Javascript

Going Reactive with RxJS

Published Dec 28, 2020

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This article was written over 18 months ago and may contain information that is out of date.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

RxJS is the perfect tool for implementing reactive programming paradigms to your software development. In general, software development handling errors gracefully is a fundamental piece of ensuring the integrity of the application as well as ensuring the best possible user experience.

In this article, we will look at how we handle errors with RxJS and then look at how we can use RxJS to build a simple yet performant application.

Handling Errors

Our general approach to errors usually consists of us exclaiming "Oh no! What went wrong?" but it's something that is a common occurrence in all applications. The ability to manage errors well without disrupting the user's experience, while also providing accurate error logs to allow a full diagnosis of the cause of the error, is more important than ever.

RxJS gives us the tools to do this job very well! Let's take a look at some basic error handling approaches with RxJS.

Basic Error Handling

The most basic way of detecting and reacting to an error that has occurred in an Observable stream provided to us by the .subscribe() method.

obs$.subscribe(
    value => console.log("Received Value: ", value),
    error => console.error("Received Error: ", error)
)

Here we can set up two different pieces of logic—one to handle non-error emission from the Observable and one to gracefully handle errors emitted by the Observable.

We could use this to show a Notification Toast or Alert to inform the user that an error has occurred:

obs$.subscribe(
    value => console.log("Received Value: ", value),
    error => showErrorAlert(error)
)

This can help us minimize disruption for the user, giving them instant feedback that something actually hasn't worked as appropriate rather than leaving them to guess.

Composing Useful Errors

Sometimes, however, we may have situations wherein we want to throw an error ourselves. For example, some data we received isn't quite correct, or maybe some validation checks failed.

RxJS provides us with an operator that allows us to do just that. Let's take an example where we are receiving values from an API, but we encounter missing data that will cause other aspects of the app not to function correctly.

obs$
  .pipe(
    mergeMap((value) =>
      !value.id ? throwError("Data does not have an ID") : of(value)
    )
  )
  .subscribe(
    (value) => console.log(value),
    (error) => console.error("error", error)
  );

If we receive a value from the Observable that doesn't contain an ID, we throw an error that we can handle gracefully.

NOTE: Using the throwError will stop any further Observable emissions from being received.

Advanced Error Handling

We've learned that we can handle errors reactively to prevent too much disruption for the user.

But what if we want to do multiple things when we receive an error or even do a retry?

RxJS makes it super simple for us to retry errored Observables with their retry() operator.

Therefore, to create an even cleaner error handling setup in RxJS, we can set up an error management solution that will receive any errors from the Observable, retry them in the hopes of a successful emission, and, failing that, handle the error gracefully.

obs$
  .pipe(
    mergeMap((value) =>
      !value.id ? throwError("Data does not have an ID") : of(value)
    ),
    retry(2),
    catchError((error) => {
        // Handle error gracefully here
      console.error("Error: ", error);
      return EMPTY;
    })
  )
  .subscribe(
    (value) => console.log(value),
    () => console.log("completed")
  );

Once we reach an error, emitting the EMPTY observable will complete the Observable. The output of an error emission above is:

Error:  Data does not have an ID
completed

Usage in Frontend Development

RxJS can be used anywhere running JavaScript; however, I'd suggest that it's most predominately used in Angular codebases. Using RxJS correctly with Angular can massively increase the performance of your application, and also help you to maintain the Container-Presentational Component Pattern.

Let's see a super simple Todo app in Angular to see how we can use RxJS effectively.

Basic Todo App

We will have two components in this app: the AppComponent and the ToDoComponent. Let's take a look at the ToDoComponent first:

import {
  ChangeDetectionStrategy,
  Component,
  EventEmitter,
  Input,
  Output
} from "@angular/core";

export interface Todo {
  id: number;
  title: string;
}

@Component({
  selector: "todo",
  template: `
    <li>
      {{ item.title }} - <button (click)="delete.emit(item.id)">Delete</button>
    </li>
  `,
  changeDetection: ChangeDetectionStrategy.OnPush
})
export class ToDoComponent {
  @Input() item: Todo;
  @Output() delete = new EventEmitter<number>();
}

Pretty simple, right? It takes an item input and outputs an event when the delete button is clicked. It performs no real logic itself other than rendering the correct HTML.

One thing to note is changeDetection: ChangeDetectionStrategy.OnPush. This tells the Angular Change Detection System that it should only attempt to re-render this component when the Input has changed.

Doing this can increase performance massively in Angular applications and should always be applicable to pure presentational components, as they should only be rendering data.

Now, let's take a look at the AppComponent.

import { Component } from "@angular/core";
import { BehaviorSubject } from "rxjs";
import { Todo } from "./todo.component";

@Component({
  selector: "my-app",
  template: `
    <div>
      <h1>
        ToDo List
      </h1>
      <div style="width: 50%;">
        <ul>
          <todo
            *ngFor="let item of (items$ | async); trackBy: trackById"
            [item]="item"
            (delete)="deleteItem($event)"
          >
          </todo>
        </ul>
        <input #todoTitle placeholder="Add item" /><br />
        <button (click)="addItem(todoTitle.value, todoTitle)">Add</button>
      </div>
    </div>
  `,
  styleUrls: ["./app.component.css"]
})
export class AppComponent {
  private items: Todo[] = [{ id: 1, title: "Learn RxJS" }];
  items$ = new BehaviorSubject<Todo[]>(this.items);

  addItem(title: string, inputEl: HTMLInputElement) {
    const item = {
      id: this.items[this.items.length - 1].id + 1,
      title,
      completed: false
    };
    this.items = [...this.items, item];
    this.items$.next(this.items);

    inputEl.value = "";
  }

  deleteItem(idToRemove: number) {
    this.items = this.items.filter(({ id }) => id !== idToRemove);
    this.items$.next(this.items);
  }

  trackById(index: number, item: Todo) {
    return item.id;
  }
}

This is a container component, and it's called this because it handles the logic relating to updating component state as well as handles or dispatches side effects.

Let's take a look at some areas of interest:

private items: Todo[] = [{ id: 1, title: "Learn RxJS" }];
items$ = new BehaviorSubject<Todo[]>(this.items);

We create a basic local store to store our ToDo items; however, this could be done via a state management system or an API.
We then set up our Observable, which will stream the value of our ToDo list to anyone who subscribes to it.

You may now look over the code and begin to wonder where we have subscribed to items$.

Angular provides a very convenient Pipe that handles this for us. We can see this in the template:

*ngFor="let item of (items$ | async); trackBy: trackById"

In particular, it's the (items$ | async) this will take the latest value emitted from the Observable and provide it to the template. It does much more than this though. It also will manage the subscription for us, meaning when we destroy this container component, it will unsubscribe automatically for us, preventing unexpected outcomes.

Using a pure pipe in Angular also has another performance benefit. It will only ever re-run the code in the Pipe if the input to the pipe changes. In our case, that would mean that item$ would need to change to a whole new Observable for the code in the async pipe to be executed again. We never have to change item$ as our values are then streamed through the Observable.

Conclusion

Hopefully, you have learned both about how to handle errors effectively as well put RxJS into practice into a real-world app that improves the overall performance of your application. You should also start to see the power that using RxJS effectively can bring!

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

Mapping Returned HTTP Data with RxJS

In frontend development, it's likely that you will make API requests to retrieve data from some backend resource. However, some backends are set up in such a way that they either send too much data or not enough data back. When we combine what we know already about Reactive Programming and RxJS, we can handle these situations in a very elegant manner using some useful operators that RxJS provides us. In this article, we will look at handling both scenarios and look at four operators in particular: map, mergeMap, concatMap and switchMap. We will also provide links to some StackBlitz examples so you can see these live. For fun, we'll use the Star Wars API to fetch data and use Angular as our Frontend framework of choice as its HTTP library has Reactive Bindings out of the box. Handling too much data (part 1) Ok, let's set up the scenario. We want to find out some details about Luke Skywalker such as his name, birth year, height, weight, and eye color. With Angular, we can do this by simply making an HTTP request: ` If we do this, we _do_ get back the info we need, but we _also_ get back a lot of info we _don't_ need such as when the API entry was created and edited, Luke's species, his Vehicles etc. Right now, we don't care about those details. Let's see how we could use RxJS's map operator to only return the data we want. ` We can see from the example above that it's super easy to only pull the values you need from the response object! Note You can also see how we managed to map some of the fields in the response from snake_case to camelCase which is more of a convention in JavaScript _as well as_ mapping some fields in the response to a new name (mass -> weight). We can also convert some types to other types, such as mass as string to weight as number. This can be super helpful to keep the domain language of your frontend codebase intact. Live Example You can check this code out in action over at the live example here on StackBlitz. Feel free to fork it and play with it. Handling too much data (part 2) Another common use case of having too much data is search results. Some times we only want to display the first result from a bunch of search results. Let's set up a new scenario. We'll create a typeahead search that only shows the most relevant search result. We want to request search results after every key press the user makes; however, we also don't want to make requests that are not needed. Therefore, we want to cancel any inflight requests created as the user types. For this scenario, we'll be using a mix of the map and switchMap operators. We'll also use Angular's Reactive Forms Module to provide us with some reactive bindings. Our code for this is very simple: ` It's that simple to create an eager typeahead search with Angular and RxJS. You can see the live example of this here on StackBlitz. Handling too little data We've looked at how to handle too much data in the API response with RxJS, but how about when we have too little data? We can build this scenario out perfectly with the Star Wars API. Let's say we want to see what films the characters we are searching for appear in. The API response for the characters _does_ contain what films they are in, but it _does not_ give us details, just a URL that we can send a new request to get that film's data. This is also an Array of films so we _may_ want to get the details for all the films they appear in at this time. Let's see how we can transform our search code to allow us to fetch more data _related_ to the results and map it into the final object that we use to render the data. ` I highly recommend reading the code above and the comments to understand exactly how to achieve this scenario. This pattern is very powerful, especially for example if you need to iterate over an array of user IDs and fetch the user details associated with those IDs. There is also a live example of this here on StackBlitz that you can use to try it out. Conclusion This is a small introduction to mapping data returned from HTTP requests with RxJS, but hopefully you can see use this as a reference point if you ever need to perform complex data mapping that involves additional API requests....

Jan 4, 2021

4 mins

RxJSAngularJavaScript

The HTML Dialog Element: Enhancing Accessibility and Ease of Use

The HTML Dialog Element: Enhancing Accessibility and Ease of Use Dialogs are a common component added to applications, whether on the web or in native applications. Traditionally there has not been a standard way of implementing these on the web, resulting in many ad-hoc implementations that don’t act consistently across different web applications. Often, commonly expected features are missing from dialogs due to the complexity of implementing them. However, web browsers now offer a standard dialog element. Why use the dialog element? The native dialog element streamlines the implementation of dialogs, modals, and other kinds of non-modal dialogs. It does this by implementing many of the features needed by dialogs for you that are already baked into the browser. This is helpful as it reduces the burden on the developer when making their applications accessible by ensuring that user expectations concerning interaction are met, and it can also potentially simplify the implementation of dialogs in general. Basic usage Adding a dialog using the new tag can be achieved with just a few lines of code. ` However, adding the dialog alone won’t do anything to the page. It will show up only once you call the .showModal() method against it. ` Then if you want to close it you can call the .close() method on the dialog, or press the escape key to close it, just like most other modals work. Also, note how a backdrop appears that darkens the rest of the page and prevents you from interacting with it. Neat! Accessibility and focus management Correctly handling focus is important when making your web applications accessible to all users. Typically you have to move the current focus to the active dialog when showing them, but with the dialog element that’s done for you. By default, the focus will be set on the first focusable element in the dialog. You can optionally change which element receives focus first by setting the autofocus attribute on the element you want the focus to start on, as seen in the previous example where that attribute was added to the close element. Using the .showModal() method to open the dialog also implicitly adds the dialog ARIA role to the dialog element. This helps screen readers understand that a modal has appeared and the screen so it can act accordingly. Adding forms to dialogs Forms can also be added to dialogs, and there’s even a special method value for them. If you add a element with the method set to dialog then the form will have some different behaviors that differ from the standard get and post form methods. First off, no external HTTP request will be made with this new method. What will happen instead is that when the form gets submitted, the returnValue property on the form element will be set to the value of the submit button in the form. So given this example form: ` The form element with the example-form id will have its returnValue set to Submit. In addition to that, the dialog will close immediately after the submit event is done being handled, though not before automatic form validation is done. If this fails then the invalid event will be emitted. You may have already noticed one caveat to all of this. You might not want the form to close automatically when the submit handler is done running. If you perform an asynchronous request with an API or server you may want to wait for a response and show any errors that occur before dismissing the dialog. In this case, you can call event.preventDefault() in the submit event listener like so: ` Once your desired response comes back from the server, you can close it manually by using the .close() method on the dialog. Enhancing the backdrop The backdrop behind the dialog is a mostly translucent gray background by default. However, that backdrop is fully customizable using the ::backdrop pseudo-element. With it, you can set a background-color to any value you want, including gradients, images, etc. You may also want to make clicking the backdrop dismiss the modal, as this is a commonly implemented feature of them. By default, the <dialog> element doesn’t do this for us. There are a couple of changes that we can make to the dialog to get this working. First, an event listener is needed so that we know when the user clicks away from the dialog. ` Alone this event listener looks strange. It appears to dismiss the dialog whenever the dialog is clicked, not the backdrop. That’s the opposite of what we want to do. Unfortunately, you cannot listen for a click event on the backdrop as it is considered to be part of the dialog itself. Adding this event listener by itself will effectively make clicking anywhere on the page dismiss the dialog. To correct for this we need to wrap the contents of the dialog content with another element that will effectively mask the dialog and receive the click instead. A simple element can do! ` Even this isn’t perfect though as the contents of the div may have elements with margins in them that will push the div down, resulting in clicks close to the edges of the dialog to dismiss it. This can be resolved by adding a couple of styles the the wrapping div that will make the margin stay contained within the wrapper element. The dialog element itself also has some default padding that will exacerbate this issue. ` The wrapping div can be made into an inline-block element to contain the margin, and by moving the padding from the parent dialog to the wrapper, clicks made in the padded portions of the dialog will now interact with the wrapper element instead ensuring it won’t be dismissed. Conclusion Using the dialog element offers significant advantages for creating dialogs and modals by simplifying implementation with reasonable default behavior, enhancing accessibility for users that need assistive technologies such as screen readers by using automatic ARIA role assignment, tailored support for form elements, and flexible styling options....

Oct 25, 2024

4 mins

HTMLJavaScript

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Going Reactive with RxJS

Handling Errors

Basic Error Handling

Composing Useful Errors

Advanced Error Handling

Usage in Frontend Development

Basic Todo App

Conclusion

Colum Ferry

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