https://github.com/json4s/json4s/tree/v.3.2.0_scala2.10

SON4S 

At this moment there are at least 6 json libraries for scala, not counting the java json libraries. All these libraries have a very similar AST. This project aims to provide a single AST to be used by other scala json libraries.

At this moment the approach taken to working with the AST has been taken from lift-json and the native package is in fact lift-json but outside of the lift project.

Lift JSON

This project also attempts to set lift-json free from the release schedule imposed by the lift framework. The Lift framework carries many dependencies and as such it's typically a blocker for many other scala projects when a new version of scala is released.

So the native package in this library is in fact verbatim lift-json in a different package name; this means that your import statements will change if you use this library.

import org.json4s._
import org.json4s.native.JsonMethods._

After that everything works exactly the same as it would with lift-json

Jackson

In addition to the native parser there is also an implementation that uses jackson for parsing to the AST. The jackson module includes most of the jackson-module-scala functionality and the ability to use it with the lift-json AST.

To use jackson instead of the native parser:

import org.json4s._
import org.json4s.jackson.JsonMethods._

Be aware that the default behavior of the jackson integration is to close the stream when it's done. If you want to change that:

import com.fasterxml.jackson.databind.SerializationFeature
org.json4s.jackson.JsonMethods.mapper.configure(SerializationFeature.CLOSE_CLOSEABLE, false)

Guide

Parsing and formatting utilities for JSON.

A central concept in lift-json library is Json AST which models the structure of a JSON document as a syntax tree.

sealed abstract class JValue
case object JNothing extends JValue // 'zero' for JValue
case object JNull extends JValue
case class JString(s: String) extends JValue
case class JDouble(num: Double) extends JValue
case class JDecimal(num: BigDecimal) extends JValue
case class JInt(num: BigInt) extends JValue
case class JLong(num: Long) extends JValue
case class JBool(value: Boolean) extends JValue
case class JObject(obj: List[JField]) extends JValue
case class JArray(arr: List[JValue]) extends JValue

type JField = (String, JValue)

All features are implemented in terms of the above AST. Functions are used to transform the AST itself, or to transform the AST between different formats. Common transformations are summarized in a following picture.

Summary of the features:

• Fast JSON parser
• LINQ-style queries
• Case classes can be used to extract values from parsed JSON
• Diff & merge
• DSL to produce valid JSON
• XPath-like expressions and HOFs to manipulate JSON
• Pretty and compact printing
• XML conversions
• Serialization
• Low-level pull parser API

Installation

You can add the json4s as a dependency in following ways. Note, replace {latestVersion} with correct Json4s version.

You can find available versions here:

SBT users

For the native support add the following dependency to your project description:

val json4sNative = "org.json4s" %% "json4s-native" % "{latestVersion}"

For the Jackson support add the following dependency to your project description:

val json4sJackson = "org.json4s" %% "json4s-jackson" % "{latestVersion}"

Maven users

For the native support add the following dependency to your pom:

<dependency>
  <groupId>org.json4s</groupId>
  <artifactId>json4s-native_${scala.version}</artifactId>
  <version>{latestVersion}</version>
</dependency>

For the jackson support add the following dependency to your pom:

<dependency>
  <groupId>org.json4s</groupId>
  <artifactId>json4s-jackson_${scala.version}</artifactId>
  <version>{latestVersion}</version>
</dependency>

Extras

• ext

Support for Enum, Joda-Time, ...

Applicative style parsing with Scalaz

Migration from older versions

3.3.0 ->

json4s 3.3 basically should be source code compatible with 3.2.x. Since json4s 3.3.0, We've started using MiMa for binary compatibility verification not to repeat the bin compatibility issue described here.

The behavior of .toOption on JValue has changed. Now both JNothing and JNull return None. For the old behavior you can use toSome which will only turn a JNothing into a None.

3.0.0 ->

JField is no longer a JValue. This means more type safety since it is no longer possible to create invalid JSON where JFields are added directly into JArrays for instance. The most noticeable consequence of this change are that map, transform, find and filter come in two versions:

def map(f: JValue => JValue): JValue
def mapField(f: JField => JField): JValue
def transform(f: PartialFunction[JValue, JValue]): JValue
def transformField(f: PartialFunction[JField, JField]): JValue
def find(p: JValue => Boolean): Option[JValue]
def findField(p: JField => Boolean): Option[JField]
//...

Use *Field functions to traverse fields in the JSON, and use the functions without 'Field' in the name to traverse values in the JSON.

2.2 ->

Path expressions were changed after version 2.2. Previous versions returned JField, which unnecessarily complicated the use of the expressions. If you have used path expressions with pattern matching like:

val JField("bar", JInt(x)) = json \ "foo" \ "bar"

it is now required to change that to:

val JInt(x) = json \ "foo" \ "bar"

Parsing JSON

Any valid json can be parsed into internal AST format. For native support:

scala> import org.json4s._
scala> import org.json4s.native.JsonMethods._

scala> parse(""" { "numbers" : [1, 2, 3, 4] } """)
res0: org.json4s.JsonAST.JValue =
      JObject(List((numbers,JArray(List(JInt(1), JInt(2), JInt(3), JInt(4))))))

scala> parse("""{"name":"Toy","price":35.35}""", useBigDecimalForDouble = true)
res1: org.json4s.package.JValue = 
      JObject(List((name,JString(Toy)), (price,JDecimal(35.35))))

For jackson support:

scala> import org.json4s._
scala> import org.json4s.jackson.JsonMethods._

scala> parse(""" { "numbers" : [1, 2, 3, 4] } """)
res0: org.json4s.JsonAST.JValue =
      JObject(List((numbers,JArray(List(JInt(1), JInt(2), JInt(3), JInt(4))))))

scala> parse("""{"name":"Toy","price":35.35}""", useBigDecimalForDouble = true)
res1: org.json4s.package.JValue = 
      JObject(List((name,JString(Toy)), (price,JDecimal(35.35))))

Producing JSON

You can generate json in 2 modes: either in DoubleMode or in BigDecimalMode; the former will map all decimal values into JDoubles, and the latter into JDecimals.

For the double mode dsl use:

import org.json4s.JsonDSL._
// or
import org.json4s.JsonDSL.WithDouble._

For the big decimal mode dsl use:

import org.json4s.JsonDSL.WithBigDecimal._

DSL rules

• Primitive types map to JSON primitives.
• Any seq produces JSON array.

scala> val json = List(1, 2, 3)

scala> compact(render(json))
res0: String = [1,2,3]

• Tuple2[String, A] produces field.

scala> val json = ("name" -> "joe")

scala> compact(render(json))
res1: String = {"name":"joe"}

• ~ operator produces object by combining fields.

scala> val json = ("name" -> "joe") ~ ("age" -> 35)

scala> compact(render(json))
res2: String = {"name":"joe","age":35}

• Any value can be optional. The field and value are completely removed when it doesn't have a value.

scala> val json = ("name" -> "joe") ~ ("age" -> Some(35))

scala> compact(render(json))
res3: String = {"name":"joe","age":35}

scala> val json = ("name" -> "joe") ~ ("age" -> (None: Option[Int]))

scala> compact(render(json))
res4: String = {"name":"joe"}

• Extending the dsl

To extend the dsl with your own classes you must have an implicit conversion in scope of signature:

type DslConversion = T => JValue

Example

object JsonExample extends App {
  import org.json4s._
  import org.json4s.JsonDSL._
  import org.json4s.jackson.JsonMethods._

  case class Winner(id: Long, numbers: List[Int])
  case class Lotto(id: Long, winningNumbers: List[Int], winners: List[Winner], drawDate: Option[java.util.Date])

  val winners = List(Winner(23, List(2, 45, 34, 23, 3, 5)), Winner(54, List(52, 3, 12, 11, 18, 22)))
  val lotto = Lotto(5, List(2, 45, 34, 23, 7, 5, 3), winners, None)

  val json =
    ("lotto" ->
      ("lotto-id" -> lotto.id) ~
      ("winning-numbers" -> lotto.winningNumbers) ~
      ("draw-date" -> lotto.drawDate.map(_.toString)) ~
      ("winners" ->
        lotto.winners.map { w =>
          (("winner-id" -> w.id) ~
           ("numbers" -> w.numbers))}))

  println(compact(render(json)))
}

scala> JsonExample
{"lotto":{"lotto-id":5,"winning-numbers":[2,45,34,23,7,5,3],"winners":
[{"winner-id":23,"numbers":[2,45,34,23,3,5]},{"winner-id":54,"numbers":[52,3,12,11,18,22]}]}}

The above example produces the following pretty-printed JSON. Notice that draw-date field is not rendered since its value is None:

scala> pretty(render(JsonExample.json))

{
  "lotto":{
    "lotto-id":5,
    "winning-numbers":[2,45,34,23,7,5,3],
    "winners":[{
      "winner-id":23,
      "numbers":[2,45,34,23,3,5]
    },{
      "winner-id":54,
      "numbers":[52,3,12,11,18,22]
    }]
  }
}

Merging & Diffing

Two JSONs can be merged and diffed with each other. Please see more examples in MergeExamples.scala and DiffExamples.scala.

scala> import org.json4s._
scala> import org.json4s.j