Javascript

Storybook 6.5 - Key Features to Note

Jul 5, 2022

3 min read

Storybook is an open-source tool for building UI components and pages in isolation. It allows you to work on one component at a time. You can develop entire UIs without needing to start up a complex dev stack, force certain data into your database, or navigate around your application.

Storybook 6.5 was recently released and it comes with exciting features highlighted in this article.

Support for the Latest Popular Javascript Libraries and Frameworks

Support for Angular and React Out of the Box

Storybook 6.5 supports React 18 and Angular 14 out of the box.

When you run your React project for the first time, it will auto-detect the React version and use the new root API if it detects it on React 18.

Check out #17215.

Figma Plugin

With Storybook 6.5, you can easily compare design specs and different implementations with the help of the Figma plugin’s Storybook Connect which embeds stories into the Figma workspace.

This plugin allows developers to interact with the Figma design using a link created by the Figma plugin between the stories and designs. Check out more here.

Interaction Testing

Storybook Interaction Testing allows developers to write tests for your application in the story file itself. The tests execute in the browser, and you can get a GUI to visualize and debug them. Under the hood, it is powered by Jest, Playwright, and a testing library, giving you the familiarity of testing the application.

Check out Integrated Test.

Webpack 5 Lazy Compilation

Lazy Compilation is a feature that only calls the content of a page when it is needed, and delays every other content until a route to the content is called.

Storybook 6.5 only compiles the core runtime, and builds stories as you visit them. This enables the developer to quickly spin-up stories, and rebuild larger Storybooks.

Learn more about Storybook Lazy Compilation

Other features

Storybook support for Vite Builder has been improved with instant rebuild of stories, and have officially been brought into Storybook's core.

There were also improvements to accessibility features for Storybook and UI design features for stories.

Wrap Up

Storybook 6.5 offers a number of features and out of the box support for both React and Angular, making this release among the most exciting for this open source UI tool:

Figma’s Storybook Connect embeds stories into the Figma workspace. Write tests for your application in the story file itself with Storybook Interaction Testing.

Webpack 5 Lazy Compilation calls the content of a page when it is needed, and delays every other content until a route to the content is called.

If you get a chance to try out Storybook yourself, please let us know by tweeting us at @ThisDotMedia!

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.

Hassan Sani

@inidaname @inidaname

How to create and use custom GraphQL Scalars

How to create and use custom GraphQL Scalars In the realm of GraphQL, scalars form the bedrock of the type system, representing the most fundamental data types like strings, numbers, and booleans. As explored in our previous post, "Leveraging GraphQL Scalars to Enhance Your Schema," scalars play a pivotal role in defining how data is structured and validated. But what happens when the default scalars aren't quite enough? What happens when your application demands a data type as unique as its requirements? Enter the world of custom GraphQL scalars. These data types go beyond the conventional, offering the power and flexibility to tailor your schema to precisely match your application's unique needs. Whether handling complex data structures, enforcing specific data formats, or simply bringing clarity to your API, custom scalars open up a new realm of possibilities. In this post, we'll explore how to understand, create, and effectively utilize custom scalars in GraphQL. From conceptualization to implementation, we'll cover the essentials of extending your GraphQL toolkit, empowering you to transform abstract ideas into concrete, practical solutions. So, let's embark together on the journey of understanding and utilizing custom GraphQL scalars, enhancing and expanding the capabilities of your GraphQL schema. Understanding Custom Scalars Custom scalars in GraphQL extend beyond basic types like String or Int, allowing data to be defined, validated, and processed more precisely. They're instrumental when default types don't quite capture the complexity or specificity of the data, such as with specialized date formats or unique identifiers. The use of custom scalars brings several benefits: * Enhanced Clarity: They offer a clearer representation of what data looks like and how it behaves. * Built-in Validation: Data integrity is bolstered at the schema level. * Flexibility: They can be tailored to specific data handling needs, making your schema more adaptable and robust. With this understanding, we'll explore creating and integrating custom scalars into a GraphQL schema, turning theory into practice. Creating a Custom Scalar Defining a Custom Scalar in TypeScript: Creating a custom scalar in GraphQL with TypeScript involves defining its behavior through parsing, serialization, and validation functions. * Parsing: Transforms input data from the client into a server-understandable format. * Serializing: Converts server data back to a client-friendly format. * Validation: Ensures data adheres to the defined format or criteria. Example: A 'Color' Scalar in TypeScript The Color scalar will ensure that every color value adheres to a valid hexadecimal format, like #FFFFFF for white or #000000 for black: ` In this TypeScript implementation: * validateColors: a function that checks if the provided string matches the hexadecimal color format. * parseValue: a method function that converts the scalar’s value from the client into the server’s representation format - this method is called when a client provides the scalar as a variable. See parseValue docs for more information * serialize: a method function that converts the scalar’s server representation format to the client format, see serialize docs for more information * parseLiteral: similar to parseValue, this method function converts the scalar’s value from the client to the server’s representation format. Still, this method is called when the scalar is provided as a hard-coded argument (inline). See parseLiteral docs for more information In the upcoming section, we'll explore how to incorporate and validate these custom scalars within your schema, ensuring they function seamlessly in real-world scenarios. Integrating Custom Scalars into a Schema Incorporating the 'Color' Scalar After defining your custom Color scalar, the next crucial step is effectively integrating it into your GraphQL schema. This integration ensures that your GraphQL server recognizes and correctly utilizes the scalar. Step-by-Step Integration 1. Add the scalar to Type Definitions: Include the Color scalar in your GraphQL type definitions. This inclusion informs GraphQL about this new scalar type. 2. Resolver Mapping: Map your custom scalar type to its resolver. This connection is key for GraphQL to understand how to process this type during queries and mutations. ` 1. Use the scalar: Update your type to use the new custom scalar ` Testing the Integration With your custom Color scalar integrated, conducting thorough testing is vital. Ensure that your GraphQL server correctly handles the Color scalar, particularly in terms of accepting valid color formats and rejecting invalid ones. For demonstration purposes, I've adapted a creation mutation to include the primaryColor field. To keep this post focused and concise, I won't detail all the code changes here, but the following screenshots illustrate the successful implementation and error handling. Calling the mutation (createTechnology) successfully: Calling the mutation with forced fail (bad color hex): Conclusion The journey into the realm of custom GraphQL scalars reveals a world where data types are no longer confined to the basics. By creating and integrating scalars like the Color type, we unlock precision and specificity in our GraphQL schemas, which significantly enhance our applications' data handling capabilities. Custom scalars are more than just a technical addition; they testify to GraphQL's flexibility and power. They allow developers to express data meaningfully, ensuring that APIs are functional, intuitive, and robust. As we've seen, defining, integrating, and testing these scalars requires a blend of creativity and technical acumen. It encourages a deeper understanding of how data flows through your application and offers a chance to tailor that experience to your project's unique needs. So, as you embark on your GraphQL journey, consider the potential of custom scalars. Whether you're ensuring data integrity, enhancing API clarity, or simply making your schema a perfect fit for your application, the possibilities are as vast as they are exciting. Embrace the power of customization, and let your GraphQL schemas shine!...

Apr 10, 2024

5 mins

GraphQLJavaScript

Overview of the New Signal APIs in Angular

Overview of the New Signal APIs in Angular Google's Minko Gechev and Jeremy Elbourn announced many exciting things at NG Conf 2024. Among them is the addition of several new signal-based APIs. They are already in developer preview, so we can play around with them. Let's dig into it, starting with signal-based inputs and the new matching outputs API. Signal Based Inputs Discussions about signal-based inputs have been taking place in the Angular community for some time now, and they are finally here. Until now, you used the @Input() decorator to define inputs. This is what you'd have to write in your component to declare an optional and a required input: ` With the new signal-based inputs, you can write much less boilerplate code. Here is how you can define the same inputs using the new syntax: ` It's not only less boilerplate, but because the values are signals, you can also use them directly in computed signals and effects. That, effectively, means you get to avoid computing combined values in ngOnChanges or using setters for your inputs to be able to compute derived values. In addition, input signals are read-only. The New Output I intentionally avoid calling them signal-based outputs because they are not. They still work the same way as the old outputs. The Angular team has just introduced a new output API that is more consistent with the latest inputs API and allows you to write less boilerplate, similar to the new input API. Here is how you would define an output until now: ` Here is how you can define the same output using the new syntax: ` The thing I like about the new output API is that sometimes it happens to me that I forget to instantiate the EventEmitter because I do this instead: ` You won't forget to instantiate the output with the new syntax because the output function does it for you. Signal Queries I am sure most readers know the @ViewChild, @ViewChildren, @ContentChild, and @ContentChildren decorators very well and have experienced the pain of triggering the infamous ExpressionChangedAfterItHasBeenCheckedError or having the values unavailable when needed. Here is a refresher on how you would use these decorators until now: ` With the new signal queries, similar to the new input API, the values are signals, and you can use them directly in computed signals and effects. You can define the same queries using the new syntax: ` Jeremy Elbourn mentioned that the new signal queries have better type inference and are more consistent with the new input and output APIs. He also showcased a brand new feature not available with the old queries. You can now define a query as required, and the Angular compiler will throw an error if the query has no result, guaranteeing that the value won't be undefined. Here is how you can define a required query: ` Model Inputs Jeremy and Minko announced the last new feature is the model inputs. The name is vague, but the feature is cool—it simplifies the definition of two-way bindings. Until now, to achieve two-way binding, you would have to define an input and an output following a given naming convention. @Input and @Output had to be defined with the same name (followed by "Change" in the case of the output). Then, you could use the template's [()] syntax. ` ` That way, you could keep the value in sync between the parent and the child component. With the new model inputs, you can define a two-way binding with a single line of code. Here is how you can define the same two-way binding using the new syntax: ` The html template stays the same: ` The model function returns a writable signal that can be updated directly. The value will be propagated back to any two-way bindings. Conclusion The new signal-based APIs are a great addition to Angular. They allow you to write less boilerplate code and make your components more reactive. The new APIs are already in developer preview, so you can start playing around with them today. I look forward to seeing how the community will adopt these new features and what other exciting things the Angular team has in store for us, such as zoneless apps by default....

Apr 3, 2024

3 mins

AngularJavaScript

How to Create Better Test Coverage Using Cypress 10

Testing is an integral part of software development, and it is important that all developers learn best testing practices. Jordan Powell, DX engineer at Cypress and Angular Google Developer Expert, has some tips to share with developers on how to write better tests using Cypress 10. In this article, we will take a look at Powell’s tips for writing end-to-end tests, component tests, and advanced testing patterns in Cypress. If you want to learn more from Jordan Powell, please check out his Advanced Cypress JS Drop training. Table of Contents - Why is Testing important? - Types of Testing - A new take on the testing pyramid - Differences between end-to-end testing and component testing - Jordan Powell’s best practices for E2E testing - Don’t use HTML Native selectors - Use Closures - Independent Test - Use Route Aliases - Setting a Global baseUrl - Jordan Powell’s Best Practices for Component Testing - Default Config Mount - Cypress Intercept - Use createOutputSpy - Jordan Powell’s Advanced Cypress Patterns - Session - Origin - Conclusion Why is Testing important? Software testing identifies issues within the application, and helps ensure that only high quality products are shipped to the user. Here are Jordan Powell’s reasons on why testing is important, and how it helps developers: Documentation: Good testing coverage will result in developers creating stronger test plans and better QA testing for new releases. Confidence: Writing good tests allows developers to build new features in confidence because the applications are working as intended. Safe Refactoring: Good test coverage leads to less refactoring down the road, and provides developers more time to work on new features. Improved UX: Good test coverage provides better UX (User Experience) for the end user because the application is working as intended. Types of Testing E2E, Integration, and Unit testing are three common methods for testing software applications. Unit Test: Unit testing serves as the foundation of the test pyramid. If you're working in a functional language, a unit will most likely be a single function. Your unit tests will call a function with different parameters and ensure that it returns the expected values. In an object-oriented language, a unit can range from a single method to an entire class. Integration test: Integration testing is where individual components of your application are tested as a group. End-to-end testing: E2E Testing is a technique that tests your app from the web browser through to the back end of your application, as well as testing integrations with third-party APIs and services. These types of tests are great at making sure your entire app is functioning as a cohesive whole. A new take on the testing pyramid In Jordan Powell’s Advanced Cypress JS Drop training, he challenges developers to rethink the traditional testing pyramid, and believes that component testing should also be included. Component Testing with Cypress 10 allows developers to test individual components quickly, regardless of its complexity. Component tests differ from end-to-end tests in that instead of visiting a URL to pull up an entire app, a component can be "mounted" and tested on its own. Differences between end-to-end testing and component testing Here are a few key differences between End-to-end and component testing: | End-to-end testing | Component testing | | ------------------------------------------------------- | ------------------------------------------------------------------------ | | The entire application and all of its layers are tested | Only the independent components are tested | | Testing can be done by developers and QA Teams | Testing is done by the developers | | Often requires a complex setup | No extra configuration for CI(Continuous Integration) environments needed | | Initialization command: cy.visit(url) | Initialization command: cy.mount() | Jordan Powell’s best practices for E2E testing Don’t use HTML Native selectors It is not good practice to use element selectors, id attributes, or class attributes when writing End-to-end tests. Using HTML Native selectors can lead to team members refactoring tests later on, or changing attributes which could affect the tests. Jordan Powell recommends using data attributes that can inform the team that this is a test attribute. When other team members need to change anything, they will be aware of the function of the attribute and what it may affect. Use Closures Jordan warns against assigned return values for Cypress assertions, and recommends using closures to access the Commands yield like this: ` Independent Test It is not good practice to combine related tests. Jordan Powell suggests that tests should be run independently from one another without sharing or relying on other test states. If test suites are related in any way, run the related properties or methods before each of the test runs, like in the code below: ` Use Route Aliases Another recommended practice is to use route aliases to guard Cypress against proceeding until an explicit condition is met. ` Setting a Global baseUrl It is bad practice to use hardcoded URL strings for the baseUrl because it will eventually fail when the environment changes. Instead, Powell recommends using a config file that holds the environment baseUrl. Jordan Powell’s Best Practices for Component Testing All of the code examples in this next section will be for Angular, but Cypress component testing works for all major Frontend JavaScript frameworks. Default Config Mount Component testing takes two parameters: the component to mount, and the object for configuration. A Custom Mount Config can boost flexibility. It ships a default mount config which you can use, but to manage multiple modules and import without adding too many boilerplate codes, it is recommended to have a custom mount config for specific instances. ` Cypress Intercept Component testing handles the individual components you are testing at a particular time, to access external API it is recommended to use cy.intercept. According to the Doc Cy.intercept can be used to passively listen for matching routes without manipulating the request or its response in any way. ` Use createOutputSpy When working with eventEmitter for components that may contain forms or other elements with events, createOutputSpy will automatically create an EventEmitter and set up the spy on it's .emit() method. ` Jordan Powell’s Advanced Cypress Patterns Session When testing for routes or components that require authentication Cypress provides cy.session which eliminates creating functions in your test to check for sessions on every call to the route or component. cy.session caches the sessions, and it will skip the login process for testing components that need the sessions on a second call. ` Origin Running tests for projects that require a visit to multiple different domains could get CORS, or a limitation of visits, due to browser environment. Cypress provides Origin to help bypass some of the browser limitations. ` Conclusion In this article, we looked at Jordan Powell’s tips for writing End-to-end tests, component tests, and advanced testing patterns in Cypress. I recommend watching the full video for Jordan Powell’s Advanced Cypress JS Drop training. Are you excited about the Cypress Component Testing? Let us know on Twitter....

Dec 19, 2022

6 mins

CypressTesting

Transforming Platform Engineering Through Chargeback Programs with Shuchi Mittal

Shuchi Mittal, the Head of Cloud enablement at Honeywell, discusses how she as a leader in platform engineering has been able to transform internal platform engineering teams at other organizations by providing teams with value-added services, and how they effectively managed costs. She talks about how to treat these teams as customers, and delivering services that meet the customer needs, but also charging them for their usage. By providing policy-compliant infrastructure and unique services tailored to their requirements, platform engineering teams can showcase their commitment to supporting the success of other teams within an organization. This approach not only fosters trust but also positions platform engineering as a strategic partner rather than just a service provider. By going beyond the basic infrastructure provisioning, the platform engineering team can offer services that help development and product teams streamline their processes and improve efficiency. Shuchi shares her work at Fiserv where she implemented a chargeback system to track usage and costs effectively, incentivizing better development practices. This not only helped in managing costs but also encouraged teams to optimize their resource utilization, leading to improved overall efficiency and more easily scalable systems. Her platform engineering team recognized the importance of effectively managing financial aspects to secure upfront investment for product development. By implementing a billing system based on gigabyte hours, they aligned costs with usage, enabling teams to have a clear understanding of their resource consumption. This approach not only provided transparency but also incentivized teams to adopt cost-effective practices. By strategically managing financial aspects, the platform engineering team gained the trust of stakeholders and secured the necessary resources to drive innovation and deliver value to the organization. Shuchi’s journey of platform engineering serves as a valuable example of how a team can transition from being a basic service provider to becoming an innovation partner within an organization. By building trust, offering value-added services, and strategically managing financial aspects, the platform engineering team successfully elevated their role and became a strategic enabler of innovation. Download this episode here....

Apr 16, 2024

2 mins

Engineering LeadershipSoftware Engineering

Storybook 6.5 - Key Features to Note

Support for the Latest Popular Javascript Libraries and Frameworks

Hassan Sani

You might also like

How to create and use custom GraphQL Scalars

Overview of the New Signal APIs in Angular

How to Create Better Test Coverage Using Cypress 10

Transforming Platform Engineering Through Chargeback Programs with Shuchi Mittal

You might also like

How to create and use custom GraphQL Scalars

Overview of the New Signal APIs in Angular

How to Create Better Test Coverage Using Cypress 10

Transforming Platform Engineering Through Chargeback Programs with Shuchi Mittal