Java開發工具-scala處理json格式利器-json4s詳解
1.為什麼是json4s
從json4s的官方描述
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.
在scala庫中，至少有6個jso程式設計客棧n庫，並且不包括 java的json庫，這些庫都有著類似的抽象語法樹AST，json4s的目的就是為了使用簡單的一種語法支援這些json庫，因此說json4s可以說是一種json的規範處理，配合scala開發過程中極其簡介的語法特性，可以輕鬆地實現比如json合併，json的diff操作，可以方gAlvxC便地處理jsonArray的字串，所以如果使用scala，那麼json4s一定不能錯過，在實際場景下使用json處理資料很常見，比如spark開發中處理原始json資料等等，開始上手可能看起來比較複雜，但是用起來你會很爽。
2.json4s的資料結構
json4s包括10個型別和一個type型別的物件，分別如下
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)
可以看到，他們都繼承自JValue,JValue是json4s裡面類似於java的object地位，而JField是用來一次性匹配json的key,value對而準備的。
3.json4s的實踐
下面來看，我們如何來使用json4s
<dependency> <groupId>org.json4s</groupId> <artifactId>json4s-native_2.11</artifactId> <version>3.7.0-M6</version> </dependency>
看下面的程式碼即可，註釋寫的比較清晰，一般來說json的使用無外乎是字串到物件或者物件到字串，而字串到物件可以用case class 也可以用原始的比如上面提到的類
package com.hoult.scala.json4s import org.json4s._ import 程式設計客棧org.json4s.JsonDSL._ import org.json4s.native.JsonMethods._ object Demo1 { def main(args: Array[String]): Unit = { //parse方法表示從字串到json-object val person = parse( """ |{"name":"Toy","price":35.35} |""".stripMargin,useBigDecimalForDouble = true) // 1.模式匹配提取， \表示提取 val JString(name) = (person \ "name") println(name) // 2.extract[String]取值 // implicit val formats = org.json4s.Formats implicit val formats = DefaultFormats val name2 程式設計客棧= (person \ "name").extract[String] val name3 = (person \ "name").extractOpt[String] val name4 = (person \ "name").extractOrElse("") // 3.多層巢狀取值 val parseJson: JValue = parse( """ |{"name":{"tome":"new"},useBigDecimalForDouble = true) //3.1 逐層訪問 val value = (parseJson \ "name程式設計客棧" \ "tome").extract[String] //3.2 迴圈訪問 val value2 = (parseJson \\ "tome") println(value2) //4.巢狀json串解析 val json = parse( """ { "name": "joe","children": [ { "name": "Mary","age": 20 },{ "name": "Mazy","age": 10 } ] } """) // println(json \ "children") //模式匹配 for (JArray(child) <- json) println(child) //提取object 下 某欄位的值 val ages = for { JObject(child) <- json JField("age",JInt(age)) <- child } yield age println(ages) // 巢狀取陣列中某個欄位值，並新增過濾 val nameAges = for { JObject(child) <- json JField("name",JString(name)) <- child JField("age",JInt(age)) <- child if age > 10 } yield (name,age) println(nameAges) // 5.json和物件的轉換,[就是json陣列] case class ClassA(a: Int,b: Int) val json2: String = """[{"a":1,"b":2},{"a":1,"b":2}]""" val bb: List[ClassA] = parse(json2).extract[List[ClassA]] println(bb) // 6.json轉物件，[json 非json陣列，但是每個級別要明確] case class ClassC(a: Int,b: Int) case class ClassB(c: List[ClassC]) val json3: String = """{"c":[{"a":1,"b":2}]}""" val cc: ClassB = parse(json3).extract[ClassB] println(cc) // 7.使用org.json4s產生json字串 // import org.json4s.JsonDSL._ val json1 = List(1,2,3) val jsonMap = ("name" -> "joe") val jsonUnion = ("name" -> "joe") ~ ("age" -> 10) val jsonOpt = ("name" -> "joe") ~ ("age" -> Some(1)) val jsonOpt2 = ("name" -> "joe") ~ ("age" -> (None: Option[Int])) 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(10,List(1,5)),Winner(11,0))) val lotto = Lotto(11,5),winners,None) val jsonCase = ("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(json1))) println(compact(render(jsonMap))) println(compact(render(jsonUnion))) println(compact(render(jsonOpt))) println(compact(render(jsonOpt2))) println(compact(render(jsonCase))) // 8.json格式化 println(pretty(render(jsonCase))) // 9.合併字串 val lotto1 = parse("""{ "lotto":{ "lotto-id": 1,"winning-numbers":[7,8,9],"winners":[{ "winner-id": 1,"numbers":[7,9] }] } }""") val lotto2 = parse("""{ "lotto":{ "winners":[{ "winner-id": 2,"numbers":[1,23,5] }] } }""") val mergedLotto = lotto1 merge lotto2 // println(pretty(render(mergedLotto))) // 10.字串尋找差異 val Diff(changed,added,deleted) = mergedLotto diff lotto1 println(changed) println(added) println(deleted) val json10 = parse( """ """) println("********8") println(json10) for (JObject(j) <- json10) println(j) println("********11") // 11.遍歷json，使用for // key1 values key1_vk1:v1 .... val str = "{\"tag_name\":\"t_transaction_again_day\",\"tag_distribute_json\":\"{\\\"1\\\":\\\"0.0011231395\\\",\\\"0\\\":\\\"0.9988768605\\\"}\"}" val valueJson = parse(str) \ "tag_distribute_json" println(valueJson) for { JString(obj) <- valueJson JObject(dlist) <- parse(obj) (key,JString(value))<- dlist } { println(key + "::" + value) // val kvList = for (JObject(key,value) <- parse(obj)) yield (key,value) // println("obj : " + kvList.mkString(",")) } } }
4.注意
4.1 compact 和 render的使用
常用寫法compact(render(json)),用來把一個json物件轉成字串，並壓縮顯示，當然也可以用prety(render(json))
4.2 序列化時候需要一個隱式物件
例如下面的
implicit val formats = Serialization.formats(NoTypeHints)
參考
https://json4s.org/
https://github.com/json4s/json4s/tree/v.3.2.0_scala2.10
https://www.cnblogs.com/yyy-blog/p/11819302.html
https://www.shuzhiduo.com/A/Vx5MBVOYdN/
https://segmentfault.com/a/1190000007302496
https://www.coder.work/article/6786418
https://www.wolai.com/sTVar6XXjpuM9ANFn2sx9n
https://www.wolai.com/sTVar6XXjpuM9ANFn2sx9n
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