Instrumented Testing with Dagger2 - how to reference fake repository? - android

My goal is to test an app with Espresso.
First Screen Activity depends on settings received from a Repository. Repository checks whether the user saved a location preference in Shared Preferences. If he has, it moves on to the Main Activity. That's the part of logic that I am trying to test.
I want to substitute fake repository (HashMap representing shared preferences) to achieve consistency. Tests run and pass if the repository is empty (base state). However, I want to test whether the app moves forward if the location is saved.
Test in question:
#Test
fun onLaunch_withLocationSaved_checkMainActivityIsShown() {
fakeRepository.saveLocation("40,80")
ActivityScenario.launch(FirstScreenActivity::class.java)
onView(withText(R.string.welcome_message)).check(matches(not(isDisplayed())))
}
How do I get a reference to fakeRepository to be able to save location that ViewModel will read from?
If it's created (which defeats the point of injection) like this:
#Before
fun init() {
fakeRepository = FakeSimpleRepository()
fakeRepository.saveLocation("")
viewModel = FirstScreenViewModel(fakeRepository)
}
The viewmodel gets injected with a different fakeRepository object (I compared addresses with a debugger).
I followed Google's codelabs and official documentation how to set up Dagger with my app. Their examples do not show how to reference the repository though to make changes.

This blog cover what you want to achieve
The idea is that you have to override your dagger module to inject the mock object. Then you create a custom runner class to override the application class.

Related

Why does by repository Flow not update my viewModels livedata?

So currently I have a Dao with a function that emits a Flow<>
#Query("SELECT * FROM ${Constants.Redacted}")
fun loadAllContacts(): Flow<List<Redacted>>
I am calling this from a repository like so
val loadAllContacts: Flow<List<Redacted>> = contactDao.loadAllContacts()
I am injecting the repository into the viewModel's constructor, and then at the top of my viewModel I have a val like so
val contacts: LiveData<List<Redacted>> = contactRepository.loadAllContacts.asLiveData()
Which is being observed in my Activity like so
viewModel.contacts.observe(this) { contacts ->
viewModel.onContactsChange(contacts)
}
My thinking is that the Flow is converted to a LiveData, and then I can observe this LiveData from my activity and kick off this function to actually update the viewModel upon the data being updated.
For now onContactsChange just looks like
fun onContactsChange(list: List<Redacted>) {
Timber.i("VIEW UPDATE")
}
The problem is that I only see this Timber log upon opening the activity, and never again. I verified that data IS going into my database, and I verified that an insert occurred successfully while the activity & viewModel are open. But I never see the log from onContactsChange again. When I close the activity, and reopen it, I do see my new data, so that is another reason I know my insert is working correctly.
I would like to add that I am using a single instance (singleton) of my repository, and I think I can verify this by the fact that I can see my data at all, at least when the view is first made.
Figured it out:
Note: If your app runs in a single process, you should follow the singleton design pattern when instantiating an AppDatabase object. Each RoomDatabase instance is fairly expensive, and you rarely need access to multiple instances within a single process.
If your app runs in multiple processes, include enableMultiInstanceInvalidation() in your database builder invocation. That way, when you have an instance of AppDatabase in each process, you can invalidate the shared database file in one process, and this invalidation automatically propagates to the instances of AppDatabase within other processes.
It's a little bit hard to follow your question, but I think I see the overall problem with your Flow object not updating the way you want it too.
Following this quick tutorial, it seems that first you should declare your Flow object inside your Repository the same way you're already doing
val loadAllContacts: Flow<List<Redacted>> = contactDao.loadAllContacts()
and have your VM 'subscribe' to it by using the collect coroutine which would then allow you to dump all this data into a MutableLiveData State
data class YourState(..)
val state = MutableLiveData<YourState>()
init {
contactRepository.loadAllContacts().collect {
if (it.isNotEmpty()) {
state.postValue(YourState(
...
)
}
}
}
that your Activity/Fragment could then observe for changes
viewModel.state.observe(.. { state ->
// DO SOMETHING
})
P.S. The tutorial also mentions that because of how Dao's work, you might be getting updates for even the slightest of changes, but that you can use the distinctUntilChanged() Flow extension function to get more specific results.

Where to do Arrow.io IO.runUnsafeSync() ? ViewModel or Activity/Fragment?

I'm trying to learn the Arrow library and improve my functional programming by transitioning some of my Android Kotlin code from more imperative style to functional style. I've been doing a type of MVI programming in the application to make testing simpler.
"Traditional" Method
ViewModel
My view model has a LiveData of the view's state plus a public method to pass user interactions from the view to the viewmodel so the view model can update state in whatever way is appropriate.
class MyViewModel: ViewModel() {
val state = MutableLiveData(MyViewState()) // MyViewState is a data class with relevant data
fun instruct(intent: MyIntent) { // MyIntent is a sealed class of data classes representing user interactions
return when(intent) {
is FirstIntent -> return viewModelScope.launch(Dispatchers.IO) {
val result = myRoomRepository.suspendFunctionManipulatingDatabase(intent.myVal)
updateStateWithResult(result)
}.run { Unit }
is SecondIntent -> return updateStateWithResult(intent.myVal)
}
}
}
Activity
The Activity subscribes to the LiveData and, on changes to state, it runs a render function using the state. The activity also passes user interactions to the view model as intents (not to be confused with Android's Intent class).
class MyActivity: AppCompatActivity() {
private val viewModel = MyViewModel()
override fun onCreateView() {
viewModel.state.observe(this, Observer { render(it) })
myWidget.onClickObserver = {
viewModel.instruct(someIntent)
}
}
private fun render(state: MyViewState) { /* update view with state */ }
}
Arrow.IO Functional Programming
I'm having trouble finding examples that aren't way over my head using Arrow's IO monad to make impure functions with side effects obvious and unit-testable.
View Model
So far I have turned my view model into:
class MyViewModel: ViewModel() {
// ...
fun instruct(intent: MyIntent): IO<Unit> {
return when(intent) {
is FirstIntent -> IO.fx {
val (result) = effect { myRoomRepository.suspendFunctionManipulatingDatabase(intent.myVal) }
updateStateWithResult(result)
}
is SecondIntent -> IO { updateStateWithResult(intent.myVal) }
}
}
}
I do not know how I am supposed to make this IO stuff run in Dispatcher.IO like I've been doing with viewModelScope.launch. I can't find an example for how to do this with Arrow. The ones that make API calls all seem to be something other than Android apps, so there is no guidance about Android UI vs IO threads.
View model unit test
Now, because one benefit I'm seeing to this is that when I write my view model's unit tests, I can have a test. If I mock the repository in order to check whether suspendFunctionManipulatingDatabase is called with the expected parameter.
#Test
fun myTest() {
val result: IO<Unit> = viewModel.instruct(someIntent)
result.unsafeRunSync()
// verify suspendFunctionManipulatingDatabase argument was as expected
}
Activity
I do not know how to incorporate the above into my Activity.
class MyActivity: AppCompatActivity() {
private val viewModel = MyViewModel()
override fun onCreateView() {
viewModel.state.observe(this, Observer { render(it) })
myWidget.onClickObserver = {
viewModel.instruct(someIntent).unsafeRunSync() // Is this how I should do it?
}
}
// ...
}
My understanding is anything in an IO block does not run right away (i.e., it's lazy). You have to call attempt() or unsafeRunSync() to get the contents to be evaluated.
Calling viewModel.instruct from Activity means I need to create some scope and invoke in Dispatchers.IO right? Is this Bad(TM)? I was able to confine coroutines completely to the view model using the "traditional" method.
Where do I incorporate Dispatchers.IO to replicate what I did with viewModelScope.launch(Dispatchers.IO)?
Is this the way you're supposed to structure a unit test when using Arrow's IO?
That's a really good post to read indeed. I'd also recommend digging into this sample app I wrote that is using ArrowFx also.
https://github.com/JorgeCastilloPrz/ArrowAndroidSamples
Note how we build the complete program using fx and returning Kind at all levels in our architecture. That makes the code polymorphic to the type F, so you can run it using different runtime data types for F at will, depending on the environment. In this case we end up running it using IO at the edges. That's the activity in this case, but could also be the application class or a fragment. Think about this as what'd be the entry points to your apps. If we were talking about jvm programs the equivalent would be main(). This is just an example of how to write polymorphic programs, but you could use IO.fx instead and return IO everywhere, if you want to stay simpler.
Note how we use continueOn() in the data source inside the fx block to leave and come back to the main thread. Coroutine context changes are explicit in ArrowFx, so the computation jumps to the passed thread right after the continueOn until you deliberately switch again to a different one. That intentionally makes thread changes explicit.
You could inject those dispatchers to use different ones in tests. Hopefully I can provide examples of this soon in the repo, but you can probably imagine how this would look.
For the syntax on how to write tests note that your program will return Kind (if you go polymorphic) or IO, so you would unsafeRunSync it from tests (vs unsafeRunAsync or unsafeRunAsyncCancellable in production code since Android needs it to be asynchronous). That is because we want our test to be synchronous and also blocking (for the latter we need to inject the proper dispatchers).
Current caveats: The solution proposed in the repo still doesn't care of cancellation, lifecycle or surviving config changes. That's something I'd like to address soon. Using ViewModels with a hybrid style might have a chance. This is Android so I'd not fear hybrid styles if that brings better productivity. Another alternative I've got in mind would maybe be something a bit more functional. ViewModels end up retaining themselves using the retain config state existing APIs under the hood by using the ViewModelStore. That ultimately sounds like a simple cache that is definitely a side effect and could be implemented wrapped into IO. I want to give a thought to this.
I would definitely also recommend reading the complete ArrowFx docs for better understanding: https://arrow-kt.io/docs/fx/ I think it would be helpful.
For more thoughts on approaches using Functional Programming and Arrow to Android you can take a look to my blog https://jorgecastillo.dev/ my plan is to write deep content around this starting 2020, since there's a lot of people interested.
In the other hand, you can find me or any other Arrow team maintainers in the Kotlinlang JetBrains Slack, where we could have more detailed conversations or try to resolve any doubts you can have https://kotlinlang.slack.com/
As a final clarification: Functional Programming is just a paradigm that resolves generic concerns like asynchrony, threading, concurrency, dependency injection, error handling, etc. Those problems can be found on any program, regardless of the platform. Even within an Android app. That is why FP is an option as valid for mobile as any other one, but we are still into explorations to provide the best APIs to fulfill the usual Android needs in a more ergonomic way. We are in the process of exploration in this sense, and 2020 is going to be a very promising year.
Hopefully this helped! Your thoughts seem to be well aligned with how things should work in this approach overall.

Unit test a helper class around SharedPreference

I have a helper class to save user object to shared preferences. I have used a serialize(): String function and a create(serializedString: String) function in my User data model. They use GSon serializer and are working good as suggested by the unit tests on them.
Now my helper class is called SharedPreferenceUserStore.kt which takes a Context object. The code is:
class SharedPreferenceUserStore(context: Context) {
companion object {
val TAG = SharedPreferenceUserStore::class.java.simpleName
}
var userLocalSharedPref: SharedPreferences =
context.getSharedPreferences(USER_LOCAL_STORE_SHARED_PREF_NAME, Context.MODE_PRIVATE)
/*
Store the required data to shared preference
*/
#SuppressLint("ApplySharedPref")
fun storeUserData(user: User) {
val userLocalDatabaseEditor = userLocalSharedPref.edit()
val serializedData = user.serialize()
userLocalDatabaseEditor.putString(
USER_LOCAL_STORE_SHARED_PREF_SERIALIZED_DATA_KEY,
serializedData
)
if (userLocalDatabaseEditor.commit()) {
Log.d(TAG, " Store Commit return true")
}
}
/*
Clear all the locally stored data from the shared pref
*/
#SuppressLint("ApplySharedPref")
fun clearUserData() {
val userLocalDatabaseEditor = userLocalSharedPref.edit()
userLocalDatabaseEditor.clear()
userLocalDatabaseEditor.commit()
}
fun getLoggedInUser(): User? {
val stringUser = userLocalSharedPref.getString(
USER_LOCAL_STORE_SHARED_PREF_SERIALIZED_DATA_KEY, "")
return if (stringUser==null || stringUser == ""){
null
} else{
User.create(stringUser)
}
}
And I have written some unit tests for this helper class as follows:
#RunWith(JUnit4::class)
class SharedPreferenceUserStoreTest {
lateinit var sharedPreferenceUserStore: SharedPreferenceUserStore
lateinit var user: User
//to be mocked
lateinit var sharedPreferences: SharedPreferences
lateinit var sharedPreferencesEditor: SharedPreferences.Editor
lateinit var context: Context
#Before
fun setUp() {
//mocking Context and SharedPreferences class
context = mock(Context::class.java)
sharedPreferences = mock(SharedPreferences::class.java)
sharedPreferencesEditor = mock(SharedPreferences.Editor::class.java)
//specifying that the context.getSharedPreferences() method call should return the mocked sharedpref
`when`<SharedPreferences>(context.getSharedPreferences(anyString(), anyInt()))
.thenReturn(sharedPreferences)
//specifying that the sharedPreferences.edit() method call should return the mocked sharedpref editor
`when`(sharedPreferences.edit()).thenReturn(sharedPreferencesEditor)
//specifying that the sharedPreferencesEditor.putString() method call should return the mocked sharedpref Editor
`when`(sharedPreferencesEditor.putString(anyString(), anyString())).thenReturn(
sharedPreferencesEditor
)
`when`(sharedPreferences.getString(anyString(), anyString())).thenReturn("")
//instantiating SharedPreferenceUserStore from the mocked context
sharedPreferenceUserStore = SharedPreferenceUserStore(context)
user = User(
35,
"Prashanna Bhandary",
"prashanna.bhandary#gmail.com",
"dd58a617ea618010c2052cb54079ad67.jpeg",
"98********",
"test address 01",
1,
"yes",
"2019-08-30 04:56:43",
"2019-08-30 05:14:47",
0
)
}
#After
fun tearDown() {
}
#Test
fun passUser_storeUserData() {
sharedPreferenceUserStore.storeUserData(user)
verify(sharedPreferencesEditor).putString(
Constants.USER_LOCAL_STORE_SHARED_PREF_SERIALIZED_DATA_KEY,
user.serialize()
)
verify(sharedPreferencesEditor).commit()
}
#Test
fun testClearUserData() {
sharedPreferenceUserStore.clearUserData()
verify(sharedPreferencesEditor).clear()
}
#Test
fun testGetLoggedInUser_storeNotCalled() {
//calling getLoggedInUser() without calling storeUserData() should give null
assertEquals(null, sharedPreferenceUserStore.getLoggedInUser())
//verify that getString() was called on the shared preferences
verify(sharedPreferences).getString(Constants.USER_LOCAL_STORE_SHARED_PREF_SERIALIZED_DATA_KEY, "")
}
#Test
fun testGetLoggedInUser_storeCalled(){
//call getLoggedInUser(), we are expecting null
assertNull(sharedPreferenceUserStore.getLoggedInUser())
//verify that getString() was called on the shared preferences
verify(sharedPreferences).getString(Constants.USER_LOCAL_STORE_SHARED_PREF_SERIALIZED_DATA_KEY, "")
}
}
As I am really new to Unit Testing and Mocking libraries like Mockito. Now my question is are my tests any good? and I wanted to test if the getLoggedInUser() funciton of my helper class is doing what it is supposed to do (ie. get logged in user if shared pref has it), how do I do that?
In addition do suggest me any improvements I can make to my test or the helper class itself. Thank you.
Judging your test for what it is - A unit test running on a host machine with Android dependencies mocked with Mockito - it looks fine and like what you would expect.
The benefit-to-effort ratio of such tests are debatable, though. Personally I think it would be more valuable to run such a test against the real SharedPreferences implementation on a device, and assert on actual side effects instead of verifying on mocks. This has a couple of benefits over mocked tests:
You don't have to re-implement SharedPreferences with mocking
You know that SharedPreferenceUserStore will work with the real SharedPreferences implementation
But, such tests also have a debatable benefit-to-effort ratio. For a solo developer project, think about what kind of testing that is most important. Your time is limited so you will only have time to spend on writing the most important kind of tests.
The most important kinds of tests are the ones that test your app in the same way your users will use it. In other words, write high-level UI Automator tests. You can write how many mocked or on-device unit tests as you want. If you don't test that your entire app as a whole works, you will not know that it works. And if you don't know that your app as a whole works, you can't ship it. So in some way you have to test your app in its entirety. Doing it manually quickly becomes very labour intensive as you add more and more functionality. The only way to continually test your app is to automate the high-level UI testing of your app. That way you will also get code coverage that matters.
One big benefit of high-level UI testing that is worth pointing out is that you don't have to change them whenever you change some implementation detail in your app. If you have lots of mocked unit tests, you will have to spend a lot of time to refactor your unit tests as you refactor the real app code, which can be very time consuming, and thus a bad idea if you are a solo developer. Your UI Automator tests do not depend on low-level implementation details and will thus remain the same even if you change implementation details.
For example, maybe in the future you want to use Room from Android Jetpack to store your user data instead of SharedPreference. You will be able to do that without changing your high level UI tests at all. And they will be a great way to regression test such a change. If all you have are mocked unit tests, it will be a lot of work to rewrite all relevant unit tests to work with Room instead.
I agree with what #Enselic say about favoring Integration Test over Unit Tests.
However I disagree with his statement that this mockito test looks fine.
The reason for that is that (almost) every line in your code under test involves a mock operation. Basically mocking the complete method would have the same result.
What you are doing in your test is testing that mockito works as expected, which is something you should not need to test.
On the other hand your test is a complete mirror of the implementation itself. Which means everytime you refactor something, you have to touch the test. Preferably would be a black box test.
If you use Mockito you should try to restrict its use to methods that actually do something (that is not mocked).
Classes that generally should be mocked for testing purposes are dependencies that interact with external components (like a database or a webservice), however in these cases you are normally required to have Integration Tests as well.
And if your Integration-Tests already cover most part of the code, you can check whether you want to add a test using a mock for those parts that are not covered.
I have no official source for what I am trying to express, its just based on my experience (and therefore my own opinion). Treat it as such.
There is not much that can be said regarding the tests that guys before me haven't said.
However, one thing that you might want to consider is refactoring your SharedPreferenceUserStore to accept not Context(which is quite a huge thing, and if not handled properly could lead to unforeseen issues and/or memory leaks), but rather SharedPreferences themselves. This way, your class, that deals only with updating the prefs doesn't have access to more than it should.

Android MVVM App Architecture: How to set up FirebaseFirestore as Repository

I want to create a app with the new architecture components and i already set up the views and the ViewModel. At the moment my app performs all Firestore queries in the ViewModel and it works to some extent. Google recommends that you should provide a Repository that caches some data and decides whether to fetch new data. This makes perfectly sense for my application since a have several Fragments nested in my MainActivity and lots of other activites.
I decided to implement the repository and created a Kotlin Object (Singleton) for my repository. As a consequence i got the warning that i should not store a FirebaseFirestore instance in it because it contains a Context field (i need an instance to assign snapshotListeners).
Do not place Android context classes in static fields; this is a memory leak (and also breaks Instant Run)
I completely understand this warning but i wonder how i should implement the Repository pattern with Firebase in my app without being in danger of causing a memory leak? Since Firebase and the new Architecure Components/Guidlines are both from Google i assume there are designed to work together but after doing some research i wasn't able to figure it out.
Does anyone know an effective way to implement a repository with Firebase snapshotListeners?
It's been a while since I asked this question. Meanwhile, I have found a great way to solve this problem. The best way is to make use of the repository pattern and Dependency Injection.
That means you have a class with a private field firebaseFirestore that implements an interface that defines all database operations (RemoteRepository in my case).
The class itself is provided as a Singelton via Dependency Injection.
class FirebaseRepository : RemoteRepository {
private val firebaseFirestore = FirebaseFirestore.getInstance()
override suspend fun saveSomething(...) {
...
}
override suspend fun getSomething(id: String) : T {
return ...
}
}

Lazy Injection with Dagger 2 on Android

I’m new to Dagger 2. I have this scenario, I wan't to inject an object across my app (in presenters, in api)
I do not have a way to provide it initially. It is not created till after authentication at some stage in my app.
From the documentation http://google.github.io/dagger/
I see Lazy loading might be a way to solve this e.g
#Inject
Lazy<Grinder> lazyGrinder;
and then get the value like this using:
lazyGrinder.get().grind();
My questions are:
Can I safely swap the object after this with a new one?
Are there any other recommended ways to do this?
Thanks
This isn't a good match for Lazy. Lazy is a great way to delay expensive object initialization, but it implies some semantics that you don't want or need, particularly regarding the "safely swap" behavior you want.
To put it simply, Lazy is a Provider wrapper that memoizes locally:
If you never call get, Dagger never creates the object in question.
The first call to get creates and stores the object instance.
The second call to get returns the same instance, and so on forever, regardless of whether the object was marked as Singleton.
This makes Lazy an excellent choice for an expensive object that would otherwise be a field (but may never be used). However, if the reference is likely to change (as your will), Lazy will simply be confusing: It will store the value at first use and never locally update, so multiple out-of-date copies might be floating around in your application regardless of what the "right" value is at any given time.
To borrow the use of Grinder from your example, better solutions include:
Using a #Provides method that returns a field in a Module, which can be updated later. You'll need to inject Provider<Grinder> for every long-lived object instance, because injected references to Grinder alone won't update. This still might be the best bet if you have a lot of short-lived objects.
The reference is implicitly singleton, but is not annotated as such, because you're controlling the instance yourself. Dagger will call your getGrinder method frequently.
#Module public class YourModule {
private Grinder grinder;
public void setGrinder(Grinder grinder) {
this.grinder = grinder;
}
#Provides public Grinder getGrinder() {
return grinder;
}
}
/* elsewhere */
YourModule module = new YourModule();
YourComponent component = DaggerYourComponent.builder()
.yourModule(module)
.build();
/* ... */
module.setGrinder(latestAndGreatestGrinder);
As EpicPandaForce mentioned in the comments, create/bind a singleton GrinderHolder, GrinderController, or AtomicReference object that provides the current instance and allows for updating. That way it's impossible to inject a Grinder directly, but easy and obvious to inject the object that fetches the current correct Grinder. If your singleton GrinderHolder implementation doesn't create the Grinder until the first time you ask for it, then you have effectively created a Lazy singleton on your own.
If you aren't able to provide the object at the time of Component creation, don't add it to your Component graph! That is asking for confusing graph dependencies and inconsistency. A better solution to what you are considering is a #Subcomponent approach, which allows you to create a new component which inherits the dependencies from the parent, but also adds new one. Here's an example:
#Component
interface RegularComponent {
#AppInstanceId String appInstanceId(); // unique per app install; not related to logging in
AuthenticatedComponent newAuthenticatedComponent();
}
#Subcomponent
interface AuthenticatedComponent {
Set<Friend> friends();
#AccountId String accountId();
}
Here, the #AccountId in the subcomponent could use the appInstanceId to provide the account ID (if it needed to) since the Subcomponent shares dependencies with its parent component.
If you need to supply state to your modules for the subcomponent (with the accountId, auth token, etc) feel free to pass it in as a parameter to the #Module and store it in a private final field. You can read more on how to supply subcomponent modules in the documentation.

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