How to conveniently convert Seq[Try[Option[String, Any]]] into Try[Option[Map[String, Any]]].
If any Try before convert throws an exception, the converted Try should throw as well.
Assuming that the input type has a tuple inside the Option then this should give you the result you want:
val in: Seq[Try[Option[(String, Any)]]] = ???
val out: Try[Option[Map[String,Any]]] = Try(Some(in.flatMap(_.get).toMap))
If any of the Trys is Failure then the outer Try will catch the exception raised by the get and return Failure
The Some is there to give the correct return type
The get extracts the Option from the Try (or raises an exception)
Using flatMap rather than map removes the Option wrapper, keeping all Some values and discaring None values, giving Seq[(String, Any)]
The toMap call converts the Seq to a Map
Here is something that's not very clean but may help get you started. It assumes Option[(String,Any)], returns the first Failure if there are any in the input Seq and just drops None elements.
foo.scala
package foo
import scala.util.{Try,Success,Failure}
object foo {
val x0 = Seq[Try[Option[(String, Any)]]]()
val x1 = Seq[Try[Option[(String, Any)]]](Success(Some(("A",1))), Success(None))
val x2 = Seq[Try[Option[(String, Any)]]](Success(Some(("A",1))), Success(Some(("B","two"))))
val x3 = Seq[Try[Option[(String, Any)]]](Success(Some(("A",1))), Success(Some(("B","two"))), Failure(new Exception("bad")))
def f(x: Seq[Try[Option[(String, Any)]]]) =
x.find( _.isFailure ).getOrElse( Success(Some(x.map( _.get ).filterNot( _.isEmpty ).map( _.get ).toMap)) )
}
Example session
bash-3.2$ scalac foo.scala
bash-3.2$ scala -classpath .
Welcome to Scala 2.13.1 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_66).
Type in expressions for evaluation. Or try :help.
scala> import foo.foo._
import foo.foo._
scala> f(x0)
res0: scala.util.Try[Option[Equals]] = Success(Some(Map()))
scala> f(x1)
res1: scala.util.Try[Option[Equals]] = Success(Some(Map(A -> 1)))
scala> f(x2)
res2: scala.util.Try[Option[Equals]] = Success(Some(Map(A -> 1, B -> two)))
scala> f(x3)
res3: scala.util.Try[Option[Equals]] = Failure(java.lang.Exception: bad)
scala> :quit
If you're willing to use a functional support library like Cats then there are two tricks that can help this along:
Many things like List and Try are traversable, which means that (if Cats's implicits are in scope) they have a sequence method that can swap two types, for example converting List[Try[T]] to Try[List[T]] (failing if any of the items in the list are failure).
Almost all of the container types support a map method that can operate on the contents of a container, so if you have a function from A to B then map can convert a Try[A] to a Try[B]. (In Cats language they are functors but the container-like types in the standard library generally have map already.)
Cats doesn't directly support Seq, so this answer is mostly in terms of List instead.
Given that type signature, you can iteratively sequence the item you have to in effect push the list type down one level in the type chain, then map over that container to work on its contents. That can look like:
import cats.implicits._
import scala.util._
def convert(listTryOptionPair: List[Try[Option[(String, Any)]]]): Try[
Option[Map[String, Any]]
] = {
val tryListOptionPair = listTryOptionPair.sequence
tryListOptionPair.map { listOptionPair =>
val optionListPair = listOptionPair.sequence
optionListPair.map { listPair =>
Map.from(listPair)
}
}
}
https://scastie.scala-lang.org/xbQ8ZbkoRSCXGDJX0PgJAQ has a slightly more complete example.
One way to approach this is by using a foldLeft:
// Let's say this is the object you're trying to convert
val seq: Seq[Try[Option[(String, Any)]]] = ???
seq.foldLeft(Try(Option(Map.empty[String, Any]))) {
case (acc, e) =>
for {
accOption <- acc
elemOption <- e
} yield elemOption match {
case Some(value) => accOption.map(_ + value)
case None => accOption
}
}
You start off with en empty Map. You then use a for comprehension to go through the current map and element and finally you add a new tuple in the map if present.
The following solutions is based on this answer to the point that almost makes the question a duplicate.
Method 1: Using recursion
def trySeqToMap1[X,Y](trySeq : Seq[Try[Option[(X, Y)]]]) : Try[Option[Map[X,Y]]] = {
def helper(it : Iterator[Try[Option[(X,Y)]]], m : Map[X,Y] = Map()) : Try[Option[Map[X,Y]]] = {
if(it.hasNext) {
val x = it.next()
if(x.isFailure)
Failure(x.failed.get)
else if(x.get.isDefined)
helper(it, m + (x.get.get._1-> x.get.get._2))
else
helper(it, m)
} else Success(Some(m))
}
helper(trySeq.iterator)
}
Method 2: directly pattern matching in case you are able to get a stream or a List instead:
def trySeqToMap2[X,Y](trySeq : LazyList[Try[Option[(X, Y)]]], m : Map[X,Y]= Map.empty[X,Y]) : Try[Option[Map[X,Y]]] =
trySeq match {
case Success(Some(h)) #:: tail => trySeqToMap2(tail, m + (h._1 -> h._2))
case Success(None) #:: tail => tail => trySeqToMap2(tail, m)
case Failure(f) #:: _ => Failure(f)
case _ => Success(Some(m))
}
note: this answer was previously using different method signatures. It has been updated to conform to the signature given in the question.
Related
I am running into this famous 10 year old ticket in Scala https://github.com/scala/bug/issues/2823
Because I am expecting for-comprehensions to work like do-blocks in Haskell. And why shouldn't they, Monads go great with a side of sugar. At this point I have something like this:
import scalaz.{Monad, Traverse}
import scalaz.std.either._
import scalaz.std.list._
type ErrorM[A] = Either[String, A]
def toIntSafe(s : String) : ErrorM[Int] = {
try {
Right(s.toInt)
} catch {
case e: Exception => Left(e.getMessage)
}
}
def convert(args: List[String])(implicit m: Monad[ErrorM], tr: Traverse[List]): ErrorM[List[Int]] = {
val expanded = for {
arg <- args
result <- toIntSafe(arg)
} yield result
tr.sequence(expanded)(m)
}
println(convert(List("1", "2", "3")))
println(convert(List("1", "foo")))
And I'm getting the error
"Value map is not a member of ErrorM[Int]"
result <- toIntSafe(arg)
How do I get back to beautiful, monadic-comprehensions that I am used to? Some research shows the FilterMonadic[A, Repr] abstract class is what to extend if you want to be a comprehension, any examples of combining FilterMonadic with scalaz?
Can I reuse my Monad implicit and not have to redefine map, flatMap etc?
Can I keep my type alias and not have to wrap around Either or worse, redefine case classes for ErrorM?
Using Scala 2.11.8
EDIT: I am adding Haskell code to show this does indeed work in GHC without explicit Monad transformers, only traversals and default monad instances for Either and List.
type ErrorM = Either String
toIntSafe :: Read a => String -> ErrorM a
toIntSafe s = case reads s of
[(val, "")] -> Right val
_ -> Left $ "Cannot convert to int " ++ s
convert :: [String] -> ErrorM [Int]
convert = sequence . conv
where conv s = do
arg <- s
return . toIntSafe $ arg
main :: IO ()
main = do
putStrLn . show . convert $ ["1", "2", "3"]
putStrLn . show . convert $ ["1", "foo"]
Your haskell code and your scala code are not equivalent:
do
arg <- s
return . toIntSafe $ arg
corresponds to
for {
arg <- args
} yield toIntSafe(arg)
Which compiles fine.
To see why your example one doesn't compile, we can desugar it:
for {
arg <- args
result <- toIntSafe(arg)
} yield result
=
args.flatMap { arg =>
toIntSafe(arg).map {result => result}
}
Now looking at types:
args: List[String]
args.flatMap: (String => List[B]) => List[B]
arg => toIntSafe(arg).map {result => result} : String => ErrorM[Int]
Which shows the problem. flatMap is expecting a function returning a List but you are giving it a function returning an ErrorM.
Haskell code along the lines of:
do
arg <- s
result <- toIntSafe arg
return result
wouldn't compile either for roughly the same reason: trying to bind across two different monads, List and Either.
A for comprehension in scala will or a do expression in haskell will only ever work for the same underlying monad, because they are both basically syntactic translations to series of flatMaps and >>=s respectively. And those still need to typecheck.
If you want to compose monads one thing you can do use monad transformers ( EitherT), although in your above example I don't think you want to, since you actually want to sequence in the end.
Finally, in my opinion the most elegant way of expressing your code is:
def convert(args: List[String]) = args.traverse(toIntSafe)
Because map followed by sequence is traverse
I have a java.util.Map[String, MyObject] and want to create a Scala List[MyNewObject] consisting of alle entries of the map with some special values.
I found a way but, well, this is really ugly:
val result = ListBuffer[MyNewObject]()
myJavaUtilMap.forEach
(
(es: Entry[String, MyObject]) =>
{ result += MyNewObject(es.getKey(), ey.getValue().getMyParameter); println("Aa")}
)
How can I get rid of the println("Aa")? Just deleting does not help because foreach needs a Consumer but the += operation yields a list....
Is there a more elegant way to convert the java.util.Map to a List[MyNewObject]?
Scala has conversions that give you all the nice methods of the Scala collection API on Java collections:
import collection.JavaConversions._
val result = myJavaUtilMap.map{
case (k,v) => MyNewObject(k, v.getMyParameter)
}.toList
By the way: to define a function which returns Unit, you can explicitly specify the return type:
val f = (x: Int) => x: Unit
Is it possible to handle Either in similar way to Option? In Option, I have a getOrElse function, in Either I want to return Left or process Right. I'm looking for the fastest way of doing this without any boilerplate like:
val myEither:Either[String, Object] = Right(new Object())
myEither match {
case Left(leftValue) => value
case Right(righValue) =>
"Success"
}
In Scala 2.12,
Either is right-biased, which means that Right is assumed to be the default case to operate on. If it is Left, operations like map, flatMap, ... return the Left value unchanged
so you can do
myEither.map(_ => "Success").merge
if you find it more readable than fold.
You can use .fold:
scala> val r: Either[Int, String] = Right("hello")
r: Either[Int,String] = Right(hello)
scala> r.fold(_ => "got a left", _ => "Success")
res7: String = Success
scala> val l: Either[Int, String] = Left(1)
l: Either[Int,String] = Left(1)
scala> l.fold(_ => "got a left", _ => "Success")
res8: String = got a left
Edit:
Re-reading your question it's unclear to me whether you want to return the value in the Left or another one (defined elsewhere)
If it is the former, you can pass identity to .fold, however this might change the return type to Any:
scala> r.fold(identity, _ => "Success")
res9: Any = Success
Both cchantep's and Marth's are good solutions to your immediate problem. But more broadly, it's difficult to treat Either as something fully analogous to Option, particularly in letting you express sequences of potentially failable computations for comprehensions. Either has a projection API (used in cchantep's solution), but it is a bit broken. (Either's projections break in for comprehensions with guards, pattern matching, or variable assignment.)
FWIW, I've written a library to solve this problem. It augments Either with this API. You define a "bias" for your Eithers. "Right bias" means that ordinary flow (map, get, etc) is represented by a Right object while Left objects represent some kind of problem. (Right bias is conventional, although you can also define a left bias if you prefer.) Then you can treat the Either like an Option; it offers a fully analogous API.
import com.mchange.leftright.BiasedEither
import BiasedEither.RightBias._
val myEither:Either[String, Object] = ...
val o = myEither.getOrElse( "Substitute" )
More usefully, you can now treat Either like a true scala monad, i.e. use flatMap, map, filter, and for comprehensions:
val myEither : Either[String, Point] = ???
val nextEither = myEither.map( _.x ) // Either[String,Int]
or
val myEither : Either[String, Point] = ???
def findGalaxyAtPoint( p : Point ) : Either[String,Galaxy] = ???
val locPopPair : Either[String, (Point, Long)] = {
for {
p <- myEither
g <- findGalaxyAtPoint( p )
} yield {
(p, g.population)
}
}
If all processing steps succeeded, locPopPair will be a Right[Long]. If anything went wrong, it will be the first Left[String] encountered.
It's slightly more complex, but a good idea to define an empty token. Let's look at a slight variation on the for comprehension above:
val locPopPair : Either[String, (Point, Long)] = {
for {
p <- myEither
g <- findGalaxyAtPoint( p ) if p.x > 1000
} yield {
(p, g.population)
}
}
What would happen if the test p.x > 1000 failed? We'd want to return some Left that signifies "empty", but there is no universal appropriate value (not all Left's are Left[String]. As of now, what would happen is the code would throw a NoSuchElementException. But we can specify an empty token ourselves, as below:
import com.mchange.leftright.BiasedEither
val RightBias = BiasedEither.RightBias.withEmptyToken[String]("EMPTY")
import RightBias._
val myEither : Either[String, Point] = ???
def findGalaxyAtPoint( p : Point ) : Either[String,Galaxy] = ???
val locPopPair : Either[String, (Point, Long)] = {
for {
p <- myEither
g <- findGalaxyAtPoint( p ) if p.x > 1000
} yield {
(p, g.population)
}
}
Now, if the p.x > 1000 test fails, there will be no Exception, locPopPair will just be Left("EMPTY").
I guess you can do as follows.
def foo(myEither: Either[String, Object]) =
myEither.right.map(rightValue => "Success")
In scala 2.13, you can use myEither.getOrElse
Right(12).getOrElse(17) // 12
Left(12).getOrElse(17) // 17
Learning Scala and I keep wanting an equivalent to LINQ's Single() method. Example,
val collection: Seq[SomeType]
val (desiredItem, theOthers) = collection.partition(MyFunc)
desiredItem.single.doSomething
// ^^^^^^
I could use desiredItem.head but what if MyFunc actually matched several? I want the assurance that there's only one.
Edit #2 The duplicate question says 'no there isn't but here's how to build it'. So I am thinking if this was a common need it would be in the base API. Do properly written Scala programs need this?
I'd use something more verbose instead of single:
(desiredItem match {
case Seq(single) => single
case _ => throw IllegalStateException("Not a single element!")
}).doSomething
Its advantage over single is that it allows you to explicitly control the behavior in exceptional case (trow an exception, return fallback value).
Alternatively you can use destructuring assignment:
val Seq(single) = desiredItem
single.doSomething
In this case you'll get MatchError if desiredItem doesn't contain exactly one element.
UPD: I looked again at your code. Destructuring assignment is the way to go for you:
val collection: Seq[SomeType]
val (Seq(desiredItem), theOthers) = collection.partition(MyFunc)
desiredItem.doSomething
There's no prebuilt method in the API to do that. You can create your own method to do something similar though.
scala> def single[A](xs: List[A]) = xs match{
| case List() => None
| case x::Nil => Some(x)
| case x::xs => throw new Exception("More than one element")
| }
single: [A](xs: Seq[A])Option[A]
scala> single(List(1,2,3))
java.lang.Exception: More than one element
at .single(<console>:11)
... 33 elided
scala> single(List(1))
res13: Any = Some(1)
scala> single(List())
res14: Any = None
Like others indicated, there is no library implementation of what you seek. But it's easy to implement your own using a Pimp My Library approach. For example you can do the following.
object Main extends App {
object PML {
implicit class TraversableOps[T](val collection: TraversableOnce[T]) {
def single: Option[T] = collection.toList match {
case List(x) => Some(x)
case _ => None
}
}
}
import PML._
val collection: Seq[Int] = Seq(1, 2)
val (desiredItem, theOthers) = collection.partition(_ < 2)
println(desiredItem.single) // Some(1)
println(collection.single) // None
println(List.empty.single) // None
}
I wish to find a match within a List and return values dependant on the match. The CollectFirst works well for matching on the elements of the collection but in this case I want to match on the member swEl of the element rather than on the element itself.
abstract class CanvNode (var swElI: Either[CSplit, VistaT])
{
private[this] var _swEl: Either[CSplit, VistaT] = swElI
def member = _swEl
def member_= (value: Either[CSplit, VistaT] ){ _swEl = value; attach}
def attach: Unit
attach
def findVista(origV: VistaIn): Option[Tuple2[CanvNode,VistaT]] = member match
{
case Right(v) if (v == origV) => Option(this, v)
case _ => None
}
}
def nodes(): List[CanvNode] = topNode :: splits.map(i => List(i.n1, i.n2)).flatten
//Is there a better way of implementing this?
val temp: Option[Tuple2[CanvNode, VistaT]] =
nodes.map(i => i.findVista(origV)).collectFirst{case Some (r) => r}
Do I need a View on that, or will the collectFirst method ensure the collection is only created as needed?
It strikes me that this must be a fairly general pattern. Another example could be if one had a List member of the main List's elements and wanted to return the fourth element if it had one. Is there a standard method I can call? Failing that I can create the following:
implicit class TraversableOnceRichClass[A](n: TraversableOnce[A])
{
def findSome[T](f: (A) => Option[T]) = n.map(f(_)).collectFirst{case Some (r) => r}
}
And then I can replace the above with:
val temp: Option[Tuple2[CanvNode, VistaT]] =
nodes.findSome(i => i.findVista(origV))
This uses implicit classes from 2.10, for pre 2.10 use:
class TraversableOnceRichClass[A](n: TraversableOnce[A])
{
def findSome[T](f: (A) => Option[T]) = n.map(f(_)).collectFirst{case Some (r) => r}
}
implicit final def TraversableOnceRichClass[A](n: List[A]):
TraversableOnceRichClass[A] = new TraversableOnceRichClass(n)
As an introductory side node: The operation you're describing (return the first Some if one exists, and None otherwise) is the sum of a collection of Options under the "first" monoid instance for Option. So for example, with Scalaz 6:
scala> Stream(None, None, Some("a"), None, Some("b")).map(_.fst).asMA.sum
res0: scalaz.FirstOption[java.lang.String] = Some(a)
Alternatively you could put something like this in scope:
implicit def optionFirstMonoid[A] = new Monoid[Option[A]] {
val zero = None
def append(a: Option[A], b: => Option[A]) = a orElse b
}
And skip the .map(_.fst) part. Unfortunately neither of these approaches is appropriately lazy in Scalaz, so the entire stream will be evaluated (unlike Haskell, where mconcat . map (First . Just) $ [1..] is just fine, for example).
Edit: As a side note to this side note: apparently Scalaz does provide a sumr that's appropriately lazy (for streams—none of these approaches will work on a view). So for example you can write this:
Stream.from(1).map(Some(_).fst).sumr
And not wait forever for your answer, just like in the Haskell version.
But assuming that we're sticking with the standard library, instead of this:
n.map(f(_)).collectFirst{ case Some(r) => r }
I'd write the following, which is more or less equivalent, and arguably more idiomatic:
n.flatMap(f(_)).headOption
For example, suppose we have a list of integers.
val xs = List(1, 2, 3, 4, 5)
We can make this lazy and map a function with a side effect over it to show us when its elements are accessed:
val ys = xs.view.map { i => println(i); i }
Now we can flatMap an Option-returning function over the resulting collection and use headOption to (safely) return the first element, if it exists:
scala> ys.flatMap(i => if (i > 2) Some(i.toString) else None).headOption
1
2
3
res0: Option[java.lang.String] = Some(3)
So clearly this stops when we hit a non-empty value, as desired. And yes, you'll definitely need a view if your original collection is strict, since otherwise headOption (or collectFirst) can't reach back and stop the flatMap (or map) that precedes it.
In your case you can skip findVista and get even more concise with something like this:
val temp = nodes.view.flatMap(
node => node.right.toOption.filter(_ == origV).map(node -> _)
).headOption
Whether you find this clearer or just a mess is a matter of taste, of course.