How to create a play.api.libs.iteratee.Enumerator which inserts some data between the items of a given Enumerator? - mongodb

I use Play framework with ReactiveMongo. Most of ReactiveMongo APIs are based on the Play Enumerator. As long as I fetch some data from MongoDB and return it "as-is" asynchronously, everything is fine. Also the transformation of the data, like converting BSON to String, using Enumerator.map is obvious.
But today I faced a problem which at the bottom line narrowed to the following code. I wasted half of the day trying to create an Enumerator which would consume items from the given Enumerator and insert some items between them. It is important not to load all the items at once, as there could be many of them (the code example has only two items "1" and "2"). But semantically it is similar to mkString of the collections. I am sure it can be done very easily, but the best I could come with - was this code. Very similar code creating an Enumerator using Concurrent.broadcast serves me well for WebSockets. But here even that does not work. The HTTP response never comes back. When I look at Enumeratee, it looks that it is supposed to provide such functionality, but I could not find the way to do the trick.
P.S. Tried to call chan.eofAndEnd in Iteratee.mapDone, and chunked(enums >>> Enumerator.eof instead of chunked(enums) - did not help. Sometimes the response comes back, but does not contain the correct data. What do I miss?
def trans(in:Enumerator[String]):Enumerator[String] = {
val (res, chan) = Concurrent.broadcast[String]
val iter = Iteratee.fold(true) { (isFirst, curr:String) =>
if (!isFirst)
chan.push("<-------->")
chan.push(curr)
false
}
in.apply(iter)
res
}
def enums:Enumerator[String] = {
val en12 = Enumerator[String]("1", "2")
trans(en12)
//en12 //if I comment the previous line and uncomment this, it prints "12" as expected
}
def enum = Action {
Ok.chunked(enums)
}

Here is my solution which I believe to be correct for this type of problem. Comments are welcome:
def fill[From](
prefix: From => Enumerator[From],
infix: (From, From) => Enumerator[From],
suffix: From => Enumerator[From]
)(implicit ec:ExecutionContext) = new Enumeratee[From, From] {
override def applyOn[A](inner: Iteratee[From, A]): Iteratee[From, Iteratee[From, A]] = {
//type of the state we will use for fold
case class State(prev:Option[From], it:Iteratee[From, A])
Iteratee.foldM(State(None, inner)) { (prevState, newItem:From) =>
val toInsert = prevState.prev match {
case None => prefix(newItem)
case Some(prevItem) => infix (prevItem, newItem)
}
for(newIt <- toInsert >>> Enumerator(newItem) |>> prevState.it)
yield State(Some(newItem), newIt)
} mapM {
case State(None, it) => //this is possible when our input was empty
Future.successful(it)
case State(Some(lastItem), it) =>
suffix(lastItem) |>> it
}
}
}
// if there are missing integers between from and to, fill that gap with 0
def fillGap(from:Int, to:Int)(implicit ec:ExecutionContext) = Enumerator enumerate List.fill(to-from-1)(0)
def fillFrom(x:Int)(input:Int)(implicit ec:ExecutionContext) = fillGap(x, input)
def fillTo(x:Int)(input:Int)(implicit ec:ExecutionContext) = fillGap(input, x)
val ints = Enumerator(10, 12, 15)
val toStr = Enumeratee.map[Int] (_.toString)
val infill = fill(
fillFrom(5),
fillGap,
fillTo(20)
)
val res = ints &> infill &> toStr // res will have 0,0,0,0,10,0,12,0,0,15,0,0,0,0

You wrote that you are working with WebSockets, so why don't you use dedicated solution for that? What you wrote is better for Server-Sent-Events rather than WS. As I understood you, you want to filter your results before sending them back to client? If its correct then you Enumeratee instead of Enumerator. Enumeratee is transformation from-to. This is very good piece of code how to use Enumeratee. May be is not directly about what you need but I found there inspiration for my project. Maybe when you analyze given code you would find best solution.

Related

request timeout from flatMapping over cats.effect.IO

I am attempting to transform some data that is encapsulated in cats.effect.IO with a Map that also is in an IO monad. I'm using http4s with blaze server and when I use the following code the request times out:
def getScoresByUserId(userId: Int): IO[Response[IO]] = {
implicit val formats = DefaultFormats + ShiftJsonSerializer() + RawShiftSerializer()
implicit val shiftJsonReader = new Reader[ShiftJson] {
def read(value: JValue): ShiftJson = value.extract[ShiftJson]
}
implicit val shiftJsonDec = jsonOf[IO, ShiftJson]
// get the shifts
var getDbShifts: IO[List[Shift]] = shiftModel.findByUserId(userId)
// use the userRoleId to get the RoleId then get the tasks for this role
val taskMap : IO[Map[String, Double]] = taskModel.findByUserId(userId).flatMap {
case tskLst: List[Task] => IO(tskLst.map((task: Task) => (task.name -> task.standard)).toMap)
}
val traversed: IO[List[Shift]] = for {
shifts <- getDbShifts
traversed <- shifts.traverse((shift: Shift) => {
val lstShiftJson: IO[List[ShiftJson]] = read[List[ShiftJson]](shift.roleTasks)
.map((sj: ShiftJson) =>
taskMap.flatMap((tm: Map[String, Double]) =>
IO(ShiftJson(sj.name, sj.taskType, sj.label, sj.value.toString.toDouble / tm.get(sj.name).get)))
).sequence
//TODO: this flatMap is bricking my request
lstShiftJson.flatMap((sjLst: List[ShiftJson]) => {
IO(Shift(shift.id, shift.shiftDate, shift.shiftStart, shift.shiftEnd,
shift.lunchDuration, shift.shiftDuration, shift.breakOffProd, shift.systemDownOffProd,
shift.meetingOffProd, shift.trainingOffProd, shift.projectOffProd, shift.miscOffProd,
write[List[ShiftJson]](sjLst), shift.userRoleId, shift.isApproved, shift.score, shift.comments
))
})
})
} yield traversed
traversed.flatMap((sLst: List[Shift]) => Ok(write[List[Shift]](sLst)))
}
as you can see the TODO comment. I've narrowed down this method to the flatmap below the TODO comment. If I remove that flatMap and merely return "IO(shift)" to the traversed variable the request does not timeout; However, that doesn't help me much because I need to make use of the lstShiftJson variable which has my transformed json.
My intuition tells me I'm abusing the IO monad somehow, but I'm not quite sure how.
Thank you for your time in reading this!
So with the guidance of Luis's comment I refactored my code to the following. I don't think it is optimal (i.e. the flatMap at the end seems unecessary, but I couldnt' figure out how to remove it. BUT it's the best I've got.
def getScoresByUserId(userId: Int): IO[Response[IO]] = {
implicit val formats = DefaultFormats + ShiftJsonSerializer() + RawShiftSerializer()
implicit val shiftJsonReader = new Reader[ShiftJson] {
def read(value: JValue): ShiftJson = value.extract[ShiftJson]
}
implicit val shiftJsonDec = jsonOf[IO, ShiftJson]
// FOR EACH SHIFT
// - read the shift.roleTasks into a ShiftJson object
// - divide each task value by the task.standard where task.name = shiftJson.name
// - write the list of shiftJson back to a string
val traversed = for {
taskMap <- taskModel.findByUserId(userId).map((tList: List[Task]) => tList.map((task: Task) => (task.name -> task.standard)).toMap)
shifts <- shiftModel.findByUserId(userId)
traversed <- shifts.traverse((shift: Shift) => {
val lstShiftJson: List[ShiftJson] = read[List[ShiftJson]](shift.roleTasks)
.map((sj: ShiftJson) => ShiftJson(sj.name, sj.taskType, sj.label, sj.value.toString.toDouble / taskMap.get(sj.name).get ))
shift.roleTasks = write[List[ShiftJson]](lstShiftJson)
IO(shift)
})
} yield traversed
traversed.flatMap((t: List[Shift]) => Ok(write[List[Shift]](t)))
}
Luis mentioned that mapping my List[Shift] to a Map[String, Double] is a pure operation so we want to use a map instead of flatMap.
He mentioned that I'm wrapping every operation that comes from the database in IO which is causing a great deal of recomputation. (including DB transactions)
To solve this issue I moved all of the database operations inside of my for loop, using the "<-" operator to flatMap each of the return values allows the variables being used to preside within the IO monads, hence preventing the recomputation experienced before.
I do think there must be a better way of returning my return value. flatMapping the "traversed" variable to get back inside of the IO monad seems to be unnecessary recomputation, so please anyone correct me.

How to functionally handle a logging side effect

I want to log in the event that a record doesn't have an adjoining record. Is there a purely functional way to do this? One that separates the side effect from the data transformation?
Here's an example of what I need to do:
val records: Seq[Record] = Seq(record1, record2, ...)
val accountsMap: Map[Long, Account] = Map(record1.id -> account1, ...)
def withAccount(accountsMap: Map[Long, Account])(r: Record): (Record, Option[Account]) = {
(r, accountsMap.get(r.id))
}
def handleNoAccounts(tuple: (Record, Option[Account]) = {
val (r, a) = tuple
if (a.isEmpty) logger.error(s"no account for ${record.id}")
tuple
}
def toRichAccount(tuple: (Record, Option[Account]) = {
val (r, a) = tuple
a.map(acct => RichAccount(r, acct))
}
records
.map(withAccount(accountsMap))
.map(handleNoAccounts) // if no account is found, log
.flatMap(toRichAccount)
So there are multiple issues with this approach that I think make it less than optimal.
The tuple return type is clumsy. I have to destructure the tuple in both of the latter two functions.
The logging function has to handle the logging and then return the tuple with no changes. It feels weird that this is passed to .map even though no transformation is taking place -- maybe there is a better way to get this side effect.
Is there a functional way to clean this up?
I could be wrong (I often am) but I think this does everything that's required.
records
.flatMap(r =>
accountsMap.get(r.id).fold{
logger.error(s"no account for ${r.id}")
Option.empty[RichAccount]
}{a => Some(RichAccount(r,a))})
If you're using scala 2.13 or newer you could use tapEach, which takes function A => Unit to apply side effect on every element of function and then passes collection unchanged:
//you no longer need to return tuple in side-effecting function
def handleNoAccounts(tuple: (Record, Option[Account]): Unit = {
val (r, a) = tuple
if (a.isEmpty) logger.error(s"no account for ${record.id}")
}
records
.map(withAccount(accountsMap))
.tapEach(handleNoAccounts) // if no account is found, log
.flatMap(toRichAccount)
In case you're using older Scala, you could provide extension method (updated according to Levi's Ramsey suggestion):
implicit class SeqOps[A](s: Seq[A]) {
def tapEach(f: A => Unit): Seq[A] = {
s.foreach(f)
s
}
}

Conditional chain of futures

I have a sequence of parameters. For each parameter I have to perform DB query, which may or may not return a result. Simply speaking, I need to stop after the first result is non-empty. Of course, I would like to avoid doing unnecessary calls. The caveat is - I need to have this operation(s) contained as a another Future - or any "most reactive" approach.
Speaking of code:
//that what I have
def dbQuery(p:Param): Future[Option[Result]] = {}
//my list of params
val input = Seq(p1,p2,p3)
//that what I need to implements
def getFirstNonEmpty(params:Seq[Param]): Future[Option[Result]]
I know I can possibly just wrap entire function in yet another Future and execute code sequentially (Await? Brrr...), but that not the cleanest solution.
Can I somehow create lazy initialized collection of futures, like
params.map ( p => FutureWhichWontStartUnlessAskedWhichWrapsOtherFuture { dbQuery(p) }).findFirst(!_.isEmpty())
I believe it's possible!
What do you think about something like this?
def getFirstNonEmpty(params: Seq[Param]): Future[Option[Result]] = {
params.foldLeft(Future.successful(Option.empty[Result])) { (accuFtrOpt, param) =>
accuFtrOpt.flatMap {
case None => dbQuery(param)
case result => Future.successful(result)
}
}
}
This might be overkill, but if you are open to using scalaz we can do this using OptionT and foldMap.
With OptionT we sort of combine Future and Option into one structure. We can get the first of two Futures with a non-empty result using OptionT.orElse.
import scalaz._, Scalaz._
import scala.concurrent.Future
import scala.concurrent.ExecutionContext.Implicits.global
val someF: Future[Option[Int]] = Future.successful(Some(1))
val noneF: Future[Option[Int]] = Future.successful(None)
val first = OptionT(noneF) orElse OptionT(someF)
first.run // Future[Option[Int]] = Success(Some(1))
We could now get the first non-empty Future from a List with reduce from the standard library (this will however run all the Futures) :
List(noneF, noneF, someF).map(OptionT.apply).reduce(_ orElse _).run
But with a List (or other collection) we can't be sure that there is at least one element, so we need to use fold and pass a start value. Scalaz can do this work for us by using a Monoid. The Monoid[OptionT[Future, Int]] we will use will supply the start value and combine the Futures with the orElse used above.
type Param = Int
type Result = Int
type FutureO[x] = OptionT[Future, x]
def query(p: Param): Future[Option[Result]] =
Future.successful{ println(p); if (p > 2) Some(p) else None }
def getFirstNonEmpty(params: List[Param]): Future[Option[Result]] = {
implicit val monoid = PlusEmpty[FutureO].monoid[Result]
params.foldMap(p => OptionT(query(p))).run
}
val result = getFirstNonEmpty(List(1,2,3,4))
// prints 1, 2, 3
result.foreach(println) // Some(3)
This is an old question, but if someone comes looking for an answer, here is my take. I solved it for a use case that required me to loop through a limited number of futures sequentially and stop when the first of them returned a result.
I did not need a library for my use-case, a light-weight combination of recursion and pattern matching was sufficient. Although the question here does not have the same problem as a sequence of futures, looping through a sequence of parameters would be similar.
Here would be the pseudo-code based on recursion.
I have not compiled this, fix the types being matched/returned.
def getFirstNonEmpty(params: Seq[Param]): Future[Option[Result]] = {
if (params.isEmpty) {
Future.successful(None)
} else {
val head = params.head
dbQuery(head) match {
case Some(v) => Future.successful(Some(v))
case None => getFirstNonEmpty(params.tail)
}
}
}

Using Futures in Scala?

I am trying to incorporate a database into my http-microservice.
The microservice has a function getValueFromInternet(val: Foo): Future[Value] which was being called by my microservice on a GET request. Now, I want it to happen such that, a function getValue(val: Foo): Future[Value] would first query a db and if the database returns no results, call getValueFromInternet. The database query returns a Future[Seq[Value2]] where I can convert Value2 to Value using a function. And if no entry is found corresponding to that value, an empty Vector is returned.
This is what I have tried so far:
def getValue(val: Foo): Future[Value] = {
val resultFuture = db.getValue(val)
// 1st attempt. Clearly wrong
resultFuture onComplete {
case Success(Vector()) => getValueFromInternet(val)
case Success(vec) => convertValue2to1(vec.head)
}
// 2nd attempt. This is also wrong
resultFuture match {
case Future(Success(Vector())) => getValueFromInternet(val)
case Future(Success(vec)) => convertValue2to1(vec.head)
}
}
I would be grateful for any help suggesting how I can do this.
I have implemented the database and microservice independently and you can find them here and here
You have to use flatMap, since the thing you want to do if the first operation does not return a result also returns a future.
This is as close to your code as possible while still compiling. Note that you can't have identifiers called val in scala, since that is a keyword.
def getValue(v: Foo)(implicit ec: ExecutionContext): Future[Value] = {
val resultFuture: Future[Seq[Value2]] = db.getValue(v)
resultFuture.flatMap { vec =>
if(vec.isEmpty)
getValueFromInternet(v)
else
Future.successful(convertValue2to1(vec.head))
}
}

Wait for a list of futures with composing Option in Scala

I have to get a list of issues for each file of a given list from a REST API with Scala. I want to do the requests in parallel, and use the Dispatch library for this. My method is called from a Java framework and I have to wait at the end of this method for the result of all the futures to yield the overall result back to the framework. Here's my code:
def fetchResourceAsJson(filePath: String): dispatch.Future[json4s.JValue]
def extractLookupId(json: org.json4s.JValue): Option[String]
def findLookupId(filePath: String): Future[Option[String]] =
for (json <- fetchResourceAsJson(filePath))
yield extractLookupId(json)
def searchIssuesJson(lookupId: String): Future[json4s.JValue]
def extractIssues(json: org.json4s.JValue): Seq[Issue]
def findIssues(lookupId: String): Future[Seq[Issue]] =
for (json <- searchIssuesJson(componentId))
yield extractIssues(json)
def getFilePathsToProcess: List[String]
def thisIsCalledByJavaFramework(): java.util.Map[String, java.util.List[Issue]] = {
val finalResultPromise = Promise[Map[String, Seq[Issue]]]()
// (1) inferred type of issuesByFile not as expected, cannot get
// the type system happy, would like to have Seq[Future[(String, Seq[Issue])]]
val issuesByFile = getFilePathsToProcess map { f =>
findLookupId(f).flatMap { lookupId =>
(f, findIssues(lookupId)) // I want to yield a tuple (String, Seq[Issue]) here
}
}
Future.sequence(issuesByFile) onComplete {
case Success(x) => finalResultPromise.success(x) // (2) how to return x here?
case Failure(x) => // (3) how to return null from here?
}
//TODO transform finalResultPromise to Java Map
}
This code snippet has several issues. First, I'm not getting the type I would expect for issuesByFile (1). I would like to just ignore the result of findLookUpId if it is not able to find the lookUp ID (i.e., None). I've read in various tutorials that Future[Option[X]] is not easy to handle in function compositions and for expressions in Scala. So I'm also curious what the best practices are to handle these properly.
Second, I somehow have to wait for all futures to finish, but don't know how to return the result to the calling Java framework (2). Can I use a promise here to achieve this? If yes, how can I do it?
And last but not least, in case of any errors, I would just like to return null from thisIsCalledByJavaFramework but don't know how (3).
Any help is much appreciated.
Thanks,
Michael
Several points:
The first problem at (1) is that you don't handle the case where findLookupId returns None. You need to decide what to do in this case. Fail the whole process? Exclude that file from the list?
The second problem at (1) is that findIssues will itself return a Future, which you need to map before you can build the result tuple
There's a shortcut for map and then Future.sequence: Future.traverse
If you cannot change the result type of the method because the Java interface is fixed and cannot be changed to support Futures itself you must wait for the Future to be completed. Use Await.ready or Await.result to do that.
Taking all that into account and choosing to ignore files for which no id could be found results in this code:
// `None` in an entry for a file means that no id could be found
def entryForFile(file: String): Future[(String, Option[Seq[Issue]])] =
findLookupId(file).flatMap {
// the need for this kind of pattern match shows
// the difficulty of working with `Future[Option[T]]`
case Some(id) ⇒ findIssues(id).map(issues ⇒ file -> Some(issues))
case None ⇒ Future.successful(file -> None)
}
def thisIsCalledByJavaFramework(): java.util.Map[String, java.util.List[Issue]] = {
val issuesByFile: Future[Seq[(String, Option[Seq[Issue]])]] =
Future.traverse(getFilePathsToProcess)(entryForFile)
import scala.collection.JavaConverters._
try
Await.result(issuesByFile, 10.seconds)
.collect {
// here we choose to ignore entries where no id could be found
case (f, Some(issues)) ⇒ f -> issues
}
.toMap.mapValues(_.asJava).asJava
catch {
case NonFatal(_) ⇒ null
}
}