Javascript

Testing Accessibility Features With Playwright

Published Jan 31, 2024

Updated Feb 2, 2024

5 min read

Testing Accessibility Features With Playwright

In one of my previous posts, I mentioned the importance of having e2e tests to verify that your keyboard navigation works properly. I also suggested Playwright as a tool to write those tests.

I owe you a little tutorial on how to do that. And because keyboard navigation is not the only accessibility feature you should test and since Playwright has some nice built-in tools for accessibility testing, I will also show you how to test other aspects of your website.

What is Playwright?

Let's start with a short introduction for those who don't know Playwright yet. Playwright is an open-source automation library developed by Microsoft, designed to enable developers and testers to write scripts that can control a web browser's behavior. It is a Node.js library that provides a high-level API to control headless Chrome, Firefox, and WebKit with a single interface. This means you can write your tests once and run them in multiple browsers, ensuring cross-browser compatibility.

If you're new to Playwright, you can check out Dane's article, which nicely introduces the basics such as configuration or selectors, and presents some nice test examples.

Keyboard Accessibility Testing

Now, as promised, let's dive into keyboard accessibility testing with Playwright. As I already mentioned, keyboard navigation is one of the most important accessibility features to test, given that it can break anytime you add new functionality to your application and the problem can easily go unnoticed. It is also one of the easiest to test with Playwright because it provides a neat keyboard API that allows you to simulate keyboard input and verify that the correct elements are focused or activated.

Verifying Element Focus

To check which element is selected after a series of keyboard inputs, you can use the toBeFocused() method to check whether it is focused or not, like this:

await page.keyboard.press('Tab');
await page.keyboard.press('Tab');
await page.keyboard.press('Tab');

const textbox = page.getByRole('textbox');

// Verify that the textbox is focused
await expect(textbox).toBeFocused();

// Tab out of the textbox
await page.keyboard.press('Tab');

// And verify that the textbox is not focused
await expect(textbox).not.toBeFocused();

This code snippet simulates pressing the Tab key three times and then checks that an input is focused. It then presses the Tab key again, verifying that the input is no longer focused.

If you read my previous article, you might remember that I mentioned that many websites have a bug that prevents you from tabbing out of a textbox. This simple test can catch this bug and prevent headaches for your users.

Simulating Complex Keyboard Interactions

Playwright's keyboard class provides a keyboard.press() method to simulate pressing a key and releasing it immediately. It allows you to simulate pressing a single key, a combination of keys, or a key combination with a modifier key:

await page.keyboard.press('Shift+KeyA'); // Presses uppercase 'A'
await page.keyboard.press('Control+A'); // Select all text (on Windows/Linux)

You can find the full list of keys you can pass to the keyboard.press function on MDN.

If you need finer control over the keyboard, you can use the keyboard.down() and keyboard.up() methods to simulate pressing and releasing a key separately. One use case for this is to simulate pressing a key and holding it down for a certain amount of time, such as holding the Shift key to select multiple elements or lines of text:

// Press Shift and hold it down
await page.keyboard.down('Shift');

//Press the down arrow 5 times
for (let i = 0; i < 5; i++) {
  await page.keyboard.press('ArrowDown');
}

//Release the Shift key
await page.keyboard.up('Shift');

// and verify that the first 5 list items are selected
for (let i = 0; i < 5; i++) {
    // construct the selector for the ith list item
    const listItemSelector = `ul#myList > li:nth-child(${i + 1})`;

    // use the `toHaveClass` assertion to check if the item has the 'selected' class
    await expect(page.locator(listItemSelector)).toHaveClass(/.*selected.*/);
}

You can also use the keyboard.insertText() method to insert text into an element, but note that modifier keys do not affect this method (e.g. holding down the Shift key will not type the text uppercase) and it only dispatches the input event and does not emit the keydown, keyup or keypress events.

// press Tab to focus the textbox
await page.keyboard.press('Tab');
// insert text into the textbox
await page.keyboard.insertText('Hello World!');
// expect the textbox to contain the text
await expect(page.getByRole('textbox')).toHaveValue('Hello World!');

The keyboard API allows you to test keyboard input, keyboard shortcuts; and ensure that your application responds correctly to user input without a mouse. Although this might seem unnecessary, believe me when I say it is not. As I mentioned in my previous article, many applications try to implement keyboard navigation but contain a nasty bug that renders the effort useless. And it is worth spending some time writing a few simple e2e tests to avoid invalidating your efforts.

Testing Other Accessibility Features

This article focuses mostly on keyboard accessibility, but I have good news! You can easily test other accessibility aspects with Playwright too! It conveniently integrates with the axe accessibility testing engine using the @axe-core/playwright package to run automated accessibility tests. These tests can catch various issues, such as poor color contrast, missing labels on UI controls, and duplicate IDs that can confuse assistive technologies.

Example Test for Entire Page Accessibility

Here's how you can scan your entire page for accessibility issues using Playwright:

import { test, expect } from '@playwright/test';
import AxeBuilder from '@axe-core/playwright';

test.describe('homepage', () => {
  test('should not have any automatically detectable accessibility issues', async ({ page }) => {
    await page.goto('https://your-site.com/');
    const accessibilityScanResults = await new AxeBuilder({ page }).analyze();
    expect(accessibilityScanResults.violations).toEqual([]);
  });
});

Scanning Specific Page Sections

You can also target specific parts of your page by using AxeBuilder.include() to focus the accessibility scan:

test('navigation menu should not have automatically detectable accessibility violations', async ({ page }) => {
  await page.goto('https://your-site.com/');
  await page.getByRole('button', { name: 'Navigation Menu' }).click();
  await page.locator('#navigation-menu-flyout').waitFor();
  const accessibilityScanResults = await new AxeBuilder({ page })
    .include('#navigation-menu-flyout')
    .analyze();
  expect(accessibilityScanResults.violations).toEqual([]);
});

Handling Known Accessibility Issues

When you have known accessibility issues that you cannot immediately fix, Playwright allows you to exclude certain elements from scans or disable specific rules:

const accessibilityScanResults = await new AxeBuilder({ page })
  .exclude('#element-with-known-issue')
  .analyze();

Reporting Accessibility Issues

If you want to report accessibility issues in your test results, you can use the testInfo.attach() method to attach the scan results to your test report:

test('example with attachment', async ({ page }, testInfo) => {
  await page.goto('https://your-site.com/');

  const accessibilityScanResults = await new AxeBuilder({ page }).analyze();

  await testInfo.attach('accessibility-scan-results', {
    body: JSON.stringify(accessibilityScanResults, null, 2),
    contentType: 'application/json'
  });

  expect(accessibilityScanResults.violations).toEqual([]);
});

You can then use reporters to embed or link the scan results in your test output.

Conclusion

While your e2e tests should not serve as a replacement for manual testing and you should still check your app yourself to catch any issues that automated tests won't reveal, Playwright provides a convenient way to automate checks whether all of your website's accessibility features work as intended. It allows you to test keyboard navigation and other accessibility aspects such as color contrast or missing labels to make sure you aren't shipping a broken experience.

Testing accessibility with Playwright requires little effort, and in my opinion, is very much worth it. So, if you haven't done so yet, I encourage you to give it a try! And if you're still unconvinced, read about how I broke my hand to appreciate the importance of accessibility.

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.

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About the author(s)

Jan Kaiser
Software engineer passionate about everything web-related. Particularly loves Angular, SCSS, TypeScript, soccer and dachshunds
@honzikec @honzikec

Quick Guide to Playwright Fixtures: Enhancing Your Tests

Introduction Following our recent blog post on migrating E2E tests from Cypress to Playwright, we've identified opportunities to enhance our test scripts further. In this guide, we'll delve into the basics of Playwright fixtures, demonstrating their utility and flexibility in test environments. Playwright fixtures are reusable components that set up and tear down the environment or conditions necessary for tests. They are crucial for writing clean, maintainable, and scalable tests. Fixtures can handle tasks like opening a browser, initializing a database, or logging into an application—actions you might need before running your tests. As a practical example, we'll revisit one of the tests from our previous post, enhancing it with a new fixture to streamline the testing process and significantly improve maintainability. This post is designed to provide the foundational skills to integrate fixtures into your testing workflows effectively, giving you the confidence to manage and maintain your test scripts more efficiently. Creating Our First Fixture To illustrate the power of fixtures in Playwright, let’s consider a practical example from a test scenario in our project. Below is a snippet of a test case from our newsletter page: ` This test scenario navigates to the newsletter page, fills in an email, submits the form, and checks for a success message. To optimize our test suite, we'll refactor common actions like navigation, form completion, and submission into reusable fixtures. This approach makes our tests cleaner and more maintainable and reduces redundancy across similar test scenarios. Implementing the Fixture Here’s how the fixture looks: ` This fixture encapsulates the actions of navigating to the page, filling out the email field, and submitting the form. By abstracting these actions, we simplify and focus our test cases. Refactoring the Test With the fixture in place, let’s see how it changes our original test file: ` A beforeEach method to reset the state of the NewsletterPage fixture ensures a clean and consistent environment for each test scenario. This practice is crucial for maintaining the integrity and reliability of your tests. By leveraging the NewsletterPage fixture, each test within the "Newsletter page" suite starts with a clean and pre-configured environment. This setup improves test clarity and efficiency and aligns with best practices for scalable test architecture. Conclusion As we've seen, fixtures are powerful tools that help standardize test environments, reduce code redundancy, and ensure that each test operates in a clean state. By abstracting common setup and teardown tasks into fixtures, we can focus our testing efforts on what matters most, verifying the behavior and reliability of the software we're developing. Remember, the key to successful test management is choosing the right tools and using them wisely to create scalable, maintainable, and robust testing frameworks. Playwright fixtures offer a pathway towards achieving these goals, empowering teams to build better software faster and more confidently....

Jul 26, 2024

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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

Exploring Angular Forms: A New Alternative with Signals

Exploring Angular Forms: A New Alternative with Signals In the world of Angular, forms are essential for user interaction, whether you're crafting a simple login page or a more complex user profile interface. Angular traditionally offers two primary approaches: template-driven forms and reactive forms. In my previous series on Angular Reactive Forms, I explored how to harness reactive forms' power to manage complex logic, create dynamic forms, and build custom form controls. A new tool for managing reactivity - signals - has been introduced in version 16 of Angular and has been the focus of Angular maintainers ever since, becoming stable with version 17. Signals allow you to handle state changes declaratively, offering an exciting alternative that combines the simplicity of template-driven forms with the robust reactivity of reactive forms. This article will examine how signals can add reactivity to both simple and complex forms in Angular. Recap: Angular Forms Approaches Before diving into the topic of enhancing template-driven forms with signals, let’s quickly recap Angular's traditional forms approaches: 1. Template-Driven Forms: Defined directly in the HTML template using directives like ngModel, these forms are easy to set up and are ideal for simple forms. However, they may not provide the fine-grained control required for more complex scenarios. Here's a minimal example of a template-driven form: ` ` 2. Reactive Forms: Managed programmatically in the component class using Angular's FormGroup, FormControl, and FormArray classes; reactive forms offer granular control over form state and validation. This approach is well-suited for complex forms, as my previous articles on Angular Reactive Forms discussed. And here's a minimal example of a reactive form: ` ` Introducing Signals as a New Way to Handle Form Reactivity With the release of Angular 16, signals have emerged as a new way to manage reactivity. Signals provide a declarative approach to state management, making your code more predictable and easier to understand. When applied to forms, signals can enhance the simplicity of template-driven forms while offering the reactivity and control typically associated with reactive forms. Let’s explore how signals can be used in both simple and complex form scenarios. Example 1: A Simple Template-Driven Form with Signals Consider a basic login form. Typically, this would be implemented using template-driven forms like this: ` ` This approach works well for simple forms, but by introducing signals, we can keep the simplicity while adding reactive capabilities: ` ` In this example, the form fields are defined as signals, allowing for reactive updates whenever the form state changes. The formValue signal provides a computed value that reflects the current state of the form. This approach offers a more declarative way to manage form state and reactivity, combining the simplicity of template-driven forms with the power of signals. You may be tempted to define the form directly as an object inside a signal. While such an approach may seem more concise, typing into the individual fields does not dispatch reactivity updates, which is usually a deal breaker. Here’s an example StackBlitz with a component suffering from such an issue: Therefore, if you'd like to react to changes in the form fields, it's better to define each field as a separate signal. By defining each form field as a separate signal, you ensure that changes to individual fields trigger reactivity updates correctly. Example 2: A Complex Form with Signals You may see little benefit in using signals for simple forms like the login form above, but they truly shine when handling more complex forms. Let's explore a more intricate scenario - a user profile form that includes fields like firstName, lastName, email, phoneNumbers, and address. The phoneNumbers field is dynamic, allowing users to add or remove phone numbers as needed. Here's how this form might be defined using signals: ` > Notice that the phoneNumbers field is defined as a signal of an array of signals. This structure allows us to track changes to individual phone numbers and update the form state reactively. The addPhoneNumber and removePhoneNumber methods update the phoneNumbers signal array, triggering reactivity updates in the form. ` > In the template, we use the phoneNumbers signal array to dynamically render the phone number input fields. The addPhoneNumber and removePhoneNumber methods allow users to reactively add or remove phone numbers, updating the form state. Notice the usage of the track function, which is necessary to ensure that the ngFor directive tracks changes to the phoneNumbers array correctly. Here's a StackBlitz demo of the complex form example for you to play around with: Validating Forms with Signals Validation is critical to any form, ensuring that user input meets the required criteria before submission. With signals, validation can be handled in a reactive and declarative manner. In the complex form example above, we've implemented a computed signal called formValid, which checks whether all fields meet specific validation criteria. The validation logic can easily be customized to accommodate different rules, such as checking for valid email formats or ensuring that all required fields are filled out. Using signals for validation allows you to create more maintainable and testable code, as the validation rules are clearly defined and react automatically to changes in form fields. It can even be abstracted into a separate utility to make it reusable across different forms. In the complex form example, the formValid signal ensures that all required fields are filled and validates the email and phone numbers format. This approach to validation is a bit simple and needs to be better connected to the actual form fields. While it will work for many use cases, in some cases, you might want to wait until explicit "signal forms" support is added to Angular. Tim Deschryver started implementing some abstractions around signal forms, including validation and wrote an article about it. Let's see if something like this will be added to Angular in the future. Why Use Signals in Angular Forms? The adoption of signals in Angular provides a powerful new way to manage form state and reactivity. Signals offer a flexible, declarative approach that can simplify complex form handling by combining the strengths of template-driven forms and reactive forms. Here are some key benefits of using signals in Angular forms: 1. Declarative State Management: Signals allow you to define form fields and computed values declaratively, making your code more predictable and easier to understand. 2. Reactivity: Signals provide reactive updates to form fields, ensuring that changes to the form state trigger reactivity updates automatically. 3. Granular Control: Signals allow you to define form fields at a granular level, enabling fine-grained control over form state and validation. 4. Dynamic Forms: Signals can be used to create dynamic forms with fields that can be added or removed dynamically, providing a flexible way to handle complex form scenarios. 5. Simplicity: Signals can offer a simpler, more concise way to manage form states than traditional reactive forms, making building and maintaining complex forms easier. Conclusion In my previous articles, we explored the powerful features of Angular reactive forms, from dynamic form construction to custom form controls. With the introduction of signals, Angular developers have a new tool that merges the simplicity of template-driven forms with the reactivity of reactive forms. While many use cases warrant Reactive Forms, signals provide a fresh, powerful alternative for managing form state in Angular applications requiring a more straightforward, declarative approach. As Angular continues to evolve, experimenting with these new features will help you build more maintainable, performant applications. Happy coding!...

Oct 4, 2024

5 mins

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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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We're ready to be your trusted technical partners in your digital innovation journey.

Whether it's modernization or custom software solutions, our team of experts can guide you through best practices and how to build scalable, performant software that lasts.

Testing Accessibility Features With Playwright

Testing Accessibility Features With Playwright

What is Playwright?

Keyboard Accessibility Testing

Verifying Element Focus

Simulating Complex Keyboard Interactions

Testing Other Accessibility Features

Example Test for Entire Page Accessibility

Scanning Specific Page Sections

Handling Known Accessibility Issues

Reporting Accessibility Issues

Conclusion

Jan Kaiser

You might also like

Quick Guide to Playwright Fixtures: Enhancing Your Tests

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

Exploring Angular Forms: A New Alternative with Signals

Introduction to Zod for Data Validation

Let's innovate together!

You might also like

Quick Guide to Playwright Fixtures: Enhancing Your Tests

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

Exploring Angular Forms: A New Alternative with Signals

Introduction to Zod for Data Validation