使用 µPickle 序列化多态类型

Question

我正在阅读 µPickle 的文档并在互联网上搜索，但我找不到任何关于一项非常基本的功能的提及，我记得我可能为我使用的所有序列化库都记录了它before (Jackson, Prickle ...)：多态类型。我找到的唯一文档是密封特征/类。考虑以下代码：

import upickle.default._

trait Base

object Base{
  implicit val rw: ReadWriter[Base] = ReadWriter.merge(C1.rw, C2.rw)
}
object C1 {
  implicit val rw: ReadWriter[C1] = macroRW
}
object C2 {
  implicit val rw: ReadWriter[C2] = macroRW
}
case class C1(x: Int) extends Base
case class C2(s: String) extends Base

object Main extends App {
  val c1: Base = new C1(0)
  val c2: Base = new C2("X")

  val c1String = write(c1)
  val c2String = write(c2)
  println("c1 " + c1String)
  println("c2 " + c2String)

}

如果我将 trait Base 更改为 sealed trait Base，此代码将起作用。我同意在序列化器中列出所有派生的类的要求，这也是我提到的其他库所需要的，但是并不总是可能或不希望有多个大的类一个源文件，以便可以密封基地。如果基数不密封，如何使用 uPickle 序列化多态类型？

Answer 1

µPickle 在编译时工作（宏在编译时工作）。为了派生具有 subclasses 实例的 trait 的类型 class 实例，你应该在编译时知道所有 trait subclasses。这仅适用于密封特征（通过 knownDirectSubclasses https://github.com/lihaoyi/upickle/blob/master/implicits/src/upickle/implicits/internal/Macros.scala#L124 ）。

http://www.lihaoyi.com/upickle/#SupportedTypes

Supported Types

Out of the box, uPickle supports writing and reading the following types:

Boolean, Byte, Char, Short, Int, Long, Float, Double

Tuples from 1 to 22

Immutable Seq, List, Vector, Set, SortedSet, Option, Array, Maps, and all other collections with a reasonable CanBuildFrom implementation

Duration, Either

Stand-alone case classes and case objects, and their generic equivalents,

Non-generic case classes and case objects that are part of a sealed trait or sealed class hierarchy

sealed trait and sealed classes themselves, assuming that all subclasses are picklable

UUIDs

null

如您所见，仅支持密封特征。

解决方法是在多个源文件中具有密封特征，并使用自定义 pickler 具有共同的父特征。

  trait Base

  object Base {
    implicit val rw: ReadWriter[Base] = readwriter[ujson.Value].bimap[Base]({
      case c: Base1 => writeJs(c)
      case c: Base2 => writeJs(c)
    },
      s => Try(read[Base1](s)).getOrElse(read[Base2](s))
    )
  }

  sealed trait Base1 extends Base
  object Base1 {
    implicit val rw: ReadWriter[Base1] = ReadWriter.merge(C1.rw, C11.rw)
  }

  case class C1(x: Int) extends Base1
  object C1 {
    implicit val rw: ReadWriter[C1] = macroRW
  }

  case class C11(x: Int) extends Base1
  object C11 {
    implicit val rw: ReadWriter[C11] = macroRW
  }

  sealed trait Base2 extends Base
  object Base2 {
    implicit val rw: ReadWriter[Base2] = ReadWriter.merge(C2.rw, C22.rw)
  }

  case class C2(s: String) extends Base2
  object C2 {
    implicit val rw: ReadWriter[C2] = macroRW
  }

  case class C22(s: String) extends Base2
  object C22 {
    implicit val rw: ReadWriter[C22] = macroRW
  }

  val c1: Base = new C1(0)
  val c2: Base = new C2("X")

  val c1String = write(c1)
  val c2String = write(c2)
  println("c1 " + c1String) // c1 {"$type":"App.C1","x":0}
  println("c2 " + c2String) // c2 {"$type":"App.C2","s":"X"}

  println(read[Base](c1String)) // C1(0)
  println(read[Base](c2String)) // C2(X)

使用 µPickle 序列化多态类型

Serializing polymorphic types with µPickle

serialization

scala

upickle