我想将外部流程执行表示为Observable[String]
,其中String
-流程输出中的一行。这是我所做的示例,它确实有效:
import monix.eval.Task
import monix.execution.Scheduler.Implicits.global
import monix.reactive.Observable
object TestSo {
def main(args: Array[String]): Unit = {
val lineStream = scala.sys.process.Process("python3 test.py").lineStream
val lineStreamO: Observable[String] = Observable.fromIterator(Task(lineStream.iterator))
.doOnNext(l => Task(println(l))) //logging
.guarantee(Task(println("clean resources")))
println(lineStreamO.toListL.runSyncUnsafe())
}
}
您可以看到,该进程每秒发出新的一行。但是这没关系。仅提供完整示例,test.py
:
from time import sleep
print(0, flush=True)
sleep(1)
print(1, flush=True)
sleep(1)
print(2, flush=True)
sleep(1)
print(3, flush=True)
sleep(1)
print(4, flush=True)
输出:
0
1
2
3
4
5
clean resources
List(0, 1, 2, 3, 4, 5)
问题:
我想超时-如果进程冻结(例如sleep 100000
),则应在超时后终止进程。另外,如果进程被强制执行或失败,则应清除一些资源(例如guarantee
)。 NonZero退出代码应代表失败。
如何通过适当的错误处理将流程执行为Observable[String]
?欢迎rx-java
解决方案。
答案 0 :(得分:2)
需要超时将迫使您重新编写lineStream
逻辑的主要部分。另一方面,通过这样的重写,您可以避免中间的Iterator
并将行直接推入Subject
中。对于超时逻辑,可以使用Monix timeoutOnSlowUpstream
方法,但是您仍然必须处理超时错误并关闭启动的进程。
对于长输出和多个订阅者,还有一个选择。在此代码中,我决定使用replayLimited
的有限缓冲区。根据您的需求,您可以选择一些不同的策略。这是一个解决方案的草图:
object ProcessHelper {
import scala.sys.process.{Process, BasicIO}
import scala.concurrent.duration.FiniteDuration
import monix.eval.Task
import monix.execution.Scheduler
import monix.reactive.subjects.ConcurrentSubject
import monix.reactive.Observable
private class FinishedFlagWrapper(var finished: Boolean = false)
def buildProcessLinesObservable(cmd: String, timeout: FiniteDuration, bufferLines: Int = 100)(implicit scheduler: Scheduler): Observable[String] = {
// works both as a holder for a mutable boolean var and as a synchronization lock
// that is required to preserve semantics of a Subject, particularly
// that onNext is never called after onError or onComplete
val finished = new FinishedFlagWrapper()
// whether you want here replayLimited or some other logic depends on your needs
val subj = ConcurrentSubject.replayLimited[String](bufferLines)
val proc = Process(cmd).run(BasicIO(withIn = false,
line => finished.synchronized {
if (!finished.finished)
subj.onNext(line)
}, None))
// unfortunately we have to block a whole thread just to wait for the exit code
val exitThread = new Thread(() => {
try {
val exitCode = proc.exitValue()
finished.synchronized {
if (!finished.finished) {
finished.finished = true
if (exitCode != 0) {
subj.onError(new RuntimeException(s"Process '$cmd' has exited with $exitCode."))
}
else {
subj.onComplete()
}
}
}
}
catch {
// ignore when this is a result of our timeout
case e: InterruptedException => if(!finished.finished) e.printStackTrace()
}
}, "Process-exit-wait")
exitThread.start()
subj.timeoutOnSlowUpstream(timeout)
.guarantee(Task(finished.synchronized {
if (!finished.finished) {
finished.finished = true
proc.destroy()
exitThread.interrupt()
}
}))
}
}
用法示例如下:
def test(): Unit = {
import monix.execution.Ack._
import monix.reactive._
import scala.concurrent._
import scala.concurrent.duration._
import monix.execution.Scheduler.Implicits.global
val linesO = ProcessHelper.buildProcessLinesObservable("python3 test.py", 5 seconds, 2) // buffer is reduced to just 2 lines just for this example
linesO.subscribe(new Observer[String] {
override def onNext(s: String): Future[Ack] = {
println(s"Received '$s'")
Future.successful(Continue)
}
override def onError(ex: Throwable): Unit = println(s"Error '$ex'")
override def onComplete(): Unit = println("Complete")
})
try {
println(linesO.toListL.runSyncUnsafe())
println(linesO.toListL.runSyncUnsafe()) // second run will show only last 2 values because of the reduced buffer size
println("Finish success")
}
catch {
case e: Throwable => println("Failed with " + e)
}
}
答案 1 :(得分:0)
我在小library中将过程执行实现为反应性rxjava2
Observable
,以反应性方式包装NuProcess。例如:
PreparedStreams streams = builder.asStdInOut();
Single<NuProcess> started = streams.started();
Single<Exit> done = streams.waitDone();
Observable<byte[]> stdout = streams.stdOut();
Observer<byte[]> stdin = streams.stdIn();
done.subscribe();