§Handling data streams reactively
§The realm of Enumeratees
‘Enumeratee’ is a very important component in the iteratees API. It provides a way to adapt and transform streams of data. An Enumeratee that might sound familiar is the Enumeratee.map.
Starting with a simple problem, consider the following Iteratee:
val sum: Iteratee[Int,Int] = Iteratee.fold[Int,Int](0){ (s,e) => s + e }
This Iteratee takes Int objects as input and computes their sum. Now if we have an Enumerator like the following:
val strings: Enumerator[String] = Enumerator("1","2","3","4")
Then obviously we can not apply the strings:Enumerator[String] to an Iteratee[Int,Int]. What we need is transform each String to the corresponding Int so that the source and the consumer can be fit together. This means we either have to adapt the Iteratee[Int,Int] to be Iteratee[String,Int], or adapt the Enumerator[String] to be rather an Enumerator[Int].
An Enumeratee is the right tool for doing that. We can create an Enumeratee[String,Int] and adapt our Iteratee[Int,Int] using it:
//create am Enumeratee using the map method on Enumeratee
val toInt: Enumeratee[String,Int] = Enumeratee.map[String]{ s => s.toInt }
val adaptedIteratee: Iteratee[String,Int] = toInt.transform(sum)
//this works!
strings |>> adaptedIteratee
There is a symbolic alternative to the transform method, &>> which we can use in our previous example:
strings |>> toInt &>> sum
The map method will create an ‘Enumeratee’ that uses a provided From => To function to map the input from the From type to the To type. We can also adapt the Enumerator:
val adaptedEnumerator: Enumerator[Int] = strings.through(toInt)
//this works!
adaptedEnumerator |>> sum
Here too, we can use a symbolic version of the through method:
strings &> toInt |>> sum
Let’s have a look at the transform signature defined in the Enumeratee trait:
trait Enumeratee[From, To] {
def transform[A](inner: Iteratee[To, A]): Iteratee[From, A] = ...
}
This is a fairly simple signature, and is the same for through defined on an Enumerator :
trait Enumerator[E] {
def through[To](enumeratee: Enumeratee[E, To]): Enumerator[To]
}
The transform and through methods on an Enumeratee and Enumerator, respectively, both use the apply method on Enumeratee, which has a slightly more sophisticated signature:
trait Enumeratee[From, To] {
def apply[A](inner: Iteratee[To, A]): Iteratee[From, Iteratee[To, A]] = ...
}
Indeed, an Enumeratee is more powerful than just transforming an Iteratee type. It really acts like an adapter in that you can get back your original Iteratee after pushing some different input through an Enumeratee. So in the previous example, we can get back the original Iteratee[Int,Int] to continue pushing some Int objects in:
val sum:Iteratee[Int,Int] = Iteratee.fold[Int,Int](0){ (s,e) => s + e }
//create am Enumeratee using the map method on Enumeratee
val toInt: Enumeratee[String,Int] = Enumeratee.map[String]{ s => s.toInt }
val adaptedIteratee: Iteratee[String,Iteratee[Int,Int]] = toInt(sum)
// pushing some strings
val afterPushingStrings: Future[Iteratee[String,Iteratee[Int,Int]]] = {
Enumerator("1","2","3","4") |>> adaptedIteratee
}
val flattenAndRun:Future[Iteratee[Int,Int]] = Iteratee.flatten(afterPushingStrings).run
val originalIteratee = Iteratee.flatten(flattenAndRun)
val moreInts: Future[Iteratee[Int,Int]] = Enumerator(5,6,7) |>> originalIteratee
val sumFuture:Future[Int] = Iteratee.flatten(moreInts).run
sumFuture onSuccess {
case s => println(s)// eventually prints 28
}
That’s why we call the adapted (original) Iteratee ‘inner’ and the resulting Iteratee ‘outer’.
Now that the Enumeratee picture is clear, it is important to know that transform drops the left input of the inner Iteratee when it is Done. This means that if we use Enumeratee.map to transform input, if the inner Iteratee is Done with some left transformed input, the transform method will just ignore it.
That might have seemed like a bit too much detail, but it is useful for grasping the model.
Back to our example on Enumeratee.map, there is a more general method Enumeratee.mapInput which, for example, gives the opportunity to return an EOF on some signal:
val toIntOrEnd: Enumeratee[String,Int ] = Enumeratee.mapInput[String] {
case Input.El("end") => Input.EOF
case other => other.map(e => e.toInt)
}
Enumeratee.map and Enumeratee.mapInput are pretty straightforward, they operate on a per chunk basis and they convert them. Another useful Enumeratee is the Enumeratee.filter :
def filter[E](predicate: E => Boolean): Enumeratee[E, E]
The signature is pretty obvious, Enumeratee.filter creates an Enumeratee[E,E] and it will test each chunk of input using the provided predicate: E => Boolean and it passes it along to the inner (adapted) iteratee if it statisfies the predicate:
val numbers = Enumerator(1,2,3,4,5,6,7,8,9,10)
val onlyOdds = Enumeratee.filter[Int](i => i % 2 != 0)
numbers.through(onlyOdds) |>> sum
There are methods, such as Enumeratee.collect, Enumeratee.drop, Enumeratee.dropWhile, Enumeratee.take, Enumeratee.takeWhile, which work on the same principle.
Let try to use the Enumeratee.take on an Input of chunks of bytes:
// computes the size in bytes
val fillInMemory: Iteratee[Array[Byte],Array[Byte]] = {
Iteratee.consume[Array[Byte]]()
}
val limitTo100: Enumeratee[Array[Byte],Array[Byte]] = {
Enumeratee.take[Array[Byte]](100)
}
val limitedFillInMemory: Iteratee[Array[Byte],Array[Byte]] = {
limitTo100 &>> fillInMemory
}
It looks good, but how many bytes are we taking? What would ideally limit the size, in bytes, of loaded input. What we do above is to limit the number of chunks instead, whatever the size of each chunk is. It seems that the Enumeratee.take is not enough here since it has no information about the type of input (in our case an Array[Byte]) and this is why it can’t count what’s inside.
Luckily there is a Traversable object that offers a set of methods for creating Enumeratee instances for Input types that are TraversableLike. An Array[Byte] is TraversableLike and so we can useTraversable.take:
val fillInMemory: Iteratee[Array[Byte],Array[Byte]] = {
Iteratee.consume[Array[Byte]]()
}
val limitTo100: Enumeratee[Array[Byte],Array[Byte]] = {
Traversable.take[Array[Byte]](100)
}
// We are sure not to get more than 100 bytes loaded into memory
val limitedFillInMemory: Iteratee[Array[Byte],Array[Byte]] = {
limitTo100 &>> fillInMemory
}
Other Traversable methods exist including Traversable.takeUpTo, Traversable.drop.
Finally, you can compose different Enumeratee instances using the compose method, which has the symbolic equivalent ><>. Note that any left input on the Done of the composed Enumeratee instances will be dropped. However, if you use composeConcat aliased >+>, any left input will be concatenated.
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