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Version: ZIO 2.x

Getting Started with ZIO Json

ZIO Json is a fast and secure JSON library with tight ZIO integration.

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Introduction​

The goal of this project is to create the best all-round JSON library for Scala:

  • Performance to handle more requests per second than the incumbents, i.e. reduced operational costs.
  • Security to mitigate against adversarial JSON payloads that threaten the capacity of the server.
  • Fast Compilation no shapeless, no type astronautics.
  • Future-Proof, prepared for Scala 3 and next-generation Java.
  • Simple small codebase, concise documentation that covers everything.
  • Helpful errors are readable by humans and machines.
  • ZIO Integration so nothing more is required.

Installation​

In order to use this library, we need to add the following line in our build.sbt file:

libraryDependencies += "dev.zio" %% "zio-json" % "0.5.0"

Example​

Let's try a simple example of encoding and decoding JSON using ZIO JSON.

All the following code snippets assume that the following imports have been declared

import zio.json._

Say we want to be able to read some JSON like

{"curvature":0.5}

into a Scala case class

case class Banana(curvature: Double)

To do this, we create an instance of the JsonDecoder typeclass for Banana using the zio-json code generator. It is best practice to put it on the companion of Banana, like so

object Banana {
  implicit val decoder: JsonDecoder[Banana] = DeriveJsonDecoder.gen[Banana]
}

Note: If you’re using Scala 3 and your case class is defining default parameters, -Yretain-trees needs to be added to scalacOptions.

Now we can parse JSON into our object

scala> """{"curvature":0.5}""".fromJson[Banana]
val res: Either[String, Banana] = Right(Banana(0.5))

Likewise, to produce JSON from our data we define a JsonEncoder

object Banana {
  ...
  implicit val encoder: JsonEncoder[Banana] = DeriveJsonEncoder.gen[Banana]
}

scala> Banana(0.5).toJson
val res: String = {"curvature":0.5}

scala> Banana(0.5).toJsonPretty
val res: String =
{
  "curvature" : 0.5
}

And bad JSON will produce an error in jq syntax with an additional piece of contextual information (in parentheses)

scala> """{"curvature": womp}""".fromJson[Banana]
val res: Either[String, Banana] = Left(.curvature(expected a number, got w))

Say we extend our data model to include more data types

sealed trait Fruit
case class Banana(curvature: Double) extends Fruit
case class Apple (poison: Boolean)   extends Fruit

we can generate the encoder and decoder for the entire sealed family

object Fruit {
  implicit val decoder: JsonDecoder[Fruit] = DeriveJsonDecoder.gen[Fruit]
  implicit val encoder: JsonEncoder[Fruit] = DeriveJsonEncoder.gen[Fruit]
}

allowing us to load the fruit based on a single field type tag in the JSON

scala> """{"Banana":{"curvature":0.5}}""".fromJson[Fruit]
val res: Either[String, Fruit] = Right(Banana(0.5))

scala> """{"Apple":{"poison":false}}""".fromJson[Fruit]
val res: Either[String, Fruit] = Right(Apple(false))

Almost all of the standard library data types are supported as fields on the case class, and it is easy to add support if one is missing.

import zio.json._

sealed trait Fruit                   extends Product with Serializable
case class Banana(curvature: Double) extends Fruit
case class Apple(poison: Boolean)    extends Fruit

object Fruit {
  implicit val decoder: JsonDecoder[Fruit] =
    DeriveJsonDecoder.gen[Fruit]

  implicit val encoder: JsonEncoder[Fruit] =
    DeriveJsonEncoder.gen[Fruit]
}

val json1         = """{ "Banana":{ "curvature":0.5 }}"""
val json2         = """{ "Apple": { "poison": false }}"""
val malformedJson = """{ "Banana":{ "curvature": true }}"""

json1.fromJson[Fruit]
json2.fromJson[Fruit]
malformedJson.fromJson[Fruit]

List(Apple(false), Banana(0.4)).toJsonPretty

How

Extreme performance is achieved by decoding JSON directly from the input source into business objects (inspired by plokhotnyuk). Although not a requirement, the latest advances in Java Loom can be used to support arbitrarily large payloads with near-zero overhead.

Best in class security is achieved with an aggressive early exit strategy that avoids costly stack traces, even when parsing malformed numbers. Malicious (and badly formed) payloads are rejected before finishing reading.

Fast compilation and future-proofing is possible thanks to Magnolia which allows us to generate boilerplate in a way that will survive the exodus to Scala 3. zio-json is internally implemented using a java.io.Reader / java.io.Writer-like interface, which is making a comeback to center stage in Loom.

Simplicity is achieved by using well-known software patterns and avoiding bloat. The only requirement to use this library is to know about Scala's encoding of typeclasses, described in Functional Programming for Mortals.

Helpful errors are produced in the form of a jq query, with a note about what went wrong, pointing to the exact part of the payload that failed to parse.