Angular

Introduction to NgRx

Published Feb 24, 2021

Updated Feb 14, 2023

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This article was written over 18 months ago and may contain information that is out of date.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

Why

Angular projects are getting more and more complex these days. With handling all the user interaction, application state and accessing this state in every place, it might be necessary but quickly become over complicated. This is why having a one, global app-wide state management system that can be accessible throughout the application may be very useful in modern frontend application. One of the solutions available for Angular applications is NgRx.

What

In this post, I will give you a quick introduction on how to get started using NgRx in you Angular application. I'll base this intro on a simple Angular app where we can display a photo which then can be liked or disliked. You can find the entry point for this application on my GitHub repo. If you want to follow this article's code, please clone the repository and checkout entry_point tag.

git clone git@github.com:ktrz/introduction-to-ngrx.git

git checkout entry_point

After cloning just install all the dependencies

yarn install

and you can see the example app by running

yarn start -o

We will convert this application to use the NgRx state management in just few steps.

How

Key concepts

Let's start with introducing a few key concepts and building blocks of NgRx. NgRx is a state management tool inspired by Redux, so the building blocks might be familiar to Redux users. To build and operate on our state, we will need the following basic building blocks:

Store is where state of the application will be stored. It's both an Observable of a state and an Observer of action.
Actions describe all the possible and unique events that can occur within the application. They can occur ie. by user interaction, communication with the server or can be a result of other actions.
Reducers are what binds the actions and the state. All the state changes must occur as result of an action. Those changes are handled by pure functions called reducers. They take the current state and the latest action and compute new state value based on that.
Selectors - to retrieve part of the state that we're interested in, we use pure functions which extract the portion of the state that a given component might be interested in.

NgRx flow

NgRx makes sure that all the interactions in the application follow a certain unidirectional flow. The following diagram illustrates the general flow of the state: NgRx basic flow

Getting started

The easiest way to add NgRx to the project and get started is to use a Angular CLI schematic.

sh ng add @ngrx/store@latest

This command will

add the @ngrx/store package to package.json -> dependencies
yarn install or npm install those dependencies
import the StoreModule.forRoot({}, {}) in your AppModule

Define Actions

The first thing to do after installing the necessary dependencies is to define some actions that can occur in our application. In our case, this can define the following action:

like photo
dislike photo

To put that into code, let's create the following file: src/app/store/photo.actions.ts

import {createAction} from '@ngrx/store';

export const likePhoto = createAction('[Photo List] Like Photo');
export const dislikePhoto = createAction('[Photo List] Dislike Photo');

In this file, we define all the actions (action creators) that can occur in our app. In general, the shape of the action has to be in the following share:

const someAction = {
  type: 'Unique type',
  /* ... some additional properties */
}

The required part is the type property which will be used to identify our action. Other properties are optional and might be used to pass some additional data associated with the event ie. id of the liked/disliked photo.

What we've just defined are action creators. They are functions which return an action of a specific type. To create ie. like action we can do it as following:

const likeAction = likePhoto()

Define Reducer

Now that we have our actions defined, we need a way to consume them and thus make actual changes to the store's state. As described before, this is done using pure functions called reducers. We could define the functions from scratch using ie. switch case statements, but NgRx comes with some handy helper functions which make this process much nicer. Let's create a file to keep our photo reducer in: src/app/store/photo.reducer.ts

import {createReducer, on} from '@ngrx/store';
import {dislikePhoto, likePhoto} from './photo.actions';

export type PhotoState = number;

const initialState: PhotoState = 0;

export const photoReducer = createReducer(
  initialState,
  on(likePhoto, state => state + 1),
  on(dislikePhoto, state => state - 1)
);

As you can see, you import the actions which we've defined previously and use them in our reducer. createReducer is an utility function which creates a reducer with a provided initial state. This gives us a nice quick way to define new reducers as well as great type inference. TypeScript knows the shape of state that photoReducer operates on from the shape of initialState object.

on(...) function can be considered as case statements within a switch. We define that if we encounter a given action, we produce a new state derived from its previous value and optional properties provided within the action.

All this code could be rewritten in the following shape. In my opinion, the construction mentioned above is both more consise and self explanatory as well, so I suggest using it.

export function photoReducer(state = initialState, action: Action): PhotoState {
  switch (action.type) {
    case likePhoto.type:
      return state + 1;
    case dislikePhoto.type:
      return state - 1;
    default:
        return state;
  }
}

After creating a reducer, we need to let our application know that we want to use it. We can define it in our AppModule file and add it to the properties of the StoreModule.forRoot's first param.

  imports: [
    /* ... other modules */
    StoreModule.forRoot({
        photo: photoReducer
      },
      {}
    )
  ],

Define Selectors

Now that we've defined both possible actions and reducer to handle them, we need a way to get the data from the store. To do this, we'll create another pure function called selectors. The responsibility of selectors is to transform the whole state object (which can we a really large object in real life examples) into small bits necessary for a specific part of the application. In our case, we need a way to get the photo information along with the number of likes/dislikes that it currently has.

Let's create another file in our src/app/store directory src/app/store/photo.selectors.ts

import {createSelector} from '@ngrx/store';
import {PhotoState} from './photo.reducer';

const selectPhotoFeature = (state: { photo: PhotoState }) => state.photo;

export const selectPhoto = createSelector(selectPhotoFeature, likes => ({
    title: 'Introduction to NgRx',
    url: 'https://ngrx.io/assets/images/ngrx-badge.png',
    likes
  })
);

We are again using the utility function provided with NgRx - createSelector. Because our state can be a nested tree of objects, this enables us to create more complex selectors based on the already existing ones. In this case, we combine selecting a photo slice of our whole state with selection of the whole photo object (in this case most of its props are static). Whenever a number of likes change, we will get a new instance of the photo, which makes detection of changes super easy and performant.

Use all the building blocks in our component

Now that we've defined all the necessary building blocks, we can finally start using them in our AppComponent. The first thing we need to do is inject the Store service into our component.

import {Store} from '@ngrx/store';

interface AppState {
  photo: PhotoState;
}

@Component({/* ... */})
export class AppComponent {
  constructor(private store: Store<AppState>) {
  }
}

This gives us access to both selecting data from the store (as an Observable) and notifying it about actions happening (by dispatching actions).

Now let's select the state of the photo into a component's property and define methods for dispatching like and dislike actions.

import {select, Store} from '@ngrx/store';
import {selectPhoto} from './store/photo.selectors';
import {dislikePhoto, likePhoto} from './store/photo.actions';

@Component({/* ... */})
export class AppComponent {
  photo$ = this.store.pipe(select(selectPhoto));

  constructor(private store: Store<AppState>) {
  }

  onLike(): void {
    this.store.dispatch(likePhoto());
  }

  onDislike(): void {
    this.store.dispatch(dislikePhoto());
  }
}

To select data from store, we can basically treat it as an Observable and use pipe operator on it. To select data with our previously created selectors, we can use select operator provided by @ngrx/store package.

To dispatch actions and notify the store of it, we can use dispatch() method and feed it with the necessary action (also defined above).

Now all that is left to do is hook up all this state and methods into our component's template.


@Component({
  selector: 'app-root',
  template: `
    <div class="photos">
      <app-photo class="photo" [photo]="photo$ | async" (like)="onLike()" (dislike)="onDislike()"></app-photo>
    </div>
  `,
})

As you can see, we use async pipe to unwrap the photo$ observable and pass a plain object into the [photo] input. The app-photo component provides two outputs: like and dislike which we can react to with our AppComponent's methods.

For clarity purposes, let's define our PhotoComponent in src/app/photo/photo.component.ts (It's already defined within the entry point repo but needs some minor tweaks.)

import {Component, EventEmitter, Input, Output} from '@angular/core';
import {Photo} from './photo';

@Component({
  selector: 'app-photo',
  template: `
    <mat-card class="example-card" *ngIf="photo">
      <mat-card-header>
        <div mat-card-avatar class="example-header-image"></div>
        <mat-card-title>{{photo.title}}</mat-card-title>
      </mat-card-header>
      <mat-card-content>
        <img mat-card-image [src]="photo.url" alt="Intro to NgRx">
      </mat-card-content>
      <mat-card-actions align="end">
        <button mat-icon-button color="warn" (click)="onLike()">
          <ng-container *ngIf="photo.likes > 0; else notLikedButton">
            <mat-icon [matBadge]="photo.likes" matBadgeColor="warn" color="primary">thumb_up</mat-icon>
          </ng-container>
          <ng-template #notLikedButton>
            <mat-icon color="primary">thumb_up_off_alt</mat-icon>
          </ng-template>
        </button>
        <button mat-icon-button (click)="onDislike()">
          <ng-container *ngIf="photo.likes < 0; else notDislikedButton">
            <mat-icon [matBadge]="-photo.likes" matBadgeColor="warn" color="primary">thumb_down</mat-icon>
          </ng-container>
          <ng-template #notDislikedButton>
            <mat-icon color="primary">thumb_down_off_alt</mat-icon>
          </ng-template>
        </button>
      </mat-card-actions>
    </mat-card>

  `,
  styleUrls: ['./photo.component.scss']
})
export class PhotoComponent {
  @Input() photo?: Photo | null;

  @Output() like = new EventEmitter();
  @Output() dislike = new EventEmitter();

  onLike(): void {
    this.like.next();
  }

  onDislike(): void {
    this.dislike.next();
  }
}

and PhotoModule in src/app/photo/photo.module.ts

import { NgModule } from '@angular/core';
import { CommonModule } from '@angular/common';
import {MatBadgeModule} from '@angular/material/badge';
import {MatButtonModule} from '@angular/material/button';
import {MatCardModule} from '@angular/material/card';
import {MatIconModule} from '@angular/material/icon';
import { PhotoComponent } from './photo.component';

@NgModule({
  declarations: [PhotoComponent],
  imports: [
    CommonModule,
    MatCardModule,
    MatButtonModule,
    MatIconModule,
    MatBadgeModule
  ],
  exports: [PhotoComponent]
})
export class PhotoModule { }

Now start your application again and see the result it the browser. You can still like/dislike the photo and the state of the app is stored withing NgRx store.

Conclusion

As you can see, setting up this example required a bit more code to start with. But when the application grows, this additional code pays off as we get one central place where all the state changes are happening. We can see exactly what actions are being dispatched (ie. by using Redux Devtools) and therefore our application is more maintainable.

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

More articles are coming soon! Do not miss any of them and visit the This Dot Blog to be up-to-date.

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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

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

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

How to Create a Bot That Sends Slack Messages Using Block Kit and GitHub Actions

Have you ever wanted to get custom notifications in Slack about new interactions in your GitHub repository? If so, then you're in luck. With the help of GitHub actions and Slack's Block Kit, it is super easy to set up automated workflows that will send custom messages to your Slack channel of choice. In this article, I will guide you on how to set up the Slack bot and send automatic messages using GH actions. Create a Slack app Firstly, we need to create a new Slack application. Go to Slack's app page. If you haven't created an app before you should see: otherwise you might see a list of your existing apps: Let's click the Create an App button. Frpm a modal that shows up, choose From scratch option: In the next step, we can choose the app's name (eg. My Awesome Slack App) and pick a workspace that you want to use for testing the app. After the app is created successfully, we need to configure a couple of additional options. Firstly we need to configure the OAuth & Permissions section: In the Scopes section, we need to add a proper scope for our bot. Let's click Add an OAuth Scope in the Bot Token Scopes section, and select an incoming-webhook scope: Next, in OAuth Tokens for Your Workspace section, click Install to Workspace and choose a channel that you want messages to be posted to. Finally, let's go to Incoming Webhooks page, and activate the incoming hooks toggle (if it wasn't already activated). Copy the webhook URL (we will need it for our GitHub action). Create a Github Action Workflow In this section, we will focus on setting up the GitHub action workflow that will post messages on behalf of the app we've just created. You can use any of your existing repositories, or create a new one. Setting Up Secrets In your repository, go to Settings -> Secrets and variables -> Actions section and create a New Repository Secret. We will call the secret SLACK_WEBHOOK_URL and paste the url we've previously copied as a value. Create a workflow To actually send a message we can use slackapi/slack-github-action GitHub action. To get started, we need to create a workflow file in .github/workflows directory. Let's create .github/workflows/slack-message.yml file to your repository with the following content and commit the changes to main branch. ` In this workflow, we've created a job that uses slackapi/slack-github-action action and sends a basic message with an action run id. The important thing is that we need to set our webhook url as an env variable. This was the action can use it to send a message to the correct endpoint. We've configured the action so that it can be triggered manually. Let's trigger it by going to Actions -> Send Slack notification We can run the workflow manually in the top right corner. After running the workflow, we should see our first message in the Slack channel that we've configured earlier. Manually triggering the workflow to send a message is not very useful. However, we now have the basics to create more useful actions. Automatic message on pull request merge Let's create an action that will send a notification to Slack about a new contribution to our repository. We will use Slack's Block Kit to construct our message. Firstly, we need to modify our workflow so that instead of being manually triggered, it runs automatically when a pull requests to main branch is merged. This can be configured in the on section of the workflow file: ` Secondly, let's make sure that we only run the workflow when a pull request is merged and not eg. closed without merging. We can configure that by using if condition on the job: ` We've used a repository name (github.repository) as well as the user login that created a pull request (github.event.pull_request.user.login), but we could customize the message with as many information as we can find in the pull_request event. If you want to quickly edit and preview the message template, you can use the Slack's Block Kit Builder. Now we can create any PR, eg. add some changes to README.md, and after the PR is merged, we will get a Slack message like this. Summary As I have shown in this article, sending Slack messages automatically using GitHub actions is quite easy. If you want to check the real life example, visit the starter.dev project where we are using the slackapi/slack-github-action to get notifications about new contributions (send-slack-notification.yml) If you have any questions, you can always Tweet or DM me at @ktrz. I'm always happy to help!...

Oct 18, 2023

7 mins

GitHubGitHub Actions

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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Introduction to NgRx

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Chris Trześniewski

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