Scala Pattern Matching pretty printed - scala

Is that possible to somehow marshall PartialFunction (let's assume it will always contains only one case) into something human-readable?
Let's say we have collection of type Any (messages: List[Any])
and number of PartialFuntion[Any, T] defined using pattern matching block.
case object R1
case object R2
case object R3
val pm1: PartialFunction[Any, Any] = {
case "foo" => R1
}
val pm2: PartialFunction[Any, Any] = {
case x: Int if x > 10 => R2
}
val pm3: PartialFunction[Any, Any] = {
case x: Boolean => R3
}
val messages: List[Any] = List("foo", 20)
val functions = List(pm1, pm2)
then we can find all the messages matched by provided PFs and related applications
val found: List[Option[Any]] = functions map { f =>
messages.find(f.isDefined).map(f)
}
but what if I need resulting map of 'what I expect' to 'what I've got' in the human-readable form (for logging). Say,
(case "foo") -> Some(R1)
(case Int if _ > 10) -> Some(R2)
(case Boolean) -> None
Is that possible? Some macro/meta works?

There's nothing at runtime which will print compiled code nicely.
You could write a macro which will print the source code of the tree and use that? Most macro tutorials start with a macro for printing source code -- see e.g. http://www.warski.org/blog/2012/12/starting-with-scala-macros-a-short-tutorial/
Perhaps:
// Given a partial function "pf", return the source code for pf
// as a string as well as the compiled, runnable function itself
def functionAndSource(pf: PartialFunction[Any, Any]): (String, PartialFunction[Any, Any]) = macro functionAndSourceImpl
def functionAndSourceImpl ...
val pm1: (String, PartialFunction[Any, Any]) = functionAndSource {
case "foo" => R1
}
This isn't ever going to be that easy or nice in Scala.
Scala isn't Lisp or Ruby: it's a compiled language and it is not optimised for reflection on the code itself.

Thanks for your answers. Using Macro is interesting one choice.
But as an option the solution might be to use kind of named partial functions. The idea is to name the function so in the output you can see the name of function instead source code.
object PartialFunctions {
type FN[Result] = PartialFunction[Any, Result]
case class NamedPartialFunction[A,B](name: String)(pf: PartialFunction[A, B]) extends PartialFunction[A,B] {
override def isDefinedAt(x: A): Boolean = pf.isDefinedAt(x)
override def apply(x: A): B = pf.apply(x)
override def toString(): String = s"matching($name)"
}
implicit class Named(val name: String) extends AnyVal {
def %[A,B](pf: PartialFunction[A,B]) = new NamedPartialFunction[A, B](name)(pf)
}
}
So then you can use it as follows
import PartialFunctions._
val pm1: PartialFunction[Any, Any] = "\"foo\"" % {
case "foo" => R1
}
val pm2: PartialFunction[Any, Any] = "_: Int > 10" % {
case x: Int if x > 10 => R2
}
val pm3: PartialFunction[Any, Any] = "_: Boolean" % {
case x: Boolean => R3
}
val messages: List[Any] = List("foo", 20)
val functions = List(pm1, pm2)
val found: List[Option[(String, Any)]] = functions map { case f: NamedPartialFunction =>
messages.find(f.isDefined).map(m => (f.name, f(m))
}

Related

How to Get Case Class Parameter Key Value Pairs? [duplicate]

Is there a nice way I can convert a Scala case class instance, e.g.
case class MyClass(param1: String, param2: String)
val x = MyClass("hello", "world")
into a mapping of some kind, e.g.
getCCParams(x) returns "param1" -> "hello", "param2" -> "world"
Which works for any case class, not just predefined ones. I've found you can pull the case class name out by writing a method that interrogates the underlying Product class, e.g.
def getCCName(caseobj: Product) = caseobj.productPrefix
getCCName(x) returns "MyClass"
So I'm looking for a similar solution but for the case class fields. I'd imagine a solution might have to use Java reflection, but I'd hate to write something that might break in a future release of Scala if the underlying implementation of case classes changes.
Currently I'm working on a Scala server and defining the protocol and all its messages and exceptions using case classes, as they are such a beautiful, concise construct for this. But I then need to translate them into a Java map to send over the messaging layer for any client implementation to use. My current implementation just defines a translation for each case class separately, but it would be nice to find a generalised solution.
This should work:
def getCCParams(cc: AnyRef) =
cc.getClass.getDeclaredFields.foldLeft(Map.empty[String, Any]) { (a, f) =>
f.setAccessible(true)
a + (f.getName -> f.get(cc))
}
Because case classes extend Product one can simply use .productIterator to get field values:
def getCCParams(cc: Product) = cc.getClass.getDeclaredFields.map( _.getName ) // all field names
.zip( cc.productIterator.to ).toMap // zipped with all values
Or alternatively:
def getCCParams(cc: Product) = {
val values = cc.productIterator
cc.getClass.getDeclaredFields.map( _.getName -> values.next ).toMap
}
One advantage of Product is that you don't need to call setAccessible on the field to read its value. Another is that productIterator doesn't use reflection.
Note that this example works with simple case classes that don't extend other classes and don't declare fields outside the constructor.
Starting Scala 2.13, case classes (as implementations of Product) are provided with a productElementNames method which returns an iterator over their field's names.
By zipping field names with field values obtained with productIterator we can generically obtain the associated Map:
// case class MyClass(param1: String, param2: String)
// val x = MyClass("hello", "world")
(x.productElementNames zip x.productIterator).toMap
// Map[String,Any] = Map("param1" -> "hello", "param2" -> "world")
If anybody looks for a recursive version, here is the modification of #Andrejs's solution:
def getCCParams(cc: Product): Map[String, Any] = {
val values = cc.productIterator
cc.getClass.getDeclaredFields.map {
_.getName -> (values.next() match {
case p: Product if p.productArity > 0 => getCCParams(p)
case x => x
})
}.toMap
}
It also expands the nested case-classes into maps at any level of nesting.
Here's a simple variation if you don't care about making it a generic function:
case class Person(name:String, age:Int)
def personToMap(person: Person): Map[String, Any] = {
val fieldNames = person.getClass.getDeclaredFields.map(_.getName)
val vals = Person.unapply(person).get.productIterator.toSeq
fieldNames.zip(vals).toMap
}
scala> println(personToMap(Person("Tom", 50)))
res02: scala.collection.immutable.Map[String,Any] = Map(name -> Tom, age -> 50)
If you happen to be using Json4s, you could do the following:
import org.json4s.{Extraction, _}
case class MyClass(param1: String, param2: String)
val x = MyClass("hello", "world")
Extraction.decompose(x)(DefaultFormats).values.asInstanceOf[Map[String,String]]
Solution with ProductCompletion from interpreter package:
import tools.nsc.interpreter.ProductCompletion
def getCCParams(cc: Product) = {
val pc = new ProductCompletion(cc)
pc.caseNames.zip(pc.caseFields).toMap
}
You could use shapeless.
Let
case class X(a: Boolean, b: String,c:Int)
case class Y(a: String, b: String)
Define a LabelledGeneric representation
import shapeless._
import shapeless.ops.product._
import shapeless.syntax.std.product._
object X {
implicit val lgenX = LabelledGeneric[X]
}
object Y {
implicit val lgenY = LabelledGeneric[Y]
}
Define two typeclasses to provide the toMap methods
object ToMapImplicits {
implicit class ToMapOps[A <: Product](val a: A)
extends AnyVal {
def mkMapAny(implicit toMap: ToMap.Aux[A, Symbol, Any]): Map[String, Any] =
a.toMap[Symbol, Any]
.map { case (k: Symbol, v) => k.name -> v }
}
implicit class ToMapOps2[A <: Product](val a: A)
extends AnyVal {
def mkMapString(implicit toMap: ToMap.Aux[A, Symbol, Any]): Map[String, String] =
a.toMap[Symbol, Any]
.map { case (k: Symbol, v) => k.name -> v.toString }
}
}
Then you can use it like this.
object Run extends App {
import ToMapImplicits._
val x: X = X(true, "bike",26)
val y: Y = Y("first", "second")
val anyMapX: Map[String, Any] = x.mkMapAny
val anyMapY: Map[String, Any] = y.mkMapAny
println("anyMapX = " + anyMapX)
println("anyMapY = " + anyMapY)
val stringMapX: Map[String, String] = x.mkMapString
val stringMapY: Map[String, String] = y.mkMapString
println("anyMapX = " + anyMapX)
println("anyMapY = " + anyMapY)
}
which prints
anyMapX = Map(c -> 26, b -> bike, a -> true)
anyMapY = Map(b -> second, a -> first)
stringMapX = Map(c -> 26, b -> bike, a -> true)
stringMapY = Map(b -> second, a -> first)
For nested case classes, (thus nested maps)
check another answer
I don't know about nice... but this seems to work, at least for this very very basic example. It probably needs some work but might be enough to get you started? Basically it filters out all "known" methods from a case class (or any other class :/ )
object CaseMappingTest {
case class MyCase(a: String, b: Int)
def caseClassToMap(obj: AnyRef) = {
val c = obj.getClass
val predefined = List("$tag", "productArity", "productPrefix", "hashCode",
"toString")
val casemethods = c.getMethods.toList.filter{
n =>
(n.getParameterTypes.size == 0) &&
(n.getDeclaringClass == c) &&
(! predefined.exists(_ == n.getName))
}
val values = casemethods.map(_.invoke(obj, null))
casemethods.map(_.getName).zip(values).foldLeft(Map[String, Any]())(_+_)
}
def main(args: Array[String]) {
println(caseClassToMap(MyCase("foo", 1)))
// prints: Map(a -> foo, b -> 1)
}
}
commons.mapper.Mappers.Mappers.beanToMap(caseClassBean)
Details: https://github.com/hank-whu/common4s
With the use of Java reflection, but no change of access level. Converts Product and case class to Map[String, String]:
def productToMap[T <: Product](obj: T, prefix: String): Map[String, String] = {
val clazz = obj.getClass
val fields = clazz.getDeclaredFields.map(_.getName).toSet
val methods = clazz.getDeclaredMethods.filter(method => fields.contains(method.getName))
methods.foldLeft(Map[String, String]()) { case (acc, method) =>
val value = method.invoke(obj).toString
val key = if (prefix.isEmpty) method.getName else s"${prefix}_${method.getName}"
acc + (key -> value)
}
}
Modern variation with Scala 3 might also be a bit simplified as with the following example that is similar to the answer posted by Walter Chang above.
def getCCParams(cc: AnyRef): Map[String, Any] =
cc.getClass.getDeclaredFields
.tapEach(_.setAccessible(true))
.foldLeft(Map.empty)((a, f) => a + (f.getName -> f.get(cc)))

How to express Function type?

I am currently reading Hutton's and Meijer's paper on parsing combinators in Haskell http://www.cs.nott.ac.uk/~pszgmh/monparsing.pdf. For the sake of it I am trying to implement them in scala. I would like to construct something easy to code, extend and also simple and elegant. I have come up with two solutions for the following haskell code
/* Haskell Code */
type Parser a = String -> [(a,String)]
result :: a -> Parser a
result v = \inp -> [(v,inp)]
zero :: Parser a
zero = \inp -> []
item :: Parser Char
item = \inp -> case inp of
[] -> []
(x:xs) -> [(x,xs)]
/* Scala Code */
object Hutton1 {
type Parser[A] = String => List[(A, String)]
def Result[A](v: A): Parser[A] = str => List((v, str))
def Zero[A]: Parser[A] = str => List()
def Character: Parser[Char] = str => if (str.isEmpty) List() else List((str.head, str.tail))
}
object Hutton2 {
trait Parser[A] extends (String => List[(A, String)])
case class Result[A](v: A) extends Parser[A] {
def apply(str: String) = List((v, str))
}
case object Zero extends Parser[T forSome {type T}] {
def apply(str: String) = List()
}
case object Character extends Parser[Char] {
def apply(str: String) = if (str.isEmpty) List() else List((str.head, str.tail))
}
}
object Hutton extends App {
object T1 {
import Hutton1._
def run = {
val r: List[(Int, String)] = Zero("test") ++ Result(5)("test")
println(r.map(x => x._1 + 1) == List(6))
println(Character("abc") == List(('a', "bc")))
}
}
object T2 {
import Hutton2._
def run = {
val r: List[(Int, String)] = Zero("test") ++ Result(5)("test")
println(r.map(x => x._1 + 1) == List(6))
println(Character("abc") == List(('a', "bc")))
}
}
T1.run
T2.run
}
Question 1
In Haskell, zero is a function value that can be used as it is, expessing all failed parsers whether they are of type Parser[Int] or Parser[String]. In scala we achieve the same by calling the function Zero (1st approach) but in this way I believe that I just generate a different function everytime Zero is called. Is this statement true? Is there a way to mitigate this?
Question 2
In the second approach, the Zero case object is extending Parser with the usage of existential types Parser[T forSome {type T}] . If I replace the type with Parser[_] I get the compile error
Error:(19, 28) class type required but Hutton2.Parser[_] found
case object Zero extends Parser[_] {
^
I thought these two expressions where equivalent. Is this the case?
Question 3
Which approach out of the two do you think that will yield better results in expressing the combinators in terms of elegance and simplicity?
I use scala 2.11.8
Note: I didn't compile it, but I know the problem and can propose two solutions.
The more Haskellish way would be to not use subtyping, but to define zero as a polymorphic value. In that style, I would propose to define parsers not as objects deriving from a function type, but as values of one case class:
final case class Parser[T](run: String => List[(T, String)])
def zero[T]: Parser[T] = Parser(...)
As shown by #Alec, yes, this will produce a new value every time, since a def is compiled to a method.
If you want to use subtyping, you need to make Parser covariant. Then you can give zero a bottom result type:
trait Parser[+A] extends (String => List[(A, String)])
case object Zero extends Parser[Nothing] {...}
These are in some way quite related; in system F_<:, which is the base of what Scala uses, the types _|_ (aka Nothing) and \/T <: Any. T behave the same (this hinted at in Types and Programming Languages, chapter 28). The two possibilities given here are a consequence of this fact.
With existentials I'm not so familiar with, but I think that while unbounded T forSome {type T} will behave like Nothing, Scala does not allow inhertance from an existential type.
Question 1
I think that you are right, and here is why: Zero1 below prints hello every time you use it. The solution, Zero2, involves using a val instead.
def Zero1[A]: Parser[A] = { println("hi"); str => List() }
val Zero2: Parser[Nothing] = str => List()
Question 2
No idea. I'm still just starting out with Scala. Hope someone answers this.
Question 3
The trait one will play better with Scala's for (since you can define custom flatMap and map), which turns out to be (somewhat) like Haskell's do. The following is all you need.
trait Parser[A] extends (String => List[(A, String)]) {
def flatMap[B](f: A => Parser[B]): Parser[B] = {
val p1 = this
new Parser[B] {
def apply(s1: String) = for {
(a,s2) <- p1(s1)
p2 = f(a)
(b,s3) <- p2(s2)
} yield (b,s3)
}
}
def map[B](f: A => B): Parser[B] = {
val p = this
new Parser[B] {
def apply(s1: String) = for ((a,s2) <- p(s1)) yield (f(a),s2)
}
}
}
Of course, to do anything interesting you need more parsers. I'll propose to you one simple parser combinator: Choice(p1: Parser[A], p2: Parser[A]): Parser[A] which tries both parsers. (And rewrite your existing parsers more to my style).
def choice[A](p1: Parser[A], p2: Parser[A]): Parser[A] = new Parser[A] {
def apply(s: String): List[(A,String)] = { p1(s) ++ p2(s) }
}
def unit[A](x: A): Parser[A] = new Parser[A] {
def apply(s: String): List[(A,String)] = List((x,s))
}
val character: Parser[Char] = new Parser[Char] {
def apply(s: String): List[(Char,String)] = List((s.head,s.tail))
}
Then, you can write something like the following:
val parser: Parser[(Char,Char)] = for {
x <- choice(unit('x'),char)
y <- char
} yield (x,y)
And calling parser("xyz") gives you List((('x','x'),"yz"), (('x','y'),"z")).

Specialization of Scala methods to a specific tags

I have a generic map with values, some of which can be in turn lists of values.
I'm trying to process a given key and convert the results to the type expected by an outside caller, like this:
// A map with some values being other collections.
val map: Map[String, Any] = Map("foo" -> 1, "bar" -> Seq('a', 'b'. 'a'))
// A generic method with a "specialization" for collections (pseudocode)
def cast[T](key: String) = map.get(key).map(_.asInstanceOf[T])
def cast[C <: Iterable[T]](key: String) = map.get(key).map(list => list.to[C].map(_.asIntanceOf[T]))
// Expected usage
cast[Int]("foo") // Should return 1:Int
cast[Set[Char]]("bar") // Should return Set[Char]('a', 'b')
This is to show what I would like to do, but it does not work. The compiler error complains (correctly, about 2 possible matches). I've also tried to make this a single function with some sort of pattern match on the type to no avail.
I've been reading on #specialized, TypeTag, CanBuildFrom and other scala functionality, but I failed to find a simple way to put it all together. Separate examples I've found address different pieces and some ugly workarounds, but nothing that would simply allow an external user to call cast and get an exception is the cast was invalid. Some stuff is also old, I'm using Scala 2.10.5.
This appears to work but it has a some problems.
def cast[T](m: Map[String, Any], k: String):T = m(k) match {
case x: T => x
}
With the right input you get the correct output.
scala> cast[Int](map,"foo")
res18: Int = 1
scala> cast[Set[Char]](map,"bar")
res19: Set[Char] = Set(a, b)
But it throws if the type is wrong for the key or if the map has no such key (of course).
You can do this via implicit parameters:
val map: Map[String, Any] = Map("foo" -> 1, "bar" -> Set('a', 'b'))
abstract class Casts[B] {def cast(a: Any): B}
implicit val doubleCast = new Casts[Double] {
override def cast(a: Any): Double = a match {
case x: Int => x.toDouble
}
}
implicit val intCast = new Casts[Int] {
override def cast(a: Any): Int = a match {
case x: Int => x
case x: Double => x.toInt
}
}
implicit val seqCharCast = new Casts[Seq[Char]] {
override def cast(a: Any): Seq[Char] = a match {
case x: Set[Char] => x.toSeq
case x: Seq[Char] => x
}
}
def cast[T](key: String)(implicit p:Casts[T]) = p.cast(map(key))
println(cast[Double]("foo")) // <- 1.0
println(cast[Int]("foo")) // <- 1
println(cast[Seq[Char]]("bar")) // <- ArrayBuffer(a, b) which is Seq(a, b)
But you still need to iterate over all type-to-type options, which is reasonable as Set('a', 'b').asInstanceOf[Seq[Char]] throws, and you cannot use a universal cast, so you need to handle such cases differently.
Still it sounds like an overkill, and you may need to review your approach from global perspective

Scala, partial functions

Is there any way to create a PartialFunction except through the case statement?
I'm curious, because I'd like to express the following (scala pseudo ahead!)...
val bi = BigInt(_)
if (bi.isValidInt) bi.intValue
... as a partial function, and doing
val toInt : PartialFunction[String, Int] = {
case s if BigInt(s).isValidInt => BigInt(s).intValue
}
seems redundant since I create a BigInt twice.
Not sure I understand the question. But here's my attempt: Why not create an extractor?
object ValidBigInt {
def unapply(s: String): Option[Int] = {
val bi = BigInt(s)
if (bi.isValidInt) Some(bi.intValue) else None
}
}
val toInt: PartialFunction[String, Int] = {
case ValidBigInt(i) => i
}
The other option is (and that may answer the question as to whether one can create PartialFunction other than with a case literal):
val toInt = new PartialFunction[String, Int] {
def isDefinedAt(s: String) = BigInt(s).isValidInt
def apply(s: String) = BigInt(s).intValue
}
However since the idea of a partial function is that it's only partially defined, in the end you will still do redundant things -- you need to create a big int to test whether it's valid, and then in the function application you create the big int again...
I saw a project at Github that tried to come around this by somewhat caching the results from isDefinedAt. If you go down to the benchmarks, you'll see that it turned out to be slower than the default Scala implementation :)
So if you want to get around the double nature of isDefinedAt versus apply, you should just go straight for a (full) function that provides an Option[Int] as result.
I think you're looking for lift/unlift. lift takes a partial function and turns it into a function that returns an Option. Unlift takes a function with one argument that returns an option, and returns a partial function.
import scala.util.control.Exception._
scala> def fn(s: String) = catching(classOf[NumberFormatException]) opt {BigInt(s)}
fn: (s: String)Option[scala.math.BigInt]
scala> val fnPf = Function.unlift(fn)
fnPf: PartialFunction[String,scala.math.BigInt] = <function1>
scala> val fn = fnPf.lift
fn: String => Option[scala.math.BigInt] = <function1>
Closely related, you also want to look at this answer for information about cond and condOpt:
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)
You can write out a PartialFunction "longhand" if you'd like:
object pf extends PartialFunction[Int,String] {
def isDefinedAt(in: Int) = in % 2 == 0
def apply(in: Int) = {
if (in % 2 == 0)
"even"
else
throw new MatchError(in + " is odd")
}
Okay, I got this
import java.lang.NumberFormatException
import scala.util.control.Exception._
val toInt: PartialFunction[String, Int] = {
catching(classOf[NumberFormatException]) opt BigInt(_) match {
case Some(bi) if bi.isValidInt => bi.intValue
}
}
How about this?
val toInt: PartialFunction[String, Int] = (s: String) => BigInt(s) match {
case bi if bi.isValidInt => bi.intValue
}

Case class to map in Scala

Is there a nice way I can convert a Scala case class instance, e.g.
case class MyClass(param1: String, param2: String)
val x = MyClass("hello", "world")
into a mapping of some kind, e.g.
getCCParams(x) returns "param1" -> "hello", "param2" -> "world"
Which works for any case class, not just predefined ones. I've found you can pull the case class name out by writing a method that interrogates the underlying Product class, e.g.
def getCCName(caseobj: Product) = caseobj.productPrefix
getCCName(x) returns "MyClass"
So I'm looking for a similar solution but for the case class fields. I'd imagine a solution might have to use Java reflection, but I'd hate to write something that might break in a future release of Scala if the underlying implementation of case classes changes.
Currently I'm working on a Scala server and defining the protocol and all its messages and exceptions using case classes, as they are such a beautiful, concise construct for this. But I then need to translate them into a Java map to send over the messaging layer for any client implementation to use. My current implementation just defines a translation for each case class separately, but it would be nice to find a generalised solution.
This should work:
def getCCParams(cc: AnyRef) =
cc.getClass.getDeclaredFields.foldLeft(Map.empty[String, Any]) { (a, f) =>
f.setAccessible(true)
a + (f.getName -> f.get(cc))
}
Because case classes extend Product one can simply use .productIterator to get field values:
def getCCParams(cc: Product) = cc.getClass.getDeclaredFields.map( _.getName ) // all field names
.zip( cc.productIterator.to ).toMap // zipped with all values
Or alternatively:
def getCCParams(cc: Product) = {
val values = cc.productIterator
cc.getClass.getDeclaredFields.map( _.getName -> values.next ).toMap
}
One advantage of Product is that you don't need to call setAccessible on the field to read its value. Another is that productIterator doesn't use reflection.
Note that this example works with simple case classes that don't extend other classes and don't declare fields outside the constructor.
Starting Scala 2.13, case classes (as implementations of Product) are provided with a productElementNames method which returns an iterator over their field's names.
By zipping field names with field values obtained with productIterator we can generically obtain the associated Map:
// case class MyClass(param1: String, param2: String)
// val x = MyClass("hello", "world")
(x.productElementNames zip x.productIterator).toMap
// Map[String,Any] = Map("param1" -> "hello", "param2" -> "world")
If anybody looks for a recursive version, here is the modification of #Andrejs's solution:
def getCCParams(cc: Product): Map[String, Any] = {
val values = cc.productIterator
cc.getClass.getDeclaredFields.map {
_.getName -> (values.next() match {
case p: Product if p.productArity > 0 => getCCParams(p)
case x => x
})
}.toMap
}
It also expands the nested case-classes into maps at any level of nesting.
Here's a simple variation if you don't care about making it a generic function:
case class Person(name:String, age:Int)
def personToMap(person: Person): Map[String, Any] = {
val fieldNames = person.getClass.getDeclaredFields.map(_.getName)
val vals = Person.unapply(person).get.productIterator.toSeq
fieldNames.zip(vals).toMap
}
scala> println(personToMap(Person("Tom", 50)))
res02: scala.collection.immutable.Map[String,Any] = Map(name -> Tom, age -> 50)
If you happen to be using Json4s, you could do the following:
import org.json4s.{Extraction, _}
case class MyClass(param1: String, param2: String)
val x = MyClass("hello", "world")
Extraction.decompose(x)(DefaultFormats).values.asInstanceOf[Map[String,String]]
Solution with ProductCompletion from interpreter package:
import tools.nsc.interpreter.ProductCompletion
def getCCParams(cc: Product) = {
val pc = new ProductCompletion(cc)
pc.caseNames.zip(pc.caseFields).toMap
}
You could use shapeless.
Let
case class X(a: Boolean, b: String,c:Int)
case class Y(a: String, b: String)
Define a LabelledGeneric representation
import shapeless._
import shapeless.ops.product._
import shapeless.syntax.std.product._
object X {
implicit val lgenX = LabelledGeneric[X]
}
object Y {
implicit val lgenY = LabelledGeneric[Y]
}
Define two typeclasses to provide the toMap methods
object ToMapImplicits {
implicit class ToMapOps[A <: Product](val a: A)
extends AnyVal {
def mkMapAny(implicit toMap: ToMap.Aux[A, Symbol, Any]): Map[String, Any] =
a.toMap[Symbol, Any]
.map { case (k: Symbol, v) => k.name -> v }
}
implicit class ToMapOps2[A <: Product](val a: A)
extends AnyVal {
def mkMapString(implicit toMap: ToMap.Aux[A, Symbol, Any]): Map[String, String] =
a.toMap[Symbol, Any]
.map { case (k: Symbol, v) => k.name -> v.toString }
}
}
Then you can use it like this.
object Run extends App {
import ToMapImplicits._
val x: X = X(true, "bike",26)
val y: Y = Y("first", "second")
val anyMapX: Map[String, Any] = x.mkMapAny
val anyMapY: Map[String, Any] = y.mkMapAny
println("anyMapX = " + anyMapX)
println("anyMapY = " + anyMapY)
val stringMapX: Map[String, String] = x.mkMapString
val stringMapY: Map[String, String] = y.mkMapString
println("anyMapX = " + anyMapX)
println("anyMapY = " + anyMapY)
}
which prints
anyMapX = Map(c -> 26, b -> bike, a -> true)
anyMapY = Map(b -> second, a -> first)
stringMapX = Map(c -> 26, b -> bike, a -> true)
stringMapY = Map(b -> second, a -> first)
For nested case classes, (thus nested maps)
check another answer
I don't know about nice... but this seems to work, at least for this very very basic example. It probably needs some work but might be enough to get you started? Basically it filters out all "known" methods from a case class (or any other class :/ )
object CaseMappingTest {
case class MyCase(a: String, b: Int)
def caseClassToMap(obj: AnyRef) = {
val c = obj.getClass
val predefined = List("$tag", "productArity", "productPrefix", "hashCode",
"toString")
val casemethods = c.getMethods.toList.filter{
n =>
(n.getParameterTypes.size == 0) &&
(n.getDeclaringClass == c) &&
(! predefined.exists(_ == n.getName))
}
val values = casemethods.map(_.invoke(obj, null))
casemethods.map(_.getName).zip(values).foldLeft(Map[String, Any]())(_+_)
}
def main(args: Array[String]) {
println(caseClassToMap(MyCase("foo", 1)))
// prints: Map(a -> foo, b -> 1)
}
}
commons.mapper.Mappers.Mappers.beanToMap(caseClassBean)
Details: https://github.com/hank-whu/common4s
With the use of Java reflection, but no change of access level. Converts Product and case class to Map[String, String]:
def productToMap[T <: Product](obj: T, prefix: String): Map[String, String] = {
val clazz = obj.getClass
val fields = clazz.getDeclaredFields.map(_.getName).toSet
val methods = clazz.getDeclaredMethods.filter(method => fields.contains(method.getName))
methods.foldLeft(Map[String, String]()) { case (acc, method) =>
val value = method.invoke(obj).toString
val key = if (prefix.isEmpty) method.getName else s"${prefix}_${method.getName}"
acc + (key -> value)
}
}
Modern variation with Scala 3 might also be a bit simplified as with the following example that is similar to the answer posted by Walter Chang above.
def getCCParams(cc: AnyRef): Map[String, Any] =
cc.getClass.getDeclaredFields
.tapEach(_.setAccessible(true))
.foldLeft(Map.empty)((a, f) => a + (f.getName -> f.get(cc)))