class
StreamInverter extends AnyRef
Value Members
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final
def
!=(arg0: AnyRef): Boolean
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: AnyRef): Boolean
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final
def
==(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
finalize(): Unit
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final
def
getClass(): Class[_]
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def
hashCode(): Int
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val
input: InputStream
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final
def
isInstanceOf[T0]: Boolean
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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val
output: OutputStream
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
Inherited from AnyRef
Inherited from Any
A stream inverter lets you transform an
InputStreamto anOutputStreamor vice versa.It's often the case that you need to pass a particular kind of stream into an API. In some situations, especially if you're using something like Akka Streams, you may really want to have the opposite of what you need to pass in.
E.g., when receive a document upload, a legacy API may ask you to pass in an
OutputStreamto which it will push the bytes. In a streaming context, what you really want is for that API to give you anInputStreamfrom which you will pull the bytes (or which you'll use to create a streamSource).A
StreamInverterprovides exactly that conversion.Warning: the jobs on each side of the inverter both need to be running on their own thread or you are likely to starve the buffer and lock the application. In the streaming context, this often means invoking the traditional API in a scala.concurrent.Future. IO jobs typically hold threads for a long time, so you probably want to have a dedicated scala.concurrent.ExecutionContext for those futures. A good option is org.gerweck.scala.util.io.ioExecutionContext, which is a premade context with good settings for dedicated IO threads.