As a developer you want to be able to fire off requests without worrying about what order they’re in or when they arrive. All you really care about is when they’re completed. And, with a little Rx magic, that’s when you stumble upon Single.zip
:
/**
* Waits until all SingleSource sources provided by the Iterable sequence signal a success
* value and calls a zipper function with an array of these values to return a result
* to be emitted to downstream.
...
Next, you pass along your list of Single
into Single.zip
like so…
Single.zip(
listOf(source1, source2, source3, ...)
) { results -> /* do something */ }
.subscribeBy(
onError = Timber::e,
onSuccess = {
celebrate()
}
)
Everything appears to be going smoothly. Until you push the app out into the world and begin receiving crash reports.
The exception couldn’t be delivered to the user because it already canceled/disposed the flow. That, or the exception has nowhere to go in the first place.
Why is this? Like any responsible programmer, you added an onError
condition to your subscription. But, instead of seeing it being called, you’re left with a crash that happens after the single has been completed.
You question how this could be happening and begin searching for the answer. Fortunately (or unfortunately), you begin to realize it’s entirely by design..
RxJava 2 tries to avoid losing exceptions which could be important to the developer even if it happens after the natural lifecycle of a flow.
Then you see one of the authors propose a couple of “solutions.”
Override the default handler with
RxJavaPlugins.setOnError()
and suppress what you don’t consider fatal. Alternatively, apply a per sourceonErrorReturn
oronErrorResumeNext
before zipping them together.
Though it would be nice to have a delayError
flag similar to Observable.zip
, you’re out of luck. Hey, we all occasionally forget to add an onErrorReturn
to every one of our Single
variables (although I strongly recommend taking this step).
Moving forward, I’ve been able to protect myself by using safeZip
which automatically wraps all of your Single
s, then returns all various errors along the way in a single error at the end.
sealed class SafeResult<out T> {
class Success<T>(val result: T): SafeResult<T>()
class Failure<T>(val error: Throwable): SafeResult<Nothing>()
}
/**
* Zip [Single] together safely. An onErrorReturn is automatically applied to each source
* to prevent any source from throwing. Then after all sources have completed, any errors
* are then reported
*/
fun <T> zipSafe(sources: List<Single<T>>): Single<List<T>> {
val safeSources = sources.map { source ->
source
.map<SafeResult<T>> { SafeResult.Success(it) }
.onErrorReturn { SafeResult.Failure(it) }
}
return Single.zip(safeSources) { it.filterIsInstance<SafeResult<T>>() }
.flatMap<List<T>> { safeResults ->
val failures = safeResults.filterIsInstance<SafeResult.Failure<T>>()
if (failures.isNotEmpty()) {
Single.error(CompositeException(failures.map { it.error }))
} else {
Single.just(
safeResults.map { (it as SafeResult.Success<T>).result }
)
}
}
}
Except there’s still a problem. If an empty list is passed into Single.zip
you will throw a java.util.NoSuchElementException
exception. Though this will be handled by an onError
in the subscription, if this is part of a larger stream, then the stream will have been completed. To avoid this issue you can make our safe zipper that much safer by returning an empty list when one is provided.
/**
* Zip [Single] together safely. An onErrorReturn is automatically applied to each source
to prevent any source from throwing. Then, after all sources have completed, any errors will then be reported.
*/
fun <T> zipSafe(sources: List<Single<T>>): Single<List<T>> {
if (sources.isEmpty()) {
return Single.just(emptyList())
}
val safeSources = sources.map { source ->
source
.map<SafeResult<T>> { SafeResult.Success(it) }
.onErrorReturn { SafeResult.Failure(it) }
}
return Single.zip(safeSources) { it.filterIsInstance<SafeResult<T>>() }
.flatMap<List<T>> { safeResults ->
val failures = safeResults.filterIsInstance<SafeResult.Failure<T>>()
if (failures.isNotEmpty()) {
Single.error(CompositeException(failures.map { it.error }))
} else {
Single.just(
safeResults.map { (it as SafeResult.Success<T>).result }
)
}
}
}
Success!
Looking for more like this?
Sign up for our monthly newsletter to receive helpful articles, case studies, and stories from our team.
UX Writing Tips
February 3, 2023Kai shares a few tips he's collected on how to write for user interfaces.
Read moreBetween the brackets: MichiganLabs’ approach to software development
February 12, 2024 Read moreWhat the smartest executive leaders are doing right now
July 25, 2024We are consistently seeing three things right now in terms of how executives are tackling the technological challenges they are facing.
Read more