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Cypress 10 - The Latest Release Details - Component Testing, Configuration Options

Published Jul 25, 2022

Updated Jan 30, 2023

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This article was written over 18 months ago and may contain information that is out of date.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

Cypress 10 was recently released with some long awaited features and bug fixes!

In this article, I will talk about some of the exciting features in the latest releases of 10.3.0, 10.2.0 and 10.1.0. Some of these features include component testing, changes to the Cypress configuration file, a new design for Cypress Onboarding UI Design, enabling Cypress natively for Apple silicon and Linux ARM64 and AArch64 systems, and adding live test data into the Cypress Dashboard!

Critical features of Cypress 10

Cypress 10 release was announced on June 2022. This was a feature-packed release with many community-request features like component testing, TypeScript improvements, improved onboarding experience, improved error messages, Cypress configuration files, and more.

To learn more, check out ChangeLog for a detailed list.

Component Testing

Let’s start with component testing. Component testing is directly integrated into the main Cypress application.

Testing applications to achieve full coverage could be done using many approaches. Major web frameworks focus on breaking applications into components to create a complex functional component. Component testing allows you to test components independently in isolation, and focuses on the functionality of the particular component providing more focused coverage.

End-to-end testing focuses on testing the entire application to ensure the application runs as expected while unit testing breaks down the application into smaller individual units of functions, methods, or modules tested in isolation.

Unit testing provides little interaction between components and the application, which tends to make debugging difficult.

The new Cypress 10 component testing provides component interaction between other components and the entire application. This is rendered in a real browser providing access to dev tools, and making debugging a lot easier during tests.

To learn more about component testing, check out GitHub Issue #21111.

To learn more about Cypress 10 and other included features, you can check out the announcement blog.

Cypress Config File

To provide a flexible and extensible configuration option for testing, Cypress 10 now supports multiple configuration file types, including TypeScript, CommonJS, or ESM Module configuration, and drop the cypress.json configuration file. The Cypress configuration file can be cypress.config.js, cypress.config.ts, cypress.config.cjs, or cypress.config.mjs file. 20643.

A configuration file is required in a project. Running cypress open will walk you through to set up your Cypress project with specific testing options for your project. 20643.

Cypress Onboarding UI Design

Project set up for Cypress 10 now takes you through a beautiful UI, built with Vue. Running cypress open renders the on-boarding UI with specific instructions for your test configuration, and allows you to choose between end-to-end testing or component testing.

Cypress 10.2.0

A minor version release of Cypress 10.2.0 was announced on Jun 21, 2022. This release focuses on machine compatibility for Apple and Linux distros.

Cypress is now available natively on Apple silicon. This means no extra system configuration with emulators, and approximately 2.5x faster testing environment on Apple devices including M1 and M2. 19908 20686

Cypress is now natively available on ARM64 and AArch64 systems running Linux 22252.

To learn more about the 10.2.0 release read Cypress 10.2.0: Run tests up to 2x faster on Apple silicon (M1)

Cypress 10.3.0

A minor version release of Cypress 10.3.0 was announced on Jun 28, 2022. This version focuses on improving the cloud testing developer experience workflow.

Cypress added actionable test data in the Cypress Dashboard from the test runs. Cypress Dashboard is a service by Cypress to provide access to recorded test results when running Cypress tests from a CI provider, giving insight to the tests which helps with tracking and debugging.

With Cypress 10.3.0, test result data are directly retrieved and cached whenever possible to provide real-time metrics for test coverage. New columns include #21250:

Latest runs to monitor, run, and fix tests locally within CI workflows. Average duration to help quickly identify and take action to improve the performance. To learn more check out Cypress 10.3.0: Speed up testing workflows with improved visibility into your test results

Conclusion

What do you think of these new features and the latest release?

Make sure to read the ChangeLogs for a complete list of features in the releases including bug fixes. To start using the latest Cypress, run npm install cypress@latest --save-dev from your 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)

Hassan Sani
@inidaname @inidaname

How to Run End-to-End Tests on Vercel Preview Deployments

How to Run End-to-End Tests on Vercel Preview Deployments End-to-end (E2E) tests are an essential part of modern web development. They simulate real user interactions and ensure your application works as expected in a live environment. When you're working with platforms like Vercel, which provide seamless deployment experiences, running E2E tests on preview deployments makes sense to catch any issues before merging your changes into the main branch. However, running E2E tests on preview deployments can be challenging as if the deployment isn’t ready when the tests start running, you’ll get errors when they should have succeeded. The Challenge: Timing Your E2E Tests Imagine you're working on a feature and pushing your changes to a branch. Vercel starts deploying the preview, and once that's done, you want to run your E2E tests automatically. But if the deployment isn't ready when the tests start, they might fail, and you'll be left wondering if the issue is with your code or the deployment process. Github Actions allow us to leverage a combination of actions that work together to ensure that your E2E tests only start once the Vercel deployment is ready. The Solution: Combining GitHub Actions for Seamless Testing To solve this problem, we can use two GitHub Actions in tandem: 1. vercel-preview-url: This action retrieves the preview URL of the Vercel deployment. It runs on push and pull request events, ensuring you get the exact URL of your deployment, which can then be used for further tests or other integrations. 2. github-action-await-vercel: This action waits until the Vercel deployment is marked as "READY". It continuously checks the deployment status, ensuring your tests only run once the deployment is fully prepared. ` Breaking Down the Workflow 1. Fetch the Preview URL: The vercel-preview-url action first retrieves the URL of the Vercel deployment. This URL is unique to the deployment, and we need to know it to run our E2E tests against the correct environment. This step ensures that we have the right URL before proceeding to the next steps. 2. Await Deployment Readiness: The github-action-await-vercel action waits for the deployment to be fully ready. It checks the deployment status at intervals (e.g., every 15 seconds) and only proceeds once the deployment is marked as "READY." This step ensures that your E2E tests don't run prematurely, preventing false failures. 3. Run E2E Tests: Once the deployment is ready, your E2E tests are executed against the live preview. By this point, you can be confident that the environment is fully set up, and any failures will likely be due to actual issues in the code rather than deployment timing. Why This Workflow Matters This workflow is essential for teams that rely on automated testing as part of their CI/CD pipelines. By waiting for the Vercel deployment to be fully ready, you minimize the risk of flaky tests that fail due to timing issues rather than code problems. This approach saves time and effort, as developers can focus on fixing real bugs rather than troubleshooting deployment issues. Moreover, this setup is flexible and can be adapted to various project needs. Whether you're running tests on a simple static site or a complex application, ensuring that your deployment is ready before running tests can dramatically improve the reliability of your CI/CD pipeline. Conclusion In modern web development, ensuring the reliability of your CI/CD pipeline is crucial. By leveraging GitHub Actions like vercel-preview-url and github-action-await-vercel, you can confidently run E2E tests on Vercel preview deployments. However, remember that the Vercel deployment can take some time to deploy, especially for larger projects, so use this approach wisely and ensure you only run it when necessary....

Sep 20, 2024

3 mins

InfrastructureVercelPlaywrightCypress

Enhancing Your Playwright Workflow: A Guide to the VSCode Extension

Introduction In my last post, Quick Guide to Playwright Fixtures: Enhancing Your Tests, I delved into some of the enhancements we've been implementing in our end-to-end (E2E) tests using Playwright. As I refine our testing strategies, I've come across a tool that has quickly become an essential part of my workflow: the Playwright VSCode extension. If you're like me and constantly looking for ways to streamline testing and debugging, you'll appreciate any tool that can make the process more efficient and enjoyable. That's where this extension comes in. It's not just about writing tests - it's about enhancing the entire development experience. In this post, I'll walk you through getting started with the Playwright VSCode extension, sharing some tips and tricks that have made a real difference in my day-to-day work. Installing the Extension & Basic Setup Before diving into the Playwright VSCode extension, it's essential to have Playwright installed on your machine. If you haven't done so already, you can quickly install it by running: ` This command will set up Playwright and ensure all necessary dependencies are installed. Once Playwright is ready, the VSCode extension will be installed next. Open Visual Studio Code, navigate to the Extensions view by clicking on the Extensions icon in the Activity Bar on the side of the window, and search for “Playwright”. The official extension, ID: ms-playwright.playwright / named: “Playwright Test for VSCode” by Microsoft, should appear at the top of the list. Click "Install," and you're all set. With the extension installed, you can start leveraging its powerful features to enhance your Playwright testing workflow within VSCode. Running the Tests and Identifying Outputs To run a test, simply open the test file in VSCode. The Playwright extension will automatically detect test files and display a "Run" icon next to each test and test suite. You can click on this icon to run individual tests or test suites. Alternatively, you can run all the tests in your project using the Playwright Test Explorer, accessible from the sidebar. Once you start running your tests, the extension provides real-time feedback within the editor. You'll see the status of each test - whether it passes, fails, or is skipped - right next to the corresponding test in your code. This immediate feedback loop is incredibly helpful for catching issues as you write your tests. The output of your tests will be displayed in the VSCode terminal. You'll see detailed information about each test run. Debugging Step-by-Step I find debugging particularly useful when a test fails unexpectedly or when I want to verify that certain actions are being performed as intended. Instead of guessing what might be wrong, I can see exactly what's going on in each test step, making debugging a much more straightforward and less frustrating process. To start debugging, you can easily set a breakpoint in your test file by clicking on the left margin next to the line number where you'd like the execution to pause. Once your breakpoints are in place, you can initiate the debug process by selecting the "Debug" option next to the test you'd like to investigate. Once the debugger is running, the extension allows you to step through your code, inspect variables, and evaluate expressions - all within VSCode. This real-time insight into your test execution is a game-changer, enabling you to pinpoint issues more effectively and confidently refine your tests. Using the Pick Locator Tool Another handy feature is the "Pick Locator" tool. If you've ever struggled with selecting the right element in your tests, this tool can be a time saver. It helps you generate reliable locators by letting you interact directly with the webpage elements you want to target. To use the Pick Locator tool, click the "Pick Locator" button in the Playwright Test Explorer. This will open a new window where you can navigate to the site you're testing. As you hover over elements on the page, the tool will suggest locators, allowing you to select the most appropriate one for your test. While the Pick Locator tool is handy, it’s important to ensure that the locators you generate are robust and maintainable. This is especially true when integrating them with the fixtures I discussed in my previous blog post. Combining the proper locators with well-designed fixtures can create more reliable and reusable test setups, ultimately making your E2E tests more efficient. Conclusion The Playwright VSCode extension has quickly become indispensable in my development workflow. It significantly enhanced my experience of writing and running Playwright tests. Whether you’re just starting with Playwright or looking to optimize your existing tests, this extension offers a range of features that can save you time and effort. Combining these tools with thoughtful test design, such as leveraging fixtures, you can create a more efficient and effective testing process. I hope this guide has given you a good overview of what the Playwright VSCode extension can do and how it can benefit your work. If you haven’t tried it yet, I highly recommend giving it a go. And as always, feel free to explore further and experiment with the features that best suit your needs....

Sep 6, 2024

5 mins

VSCodeTestingPlaywright

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

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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Cypress 10 - The Latest Release Details - Component Testing, Configuration Options

Critical features of Cypress 10

Component Testing

Cypress Config File

Cypress Onboarding UI Design

Cypress 10.2.0

Cypress 10.3.0

Conclusion

Hassan Sani

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How to Create Better Test Coverage Using Cypress 10

Introduction to Zod for Data Validation

Let's innovate together!

You might also like

How to Run End-to-End Tests on Vercel Preview Deployments

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How to Create Better Test Coverage Using Cypress 10

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