Develop Reference

How does differentiate between Serialized data class and normal Serialized class?

While writing code for RecyclerView to get data I figured out there's a data class in Kotlin.
Following codes are taken from two different projects which are linked above.
#Serializable
data class MarsPhoto(
val id: String,
#SerialName(value = "img_src")
val imgSrc: String
)
class Contacts {
#SerializedName("country")
private val country:String? = null
fun getCountry():String?{
return country
}
}
I know that both classes are doing same job. So what does differentiate them? I also wonder in the MarsPhoto data class how they can get the id without declaring SerialName just the way they did for imgSrc. (I am just on the way to learning kotlin now, so I'm absolute beginner).

Basically for "data" class the compiler automatically derives the following members from all properties declared in the primary constructor:
equals()/hashCode() pair
toString() of the form "MarsPhoto(id=1, imgSrc=asdf)"
componentN() functions corresponding to the properties in their order of declaration.
copy()
You can read a lot more at enter link description here
On the SerializedName part of your question. if you are dealing with Gson lib by default it is using fields name as "SerializedName". And only if you want to use something different then field name, you can use SerializedName annotation and pass your custom value there. But usually, everybody just writes #SerializedName() with duplication of field names as value for every field.
It's a good idea if you are receiving and Serializing data from server from Json. Because Backend developers can use a bad keys in response, which you don't want to use in your code, so #SerializedName will be the only place where you will have to see this key, and you can name your fields however you like.

#Serializable used to mark class as serializable to disk or like into a file( alternative is Parcel able in android) special useful in case of process death or configuration changes and #SerializedName("country") used for json parsing when u receive the response from server

You get the id without #SerializedName because the JSON property field is the same as your variable name, but imgSrc and img_src is not. Still, even if they are the same, you should always use #SerializedName, because your variable names could be converted to random letters during code optimization, and obfuscation.

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 make fields optional in Kotlin serialization in using it in retrofit?

I have an API which its response is kind of dynamic. I mean sometimes it return a Jason object with "token" value, and sometimes it returns with "message" value. For handling this scenario I decided to have both field in my data class like below:
data class response {
val message:String;
val token:String;
}
Now I want to make both fields optional in Kotlin serialization. I mean, I want to tell Kotlin serialization that if you couldn't find token in response JSON it's ok to ignore it.
How can I achieve this?

All Kotlin properties with default values are automatically optional.
All I need to do is this:
data class response {
val message:String="";
val token:String="";
}

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

Moshi custom field not working on serialization

I'm using Moshi 1.8.0 on Android, and I'm following the instructions on the Moshi documentation create custom fields: https://github.com/square/moshi#custom-field-names-with-json
This means that my request data class is like this:
data class GetStuff(
#Json(name = "RequestContext") val context: RequestContext,
)
but the issue is that the actual HTTP request gets sent like this:
{"context": "blah... }
What I'm expecting to happen is for my request to be like this instead:
{"RequestContext": "blah... }
This seems to work fine for the response, but I can't figure out how to make it work for the request.
Thank you!
Is this not how the #Json(name = "") annotation works for request?

Ugh, I'm an idiot.
I'll answer this for whoever needs this in the future (likely me again).
In order to convert Json to an data class, you have to change your API call to be have this annotation:
#MoshiDeserialization
I knew that, and that's the magic annotation that makes deserialization work.
However, I didn't know I also needed a second magic annotation for the serialization part to work as well:
#MoshiSerialization
Now it works.