles

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