joneshf / xenomorph

Scala library for free applicative schemas capable of parsing/rendering JSON data structures.

Xenomorph

Xenomorph is a Scala library for building well-typed descriptions of other Scala data structures, from which one can then automatically derive serialization, parsing, and generation functions. Implementations are currently provided for producing argonaut DecodeJson and EncodeJson instances, as well as scalacheck Gen values. Similar facilities for scodec, protobuf, and whatever else might be useful will be coming as time permits and interest demands.

Getting Started

Xenomorph is still awaiting an initial release, so for now you'll have to build it locally for yourself.

Creating a Schema

Begin with the data type for which you wish to create a schema. Here's an example:

import monocle.macros._

@Lenses case class Person(
  name: String, 
  birthDate: Instant,
  roles: Vector[Role]
)

sealed trait Role

case object User extends Role {
  val prism = GenPrism[Role, User.type]
}

@Lenses case class Administrator(department: String, subordinateCount: Int) extends Role
object Administrator {
  val prism = GenPrism[Role, Administrator]
}

In this example, you can see:

• A simple record type Person
• A sum type Role with two constructors, User and Administrator

To build a schema for the Person type, we will use the Scalaz applicative constructor at arity 3 (^^) as shown below:

import scalaz.syntax.apply._
import xenomorph.Schema._
import xenomorph.json.JType._

val personSchema: Schema[JSchema, Person] = rec(
  ^^(
    required("name", jStr, Person.name.asGetter),
    required(
      "birthDate", jLong.composeIso(Iso(new Instant(_:Long))((_:Instant).getMillis)), 
      Person.birthDate.asGetter
    ),
    required("roles", jArray(roleSchema), Person.roles.asGetter)
  )(Person.apply _)
)

The schema for the Role sum type is created as a nonempty list of alternatives, each of which provides a prism from the sum type to the underlying data type associated with each constructor. In the case of the User case object, the underlying schema is that of the empty object, which is isomorphic to Unit. () is the empty tuple, so we treat the empty record as the Unit schema constructor.

val roleSchema: Schema[JSchema, Role] = Schema.oneOf(
  alt[JSchema, Role, User.type](
    "user", 
    Schema.const(User),
    User.prism
  ) ::
  alt[JSchema, Role, Administrator](
    "administrator", 
    rec(
      ^(
        required("department", jStr, Administrator.department.asGetter),
        required("subordinateCount", jInt, Administrator.subordinateCount.asGetter)
      )(Administrator.apply _)
    ),
    Administrator.prism
  ) :: shapeless.HNil
)

This schema is constructed using the JType GADT to define the set of recognized primitive types. However, the set of primitive types is a user-definable feature at the time of schema construction.

Once you have a Schema value, you can use it to produce parsers, serializers, and generators.

import argonaut._
import xenomorph.json.ToJson._
import xenomorph.json.FromJson._
import xenomorph.scalacheck.ToGen._

val personJson: Json = personSchema.toJson(person) 

val parsedPerson: Option[Person] = personSchema.fromJson(personJson).toOption

val personGen: Gen[Person] = personSchema.toGen

Contributors

Kris Nuttycombe (@nuttycom) Antonio Alonso Dominguez Doug Clinton