如何使用标准 Scala 类在 Scala 中解析 JSON？

Question

我正在使用 Scala 2.8 中的 JSON 类构建来解析 JSON 代码。由于依赖性最小化，我不想使用 Liftweb 之一或任何其他。

我这样做的方式似乎太必要了，有更好的方法吗？

import scala.util.parsing.json._
...
val json:Option[Any] = JSON.parseFull(jsonString)
val map:Map[String,Any] = json.get.asInstanceOf[Map[String, Any]]
val languages:List[Any] = map.get("languages").get.asInstanceOf[List[Any]]
languages.foreach( langMap => {
val language:Map[String,Any] = langMap.asInstanceOf[Map[String,Any]]
val name:String = language.get("name").get.asInstanceOf[String]
val isActive:Boolean = language.get("is_active").get.asInstanceOf[Boolean]
val completeness:Double = language.get("completeness").get.asInstanceOf[Double]
}

Answer 1

val jsonString =
  """
    |{
    | "languages": [{
    |     "name": "English",
    |     "is_active": true,
    |     "completeness": 2.5
    | }, {
    |     "name": "Latin",
    |     "is_active": false,
    |     "completeness": 0.9
    | }]
    |}
  """.stripMargin

val result = JSON.parseFull(jsonString).map {
  case json: Map[String, List[Map[String, Any]]] =>
    json("languages").map(l => (l("name"), l("is_active"), l("completeness")))
}.get

println(result)

assert( result == List(("English", true, 2.5), ("Latin", false, 0.9)) )

Answer 2

你可以这样做！非常容易解析 JSON 代码：P

package org.sqkb.service.common.bean

import java.text.SimpleDateFormat

import org.json4s
import org.json4s.JValue
import org.json4s.jackson.JsonMethods._
//import org.sqkb.service.common.kit.{IsvCode}

import scala.util.Try

/**
  *
  */
case class Order(log: String) {

  implicit lazy val formats = org.json4s.DefaultFormats

  lazy val json: json4s.JValue = parse(log)

  lazy val create_time: String = (json \ "create_time").extractOrElse("1970-01-01 00:00:00")
  lazy val site_id: String = (json \ "site_id").extractOrElse("")
  lazy val alipay_total_price: Double = (json \ "alipay_total_price").extractOpt[String].filter(_.nonEmpty).getOrElse("0").toDouble
  lazy val gmv: Double = alipay_total_price
  lazy val pub_share_pre_fee: Double = (json \ "pub_share_pre_fee").extractOpt[String].filter(_.nonEmpty).getOrElse("0").toDouble
  lazy val profit: Double = pub_share_pre_fee

  lazy val trade_id: String = (json \ "trade_id").extractOrElse("")
  lazy val unid: Long = Try((json \ "unid").extractOpt[String].filter(_.nonEmpty).get.toLong).getOrElse(0L)
  lazy val cate_id1: Int = (json \ "cate_id").extractOrElse(0)
  lazy val cate_id2: Int = (json \ "subcate_id").extractOrElse(0)
  lazy val cate_id3: Int = (json \ "cate_id3").extractOrElse(0)
  lazy val cate_id4: Int = (json \ "cate_id4").extractOrElse(0)
  lazy val coupon_id: Long = (json \ "coupon_id").extractOrElse(0)

  lazy val platform: Option[String] = Order.siteMap.get(site_id)


  def time_fmt(fmt: String = "yyyy-MM-dd HH:mm:ss"): String = {
    val dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss")
    val date = dateFormat.parse(this.create_time)
    new SimpleDateFormat(fmt).format(date)
  }

}

Answer 3

这是我使用 Scala Parser Combinator Library 的方式：

import scala.util.parsing.combinator._
class ImprovedJsonParser extends JavaTokenParsers {

  def obj: Parser[Map[String, Any]] =
    "{" ~> repsep(member, ",") <~ "}" ^^ (Map() ++ _)

  def array: Parser[List[Any]] =
    "[" ~> repsep(value, ",") <~ "]"

  def member: Parser[(String, Any)] =
    stringLiteral ~ ":" ~ value ^^ { case name ~ ":" ~ value => (name, value) }

  def value: Parser[Any] = (
    obj
      | array
      | stringLiteral
      | floatingPointNumber ^^ (_.toDouble)
      |"true"
      |"false"
    )

}
object ImprovedJsonParserTest extends ImprovedJsonParser {
  def main(args: Array[String]) {
    val jsonString =
    """
      {
        "languages": [{
            "name": "English",
            "is_active": true,
            "completeness": 2.5
        }, {
            "name": "Latin",
            "is_active": false,
            "completeness": 0.9
        }]
      }
    """.stripMargin


    val result = parseAll(value, jsonString)
    println(result)

  }
}

Answer 4

scala.util.parsing.json.JSON 已弃用。

这是 circe 的另一种方法。仅供参考的文档：https://circe.github.io/circe/cursors.html

在build.sbt中添加依赖，我使用的是scala 2.13.4，注意scala版本必须与库版本一致。

val circeVersion = "0.14.0-M2"

libraryDependencies ++= Seq(
  "io.circe"  %% "circe-core"     % circeVersion,
  "io.circe"  %% "circe-generic"  % circeVersion,
  "io.circe"  %% "circe-parser"   % circeVersion
)

示例1：

case class Person(name: String, age: Int)

object Main {
  def main(args: Array[String]): Unit = {
    val input =
      """
        |{
        |  "kind": "Listing",
        |  "data": [
        |    {
        |      "name": "Frodo",
        |      "age": 51
        |    },
        |    {
        |      "name": "Bilbo",
        |      "age": 60
        |    }
        |  ]
        |}
        |""".stripMargin

    implicit val decoderPerson: Decoder[Person] = deriveDecoder[Person] // decoder required to parse to custom object

    val parseResult: Json = circe.parser.parse(input).getOrElse(Json.Null)
    val data: ACursor = parseResult.hcursor.downField("data") // get the data field
    val personList: List[Person] = data.as[List[Person]].getOrElse(null) // parse the dataField to a list of Person
    for {
      person <- personList
    } println(person.name + " is " + person.age)
  }
}

示例2，json有一个对象中的对象：

case class Person(name: String, age: Int, position: Position)
case class Position(x: Int, y: Int)

object Main {
  def main(args: Array[String]): Unit = {
    val input =
      """
        |{
        |  "kind": "Listing",
        |  "data": [
        |    {
        |      "name": "Frodo",
        |      "age": 51,
        |      "position": {
        |        "x": 10,
        |        "y": 20
        |      }
        |    },
        |    {
        |      "name": "Bilbo",
        |      "age": 60,
        |      "position": {
        |        "x": 75,
        |        "y": 85
        |      }
        |    }
        |  ]
        |}
        |""".stripMargin

    implicit val decoderPosition: Decoder[Position] = deriveDecoder[Position] // must be defined before the Person decoder
    implicit val decoderPerson: Decoder[Person] = deriveDecoder[Person]

    val parseResult = circe.parser.parse(input).getOrElse(Json.Null)
    val data = parseResult.hcursor.downField("data")
    val personList = data.as[List[Person]].getOrElse(null)
    for {
      person <- personList
    } println(person.name + " is " + person.age + " at " + person.position)
  }
}

Answer 5

这是一个基于提取器的解决方案，它将执行类转换：

class CC[T] { def unapply(a:Any):Option[T] = Some(a.asInstanceOf[T]) }

object M extends CC[Map[String, Any]]
object L extends CC[List[Any]]
object S extends CC[String]
object D extends CC[Double]
object B extends CC[Boolean]

val jsonString =
    """
      {
        "languages": [{
            "name": "English",
            "is_active": true,
            "completeness": 2.5
        }, {
            "name": "Latin",
            "is_active": false,
            "completeness": 0.9
        }]
      }
    """.stripMargin

val result = for {
    Some(M(map)) <- List(JSON.parseFull(jsonString))
    L(languages) = map("languages")
    M(language) <- languages
    S(name) = language("name")
    B(active) = language("is_active")
    D(completeness) = language("completeness")
} yield {
    (name, active, completeness)
}

assert( result == List(("English",true,2.5), ("Latin",false,0.9)))

在 for 循环开始时，我人为地将结果包装在列表中，以便它在末尾生成一个列表。然后，在 for 循环的其余部分中，我使用生成器（使用 <-）和值定义（使用 =）将利用 unapply 方法的事实。

（较旧的答案已被编辑 - 如果您好奇，请检查编辑历史记录）

Answer 6

这是我进行模式匹配的方式：

val result = JSON.parseFull(jsonStr)
result match {
  // Matches if jsonStr is valid JSON and represents a Map of Strings to Any
  case Some(map: Map[String, Any]) => println(map)
  case None => println("Parsing failed")
  case other => println("Unknown data structure: " + other)
}

Answer 7

我喜欢@huynhjl 的回答，它引导我走上了正确的道路。但是，它不擅长处理错误情况。如果所需的节点不存在，则会出现强制转换异常。我对此进行了稍微调整，以利用 Option 更好地处理这个问题。

class CC[T] {
  def unapply(a:Option[Any]):Option[T] = if (a.isEmpty) {
    None
  } else {
    Some(a.get.asInstanceOf[T])
  }
}

object M extends CC[Map[String, Any]]
object L extends CC[List[Any]]
object S extends CC[String]
object D extends CC[Double]
object B extends CC[Boolean]

for {
  M(map) <- List(JSON.parseFull(jsonString))
  L(languages) = map.get("languages")
  language <- languages
  M(lang) = Some(language)
  S(name) = lang.get("name")
  B(active) = lang.get("is_active")
  D(completeness) = lang.get("completeness")
} yield {
  (name, active, completeness)
}

当然，这与其说是处理错误，不如说是避免错误。如果缺少任何 json 节点，这将产生一个空列表。您可以在执行操作之前使用 match 检查节点是否存在...

for {
  M(map) <- Some(JSON.parseFull(jsonString))
} yield {
  map.get("languages") match {
    case L(languages) => {
      for {
        language <- languages
        M(lang) = Some(language)
        S(name) = lang.get("name")
        B(active) = lang.get("is_active")
        D(completeness) = lang.get("completeness")
      } yield {
        (name, active, completeness)
      }        
    }
    case None => "bad json"
  }
}

Answer 8

我尝试了一些方法，倾向于将模式匹配作为避免强制转换的一种方式，但在集合类型上的类型擦除方面遇到了麻烦。

主要问题似乎是解析结果的完整类型反映了 JSON 数据的结构，并且要么很麻烦，要么无法完全说明。我想这就是为什么使用 Any 来截断类型定义的原因。使用 Any 会导致需要进行强制转换。

我已经破解了下面的一些内容，该内容很简洁，但对于问题中的代码隐含的 JSON 数据非常具体。更通用的东西会更令人满意，但我不确定它是否会非常优雅。

implicit def any2string(a: Any)  = a.toString
implicit def any2boolean(a: Any) = a.asInstanceOf[Boolean]
implicit def any2double(a: Any)  = a.asInstanceOf[Double]

case class Language(name: String, isActive: Boolean, completeness: Double)

val languages = JSON.parseFull(jstr) match {
  case Some(x) => {
    val m = x.asInstanceOf[Map[String, List[Map[String, Any]]]]

    m("languages") map {l => Language(l("name"), l("isActive"), l("completeness"))}
  }
  case None => Nil
}

languages foreach {println}