Component Testing With Vitest

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Testing is important. Proper unit tests can eliminate the chance for bugs to appear. But which testing framework will be suitable? Let’s explore how we can develop a reliable and efficient strategy for component development and testing with Vitest

This talk has been presented at TestJS Summit 2023, check out the latest edition of this Tech Conference.

FAQ

Maya Chavin is a Senior Software Engineer at Microsoft, working for a group called Microsoft Industry AI. She leverages different AI technologies to build industry-specific solutions with JetGPT, GPT, and other modules.

The focus of Maya Chavin's talk is on testing in software development, specifically using the VTest framework for unit and integration testing of React components.

VTest is a JavaScript and TypeScript unit testing framework developed by the VIT team. It is designed for fast testing with support for TypeScript and JSX out of the box and is compatible with other testing frameworks like Jest and Mocha.

Maya Chavin mentions several challenges in software testing, including code complexity, choosing the right testing framework, the learning curve associated with new frameworks, and ensuring that tests meet minimum coverage requirements.

Planning tests before coding is important because it helps ensure that the tests will cover the necessary functionalities and scenarios. It also helps in choosing the right testing framework and tools, and in identifying the types of tests needed for different parts of the project.

Maya Chavin discusses three types of tests: unit tests, which test individual pieces of code; integration tests, which test the interaction between different pieces of code; and end-to-end tests, which test the actual user interaction using real data.

Asynchronous code in testing can be handled by mocking asynchronous functions, using tools like VTest to spy on functions, and using the 'waitFor' function to ensure that asynchronous operations are completed before assertions are made.

The recommended approach is to split the component logic into hooks and test these hooks separately. This allows for easier testing and maintenance, as changes in one part of the logic won't affect the entire component.

Using data-test-id in testing helps ensure that test selectors remain stable and are not affected by changes in the component's class or ID attributes. This makes the tests more reliable and easier to maintain.

Maya Chavin recommends using additional tools like HappyDOM for a faster and more reliable DOM API, and Xscore React for accessibility testing of React components.

Maya Shavin
Maya Shavin
29 min
07 Dec, 2023

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Video Summary and Transcription

This Talk explores the challenges of choosing and learning testing frameworks, emphasizing the importance of planning, automation, and prioritizing unit testing. The VTEST framework is introduced as a fast and stable option for unit testing JavaScript and TypeScript code, with a focus on logic and mocking external dependencies. The Talk also covers testing React hooks, integration testing with TestingLibraryReact, component testing, and achieving code coverage. Best practices include performing accessibility tests, planning tests before coding, and using data test IDs for stability.
Available in Español: Pruebas de Componentes con Vitest

1. Introduction to Testing Frameworks

Short description:

Thank you! I'm Maya Chavin, a Senior Software Engineer at Microsoft working with Microsoft Industry AI. I hate tests, but we know we need them. Codepay complexity and choosing a testing framework are challenges. This talk is about another framework and its learning curve.

Thank you! Okay, so it's pretty early in the morning though and one minute, yep, it's buffering. How are you feeling today? All good? You have coffee? I actually got a sip of coffee and I'm still very cool. The weather is crazy to me.

Anyway, so before we deep dive into our talk, I just want to repeat what I was talking about myself. So I'm Maya Chavin, I'm a Senior Software Engineer at Microsoft. I'm working for a group called Microsoft Industry AI. So we do kind of like leverage different AI technologies to build industry-specific solutions with JetGPT, GPT, and all this module. I have my book published just two days ago, yes. So if you are and you haven't known Vue before, you want to learn Vue, yeah, check it out. And I was an open source maintainer. You can follow me at Maya Chavin or follow my blog post. I post article once in every blue moon, hopefully.

Anyway, testing. So yeah, we have to test, everyone knows that, right? I have a disclaimer before I move on. I hate tests. Yeah. I do hate tests. Every time when I come to tests, I hate tests. Before I come to test, I say, yeah, everyone have to write test, everyone, literally including me. And I always say to everyone in my team, you got to write tests. But when I go to write test myself, I like, come on, why do anyone want test? Well, you know, we know that we need test, but we always face the dilemma, and that's why we hate test, kind of. Codepay complexity. Anyone who works with a very large code page will know the pain when you need to write test. And you need to write test in order to make sure that your test will only check what happened in your code and not because someone else do something and then it affects your qualities of your code. Testing framework. You're not going to choose framework. What framework are you going to choose? And yes, this talk is about another framework. Yep. I know that. And learning curve.

2. Challenges of Testing Frameworks

Short description:

Every time we talk about a new testing framework, we switch from one to another because it's cooler and faster. But there's always a learning curve. Not everyone agrees, and APIs differ. The dilemma is ensuring 90% code coverage. If not, PRs won't be merged. It all comes down to time. How do we allocate time and effort to testing?

Every time we talk about a new testing framework, we switch from one testing framework to another because the other one is way cooler and faster. However, we always have a learning curve. Not everyone likes to agree, and not every API looks, feels, or does the same thing. This leads to a specific point of dilemma. Even if you pass all of this, you still need to make sure that your tests cover a minimum of 90% of your code base. If someone decides that 90% coverage is required, then 89% or 99% won't cut it. This can prevent your pull request from being merged, and it can be frustrating. Ultimately, this dilemma comes down to one thing: time. How are we going to allocate time and effort to testing? We need to do it, but how?

QnA

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