I am getting an error in the extractor step (unapply method call).
The error message is: Wrong number of arguments for the extractors. found 2; expected 0
Can someone please help what is causing the error (where my misunderstanding is).
class ABC(val name:String, val age:Int) //class is defined.
object ABC{
def apply(age:Int, name:String) = new ABC(name, age)
def unapply(x:ABC) = (x.name, x.age)
}
val ins = ABC(25, "Joe") //here apply method is in action.
val ABC(x,y) = ins //unapply is indirectly called. As per my understanding , 25 and Joe suppose to be captured in x and y respectively. But this steps gives error.
The error I get is
an unapply result must have a member def isEmpty: Boolean
The easiest way to fix this is to make unapply return an Option:
def unapply(x: ABC) = Option((x.name, x.age))
The unapply method in an extractor which binds values must return an Option. This is because there's no intrinsic guarantee that an extractor will always succeed. For instance consider this massively oversimplified example of an extractor for an email address:
object Email {
def unapply(s: String): Option[(String, String)] =
s.indexOf('#') match {
case idx if idx >= 0 =>
val (user, maybeSite) = s.splitAt(idx)
if (maybeSite.length < 2 || maybeSite.lastIndexOf('#') > 0) None
else Some(user -> maybeSite.tail)
case _ => None
}
}
At the application site:
val Email(u, s) = "user3103957#stackoverflow.example.xyz"
Turns into code that's basically (from the description in Programming In Scala (Odersky, Spoon, Venners (3rd ed))):
val _tmpTuple2 =
"user3103957#stackoverflow.example.xyz" match {
case str: String =>
Email.unapply(str).getOrElse(throw ???)
case _ => throw ???
}
val u = _tmpTuple2._1
val s = _tmpTuple2._2
Technically, since the compiler already knows that the value is a String, the type check is elided, but I've included the type check for generality. The desugaring of extractors in a pattern match also need not throw except for the last extractor attempt.
Related
Is it possible to run multiple extractors in one match statement?
object CoolStuff {
def unapply(thing: Thing): Option[SomeInfo] = ...
}
object NeatStuff {
def unapply(thing: Thing): Option[OtherInfo] = ...
}
// is there some syntax similar to this?
thing match {
case t # CoolStuff(someInfo) # NeatStuff(otherInfo) => process(someInfo, otherInfo)
case _ => // neither Cool nor Neat
}
The intent here being that there are two extractors, and I don't have to do something like this:
object CoolNeatStuff {
def unapply(thing: Thing): Option[(SomeInfo, OtherInfo)] = thing match {
case CoolStuff(someInfo) => thing match {
case NeatStuff(otherInfo) => Some(someInfo -> otherInfo)
case _ => None // Cool, but not Neat
case _ => None// neither Cool nor Neat
}
}
Can try
object ~ {
def unapply[T](that: T): Option[(T,T)] = Some(that -> that)
}
def too(t: Thing) = t match {
case CoolStuff(a) ~ NeatStuff(b) => ???
}
I've come up with a very similar solution, but I was a bit too slow, so I didn't post it as an answer. However, since #userunknown asks to explain how it works, I'll dump my similar code here anyway, and add a few comments. Maybe someone finds it a valuable addition to cchantep's minimalistic solution (it looks... calligraphic? for some reason, in a good sense).
So, here is my similar, aesthetically less pleasing proposal:
object && {
def unapply[A](a: A) = Some((a, a))
}
// added some definitions to make your question-code work
type Thing = String
type SomeInfo = String
type OtherInfo = String
object CoolStuff {
def unapply(thing: Thing): Option[SomeInfo] = Some(thing.toLowerCase)
}
object NeatStuff {
def unapply(thing: Thing): Option[OtherInfo] = Some(thing.toUpperCase)
}
def process(a: SomeInfo, b: OtherInfo) = s"[$a, $b]"
val res = "helloworld" match {
case CoolStuff(someInfo) && NeatStuff(otherInfo) =>
process(someInfo, otherInfo)
case _ =>
}
println(res)
This prints
[helloworld, HELLOWORLD]
The idea is that identifiers (in particular, && and ~ in cchantep's code) can be used as infix operators in patterns. Therefore, the match-case
case CoolStuff(someInfo) && NeatStuff(otherInfo) =>
will be desugared into
case &&(CoolStuff(someInfo), NeatStuff(otherInfo)) =>
and then the unapply method method of && will be invoked which simply duplicates its input.
In my code, the duplication is achieved by a straightforward Some((a, a)). In cchantep's code, it is done with fewer parentheses: Some(t -> t). The arrow -> comes from ArrowAssoc, which in turn is provided as an implicit conversion in Predef. This is just a quick way to create pairs, usually used in maps:
Map("hello" -> 42, "world" -> 58)
Another remark: notice that && can be used multiple times:
case Foo(a) && Bar(b) && Baz(c) => ...
So... I don't know whether it's an answer or an extended comment to cchantep's answer, but maybe someone finds it useful.
For those who might miss the details on how this magic actually works, just want to expand the answer by #cchantep anf #Andrey Tyukin (comment section does not allow me to do that).
Running scalac with -Xprint:parser option will give something along those lines (scalac 2.11.12)
def too(t: String) = t match {
case $tilde(CoolStuff((a # _)), NeatStuff((b # _))) => $qmark$qmark$qmark
}
This basically shows you the initial steps compiler does while parsing source into AST.
Important Note here is that the rules why compiler makes this transformation are described in Infix Operation Patterns and Extractor Patterns. In particular, this allows you to use any object as long as it has unapply method, like for example CoolStuff(a) AndAlso NeatStuff(b). In previous answers && and ~ were picked up as also possible but not the only available valid identifiers.
If running scalac with option -Xprint:patmat which is a special phase for translating pattern matching one can see something similar to this
def too(t: String): Nothing = {
case <synthetic> val x1: String = t;
case9(){
<synthetic> val o13: Option[(String, String)] = main.this.~.unapply[String](x1);
if (o13.isEmpty.unary_!)
{
<synthetic> val p3: String = o13.get._1;
<synthetic> val p4: String = o13.get._2;
{
<synthetic> val o12: Option[String] = main.this.CoolStuff.unapply(p3);
if (o12.isEmpty.unary_!)
{
<synthetic> val o11: Option[String] = main.this.NeatStuff.unapply(p4);
if (o11.isEmpty.unary_!)
matchEnd8(scala.this.Predef.???)
Here ~.unapply will be called on input parameter t which will produce Some((t,t)). The tuple values will be extracted into variables p3 and p4. Then, CoolStuff.unapply(p3) will be called and if the result is not None NeatStuff.unapply(p4) will be called and also checked if it is not empty. If both are not empty then according to Variable Patterns a and b will be bound to returned results inside corresponding Some.
I am trying to write the following implicit:
implicit class ExtractOrElse[K, V](o: Option[Map[K, V]]) {
def extractOrElse(key: K)(f: => V): V = { if (o.isDefined) o.get(key) else f }
}
Which I want to use in this way:
normalizationContexts.extractOrElse(shardId)(defaultNormalizationContext)
to avoid a clunkier syntax (normalizationContexts is an Option[Map[String, NormzalitionContext]]).
Also, let me add that it is intentional that there is only one default value: it will be used if the Option isEmpty, but if the Option isDefined, then the behavior of the Map is not changed, and it will throw an exception if the key is not found - so the default value won't be used in that case, and this is all intentional.
However, I get an error when passing in None in unit tests:
assertEquals(None.extractOrElse('a')(0), 0)
results in:
Error:(165, 37) type mismatch;
found : Char('a')
required: K
assertEquals(None.extractOrElse('a')(0), 0)
I realize that None is not parametric, as it is defined as:
case object None extends Option[Nothing] {
def isEmpty = true
def get = throw new NoSuchElementException("None.get")
What is the best way to make this work?
Instead of None.extractOrElse(...), try Option.empty[Map[Char, Int]].extractOrElse(...).
If you always use the same types for your test cases, you could also create a type alias in the specs class in order to reduce the clutter:
type OpMap = Option[Map[Char, Int]]
// ...
assertEquals(Option.empty[OpMap].extractOrElse('a')(0), 0)
Just in case, you can use flatMap and getOrElse to achieve the same thing without writing a new method:
val n = Option.empty[Map[String, Int]]
val s = Some(Map("x" → 1, "y" → 2))
n.flatMap(_.get("x")).getOrElse(3) // 3
s.flatMap(_.get("x")).getOrElse(3) // 1
s.flatMap(_.get("z")).getOrElse(3) // 3
The type system doesn't have enough information about the types K and V. There is no way to know what the type of A would be in the case where your None was Some[A].
When I create an example with explicit types, the code works as expected:
// Like this
val e = new ExtractOrElse(Option.empty[Map[Char, Int]])
e.extractOrElse('a')(0) // Equals 0
// Or like this
val e = new ExtractOrElse[Char, Int](None)
println(e.extractOrElse('a')(0))
// Or like this
val m: Option[Map[Char, Int]] = None
val e = new ExtractOrElse(m)
println(e.extractOrElse('a')(0))
Suppose I have few case classes and functions to test them:
case class PersonName(...)
case class Address(...)
case class Phone(...)
def testPersonName(pn: PersonName): Either[String, PersonName] = ...
def testAddress(a: Address): Either[String, Address] = ...
def testPhone(p: Phone): Either[String, Phone] = ...
Now I define a new case class Person and a test function, which fails fast.
case class Person(name: PersonName, address: Address, phone: Phone)
def testPerson(person: Person): Either[String, Person] = for {
pn <- testPersonName(person.name).right
a <- testAddress(person.address).right
p <- testPhone(person.phone).right
} yield person;
Now I would like function testPerson to accumulate the errors rather than just fail fast.
I would like testPerson to always execute all those test* functions and return Either[List[String], Person]. How can I do that ?
You want to isolate the test* methods and stop using a comprehension!
Assuming (for whatever reason) that scalaz isn't an option for you... it can be done without having to add the dependency.
Unlike a lot of scalaz examples, this is one where the library doesn't reduce verbosity much more than "regular" scala can:
def testPerson(person: Person): Either[List[String], Person] = {
val name = testPersonName(person.name)
val addr = testAddress(person.address)
val phone = testPhone(person.phone)
val errors = List(name, addr, phone) collect { case Left(err) => err }
if(errors.isEmpty) Right(person) else Left(errors)
}
Scala's for-comprehensions (which desugar to a combination of calls to flatMap and map) are designed to allow you to sequence monadic computations in such a way that you have access to the result of earlier computations in subsequent steps. Consider the following:
def parseInt(s: String) = try Right(s.toInt) catch {
case _: Throwable => Left("Not an integer!")
}
def checkNonzero(i: Int) = if (i == 0) Left("Zero!") else Right(i)
def inverse(s: String): Either[String, Double] = for {
i <- parseInt(s).right
v <- checkNonzero(i).right
} yield 1.0 / v
This won't accumulate errors, and in fact there's no reasonable way that it could. Suppose we call inverse("foo"). Then parseInt will obviously fail, which means there's no way we can have a value for i, which means there's no way we could move on to the checkNonzero(i) step in the sequence.
In your case your computations don't have this kind of dependency, but the abstraction you're using (monadic sequencing) doesn't know that. What you want is an Either-like type that isn't monadic, but that is applicative. See my answer here for some details about the difference.
For example, you could write the following with Scalaz's Validation without changing any of your individual validation methods:
import scalaz._, syntax.apply._, syntax.std.either._
def testPerson(person: Person): Either[List[String], Person] = (
testPersonName(person.name).validation.toValidationNel |#|
testAddress(person.address).validation.toValidationNel |#|
testPhone(person.phone).validation.toValidationNel
)(Person).leftMap(_.list).toEither
Although of course this is more verbose than necessary and is throwing away some information, and using Validation throughout would be a little cleaner.
As #TravisBrown is telling you, for comprehensions don't really mix with error accumulations. In fact, you generally use them when you don't want fine grained error control.
A for comprehension will "short-circuit" itself on the first error found, and this is almost always what you want.
The bad thing you are doing is using String to do flow control of exceptions. You should at all times use Either[Exception, Whatever] and fine tune logging with scala.util.control.NoStackTrace and scala.util.NonFatal.
There are much better alternatives, specifically:
scalaz.EitherT and scalaz.ValidationNel.
Update:(this is incomplete, I don't know exactly what you want). You have better options than matching, such as getOrElse and recover.
def testPerson(person: Person): Person = {
val attempt = Try {
val pn = testPersonName(person.name)
val a = testAddress(person.address)
testPhone(person.phone)
}
attempt match {
case Success(person) => //..
case Failure(exception) => //..
}
}
Starting in Scala 2.13, we can partitionMap a List of Eithers in order to partition elements based on their Either's side.
// def testName(pn: Name): Either[String, Name] = ???
// def testAddress(a: Address): Either[String, Address] = ???
// def testPhone(p: Phone): Either[String, Phone] = ???
List(testName(Name("name")), testAddress(Address("address")), testPhone(Phone("phone")))
.partitionMap(identity) match {
case (Nil, List(name: Name, address: Address, phone: Phone)) =>
Right(Person(name, address, phone))
case (left, _) =>
Left(left)
}
// Either[List[String], Person] = Left(List("wrong name", "wrong phone"))
// or
// Either[List[String], Person] = Right(Person(Name("name"), Address("address"), Phone("phone")))
If the left side is empty, then no elements were Left and thus we can build a Person out of the Right elements.
Otherwise, we return a Left List of the Left values.
Details of the intermediate step (partitionMap):
List(Left("bad name"), Right(Address("addr")), Left("bad phone"))
.partitionMap(identity)
// (List[String], List[Any]) = (List("bad name", "bad phone"), List[Any](Address("addr")))
This file:
object Test extends App {
val obj = List(1,2,3) : Object
val res = obj match {
case Seq(1,2,3) => "first"
case _ => "other"
}
println(res)
}
Gives this warning:
Test.scala:6: warning: non variable type-argument A in type pattern Seq[A]
is unchecked since it is eliminated by erasure
case Seq(1,2,3) => "first"
Scala version 2.9.0.1.
I don't see how an erased type parameter is needed to perform the match. That first case clause is meant to ask if obj is a Seq with 3 elements equal to 1, 2, and 3.
I would understand this warning if I had written something like:
case strings : Seq[String] => ...
Why do I get the warning, and what is a good way to make it go away?
By the way, I do want to match against something with static type of Object. In the real code I'm parsing something like a Lisp datum - it might be an String, sequence of datums, Symbol, Number, etc.
Here is some insight to what happens behind the scene. Consider this code:
class Test {
new Object match { case x: Seq[Int] => true }
new Object match { case Seq(1) => true }
}
If you compile with scalac -Xprint:12 -unchecked, you'll see the code just before the erasure phase (id 13). For the first type pattern, you will see something like:
<synthetic> val temp1: java.lang.Object = new java.lang.Object();
if (temp1.isInstanceOf[Seq[Int]]())
For the Seq extractor pattern, you will see something like:
<synthetic> val temp3: java.lang.Object = new java.lang.Object();
if (temp3.isInstanceOf[Seq[A]]()) {
<synthetic> val temp4: Seq[A] = temp3.asInstanceOf[Seq[A]]();
<synthetic> val temp5: Some[Seq[A]] = collection.this.Seq.unapplySeq[A](temp4);
// ...
}
In both cases, there is a type test to see if the object is of type Seq (Seq[Int] and Seq[A]). Type parameters will be eliminated during the erasure phase. Thus the warning. Even though the second may be unexpected, it does make sense to check the type since if object is not of type Seq that clause won't match and the JVM can proceed to the next clause. If the type does match, then the object can be casted to Seq and unapplySeq can be called.
RE: thoredge comment on the type check. May be we are talking about different things. I was merely saying that:
(o: Object) match {
case Seq(i) => println("seq " + i)
case Array(i) => println("array " + i)
}
translates to something like:
if (o.isInstanceOf[Seq[_]]) { // type check
val temp1 = o.asInstanceOf[Seq[_]] // cast
// verify that temp1 is of length 1 and println("seq " + temp1(0))
} else if (o.isInstanceOf[Array[_]]) { // type check
val temp1 = o.asInstanceOf[Array[_]] // cast
// verify that temp1 is of length 1 and println("array " + temp1(0))
}
The type check is used so that when the cast is done there is no class cast exception.
Whether the warning non variable type-argument A in type pattern Seq[A] is unchecked since it is eliminated by erasure is justified and whether there would be cases where there could be class cast exception even with the type check, I don't know.
Edit: here is an example:
object SeqSumIs10 {
def unapply(seq: Seq[Int]) = if (seq.sum == 10) Some(seq) else None
}
(Seq("a"): Object) match {
case SeqSumIs10(seq) => println("seq.sum is 10 " + seq)
}
// ClassCastException: java.lang.String cannot be cast to java.lang.Integer
Declaring the match object outside at least makes it go away, but I'm not sure why:
class App
object Test extends App {
val obj = List(1,2,3) : Object
val MatchMe = Seq(1,2,3)
val res = obj match {
case MatchMe => "first"
case _ => "other"
}
println(res)
}
In Groovy language, it is very simple to check for null or false like:
groovy code:
def some = getSomething()
if(some) {
// do something with some as it is not null or emtpy
}
In Groovy if some is null or is empty string or is zero number etc. will evaluate to false. What is similar concise method of testing for null or false in Scala?
What is the simple answer to this part of the question assuming some is simply of Java type String?
Also another even better method in groovy is:
def str = some?.toString()
which means if some is not null then the toString method on some would be invoked instead of throwing NPE in case some was null. What is similar in Scala?
What you may be missing is that a function like getSomething in Scala probably wouldn't return null, empty string or zero number. A function that might return a meaningful value or might not would have as its return an Option - it would return Some(meaningfulvalue) or None.
You can then check for this and handle the meaningful value with something like
val some = getSomething()
some match {
case Some(theValue) => doSomethingWith(theValue)
case None => println("Whoops, didn't get anything useful back")
}
So instead of trying to encode the "failure" value in the return value, Scala has specific support for the common "return something meaningful or indicate failure" case.
Having said that, Scala's interoperable with Java, and Java returns nulls from functions all the time. If getSomething is a Java function that returns null, there's a factory object that will make Some or None out of the returned value.
So
val some = Option(getSomething())
some match {
case Some(theValue) => doSomethingWith(theValue)
case None => println("Whoops, didn't get anything useful back")
}
... which is pretty simple, I claim, and won't go NPE on you.
The other answers are doing interesting and idiomatic things, but that may be more than you need right now.
Well, Boolean cannot be null, unless passed as a type parameter. The way to handle null is to convert it into an Option, and then use all the Option stuff. For example:
Option(some) foreach { s => println(s) }
Option(some) getOrElse defaultValue
Since Scala is statically type, a thing can't be "a null or is empty string or is zero number etc". You might pass an Any which can be any of those things, but then you'd have to match on each type to be able to do anything useful with it anyway. If you find yourself in this situation, you most likely are not doing idiomatic Scala.
In Scala, the expressions you described mean that a method called ? is invoked on an object called some. Regularly, objects don't have a method called ?. You can create your own implicit conversion to an object with a ? method which checks for nullness.
implicit def conversion(x: AnyRef) = new {
def ? = x ne null
}
The above will, in essence, convert any object on which you call the method ? into the expression on the right hand side of the method conversion (which does have the ? method). For example, if you do this:
"".?
the compiler will detect that a String object has no ? method, and rewrite it into:
conversion("").?
Illustrated in an interpreter (note that you can omit . when calling methods on objects):
scala> implicit def any2hm(x: AnyRef) = new {
| def ? = x ne null
| }
any2hm: (x: AnyRef)java.lang.Object{def ?: Boolean}
scala> val x: String = "!!"
x: String = "!!"
scala> x ?
res0: Boolean = true
scala> val y: String = null
y: String = null
scala> y ?
res1: Boolean = false
So you could write:
if (some ?) {
// ...
}
Or you could create an implicit conversion into an object with a ? method which invokes the specified method on the object if the argument is not null - do this:
scala> implicit def any2hm[T <: AnyRef](x: T) = new {
| def ?(f: T => Unit) = if (x ne null) f(x)
| }
any2hm: [T <: AnyRef](x: T)java.lang.Object{def ?(f: (T) => Unit): Unit}
scala> x ? { println }
!!
scala> y ? { println }
so that you could then write:
some ? { _.toString }
Building (recursively) on soc's answer, you can pattern match on x in the examples above to refine what ? does depending on the type of x. :D
If you use extempore's null-safe coalescing operator, then you could write your str example as
val str = ?:(some)(_.toString)()
It also allows you to chain without worrying about nulls (thus "coalescing"):
val c = ?:(some)(_.toString)(_.length)()
Of course, this answer only addresses the second part of your question.
You could write some wrapper yourself or use an Option type.
I really wouldn't check for null though. If there is a null somewhere, you should fix it and not build checks around it.
Building on top of axel22's answer:
implicit def any2hm(x: Any) = new {
def ? = x match {
case null => false
case false => false
case 0 => false
case s: String if s.isEmpty => false
case _ => true
}
}
Edit: This seems to either crash the compiler or doesn't work. I'll investigate.
What you ask for is something in the line of Safe Navigation Operator (?.) of Groovy, andand gem of Ruby, or accessor variant of the existential operator (?.) of CoffeeScript. For such cases, I generally use ? method of my RichOption[T], which is defined as follows
class RichOption[T](option: Option[T]) {
def ?[V](f: T => Option[V]): Option[V] = option match {
case Some(v) => f(v)
case _ => None
}
}
implicit def option2RichOption[T](option: Option[T]): RichOption[T] =
new RichOption[T](option)
and used as follows
scala> val xs = None
xs: None.type = None
scala> xs.?(_ => Option("gotcha"))
res1: Option[java.lang.String] = None
scala> val ys = Some(1)
ys: Some[Int] = Some(1)
scala> ys.?(x => Some(x * 2))
res2: Option[Int] = Some(2)
Using pattern matching as suggested in a couple of answers here is a nice approach:
val some = Option(getSomething())
some match {
case Some(theValue) => doSomethingWith(theValue)
case None => println("Whoops, didn't get anything useful back")
}
But, a bit verbose.
I prefer to map an Option in the following way:
Option(getSomething()) map (something -> doSomethingWith(something))
One liner, short, clear.
The reason to that is Option can be viewed as some kind of collection – some special snowflake of a collection that contains either zero elements or exactly one element of a type and as as you can map a List[A] to a List[B], you can map an Option[A] to an Option[B]. This means that if your instance of Option[A] is defined, i.e. it is Some[A], the result is Some[B], otherwise it is None. It's really powerful!