Angular

Getting Started with Custom Structural Directives in Angular

Published Nov 22, 2021

Updated Feb 13, 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This article was written over 18 months ago and may contain information that is out of date.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.

Introduction

Angular comes with many built-in directives. Some of them (eg. NgIf, NgModel or FormControlDirective) are used daily by Angular developers. Those directives can be split into 2 categories:

Attribute directives

They can be used to modify the appearance of behavior of Angular components and DOM elements. For example:
Structural directives

They can be used to manipulate the HTML structure in the DOM. Using them, we can change the structure of part of the DOM that they control. For example:
- NgIf
- NgForOf
- NgSwitch

In this article, I will focus on the latter.

Creating a custom structural directive

As I've mentioned above, there are a couple of built-in structural directives in Angular. However, we might come across a case that the ones provided with the framework don't solve. This is where a custom structural directive might help us resolve the issue. But how do we write one?

All the code examples in this article use the Angular CLI or Nx CLI generated project as a starting point. You can generate a project using the following command, or use Stackblitz starter project.

npx create-nx-workspace --preset=angular --prefix=csd --appName=custom-structural-directive

# or
# ng new custom-structural-directive --prefix=csd

NgIf directive clone

Let's learn the basic concepts by reimplementing the basic features of the NgIf directive. We will call it CsdIf (CSR prefix stands for Custom Structural Directive :))

The structural directive is actually just a regular directive (with some additional syntactic sugars provided by Angular). So we can start with creating a module and empty directive using AngularCLI:

ng generate module if
ng generate directive if/if --module if

# or shorthand
# ng g m if
# ng g d if/if --module if

our new directive should look like this:

import { Directive } from '@angular/core';

@Directive({
  selector: '[csdIf]',
})
export class IfDirective {
  constructor() {}
}

Let's implement the basic functionality of displaying the content if passed value is true.

<h2 *csdIf="true">My visible conditional header</h2>
<h2 *csdIf="false">My hidden conditional header</h2>

To achieve that, we need a couple of elements:

an input that will determine whether to show or hide the content (@Input)
a reference to the template that we want to conditionally display (TemplateRef)
a container that will provide us with access to Angular's view (ViewContainerRef)

The input can be just a regular class property with Angular's @Input decorator. The important thing is to use a proper naming convention. For it to work as it does in the example code shown above, we need to name the property the same as the attribute's selector:

import { Directive, Input } from '@angular/core';

@Directive({
  selector: '[csdIf]',
})
export class IfDirective {
  @Input() csdIf: boolean = false;

  constructor() {}
}

Now our directive has the information whether to display the content or not but we need to also gain access to the TemplateRef and ViewContainerRef instances. We can do that by injecting them via a constructor:

import { Directive, Input, TemplateRef, ViewContainerRef } from '@angular/core';

@Directive({
  selector: '[csdIf]',
})
export class IfDirective {
  @Input() csdIf: boolean = false;

  constructor(
    private templateRef: TemplateRef<unknown>,
    private vcr: ViewContainerRef
  ) {}
}

Now we have all the necessary tools and information to display or hide the content. We can use ViewContainerRef's createEmbeddedView method to display and clear method to remove the content. Important note: To make sure the csdIf property is assigned already, we need to use ngOnInit lifecycle hook.

import {
  Directive,
  Input,
  OnInit,
  TemplateRef,
  ViewContainerRef,
} from '@angular/core';

@Directive({
  selector: '[csdIf]',
})
export class IfDirective implements OnInit {
  @Input() csdIf: boolean = false;

  constructor(
    private templateRef: TemplateRef<unknown>,
    private vcr: ViewContainerRef
  ) {}

  ngOnInit(): void {
    if (this.csdIf) {
      this.vcr.createEmbeddedView(this.templateRef);
    } else {
      this.vcr.clear();
    }
  }
}

With this implementation, the following example already works as expected.

<h2 *csdIf="true">My visible conditional header</h2>
<h2 *csdIf="false">My hidden conditional header</h2>

There is still a problem with this implementation. Let's try to use the following example:

<input id="showInput" type="checkbox" [(ngModel)]="showInput" />
<label for="showInput">Show conditional header</label>
<h2 *csdIf="showInput">My conditional header</h2>

The "My conditional header" is displayed correctly when the page renders but as soon as we uncheck the showInput, our header doesn't disappear as we would expect. This is because we only check the csdIf input value inside of ngOnInit, but we do not react to the input's changes. To resolve this, we can either use ngOnChanges lifecycle hook or modify the csdIf to be a setter rather than just a property. I will show you the later solution but implementing it using ngOnChanges should be very similar.

As a first step, let's modify the csdIf to be a setter, and store its value in a private property show.

@Directive({
  selector: '[csdIf]',
})
export class IfDirective implements OnInit {
  private show = false;
  @Input() set csdIf(show: boolean) {
    this.show = show;
  }

  /* constructor */

  ngOnInit(): void {
    if (this.show) {
      this.vcr.createEmbeddedView(this.templateRef);
    } else {
      this.vcr.clear();
    }
  }
}

Secondly, when the new csdIf value is set, we need to perform the same logic as we do in ngOnInit. We need to make sure though that we don't render the template twice so we can clear the view first in all cases.

@Directive({
  selector: '[csdIf]',
})
export class IfDirective implements OnInit {
  private show = false;
  @Input() set csdIf(show: boolean) {
    this.show = show;
    this.vcr.clear();
    if (this.show) {
      this.vcr.createEmbeddedView(this.templateRef);
    }
  }

  /* constructor */

  ngOnInit(): void {
    this.vcr.clear();
    if (this.show) {
      this.vcr.createEmbeddedView(this.templateRef);
    }
  }
}

As a final step, let's refactor to remove the code duplication by extracting the common logic into a method.

@Directive({
  selector: '[csdIf]',
})
export class IfDirective implements OnInit {
  private show = false;
  @Input() set csdIf(show: boolean) {
    this.show = show;
    this.displayTemplate();
  }

  /* constructor */

  ngOnInit(): void {
    this.displayTemplate();
  }

  private displayTemplate() {
    this.vcr.clear();
    if (this.show) {
      this.vcr.createEmbeddedView(this.templateRef);
    }
  }
}

Now, our second example works as expected:

<input id="showInput" type="checkbox" [(ngModel)]="showInput" />
<label for="showInput">Show conditional header</label>
<h2 *csdIf="showInput">My conditional header</h2>

Handling additional parameters - else template

The CsdIf directive shows and hides the content based on the boolean input correctly. But the original NgIf directive allows for specifying an alternative template via the "else" property as well. How do we achieve this behavior in our custom directive? This is where understanding the "syntactic sugar" that stands behind the structural directives is crucial. The following NgIf syntax:

<h2 *ngIf="show; else alternativeTemplate">My conditional header</h2>
<ng-template #alternativeTemplate>
  <h2>My alternative header</h2>
</ng-template>

is actually equivalent to the following syntax:

<ng-template [ngIf]="show" [ngIfElse]="alternativeTemplate">
  <h2>My conditional header</h2>
</ng-template>
<ng-template #alternativeTemplate>
  <h2>My alternative header</h2>
</ng-template>

This means that the else property is actually becoming ngIfElse input parameter. In general, we can construct the property name by concatenating the attribute following * and the capitalized property name (eg. "ngIf" + "Else" = "ngIfElse""). In case of our custom directive it will become "csdIf" + "Else" = "csdIfElse

<h2 *csdIf="show; else alternativeTemplate">My conditional header</h2>
<ng-template #alternativeTemplate>
  <h2>My alternative header</h2>
</ng-template>

is equivalent to

<ng-template [csdIf]="show" [csdIfElse]="alternativeTemplate">
  <h2>My conditional header</h2>
</ng-template>
<ng-template #alternativeTemplate>
  <h2>My alternative header</h2>
</ng-template>

By analyzing the "unwrapped" syntax we can notice the the reference to an alternative template is passed via the csdIfElse property. Let's add and handle that property in the custom directive implementation:

@Directive({
  selector: '[csdIf]',
})
export class IfDirective implements OnInit {
  private show = false;

  @Input() set csdIf(show: boolean) {
    this.show = show;
    this.displayTemplate();
  }

  @Input() csdIfElse?: TemplateRef<unknown>;

  /* constructor */

  ngOnInit(): void {
    this.displayTemplate();
  }

  private displayTemplate() {
    this.vcr.clear();
    if (this.show) {
      this.vcr.createEmbeddedView(this.templateRef);
    } else if (this.csdIfElse) {
      this.vcr.createEmbeddedView(this.csdIfElse);
    }
  }
}

This addition makes our directive much more useful, and allows for displaying content for cases when the condition is true or false.

If something is not clear, or you want to play with the example directive please visit the example on Stackblitz.

Real life example

The above example is very simple, but it gives you tools to create your own custom directive when you need it. If you want to have a look at some real-life custom directive example that we've found useful at This Dot Labs, I suggest checking out our route-config open source library. You can read more about it in one of our articles:

Summary

In this article, we've learnt how to write a simple custom structural directive that handles additional inputs. We've covered the syntactic sugar that stands behind the structural directive, and how it translates into directive's inputs. In the second part, I will show you how to add some additional functionalities to the custom structural directive and present ways to improve type checking experience for the custom directive's templates.

In case you have any questions, you can always tweet or DM me at @ktrz. I'm always happy to help!

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

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

About the author(s)

Chris Trześniewski
Software Engineer, ultra-marathoner. He is passionate about functional programming in JavaScript and loves working with RxJS. In his free time he likes to go jogging.
@ktrz__@ktrz

End-to-end type-safety with JSON Schema

End-to-end type-safety with JSON Schema I recently wrote an introduction to JSON Schema post. If you’re unfamiliar with it, check out the post, but TLDR: It’s a schema specification that can be used to define the input and output data for your JSON API. In my post, I highlight many fantastic benefits you can reap from defining schemas for your JSON API. One of the more interesting things you can achieve with your schemas is end-to-end type safety from your backend API to your client application(s). In this post, we will explore how this can be accomplished slightly deeper. Overview The basic idea of what we want to achieve is: * a JSON API server that validates input and output data using JSON Schema * The JSON Schema definitions that our API uses transformed into TypeScript types With those pieces in place, we can achieve type safety on our API server and the consuming client application. The server side is pretty straightforward if you’re using a server like Fastify with already enabled JSON Schema support. This post will focus on the concepts more than the actual implementation details though. Here’s a simple diagram illustrating the high-level concept: We can share the schema and type declaration between the client and server. In that case, we can make a request to an endpoint where we know its type and schema, and assuming the server validates the data against the schema before sending it back to the client, our client can be confident about the type of the response data. Marrying JSON Schema and TypeScript There are a couple of different ways to accomplish this: * Generating types from schema definitions using code generation tools * Creating TypeBox definitions that can infer TypeScript types and be compiled to JSON Schema I recommend considering both and figuring out which would better fit your application and workflows. Like anything else, each has its own set of trade-offs. In my experience, I’ve found TypeBox to be the most compelling if you want to go deep with this pattern. Code generation A couple of different packages are available for generating TS types from JSON Schema definitions. * https://github.com/bcherny/json-schema-to-typescript * https://github.com/vega/ts-json-schema-generator They are CLI tools that you can provide a glob path to where your schema files are located and will generate TS declaration files to a specified output path. You can set up an npm hook or a similar type of script that will generate types for your development environment. TypeBox TypeBox is a JSON Schema type builder. With this approach, instead of json files, we define schemas in code using the TypeBox API. The TypeBox definitions infer to TypeScript types directly, which eliminates the code generation step described above. Here’s a simple example from the documentation of a JSON Schema definition declared with TypeBox: ` This can then be inferred as a TypeScript type: ` Aside from schemas and types, TypeBox can do a lot more to help us on our type-safety journey. We will explore it a bit more in upcoming sections. Sharing schemas between client and server applications Sharing our JSON Schema between our server and client app is the main requirement for end-to-end type-safety. There are a couple of different ways to accomplish this, but the simplest would be to set up our codebase as a monorepo that contains both the server and client app. Some popular options for TypeScript monorepos are: PNPM, Turborepo, and NX. If a monorepo is not an option, you can publish your schema and types as a package that can be installed in both projects. However, this setup would require a lot more maintenance work. Ultimately, as long as you can import your schemas and types from the client and server app, you are in good shape. Server-to-client validation and type-safety For the sake of simplicity, let's focus on data flowing from the server to the client for now. Generally speaking, the concepts also apply in reverse, as long as your JSON API server validates your inputs and outputs. We’ll look at the most basic version of having strongly typed data on the client from a request to our server. Type-safe client requests In our server application, if we validate the /users endpoint with a shared schema - on the client side, when we make the request to the endpoint, we know that the response data is validated using the user schema. As long as we are confident of this fact, we can use the generated type from that schema as the return type on our client fetch call. Here’s some pseudocode: ` Our server endpoint would look something like this: ` You could get creative and build out a map that defines all of your endpoints, their metadata, and schemas, and use the map to define your server endpoints and create an API client. Transforming data over the wire Everything looks stellar, but we can still take our efforts a bit further. To this point, we are still limited to serialized JSON data. If we have a created_at field (number or ISO string) tied to our user, and we want it to be a Date object when we get a hold of it on the client side - additional work and consideration are required. There are some different strategies out there for deserializing JSON data. The great thing about having shared schemas between our client and server is that we can encode our type information in the schema without sending additional metadata from our server to the client. Using format to declare type data In my initial JSON Schema blog post, I touched on the format field of the specification. In our schema, if the actual type of our date is a string in ISO8601 format, we can declare our format to be "date-time". We can use this information on the client to transform the field into a proper Date object. ` Transforming serialized JSON Data This can be a little bit tricky; again, there are many ways to accomplish it. To demonstrate the concept, we’ll use TypeBox to define our schemas as discussed above. TypeBox provides a Transform type that you can use to declare, encode, and decode methods for your schema definition. ` It even provides helpers to statically generate the decoded and encoded types for your schema ` If you declare your decode and encode functions for your schemas, you can then use the TypeBox API to handle decoding the serialized values returned from your JSON API. Here’s what the concept looks like in practice fetching a user from our API: ` Nice. You could use a validation library like Zod to achieve a similar result but here we aren’t actually doing any validation on our client side. That happened on the server. We just know the types based on the schema since both ends share them. On the client, we are just transforming our serialized JSON into what we want it to be in our client application. Summary There are a lot of pieces in play to accomplish end-to-end type safety. With the help of JSON Schema and TypeBox though, it feels like light work for a semi-roll-your-own type of solution. Another great thing about it is that it’s flexible and based on pretty core concepts like a JSON API paired with a TypeScript-based client application. The number of benefits that you can reap from defining JSON Schemas for your APIs is really great. If you’re like me and wanna keep it simple by avoiding GraphQL or other similar tools, this is a great approach....

Apr 17, 2024

6 mins

JSONTypeScript

Angular 18 Announced: Zoneless Change Detection and More

Angular 18 Announced: Zoneless Change Detection and More Angular 18 has officially landed, and yet again, the Angular team has proven that they are listening to the community and are committed to continuing the framework's renaissance. The release polishes existing features, addresses common developer requests, and introduces experimental zoneless change detection. Let's examine the major updates and enhancements that Angular 18 offers. 1. Zoneless Angular One of the most exciting features of Angular 18 is the introduction of experimental support for zoneless change detection. Historically, Zone.js has been responsible for triggering Angular's change detection. However, this approach has downsides, especially regarding performance and debugging complexity. The Angular team has been working towards making Zone.js optional, and Angular 18 marks a significant milestone in this journey. Key Features of Zoneless Angular 1. Hybrid Change Detection: In Angular 18, a new hybrid change detection mode is enabled by default. This mode allows Angular to listen to changes from signals and other notifications regarding changes that occur either inside an Angular zone or not. That effectively means you can write (library) code that works regardless of whether Zone.js is being used, paving the way to fully zoneless apps without compromising backward compatibility. For new applications, Angular enables zone coalescing by default, which removes the number of change detection cycles and improves performance. For existing applications, you can enable zone coalescing by configuring your NgZone provider in bootstrapApplication: ` 2. Experimental API for Zoneless Mode: Angular 18 introduces an experimental API to disable Zone.js entirely. This API allows developers to run applications in a fully zoneless mode, paving the way for improved performance and simpler debugging. The zoneless change detection requires an entirely new scheduler which relies on notifications from the Angular core APIs, such as ChangeDetectorRef.markForCheck (called automatically by the AsyncPipe), ComponentRef.setInput, signal updates, host listener updates, or attaching a view that was marked dirty. 3. Improved Composability and Interoperability: Zoneless change detection enhances composability for micro-frontends and interoperability with other frameworks. It also offers faster initial render and runtime, smaller bundle sizes, more readable stack traces, and simpler debugging. How to Try Zoneless Angular To experiment with zoneless change detection, you can add the provideExperimentalZonelessChangeDetection provider to your application bootstrap: ` After adding the provider, remove Zone.js from your polyfills in angular.json. You can read more about the experimental zoneless change detection in the official documentation. By the way, angular.dev is now considered the official home for Angular developers! 2. Server-side Rendering and Hydration Enhancements A feature I'm particularly excited about is the improvements to Angular's server-side rendering (SSR) and hydration in terms of developer experience and debugging: 1. Enhanced DevTools Support: Angular DevTools now includes overlays and detailed error breakdowns to help visualize and debug hydration issues directly in the browser. This refreshing focus on developer experience shows that the Angular team wants to make the framework more approachable and user-friendly. 2. Hydration Support for Angular Material: All Angular Material components now support client hydration and are no longer skipped, which enhances performance and user experience. 3. Event Replay: Available in developer preview, event replay captures user interactions during SSR and replays them once the application is hydrated, ensuring a seamless user experience before complete hydration. It is powered by the same library as Google Search. 4. i18n Hydration Support: Up to v17, Angular skipped hydration for components with i18n blocks. From v18, hydration support for i18n blocks is in developer preview, allowing developers to use client hydration in internationalized applications. 3. Stable Material Design 3 After introducing experimental support for Material Design 3 in Angular 17, Angular 18 now includes stable support. The key features of Material Design 3 in Angular 18 include: 1. Simplified Theme Styles: Based on CSS variables, the new theming styles offer more granular customization and a flexible API for applying color variants to components. 2. Theming Generation Schematics: Using the Ng CLI, you can generate Material 3 themes. 3. Sass APIs: New Sass APIs allow developers to read colors, typography, and other properties from the Material 3 theme, making it easier to create custom components. How to use Material Design 3 in Angular 18 To use Material Design 3 in Angular 18, you can define a theme in your application's styles.scss file using the mat.defineTheme function: ` Or generate a Material 3 theme using the Ng CLI: ` You can then apply the theme to your application using the mat.theme mixin: ` Head to the official guide for a more detailed guide. You'll also notice they have refreshed the docs with the new themes and further documentation. 4. Signal-Based APIs The path to fully signal-based components includes new signal inputs, model inputs, and signal query APIs. We already wrote about them as they were in developer-preview in v17, but they have been further refined in v18. These APIs offer a type-safe, reactive way to manage state changes and interactions within components: 1. Signal Input API: Signal inputs allow values to be bound from parent to child components. Those values are exposed using a signal and can change during the component's life cycle. 2. Model Input API: Model inputs are a special input type that enables a component to propagate new values back to the parent component. That allows developers to keep the parent component in sync with the child component with two-way binding. 3. Signal Query API: This was a particularly requested feature from the community. The signal query APIs work the same way as ViewChild and ContentChild under the hood, but they return signals, providing more predictable timing and type safety. 5. Fallback Content For ng-content A very requested feature from the community, Angular 18 introduces a new ng-content directive that allows developers to define fallback content when no content is projected into a component. This feature is particularly useful for creating reusable components with default content. Here's an example of using the new ng-content directive. Using the following component ` like this ` will render Howdy World. 6. Other Improvements In addition to the major updates mentioned above, Angular 18 also includes several other improvements and updates: 1. TypeScript 5.4: Angular 18 now supports TypeScript 5.4, which lets you take advantage of new features such as preserved narrowing in closures following last assignments. 2. Global Observable in Angular Forms: Angular 18 introduces a global events observable in Angular forms, which allows you to track all changes around any abstract control and its children, including the touched or dirty in a single observable. Here's an example of how you can use the global observable: ` 3. Stable Deferrable views: Deferrable views are now stable in Angular 18. 4. Stable Control Flow: The built-in control flow is now stable in Angular 18! It is more performant than its predecessor. It also received improved type checking, including guardrails for certain performance-related anti-patterns. 5. Route Redirects as Functions: For added flexibility in managing redirects, Angular v18 now lets you use a function for redirectTo that returns a string, which allows you to create more sophisticated redirection logic based on runtime conditions. For example: ` Conclusion Angular 18 is a significant release that brings many new features, enhancements, and experimental APIs to the Angular ecosystem. The introduction of zoneless change detection, improvements to server-side rendering and hydration, stable Material Design 3 support, signal-based APIs, and fallback content for ng-content are just a few of the highlights of this release. The Angular team has again demonstrated its commitment to improving the framework's developer experience, performance, and flexibility. It also demonstrated a clear vision for Angular's future. If you're curious about what's next, you can check out the Angular roadmap....

May 29, 2024

3 mins

AngularJavaScript

Introduction to Directives Composition API in Angular

In version 15, Angular introduced a new directives composition API that allows developers to compose existing directives into new more complex directives or components. This allows us to encapsulate behaviors into smaller directives and reuse them across the application more easily. In this article, we will explore the new API, and see how we can use it in our own components. All the examples from this article (and more) can be found on Stackblitz here. Starting point In the article, I will use two simple directives as an example * HighlightDirective - a directive borrowed from Angular's Getting started guide. This directive will change an element's background color whenever the element hovers. ` Fig. 1 * BorderDirective - a similar directive that will apply a border of a specified color to the element whenever it hovers ` Fig. 2 We can now easily apply our directives to any element we want ie. a paragraph: ` Fig. 3 However, if we wanted to apply both highlighting and border on hover we would need to add both directives explicitly: ` Fig. 4 With the new directives composition API, we can easily create another directive that composes behaviors of our 2 directives. Host Directives Angular 15 added a new property to the @Directive and @Component decorators. In this property, we can specify an array of different directives that we want our new component or directive to apply on a host element. We can do it as follows: ` As you can see in the above example, by just defining the hostDirectives property containing our highlight and border directives, we created a new directive that composes both behaviors into one directive. We can now achieve the same result as in Fig. 4 by using just a single directive: ` Fig. 5 Passing inputs and outputs Our newly composed directive works nicely already, but there is a problem. How do we pass properties to the directives that are defined in the hostDirectives array? They are not passed by default, but we can configure them to do so pretty easily by using an extended syntax: ` Fig. 6 This syntax takes exposes the "inner" directives\ color input from the HighlightAndBorderDirective`, and passes them down to both highlight and border directives. ` Fig. 7 This works, but we ended up with a border and highlight color both being blue. Luckily Angular's API allows us to easily redefine the properties' names using the : syntax. So let's remap out properties to highlightColor and borderColor so that the names don't collide with each other: ` Fig. 8 Now we can control both colors individually: ` Fig. 9 We could apply the same approach to mapping directive's outputs eg. ` Fig. 10 or ` Fig. 11 Adding host directives to a component Similarly to composing a directive out of other directives, we can apply the same approach to adding behavior to components using hostDirectives API. This way, we could, for example, create a more specialized component or just apply the behavior of the directive to a whole host element: ` Fig. 12 This component will render the paragraph, and apply both directives' behavior to the host element: ` Fig. 13 Just like we did for the directive, we can also expose and remap the directives inputs using the extended syntax. But if we would like to access and modify the directives inputs from within our component, we can also do that. This is where Angular's dependency injection comes in handy. We can inject the host directives via a constructor just like we would do for a service. After we have the directives instances available, we can modify them ie. in the ngOnInit lifecycle hook: ` Fig. 14 With this change, the code from Fig. 13 will use lightcoral as a background color and red as a border color. Performance Note While this API gives us a powerful tool-set for reusing behaviors across different components, it can impact the performance of our application if used excessively. For each instance of a given composed component Angular will create objects of the component class itself as well as an instance of each directive that it is composed of. If the component appears only a couple of times in the application. then it won't make a significant difference. However, if we create, for example, a composed checkbox component that appears hundreds of times in the app, this may have a noticeable performance impact. Please make sure you use this pattern with caution, and profile your application in order to find the right composition pattern for your application. Summary As I have shown in the above examples, the directives composition API can be a quite useful but easy-to-use tool for extracting behaviors into smaller directives and combining them into more complex behaviors. In case you have any questions, you can always tweet or DM me at @ktrz. I'm always happy to help!...

Jan 4, 2023

4 mins

TypeScriptDirectiveAngular

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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Getting Started with Custom Structural Directives in Angular

Introduction

Creating a custom structural directive

NgIf directive clone

Handling additional parameters - else template

Real life example

Summary

Chris Trześniewski

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