In June 2016, Chris Eidhof and Florian Kugler (of objc.io fame) started a new Swift screencast series called Swift Talk. The format is simple: for 15 to 20 minutest each week, two experienced programmers pair-program, problem-solve and refactor together. The result is some excellent insight into the process of programming and design.
Last week in episode #34, Chris and Florian did their first episode on one of my favourite topics: Reactive Programming. They work through a reactive programming problem using RxSwift, exploring some of the most common use cases for a reactive programming library: asynchronous networking, combining event streams from multiple sources, and binding values to UI controls. The source code for the episode is available for free on GitHub. Whether or not you’ve watched the episode, I recommend cloning the repo and playing around with the app in the simulator.
I haven’t yet had the opportunity to work with RxSwift, but I have a lot of experience with ReactiveCocoa, and have made a few contributions. Since the recent release of ReactiveCocoa 5, which overhauled its UI binding APIs for Swift 3, and ReactiveSwift (the cross-platform core of ReactiveCocoa), I thought it would be interesting to use this example app from Swift Talk to compare the two libraries.
A quick note on terminology: throughout this article, I’ll be using RxSwift to also refer to RxCocoa, which is bundled alongside it and provides the UI binding layer. In the same way, I’ll be using ReactiveSwift and ReactiveCocoa interchangeably.
Porting from RxSwift to ReactiveSwift
Let’s take a first pass and port examples in the source directly to the equivalent ReactiveSwift APIs. Even though the changes are fairly minimal, we can learn a lot about about the philosophical differences between the two libraries.
Observing changes to a simple UI control
-let priceSignal = priceSlider.rx.value
+let priceSignal = priceSlider.reactive.values
.map { floor(Double($0)) }
-priceSignal
+priceLabel.reactive.text <~ priceSignal
.map { "\($0) USD" }
- .bindTo(priceLabel.rx.text)
- .addDisposableTo(disposeBag)
RxSwift’s bindTo(_:)
and addDisposableTo(_:)
functions are both unified in
ReactiveSwift under the binding operator, <~
. On the left side of the
operator is the “binding target”, defined by BindingTargetProtocol
. Binding
targets do two things: consume values from a stream, and define a
Lifetime
, i.e., when the binding should end (usually when the
target is deinitialised).
Wrapping a network call
-func load<A>(_ resource: Resource<A>) -> Observable<A> {
- return Observable.create { observer in
+func load<A>(_ resource: Resource<A>) -> SignalProducer<A, AnyError> {
+ return SignalProducer { observer, disposable in
print("start loading")
self.load(resource) { result in
sleep(1)
switch result {
case .error(let error):
- observer.onError(error)
+ observer.send(error: AnyError(error))
case .success(let value):
- observer.onNext(value)
- observer.onCompleted()
+ observer.send(value: value)
+ observer.sendCompleted()
}
}
- return Disposables.create()
}
}
The biggest difference here is the SignalProducer
type.
Here’s where ReactiveSwift begins to diverge from RxSwift: the notion of
“hot” and “cold” signals are separated out into two different types. You can
compare RxSwift’s explanation of the difference with
ReactiveSwift’s TV streaming analogy.
The second major difference between the two libraries is ReactiveSwift’s
Signal
and SignalProducer
add a second generic type parameter: the
Error
type. If you’re familiar with Swift’s error handling
model, it might seem like an unconventional choice to
have strongly-typed errors. One benefit is that errors can become
self-documenting: you have a type whose documentation or source code can be
looked up to discover what errors might occur. But the real benefit is the
existence of the NoError
type, which allows you to prove at
compile time that no event will ever occur, by being impossible to construct.
Many of ReactiveSwift’s error handling features are made possible by
NoError
.
In this case, because we’re bridging untyped Swift errors into the
strongly-typed model of ReactiveSwift, we use the AnyError
wrapper type.
Combining the results
-let vatSignal = countriesDataSource.selectedIndex.asObservable()
- .distinctUntilChanged()
+let vatSignal = countriesDataSource.selectedIndex.producer
+ .skipRepeats()
.map { [unowned self] index in
self.countriesDataSource.countries[index].lowercased()
- }.flatMap { [unowned self] country in
- self.webservice.load(vat(country: country)).map { Optional.some($0) }.startWith(nil)
- }.shareReplay(1)
+ }.flatMap(.latest) { [unowned self] country in
+ self.webservice.load(vat(country: country)).map { Optional.some($0) }.prefix(value: nil)
+ }.replayLazily(upTo: 1)
There’s a little more going on here:
countriesDataSource.selectedIndex
has changed from aVariable<Int>
to aMutableProperty<Int>
. To observe the current value, followed by all future changes, we use theproducer
property, which returns aSignalProducer<Int, NoError>
.There’s a new
.latest
parameter toflatMap()
. You can learn about the differences between flattening strategies in ReactiveSwift’s documentation. These strategies are all possible in RxSwift, but theflatMap
operator chooses a default strategy. In ReactiveSwift, no strategy is considered to be a sensible default for all cases, and so you instead choose the strategy that is most appropriate for your use case.The
shareReplay()
operator is basically the same, but under the namereplayLazily(upTo:)
.
RxSwift provides the Variable
type, a mutable box that holds a current value
and lets you observe changes to its value over time. In order to combine
Variable
s with other streams, you have to convert it to an Observable
,
losing its “Variable
-ness” in the process. ReactiveSwift’s MutableProperty
is equivalent, but along with PropertyProtocol
, there are a number of
interesting ways you can combine properties, while preserving the fact that a)
they are guaranteed to have a current value, and b) they are guaranteed to
never fail. You can read more about Property
in ReactiveSwift’s
documentation.
What next?
RxSwift and ReactiveSwift are two different approaches — perhaps surprisingly so — to the same underlying problem. Both make heavy use of Swift’s type system to help you describe your application’s asynchronous logic in a high-level way, and with very different results.
This episode of Swift Talk was an introduction to reactive programming, and not intended to prescribe the “right way” of solving the problem. There’s certainly a more idiomatic way to write this code with either library. By comparing these two libraries, we’ve been able to see how even apparently subtle differences in API design can influence the code we write.