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Use observe for a variable that updated inside another observe in Kotlin

I am trying first handle the response from API by using observe. Later after observing the handled variable I want to save it to database.
The variable tokenFromApi is updated inside tokenResponseFromApi's observer. Is it possible to observe tokenFromApi outside the observer of tokenResponseFromApi? When debugged, the code did not enter inside tokenFromApi observer when the app started.
override fun onViewCreated(view: View, savedInstanceState: Bundle?) {
var tokenResponseFromApi: LiveData<String>? = MutableLiveData<String>()
var tokenFromApi: LiveData<TokenEntity>? = MutableLiveData<TokenEntity>()
tokenResponseFromApi?.observe(viewLifecycleOwner, Observer {
tokenResponseFromApi ->
if (tokenResponseFromApi != null) {
tokenFromApi = viewModel.convertTokenResponseToEntity(tokenResponseFromApi, dh.asDate)
}
})
tokenFromApi?.observe(viewLifecycleOwner, Observer {
tokenFromApi ->
if (tokenFromApi != null) {
viewModel.saveTokenToDB(repo, tokenFromApi)
}
})
}

Your problem is that you're registering the observer on tokenFromApi during setup, and when you get your API response, you're replacing tokenFromApi without registering an observer on it. So if it ever emits a value, you'll never know about it. The only observer you have registered is the one on the discarded tokenFromApi which is never used by anything
Honestly your setup here isn't how you're supposed to use LiveData. Instead of creating a whole new tokenFromApi for each response, you'd just have a single LiveData that things can observe. When there's a new value (like an API token) you set that on the LiveData, and all the observers see it and react to it. Once that's wired up, it's done and it all works.
The way you're doing it right now, you have a data source that needs to be taken apart, replaced with a new one, and then everything reconnected to it - every time there's a new piece of data, if you see what I mean.
Ideally the Fragment is the UI, so it reacts to events (by observing a data source like a LiveData and pushes UI events to the view model (someone clicked this thing, etc). That API fetching and DB storing really belongs in the VM - and you're already half doing that with those functions in the VM you're calling here, right? The LiveDatas belong in the VM because they're a source of data about what's going on inside the VM, and the rest of the app - they expose info the UI needs to react to. Having the LiveData instances in your fragment and trying to wire them up when something happens is part of your problem
Have a look at the App Architecture guide (that's the UI Layer page but it's worth being familiar with the rest), but this is a basic sketch of how I'd do it:
class SomeViewModel ViewModel() {
// private mutable version, public immutable version
private val _tokenFromApi = MutableLiveData<TokenEntity>()
val tokenFromApi: LiveData<TokenEntity> get() = _tokenFromApi
fun callApi() {
// Do your API call here
// Whatever callback/observer function you're using, do this
// with the result:
result?.let { reponse ->
convertTokenResponseToEntity(response, dh.asDate)
}?.let { token ->
saveTokenToDb(repo, token)
_tokenFromApi.setValue(token)
}
}
private fun convertTokenResponseToEntity(response: String, date: Date): TokenEntity? {
// whatever goes on in here
}
private fun saveTokenToDb(repo: Repository, token: TokenEntity) {
// whatever goes on in here too
}
}
so it's basically all contained within the VM - the UI stuff like fragments doesn't need to know anything about API calls, whether something is being stored, how it's being stored. The VM can update one of its exposed LiveData objects when it needs to emit some new data, update some state, or whatever - stuff that's interesting to things outside the VM, not its internal workings. The Fragment just observes whichever one it's interested in, and updates the UI as required.
(I know the callback situation might be more complex than that, like saving to the DB might involve a Flow or something. But the idea is the same - in its callback/result function, push a value to your LiveData as appropriate so observers can receive it. And there's nothing wrong with using LiveData or Flow objects inside the VM, and wiring those up so a new TokenEntity gets pushed to an observer that calls saveTokenToDb, if that kind of pipeline setup makes sense! But keep that stuff private if the outside world doesn't need to know about those intermediate steps

Changing Data Class From Live Data

I have a BaseViewModel that basically has the function to get the user data like so:
abstract class BaseViewModel(
private val repository: BaseRepository
) : ViewModel() {
private var _userResponse: MutableLiveData<Resource<UserResponse>> = MutableLiveData()
val userResponse: LiveData<Resource<UserResponse>> get() = _userResponse
fun getUserData() = viewModelScope.launch {
_userResponse.value = Resource.Loading
_userResponse.value = repository.getLoggedInUserData()
}
}
In my Fragment, I access this data by just calling viewModel.getUserData(). This works. However, I'd like to now be able to edit the data. For example, the data class of UserResponse looks like this:
data class UserResponse(
var id: Int,
var username: String,
var email: String
)
In other fragments, I'd like to edit username and email for example. How do I do access the UserResponse object and edit it? Is this a good way of doing things? The getUserData should be accessed everywhere and that is why I'm including it in the abstract BaseViewModel. Whenever the UserResponse is null, I do the following check:
if (viewModel.userResponse.value == null) {
viewModel.getUserData()
}

If you want to be able to edit the data in userResponse, really what you're talking about is changing the value it holds, right? The best way to do that is through the ViewModel itself:
abstract class BaseViewModel(
private val repository: BaseRepository
) : ViewModel() {
private var _userResponse: MutableLiveData<Resource<UserResponse>> = MutableLiveData()
val userResponse: LiveData<Resource<UserResponse>> get() = _userResponse
fun setUserResponse(response: UserResponse) {
_userResponse.value = response
}
...
}
This has a few advantages - first, the view model is responsible for holding and managing the data, and provides an interface for reading, observing, and updating it. Rather than having lots of places where the data is manipulated, those places just call this one function instead. That makes it a lot easier to change things later, if you need to - the code that calls the function might not need to change at all!
This also means that you can expand the update logic more easily, since it's all centralised in the VM. Need to write the new value to a SavedStateHandle, so it's not lost if the app goes to the background? Just throw that in the update function. Maybe persist it to a database? Throw that in. None of the callers need to know what's happening in there
The other advantage is you're actually setting a new value on the LiveData, which means your update behaviour is consistent and predictable. If the user response changes (either a whole new one, or a change to the current one) then everything observeing that LiveData sees the update, and can decide what to do with it. It's less brittle than this idea that one change to the current response is "new" and another change is "an update" and observers will only care about one of those and don't need to be notified of the other. Consistency in how changes are handled will avoid bugs being introduced later, and just make it easier to reason about what's going on
There's nothing stopping you from updating the properties of the object held in userResponse, just like there's nothing stopping you from holding a List in a LiveData, and adding elements to that list. Everything with a reference to that object will see the new data, but only if they look at it. The point of LiveData and the observer pattern is to push updates to observers, so they can react to changes (like, say, updating text displayed in a UI). If you change one of the vars in that data class, how are you going to make sure everything that needs to see those changes definitely sees them? How can you ensure that will always happen, as the app gets developed, possibly by other people? The observer pattern is about simplifying that logic - update happens, observers are notified, the end
If you are going to do things this way, then I'd still recommend putting an update function in your VM, and let that update the vars. You get the same benefits - centralising the logic, enabling things like persistence if it ever becomes necessary, etc. It could be as simple as
fun setUserResponse(response: UserResponse) {
_userResponse.value?.run {
id = response.id
username = response.username
email = response.email
}
}
and if you do decide to go with the full observer pattern for all changes later, everything is already calling the function the right way, no need for changes there. Or you could just make separate updateEmail(email: String) etc functions, whatever you want to do. But putting all that logic in the VM is a good idea, it's kinda what it's there for
Oh and you access that object through userResponse.value if you want to poke at it - but like I said, better to do that inside a function in the VM, keep that implementation detail, null-safety etc in one place, so callers don't need to mess with it

The ideal way to update userResponse you should change/edit _userResponse so that your userResponse we'll give you the updated data.
it should be something like this
_userResponse.value = Resource<UserResponse>()

How to know when job from viewModel is done

I am trying to figure out how jobs with coroutines work. Basically, I want to launch this coroutine from FirstFragment and after that navigate to SecondFragment and get notified when this job is done. I call getData() in FirstFragment onViewCreated() and navigate to SecondFragment. Whether I write getData().isCompleted or getData().invokeOnCompletion { } in SecondFragment nothing happens. I don't know if I am missing something or not starting job correctly or something else.
private val _data = MutableStateFlow<GetResource<String>?>(null)
val data: StateFlow<GetResource<String>?> = _data
fun getData() = viewModelScope.launch {
repository.getData().collect {
_data.value = it
}
}

A Flow from a database never completes because it is supposed to monitor the database for changes indefinitely. It only stops when the coroutine is cancelled. Therefore the Job that collects such a Flow will never complete. Also, if you call getData() on the repo again, you are getting a new Flow instance each time.
Regardless of what you're doing, you need to be sure you are using the same ViewModel instance between both fragments by scoping it to the Activity. (Use by activityViewModels() for example.) This is so the viewModelScope won't be cancelled during the transition between Fragments.
If all you need is a single item from the repo one time, probably the simplest thing to do would be to expose a suspend function from the repo instead of a Flow. Then turn it into a Deferred. Maybe by making it a Lazy, you can selectively decide when to start retrieving the value. Omit the lazy if you just want to start retrieving the value immediately when the first Fragment starts.
// In the shared view model:
val data: Deferred<GetResource<String>> by lazy {
viewModelScope.async {
repository.getData() // suspend function returning GetResource<String>
}
}
fun startDataRetrieval() { data } // access the lazy property to start its coroutine
// In second fragment:
lifecycleScope.launch {
val value = mySharedViewModel.data.await()
// do something with value
}
But if you have to have the Flow because you’re using it for other purposes:
If you just want the first available value from the Flow, have the second Fragment monitor your data StateFlow for its first valid value.
lifecycleScope.launch {
val value = mySharedViewModel.data.filterNotNull().first()
// do something with first arrived value
}
And you can use SharedFlow so you don’t have to make the data type nullable. If you do this you can omit filterNotNull() above. In your ViewModel, it’s easier to do this with shareIn than your code that has to use a backing property and manually collect the source.
val data: SharedFlow<GetResource<String>> = repository.getData()
.shareIn(viewModelScope, replay = 1, SharingStarted.Eagerly)
If you need to wait before starting the collection to the SharedFlow, then you could make the property lazy.

Agreed with #Tenfour04 's answer, I would like to contribute a little more.
If you really want to control over the jobs or Structured Concurrency, i would suggest use custom way of handling the coroutine rather than coupled your code with the viewModelScope.
There are couple of things you need to make sure:
1- What happen when cancellation or exception occurrs
2- you have to manage the lifecycle of the coroutine(CoroutineScope)
3- Cancelling scope, depends on usecase like problem facing you are right now
4- Scope of ViewModel e.g: Either it is tied to activity(Shared ViewModel) or for specific fragment.
If you are not handling either of these carefully specifically first 3, your are more likely to leaking the coroutine your are gurenteed gonna get misbehavior of you app.
Whenever you start any coroutine in Custom way you have to make sure, what is going to be the lifecycle, when it gonna end, This is so important, it can cause real problems
Luckily, i have this sample of CustomViewModel using Jobs: Structured Concurrency sample code

Map multiple suspend functions to single LiveData

The company I just started working at uses a so called Navigator, which I for now interpreted as a stateless ViewModel. My Navigator receives some usecases, with each contains 1 suspend function. The result of any of those usecases could end up in a single LiveData. The Navigator has no coroutine scope, so I pass the responsibility of scoping suspending to the Fragment using fetchValue().
Most current code in project has LiveData in the data layer, which I tried not to. Because of that, their livedata is linked from view to dao.
My simplified classes:
class MyFeatureNavigator(
getUrl1: getUrl1UseCase,
getUrl1: getUrl1UseCase
) {
val url = MediatorLiveData<String>()
fun goToUrl1() {
url.fetchValue { getUrl1() }
}
fun goToUrl2() {
url.fetchValue { getUrl2() }
}
fun <T> MediatorLiveData<T>.fetchValue(provideValue: suspend () -> T) {
val liveData = liveData { emit(provideValue()) }
addSource(liveData) {
removeSource(liveData)
value = it
}
}
}
class MyFeatureFragment : Fragment {
val viewModel: MyFeatureViewModel by viewModel()
val navigator: MyFeatureNavigator by inject()
fun onViewCreated() {
button.setOnClickListener { navigator.goToUrl1() }
navigator.url.observe(viewLifecycleOwner, Observer { url ->
openUrl(url)
})
}
}
My two questions:
Is fetchValue() a good way to link a suspend function to LiveData? Could it leak? Any other concerns?
My main reason to only use coroutines (and flow) in the data layer, is 'because Google said so'. What's a better reason for this? And: what's the best trade off in being consistent with the project and current good coding practices?

Is fetchValue() a good way to link a suspend function to LiveData?
Could it leak? Any other concerns?
Generally it should work. You probably should remove the previous source of the MediatorLiveData before adding new one, otherwise if you get two calls to fetchValue in a row, the first url can be slower to fetch, so it will come later and win.
I don't see any other correctness concerns, but this code is pretty complicated, creates a couple of intermediate objects and generally difficult to read.
My main reason to only use coroutines (and flow) in the data layer,
is 'because Google said so'. What's a better reason for this?
Google has provided a lot of useful extensions to use coroutines in the UI layer, e.g. take a look at this page. So obviously they encourage people to use it.
Probably you mean the recommendation to use LiveData instead of the Flow in the UI layer. That's not a strict rule and it has one reason: LiveData is a value holder, it keeps its value and provides it immediately to new subscribers without doing any work. That's particularly useful in the UI/ViewModel layer - when a configuration change happens and activity/fragment is recreated, the newly created activity/fragment uses the same view model, subscribes to the same LiveData and receives the value at no cost.
At the same time Flow is 'cold' and if you expose a flow from your view model, each reconfiguration will trigger a new flow collection and the flow will be to execute from scratch.
So e.g. if you fetch data from db or network, LiveData will just provide the last value to new subscriber and Flow will execute the costly db/network operation again.
So as I said there is no strict rule, it depends on the particular use-case. Also I find it very useful to use Flow in view models - it provides a lot of operators and makes the code clean and concise. But than I convert it to a LiveData with help of extensions like asLiveData() and expose this LiveData to the UI. This way I get best from both words - LiveData catches value between reconfigurations and Flow makes the code of view models nice and clean.
Also you can use latest StateFlow and SharedFlow often they also can help to overcome the mentioned Flow issue in the UI layer.
Back to your code, I would implement it like this:
class MyFeatureNavigator(
getUrl1: getUrl1UseCase,
getUrl1: getUrl1UseCase
) {
private val currentUseCase = MutableStateFlow<UseCase?>(null)
val url = currentUseCase.filterNotNull().mapLatest { source -> source.getData()}.asLiveData()
fun goToUrl1() {
currentUseCase.value = getUrl1
}
fun goToUrl2() {
currentUseCase.value = getUrl2
}
}
This way there are no race conditions to care about and code is clean.
And: what's the best trade off in being consistent with the project
and current good coding practices?
That's an arguable question and it should be primarily team decision. In most projects I participated we adopted this rule: when fixing bugs, doing maintenance of existing code, one should follow the same style. When doing big refactoring/implementing new features one should use latest practices adopted by the team.

Kotlin Coroutines Flow with Room and state handling

I'm trying out the new coroutine's flow, my goal is to make a simple repository that can fetch data from a web api and save it to db, also return a flow from the db.
I'm using room and firebase as the web api, now everything seems pretty straight forward until i try to pass errors coming from the api to the ui.
Since i get a flow from the database which only contains the data and no state, what is the correct approach to give it a state (like loading, content, error) by combining it with the web api result?
Some of the code i wrote:
The DAO:
#Query("SELECT * FROM users")
fun getUsers(): Flow<List<UserPojo>>
The Repository:
val users: Flow<List<UserPojo>> = userDao.getUsers()
The Api call:
override fun downloadUsers(filters: UserListFilters, onResult: (result: FailableWrapper<MutableList<UserApiPojo>>) -> Unit) {
val data = Gson().toJson(filters)
functions.getHttpsCallable("users").call(data).addOnSuccessListener {
try {
val type = object : TypeToken<List<UserApiPojo>>() {}.type
val users = Gson().fromJson<List<UserApiPojo>>(it.data.toString(), type)
onResult.invoke(FailableWrapper(users.toMutableList(), null))
} catch (e: java.lang.Exception) {
onResult.invoke(FailableWrapper(null, "Error parsing data"))
}
}.addOnFailureListener {
onResult(FailableWrapper(null, it.localizedMessage))
}
}
I hope the question is clear enough
Thanks for the help
Edit: Since the question wasn't clear i'll try to clarify. My issue is that with the default flow emitted by room you only have the data, so if i were to subscribe to the flow i would only receive the data (eg. In this case i would only receive a list of users). What i need to achieve is some way to notify the state of the app, like loading or error. At the moment the only way i can think of is a "response" object that contains the state, but i can't seem to find a way to implement it.
Something like:
fun getUsers(): Flow<Lce<List<UserPojo>>>{
emit(Loading())
downloadFromApi()
if(downloadSuccessful)
return flowFromDatabase
else
emit(Error(throwable))
}
But the obvious issue i'm running into is that the flow from the database is of type Flow<List<UserPojo>>, i don't know how to "enrich it" with the state editing the flow, without losing the subscription from the database and without running a new network call every time the db is updated (by doing it in a map transformation).
Hope it's clearer

I believe this is more of an architecture question, but let me try to answer some of your questions first.
My issue is that with the default flow emitted by room you only have
the data, so if i were to subscribe to the flow i would only receive
the data
If there is an error with the Flow returned by Room, you can handle it via catch()
What i need to achieve is some way to notify the state of the app,
like loading or error.
I agree with you that having a State object is a good approach. In my mind, it is the ViewModel's responsibility to present the State object to the View. This State object should have a way to expose errors.
At the moment the only way i can think of is a "response" object that
contains the state, but i can't seem to find a way to implement it.
I have found that it is easier to have the State object that the ViewModel controls be responsible for errors instead of an object that bubbles up from the Service layer.
Now with these questions out of the way, let me try to propose one particular "solution" to your issue.
As you mention, it is common practice to have a Repository that handles retrieving data from multiple data sources. In this case, the Repository would take the DAO and an object that represents getting data from the network, let's call it Api. I am assuming that you are using FirebaseFirestore, so the class and method signature would look something like this:
class Api(private val firestore: FirebaseFirestore) {
fun getUsers() : Flow<List<UserApiPojo>
}
Now the question becomes how to turn a callback based API into a Flow. Luckily, we can use callbackFlow() for this. Then Api becomes:
class Api(private val firestore: FirebaseFirestore) {
fun getUsers() : Flow<List<UserApiPojo> = callbackFlow {
val data = Gson().toJson(filters)
functions.getHttpsCallable("users").call(data).addOnSuccessListener {
try {
val type = object : TypeToken<List<UserApiPojo>>() {}.type
val users = Gson().fromJson<List<UserApiPojo>>(it.data.toString(), type)
offer(users.toMutableList())
} catch (e: java.lang.Exception) {
cancel(CancellationException("API Error", e))
}
}.addOnFailureListener {
cancel(CancellationException("Failure", e))
}
}
}
As you can see, callbackFlow allows us to cancel the flow when something goes wrong and have someone donwnstream handle the error.
Moving to the Repository we would now like to do something like:
val users: Flow<List<User>> = Flow.concat(userDao.getUsers().toUsers(), api.getUsers().toUsers()).first()
There are a few caveats here. first() and concat() are operators you will have to come up with it seems. I did not see a version of first() that returns a Flow; it is a terminal operator (Rx used to have a version of first() that returned an Observable, Dan Lew uses it in this post). Flow.concat() does not seem to exist either. The goal of users is to return a Flow that emits the first value emitted by any of the source Flows. Also, note that I am mapping DAO users and Api users to a common User object.
We can now talk about the ViewModel. As I said before, the ViewModel should have something that holds State. This State should represent data, errors and loading states. One way that can be accomplished is with a data class.
data class State(val users: List<User>, val loading: Boolean, val serverError: Boolean)
Since we have access to the Repository the ViewModel can look like:
val state = repo.users.map {users -> State(users, false, false)}.catch {emit(State(emptyList(), false, true)}
Please keep in mind that this is a rough explanation to point you in a direction, there are many ways to accomplish state management and this is by no means a complete implementation. It may not even make sense to turn the API call into a Flow, for example.

The answer from Emmanuel is really close to answering what i need, i need some clarifications about some of it.
It may not even make sense to turn the API call into a Flow
You are totally right, in fact i only want to actually make it a coroutine, i don't really need it to be a flow.
If there is an error with the Flow returned by Room, you can handle it via catch()
Yes i discovered this after posting the question. But my problem is more something like:
I'd like to call a method, say "getData", this method should return the flow from db, start the network call to update the db (so that i'm going to be notified when it's done via the db flow) and somewhere in here, i would need to let the ui know if db or network errored, right?. Or should i maybe do a separate "getDbFlow" and "updateData" and get the errors separately for each one?
val users: Flow> = Flow.concat(userDao.getUsers().toUsers(), api.getUsers().toUsers()).first()
This is a good idea, but i'd like to keep the db as the single source of truth, and never return to the ui any data directly from the network