Javascript

Best Practices for Managing RxJS Subscriptions

Published Dec 14, 2020

Updated Feb 14, 2023

5 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This article was written over 18 months ago and may contain information that is out of date.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.

When we use RxJS, it's standard practice to subscribe to Observables. By doing so, we create a Subscription. This object provides us with some methods that will aid in managing these subscriptions. This is very important, and is something that should not be overlooked!

Why do we care about subscription management?

If we do not put some thought into how we manage and clean up the subscriptions we create, we can cause an array of problems in our applications. This is due to how the Observer Pattern is implemented.

When an Observable emits a new value, its Observers execute code that was set up during the subscription. For example:

obs$.subscribe(data => doSomethingWithDataReceived(data));

If we do not manage this subscription, every time obs$ emits a new value doSomethingWithDataReceived will be called.

Let's say this code is set up on the Home View of our App. It should only ever be run when the user is on the Home View. Without managing this subscription correctly when the user navigates to a new view in the App, doSomethingWithDataReceived could still be called, potentially causing unexpected results, errors or even hard-to-track bugs.

So what do we mean by Subscription Management?

Essentially, subscription management revolves around knowing when to complete or unsubscribe from an Observable, to prevent incorrect code from being executed, especially when we would not expect it to be executed.

We can refer to this management of subscriptions as cleaning up active subscriptions.

How can we clean up subscriptions?

So, now that we know that managing subscriptions are an essential part of working with RxJS, what methods are available for us to manage them?

Unsubscribing Manually

One method we can use, is to unsubscribe manually from active subscriptions when we no longer require them. RxJS provides us with a convenient method to do this. It lives on the Subscription object and is simply called .unsubscribe().

If we take the example we had above; we can see how easy it is to unsubscribe when we need to:

let homeViewSubscription = null;

function onEnterView() {
  homeViewSubscription = obs$.subscribe(data => doSomethingWithDataReceived(data));
}

function onLeaveView() {
  homeViewSubscription.unsubscribe();
}

We create a variable to store the subscription.
We store the subscription in a variable when we enter the view.
We unsubscribe from the subscription when we leave the view preventing doSomethingWithDataReceived() from being executed when we don't need it.

This is great; however, when working with RxJS, you will likely have more than one subscription. Calling unsubscribe for each of them could get tedious. A solution I have seen many codebases employ is to store an array of active subscriptions, loop through this array, unsubscribing from each when required.

Let's modify the example above to see how we could do this:

const homeViewSubscriptions = [];

function onEnterView() {
  homeViewSubscriptions.push(
      obs$.subscribe(data => doSomethingWithDataReceived(data)),
      anotherObs$.subscribe(user => updateUserData(user))
    );
}

function onLeaveView() {
  homeViewSubscriptions.forEach(subscription => subscription.unsubscribe());
}

We create an array to store the subscriptions.
We add each subscription to the array when we enter the view.
We loop through and unsubscribe from the subscriptions in the array.

These are both valid methods of managing subscriptions and can and should be employed when necessary. There are other options however, that can add a bit more resilience to your management of subscriptions.

Using Operators

RxJS provides us with some operators that will clean up the subscription automatically when a condition is met, meaning we do not need to worry about setting up a variable to track our subscriptions.

Let's take a look at some of these!

`first`

The first operator will take only the first value emitted, or the first value that meets the specified criteria. Then it will complete, meaning we do not have to worry about manually unsubscribing. Let's see how we would use this with our example above:

function onEnterView() {
    obs$.pipe(first())
        .subscribe(data => doSomethingWithDataReceived(data))
}

When obs$ emits a value, first() will pass the value to doSomethingWithDataReceived and then unsubscribe!

`take`

The take operator allows us to specify how many values we want to receive from the Observable before we unsubscribe. This means that when we receive the specified number of values, take will automatically unsubscribe!

function onEnterView() {
    obs$.pipe(take(5))
        .subscribe(data => doSomethingWithDataReceived(data))
}

Once obs$ has emitted five values, take will unsubscribe automatically!

`takeUntil`

The takeUntil operator provides us with an option to continue to receive values from an Observable until a different, notifier Observable emits a new value.

Let's see it in action:


const notifier$ = new Subject();

function onEnterView() {
      obs$.pipe(takeUntil(notifier$)).subscribe(data => doSomethingWithDataReceived(data))
}

function onLeaveView() {
  notifier$.next();
  notifier$.complete();
}

We create a notifier$ Observable using a Subject. (You can learn more about Creating Observables here.)
We use takeUntil to state that we want to receive values until notifier$ emits a value
We tell notifier$ to emit a value and complete _(we need to clean notifer$ up ourselves) when we leave the view, allowing our original subscription to be unsubscribed.

`takeWhile`

Another option is the takeWhile operator. It allows us to continue receiving values whilst a specified condition remains true. Once it becomes false, it will unsubscribe automatically.

function onEnterView() {
      obs$
        .pipe(takeWhile(data => data.finished === false))
        .subscribe(data => doSomethingWithDataReceived(data))
}

In the example above we can see that whilst the property finished on the data emitted is false we will continue to receive values. When it turns to true, takeWhile will unsubscribe!

BONUS: With Angular

RxJS and Angular go hand-in-hand, even if the Angular team has tried to make the framework as agnostic as possible. From this, we usually find ourselves having to manage subscriptions in some manner.

`async` Pipe

Angular itself provides one option for us to manage subscriptions, the async pipe. This pipe will subscribe to an Observable in the template, and when the template is destroyed, it will unsubscribe from the Observable automatically. It's very simple to use:

<div *ngIf="obs$ | async as data">
  {{ data | json }}
</div>

By using the as data, we set the value emitted from the Observable to a template variable called data, allowing us to use it elsewhere in the children nodes to the div node.

When the template is destroyed, Angular will handle the cleanup!

`untilDestroyed`

Another option comes from a third-party library developed by Netanel Basal. It's called until-destroyed, and it provides us with multiple options for cleaning up subscriptions in Angular when Angular destroys a Component.

We can use it similarly to takeUntil:

import { UntilDestroy, untilDestroyed } from '@ngneat/until-destroy';

@UntilDestroy()
@Component({
    selector: 'home'
})
export class HomeComponent implements OnInit {
  ngOnInit() {
    obs$
      .pipe(untilDestroyed(this))
      .subscribe(data => this.doSoemthingWithDataReceived(data));
  }
}

It can also find which properties in your component are Subscription objects and automatically unsubscribe from them:

@UntilDestroy({ checkProperties: true })
@Component({
    selector: 'home'
})
export class HomeComponent {

  subscription = obs$
      .pipe(untilDestroyed(this))
      .subscribe(data => this.doSoemthingWithDataReceived(data));
}

This little library can be beneficial for managing subscriptions for Angular!

When should we employ one of these methods?

The simple answer to this question would be:

When we no longer want to execute code when the Observable emits a new value

But that doesn't give an example use-case.

We have covered one example use case in this article: when you navigate away from a view in your SPA.
In Angular, you'd want to use it when you destroy Components.
Combined with State Management, you could use it only to select a slice of state once that you do not expect to change over the lifecycle of the application.
Generally, you'd want to do it when a condition is met. This condition could be anything from the first click a user makes to when a certain length of time has passed.

Next time you're working with RxJS and subscriptions, think about when you no longer want to receive values from an Observable, and ensure you have code that will allow this to happen!

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)

Colum Ferry
JavaScript Developer and Enthusiast. Really enjoy working with Angular. Married with 2 amazing kids. Powered by Coffee.
@FerryColum @https://github.com/coly010

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

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

AngularJavaScript

NgRx Facade Pattern

NgRx Facade Pattern The NgRx Facade Pattern was first introduced by Thomas Burleson in 2018 and has drawn a lot of attention in recent years. In this article, we will discuss the pattern, how to implement it in Angular and discuss whether or not we _should_ implement it. What is NgRx? First, what is NgRx? NgRx is a state management solution for Angular built on top of RxJS which adheres to the redux pattern. It contains an immutable centralized store where the state of our application gets stored. - We select slices of state from the Store using Selectors, which we can then render in our components. - We dispatch Actions to our Store. - Our Store redirects our Action to our Reducers to recalculate our state and replaces the state within our Store. See the diagram below for an illustrated example: This provides us with a tried and tested pattern for managing the state of our application. What is the Facade Pattern? Now that we know what NgRx is, what is the Facade Pattern? Well, what _are_ Facades? Facades are a pattern that provides a simple public interface to mask more complex usage. As we use NgRx more and more in our application, we add more actions and more selectors that our components must use and track. This increases the coupling between our component and the actions and selectors themselves. The Facade pattern wants to simplify this approach by wrapping the NgRx interactions in one place, allowing the Component to only ever interact with the Facade. This means you are free to refactor the NgRx artefacts without worrying about breaking your Components. In Angular, NgRx Facades are simply services. They inject the NgRx Store allowing you to contain your interactions with the Store in the service. How do we implement it? To begin with, let's show a Component that uses NgRx directly: ` As we can see, this depends a lot on interactions with the Store and has made our component fairly complex and coupled to NgRx. Let's create a Facade that will encapsulate this interaction with NgRx: ` It's essentially everything we had in the component, except now in a service. We then inject this service into our Component: ` By implementing the Facade and using it in our Component, our component no longer depends on NgRx and we do not have to import all actions and selectors. The Facade hides those implementation details, keeping our Component cleaner and easier tested. Pros What are some advantages of using Facades? - It adds a single abstraction of a section of the Store. - This service can be used by any component that needs to interact with this section of the store. For example, if another component needs to access the TodoListState from our example above, they do not have to reimplement the action dispatch or state selector code. It's all readily available in the Facade. - Facades are scalable - As Facades are just services, we can compose them within other Facades allowing us to maintain the encapsulation and hide complex logic that interacts directly with NgRx, leaving us with an API that our developers can consume. Cons - Facades lead to reusing Actions. - Mike Ryan gave a talk at ng-conf 2018 on Good Action Hygiene which promotes creating as many actions as possible that dictate how your user is using your app and allowing NgRx to update the state of the application from your user's interactions. - Facades force actions to be reused. This becomes a problem as we no longer update state based on the user's interactions. Instead, we create a coupling between our actions and various component areas within our application. - Therefore, by changing one action and one accompanying reducer, we could be impacting a significant portion of our application. - We lose indirection - Indirection is when a portion of our app is responsible for certain logic, and the other pieces of our app (the view layer etc.) communicate with it via messages. - In NgRx, this means that our Effects or Reducers do not know what told them to work; they just know they have to. - With Facades, we hide this indirection as only the service knows about how the state is being updated. - Knowledge Cost - It becomes more difficult for junior developers to understand how to interact, update and work with NgRx if their only interactions with the state management solution are through Facades. - It also becomes more difficult for them to write new Actions, Reducers and Selectors as they may not have been exposed to them before. Conclusion Hopefully, this gives you an introduction to NgRx Facades and the pros and cons of using them. This should help you evaluate whether to use them or not....

Feb 9, 2021

4 mins

AngularNgRxJavaScriptTypeScript

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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Best Practices for Managing RxJS Subscriptions

Why do we care about subscription management?

So what do we mean by Subscription Management?

How can we clean up subscriptions?

Unsubscribing Manually

Using Operators

`first`

`take`

`takeUntil`

`takeWhile`

BONUS: With Angular

`async` Pipe

`untilDestroyed`

When should we employ one of these methods?

Colum Ferry

You might also like

Introduction to Zod for Data Validation

Exploring Angular Forms: A New Alternative with Signals

NgRx Facade Pattern

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

Let's innovate together!

You might also like

Introduction to Zod for Data Validation

Exploring Angular Forms: A New Alternative with Signals

NgRx Facade Pattern

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

Why do we care about subscription management?

So what do we mean by Subscription Management?

How can we clean up subscriptions?

Unsubscribing Manually

Using Operators

first

take

takeUntil

takeWhile

BONUS: With Angular

async Pipe

untilDestroyed

When should we employ one of these methods?

Colum Ferry

Introduction to Zod for Data Validation

Exploring Angular Forms: A New Alternative with Signals

NgRx Facade Pattern

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

Let's innovate together!

Introduction to Zod for Data Validation

Exploring Angular Forms: A New Alternative with Signals

NgRx Facade Pattern

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

`first`

`take`

`takeUntil`

`takeWhile`

`async` Pipe

`untilDestroyed`