json4s/json4s: JSON library

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开源软件名称（OpenSource Name）：

json4s/json4s

开源软件地址(OpenSource Url)：

https://github.com/json4s/json4s

开源编程语言(OpenSource Language)：

Scala 96.2%

开源软件介绍(OpenSource Introduction)：

JSON4S

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:

https://search.maven.org/search?q=org.json4s

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

Support for Enum, Joda-Time, Java 8 Date & Time...

scalaz

Applicative style parsing with Scalaz

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.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.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.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.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}

~~ operator works the same as ~ and is useful in situations where ~ is shadowed, eg. when using Spray or akka-http.

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

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])

object JsonExample {

  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))}))

  def main(args: Array[String]): Unit = {
    println(compact(render(json)))
  }
}

scala> JsonExample.main(Array.empty[String])
{"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.jackson.JsonMethods._

scala> val lotto1 = parse("""{
         "lotto":{
           "lotto-id":5,
           "winning-numbers":[2,45,34,23,7,5,3],
           "winners":[{
             "winner-id":23,
             "numbers":[2,45,34,23,3,5]
           }]
         }
       }""")

scala> val lotto2 = parse("""{
         "lotto":{
           "winners":[{
             "winner-id":54,
             "numbers":[52,3,12,11,18,22]
           }]
         }
       }""")

scala> val mergedLotto = lotto1 merge lotto2

scala> pretty(render(mergedLotto))
res0: String =
{
  "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]
    }]
  }
}

scala> val Diff(changed, added, deleted) = mergedLotto diff lotto1
changed: org.json4s.JValue = JNothing
added: org.json4s.JValue = JNothing
deleted: org.json4s.JValue = JObject(List((lotto,JObject(List(JField(winners,
JArray(List(JObject(List((winner-id,JInt(54)), (numbers,JArray(
List(JInt(52), JInt(3), JInt(12), JInt(11), JInt(18), JInt(22))))))))))))))

Querying JSON

"LINQ" style

JSON values can be extracted using for-comprehensions. Please see more examples in JsonQueryExamples.scala.

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

scala> val json = parse("""
         { "name": "joe",
           "children": [
             {
               "name": "Mary",
               "age": 5
             },
             {
               "name": "Mazy",
               "age": 3
             }
           ]
         }
       """)

scala> for {
         JObject(child) <- json
         JField("age", JInt(age))  <- child
       } yield age
res0: List[BigInt] = List(5, 3)

scala> for {
         JObject(child) <- json
         JField("name", JString(name)) <- child
         JField("age", JInt(age)) <- child
         if age > 4
       } yield (name, age)
res1: List[(String, BigInt)] = List((Mary,5))

XPath + HOFs

The json AST can be queried using XPath-like functions. The following REPL session shows the usage of '\', '\\', 'find', 'filter', 'transform', 'remove' and 'values' functions.

The example json is:

{
  "person": {
    "name": "Joe",
    "age": 35,
    "spouse": {
      "person": {
        "name": "Marilyn",
        "age": 33
      }
    }
  }
}

Translated to DSL syntax:

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

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

scala> val json: JObject =
  ("person" ->
    ("name" -> "Joe") ~
    ("age" -> 35) ~
    ("spouse" ->
      ("person" ->
        ("name"  
                       
                    
                     
                      



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json4s/json4s: JSON library

开源软件名称（OpenSource Name）：

开源软件地址(OpenSource Url)：

开源编程语言(OpenSource Language)：

开源软件介绍(OpenSource Introduction)：

JSON4S

Lift JSON

Jackson

Guide

Installation

SBT users

Maven users

Extras

Parsing JSON

Producing JSON

DSL rules

Example

Merging & Diffing

Querying JSON

"LINQ" style

XPath + HOFs

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