Say I have a monadic function in called processOne defined like this:
def processOne(input: Input): Either[ErrorType, Output] = ...
Given a list of "Inputs", I would like to return a corresponding list of "Outputs" wrapped in an Either:
def processMany(inputs: Seq[Input]): Either[ErrorType, Seq[Output]] = ...
processMany will call processOne for each input it has, however, I would like it to terminate the first time (if any) that processOne returns a Left, and return that Left, otherwise return a Right with a list of the outputs.
My question: what is the best way to implement processMany? Is it possible to accomplish this behavior using a for expression, or is it going to be necessary for me to iterate the list myself recursively?
With Scalaz 7:
def processMany(inputs: Seq[Input]): Either[ErrorType, Seq[Output]] =
inputs.toStream traverseU processOne
Converting inputs to a Stream[Input] takes advantage of the non-strict traverse implementation for Stream, i.e. gives you the short-circuiting behaviour you want.
By the way, you tagged this "monads", but traversal requires only an applicative functor (which, as it happens, is probably defined in terms of the monad for Either). For further reference, see the paper The Essence of the Iterator Pattern, or, for a Scala-based interpretation, Eric Torreborre's blog post on the subject.
The easiest with standard Scala, which doesn't evaluate more than is necessary, would probably be
def processMany(inputs: Seq[Input]): Either[ErrorType, Seq[Output]] = {
Right(inputs.map{ x =>
processOne(x) match {
case Right(r) => r
case Left(l) => return Left(l)
}
})
}
A fold would be more compact, but wouldn't short-circuit when it hit a left (it'd just keep carrying it along while you iterated through the entire input).
For now, I've decided to just solve this using recursion, as I am reluctant to add a dependency to a library (Scalaz).
(Types and names in my application have been changed here in order to appear more generic)
def processMany(inputs: Seq[Input]): Either[ErrorType, Seq[Output]] = {
import scala.annotation.tailrec
#tailrec
def traverse(acc: Vector[Output], inputs: List[Input]): Either[ErrorType, Seq[Output]] = {
inputs match {
case Nil => Right(acc)
case input :: more =>
processOne(input) match {
case Right(output) => traverse(acc :+ output, more)
case Left(e) => Left(e)
}
}
}
traverse(Vector[Output](), inputs.toList)
}
Related
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)
}
}
}
I have a Scala Option[T]. If the value is Some(x) I want to process it with a a process that does not return a value (Unit), but if it is None, I want to print an error.
I can use the following code to do this, but I understand that the more idiomatic way is to treat the Option[T] as a sequence and use map, foreach, etc. How do I do this?
opt match {
case Some(x) => // process x with no return value, e.g. write x to a file
case None => // print error message
}
I think explicit pattern matching suits your use case best.
Scala's Option is, sadly, missing a method to do exactly this. I add one:
class OptionWrapper[A](o: Option[A]) {
def fold[Z](default: => Z)(action: A => Z) = o.map(action).getOrElse(default)
}
implicit def option_has_utility[A](o: Option[A]) = new OptionWrapper(o)
which has the slightly nicer (in my view) usage
op.fold{ println("Empty!") }{ x => doStuffWith(x) }
You can see from how it's defined that map/getOrElse can be used instead of pattern matching.
Alternatively, Either already has a fold method. So you can
op.toRight(()).fold{ _ => println("Empty!") }{ x => doStuffWith(x) }
but this is a little clumsy given that you have to provide the left value (here (), i.e. Unit) and then define a function on that, rather than just stating what you want to happen on None.
The pattern match isn't bad either, especially for longer blocks of code. For short ones, the overhead of the match starts getting in the way of the point. For example:
op.fold{ printError }{ saveUserInput }
has a lot less syntactic overhead than
op match {
case Some(x) => saveUserInput(x)
case None => printError
}
and therefore, once you expect it, is a lot easier to comprehend.
I'd recommend to simply and safely use opt.get which itself throws a NoSuchElementException exception if opt is None. Or if you want to throw your own exception, you can do this:
val x = opt.getOrElse(throw new Exception("Your error message"))
// x is of type T
as #missingfaktor says, you are in the exact scenario where pattern matching is giving the most readable results.
If Option has a value you want to do something, if not you want to do something else.
While there are various ways to use map and other functional constructs on Option types, they are generally useful when:
you want to use the Some case and ignore the None case e.g. in your case
opt.map(writeToFile(_)) //(...if None just do nothing)
or you want to chain the operations on more than one option and give a result only when all of them are Some. For instance, one way of doing this is:
val concatThreeOptions =
for {
n1 <- opt1
n2 <- opt2
n3 <- opt3
} yield n1 + n2 + n3 // this will be None if any of the three is None
// we will either write them all to a file or none of them
but none of these seem to be your case
Pattern matching is the best choice here.
However, if you want to treat Option as a sequence and to map over it, you can do it, because Unit is a value:
opt map { v =>
println(v) // process v (result type is Unit)
} getOrElse {
println("error")
}
By the way, printing an error is some kind of "anti-pattern", so it's better to throw an exception anyway:
opt.getOrElse(throw new SomeException)
In Scala, I have progressively lost my Java/C habit of thinking in a control-flow oriented way, and got used to go ahead and get the object I'm interested in first, and then usually apply something like a match or a map() or foreach() for collections. I like it a lot, since it now feels like a more natural and more to-the-point way of structuring my code.
Little by little, I've wished I could program the same way for conditions; i.e., obtain a Boolean value first, and then match it to do various things. A full-blown match, however, does seem a bit overkill for this task.
Compare:
obj.isSomethingValid match {
case true => doX
case false => doY
}
vs. what I would write with style closer to Java:
if (obj.isSomethingValid)
doX
else
doY
Then I remembered Smalltalk's ifTrue: and ifFalse: messages (and variants thereof). Would it be possible to write something like this in Scala?
obj.isSomethingValid ifTrue doX else doY
with variants:
val v = obj.isSomethingValid ifTrue someVal else someOtherVal
// with side effects
obj.isSomethingValid ifFalse {
numInvalid += 1
println("not valid")
}
Furthermore, could this style be made available to simple, two-state types like Option? I know the more idiomatic way to use Option is to treat it as a collection and call filter(), map(), exists() on it, but often, at the end, I find that I want to perform some doX if it is defined, and some doY if it isn't. Something like:
val ok = resultOpt ifSome { result =>
println("Obtained: " + result)
updateUIWith(result) // returns Boolean
} else {
numInvalid += 1
println("missing end result")
false
}
To me, this (still?) looks better than a full-blown match.
I am providing a base implementation I came up with; general comments on this style/technique and/or better implementations are welcome!
First: we probably cannot reuse else, as it is a keyword, and using the backticks to force it to be seen as an identifier is rather ugly, so I'll use otherwise instead.
Here's an implementation attempt. First, use the pimp-my-library pattern to add ifTrue and ifFalse to Boolean. They are parametrized on the return type R and accept a single by-name parameter, which should be evaluated if the specified condition is realized. But in doing so, we must allow for an otherwise call. So we return a new object called Otherwise0 (why 0 is explained later), which stores a possible intermediate result as a Option[R]. It is defined if the current condition (ifTrue or ifFalse) is realized, and is empty otherwise.
class BooleanWrapper(b: Boolean) {
def ifTrue[R](f: => R) = new Otherwise0[R](if (b) Some(f) else None)
def ifFalse[R](f: => R) = new Otherwise0[R](if (b) None else Some(f))
}
implicit def extendBoolean(b: Boolean): BooleanWrapper = new BooleanWrapper(b)
For now, this works and lets me write
someTest ifTrue {
println("OK")
}
But, without the following otherwise clause, it cannot return a value of type R, of course. So here's the definition of Otherwise0:
class Otherwise0[R](intermediateResult: Option[R]) {
def otherwise[S >: R](f: => S) = intermediateResult.getOrElse(f)
def apply[S >: R](f: => S) = otherwise(f)
}
It evaluates its passed named argument if and only if the intermediate result it got from the preceding ifTrue or ifFalse is undefined, which is exactly what is wanted. The type parametrization [S >: R] has the effect that S is inferred to be the most specific common supertype of the actual type of the named parameters, such that for instance, r in this snippet has an inferred type Fruit:
class Fruit
class Apple extends Fruit
class Orange extends Fruit
val r = someTest ifTrue {
new Apple
} otherwise {
new Orange
}
The apply() alias even allows you to skip the otherwise method name altogether for short chunks of code:
someTest.ifTrue(10).otherwise(3)
// equivalently:
someTest.ifTrue(10)(3)
Finally, here's the corresponding pimp for Option:
class OptionExt[A](option: Option[A]) {
def ifNone[R](f: => R) = new Otherwise1(option match {
case None => Some(f)
case Some(_) => None
}, option.get)
def ifSome[R](f: A => R) = new Otherwise0(option match {
case Some(value) => Some(f(value))
case None => None
})
}
implicit def extendOption[A](opt: Option[A]): OptionExt[A] = new OptionExt[A](opt)
class Otherwise1[R, A1](intermediateResult: Option[R], arg1: => A1) {
def otherwise[S >: R](f: A1 => S) = intermediateResult.getOrElse(f(arg1))
def apply[S >: R](f: A1 => S) = otherwise(f)
}
Note that we now also need Otherwise1 so that we can conveniently passed the unwrapped value not only to the ifSome function argument, but also to the function argument of an otherwise following an ifNone.
You may be looking at the problem too specifically. You would probably be better off with the pipe operator:
class Piping[A](a: A) { def |>[B](f: A => B) = f(a) }
implicit def pipe_everything[A](a: A) = new Piping(a)
Now you can
("fish".length > 5) |> (if (_) println("Hi") else println("Ho"))
which, admittedly, is not quite as elegant as what you're trying to achieve, but it has the great advantage of being amazingly versatile--any time you want to put an argument first (not just with booleans), you can use it.
Also, you already can use options the way you want:
Option("fish").filter(_.length > 5).
map (_ => println("Hi")).
getOrElse(println("Ho"))
Just because these things could take a return value doesn't mean you have to avoid them. It does take a little getting used to the syntax; this may be a valid reason to create your own implicits. But the core functionality is there. (If you do create your own, consider fold[B](f: A => B)(g: => B) instead; once you're used to it the lack of the intervening keyword is actually rather nice.)
Edit: Although the |> notation for pipe is somewhat standard, I actually prefer use as the method name, because then def reuse[B,C](f: A => B)(g: (A,B) => C) = g(a,f(a)) seems more natural.
Why don't just use it like this:
val idiomaticVariable = if (condition) {
firstExpression
} else {
secondExpression
}
?
IMO, its very idiomatic! :)
I found myself writing something like this quite often:
a match {
case `b` => // do stuff
case _ => // do nothing
}
Is there a shorter way to check if some value matches a pattern? I mean, in this case I could just write if (a == b) // do stuff, but what if the pattern is more complex? Like when matching against a list or any pattern of arbitrary complexity. I'd like to be able to write something like this:
if (a matches b) // do stuff
I'm relatively new to Scala, so please pardon, if I'm missing something big :)
This is exactly why I wrote these functions, which are apparently impressively obscure since nobody has mentioned them.
scala> import PartialFunction._
import PartialFunction._
scala> cond("abc") { case "def" => true }
res0: Boolean = false
scala> condOpt("abc") { case x if x.length == 3 => x + x }
res1: Option[java.lang.String] = Some(abcabc)
scala> condOpt("abc") { case x if x.length == 4 => x + x }
res2: Option[java.lang.String] = None
The match operator in Scala is most powerful when used in functional style. This means, rather than "doing something" in the case statements, you would return a useful value. Here is an example for an imperative style:
var value:Int = 23
val command:String = ... // we get this from somewhere
command match {
case "duplicate" => value = value * 2
case "negate" => value = -value
case "increment" => value = value + 1
// etc.
case _ => // do nothing
}
println("Result: " + value)
It is very understandable that the "do nothing" above hurts a little, because it seems superflous. However, this is due to the fact that the above is written in imperative style. While constructs like these may sometimes be necessary, in many cases you can refactor your code to functional style:
val value:Int = 23
val command:String = ... // we get this from somewhere
val result:Int = command match {
case "duplicate" => value * 2
case "negate" => -value
case "increment" => value + 1
// etc.
case _ => value
}
println("Result: " + result)
In this case, you use the whole match statement as a value that you can, for example, assign to a variable. And it is also much more obvious that the match statement must return a value in any case; if the last case would be missing, the compiler could not just make something up.
It is a question of taste, but some developers consider this style to be more transparent and easier to handle in more real-world examples. I would bet that the inventors of the Scala programming language had a more functional use in mind for match, and indeed the if statement makes more sense if you only need to decide whether or not a certain action needs to be taken. (On the other hand, you can also use if in the functional way, because it also has a return value...)
This might help:
class Matches(m: Any) {
def matches[R](f: PartialFunction[Any, R]) { if (f.isDefinedAt(m)) f(m) }
}
implicit def any2matches(m: Any) = new Matches(m)
scala> 'c' matches { case x: Int => println("Int") }
scala> 2 matches { case x: Int => println("Int") }
Int
Now, some explanation on the general nature of the problem.
Where may a match happen?
There are three places where pattern matching might happen: val, case and for. The rules for them are:
// throws an exception if it fails
val pattern = value
// filters for pattern, but pattern cannot be "identifier: Type",
// though that can be replaced by "id1 # (id2: Type)" for the same effect
for (pattern <- object providing map/flatMap/filter/withFilter/foreach) ...
// throws an exception if none of the cases match
value match { case ... => ... }
There is, however, another situation where case might appear, which is function and partial function literals. For example:
val f: Any => Unit = { case i: Int => println(i) }
val pf: PartialFunction[Any, Unit] = { case i: Int => println(i) }
Both functions and partial functions will throw an exception if called with an argument that doesn't match any of the case statements. However, partial functions also provide a method called isDefinedAt which can test whether a match can be made or not, as well as a method called lift, which will turn a PartialFunction[T, R] into a Function[T, Option[R]], which means non-matching values will result in None instead of throwing an exception.
What is a match?
A match is a combination of many different tests:
// assign anything to x
case x
// only accepts values of type X
case x: X
// only accepts values matches by pattern
case x # pattern
// only accepts a value equal to the value X (upper case here makes a difference)
case X
// only accepts a value equal to the value of x
case `x`
// only accept a tuple of the same arity
case (x, y, ..., z)
// only accepts if extractor(value) returns true of Some(Seq()) (some empty sequence)
case extractor()
// only accepts if extractor(value) returns Some something
case extractor(x)
// only accepts if extractor(value) returns Some Seq or Tuple of the same arity
case extractor(x, y, ..., z)
// only accepts if extractor(value) returns Some Tuple2 or Some Seq with arity 2
case x extractor y
// accepts if any of the patterns is accepted (patterns may not contain assignable identifiers)
case x | y | ... | z
Now, extractors are the methods unapply or unapplySeq, the first returning Boolean or Option[T], and the second returning Option[Seq[T]], where None means no match is made, and Some(result) will try to match result as described above.
So there are all kinds of syntactic alternatives here, which just aren't possible without the use of one of the three constructions where pattern matches may happen. You may able to emulate some of the features, like value equality and extractors, but not all of them.
Patterns can also be used in for expressions. Your code sample
a match {
case b => // do stuff
case _ => // do nothing
}
can then be expressed as
for(b <- Some(a)) //do stuff
The trick is to wrap a to make it a valid enumerator. E.g. List(a) would also work, but I think Some(a) is closest to your intended meaning.
The best I can come up with is this:
def matches[A](a:A)(f:PartialFunction[A, Unit]) = f.isDefinedAt(a)
if (matches(a){case ... =>}) {
//do stuff
}
This won't win you any style points though.
Kim's answer can be “improved” to better match your requirement:
class AnyWrapper[A](wrapped: A) {
def matches(f: PartialFunction[A, Unit]) = f.isDefinedAt(wrapped)
}
implicit def any2wrapper[A](wrapped: A) = new AnyWrapper(wrapped)
then:
val a = "a" :: Nil
if (a matches { case "a" :: Nil => }) {
println("match")
}
I wouldn't do it, however. The => }) { sequence is really ugly here, and the whole code looks much less clear than a normal match. Plus, you get the compile-time overhead of looking up the implicit conversion, and the run-time overhead of wrapping the match in a PartialFunction (not counting the conflicts you could get with other, already defined matches methods, like the one in String).
To look a little bit better (and be less verbose), you could add this def to AnyWrapper:
def ifMatch(f: PartialFunction[A, Unit]): Unit = if (f.isDefinedAt(wrapped)) f(wrapped)
and use it like this:
a ifMatch { case "a" :: Nil => println("match") }
which saves you your case _ => line, but requires double braces if you want a block instead of a single statement... Not so nice.
Note that this construct is not really in the spirit of functional programming, as it can only be used to execute something that has side effects. We can't easily use it to return a value (therefore the Unit return value), as the function is partial — we'd need a default value, or we could return an Option instance. But here again, we would probably unwrap it with a match, so we'd gain nothing.
Frankly, you're better off getting used to seeing and using those match frequently, and moving away from this kind of imperative-style constructs (following Madoc's nice explanation).
Basically, I would like to be able to build a custom extractor without having to store it in a variable prior to using it.
This isn't a real example of how I would use it, it would more likely be used in the case of a regular expression or some other string pattern like construct, but hopefully it explains what I'm looking for:
def someExtractorBuilder(arg:Boolean) = new {
def unapply(s:String):Option[String] = if(arg) Some(s) else None
}
//I would like to be able to use something like this
val {someExtractorBuilder(true)}(result) = "test"
"test" match {case {someExtractorBuilder(true)}(result) => result }
//instead I would have to do this:
val customExtractor = someExtractorBuilder(true)
val customExtractor(result) = "test"
"test" match {case customExtractor(result) => result}
When just doing a single custom extractor it doesn't make much difference, but if you were building a large list of extractors for a case statement, it could make things more difficult to read by separating all of the extractors from their usage.
I expect that the answer is no you can't do this, but I thought I'd ask around first :D
Parameterising extractors would be cool, but we don't have the resources to implement them right now.
Nope.
8.1.7 Extractor Patterns
An extractor pattern x (p 1 , . . . ,
p n ) where n ≥ 0 is of the same
syntactic form as a constructor
pattern. However, instead of a case
class, the stable identifier x denotes
an object which has a member method
named unapply or unapplySeq that
matches the pattern.
One can customize extractors to certain extent using implicit parameters, like this:
object SomeExtractorBuilder {
def unapply(s: String)(implicit arg: Boolean): Option[String] = if (arg) Some(s) else None
}
implicit val arg: Boolean = true
"x" match {
case SomeExtractorBuilder(result) =>
result
}
Unfortunately this cannot be used when you want to use different variants in one match, as all case statements are in the same scope. Still, it can be useful sometimes.
Late but there is a scalac plugin in one of my lib providing syntax ~(extractorWith(param), bindings):
x match {
case ~(parametrizedExtractor(param)) =>
"no binding"
case ~(parametrizedExtractor(param), (a, b)) =>
s"extracted bindings: $a, $b"
}
https://github.com/cchantep/acolyte/blob/master/scalac-plugin/readme.md
Though what you are asking isn't directly possible,
it is possible to create an extractor returning a contaner that gets evaluated value in the if-part of the case evaluation. In the if part it is possible to provide parameters.
object DateExtractor {
def unapply(in: String): Option[DateExtractor] = Some(new DateExtractor(in));
}
class DateExtractor(input:String){
var value:LocalDate=null;
def apply():LocalDate = value;
def apply(format: String):Boolean={
val formater=DateTimeFormatter.ofPattern(format);
try{
val parsed=formater.parse(input, TemporalQueries.localDate());
value=parsed
true;
} catch {
case e:Throwable=>{
false
}
}
}
}
Usage:
object DateExtractorUsage{
def main(args: Array[String]): Unit = {
"2009-12-31" match {
case DateExtractor(ext) if(ext("dd-MM-yyyy"))=>{
println("Found dd-MM-yyyy date:"+ext())
}
case DateExtractor(ext) if(ext("yyyy-MM-dd"))=>{
println("Found yyyy-MM-dd date:"+ext())
}
case _=>{
println("Unable to parse date")
}
}
}
}
This pattern preserves the PartialFunction nature of the piece of code. I find this useful since I am quite a fan of the collect/collectFirst methods, which take a partial function as a parameter and typically does not leave room for precreating a set of extractors.