I have array of Observables, say [Observable <WriteTaskResult>]
I want to perform all write tasks keeping their order, and if any one of them fails then I want to perform Observable<ResetTaskResult>
Following function will return observable of type BatchTasksResult for tracking tasks progress.
Sample Code:
enum BatchTasksResult{
case elapsedTime(Double)
case failedFatal
case rolledback
case success
}
func writeBlocks(tasks: [WriteTask]) -> Observable<BatchTasksResult>{
return Observable.create {(observable) -> Disposable in
let allTasks: [Observable<WriteTaskResult>] = self.writeSomewhere(tasks)
Observable.concat(allTasks)
.subscribe { writeTaskResult in
observable.onNext(.elapsedTime(writeTaskResult.totalTime))
}
onError: { (err) in
// Perform Observable<ResetTaskResult>
// if ResetTask was successful then observable.onNext(.rolledback)
// if ResetTask failed then observable.onNext(.failedFatal)
}
onCompleted: {
observable.onNext(.success)
}
.disposed(by: disposeBag)
return Disposables.create()
}
}
How do I trigger rollback logic using Observable from onError of allTasks' observable?
Simple solution seems nested observable, but that's not good practice, I guess? I tried FlatMap, but it can't really solve "If any sinlge task fails, then rollback and reset" Any other solution to this?
There's no need to add the extra level of indirection with the create function. Every Observable operator already creates a new object.
And when you do use Observable.create, do not dispose in an external dispose bag and return a Disposables.create(). Just return the disposable that you just created.
Here's the appropriate way to do what you want:
func writeBlocks(tasks: [WriteTask], resetTask: Single<ResetTaskResult>) -> Observable<BatchTasksResult> {
// create the array of write tasks and concat them. You seem to have that down.
let result = Observable.concat(tasks.map(writeSomewhere(task:)).map { $0.asObservable() })
.share() // the share is needed because you are using the value twice below.
return Observable.merge(
// push out the elapsed time for each task.
result.map { BatchTasksResult.elapsedTime($0.totalTime) },
// when the last one is done, push out the success event.
result.takeLast(1).map { _ in BatchTasksResult.success }
)
.catch { _ in
resetTask // the resetTask will get subscribed to if needed.
.map { _ in BatchTasksResult.rolledback } // if successful emit a rollback
.catch { _ in Single.just(BatchTasksResult.failedFatal) } // otherwise emit the failure.
.asObservable()
}
}
func writeSomewhere(task: WriteTask) -> Single<WriteTaskResult> {
// create a Single that performs the write and emits a result.
}
Top Level Question:
I want to know how, within a retry, I can modify its source observable if it is an observable shared between multiple subscribers (in this case a BehaviorSubject/Relay).
Solution(s) I have considered:
The suggestion of using defer from this post doesn't seem to naturally port over if the source observable needs to be shared.
Use case (to fully elaborate the question)
Say I have a server connection object that, when initialized, connects to an url. Once it is created, I can also use it to get a data stream for a particular input.
class ServerConnection {
var url: URL
init(url: URL)
func getDataStream(input: String) -> Observable<Data> // the observable also errors when the instance is destroyed.
}
However, one particular url or another may be broken or overloaded. So I may want to obtain the address of a mirror and generate a new ServerConnection object. Let's say I have such a function.
// At any point in time, gets the mirror of the url with the lowest load
func getLowestLoadMirror(url: URL) -> URL {}
Ideally, I want this "mirror url" switching should be an implementation detail. The user of my code may only care about the data they receive. So we would want to encapsulate this logic in a new class:
class ServerConnectionWithMirrors {
private var currentConnection: BehaviorRelay<ServerConnection>
init(startingURL: URL)
func dataStream(for inputParams: String) -> Observable<Data>
}
// usage
let connection = ServerConnectionWithMirrors(startingURL: "www.example.com")
connection.dataStream(for: "channel1")
.subscribe { channel1Data in
// do something with channel1Data
}.disposed(by: disposeBag)
connection.dataStream(for: "channel2")
.subscribe { channel2Data in
// do something with channel2Data
}.disposed(by: disposeBag)
How should I write the dataStream() function for ServerConnectionWithMirrors? I should be using retries, but I need to ensure that the retries, when faced with a particular error (ServerOverLoadedError) update the value on the behaviorRelay.
Here is code that I have so far that demonstrates the crux at what I am trying to do. One problem is that multiple subscribers to the behaviorRelay may all update it in rapid succession when they get an error, where only one update would do.
func dataStream(for inputParams: String) -> Observable<Data> {
self.currentConnection.asObservable()
.flatMapLatest { server in
return server.getDataStream(input: inputParams)
}
.retryWhen { errors in
errors.flatMapLatest { error in
if error is ServerOverLoadedError {
self.currentConnection.accept(ServerConnection(url: getLowestLoadURL()))
} else {
return Observable.error(error)
}
}
}
}
The answer to your top level question:
I want to know how, within a retry, I can modify its source observable if it is an observable shared between multiple subscribers (in this case a BehaviorSubject/Relay).
You cannot modify a retry's source observable from within the retry. (full stop) You cannot do this whether it is shared or not. What you can do is make the source observable in such a way that it naturally updates its data for every subscription.
That is what the question you referred to is trying to explain.
func getData(from initialRequest: URLRequest) -> Observable<Data> {
return Observable.deferred {
var correctRequest = initialRequest
let correctURL = getLowestLoadMirror(url: initialRequest.url!)
correctRequest.url = correctURL
return Observable.just(correctRequest)
}
.flatMapLatest {
getDataFromServer(request: $0)
}
.retryWhen { error in
error
.do(onNext: {
guard $0 is ServerOverloadedError else { throw $0 }
})
}
}
With the above code, every time deferred is retried, it will call its closure and every time its closure is called, the URL will the lowest load will be used.
So, I have this sequence of API calls, where I fetch a employee details, then fetch the company and project details that the employee is associated with. After both fetching are complete, I combine both and publish a fetchCompleted event. I've isolated the relevant code below.
func getUserDetails() -> AnyPublisher<UserDetails, Error>
func getCompanyDetails(user: UserDetails) -> AnyPublisher<CompanyDetails, Error>
func getProjectDetails(user: UserDetails) -> AnyPublisher<ProjectDetails, Error>
If I do this,
func getCompleteUserDetails() -> AnyPublisher<UserFetchState, Never> {
let cvs = CurrentValueSubject<UserFetchState, Error>(.initial)
let companyPublisher = getUserDetails()
.flatMap { getCompanyDetails($0) }
let projectPublisher = getUserDetails()
.flatMap { getProjectDetails($0) }
companyPublisher.combineLatest(projectPublisher)
.sink { cvs.send(.fetchComplete) }
return cvs.eraseToAnyPublisher()
}
getUserDetails() will get called twice. What I need is fetch the userDetails once and with that, branch the stream into two, map it to fetch the company details and project details and re-combine both.
Is there a elegant(flatter) way to do the following.
func getCompleteUserDetails() -> AnyPublisher<UserFetchState, Never> {
let cvs = CurrentValueSubject<UserFetchState, Error>(.initial)
getUserDetails()
.sink {
let companyPublisher = getCompanyDetails($0)
let projectPublisher = getProjectDetails($0)
companyPublisher.combineLatest(projectPublisher)
.sink { cvs.send(.fetchComplete) }
}
return cvs.eraseToAnyPublisher()
}
The whole idea of Combine is that you construct a pipeline down which data flows. Actually what flows down can be a value or a completion, where a completion could be a failure (error). So:
You do not need to make a signal that the pipeline has produced its value; the arrival of that value at the end of the pipeline is that signal.
Similarly, you do not need to make a signal that the pipeline's work has completed; a publisher that has produced all the values it is going to produce produces the completion signal automatically, so the arrival of that completion at the end of the pipeline is that signal.
After all, when you receive a letter, the post office doesn't call you up on the phone and say, "You've got mail." Rather, the postman hands you the letter. You don't need to be told you've received a letter; you simply receive it.
Okay, let's demonstrate. The key to understanding your own pipeline is simply to track what kind of value is traveling down it at any given juncture. So let's construct a model pipeline that does the sort of thing you need done. I will posit three types of value:
struct User {
}
struct Project {
}
struct Company {
}
And I will imagine that it is possible to go online and fetch all of that information: the User independently, and the Project and Company based on information contained in the User. I will simulate that by providing utility functions that return publishers for each type of information; in real life these would probably be deferred futures, but I will simply use Just to keep things simple:
func makeUserFetcherPublisher() -> AnyPublisher<User,Error> {
Just(User()).setFailureType(to: Error.self).eraseToAnyPublisher()
}
func makeProjectFetcherPublisher(user:User) -> AnyPublisher<Project,Error> {
Just(Project()).setFailureType(to: Error.self).eraseToAnyPublisher()
}
func makeCompanyFetcherPublisher(user:User) -> AnyPublisher<Company,Error> {
Just(Company()).setFailureType(to: Error.self).eraseToAnyPublisher()
}
Now then, let's construct our pipeline. I take it that our goal is to produce, as the final value in the pipeline, all the information we have collected: the User, the Project, and the Company. So our final output will be a tuple of those three things. (Tuples are important when you are doing Combine stuff. Passing a tuple down the pipeline is extremely common.)
Okay, let's get started. In the beginning there is nothing, so we need an initial publisher to kick off the process. That will be our user fetcher:
let myWonderfulPipeline = self.makeUserFetcherPublisher()
What's coming out the end of that pipeline is a User. We now want to feed that User into the next two publishers, fetching the corresponding Project and Company. The way to insert a publisher into the middle of a pipeline is with flatMap. And remember, our goal is to produce the tuple of all our info. So:
let myWonderfulPipeline = self.makeUserFetcherPublisher()
// at this point, the value is a User
.flatMap { (user:User) -> AnyPublisher<(User,Project,Company), Error> in
// ?
}
// at this point, the value is a tuple: (User,Project,Company)
So what goes into flatMap, where the question mark is? Well, we must produce a publisher that produces the tuple we have promised. The tuple-making publisher par excellence is Zip. We have three values in our tuple, so this is a Zip3:
let myWonderfulPipeline = self.makeUserFetcherPublisher()
.flatMap { (user:User) -> AnyPublisher<(User,Project,Company), Error> in
// ?
let result = Publishers.Zip3(/* ? */)
return result.eraseToAnyPublisher()
}
So what are we zipping? We must zip publishers. Well, we know two of those publishers — they are the publishers we have already defined!
let myWonderfulPipeline = self.makeUserFetcherPublisher()
.flatMap { (user:User) -> AnyPublisher<(User,Project,Company), Error> in
let pub1 = self.makeProjectFetcherPublisher(user: user)
let pub2 = self.makeCompanyFetcherPublisher(user: user)
// ?
let result = Publishers.Zip3(/* ? */, pub1, pub2)
return result.eraseToAnyPublisher()
}
We're almost done! What goes in the missing slot? Remember, it must be a publisher. And what's our goal? We want to pass on the very same User that arrived from upstream. And what's the publisher that does that? It's Just! So:
let myWonderfulPipeline = self.makeUserFetcherPublisher()
.flatMap { (user:User) -> AnyPublisher<(User,Project,Company), Error> in
let pub1 = self.makeProjectFetcherPublisher(user: user)
let pub2 = self.makeCompanyFetcherPublisher(user: user)
let just = Just(user).setFailureType(to:Error.self)
let result = Publishers.Zip3(just, pub1, pub2)
return result.eraseToAnyPublisher()
}
And we're done. No muss no fuss. This is a pipeline that produces a (User,Project,Company) tuple. Whoever subscribes to this pipeline does not need some extra signal; the arrival of the tuple is the signal. And now the subscriber can do something with that info. Let's create the subscriber:
myWonderfulPipeline.sink {
completion in
if case .failure(let error) = completion {
print("error:", error)
}
} receiveValue: {
user, project, company in
print(user, project, company)
}.store(in: &self.storage)
We didn't do anything very interesting — we simply printed the tuple contents. But you see, in real life the subscriber would now do something useful with that data.
You can use the zip operator to get a Publisher which emits a value whenever both of its upstreams emitted a value and hence zip together getCompanyDetails and getProjectDetails.
You also don't need a Subject to signal the fetch being finished, you can just call map on the flatMap.
func getCompleteUserDetails() -> AnyPublisher<UserFetchState, Error> {
getUserDetails()
.flatMap { getCompanyDetails(user: $0).zip(getProjectDetails(user: $0)) }
.map { _ in UserFetchState.fetchComplete }
.eraseToAnyPublisher()
}
However, you shouldn't need a UserFetchState to signal the state of your pipeline (and especially shouldn't throw away the fetched CompanyDetails and ProjectDetails objects in the middle of your pipeline. You should simply return the fetched CompanyDetails and ProjectDetails as a result of your flatMap.
func getCompleteUserDetails() -> AnyPublisher<(CompanyDetails, ProjectDetails), Error> {
getUserDetails()
.flatMap { getCompanyDetails(user: $0).zip(getProjectDetails(user: $0)) }
.eraseToAnyPublisher()
}
I read some post says that the best practice to deal with RxSwift is to only pass fatal error to the onError and pass Result to the onNext.
It makes sense to me until I realise that I can't deal with retry anymore since it only happen on onError.
How do I deal with this issue?
Another question is, how do I handle global and local retry mixes together?
A example would be, the iOS receipt validation flow.
1, try to fetch receipt locally
2, if failed, ask Apple server for the latest receipt.
3, send the receipt to our backend to validate.
4, if success, then whole flow complete
5, if failed, check the error code if it's retryable, then go back to 1.
and in the new 1, it will force to ask for new receipt from apple server. then when it reaches 5 again, the whole flow will stop since this is the second attempt already. meaning only retry once.
So in this example, if using state machine and without using rx, I will end up using state machine and shares some global state like isSecondAttempt: Bool, shouldForceFetchReceipt: Bool, etc.
How do I design this flow in rx? with these global shared state designed in the flow.
I read some post says that the best practice to deal with RxSwift is to only pass fatal error to the onError and pass Result to the onNext.
I don't agree with that sentiment. It is basically saying that you should only use onError if the programmer made a mistake. You should use errors for un-happy paths or to abort a procedure. They are just like throwing except in an async way.
Here's your algorithm as an Rx chain.
enum ReceiptError: Error {
case noReceipt
case tooManyAttempts
}
struct Response {
// the server response info
}
func getReceiptResonse() -> Observable<Response> {
return fetchReceiptLocally()
.catchError { _ in askAppleForReceipt() }
.flatMapLatest { data in
sendReceiptToServer(data)
}
.retryWhen { error in
error
.scan(0) { attempts, error in
let max = 1
guard attempts < max else { throw ReceiptError.tooManyAttempts }
guard isRetryable(error) else { throw error }
return attempts + 1
}
}
}
Here are the support functions that the above uses:
func fetchReceiptLocally() -> Observable<Data> {
// return the local receipt data or call `onError`
}
func sendReceiptToServer(_ data: Data) -> Observable<Response> {
// send the receipt data or `onError` if the server failed to receive or process it correctly.
}
func isRetryable(_ error: Error) -> Bool {
// is this error the kind that can be retried?
}
func askAppleForReceipt() -> Observable<Data> {
return Observable.just(Bundle.main.appStoreReceiptURL)
.map { (url) -> URL in
guard let url = url else { throw ReceiptError.noReceipt }
return url
}
.observeOn(ConcurrentDispatchQueueScheduler(qos: .userInitiated))
.map { try Data(contentsOf: $0) }
}
I'm wondering how to write my code in more elegant way... I have two requests, the second request have to wait for the first one. If the first one gets failed the whole sentence should failed, I'm wondering how to catch error in one common place?
enum TestError: ErrorType {
case Connection
}
private func runTest() {
rx_firstReq()
.subscribeNext() { _ in
return self.rx_secondReq()
.subscribeNext() { _ in
print("whole req sequence finished with success!")
}.addDisposableTo(self.myDisposeBag)
}.addDisposableTo(myDisposeBag)
}
func rx_firstReq() -> Observable<Bool> {
return Observable.create() { observable -> Disposable in
observable.onError(TestError.Connection) // We are assuming that first req gets failed
observable.onCompleted()
return NopDisposable.instance
}
}
func rx_secondReq() -> Observable<Bool> {
return Observable.create() { observable -> Disposable in
observable.onNext(true)
observable.onCompleted()
return NopDisposable.instance
}
}
As you see there is no any place for error handling... I have no idea how to model it, at this moment each next request in my chain gonna create next indentation level... in my opinion it is not good usage of the RxSwift... 😕
..some hint or link with example code with handling error in common place will be great for me.
Never use one subscribe in another subscribe ! :)
For your problem, flatMap is the solution.
rx_firstReq()
.flatMap { _ -> Observable<Bool> in
rx_secondReq()
}
.subscribe(next, error ...)
.disposed(by: bag)
voilà :)