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
Related
In my android project I have tried to implement a shared View Model which does all the reading and writing data. I do this by using Mutable Live Data and my activity calls an update function within the View Model to update the Live Data. However I can't figure out how to get the data after it has been accessed. It seems that I am trying to update my UI before the data gets accessed. I have looked up this problem and it seems the solution has something to do with coroutines. I have not been successful implementing coroutines and I always get a null value for my data.
ViewModel :
private val firebaseDatabase: DatabaseReference = FirebaseDatabase.getInstance().reference
private val fAuth = FirebaseAuth.getInstance()
private val user: FirebaseUser = fAuth.currentUser!!
private var _saveLocation: MutableLiveData<LocationEvent> = MutableLiveData<LocationEvent>()
val saveLocation: LiveData<LocationEvent> get() = _saveLocation
fun loadData() {
firebaseDatabase.child("User").child(user.uid).child("SaveLocation").get()
.addOnSuccessListener {
_saveLocation.value = LocationEvent(
it.child("title").getValue<String>()!!,
it.child("organizer").getValue<String>()!!,
LatLng(
it.child("locationLatLng").child("latitude").value as Double,
it.child("locationLatLng").child("longitude").value as Double
),
it.child("address").getValue<String>()!!,
it.child("description").value as String,
it.child("allDay").value as Boolean,
it.child("sdate").getValue<Calendar>()!!,
it.child("edate").getValue<Calendar>()!!,
it.child("notifications").getValue<MutableList<Int>>()!!,
user.uid
)
}.addOnFailureListener {}
}
Activity function :
private fun loadSaveData() {
dataViewModel.loadData()
//using log statement just to see if any value
//Always get null
Log.d("MainFragment", "${dataViewModel.saveLocation.value}")
}
I did not include any attempt at coroutines above.
Question
How can I use coroutines to fix this problem?
If not coroutines than what?
(Side Question) : Why does casting to type Calendar cause a crash?
Any help whether its a solution or pointing me to a solution would be much appreciated.
Whenever you use code with names like "add listener" or "set listener" or ones with words like "fetch" or "async" in the name and take lambda parameters, you are calling an asynchronous function. This means the function returns before it finishes (and usually before it even starts) doing what you requested it to.
The purpose of the listener/callback/lambda function you pass to it is to do something sometime in the future, whenever the work eventually is completed. It could only be a few milliseconds in the future, but it absolutely will not happen until after your other code under the function call is complete.
In this case, your get() call to Firebase is synchronous, and you are adding a listener to it to tell it what to do with the results, when they eventually arrive. Then your flow of code continues on synchronously. Back in your loadSaveData() function, you are checking for the results, but the request and your listener have not been completed yet.
You don't need coroutines to get around this. Coroutines are a convenient syntax for dealing with code that normally uses callbacks, but regardless of whether you use coroutines, you need to understand what is going on. IO operations like what you're using cannot be done on the main thread, which is why they are done synchronously.
There's a lot more info about this in this StackOverflow question.
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>()
Because database fetches usually happen asynchronously by default, a variable that holds the data from the firebase database fetch will be null when used right after the fetch. To solve this I have seen people use the ".await()" feature in Kotlin coroutines but this goes against the purpose of asynchronous database queries. People also call the succeeding code from within 'addOnSuccessListener{}' but this seems to go against the purpose of MVVM, since 'addOnSuccessListener{}' will be called in the model part of MVVM, and the succeeding code that uses the fetched data will be in the ViewModel. The answer I'm looking for is maybe a listener or observer that is activated when the variable (whose value is filled from the fetched data) is given a value.
Edit:
by "succeeding code" I mean what happens after the database fetch using the fetched data.
As #FrankvanPuffelen already mentioned in his comment, that's what the listener does. When the operation for reading the data completes the listener fires. That means you know if you got the data or the operation was rejected by the Firebase servers due to improper security rules.
To solve this I have seen people use the ".await()" feature in Kotlin coroutines but this goes against the purpose of asynchronous database queries.
It doesn't. Using ".await()" is indeed an asynchronous programming technique that can help us prevent our applications from blocking. When it comes to the MVVM architecture pattern, the operation for reading the data should be done in the repository class. Since reading the data is an asynchronous operation, we need to create a suspend function. Assuming that we want to read documents that exist in a collection called "products", the following function is needed:
suspend fun getProductsFirestore(): List<Product> {
var products = listOf<Product>()
try {
products = productsRef.get().await().documents.mapNotNull { snapShot ->
snapShot.toObject(Product::class.java)
}
} catch (e: Exception) {
Log.d("TAG", e.message!!)
}
return products
}
This method can be called from within the ViewModel class:
val productsLiveData = liveData(Dispatchers.IO) {
emit(repository.getProductsFromFirestore())
}
So it can be observed in activity/fragment class:
private fun getProducts() {
viewModel.producsLiveData.observe(this, {
print(it)
//Do what you need to do with the product list
})
}
I have even written an article in which I have explained four ways in which you can read the data from Cloud Firestore:
How to read data from Cloud Firestore using get()?
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.
How can I get the value of a Flow outside a coroutine similarly to LiveData?
// Suspend function 'first' should be called only from a coroutine or another suspend function
flowOf(1).first()
// value is null
flowOf(1).asLiveData().value
// works
MutableLiveData(1).value
Context
I'm avoiding LiveData in the repository layer in favor of Flow. Yet, I need to set, observe and collect the value for immediate consumption. The later is useful for authentication purpose in a OkHttp3 Interceptor.
You can do this
val flowValue: SomeType
runBlocking(Dispatchers.IO) {
flowValue = myFlow.first()
}
Yes its not exactly what Flow was made for.
But its not always possible to make everything asynchronous and for that matter it may not even always be possible to 'just make a synchronous method'. For instance the current Datastore releases (that are supposed to replace shared preferences on Android) do only expose Flow and nothing else. Which means that you will very easiely get into such a situation, given that none of the Lifecycle methods of Activities or Fragments are coroutines.
If you can help it you should always call coroutines from suspend functions and avoid making runBlocking calls. A lot of the time it works like this. But it´s not a surefire way that works all the time. You can introduce deadlocks with runBlocking.
Well... what you're looking for isn't really what Flow is for. Flow is just a stream. It is not a value holder, so there is nothing for you retrieve.
So, there are two major avenues to go down, depending on what your interceptor needs.
Perhaps your interceptor can live without the data from the repository. IOW, you'll use the data if it exists, but otherwise the interceptor can continue along. In that case, you can have your repository emit a stream but also maintain a "current value" cache that your interceptor can use. That could be via:
BroadcastChannel
LiveData
a simple property in the repository that you update internally and expose as a val
If your interceptor needs the data, though, then none of those will work directly, because they will all result in the interceptor getting null if the data is not yet ready. What you would need is a call that can block, but perhaps evaluates quickly if the data is ready via some form of cache. The details of that will vary a lot based on the implementation of the repository and what is supplying the Flow in the first place.
You could use something like this:
fun <T> SharedFlow<T>.getValueBlockedOrNull(): T? {
var value: T?
runBlocking(Dispatchers.Default) {
value = when (this#getValueBlockedOrNull.replayCache.isEmpty()) {
true -> null
else -> this#getValueBlockedOrNull.firstOrNull()
}
}
return value
}
You can use MutableStateFlow and MutableSharedFlow for emitting the data from coroutine and receiving the data inside Activity/Fragment. MutableStateFlow can be used for state management. It requires default value when initialised. Whereas MutableSharedFlow does not need any default value.
But, if you don't want to receive stream of data, (i.e) your API call sends data only once, you can use suspend function inside coroutine scope and the function will perform the task and return the result like synchronous function call.
To get the value of a Flow outside of a coroutine, the best option is to create the flow as a StateFlow and then call the value property on the StateFlow.
class MyClass {
private val mutableProperty = MutableStateFlow(1)
val property = mutableProperty.asStateFlow()
...
mutableProperty.value = 2
}
...
val readProperty = MyClass().property.value
val propertyAsFlow = MyClass().property as Flow<Int>