Angular

QR Code Scanning & Generation

Published Dec 13, 2023

Updated Dec 13, 2023

4 min read

QR Code Scanning & Generation with ZXing and Angular

QR codes provide a very valuable way of sharing information with users, and many applications rely on them for various purposes. Common examples of places where QR codes can be useful include but are not limited to theaters, social gatherings and other booking services. Integrating QR codes can seem intimidating, but thankfully they’re not too difficult to handle with Angular and the help of a couple of robust software libraries such as ZXing.

What is ZXing?

ZXing, also known as “Zebra Crossing” is a software library that allows developers to easily integrate scanning many different types of 1D and 2D barcodes. This library was originally written in Java, however many ports to other languages and platforms exist, including JavaScript.

There are a couple of ways to use ZXing. You could either directly use the JavaScript library, which is framework-agnostic, or you could use a framework-specific library. I’m going to demonstrate how to use ZXing to scan QR codes with the Angular version of the library called ngx-scanner specifically, which has a full-fledged scanner component that makes it somewhat easy to integrate.

Let’s Scan some QR Codes with Angular!

Getting ngx-scanner up and running doesn’t take much setup at all. All you have to do is add an import to ZXingScannerModule inside of the module that you will be scanning QR codes in, and add a component to your template. Below shows a real-world example of how the <zxing-scanner> component would be used.

<zxing-scanner
  #scanner
  *ngIf="startCamera$ | async"
  class="scanner"
  [enable]="(enable$ | async) ?? false"
  [autostart]="true"
  [device]="(selectedDevice$ | async) ?? undefined"
  [formats]="allowedFormats"
  (camerasFound)="devices$.next($event)"
  (scanSuccess)="scanSuccess$.next($event)"
  (scanError)="scanError($event)"
></zxing-scanner>

You’ll notice a lot of observables being referenced here. I’ll go over them one by one. Let’s start with the devices subject:

devices$ = new BehaviorSubject<MediaDeviceInfo[]>([]);

This subject has data sent to it whenever cameras have been identified by the scanning component. We want to keep track of these so that we’re able to select a camera to use. In our case we’ll just select the first camera for simplicity's sake, as you can see happens with the selectedDevice$ observable that we have bound to the [device] attribute on the scanner:

selectedDevice$: Observable<MediaDeviceInfo> = this.devices$.pipe(
  map((device) => device[0]),
  distinctUntilChanged(),
  shareReplay(1)
);

We utilize shareReplay here so we don’t need to re-scan the devices whenever additional subscribers check what devices are available.

enable$ is a simple observable that emits true whenever devices have been detected, and startCamera$ is an observable that toggles between true and false whenever data is pushed to the toggleCamera$ subject.

toggleCamera$ = new BehaviorSubject<boolean>(false);

startCamera$ = this.toggleCamera$.pipe(
  scan((acc) => !acc, true),
  startWith(true)
);

The scan function from RxJs is utilized so we have the previous state and can use that to determine in which direction the stored boolean should toggle to.

Finally we push successfully scanned codes to scanSuccess$ which we can then subscribe to in the template.

All together the final component code should look something like this:

@Component({
  selector: 'app-scanner',
  templateUrl: './scanner.component.html',
  styleUrls: ['./scanner.component.scss'],
})
export class ScannerComponent {
  @ViewChild('scanner') scanner!: ZXingScannerComponent;

  allowedFormats = [BarcodeFormat.QR_CODE];

  devices$ = new BehaviorSubject<MediaDeviceInfo[]>([]);

  selectedDevice$: Observable<MediaDeviceInfo> = this.devices$.pipe(
    map((device) => device[0]),
    distinctUntilChanged(),
    shareReplay(1)
  );

  enable$ = this.devices$.pipe(map(Boolean));

  toggleCamera$ = new BehaviorSubject<boolean>(false);

  startCamera$ = this.toggleCamera$.pipe(
    scan((acc) => !acc, true),
    startWith(true)
  );

  scanSuccess$ = new BehaviorSubject<string>('');

  scanError(error: Error) {
    console.error(error);
  }
}

If we use this component then you should get something that looks like this: QR code scanning

Scanning QR codes is awesome, but we can also generate our own QR codes as well!

Generating our own QR Codes

Unfortunately the ZXing scanner component we’re using is limited to just scanning QR codes, however there is another component library called ngx-kjua that can do this. Like ZXing this component is also based off of another pre-existing library that is framework-agnostic, in this case, kjua.

Fortunately kjua is very easy to use. You simply supply it a code and it will render a QR code.

<ngx-kjua
  class="code"
  *ngIf="code$ | async"
  [text]="code$ | async"
  [size]="256"
></ngx-kjua>

How the QR code is rendered can change. There is an optional [render] attribute that you can specify that takes a few values. You can input ‘image’, ‘canvas’ or ‘svg’. The default render mode is ‘svg’. It should be noted that ‘svg’ and ‘canvas’ render modes made copying the image more difficult, so use ‘image’ if you want to make that possible.

The component code associated with this template is very small. The component using ngx-kjua has a code observable that is updated with a new random code whenever a “Generate” button is pressed.

import { Component } from '@angular/core';
import { BehaviorSubject } from 'rxjs';
import randomstring from 'randomstring';

@Component({
  selector: 'app-generator',
  templateUrl: './generator.component.html',
  styleUrls: ['./generator.component.scss'],
})
export class GeneratorComponent {
  code$ = new BehaviorSubject<string>(this.generateCode());

  generateCodeClick(event: MouseEvent) {
    this.code$.next(this.generateCode());
  }

  private generateCode(): string {
    return randomstring.generate({ length: 12, charset: 'alphabetic' });
  }
}

I’ve opted to go with the randomstring package in this case. This component could be modified to instead allow for custom codes using a textbox if you want to encode URLs or other useful values that typically go inside of QR codes.

The result looks like this: QR code scanner result

Summary

Thanks to projects like ZXing and kjua it is easy to integrate handling of QR codes in Angular applications, be it for scanning them or creating them. I hope this guide has helped you. You can find the full example showcasing generation and scanning of QR codes in our blog-demos repository on GitHub.

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About the author(s)

Jamie Kuppens
I’m a software engineer with an interest in web development and some more esoteric things like emulator development.
@Reshurum @Reshurum

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

SSR Finally a First-Class Citizen in Angular?

I am sure you've already heard about server-side rendering (SSR). Generally, it's a technique used to deliver the HTML content generated by the server to the client. The client-side JavaScript framework then hydrates that HTML content to provide a fully interactive application. SSR provides numerous benefits if used correctly, including improved initial load times, better content indexing by search engines, and improved performance on lower-tier devices. Driven by the need for faster, more efficient web applications, with the rise in popularity of Node.js and, thus, server-side JavaScript, SSR has become a de facto standard in modern web development frameworks. At first, SSR was being provided as a part of meta-frameworks like Next.js, Nuxt, or Analog.js. Then, React introduced React Server Components, which marked a significant milestone in the way we think about front-end development. We think of front-end frameworks as being effectively full-stack, and a purely SPA approach is falling out of favor. However, I'm willing to bet that if you're a developer focused mostly on Angular, you may not have heard as much about SSR as your React counterparts. For a long time, Angular has been mostly focused on the SPA approach, and while we had Angular Universal or Analog.js, it was not as widely adopted. And that makes sense, given that Angular was widely regarded as best suited for complex, interactive applications, such as SaaS products or internal company tools, where SEO and initial load times were not as critical as they are for consumer-facing applications. Nevertheless, we have been blessed with the so-called Angular Renaissance, which has, among other things, brought SSR to the forefront of Angular development with the @angular/ssr package. Let's look at what Angular SSR is, how it works, and how you can get started. @angular/ssr The @angular/ssr package is not new; it was written from scratch. It's still Angular Universal. However, it's been pulled into the Angular CLI repository, and the appropriate schematics have been added to make it easier to use. What that means is that you can now add SSR to your Angular application with a single command: ` and you can generate a new SSR application with: ` And to make SSR a first-class citizen, the Angular team is planning to make it the default in the next version. But surely, it's not only rebranding and some CLI commands, you may say. And you're right. You may remember that hydration in Angular Universal has not been optimal as it was destructive and required essentially a complete re-render of the application, thus pretty much negating the benefits of SSR. With the introduction of non-destructive hydration in Angular 16 and its stability in Angular 17, the Angular team has taken a significant step forward in making SSR a first-class citizen. How to Make an SSR-capable Angular Application Let's look at how to use Angular SSR in practice by creating a simple SSR app. First, we need to create a new Angular application with SSR support: ` That will generate a few server-specific files: - server.ts, which is an Express server configured to handle Angular SSR requests by default but can also be extended to handle API routes, or anything else that Express can handle. - src/app/app.config.server.ts provides configuration for the server application similar to your app.config.ts, which defines the configuration for your client application. Both export an instance of ApplicationConfig - src/main.server.ts bootstraps the server application in a similar way to what main.ts does for your client app by calling the bootstrapApplication function. You should have an SSR application ready just like that. You can verify that by running ng serve. The terminal output should show you information about the server bundles generated, and you should be able to see the default app when going to http://localhost:4200. Open the Developer Tools and check the console to see that hydration is enabled. You'll see a message with hydration-related stats, such as the number of components and nodes hydrated. Speaking of hydration... Client Hydration If you open the src/app/app.config.ts in your new SSR application, you'll notice one interesting provider: provideClientHydration(). This provider is crucial for enabling hydration - a process that restores the server-side rendered application on the client. Hydration improves application performance by avoiding extra work to re-create DOM nodes. Angular tries to match existing DOM elements to the application's structure at runtime and reuses DOM nodes when possible. This results in a performance improvement measured using Core Web Vitals statistics, such as reducing the Interaction To Next Paint (INP), Largest Contentful Paint (LCP), and Cumulative Layout Shift (CLS). Improving these metrics also positively impacts SEO performance. Without hydration enabled, server-side rendered Angular applications will destroy and re-render the application's DOM, which may result in visible UI flicker, negatively impact Core Web Vitals like LCP, and cause layout shifts. Enabling hydration allows the existing DOM to be reused and prevents flickering. Event Replay and Improved Debugging With Angular 18, event replay, a feature that significantly enhances the SSR experience, came into developer preview. Event replay captures user interactions during the SSR phase and replays them once the application is hydrated. This ensures that user actions, such as adding items to a cart, are not lost during the hydration process, providing a seamless user experience even on slow networks. To enable event replay, you can add withEventReplay to your provideClientHydration call: ` Furthermore, Angular 18 takes another step towards making SSR a first-class citizen by enhancing the debugging experience with Angular DevTools. Now, DevTools include overlays and detailed error breakdowns, empowering developers to visualize and troubleshoot hydration issues directly in the browser. Constraints However, hydration imposes a few constraints on your application that are not present without hydration enabled. Your application must have the same generated DOM structure on both the server and the client. The hydration process expects the DOM tree to have the same structure in both environments, including whitespaces and comment nodes produced during server-side rendering. Direct DOM Manipulation The fact that server and client DOM structures must match means that components that manipulate the DOM using native DOM APIs or use innerHTML or outerHTML will encounter hydration errors. The errors are thrown because Angular is unaware of these changes and cannot resolve them during hydration. Examples include accessing the document, querying for specific elements, and injecting additional nodes using appendChild. Detaching DOM nodes and moving them to other locations will also cause errors. Direct DOM manipulation is generally considered bad practice in Angular, so I recommend refactoring your components to avoid it regardless of hydration. However, in warranted cases where refactoring is not feasible, you can use the ngSkipHydration attribute until a hydration-friendly solution can be implemented. You can use it directly in a template: ` or as a host binding: ` > Note: The ngSkipHydration attribute forces Angular to skip hydrating the entire component and its children. So use this attribute carefully, as, for example, applying it to your root application component would effectively disable hydration for the entire application. Valid HTML Structure Another constraint is that invalid HTML structures in component templates can result in DOM mismatch errors during hydration. Common issues include: - without a - inside a - inside an - inside another Again, if you have an invalid HTML, you should fix this regardless of hydration. If you are unsure about your HTML's validity, you can use the W3 validator to check it. Zoneless apps or custom Zone.js Hydration relies on a signal from Zone.js when it becomes stable. Custom or "noop" Zone.js implementations may thus disrupt the timing of this event, triggering the serialization or cleanup process too early or too late. This configuration is not yet fully supported. While Zoneless is already available in developer preview and we could assume this issue will be resolved when it lands as stable, there is no explicit ETA mentioned in the official roadmap. I18n One of the biggest blockers for adoption of client hydration was the lack of support for internationalization with hydration. By default, Angular 17 skipped hydration for components that used i18n blocks, re-rendering them from scratch. In Angular 18, however, hydration for i18n blocks got into developer preview. To enable hydration for i18n blocks, you can add withI18nSupport to your provideClientHydration call. ` Third-Party Libraries with DOM Manipulation The last thing to consider is third-party libraries that manipulate DOM, such as D3 charts. They could cause DOM mismatch errors when hydration is enabled. You can use the ngSkipHydration attribute to skip hydration for components rendered using these libraries. Conclusion The Angular team has been doing great work to make the framework more modern and competitive, hearing the community feedback and adjusting the roadmap accordingly. And SSR is an excellent example of that. With the introduction of non-destructive hydration in Angular 16 and making it stable in Angular 17, the Angular team has taken a significant step forward in making SSR a first-class citizen in Angular. The @angular/ssr package is now part of the Angular CLI, making adding SSR to your Angular application easier. The Angular team plans to make SSR the default in the next version, further solidifying its position in the Angular ecosystem. However, as with any new feature, there are some constraints and best practices to follow when using SSR with Angular. You should be aware of hydration's limitations and ensure your application is compatible with it. However, if you follow the guidelines provided by the Angular team, you should be able to take advantage of the benefits of SSR without any significant issues....

Jun 26, 2024

8 mins

AngularJavaScriptExpress.js

How to Implement Soft Delete with Prisma using Partial Indexes

Most APIs and applications that allow you to manage content have some form of deletion functionality. Sometimes you may want to make something recoverable after it’s been deleted, or perform the actual deletion later, and soft deletion is a way to accomplish this. Entities in your database may also have unique identifiers such as slugs associated with them as well, and when you delete things you typically expect these identifiers to become available for use again. In the case of soft deletes though your deleted entities will still be in the database! If you’re using Postgres or SQLite you can get the best of both worlds by using partial unique indexes, which will in the case of soft deletes would only add slugs on undeleted records to the index; however if you’re connecting a partial index compatible database with Prisma then everything isn’t rainbows and sunshine when it comes to partial indexes. A Simple Soft Delete Implementation Before getting into the issue with partial unique indexes, let’s implement soft delete in Prisma using middleware. The following example is adapted from the Prisma documentation regarding soft deletes, though with some slight alterations for convenience. ` The notable change here is this version could be extended to work with multiple models fairly easily by modifying the MODELS_SUPPORTING_SOFT_DELETE constant, and we also handle the throwable variants of the find actions as well. The latter change requires we create a custom type named ExpandedPrismaAction with additional actions as the imported Prisma types don’t have these actions for some reason even though they are encountered in actual usage. Anything specified in the model's constant is assumed to have a field named deletedAt that is nullable. In this example specifically it’s a timestamp field since it’s nice to know when something has been deleted, but it could also be a boolean if you so choose. With that done, soft deletion is transparently implemented, at least insofar as select queries go. If you plan on blindly running update and delete queries as well, then you will need to add middleware for those actions as well. The Problem So as stated before we plan on using unique slugs with our model, in this case slugs for posts, and to free slugs for usage later we need to exclude them from the unique index without deleting the post records outright. Unfortunately, at the time of writing this article Prisma doesn’t allow you to define partial indexes in your schema when defining unique indexes using @@unique inside of your schema. Thankfully, there is a way to workaround this issue. The Solution To workaround this issue you can manage your unique indexes outside of the Prisma schema, though it does come with its own pitfalls that I will cover later. This can be done by creating partial indexes in a migration file instead of defining them in the schema file. It should be mentioned that if you do this then you should ensure a conflicting index is not defined in the schema, or else Prisma will try to overwrite the other index. First let’s create a basic schema with the following contents defining posts: ` In the above schema I’ve left a comment that mentions where a partial unique index definition would go if it was supported. The problem with keeping the definition solely in the migration is that it makes it difficult to discover, and also doesn’t explain the reason why it’s there. Now that we have a Post model with a deletedAt column, create an empty migration and do the following: ` Then the contents of the newly created migration file will be as follows: ` With that all initialized and the middleware setup, and router handler defined, everything should work! Check out the full example on GitHub as I don’t show the full implementation of the example API in this article. The route handlers don’t look any different than you would expect as the middleware handles all of the heavy lifting for us. It is worth noting that DELETE handlers do look different with soft-delete as we’re not intercepting delete calls to Prisma. This is how the implementation of the deletion looks for this example: ` Caveats So there are some caveats to implementing partial delete in this way. The first being that the schema doesn’t reflect the state of the database 1:1. Thankfully, Prisma doesn’t care about untracked indexes existing, but knowing the index exists requires looking in the migration files instead of the schema. This is worked around by leaving a comment, but it still isn’t great. Another downside is that upsert calls do not work with the Prisma client. Making upserts with Prisma requires a unique key, but since Prisma doesn’t track this unique key the typings needed to call upsert do not exist. This can be worked around by making raw queries without the query builder. Summary I hope this article has helped you ease the integration of soft deletes into your application. You can find a full example on → GitHub ← that includes all of the above code snippets, a buildable project, and instructions on how to get it all working....

Feb 2, 2024

4 mins

Prisma

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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QR Code Scanning & Generation

QR Code Scanning & Generation with ZXing and Angular

What is ZXing?

Let’s Scan some QR Codes with Angular!

Generating our own QR Codes

Summary

Jamie Kuppens

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