Skip to main content

Unit testing with coroutines

The coroutines API has already brought some innovation in the Android and Kotlin world. I always loved the idea of keeping it as simple as we all can. There is a saying around here that "Whoever talks to much, makes too much mistakes" and I see this a little bit related to Java's verbosity and also in the world of concurrency. It's said over and over again that concurrency is not simple and I couldn't agree more: You have to care about context, jobs running in parallel, cancelation, returning values etc.

I hope I gave my best in one of my previous articles explaining Kotlin Coroutines, therefore I will cover the testing tool of them today.

As usual, some might still fear testing, but I really find it so entertaining. But there is no new concept to add to software testing when talking about coroutines, except just defining a "default" TestCoroutineDispatcher which is only a CoroutineDispatcher which runs immediate and lazy code the same way. In other words, a Test Double for CoroutineDispatcher (not sure if it is a Fake).

So let's test. As explained we should be able to do it, once we have the dependency in our module:

After that we only need to add some small configurations for our testing to start, as described above:

Note: The coroutines testing API is still experimental,  so in order not to annotate all variables and methods with @ExperimentalCoroutinesApi just annotate the class under test (should save you time).

After that, the only new thing around here is the runBlockingTest clause (i like to call lambdas this way but it's a method) which of course is an imitation of  the runBlocking. You should be able to pass the testDispatcher as an argument but it's not mandatory:

And that's it.

Note: If you don't trust experimental API's yet, you are free to test with runBlocking even if it is not very much recommended that way (it could be a little redundant for this case). 


Since I already mentioned that concurrency is hard, and coroutines made it simple, there should be a nice tool to make testing them simple also. And the coroutines testing API is the answer. More about the dependency in the documentation page.

Stavro Xhardha.

Popular posts from this blog

What I learned from Kotlin Flow API

I used to check the docs and just read a lot about flows but didn't implement anything until yesterday. However, the API tasted really cool (even though some operations are still in Experimental state).Prerequisites: If you don't know RxJava it's fine. But a RxJava recognizer would read this faster.Cold vs Hot streamsWell, I really struggled with this concept because it is a little bit tricky. The main difference between cold and hot happened to be pretty simple: Hot streams produce when you don't care while in cold streams, if you don't collect() (or RxJava-s equivalent subscribe()) the stream won't be activated at all. So, Flows are what we call cold streams. Removing the subscriber will not produce data at all, making the Flows one of the most sophisticated asynchronous stream API ever (in the JVM world). I tried to make a illustration of hot and cold streams: Since I mentioned the word asynchronous this implies that they do support coroutines also. Flows vs…

Modularizing your Android app, breaking the monolith (Part 1)

Inspired by a Martin Fowlers post about Micro Frontends, I decided to break my monolithic app into a modular app. I tried to read a little more about breaking monolithic apps in Android, and as far as I got, I felt confident to share my experience with you. This will be some series of blog posts where we actually try to break a simple app into a modularized Android app.

Note: You should know that I am no expert in this, so if there are false statements or mistakes please feel free to criticize, for the sake of a better development. 

What do you benefit from this approach:
Well, people are moving pretty fast nowadays and delivery is required faster and faster. So, in order to achieve this, modularising Android apps is really necessary.You can share features across different apps. Independent teams and less problems per each.Conditional features update.Quicker debugging and fixing.A feature delay doesn't delay the whole app. As per writing tests, there is not too much difference about…

From Gson to Moshi, what I learned

There is no doubt that people are getting away from GSON and I agree with those reasons too. The only advantage GSON has over other parsing libraries is that it takes a really short amount of time to set up. Furthermore, the most important thing is that Moshi is embracing Kotlin support.

First let's implement the dependency:
implementation("com.squareup.moshi:moshi:1.8.0") It's not a struggle to migrate to Moshi. It's really Gson look-a-like. The only thing to do is annotate the object with @field:Json instead of @SerializedName (which is Gsons way for JS representation):

data class User( //GSON way @SerializedName("name") val name: String, @SerializedName("user_name") val userName: String, @SerializedName("last_name") val lastName: String, @SerializedName("email") val email: String ) data class User( //Moshi way @field:Json(name = "name") val name: String, @field:Json(name = "user_name…