I'm familiar with JavaScript promises, but I'm new to swift and Firebase, and I don't have anyone to ask on my team. I've tried researching different ways of handling async operations without callback hell, but I can't understand how to make it work with firebase functions. Right now I'm using a really complicated mess of DispatchGroups and callbacks to make the code somewhat work, but I really want to make it cleaner and more maintainable.
My code looks something like this (error handling removed for conciseness):
var array = []
let dispatch = DispatchGroup()
db.collection("documentA").getDocuments() { (querySnapshot, err) in
for document in querySnapshot.documents
dispatch.enter()
let dataA = document.data()["dataA"]
...
db.collection("documentB").documents(dataA).getDocuments() { (document, error) in
let dataB = document.data()["dataB"]
...
db.collection("documentC").documents(dataB).getDocuments() { (document, error) in
let dataC = document.data()["dataC"]
let newObject = NewObject(dataA,dataB,dataC)
self.array.append(newObject)
dispatch.leave()
}
}
}
//Use dispatch group to notify main queue to update tableView using contents of this array
Does anyone have any recommended learning resources or advice on how I can tackle this problem?
I recommend you consider bringing in the RxFirebase library. Rx is a great way to clean up nested closures (callback hell).
In looking over your sample code, the first thing you have to understand is that only so much can be done. The problem itself has a lot of essential complexity. Also, there's a lot going on in this code that can be broken out. Once you do that, you can boil down the problem to the following:
import Curry // the Curry library is in Cocoapods
func example(db: Firestore) -> Observable<[NewObject]> {
let getObjects = curry(getData(db:collectionId:documentId:))(db)
let xs = getObjects("documentA")("dataA")
let xys = xs.flatMap { parentsAndChildren(fn: getObjects("documentB"), parent: { $0 }, xs: $0) }
let xyzs = xys.flatMap { parentsAndChildren(fn: getObjects("documentC"), parent: { $0.1 }, xs: $0) }
return xyzs.mapT { NewObject(dataA: $0.0.0, dataB: $0.0.1, dataC: $0.1) }
}
Note that this is making extensive use of higher order functions, so understanding those will help a lot. If you don't want to use higher order functions, you could use classes instead, but the amount of code you would have to write would at least double and you would likely have problems with memory cycles.
To make the above so simple requires some support code:
func getData(db: Firestore, collectionId: String, documentId: String) -> Observable<[String]> {
return db.collection(collectionId).rx.getDocuments()
.map { getData(documentId: documentId, snapshot: $0) }
}
func parentsAndChildren<X>(fn: (String) -> Observable<[String]>, parent: (X) -> String, xs: [X]) -> Observable<[(X, String)]> {
Observable.combineLatest(xs.map { x in
fn(parent(x)).map { apply(x: x, ys: $0) }
})
.map { $0.flatMap { $0 } }
}
extension ObservableType {
func mapT<T, U>(_ transform: #escaping (T) -> U) -> Observable<[U]> where Element == [T] {
map { $0.map(transform) }
}
}
The getData(db:collectionId:documentId:) function asks for the strings in the collection associated with the document.
The parentsAndChildren(fn:parent:xs:) function is probably the most complex. It will extract the appropriate parent object from the generic X type, get the children from the server and roll them up into a single dimensional array of parents and children. For example if the parents are ["a", "b"], the children of "a" are ["w", "x"] and the children of "b" are ["y", "z"], then the function will output [("a", "w"), ("a", "x"), ("b", "y"), ("b", "z")] (contained in an Observable.)
The Observable.mapT(_:) function allows us to map through an Observable Array of objects and do something to them. Of course, you could just do xyzs.map { $0.map { NewObject(dataA: $0.0.0, dataB: $0.0.1, dataC: $0.1) } }, but I feel this is cleaner.
Here is the support code for the above functions:
extension Reactive where Base: CollectionReference {
func getDocuments() -> Observable<QuerySnapshot> {
Observable.create { [base] observer in
base.getDocuments { snapshot, error in
if let snapshot = snapshot {
observer.onNext(snapshot)
observer.onCompleted()
}
else {
observer.onError(error ?? RxError.unknown)
}
}
return Disposables.create()
}
}
}
func getData(documentId: String, snapshot: QuerySnapshot) -> [String] {
snapshot.documents.compactMap { $0.data()[documentId] as? String }
}
func apply<X>(x: X, ys: [String]) -> [(X, String)] {
ys.map { (x, $0) }
}
The Reactive.getDocuments() function actually makes the firebase request. Its job is to turn the callback closure into an object so that you can deal with it easier. This is the piece that RxFirebase should give you, but as you can see, it's pretty easy to write it on your own.
The getData(documentId:snapshot:) function just extracts the appropriate data out of the snapshot.
The app(x:ys:) function is what keeps the whole thing in a single dimensional array by copying the X for each child.
Lastly, notice that most of the functions above are easily and independently unit testable and the ones that aren't are exceptionally simple...
I am learning Swift Combine now, found quite easy video tutorial, however for some reason I get error when I try to use my enum in PassthroughSubject<Int, WeatherError>()
Check this code:
import Combine
enum WeatherError: Error {
case thingsJustHappen
}
let weatherPublisher = PassthroughSubject<Int, WeatherError>()
let subscriber = weatherPublisher
.filter {$0 > 10}
.sink { value in
print("\(value)")
}
weatherPublisher.send(10)
weatherPublisher.send(30)
".filter" is highlighted and the error is:
Referencing instance method 'sink(receiveValue:)' on 'Publisher'
requires the types 'Publishers.Filter<PassthroughSubject<Int, WeatherError>>.Failure'
(aka 'WeatherError') and 'Never' be equivalent
Surprisingly this code works in the video tutorial. How can I make my WeatherError and Never to be equivalent???
You need to provide both handlers, the completion one, and the value one:
let subscriber = weatherPublisher
.filter { $0 > 10 }
.sink(receiveCompletion: { _ in }, receiveValue: { value in
print("\(value)")
})
This is needed because the single-argument sink, is available only for publishers that can never fail:
extension Publisher where Self.Failure == Never {
/// ... many lines of documentation omitted
public func sink(receiveValue: #escaping ((Self.Output) -> Void)) -> AnyCancellable
}
It will work if you change the type to Never:
let weatherPublisher = PassthroughSubject<Int, Never>()
Or create a new Published variable:
#Published var weather = 0
let weatherPublisher = PassthroughSubject<Int, WeatherError>()
let weatherSubscriber = weather
.filter { $0 > 10 }
.sink { print($0) }
let subscriber = weatherPublisher
.sink { [weak self] value in
self?.weather = value
}
in Xcode 13 & iOS 15.4 this code needed brackets to compile.
extension Publisher where Self.Failure == Never {
// because the publisher can NEVER FAIL - by design!
public func sink(receiveValue: #escaping ((Self.Output) -> Void)) -> AnyCancellable { }
}
How do I get the asynchronous pipelines that constitute the Combine framework to line up synchronously (serially)?
Suppose I have 50 URLs from which I want to download the corresponding resources, and let's say I want to do it one at a time. I know how to do that with Operation / OperationQueue, e.g. using an Operation subclass that doesn't declare itself finished until the download is complete. How would I do the same thing using Combine?
At the moment all that occurs to me is to keep a global list of the remaining URLs and pop one off, set up that one pipeline for one download, do the download, and in the sink of the pipeline, repeat. That doesn't seem very Combine-like.
I did try making an array of the URLs and map it to an array of publishers. I know I can "produce" a publisher and cause it to publish on down the pipeline using flatMap. But then I'm still doing all the downloading simultaneously. There isn't any Combine way to walk the array in a controlled manner β or is there?
(I also imagined doing something with Future but I became hopelessly confused. I'm not used to this way of thinking.)
Use flatMap(maxPublishers:transform:) with .max(1), e.g.
func imagesPublisher(for urls: [URL]) -> AnyPublisher<UIImage, URLError> {
Publishers.Sequence(sequence: urls.map { self.imagePublisher(for: $0) })
.flatMap(maxPublishers: .max(1)) { $0 }
.eraseToAnyPublisher()
}
Where
func imagePublisher(for url: URL) -> AnyPublisher<UIImage, URLError> {
URLSession.shared.dataTaskPublisher(for: url)
.compactMap { UIImage(data: $0.data) }
.receive(on: RunLoop.main)
.eraseToAnyPublisher()
}
and
var imageRequests: AnyCancellable?
func fetchImages() {
imageRequests = imagesPublisher(for: urls).sink { completion in
switch completion {
case .finished:
print("done")
case .failure(let error):
print("failed", error)
}
} receiveValue: { image in
// do whatever you want with the images as they come in
}
}
That resulted in:
But we should recognize that you take a big performance hit doing them sequentially, like that. For example, if I bump it up to 6 at a time, itβs more than twice as fast:
Personally, Iβd recommend only downloading sequentially if you absolutely must (which, when downloading a series of images/files, is almost certainly not the case). Yes, performing requests concurrently can result in them not finishing in a particular order, but we just use a structure that is order independent (e.g. a dictionary rather than a simple array), but the performance gains are so significant that itβs generally worth it.
But, if you want them downloaded sequentially, the maxPublishers parameter can achieve that.
I've only briefly tested this, but at first pass it appears that each request waits for the previous request to finish before starting.
I'm posting this solution in search of feedback. Please be critical if this isn't a good solution.
extension Collection where Element: Publisher {
func serialize() -> AnyPublisher<Element.Output, Element.Failure>? {
// If the collection is empty, we can't just create an arbititary publisher
// so we return nil to indicate that we had nothing to serialize.
if isEmpty { return nil }
// We know at this point that it's safe to grab the first publisher.
let first = self.first!
// If there was only a single publisher then we can just return it.
if count == 1 { return first.eraseToAnyPublisher() }
// We're going to build up the output starting with the first publisher.
var output = first.eraseToAnyPublisher()
// We iterate over the rest of the publishers (skipping over the first.)
for publisher in self.dropFirst() {
// We build up the output by appending the next publisher.
output = output.append(publisher).eraseToAnyPublisher()
}
return output
}
}
A more concise version of this solution (provided by #matt):
extension Collection where Element: Publisher {
func serialize() -> AnyPublisher<Element.Output, Element.Failure>? {
guard let start = self.first else { return nil }
return self.dropFirst().reduce(start.eraseToAnyPublisher()) {
$0.append($1).eraseToAnyPublisher()
}
}
}
You could create custom Subscriber where receive returning Subscribers.Demand.max(1). In that case the subscriber will request next value only when received one. The example is for Int.publisher, but some random delay in map mimics network traffic :-)
import PlaygroundSupport
import SwiftUI
import Combine
class MySubscriber: Subscriber {
typealias Input = String
typealias Failure = Never
func receive(subscription: Subscription) {
print("Received subscription", Thread.current.isMainThread)
subscription.request(.max(1))
}
func receive(_ input: Input) -> Subscribers.Demand {
print("Received input: \(input)", Thread.current.isMainThread)
return .max(1)
}
func receive(completion: Subscribers.Completion<Never>) {
DispatchQueue.main.async {
print("Received completion: \(completion)", Thread.current.isMainThread)
PlaygroundPage.current.finishExecution()
}
}
}
(110...120)
.publisher.receive(on: DispatchQueue.global())
.map {
print(Thread.current.isMainThread, Thread.current)
usleep(UInt32.random(in: 10000 ... 1000000))
return String(format: "%02x", $0)
}
.subscribe(on: DispatchQueue.main)
.subscribe(MySubscriber())
print("Hello")
PlaygroundPage.current.needsIndefiniteExecution = true
Playground print ...
Hello
Received subscription true
false <NSThread: 0x600000064780>{number = 5, name = (null)}
Received input: 6e false
false <NSThread: 0x60000007cc80>{number = 9, name = (null)}
Received input: 6f false
false <NSThread: 0x60000007cc80>{number = 9, name = (null)}
Received input: 70 false
false <NSThread: 0x60000007cc80>{number = 9, name = (null)}
Received input: 71 false
false <NSThread: 0x60000007cc80>{number = 9, name = (null)}
Received input: 72 false
false <NSThread: 0x600000064780>{number = 5, name = (null)}
Received input: 73 false
false <NSThread: 0x600000064780>{number = 5, name = (null)}
Received input: 74 false
false <NSThread: 0x60000004dc80>{number = 8, name = (null)}
Received input: 75 false
false <NSThread: 0x60000004dc80>{number = 8, name = (null)}
Received input: 76 false
false <NSThread: 0x60000004dc80>{number = 8, name = (null)}
Received input: 77 false
false <NSThread: 0x600000053400>{number = 3, name = (null)}
Received input: 78 false
Received completion: finished true
UPDATE
finally i found .flatMap(maxPublishers: ), which force me to update this interesting topic with little bit different approach. Please, see that I am using global queue for scheduling, not only some random delay, just to be sure that receiving serialized stream is not "random" or "lucky" behavior :-)
import PlaygroundSupport
import Combine
import Foundation
PlaygroundPage.current.needsIndefiniteExecution = true
let A = (1 ... 9)
.publisher
.flatMap(maxPublishers: .max(1)) { value in
[value].publisher
.flatMap { value in
Just(value)
.delay(for: .milliseconds(Int.random(in: 0 ... 100)), scheduler: DispatchQueue.global())
}
}
.sink { value in
print(value, "A")
}
let B = (1 ... 9)
.publisher
.flatMap { value in
[value].publisher
.flatMap { value in
Just(value)
.delay(for: .milliseconds(Int.random(in: 0 ... 100)), scheduler: RunLoop.main)
}
}
.sink { value in
print(" ",value, "B")
}
prints
1 A
4 B
5 B
7 B
1 B
2 B
8 B
6 B
2 A
3 B
9 B
3 A
4 A
5 A
6 A
7 A
8 A
9 A
Based on written here
.serialize()?
defined by Clay Ellis accepted answer could be replaced by
.publisher.flatMap(maxPublishers: .max(1)){$0}
while "unserialzed" version must use
.publisher.flatMap{$0}
"real world example"
import PlaygroundSupport
import Foundation
import Combine
let path = "postman-echo.com/get"
let urls: [URL] = "... which proves the downloads are happening serially .-)".map(String.init).compactMap { (parameter) in
var components = URLComponents()
components.scheme = "https"
components.path = path
components.queryItems = [URLQueryItem(name: parameter, value: nil)]
return components.url
}
//["https://postman-echo.com/get?]
struct Postman: Decodable {
var args: [String: String]
}
let collection = urls.compactMap { value in
URLSession.shared.dataTaskPublisher(for: value)
.tryMap { data, response -> Data in
return data
}
.decode(type: Postman.self, decoder: JSONDecoder())
.catch {_ in
Just(Postman(args: [:]))
}
}
extension Collection where Element: Publisher {
func serialize() -> AnyPublisher<Element.Output, Element.Failure>? {
guard let start = self.first else { return nil }
return self.dropFirst().reduce(start.eraseToAnyPublisher()) {
return $0.append($1).eraseToAnyPublisher()
}
}
}
var streamA = ""
let A = collection
.publisher.flatMap{$0}
.sink(receiveCompletion: { (c) in
print(streamA, " ", c, " .publisher.flatMap{$0}")
}, receiveValue: { (postman) in
print(postman.args.keys.joined(), terminator: "", to: &streamA)
})
var streamC = ""
let C = collection
.serialize()?
.sink(receiveCompletion: { (c) in
print(streamC, " ", c, " .serialize()?")
}, receiveValue: { (postman) in
print(postman.args.keys.joined(), terminator: "", to: &streamC)
})
var streamD = ""
let D = collection
.publisher.flatMap(maxPublishers: .max(1)){$0}
.sink(receiveCompletion: { (c) in
print(streamD, " ", c, " .publisher.flatMap(maxPublishers: .max(1)){$0}")
}, receiveValue: { (postman) in
print(postman.args.keys.joined(), terminator: "", to: &streamD)
})
PlaygroundPage.current.needsIndefiniteExecution = true
prints
.w.h i.c hporves ht edownloadsa erh appeninsg eriall y.-) finished .publisher.flatMap{$0}
... which proves the downloads are happening serially .-) finished .publisher.flatMap(maxPublishers: .max(1)){$0}
... which proves the downloads are happening serially .-) finished .serialize()?
Seem to me very useful in other scenarios as well. Try to use default value of maxPublishers in next snippet and compare the results :-)
import Combine
let sequencePublisher = Publishers.Sequence<Range<Int>, Never>(sequence: 0..<Int.max)
let subject = PassthroughSubject<String, Never>()
let handle = subject
.zip(sequencePublisher.print())
//.publish
.flatMap(maxPublishers: .max(1), { (pair) in
Just(pair)
})
.print()
.sink { letters, digits in
print(letters, digits)
}
"Hello World!".map(String.init).forEach { (s) in
subject.send(s)
}
subject.send(completion: .finished)
From the original question:
I did try making an array of the URLs and map it to an array of publishers. I know I can "produce" a publisher and cause it to publish on down the pipeline using flatMap. But then I'm still doing all the downloading simultaneously. There isn't any Combine way to walk the array in a controlled manner β or is there?
Here's a toy example to stand in for the real problem:
let collection = (1 ... 10).map {
Just($0).delay(
for: .seconds(Double.random(in:1...5)),
scheduler: DispatchQueue.main)
.eraseToAnyPublisher()
}
collection.publisher
.flatMap() {$0}
.sink {print($0)}.store(in:&self.storage)
This emits the integers from 1 to 10 in random order arriving at random times. The goal is to do something with collection that will cause it to emit the integers from 1 to 10 in order.
Now we're going to change just one thing: in the line
.flatMap {$0}
we add the maxPublishers parameter:
let collection = (1 ... 10).map {
Just($0).delay(
for: .seconds(Double.random(in:1...5)),
scheduler: DispatchQueue.main)
.eraseToAnyPublisher()
}
collection.publisher
.flatMap(maxPublishers:.max(1)) {$0}
.sink {print($0)}.store(in:&self.storage)
Presto, we now do emit the integers from 1 to 10, in order, with random intervals between them.
Let's apply this to the original problem. To demonstrate, I need a fairly slow Internet connection and a fairly large resource to download. First, I'll do it with ordinary .flatMap:
let eph = URLSessionConfiguration.ephemeral
let session = URLSession(configuration: eph)
let url = "https://photojournal.jpl.nasa.gov/tiff/PIA23172.tif"
let collection = [url, url, url]
.map {URL(string:$0)!}
.map {session.dataTaskPublisher(for: $0)
.eraseToAnyPublisher()
}
collection.publisher.setFailureType(to: URLError.self)
.handleEvents(receiveOutput: {_ in print("start")})
.flatMap() {$0}
.map {$0.data}
.sink(receiveCompletion: {comp in
switch comp {
case .failure(let err): print("error", err)
case .finished: print("finished")
}
}, receiveValue: {_ in print("done")})
.store(in:&self.storage)
The result is
start
start
start
done
done
done
finished
which shows that we are doing the three downloads simultaneously. Okay, now change
.flatMap() {$0}
to
.flatMap(maxPublishers:.max(1) {$0}
The result now is:
start
done
start
done
start
done
finished
So we are now downloading serially, which is the problem originally to be solved.
append
In keeping with the principle of TIMTOWTDI, we can instead chain the publishers with append to serialize them:
let collection = (1 ... 10).map {
Just($0).delay(
for: .seconds(Double.random(in:1...5)),
scheduler: DispatchQueue.main)
.eraseToAnyPublisher()
}
let pub = collection.dropFirst().reduce(collection.first!) {
return $0.append($1).eraseToAnyPublisher()
}
The result is a publisher that serializes the delayed publishers in the original collection. Let's prove it by subscribing to it:
pub.sink {print($0)}.store(in:&self.storage)
Sure enough, the integers now arrive in order (with random intervals between).
We can encapsulate the creation of pub from a collection of publishers with an extension on Collection, as suggested by Clay Ellis:
extension Collection where Element: Publisher {
func serialize() -> AnyPublisher<Element.Output, Element.Failure>? {
guard let start = self.first else { return nil }
return self.dropFirst().reduce(start.eraseToAnyPublisher()) {
return $0.append($1).eraseToAnyPublisher()
}
}
}
Here is one page playground code that depicts possible approach. The main idea is to transform async API calls into chain of Future publishers, thus making serial pipeline.
Input: range of int from 1 to 10 that asynchrounosly on background queue converted into strings
Demo of direct call to async API:
let group = DispatchGroup()
inputValues.map {
group.enter()
asyncCall(input: $0) { (output, _) in
print(">> \(output), in \(Thread.current)")
group.leave()
}
}
group.wait()
Output:
>> 1, in <NSThread: 0x7fe76264fff0>{number = 4, name = (null)}
>> 3, in <NSThread: 0x7fe762446b90>{number = 3, name = (null)}
>> 5, in <NSThread: 0x7fe7624461f0>{number = 5, name = (null)}
>> 6, in <NSThread: 0x7fe762461ce0>{number = 6, name = (null)}
>> 10, in <NSThread: 0x7fe76246a7b0>{number = 7, name = (null)}
>> 4, in <NSThread: 0x7fe764c37d30>{number = 8, name = (null)}
>> 7, in <NSThread: 0x7fe764c37cb0>{number = 9, name = (null)}
>> 8, in <NSThread: 0x7fe76246b540>{number = 10, name = (null)}
>> 9, in <NSThread: 0x7fe7625164b0>{number = 11, name = (null)}
>> 2, in <NSThread: 0x7fe764c37f50>{number = 12, name = (null)}
Demo of combine pipeline:
Output:
>> got 1
>> got 2
>> got 3
>> got 4
>> got 5
>> got 6
>> got 7
>> got 8
>> got 9
>> got 10
>>>> finished with true
Code:
import Cocoa
import Combine
import PlaygroundSupport
// Assuming there is some Asynchronous API with
// (eg. process Int input value during some time and generates String result)
func asyncCall(input: Int, completion: #escaping (String, Error?) -> Void) {
DispatchQueue.global(qos: .background).async {
sleep(.random(in: 1...5)) // wait for random Async API output
completion("\(input)", nil)
}
}
// There are some input values to be processed serially
let inputValues = Array(1...10)
// Prepare one pipeline item based on Future, which trasform Async -> Sync
func makeFuture(input: Int) -> AnyPublisher<Bool, Error> {
Future<String, Error> { promise in
asyncCall(input: input) { (value, error) in
if let error = error {
promise(.failure(error))
} else {
promise(.success(value))
}
}
}
.receive(on: DispatchQueue.main)
.map {
print(">> got \($0)") // << sideeffect of pipeline item
return true
}
.eraseToAnyPublisher()
}
// Create pipeline trasnforming input values into chain of Future publishers
var subscribers = Set<AnyCancellable>()
let pipeline =
inputValues
.reduce(nil as AnyPublisher<Bool, Error>?) { (chain, value) in
if let chain = chain {
return chain.flatMap { _ in
makeFuture(input: value)
}.eraseToAnyPublisher()
} else {
return makeFuture(input: value)
}
}
// Execute pipeline
pipeline?
.sink(receiveCompletion: { _ in
// << do something on completion if needed
}) { output in
print(">>>> finished with \(output)")
}
.store(in: &subscribers)
PlaygroundPage.current.needsIndefiniteExecution = true
In all of the other Reactive frameworks this is really easy; you just use concat to concatenate and flatten the results in one step and then you can reduce the results into a final array. Apple makes this difficult because Publisher.Concatenate has no overload that accepts an array of Publishers. There is similar weirdness with Publisher.Merge. I have a feeling this has to do with the fact that they return nested generic publishers instead of just returning a single generic type like rx Observable. I guess you can just call Concatenate in a loop and then reduce the concatenated results into a single array, but I really hope they address this issue in the next release. There is certainly the need to concat more than 2 publishers and to merge more than 4 publishers (and the overloads for these two operators aren't even consistent, which is just weird).
EDIT:
I came back to this and found that you can indeed concat an arbitrary array of publishers and they will emit in sequence. I have no idea why there isn't a function like ConcatenateMany to do this for you but it looks like as long as you are willing to use a type erased publisher its not that hard to write one yourself. This example shows that merge emits in temporal order while concat emits in the order of combination:
import PlaygroundSupport
import SwiftUI
import Combine
let p = Just<Int>(1).append(2).append(3).delay(for: .seconds(0.25), scheduler: RunLoop.main).eraseToAnyPublisher()
let q = Just<Int>(4).append(5).append(6).eraseToAnyPublisher()
let r = Just<Int>(7).append(8).append(9).delay(for: .seconds(0.5), scheduler: RunLoop.main).eraseToAnyPublisher()
let concatenated: AnyPublisher<Int, Never> = [q,r].reduce(p) { total, next in
total.append(next).eraseToAnyPublisher()
}
var subscriptions = Set<AnyCancellable>()
concatenated
.sink(receiveValue: { v in
print("concatenated: \(v)")
}).store(in: &subscriptions)
Publishers
.MergeMany([p,q,r])
.sink(receiveValue: { v in
print("merge: \(v)")
}).store(in: &subscriptions)
What about the dynamic array of URLs, something like data bus ?
var array: [AnyPublisher<Data, URLError>] = []
array.append(Task())
array.publisher
.flatMap { $0 }
.sink {
}
// it will be finished
array.append(Task())
array.append(Task())
array.append(Task())
Another approach, if you want to collect all the results of the downloads, in order to know which one failed and which one not, is to write a custom publisher that looks like this:
extension Publishers {
struct Serialize<Upstream: Publisher>: Publisher {
typealias Output = [Result<Upstream.Output, Upstream.Failure>]
typealias Failure = Never
let upstreams: [Upstream]
init<C: Collection>(_ upstreams: C) where C.Element == Upstream {
self.upstreams = Array(upstreams)
}
init(_ upstreams: Upstream...) {
self.upstreams = upstreams
}
func receive<S>(subscriber: S) where S : Subscriber, Self.Failure == S.Failure, Self.Output == S.Input {
guard let first = upstreams.first else { return Empty().subscribe(subscriber) }
first
.map { Result<Upstream.Output, Upstream.Failure>.success($0) }
.catch { Just(Result<Upstream.Output, Upstream.Failure>.failure($0)) }
.map { [$0] }
.append(Serialize(upstreams.dropFirst()))
.collect()
.map { $0.flatMap { $0 } }
.subscribe(subscriber)
}
}
}
extension Collection where Element: Publisher {
func serializedPublishers() -> Publishers.Serialize<Element> {
.init(self)
}
}
The publisher takes the first download task, converts its output/failure to a Result instance, and prepends it to the "recursive" call for the rest of the list.
Usage: Publishers.Serialize(listOfDownloadTasks), or listOfDownloadTasks.serializedPublishers().
One minor inconvenient of this implementation is the fact that the Result instance needs to be wrapped into an array, just to be flattened three steps later in the pipeline. Perhaps someone can suggest a better alternative to that.
Coming from the RxJava background, I can not come up with a standard approach to implement sliding windows in RxSwift. E.g. I have the following sequence of events:
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, ...
Let's imagine event emission happens twice in a second. What I want to be able to do is to transform this sequence into a sequence of buffers, each buffer containing last three seconds of data. Plus, each buffer is to be emitted once in a second. So the result would look like that:
[1,2,3,4,5,6], [3,4,5,6,7,8], [5,6,7,8,9,10], ...
What I would do in RxJava is I would use one of the overloads of the buffer method like so:
stream.buffer(3000, 1000, TimeUnit.MILLISECONDS)
Which leads exactly to the result I need to accomplish: sequence of buffers, each buffer is emitted once in a second and contains last three seconds of data.
I checked RxSwift docs far and wide and I did not find any overloads of buffer operator which would allow me to do that. Am I missing some non-obvious (for RxJava user, ofc) operator?
I initially wrote the solution using a custom operator. I have since figured out how it can be done with the standard operators.
extension ObservableType {
func buffer(timeSpan: RxTimeInterval, timeShift: RxTimeInterval, scheduler: SchedulerType) -> Observable<[E]> {
let trigger = Observable<Int>.timer(timeSpan, period: timeShift, scheduler: scheduler)
.takeUntil(self.takeLast(1))
let buffer = self
.scan([Date: E]()) { previous, current in
var next = previous
let now = scheduler.now
next[now] = current
return next.filter { $0.key > now.addingTimeInterval(-timeSpan) }
}
return trigger.withLatestFrom(buffer)
.map { $0.sorted(by: { $0.key <= $1.key }).map { $0.value } }
}
}
I'm leaving my original solution below for posterity:
Writing your own operator is the solution here.
extension ObservableType {
func buffer(timeSpan: RxTimeInterval, timeShift: RxTimeInterval, scheduler: SchedulerType) -> Observable<[E]> {
return Observable.create { observer in
var buf: [Date: E] = [:]
let lock = NSRecursiveLock()
let elementDispoable = self.subscribe { event in
lock.lock(); defer { lock.unlock() }
switch event {
case let .next(element):
buf[Date()] = element
case .completed:
observer.onCompleted()
case let .error(error):
observer.onError(error)
}
}
let spanDisposable = scheduler.schedulePeriodic((), startAfter: timeSpan, period: timeShift, action: { state in
lock.lock(); defer { lock.unlock() }
let now = Date()
buf = buf.filter { $0.key > now.addingTimeInterval(-timeSpan) }
observer.onNext(buf.sorted(by: { $0.key <= $1.key }).map { $0.value })
})
return Disposables.create([spanDisposable, elementDispoable])
}
}
}