Beyond API Mocking

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Mocking is one of the best techniques to separate concerns during testing. When it comes to API mocking, we tend to either stub a request client or replace it with a mocked counterpart entirely. What we’re doing is altering the tested system so it makes requests to a different source, or doesn’t make them at all. That’s mainly because there was no better option. Until now.


In this talk, we’ll go through how to efficiently use API mocking that retains the integrity of your JavaScript application and results in more confident tests. On top of that, I’ll illustrate how to reuse the same mocks on different testing levels, as well as during development and debugging. All that with a single tool in your arsenal.

This talk has been presented at TestJS Summit - January, 2021, check out the latest edition of this JavaScript Conference.

FAQ

API mocking is a technique used in software testing to simulate the behaviors of API endpoints. It allows developers to substitute API communication, such as HTTP requests, with mock responses. This is crucial for ensuring that tests focus on the client-side logic without dependency on external servers, making tests more reliable and faster.

The two main approaches for implementing API mocking are using a mocking server and using a mock client. A mocking server involves setting up a standalone HTTP server that simulates the production server, while a mock client involves intercepting and substituting API calls within the application itself.

Using a Service Worker for API mocking allows requests to leave the app and get intercepted at the network level, closely mimicking real-world scenarios. This method improves test accuracy by ensuring that the application behavior during testing is identical to its behavior in production, without altering the system under test significantly.

MockServiceWorker (MSW) leverages Service Workers to intercept requests and provide mock responses without needing a separate server. It allows developers to write request handlers that specify how requests should be intercepted and responded to, facilitating easier and more accurate API mocking directly in the browser.

Yes, apart from testing, MSW can be used for development, prototyping, and debugging. It helps simulate backend services when they are not available or are under development, allows for the testing of third-party API integrations, and provides a controlled environment for reproducing and fixing data-related issues.

Future enhancements for MSW include improved support for GraphQL integrations, the introduction of WebSocket mocking, and the development of data modeling solutions. These features aim to broaden the scope and usability of MSW, catering to more diverse testing and development scenarios.

Artem Zakharchenko
Artem Zakharchenko
25 min
15 Jun, 2021

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Video Summary and Transcription
Today's Talk discusses API mocking and its role in testing. The speaker explores the advantages and disadvantages of server and client-side mocking, and introduces the use of service workers for mocking. The MockServiceWorker library (MSW) is presented as a solution that leverages service workers to intercept requests and provide mock responses. MSW is client-agnostic, widely used, and offers many features. The speaker also mentions upcoming improvements and encourages users to try MSW and provide feedback.

1. Introduction to API Mocking

Short description:

Hello, everybody. Thank you for joining. Today, I would love to talk with you about testing and specifically about API Mocking and the role it plays in it. Why do we write tests? Well, we write tests to gain confidence and ensure that the software we build is functional. To gain that confidence, we should test as a user and establish clear boundaries. Mocking is a tool that helps distribute these boundaries.

♪♪ Hello, everybody. Thank you for joining. I hope you are healthy and well, and would love to hear about API Mocking. My name is Artem, and I am a JavaScript engineer which has a huge love for open source. I've been doing open source for more than five years, during the course of which I was extremely lucky to author more than 20 packages that by this time have more than eight million downloads on NPM. And today I would love to talk with you about testing and specifically about API Mocking and the role it plays in it.

But before we begin, I'd love to ask you a question. Why do we write tests? Well, we certainly don't write them to gather code coverage. It can be useful at times, but unfortunately, it doesn't mean that our product works or works well. We are not writing tests to check each and every little piece of logic we wrote because that would be testing our code instead of testing the intention behind the code, which we shouldn't do. I think why we write tests is first of all, to gain confidence, to rest assured that the software we build is functional and our customers are enjoying and loving it. And to gain that confidence from testing, we should follow two principles. And the first one is to test as a user. And the user here doesn't mean customer necessarily. Of course, if you're having an e-commerce website and you want to double check the success scenarios in different pages, you will be performing user actions there. But let's say you're writing a test for a function or a class. Then the user for that class would be another developer. So you need to put their expectations against your class and write your test following by that expectations. I like this quote by Kenzie Dots that says, the more your test resembles the way your software is used, the more confidence they can give you. And I think it summarizes this principle pretty brilliantly. The other one principle that can gain us more confidence during tests is to establish clear boundaries. I think you're pretty familiar with this because this is the reason why we have different testing levels. So when we want to focus on a single unit of code, we write unit tests, then perhaps you want to check that pieces fit together nicely and we do some integration testing and we can wrap up with end-to-end tests to check the entire system. And I see mocking as a tool that distributes these boundaries. Let me give you an example. Let's say we have this orange square and we want to test it. Now, in a real application, this orange square probably does quite a few things and it may depend on other squares like this blue one. Now, because of this dependency, we can no longer focus our tests on the orange cube alone and we need to somehow account for the blue one. So this is where we can mock the blue one to substitute it with a seemingly compatible cube but it's going to be different. And because of this, we can control this dependency and connection between modules and make sure that our test of the orange one is focused.

2. API Mocking: Server vs Client

Short description:

API mocking allows us to substitute API communication, but it has some disadvantages. Using a mocking server requires pulling dependencies and ensuring server operability. Conditional URLs can lead to deviations between the test environment and production, resulting in potential issues for customers.

And API mocking is a technique that allows us to substitute API communication, so HTTP requests, in the same manner. There are two main practices when it comes to implementing API mocking in your projects.

The first one is to use a mocking server. This is a pretty straightforward setup and it means that you have a standalone HTTP server that will substitute a production one. And while it's fairly easy to set up and it has some sort of abstraction syntax to write the routes and responses, I think it has a few disadvantages. So, primarily, no matter what are you going to use, write your own server or use a third party library, you're going to end up pulling dependencies and the whole process will feel like you're writing an actual server but you're not doing so. Then you need to ensure the operability of your server, so it starts and stops at the right time before or after your tests, and then there are no runtime exceptions that can crash the tests. And the worst thing of a mocked server is conditional URLs. And this is what I mean by them. This is an abstract example of code where we have some fetch call to an API backend.com. Now, we don't want to hit that production URL during testing, so we probably introduced some environmental variable that says that, hey, if you're running under tests, just hit this other URL at localhost because this is where we have the mocked server running. Now, the issue with this is that during the test run, the code will never hit this line, which it does in production. And let's say we made a mistake here. We mistyped a protocol or we missed a few slashes or dots. Now, this is going to result into a perfectly passing test on CI while perfectly crashed app for our customers. And the reason that happened is because we introduced a deviation. So the app that run during test is slightly different than the one that runs on customer machines. And the more you alter the system under test, the more you're testing a different system entirely.

QnA

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