Using the new Combine framework in iOS 13.
Suppose I have an upstream publisher sending values at a highly irregular rate - sometimes seconds or minutes may go by withou
This is an interesting problem. I played with various combinations of Timer.publish
, buffer
, zip
, and throttle
, but I couldn't get any combination to work quite the way you want. So let's write a custom subscriber.
What we'd really like is an API where, when we get an input from upstream, we also get the ability to control when the upstream delivers the next input. Something like this:
extension Publisher {
/// Subscribe to me with a stepping function.
/// - parameter stepper: A function I'll call with each of my inputs, and with my completion.
/// Each time I call this function with an input, I also give it a promise function.
/// I won't deliver the next input until the promise is called with a `.more` argument.
/// - returns: An object you can use to cancel the subscription asynchronously.
func step(with stepper: @escaping (StepEvent<Output, Failure>) -> ()) -> AnyCancellable {
???
}
}
enum StepEvent<Input, Failure: Error> {
/// Handle the Input. Call `StepPromise` when you're ready for the next Input,
/// or to cancel the subscription.
case input(Input, StepPromise)
/// Upstream completed the subscription.
case completion(Subscribers.Completion<Failure>)
}
/// The type of callback given to the stepper function to allow it to continue
/// or cancel the stream.
typealias StepPromise = (StepPromiseRequest) -> ()
enum StepPromiseRequest {
// Pass this to the promise to request the next item from upstream.
case more
// Pass this to the promise to cancel the subscription.
case cancel
}
With this step
API, we can write a pace
operator that does what you want:
extension Publisher {
func pace<Context: Scheduler, MySubject: Subject>(
_ pace: Context.SchedulerTimeType.Stride, scheduler: Context, subject: MySubject)
-> AnyCancellable
where MySubject.Output == Output, MySubject.Failure == Failure
{
return step {
switch $0 {
case .input(let input, let promise):
// Send the input from upstream now.
subject.send(input)
// Wait for the pace interval to elapse before requesting the
// next input from upstream.
scheduler.schedule(after: scheduler.now.advanced(by: pace)) {
promise(.more)
}
case .completion(let completion):
subject.send(completion: completion)
}
}
}
}
This pace
operator takes pace
(the required interval between outputs), a scheduler on which to schedule events, and a subject
on which to republish the inputs from upstream. It handles each input by sending it through subject
, and then using the scheduler to wait for the pace interval before asking for the next input from upstream.
Now we just have to implement the step
operator. Combine doesn't give us too much help here. It does have a feature called “backpressure”, which means a publisher cannot send an input downstream until the downstream has asked for it by sending a Subscribers.Demand
upstream. Usually you see downstreams send an .unlimited
demand upstream, but we're not going to. Instead, we're going to take advantage of backpressure. We won't send any demand upstream until the stepper completes a promise, and then we'll only send a demand of .max(1)
, so we make the upstream operate in lock-step with the stepper. (We also have to send an initial demand of .max(1)
to start the whole process.)
Okay, so need to implement a type that takes a stepper function and conforms to Subscriber
. It's a good idea to review the Reactive Streams JVM Specification, because Combine is based on that specification.
What makes the implementation difficult is that several things can call into our subscriber asynchronously:
We'll also protect the subscriber from shenanigans involving calling a promise repeatedly, or calling outdated promises, by giving each promise a unique id.
Se here's our basic subscriber definition:
import Combine
import Foundation
public class SteppingSubscriber<Input, Failure: Error> {
public init(stepper: @escaping Stepper) {
l_state = .subscribing(stepper)
}
public typealias Stepper = (Event) -> ()
public enum Event {
case input(Input, Promise)
case completion(Completion)
}
public typealias Promise = (Request) -> ()
public enum Request {
case more
case cancel
}
public typealias Completion = Subscribers.Completion<Failure>
private let lock = NSLock()
// The l_ prefix means it must only be accessed while holding the lock.
private var l_state: State
private var l_nextPromiseId: PromiseId = 1
private typealias PromiseId = Int
private var noPromiseId: PromiseId { 0 }
}
Notice that I moved the auxiliary types from earlier (StepEvent
, StepPromise
, and StepPromiseRequest
) into SteppingSubscriber
and shortened their names.
Now let's consider l_state
's mysterious type, State
. What are all the different states our subscriber could be in?
Subscription
object from upstream.Subscription
from upstream and be waiting for a signal (an input or completion from upstream, or the completion of a promise from the stepper).So here is our definition of State
:
extension SteppingSubscriber {
private enum State {
// Completed or cancelled.
case dead
// Waiting for Subscription from upstream.
case subscribing(Stepper)
// Waiting for a signal from upstream or for the latest promise to be completed.
case subscribed(Subscribed)
// Calling out to the stopper.
case stepping(Stepping)
var subscription: Subscription? {
switch self {
case .dead: return nil
case .subscribing(_): return nil
case .subscribed(let subscribed): return subscribed.subscription
case .stepping(let stepping): return stepping.subscribed.subscription
}
}
struct Subscribed {
var stepper: Stepper
var subscription: Subscription
var validPromiseId: PromiseId
}
struct Stepping {
var subscribed: Subscribed
// If the stepper completes the current promise synchronously with .more,
// I set this to true.
var shouldRequestMore: Bool
}
}
}
Since we're using NSLock
(for simplicity), let's define an extension to ensure we always match locking with unlocking:
fileprivate extension NSLock {
@inline(__always)
func sync<Answer>(_ body: () -> Answer) -> Answer {
lock()
defer { unlock() }
return body()
}
}
Now we're ready to handle some events. The easiest event to handle is asynchronous cancellation, which is the Cancellable
protocol's only requirement. If we're in any state except .dead
, we want to become .dead
and, if there's an upstream subscription, cancel it.
extension SteppingSubscriber: Cancellable {
public func cancel() {
let sub: Subscription? = lock.sync {
defer { l_state = .dead }
return l_state.subscription
}
sub?.cancel()
}
}
Notice here that I don't want to call out to the upstream subscription's cancel
function while lock
is locked, because lock
isn't a recursive lock and I don't want to risk deadlock. All use of lock.sync
follows the pattern of deferring any call-outs until after the lock is unlocked.
Now let's implement the Subscriber
protocol requirements. First, let's handle receiving the Subscription
from upstream. The only time this should happen is when we're in the .subscribing
state, but .dead
is also possible in which case we want to just cancel the upstream subscription.
extension SteppingSubscriber: Subscriber {
public func receive(subscription: Subscription) {
let action: () -> () = lock.sync {
guard case .subscribing(let stepper) = l_state else {
return { subscription.cancel() }
}
l_state = .subscribed(.init(stepper: stepper, subscription: subscription, validPromiseId: noPromiseId))
return { subscription.request(.max(1)) }
}
action()
}
Notice that in this use of lock.sync
(and in all later uses), I return an “action” closure so I can perform arbitrary call-outs after the lock has been unlocked.
The next Subscriber
protocol requirement we'll tackle is receiving a completion:
public func receive(completion: Subscribers.Completion<Failure>) {
let action: (() -> ())? = lock.sync {
// The only state in which I have to handle this call is .subscribed:
// - If I'm .dead, either upstream already completed (and shouldn't call this again),
// or I've been cancelled.
// - If I'm .subscribing, upstream must send me a Subscription before sending me a completion.
// - If I'm .stepping, upstream is currently signalling me and isn't allowed to signal
// me again concurrently.
guard case .subscribed(let subscribed) = l_state else {
return nil
}
l_state = .dead
return { [stepper = subscribed.stepper] in
stepper(.completion(completion))
}
}
action?()
}
The most complex Subscriber
protocol requirement for us is receiving an Input
:
.more
and, if so, return the appropriate demand upstream.Since we have to call out to the stepper in the middle of this work, we have some ugly nesting of lock.sync
calls.
public func receive(_ input: Input) -> Subscribers.Demand {
let action: (() -> Subscribers.Demand)? = lock.sync {
// The only state in which I have to handle this call is .subscribed:
// - If I'm .dead, either upstream completed and shouldn't call this,
// or I've been cancelled.
// - If I'm .subscribing, upstream must send me a Subscription before sending me Input.
// - If I'm .stepping, upstream is currently signalling me and isn't allowed to
// signal me again concurrently.
guard case .subscribed(var subscribed) = l_state else {
return nil
}
let promiseId = l_nextPromiseId
l_nextPromiseId += 1
let promise: Promise = { request in
self.completePromise(id: promiseId, request: request)
}
subscribed.validPromiseId = promiseId
l_state = .stepping(.init(subscribed: subscribed, shouldRequestMore: false))
return { [stepper = subscribed.stepper] in
stepper(.input(input, promise))
let demand: Subscribers.Demand = self.lock.sync {
// The only possible states now are .stepping and .dead.
guard case .stepping(let stepping) = self.l_state else {
return .none
}
self.l_state = .subscribed(stepping.subscribed)
return stepping.shouldRequestMore ? .max(1) : .none
}
return demand
}
}
return action?() ?? .none
}
} // end of extension SteppingSubscriber: Publisher
The last thing our subscriber needs to handle is the completion of a promise. This is complicated for several reasons:
Thus:
extension SteppingSubscriber {
private func completePromise(id: PromiseId, request: Request) {
let action: (() -> ())? = lock.sync {
switch l_state {
case .dead, .subscribing(_): return nil
case .subscribed(var subscribed) where subscribed.validPromiseId == id && request == .more:
subscribed.validPromiseId = noPromiseId
l_state = .subscribed(subscribed)
return { [sub = subscribed.subscription] in
sub.request(.max(1))
}
case .subscribed(let subscribed) where subscribed.validPromiseId == id && request == .cancel:
l_state = .dead
return { [sub = subscribed.subscription] in
sub.cancel()
}
case .subscribed(_):
// Multiple completion or stale promise.
return nil
case .stepping(var stepping) where stepping.subscribed.validPromiseId == id && request == .more:
stepping.subscribed.validPromiseId = noPromiseId
stepping.shouldRequestMore = true
l_state = .stepping(stepping)
return nil
case .stepping(let stepping) where stepping.subscribed.validPromiseId == id && request == .cancel:
l_state = .dead
return { [sub = stepping.subscribed.subscription] in
sub.cancel()
}
case .stepping(_):
// Multiple completion or stale promise.
return nil
}
}
action?()
}
}
Whew!
With all that done, we can write the real step
operator:
extension Publisher {
func step(with stepper: @escaping (SteppingSubscriber<Output, Failure>.Event) -> ()) -> AnyCancellable {
let subscriber = SteppingSubscriber<Output, Failure>(stepper: stepper)
self.subscribe(subscriber)
return .init(subscriber)
}
}
And then we can try out that pace
operator from above. Since we don't do any buffering in SteppingSubscriber
, and the upstream in general isn't buffered, we'll stick a buffer
in between the upstream and our pace
operator.
var cans: [AnyCancellable] = []
func application(_ application: UIApplication, didFinishLaunchingWithOptions launchOptions: [UIApplication.LaunchOptionsKey: Any]?) -> Bool {
let erratic = Just("A").delay(for: 0.0, tolerance: 0.001, scheduler: DispatchQueue.main).eraseToAnyPublisher()
.merge(with: Just("B").delay(for: 0.3, tolerance: 0.001, scheduler: DispatchQueue.main).eraseToAnyPublisher())
.merge(with: Just("C").delay(for: 0.6, tolerance: 0.001, scheduler: DispatchQueue.main).eraseToAnyPublisher())
.merge(with: Just("D").delay(for: 5.0, tolerance: 0.001, scheduler: DispatchQueue.main).eraseToAnyPublisher())
.merge(with: Just("E").delay(for: 5.3, tolerance: 0.001, scheduler: DispatchQueue.main).eraseToAnyPublisher())
.merge(with: Just("F").delay(for: 5.6, tolerance: 0.001, scheduler: DispatchQueue.main).eraseToAnyPublisher())
.handleEvents(
receiveOutput: { print("erratic: \(Double(DispatchTime.now().rawValue) / 1_000_000_000) \($0)") },
receiveCompletion: { print("erratic: \(Double(DispatchTime.now().rawValue) / 1_000_000_000) \($0)") }
)
.makeConnectable()
let subject = PassthroughSubject<String, Never>()
cans += [erratic
.buffer(size: 1000, prefetch: .byRequest, whenFull: .dropOldest)
.pace(.seconds(1), scheduler: DispatchQueue.main, subject: subject)]
cans += [subject.sink(
receiveCompletion: { print("paced: \(Double(DispatchTime.now().rawValue) / 1_000_000_000) \($0)") },
receiveValue: { print("paced: \(Double(DispatchTime.now().rawValue) / 1_000_000_000) \($0)") }
)]
let c = erratic.connect()
cans += [AnyCancellable { c.cancel() }]
return true
}
And here, at long last, is the output:
erratic: 223394.17115897 A
paced: 223394.171495405 A
erratic: 223394.408086369 B
erratic: 223394.739186984 C
paced: 223395.171615624 B
paced: 223396.27056174 C
erratic: 223399.536717127 D
paced: 223399.536782847 D
erratic: 223399.536834495 E
erratic: 223400.236808469 F
erratic: 223400.236886323 finished
paced: 223400.620542561 E
paced: 223401.703613078 F
paced: 223402.703828512 finished
buffer
doesn't send the completion until it receives another demand after it sends the last event, and that demand is delayed by the pacing timer.I've put the the entire implementation of the step
operator in this gist for easy copy/paste.
EDIT
There's an even simpler approach to the original one outlined below, which doesn't require a pacer, but instead uses back-pressure created by flatMap(maxPublishers: .max(1))
.
flatMap
sends a demand of 1, until its returned publisher, which we could delay, completes. We'd need a Buffer
publisher upstream to buffer the values.
// for demo purposes, this subject sends a Date:
let subject = PassthroughSubject<Date, Never>()
let interval = 1.0
let pub = subject
.buffer(size: .max, prefetch: .byRequest, whenFull: .dropNewest)
.flatMap(maxPublishers: .max(1)) {
Just($0)
.delay(for: .seconds(interval), scheduler: DispatchQueue.main)
}
ORIGINAL
I know this is an old question, but I think there's a much simpler way to implement this, so I thought I'd share.
The idea is similar to a .zip
with a Timer
, except instead of a Timer
, you would .zip
with a time-delayed "tick" from a previously sent value, which can be achieved with a CurrentValueSubject
. CurrentValueSubject
is needed instead of a PassthroughSubject
in order to seed the first ever "tick".
// for demo purposes, this subject sends a Date:
let subject = PassthroughSubject<Date, Never>()
let pacer = CurrentValueSubject<Void, Never>(())
let interval = 1.0
let pub = subject.zip(pacer)
.flatMap { v in
Just(v.0) // extract the original value
.delay(for: .seconds(interval), scheduler: DispatchQueue.main)
.handleEvents(receiveOutput: { _ in
pacer.send() // send the pacer "tick" after the interval
})
}
What happens is that the .zip
gates on the pacer, which only arrives after a delay from a previously sent value.
If the next value comes earlier than the allowed interval, it waits for the pacer. If, however, the next value comes later, then the pacer already has a new value to provide instantly, so there would be no delay.
If you used it like in your test case:
let c = pub.sink { print("\($0): \(Date())") }
subject.send(Date())
subject.send(Date())
subject.send(Date())
DispatchQueue.main.asyncAfter(deadline: .now() + 1.0) {
subject.send(Date())
subject.send(Date())
}
DispatchQueue.main.asyncAfter(deadline: .now() + 10.0) {
subject.send(Date())
subject.send(Date())
}
the result would be something like this:
2020-06-23 19:15:21 +0000: 2020-06-23 19:15:21 +0000
2020-06-23 19:15:21 +0000: 2020-06-23 19:15:22 +0000
2020-06-23 19:15:21 +0000: 2020-06-23 19:15:23 +0000
2020-06-23 19:15:22 +0000: 2020-06-23 19:15:24 +0000
2020-06-23 19:15:22 +0000: 2020-06-23 19:15:25 +0000
2020-06-23 19:15:32 +0000: 2020-06-23 19:15:32 +0000
2020-06-23 19:15:32 +0000: 2020-06-23 19:15:33 +0000
Just wanted to mention that I adapted Rob's answer from earlier and converted it to a custom Publisher, in order to allow for a single unbroken pipeline (see comments below his solution). My adaptation is below, but all the credit still goes to him. It also still makes use of Rob's step
operator and SteppingSubscriber
, as this custom Publisher uses those internally.
Edit: updated with buffer as part of the modulated
operator, otherwise that would be required to be attached to buffer the upstream events.
public extension Publisher {
func modulated<Context: Scheduler>(_ pace: Context.SchedulerTimeType.Stride, scheduler: Context) -> AnyPublisher<Output, Failure> {
let upstream = buffer(size: 1000, prefetch: .byRequest, whenFull: .dropNewest).eraseToAnyPublisher()
return PacePublisher<Context, AnyPublisher>(pace: pace, scheduler: scheduler, source: upstream).eraseToAnyPublisher()
}
}
final class PacePublisher<Context: Scheduler, Source: Publisher>: Publisher {
typealias Output = Source.Output
typealias Failure = Source.Failure
let subject: PassthroughSubject<Output, Failure>
let scheduler: Context
let pace: Context.SchedulerTimeType.Stride
lazy var internalSubscriber: SteppingSubscriber<Output, Failure> = SteppingSubscriber<Output, Failure>(stepper: stepper)
lazy var stepper: ((SteppingSubscriber<Output, Failure>.Event) -> ()) = {
switch $0 {
case .input(let input, let promise):
// Send the input from upstream now.
self.subject.send(input)
// Wait for the pace interval to elapse before requesting the
// next input from upstream.
self.scheduler.schedule(after: self.scheduler.now.advanced(by: self.pace)) {
promise(.more)
}
case .completion(let completion):
self.subject.send(completion: completion)
}
}
init(pace: Context.SchedulerTimeType.Stride, scheduler: Context, source: Source) {
self.scheduler = scheduler
self.pace = pace
self.subject = PassthroughSubject<Source.Output, Source.Failure>()
source.subscribe(internalSubscriber)
}
public func receive<S>(subscriber: S) where S : Subscriber, Failure == S.Failure, Output == S.Input {
subject.subscribe(subscriber)
subject.send(subscription: PaceSubscription(subscriber: subscriber))
}
}
public class PaceSubscription<S: Subscriber>: Subscription {
private var subscriber: S?
init(subscriber: S) {
self.subscriber = subscriber
}
public func request(_ demand: Subscribers.Demand) {
}
public func cancel() {
subscriber = nil
}
}
Could Publishers.CollectByTime
be useful here somewhere?
Publishers.CollectByTime(upstream: upstreamPublisher.share(), strategy: Publishers.TimeGroupingStrategy.byTime(RunLoop.main, .seconds(1)), options: nil)