how do I build with scalac using Leon's library? - scala

I am trying to compile my Leon code using scalac directly. Unfortunately, I was not able to properly build the Leon library on which the code depends.
For instance, I have run
scalac $(find ~/my-path/leon/library/ -name "*.scala" | xargs) Queue.scala
But this actually returns errors:
.../leon/library/collection/List.scala:81: error: missing parameter type for expanded function ((x$2) => x$2.size.$eq$eq(if (i.$less$eq(0))
BigInt(0)
else
if (i.$greater$eq(this.size))
this.size
else
i))
}} ensuring { _.size == (
^
What should be passed to scalac to avoid those errors in the library and ultimately compile my own source file?
Thank you!

First of all, I suspect that the attempt here was to execute Leon programs, if so, there is a new option called --eval which will evaluate all ground functions (you can filter it further through --functions as usual). This should prevent issues with skeleton implementations being non-executable.
About the compilation issue: it should now be fixed in https://github.com/epfl-lara/leon/commit/3d73c6447916516d0ad56806fe0febf7b30a71ad
This was due to type-inference not being able to track types from the declared return type, through the untyped ensuring, to the body of the function. This causes Nil() to be imprecisely typed in the body, which in turn causes the type-less closure to be rejected.
Why did this work within Leon? Leon inserts a phase in the Scala compiler pipeline before type-checking to inject hints that make this inference possible (and convenient), since the pattern
def foo(a: A): B = { a match {
case ..
case ..
}} ensuring { .. }
is so frequent in Leon programs.

Oddly enough, writing something like:
def take(i: BigInt): List[T] = { val res: List[T] = (this, i) match {
case (Nil(), _) => Nil()
case (Cons(h, t), i) =>
if (i <= BigInt(0)) {
Nil()
} else {
Cons(h, t.take(i-1))
}
}; res} ensuring { _.size == (
if (i <= 0) BigInt(0)
else if (i >= this.size) this.size
else i
)}
...makes it clearly explicit. Scalac was not able to infer the proper parameter type, but this makes the return type of the first block explicit enough. Note however that this is not a problem using Leon directly, and that is a common syntax used throughout the Leon library, not my code.
By changing all functions as explained above I was able to compile the Leon Library - but not to run the project using normal scala syntax, since the set implementation in https://github.com/epfl-lara/leon/blob/master/library/lang/Set.scala, which is somehow not used by Leon, is missing.

Following Etienne post:
That works, but we still need to implement sets in https://github.com/epfl-lara/leon/blob/master/library/lang/Set.scala. I did it that way:
package leon.lang
import leon.annotation._
import scala.collection.{ immutable => imm }
object Set {
#library
def empty[T] = Set[T]()
protected[Set] def apply[T](elems: imm.Set[T]): Set[T] = Set(elems.toSeq :_*)
}
#ignore
case class Set[T](elems: T*) {
def +(a: T): Set[T] = Set(elems.toSet + a)
def ++(a: Set[T]): Set[T] = Set(elems.toSet ++ a.elems.toSet) //Set.trim(elems ++ a.elems) //Set((elems.toSeq ++ a.elems.toSeq).toSet.toSeq :_*)
def -(a: T): Set[T] = Set(elems.toSet - a)
def --(a: Set[T]): Set[T] = Set(elems.toSet -- a.elems.toSet)
def contains(a: T): Boolean = elems.toSet.contains(a)
def isEmpty: Boolean = this == Set.empty
def subsetOf(b: Set[T]): Boolean = elems.toSet.forall(e => b.elems.toSet.contains(e))
def &(a: Set[T]): Set[T] = Set(elems.toSet & a.elems.toSet)
}
Unfortunately this cannot be used directly as is in Leon:
[ Error ] 8:31: Scala's Set API is no longer extracted. Make sure you import leon.lang.Set that defines supported Set operations.
protected[Set] def apply[T](elems: imm.Set[T]): Set[T] = Set(elems.toSeq :_*)
^^^^^^^^^^^^^^^^^
But it works fine for compiling with scalac and running with scala using:
scalac $(find ~/my-path/leon/library/ -name "*.scala" | xargs) Queue.scala
Anyway, if --eval does the trick, let's just use it!
Thank you!

Related

How to normalise a Union Type (T | Option[T])?

I have the following case class:
case class Example[T](
obj: Option[T] | T = None,
)
This allows me to construct it like Example(myObject) instead of Example(Some(myObject)).
To work with obj I need to normalise it to Option[T]:
lazy val maybeIn = obj match
case o: Option[T] => o
case o: T => Some(o)
the type test for Option[T] cannot be checked at runtime
I tried with TypeTest but I got also warnings - or the solutions I found look really complicated - see https://stackoverflow.com/a/69608091/2750966
Is there a better way to achieve this pattern in Scala 3?
I don't know about Scala3. But you could simply do this:
case class Example[T](v: Option[T] = None)
object Example {
def apply[T](t: T): Example[T] = Example(Some(t))
}
One could also go for implicit conversion, regarding the specific use case of the OP:
import scala.language.implicitConversions
case class Optable[Out](value: Option[Out])
object Optable {
implicit def fromOpt[T](o: Option[T]): Optable[T] = Optable(o)
implicit def fromValue[T](v: T): Optable[T] = Optable(Some(v))
}
case class SomeOpts(i: Option[Int], s: Option[String])
object SomeOpts {
def apply(i: Optable[Int], s: Optable[String]): SomeOpts = SomeOpts(i.value, s.value)
}
println(SomeOpts(15, Some("foo")))
We have a specialized Option-like type for this purpose: OptArg (in Scala 2 but should be easily portable to 3)
import com.avsystem.commons._
def gimmeLotsOfParams(
intParam: OptArg[Int] = OptArg.Empty,
strParam: OptArg[String] = OptArg.Empty
): Unit = ???
gimmeLotsOfParams(42)
gimmeLotsOfParams(strParam = "foo")
It relies on an implicit conversion so you have to be a little careful with it, i.e. don't use it as a drop-in replacement for Option.
The implementation of OptArg is simple enough that if you don't want external dependencies then you can probably just copy it into your project or some kind of "commons" library.
EDIT: the following answer is incorrect. As of Scala 3.1, flow analysis is only able to check for nullability. More information is available on the Scala book.
I think that the already given answer is probably better suited for the use case you proposed (exposing an API can can take a simple value and normalize it to an Option).
However, the question in the title is still interesting and I think it makes sense to address it.
What you are observing is a consequence of type parameters being erased at runtime, i.e. they only exist during compilation, while matching happens at runtime, once those have been erased.
However, the Scala compiler is able to perform flow analysis for union types. Intuitively I'd say there's probably a way to make it work in pattern matching (as you did), but you can make it work for sure using an if and isInstanceOf (not as clean, I agree):
case class Example[T](
obj: Option[T] | T = None
) {
lazy val maybeIn =
if (obj.isInstanceOf[Option[_]]) {
obj
} else {
Some(obj)
}
}
You can play around with this code here on Scastie.
Here is the announcement from 2019 when flow analysis was added to the compiler.

EitherT + State type mismatch

I'm working on a small program using Scala Cats. I'm encountering lots of type errors when trying to use EitherT with State and for comprehensions. For instance:
import cats.data.{EitherT, State}
import cats.data.State.get
object Test {
type IntState[T] = State[Int, T]
type IntStateEither[T] = EitherT[IntState, String, T]
val test: IntStateEither[Unit] = for {
isValid <- EitherT.right(get.map((it: Int) => it % 2 == 0))
_ <- if (!isValid) EitherT.leftT("invalid number") else EitherT.rightT(()) // *
} yield ()
}
Which gives me:
(...) Test.scala:12: type mismatch;
found : cats.data.EitherT[[A(in value <local Id>)]A(in value <local Id>),_1,Unit] where type _1 <: String
required: cats.data.EitherT[[A(in class IndexedStateT)]cats.data.IndexedStateT[cats.Eval,Int,Int,A(in class IndexedStateT)],String,Unit]
one error found
If I comment out the line marked (*) above, this code compiles. I think I'm following the instructions on the Cats website under "From A or B to EitherT[F, A, B]" correctly, but do I need to give more type hints? If yes, I'm not sure where I can add them.
Any pointers are greatly appreciated!
I'm using Cats 2.0.0 and Scala 2.13.2.
It seems that the problem is that the compiler is not able to infer the correct types for EitherT.leftT and EitherT.rightT.
You can fix those errors using explicit types like: EitherT.rightT[IntState, String], or if you only need one flatMap call, it seems doing it explicitly does work:
val test: IntStateEither[Unit] =
EitherT
.right[String](State.get[Int].map(it => it % 2 == 0))
.flatMap { isValid =>
if (isValid) EitherT.rightT(())
else EitherT.leftT("invalid number")
}
PS: It may be worth checking if bm4 helps.

Get sequence of types from HList in macro

Context: I'm trying to write a macro that is statically aware of an non-fixed number of types. I'm trying to pass these types as a single type parameter using an HList. It would be called as m[ConcreteType1 :: ConcreteType2 :: ... :: HNil](). The macro then builds a match statement which requires some implicits to be found at compile time, a bit like how a json serialiser might demand implicit encoders. I've got a working implementation of the macro when used on a fixed number of type parameters, as follows:
def m[T1, T2](): Int = macro mImpl[T1, T2]
def mImpl[T1: c.WeakTypeTag, T2: c.WeakTypeTag](c: Context)(): c.Expr[Int] = {
import c.universe._
val t = Seq(
weakTypeOf[T1],
weakTypeOf[T2]
).map(c => cq"a: $c => externalGenericCallRequiringImplicitsAndReturningInt(a)")
val cases = q"input match { case ..$t }"
c.Expr[Int](cases)
}
Question: If I have a WeakTypeTag[T] for some T <: HList, is there any way to turn that into a Seq[Type]?
def hlistToSeq[T <: HList](hlistType: WeakTypeTag[T]): Seq[Type] = ???
My instinct is to write a recursive match which turns each T <: HList into either H :: T or HNil, but I don't think that kind of matching exists in scala.
I'd like to hear of any other way to get a list of arbitrary size of types into a macro, bearing in mind that I would need a Seq[Type], not Expr[Seq[Type]], as I need to map over them in macro code.
A way of writing a similar 'macro' in Dotty would be interesting too - I'm hoping it'll be simpler there, but haven't fully investigated yet.
Edit (clarification): The reason I'm using a macro is that I want a user of the library I'm writing to provide a collection of types (perhaps in the form of an HList), which the library can iterate over and expect implicits relating to. I say library, but it will be compiled together with the uses, in order for the macros to run; in any case it should be reusable with different collections of types. It's a bit confusing, but I think I've worked this bit out - I just need to be able to build macros that can operate on lists of types.
Currently you seem not to need macros. It seems type classes or shapeless.Poly can be enough.
def externalGenericCallRequiringImplicitsAndReturningInt[C](a: C)(implicit
mtc: MyTypeclass[C]): Int = mtc.anInt
trait MyTypeclass[C] {
def anInt: Int
}
object MyTypeclass {
implicit val mtc1: MyTypeclass[ConcreteType1] = new MyTypeclass[ConcreteType1] {
override val anInt: Int = 1
}
implicit val mtc2: MyTypeclass[ConcreteType2] = new MyTypeclass[ConcreteType2] {
override val anInt: Int = 2
}
//...
}
val a1: ConcreteType1 = null
val a2: ConcreteType2 = null
externalGenericCallRequiringImplicitsAndReturningInt(a1) //1
externalGenericCallRequiringImplicitsAndReturningInt(a2) //2

How to write this three-liner as a one-liner?

I like the way, you can write one-liner-methods in Scala, e.g. with List(1, 2, 3).foreach(..).map(..).
But there is a certain situation, that sometimes comes up when writing Scala code, where things get a bit ugly. Example:
def foo(a: A): Int = {
// do something with 'a' which results in an integer
// e.g. 'val result = a.calculateImportantThings
// clean up object 'a'
// e.g. 'a.cleanUp'
// Return the result of the previous calculation
return result
}
In this situation we have to return a result, but can not return it directly after the calculation is done, because we have to do some clean up before returning.
I always have to write a three-liner. Is there also a possibility to write a one-liner to do this (without changing the class of A, because this may be a external library which can not be changed) ?
There are clearly side-effects involved here (otherwise the order of invocation of calculateImportantThings and cleanUp wouldn't matter) so you would be well advised to reconsider your design.
However, if that's not an option you could try something like,
scala> class A { def cleanUp {} ; def calculateImportantThings = 23 }
defined class A
scala> val a = new A
a: A = A#927eadd
scala> (a.calculateImportantThings, a.cleanUp)._1
res2: Int = 23
The tuple value (a, b) is equivalent to the application Tuple2(a, b) and the Scala specification guarantees that its arguments will be evaluated left to right, which is what you want here.
This is a perfect use-case for try/finally:
try a.calculateImportantThings finally a.cleanUp
This works because try/catch/finally is an expression in scala, meaning it returns a value, and even better, you get the cleanup whether or not the calculation throws an exception.
Example:
scala> val x = try 42 finally println("complete")
complete
x: Int = 42
There is, in fact, a Haskell operator for just such an occasion:
(<*) :: Applicative f => f a -> f b -> f a
For example:
ghci> getLine <* putStrLn "Thanks for the input!"
asdf
Thanks for the input!
"asdf"
All that remains then is to discover the same operator in scalaz, since scalaz usually replicates everything that Haskell has. You can wrap values in Identity, since Scala doesn't have IO to classify effects. The result would look something like this:
import scalaz._
import Scalaz._
def foo(a: A): Int =
(a.calculateImportantThings.pure[Identity] <* a.cleanup.pure[Identity]).value
This is rather obnoxious, though, since we have to explicitly wrap the side-effecting computations in Identity. Well the truth is, scalaz does some magic that implicitly converts to and from the Identity container, so you can just write:
def foo(a: A): Int = Identity(a.calculateImportantThings) <* a.cleanup()
You do need to hint to the compiler somehow that the leftmost thing is in the Identity monad. The above was the shortest way I could think of. Another possibility is to use Identity() *> foo <* bar, which will invoke the effects of foo and bar in that order, and then produce the value of foo.
To return to the ghci example:
scala> import scalaz._; import Scalaz._
import scalaz._
import Scalaz._
scala> val x : String = Identity(readLine) <* println("Thanks for the input!")
<< input asdf and press enter >>
Thanks for the input!
x: String = asdf
Maybe you want to use a kestrel combinator? It is defined as follows:
Kxy = x
So you call it with the value you want to return and some side-effecting operation you want to execute.
You could implement it as follows:
def kestrel[A](x: A)(f: A => Unit): A = { f(x); x }
... and use it in this way:
kestrel(result)(result => a.cleanUp)
More information can be found here: debasish gosh blog.
[UPDATE] As Yaroslav correctly points out, this is not the best application of the kestrel combinator. But it should be no problem to define a similar combinator using a function without arguments, so instead:
f: A => Unit
someone could use:
f: () => Unit
class Test {
def cleanUp() {}
def getResult = 1
}
def autoCleanup[A <: Test, T](a: A)(x: => T) = {
try { x } finally { a.cleanUp }
}
def foo[A <: Test](a:A): Int = autoCleanup(a) { a.getResult }
foo(new Test)
You can take a look at scala-arm project for type class based solution.
Starting Scala 2.13, the chaining operation tap can be used to apply a side effect (in this case the cleanup of A) on any value while returning the original value untouched:
def tap[U](f: (A) => U): A
import util.chaining._
// class A { def cleanUp { println("clean up") } ; def calculateImportantThings = 23 }
// val a = new A
val x = a.calculateImportantThings.tap(_ => a.cleanUp)
// clean up
// x: Int = 23
In this case tap is a bit abused since we don't even use the value it's applied on (a.calculateImportantThings (23)) to perform the side effect (a.cleanUp).

Could Scala's “if … else” have been implemented as a library function?

I'm wondering if if … else could have been implemented in Predef with special compiler treatment, in a similar way to what's being done with classOf[A]: the definition is in Predef, the implementation is filled in by the compiler.
Granted, many people would find reassuring to know that an if is always an if, and an else is always an else, no matter the context. However, defining else as a method on the result type of if would remove it from the list of keywords, and allow library designers to define their own else methods. (I know I can use any keyword as an identifier with backticks, but something like `else` just looks awful in code.) Such methods could be useful in cases discusses in situations such as this one, discussed on the mailing list, where people are forced to use otherwise when defining methods that actually should be named else. (Also discussed on SO here and here.)
So:
Would such an approach be possible, even in theory, or does it break some fundamental principle in Scala?
What would the downsides be?
Maybe I don't understand your question, but you can already implement if ... else ... as a library function. Consider this:
class If[A](condition: =>Boolean)(ifBlock: =>A) {
def els(elseBlock: =>A):A = condition match {
case true => ifBlock
case false => elseBlock
}
}
new If(2==3)(
println("equal")
) els (
println("not equal")
)
Of course this doesn't do exactly what if ... else ... does, but with some polishing I think it would. I once implemented a very simple interpreter for a language that had pattern matching built in with if ... else ... being implemented in much the same way I did here.
The short answer is "yes"; branching logic on some predicate can be implemented as a library function.
It's worth pointing out that, as Viktor Klang and others have noted, if/else is essentially folding a boolean. Folding is something we do frequently - sometimes it's clear and explicit, and sometimes not.
// Either#fold is explicit
scala> Left[String, Double]("fail") fold(identity, _ + 1 toString)
res0: java.lang.String = fail
scala> Right[String, Double](4) fold(identity, _ + 1 toString)
res1: java.lang.String = 5.0
Folding an option cannot be done explicitly, but we do it all the time.
// Option has no fold - wont compile!
Some(5) fold(1+, 0)
// .. but the following is equivalent and valid
scala> Some(5) map(1+) getOrElse(0)
res3: Int = 6
Branching logic on a boolean is also a fold, and you can pimp Boolean accordingly. Note the use of by-name parameters to achieve lazy evaluation. Without this feature, such an implementation wouldn't be possible.
// pimped Boolean - evaluates t when true, f when false
class FoldableBoolean(b: Boolean) {
def fold[A](t: => A, f: => A) =
if(b) t else f
}
implicit def b2fb(b: Boolean) = new FoldableBoolean(b)
Now we can fold Booleans:
scala> true fold("true!", "false")
res24: java.lang.String = true!
scala> false fold("true!", "false")
res25: java.lang.String = false
Not just if-else, but any language feature can be overridden in a branch of the language known as "Scala Virtualized"
https://github.com/TiarkRompf/scala-virtualized
This forms the basis of the Delite project at Stanford PPL, and is also at the heart of the research being funded by Scala's EU grant. So you can reasonably expect it to be part of the core language at some point in the future.
Any object-oriented language (or any language with runtime polymorphism) can implement conditionals as a library feature, since method dispatch already is a more general form of conditional anyway. Smalltalk, for example, has absolutely no conditionals whatsoever except for method dispatch.
There is no need for any kind of compiler magic, except maybe for syntactic convenience.
In Scala, it would look maybe a little bit like this:
trait MyBooleanLike {
def iff[T <: AnyRef](thenn: => T): T
def iffElse[T](thenn: => T)(els: => T): T
def &&(other: => MyBoolean): MyBoolean
def ||(other: => MyBoolean): MyBoolean
def nott: MyBoolean
}
trait MyTruthiness extends MyBooleanLike {
def iff[T](thenn: => T) = thenn
def iffElse[T](thenn: => T)(els: => T) = thenn
def &&(other: => MyBoolean) = other
def ||(other: => MyBoolean) = MyTrue
def nott = MyFalse
}
trait MyFalsiness extends MyBooleanLike {
def iff[T](thenn: => T): T = null.asInstanceOf[T]
def iffElse[T](thenn: => T)(els: => T) = els
def &&(other: => MyBoolean) = MyFalse
def ||(other: => MyBoolean) = other
def nott = MyTrue
}
abstract class MyBoolean extends MyBooleanLike
class MyTrueClass extends MyBoolean with MyTruthiness {}
class MyFalseClass extends MyBoolean with MyFalsiness {}
object MyTrue extends MyTrueClass {}
object MyFalse extends MyFalseClass {}
Just add a little implicit conversion:
object MyBoolExtension {
implicit def boolean2MyBoolean(b: => Boolean) =
if (b) { MyTrue } else { MyFalse }
}
import MyBoolExtension._
And now we can use it:
object Main extends App {
(2 < 3) iff { println("2 is less than 3") }
}
[Note: my type-fu is rather weak. I had to cheat a little bit to get this to compile within a reasonable timeframe. Someone with a better understanding of Scala's type system may want to fix it up. Also, now that I look at it, 8 classes, traits and objects, two of them abstract, seems a little over-engineered ;-) ]
Of course, the same is true for pattern matching as well. Any language with pattern matching doesn't need other kinds of conditionals, since pattern matching is more general anyway.
[BTW: This is basically a port of this Ruby code I wrote a couple of years ago for fun.]