Java開發(fā)工具-scala處理json格式利器-json4s詳解
1.為什么是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json庫,并且不包括 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持這些json庫,因此說json4s可以說是一種json的規(guī)范處理,配合scala開發(fā)過程中極其簡介的語法特性,可以輕松地實(shí)現(xiàn)比如json合并,json的diff操作,可以方便地處理jsonArray的字符串,所以如果使用scala,那么json4s一定不能錯過,在實(shí)際場景下使用json處理數(shù)據(jù)很常見,比如spark開發(fā)中處理原始json數(shù)據(jù)等等,開始上手可能看起來比較復(fù)雜,但是用起來你會很爽。
2.json4s的數(shù)據(jù)結(jié)構(gòu)
json4s包括10個類型和一個type類型的對象,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里面類似于java的object地位,而JField是用來一次性匹配json的key,value對而準(zhǔn)備的。
3.json4s的實(shí)踐
下面來看,我們?nèi)绾蝸硎褂胘son4s
<dependency> <groupId>org.json4s</groupId> <artifactId>json4s-native_2.11</artifactId> <version>3.7.0-M6</version> </dependency>
看下面的代碼即可,注釋寫的比較清晰,一般來說json的使用無外乎是字符串到對象或者對象到字符串,而字符串到對象可以用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 org.json4s.JsonDSL._
import org.json4s.native.JsonMethods._
object Demo1 {
def main(args: Array[String]): Unit = {
//parse方法表示從字符串到j(luò)son-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 = (person \ "name").extract[String]
val name3 = (person \ "name").extractOpt[String]
val name4 = (person \ "name").extractOrElse("")
// 3.多層嵌套取值
val parseJson: JValue = parse(
"""
|{"name":{"tome":"new"},"price":35.35}
|""".stripMargin, useBigDecimalForDouble = true)
//3.1 逐層訪問
val value = (parseJson \ "name" \ "tome").extract[String]
//3.2 循環(huán)訪問
val value2 = (parseJson \\ "tome")
println(value2)
//4.嵌套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 某字段的值
val ages = for {
JObject(child) <- json
JField("age", JInt(age)) <- child
} yield age
println(ages)
// 嵌套取數(shù)組中某個字段值,并添加過濾
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和對象的轉(zhuǎn)換,[就是json數(shù)組]
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(zhuǎn)對象,[json 非json數(shù)組,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},{"a":1,"b":2}]}"""
val cc: ClassB = parse(json3).extract[ClassB]
println(cc)
// 7.使用org.json4s產(chǎn)生json字符串
// 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, 2, 5)), Winner(11, List(1, 2, 0)))
val lotto = Lotto(11, List(1, 2, 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.合并字符串
val lotto1 = parse("""{
"lotto":{
"lotto-id": 1,
"winning-numbers":[7,8,9],
"winners":[{
"winner-id": 1,
"numbers":[7,8,9]
}]
}
}""")
val lotto2 = parse("""{
"lotto":{
"winners":[{
"winner-id": 2,
"numbers":[1,23,5]
}]
}
}""")
val mergedLotto = lotto1 merge lotto2
// println(pretty(render(mergedLotto)))
// 10.字符串尋找差異
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對象轉(zhuǎn)成字符串,并壓縮顯示,當(dāng)然也可以用prety(render(json))
4.2 序列化時候需要一個隱式對象
例如下面的
implicit val formats = Serialization.formats(NoTypeHints)
參考
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
到此這篇關(guān)于開發(fā)工具-scala處理json格式利器-json4s的文章就介紹到這了,更多相關(guān)scala處理json格式利器-json4s內(nèi)容請搜索腳本之家以前的文章或繼續(xù)瀏覽下面的相關(guān)文章希望大家以后多多支持腳本之家!
相關(guān)文章
SpringBoot使用SchedulingConfigurer實(shí)現(xiàn)多個定時任務(wù)多機(jī)器部署問題(推薦)
這篇文章主要介紹了SpringBoot使用SchedulingConfigurer實(shí)現(xiàn)多個定時任務(wù)多機(jī)器部署問題,定時任務(wù)多機(jī)器部署解決方案,方式一拆分,單獨(dú)拆分出來,單獨(dú)跑一個應(yīng)用,方式二是基于aop攔截處理(搶占執(zhí)行),只要有一個執(zhí)行,其它都不執(zhí)行,需要的朋友可以參考下2023-01-01
Java利用IO流實(shí)現(xiàn)簡易的記事本功能
本文將利用Java中IO流編寫一個模擬日記本的程序,通過在控制臺輸入指令,實(shí)現(xiàn)在本地新建文件,打開日記本和修改日記本等功能,感興趣的可以了解一下2022-05-05
Mybatis超級強(qiáng)大的動態(tài)SQL語句大全
MyBatis的動態(tài)SQL是基于OGNL表達(dá)式的,它可以幫助我們方便的在SQL語句中實(shí)現(xiàn)某些邏輯,下面這篇文章主要給大家介紹了關(guān)于Mybatis超級強(qiáng)大的動態(tài)SQL語句的相關(guān)資料,需要的朋友可以參考下2022-05-05
logstash將mysql數(shù)據(jù)同步到elasticsearch方法詳解
這篇文章主要為大家介紹了logstash將mysql數(shù)據(jù)同步到elasticsearch方法詳解,有需要的朋友可以借鑒參考下,希望能夠有所幫助,祝大家多多進(jìn)步,早日升職加薪2022-12-12
JavaWeb?使用DBUtils實(shí)現(xiàn)增刪改查方式
這篇文章主要介紹了JavaWeb?使用DBUtils實(shí)現(xiàn)增刪改查方式,具有很好的參考價值,希望對大家有所幫助。如有錯誤或未考慮完全的地方,望不吝賜教2021-12-12

