Angular

State of Angular Ecosystem | December 2021

Published Dec 14, 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This article was written over 18 months ago and may contain information that is out of date.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.

This is a recap from the event State of Angular Ecosystem, you can see the full watch on State of Angular Ecosystem | Dic 2021.

This event was hosted by Rob Ocel, Software Architect and Engineering Lead at This Dot.

What's is new on the Angular Ecosystem? What should be expect on the upcoming releases? How Angular ecosystem looks like in the future?

Also, we had this amazing panel:

Minko Gechev, Software engineer at Google, Angular Core team.
Ben Lesh, RxJS core team lead.
Mark Whitfeld, Software engineer at Stackblitz, NGXS corea team lead.
Brandon Roberts, Senior Angular Engineer, Nrwl & NgRx maintainer.
James Daniels, Developer Relations, Firebase.
Jessica Janiuk, Senior Software Engineer, Google.

RxJS updates (Ben Lesh)

Weeks ago was introduced RxJS 7.4, the latest version from the RxJS team, which has many features, but first of all, the bundle size compared between RxJS 6 vs RxJS 7 (if you include everything RxJS exports, included new features!) was cut by almost the half, so if you are thinking to switch between those versions, you should go ahead.

Now, v7 has tons of typings fixes/updates, but now requires TypeScript 4.2+.

Most of the new features included in the new version are:

Top-level exports
Multi-cast simplified
Improved retry ergonomics
Animation Frames
New tap features
AsyncIterable support

That's was most of the most importants features delivered on RxJS 7.4, but there is more such as:

Ajax/fetch improvements
Supporting for aborting promises & more...

Regarding in how many downloads has RxJS, the downloads has increased consideraly since RxJS 6 in 2018. Now we can 30M downloads a week, back then in 2018 they have only 10M per week.

Stackblitz (Mark Whitfeld)

Now Stackbliz has support for Angular v13, this was thanks to the upgrade of Stackblitz v2, which runs over web-containers.

This new upgrade to Stackblitz v2, avoid to have custom-code depending on which framework you are running, making Stackblitz more agnostic from the framework (Angular, React, Vue) you are using. In fact, there is no custom-code to support any of the most used frameworks.

NGXS (Mark Whitfeld)

Now NGXS has support for Angular v13, with this mayor release there are up-to-date with the latest version of Angular. They are working on deliver another big features too.

Angular Core (Minko Gechev, Jessica Janiuk)

Ivy

Ivy now its the default engine to run compilation in Angular, which lead us a huge increase of performance vs versions who runs other engines to compile Angular.

With the implementation of Ivy as default, we can see a:

90% reduction of computational resources.
-50 mins faster build for the biggest app in Google.
Improved debuggability and profiling.
More effective relation between Github issues vs Fixes, thanks to a huge effort from the Team.
New system for RFC process.

What's new in Angular v13?

With the recent release of Angular v13 some new features are delivered, which include:

Removal of IE11 support (no more polyfills file, yaaaay)
Modern angular package format.
- Partially compiled Angular
- Removed UMD bundles
- ES2020 output
Adobe font inlining
Webpack 5 cache
Dinamic validator control
Better a11y

What are we building next?

Some of the upcoming improvements are:

Extended analysis
Simplified factory API
Advanced guides
MDC Web

Standalone components

Maybe some of the biggest updates which are upcoming on the next versions of Angular are Standalone components, who will run without adding to any module. This Standalone component will be bootstrapped directly into the Angular module, and the bundle will be reduced significantly.

NgRx (Brandon Roberts)

The most recent version of NgRx added some new features as:

Angular v13 support
RxJS 7 support
Ivy compiled libraries support
Feature creators
Improved selectors
Contributors page

Nx (Brandon Roberts)

The recent release of Nx, which is v13.2, also now include Angular v13 support. Also NgRx v13, and NestJS 8 support was included in the most recen version. Now, there is a RxJS 7 upgrade option for Nx.

AngularFire (James Daniels)

The official library from Firebase to Angular also release some of the next features:

Firebase v9 support, entirely tree-shakable support, RxJS 7 & Angular v13 support.
Firebase v8 compatibility.
Internally uses AngularFire, increased agility and less duplication.
Partial compilation, Ivy support.
Powerful new schematics

In the upcoming releases for AngularFire, the team is working to improve the next items:

Documentation drive
ng deploy capabilities
More schematics on the way...
Better bundling/rehydration
Prebuilt UI components

Conclusion

Angular v13 bring to us so many new features, therefore the Ecosystem of Angular is updating to support this new release.

Some of the most libraries used with Angular are pushing forward and taking the framework from Google to the next level.

Also the Angular team, is listening to the community and making the upcoming releases more beginner-friendly such as `Standalone components. As Angular dev, we celebrate the removal of IE11 support without that, we can take advantages of most CSS features who are not supported in that browser.

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)

Daian Scuarissi
@asdaian @SDaian

Observables: Coming to a Browser Near You with Dominic Farolino (Google Chrome)

Dominic Farolino, a software engineer on the Chrome team, discusses his involvement in adding observables to the web platform. By incorporating observables into browsers, developers can simplify their workflows and streamline complex APIs (like the Resize Observer). This not only will saves time and effort but also allows developers to focus on creating exceptional user experiences. Adding observables to the browser will drastically affect RxJS. RxJS is a popular library for reactive programming, and integrating observables into browsers will enable developers to handle asynchronous events and data streams more efficiently. This integration opens up a world of possibilities for creating responsive and interactive web applications. This does not mean RxJS will go away, but it will become more like LoDash for events. The incorporation of observables into browsers brings several benefits for web developers. Firstly, it simplifies complex APIs, making them more intuitive and easier to use. This allows developers to write cleaner and more maintainable code. Secondly, by leveraging observables, developers can handle asynchronous events and data streams more effectively, resulting in improved performance and responsiveness. Lastly, it will empower developers with a powerful toolset for reactive programming, enabling them to build more sophisticated and interactive web applications. The conversation in the podcast highlights the collaborative nature of advancing web technologies. Dominic discusses the importance of setting deadlines, sharing updates, and working together to achieve their goals. He expresses optimism about the progress of the project, with positive feedback from WebKit and plans for a future release. This collaborative approach ensures that the enhancements made to web performance benefit developers and users alike. Download this episode here....

Jul 12, 2024

2 mins

RxJSVercelDeno

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

Understanding Next.js Data Fetching for Beginners

When I started to learn Next.Js, I felt a little bit lost with some abbreviations they use to make the data fetching. All of them look pretty simmilar, but they have different meanings. If you feel the same, you are not alone. Let's discover what CSR, SSR, SSG, and ISR means, and how we can use them. It is quite confusing because I, as an Angular developer, only knew one strategy to fetch the data:HttpClient. But for example, if you are more familiar with React, you probably use a different strategy: useEffect. So, let's get started. Vercel's Next.js framework has four different data fetching options despite being known as a server-side render framework: - CSR - Client-Side Rendering is a common data fetching method using useEffect. It will fetch the data from the API every single page request on the client-side (after the page is rendered, then the function will run). - SSR - Server-Side Rendering will run a special function to fetch data from the API with every page request on the server-side (before the page is loaded, that special function will run first, creating a delay, then after that, it will serve the page). - SSG - Static Site Generation will run a special function to fetch data once when that page builds. - ISR – Incremental Static Regeneration offers a new method. Shortly put, it is a combination of SSG, and SSR, where it served statically, but at a certain time and certain condition, that page will rebuild and fetch the data from the API again. Don't worry if you don't understand any of the concepts. I will explain a little bit further shortly. CSR (Client-Side Rendering) This is a basic example of how you can use Client-Side Rendering. I'm using the well known useEffect method from React. ` You can see how it works on Stackblitz. We can highlight 2 things here: - The useEffect method to make the retrieve of the name every time the page loads. - A loading indicator, this is used to wait for the fetching data, because the data is fetched after the page is rendered. SSR (Server-Side Rendering) Just to keep in mind, when you are using Server-Side rendering, and using the method getServerSideProps(), Next.js will pre-render this page on each request using the data returned by getServerSideProps. ` You can see how it works: Stackblitz We had 3 highlights here: - Method getServerSideProps(), is a function indicating that a page is using Server-Side Rendering. - We had a delay before render, and NO loading indicator. The data is fetched before the page is rendered, so that's why we can see a little delay. - Data is fetched on every request, that's why every time we reload the page, is showing a different dad joke. SSG (Static Site Generator) If we take a look at the code below, we will see that it is pretty similar to the SSR code, but the difference here is the getStaticProps method. This method will only fetch when the app is building. ` The highlights here are: - getStaticProps is a method indicating that the page is using Static Site Generation. - Data will be fetched only when you run yarn build. The API will be hit only when the app is building. - Data will NOT change because there is no further fetch. You can see how it works: Stackblitz ISR (Incremental Static Regeneration) This strategy works pretty simmilar like SSG, but here we need to add a revalidate prop to our main getStaticProps function. ` There are a few keys to highlight here: - When you set the revalidate prop to certain amount of time (in our example we set it to 20), reloading doesn't trigger changes. The page will remain in a cooldown state. - Is the page rebuilt every 20 seconds then? No. When the cooldown state is off, if no one visits the page, it will not rebuild even after the 20s pass. But the first person who enters the page when the cooldown state is off will trigger a rebuild. However, that person will not see those changes. But the changes will be applied to the next full reload. You can see how it works: Stackblitz Conclusion Understand how these abbreviations work, and how we can use it in a Next.js app will help us develop more robust solutions, and use Next.js' full potential. I know these terms can sound overwhelming and difficult to understand, but with a little bit of practicing, we can see in action in a few steps. In future blog posts, we will see the best approach to identify and choose between them....

May 9, 2022

4 mins

NextJSJavaScriptReact

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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State of Angular Ecosystem | December 2021

RxJS updates (Ben Lesh)

Stackblitz (Mark Whitfeld)

NGXS (Mark Whitfeld)

Angular Core (Minko Gechev, Jessica Janiuk)

Ivy

What's new in Angular v13?

What are we building next?

Standalone components

NgRx (Brandon Roberts)

Nx (Brandon Roberts)

AngularFire (James Daniels)

Conclusion

Daian Scuarissi

You might also like

Observables: Coming to a Browser Near You with Dominic Farolino (Google Chrome)

Exploring Angular Forms: A New Alternative with Signals

Understanding Next.js Data Fetching for Beginners

Introduction to Zod for Data Validation

Let's innovate together!

You might also like

Observables: Coming to a Browser Near You with Dominic Farolino (Google Chrome)

Exploring Angular Forms: A New Alternative with Signals

Understanding Next.js Data Fetching for Beginners

Introduction to Zod for Data Validation