I have the following code
sealed trait DomainValidation {
def errorMessage: String
}
type ValidationResult[A] = ValidatedNel[DomainValidation, A]
val ai:ValidationResult[String] = "big".validNel
val bi:ValidationResult[String] = "leboski".validNel
val l = List(ai,bi)
I want to convert l to ValidationResult[List[String]]. I came across sequence functionality but I am unable to use cats sequence as some implicit has to be there which knows how to handle ValidationResult[A]. But I am unable figure out what exactly is needed. I wrote the following
object helper {
implicit class hello[A](l: List[ValidationResult[A]]) {
def mysequence: ValidationResult[List[A]] = {
val m = l.collect { case Invalid(a) => Invalid(a) }
if (m.isEmpty) l.map { case Valid(a) => a }.validNel
else /* merge the NonEmpty Lists */
}
}
}
I am able to do l.mysequence. But how do I use cats sequence.
PS: I am a scala beginner. Having a hard time learning :). Forgive for any incorrect mentions.
The following should work as expected on Scala 2.12:
import cats.data.ValidatedNel, cats.syntax.validated._
// Your code:
sealed trait DomainValidation {
def errorMessage: String
}
type ValidationResult[A] = ValidatedNel[DomainValidation, A]
val ai:ValidationResult[String] = "big".validNel
val bi:ValidationResult[String] = "leboski".validNel
val l = List(ai,bi)
And then:
scala> import cats.instances.list._, cats.syntax.traverse._
import cats.instances.list._
import cats.syntax.traverse._
scala> l.sequence
res0: ValidationResult[List[String]] = Valid(List(big, leboski))
You don't show your code or explain what's not working, so it's hard to diagnose your issue, but it's likely to be one of the following problems:
You're on Scala 2.11, where .sequence requires you to enable -Ypartial-unification in your compiler options. If you're using sbt, you can do this by adding scalacOptions += "-Ypartial-unification" to your build.sbt (assuming you're on 2.11.9+).
You've omitted one of the necessary imports. You need at least the Traverse instance for List and the syntax for Traverse. The example code above includes the two imports you need, or you can just import cats.implicits._ and make your life a little easier.
If it's not one of these two things, you'll probably need to include more detail in your question for us to be able to help.
Related
I have a package foo.bar in which a trait Parent is defined, and a series of objects Child1, Child2, Child3 are defined. I would like to get a List[Parent] containing all child objects defined in foo.bar. How can I write such a macro?
Right now I have the following:
def myMacro(c: blackbox.Context): c.Expr[Set[RuleGroup]] = {
val parentSymbol = c.mirror.staticClass("foo.bar.Parent")
c.mirror.staticPackage("foo.bar").info.members
// get all objects
.filter { sym =>
// remove $ objects
sym.isModule && sym.asModule.moduleClass.asClass.baseClasses.contains(parentSymbol)
}.map { ??? /* retrieve? */ }
???
}
I think this is what you'd be looking for:
.map(sym => c.mirror.reflectModule(sym.asModule).instance.asInstanceOf[Parent])
Later edit:
I have tried doing this in a trait, so not a macro like above, and when calling it with a different package than the one calling it from, it returned an empty collection of objects. Reading through it might have to do with how classloaders work in Scala as they don't have the knowledge of all the classes being loaded, but i see your macro doesn't use a classloader so maybe it still works in your case.
For me it worked using the Reflections library like this in a trait:
import org.reflections.Reflections
import scala.reflect.runtime.universe
import scala.reflect.{ClassTag, classTag}
import scala.collection.JavaConverters._
trait ChildObjects {
def childObjectsOf[Parent: ClassTag](containingPackageFullName: String): Set[Parent] = {
new Reflections(containingPackageFullName)
.getSubTypesOf(classTag[Parent].runtimeClass)
.asScala
.map(cls => {
val mirror = universe.runtimeMirror(cls.getClassLoader)
val moduleSymbol = mirror.moduleSymbol(cls)
mirror.reflectModule(moduleSymbol).instance.asInstanceOf[Parent]
})
.toSet
}
}
If the trait is not sealed you can't do that. Fundamentally if a trait is not sealed, it means new subclasses can be added later under different compilation unit.
If the trait is sealed, than you can use knownDirectSubclasses of ClassSymbolApi but beware of the possible issues the depend on order such as this and this in circe
I want to call an arbitrary public method of an arbitrary stuff via reflection. I.e. let's say, I want to write method extractMethod to be used like:
class User { def setAvatar(avatar: Avatar): Unit = …; … }
val m = extractMethod(someUser, "setAvatar")
m(someAvatar)
From the Reflection. Overview document from Scala docs, I see the following direct way to do that:
import scala.reflect.ClassTag
import scala.reflect.runtime.universe._
def extractMethod[Stuff: ClassTag: TypeTag](
stuff: Stuff,
methodName: String): MethodMirror =
{
val stuffTypeTag = typeTag[Stuff]
val mirror = stuffTypeTag.mirror
val stuffType = stuffTypeTag.tpe
val methodSymbol = stuffType
.member(TermName(methodName)).asMethod
mirror.reflect(stuff)
.reflectMethod(methodSymbol)
}
However what I'm bothered with this solution is that I need to pass implicit ClassTag[Stuff] and TypeTag[Stuff] parameters (first one is needed for calling reflect, second one — for getting stuffType). Which may be quite cumbersome, especially if extractMethod is called from generics that are called from generics and so on. I'd accept this as necessity for some languages that strongly lack runtime type information, but Scala is based on JRE, which allows to do the following:
def extractMethod[Stuff](
stuff: Stuff,
methodName: String,
parameterTypes: Array[Class[_]]): (Object*) => Object =
{
val unboundMethod = stuff.getClass()
.getMethod(methodName, parameterTypes: _*)
arguments => unboundMethod(stuff, arguments: _*)
}
I understand that Scala reflection allows to get more information that basic Java reflection. Still, here I just need to call a method. Is there a way to somehow reduce requirements (e.g. these ClassTag, TypeTag) of the Scala-reflection-based extractMethod version (without falling back to pure-Java reflection), assuming that performance doesn't matter for me?
Yes, there is.
First, according to this answer, TypeTag[Stuff] is a strictly stronger requirement than ClassTag[Stuff]. Although we don't automatically get implicit ClassTag[Stuff] from implicit TypeTag[Stuff], we can evaluate it manually as ClassTag[Stuff](stuffTypeTag.mirror.runtimeClass(stuffTypeTag.tpe)) and then implicitly or explicitly pass it to reflect that needs it:
import scala.reflect.ClassTag
import scala.reflect.runtime.universe._
def extractMethod[Stuff: TypeTag](
stuff: Stuff,
methodName: String): MethodMirror =
{
val stuffTypeTag = typeTag[Stuff]
val mirror = stuffTypeTag.mirror
val stuffType = stuffTypeTag.tpe
val stuffClassTag = ClassTag[Stuff](mirror.runtimeClass(stuffType))
val methodSymbol = stuffType
.member(TermName(methodName)).asMethod
mirror.reflect(stuff)(stuffClassTag)
.reflectMethod(methodSymbol)
}
Second, mirror and stuffType can be obtained from stuff.getClass():
import scala.reflect.ClassTag
import scala.reflect.runtime.universe._
def extractMethod(stuff: Stuff, methodName: String): MethodMirror = {
val stuffClass = stuff.getClass()
val mirror = runtimeMirror(stuffClass.getClassLoader)
val stuffType = mirror.classSymbol(stuffClass).toType
val stuffClassTag = ClassTag[Stuff](mirror.runtimeClass(stuffType))
val methodSymbol = stuffType
.member(TermName(methodName)).asMethod
mirror.reflect(stuff)(stuffClassTag)
.reflectMethod(methodSymbol)
}
Therefore we obtained Scala-style reflection entities (i.e. finally MethodMirror) without requiring ClassTag and/or TypeTag to be passed explicitly or implicitly from the caller. Not sure, however, how it compares with the ways described in the question (i.e. passing tags from outside and pure Java) in the terms of performance.
Could someone give a simple example of how I'd use scala.tools.nsc to compile a Scala class during runtime from within a JVM? I'm experimenting with some dynamic behavior where I want to be able to compile Scala classes during runtime, then load and use them. I'm mostly interested in compiling objects with pure functions of primitive types (Doubles, Floats, etc). Thanks!
The comment about scala.tools.reflect.Toolbox put me on the right track and I ended up being able to answer my own question. Something like this is what I was looking for:
import scala.reflect.runtime._
import scala.reflect.runtime.universe._
import scala.tools.reflect.ToolBox
object Main extends App {
val cm = universe.runtimeMirror(getClass.getClassLoader)
val toolBox = cm.mkToolBox()
val f = toolBox.eval(toolBox.parse("""(x:Double) => x*x"""))
f match {
case f1:scala.Function1[Double, Any] =>
println(f1(4.4))
case _ =>
throw new Exception("Expected a Function1[Double,Any] but got something else")
}
}
Im using ArgonautShapeless to define some json codecs.
When I provide the type for my codec I get StackOverflowError's but If I leave the type off it works. How can I provide the type?
My understanding of the problem is that the implicit lookup from def of[A: DecodeJson] = implicitly[DecodeJson[A]] finds my definition on the same line implicit def fooCodec: DecodeJson[Foo] and thus is recursive so breaks.
Is there some other way that will allow me to provide the type? Ideally I want to have one object in my project where I define all of the codes and they may depend on each other.
import $ivy.`com.github.alexarchambault::argonaut-shapeless_6.2:1.2.0-M4`
import argonaut._, Argonaut._
case class Foo(a: Int)
object SomeCodecs {
import ArgonautShapeless._
// this doesnt work
implicit def fooCodec: DecodeJson[Foo] = DecodeJson.of[Foo]
}
import SomeCodecs._
"""{"a":1}""".decode[Foo]
java.lang.StackOverflowError
ammonite.$sess.cmd3$SomeCodecs$.fooCodec(cmd3.sc:3)
It works if I leave the type off.
object SomeCodecs {
import ArgonautShapeless._
// this works
implicit def fooCodec = DecodeJson.of[Foo]
}
import SomeCodecs._
"""{"a":1}""".decode[Foo]
res4: Either[Either[String, (String, CursorHistory)], Foo] = Right(Foo(1))
Thanks
When encoding to Json with circe we really want the type field to show e.g.
scala> val fooJson = foo.asJson
fooJson: io.circe.Json =
{
"this_is_a_string" : "abc",
"another_field" : 123,
"type" : "Foo"
}
This is taken from the release notes which previously mentions that you can configure the encoding like this:
implicit val customConfig: Configuration =
Configuration.default.withSnakeCaseKeys.withDefaults.withDiscriminator("type")
Also other information about circe here suggests that without any configuration you should get some class type information in the encoding json.
Am I missing something? How do you get the class type to show?
UPDATE 30/03/2017: Follow up to OP's comment
I was able to make this work, as shown in the linked release notes.
Preparation step 1: add additional dependency to build.sbt
libraryDependencies += "io.circe" %% "circe-generic-extras" % "0.7.0"
Preparation step 2: setup dummy sealed trait hierarchy
import io.circe.{ Decoder, Encoder }
import io.circe.parser._, io.circe.syntax._
import io.circe.generic.extras.Configuration
import io.circe.generic.extras.auto._
import io.circe.generic.{ semiauto => boring } // <- This is the default generic derivation behaviour
import io.circe.generic.extras.{ semiauto => fancy } // <- This is the new generic derivation behaviour
implicit val customConfig: Configuration = Configuration.default.withDefaults.withDiscriminator("type")
sealed trait Stuff
case class Foo(thisIsAString: String, anotherField: Int = 13) extends Stuff
case class Bar(thisIsAString: String, anotherField: Int = 13) extends Stuff
object Foo {
implicit val decodeBar: Decoder[Bar] = fancy.deriveDecoder
implicit val encodeBar: Encoder[Bar] = fancy.deriveEncoder
}
object Bar {
implicit val decodeBar: Decoder[Bar] = boring.deriveDecoder
implicit val encodeBar: Encoder[Bar] = boring.deriveEncoder
}
Actual code using this:
val foo: Stuff = Foo("abc", 123)
val bar: Stuff = Bar("xyz", 987)
val fooString = foo.asJson.noSpaces
// fooString: String = {"thisIsAString":"abc","anotherField":123,"type":"Foo"}
val barString = bar.asJson.noSpaces
// barString: String = {"thisIsAString":"xyz","anotherField":987,"type":"Bar"}
val bar2 = for{
json <- parse(barString)
bar2 <- json.as[Stuff]
} yield bar2
// bar2: scala.util.Either[io.circe.Error,Stuff] = Right(Bar(xyz,987))
val foo2 = for{
json <- parse(fooString)
foo2 <- json.as[Stuff]
} yield foo2
// foo2: scala.util.Either[io.circe.Error,Stuff] = Right(Foo(abc,123))
So, provided you import the extra dependency (which is where Configuration comes from), it looks like it works.
Finally, as a sidenote, it does seem that there is some disconnection between Circe's DESIGN.md and practice, for which I am actually happy.
Original answer:
I am not sure this is supposed to be supported, by design.
Taken from Circe's DESIGN.md:
Implicit scope should not be used for configuration. Lots of people have asked for a way to configure generic codec derivation to use e.g. a type field as the discriminator for sealed trait hierarchies, or to use snake case for member names. argonaut-shapeless supports this quite straightforwardly with a JsonCoproductCodec type that the user can provide implicitly.
I don't want to criticize this approach—it's entirely idiomatic Scala, and it often works well in practice—but I personally don't like using implicit values for configuration, and I'd like to avoid it in circe until I am 100% convinced that there's no alternative way to provide this functionality.
What this means concretely: You'll probably never see an implicit argument that isn't a type class instance—i.e. that isn't a type constructor applied to a type in your model—in circe, and configuration of generic codec derivation is going to be relatively limited (compared to e.g. argonaut-shapeless) until we find a nice way to do this kind of thing with type tags or something similar.
In particular, customConfig: Configuration seems to be exactly the type of argument that the last paragraph refers to (e.g. an implicit argument that isn't a type class instance)
I am sure that #travis-brown or any other Circe's main contributors could shed some more light on this, in case there was in fact a way of doing this - and I would be very happy to know it! :)