RxJava: Transformers
- 5 minsRxJava provides the possibility to reuse of pieces of Observable or Flowable chains and consolidate these operators into a new operator. using ObservableTransformer and FlowableTransformer.
ObservableTransformer
Lets take the following example:
fun main() {
// Letters
Observable.just("Alpha", "Beta", "Gamma", "Delta", "Epsilon")
.collect(::StringBuilder) { sb, v -> sb.append("$v ") }
.map(StringBuilder::toString)
.subscribe { s -> println(s) }
// Numbers
Observable.range(1, 15)
.collect(::StringBuilder) { sb, v -> sb.append("$v ") }
.map(StringBuilder::toString)
.subscribe { s -> println(s) }
}
Alpha Beta Gamma Delta Epsilon
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The piece of code that is chaining of the two operators collect() and map() is exactly the same! Lets enhance the code reusability using ObservableTransformer and compose():
fun main() {
// Letters
Observable.just("Alpha", "Beta", "Gamma", "Delta", "Epsilon")
.compose(toString())
.subscribe { l -> println(l) }
// Numbers
Observable.range(1, 15)
.compose(toString())
.subscribe { l -> println(l) }
}
fun <T> toString(): ObservableTransformer<T, String> {
return ObservableTransformer { upstream ->
upstream
.collect(::StringBuilder) { sb, v -> sb.append("$v ") }
.map(StringBuilder::toString)
.toObservable()
}
}
Alpha Beta Gamma Delta Epsilon
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FlowableTransformer
The FlowableTransformer is not much different from ObservableTransformer. Of course, it will support backpressure since it is composed with Flowables:
fun main() {
// Letters
Flowable.just("Alpha", "Beta", "Gamma", "Delta", "Epsilon")
.compose(toString())
.subscribe { l -> println(l) }
// Numbers
Flowable.range(1, 15)
.compose(toString())
.subscribe { l -> println(l) }
}
fun <T> toString(): FlowableTransformer<T, String> {
return FlowableTransformer { upstream ->
upstream
.collect(::StringBuilder) { sb, v -> sb.append("$v ") }
.map(StringBuilder::toString)
.toFlowable()
}
}
Alpha Beta Gamma Delta Epsilon
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Shared States
When creating Transformers (and custom operators), state sharing between more than one subscription can cause unwanted behaviors and side effects.
fun main() {
val source = Observable.just("Alpha", "Beta", "Gamma", "Delta", "Epsilon")
.compose(withIndex())
source.subscribe { println("Subscriber 1: $it") }
source.subscribe { println("Subscriber 1: $it") }
}
fun <T> withIndex(): ObservableTransformer<T, IndexedValue<T>> {
val indexer = AtomicInteger(-1) // Bad idea!
return ObservableTransformer { upstream ->
upstream.map { v ->
IndexedValue(indexer.incrementAndGet(), v)
}
}
}
data class IndexedValue<T>(val index: Int, val value: T)
Subscriber 1: IndexedValue(index=0, value=Alpha)
Subscriber 1: IndexedValue(index=1, value=Beta)
Subscriber 1: IndexedValue(index=2, value=Gamma)
Subscriber 1: IndexedValue(index=3, value=Delta)
Subscriber 1: IndexedValue(index=4, value=Epsilon)
Subscriber 1: IndexedValue(index=5, value=Alpha) // Oops!
Subscriber 1: IndexedValue(index=6, value=Beta)
Subscriber 1: IndexedValue(index=7, value=Gamma)
Subscriber 1: IndexedValue(index=8, value=Delta)
Subscriber 1: IndexedValue(index=9, value=Epsilon)
A single instance (and state) of AtomicInteger was shared between both subscriptions. On the second subscription, instead of starting over at 0, it picks up at the index left by the previous subscription and starts at index 5 since the previous subscription ended at 4.
Note: In Kotlin, instead of using Transformers, it is possible to leverage extension functions to add operators to Observable and Flowable types.
Mouaad Aallam
Computer Software Engineer