[Original] Json4Scala is a one-file-only JSON library for Scala. The file "json.scala" has no more than 300 lines. The implementation of Json Objects is very easy, benefits from the "Any" class of Scala. Array was implemented by "Array[Value]", and Object was implemented by Map[String, Value]. I was trying to implement the code as short as possible, so you can understand the detail of the code easily. For more detail, see "Json.scala".
[samikrc] Modifications:
- Added Exception for some of the reported errors for easier integration.
- Fixed a bug.
- Added a few other improvements.
- [24-Jul-2021] Added Apache 2.0 License. Original code did not have any explicit license at the time of forking.
Note: This parser is not thread-safe. Be mindful of this when using from Spark.
class alltest extends FunSuite {
test("base") {
assert(Json.parse("123").asInt == 123)
assert(Json.parse("-123").asInt == -123)
assert(Json.parse("111111111111111").asLong == 111111111111111l)
assert(Json.parse("true").asBoolean == true)
assert(Json.parse("false").asBoolean == false)
assert(Json.parse("123.123").asDouble == 123.123)
assert(Json.parse("\"aaa\"").asString == "aaa")
assert(Json.parse("\"aaa\"").write() == "\"aaa\"")
val json = Json.Value(Map("a" -> Array(1,2,3), "b" -> Array(4, 5, 6)))
assert(json("a")(0).asInt == 1)
assert(json("b")(1).asInt == 5)
}
test("parse base") {
val str =
"""
{"int":-123, "long": 111111111111111, "string":"asdf", "bool_true": true, "foo":"foo", "bool_false": false}
"""
val json = Json.parse(str)
assert(json.asMap("int").asInt == -123)
assert(json.asMap("long").asLong == 111111111111111l)
assert(json.asMap("string").asString == "asdf")
assert(json.asMap("bool_true").asBoolean == true)
assert(json.asMap("bool_false").asBoolean == false)
println(json.write())
assert(json.write().length > 0)
}
test("parse obj") {
val str =
"""
{"asdf":[1,2,4,{"bbb":"ttt"},432]}
"""
val json = Json.parse(str)
assert(json.asMap("asdf").asArray(0).asInt == 1)
assert(json.asMap("asdf").asArray(3).asMap("bbb").asString == "ttt")
}
test("parse array") {
val str =
"""
[1,2,3,4,{"a":[1,2,3]}]
"""
val json = Json.parse(str)
assert(json.asArray(0).asInt == 1)
assert(json(4)("a")(2).asInt == 3)
assert(json(4)("a")(2).isInt)
assert(json(4)("a").isArray)
assert(json(4)("a").isMap == false)
}
test("real") {
val str = "{\"styles\":[214776380871671808,214783111085424640,214851869216866304,214829406537908224],\"group\":100,\"name\":\"AO4614【金宏达电子】现货库存 质量保证 欢迎购买@\",\"shopgrade\":8,\"price\":0.59,\"shop_id\":60095469,\"C3\":50018869,\"C2\":50024099,\"C1\":50008090,\"imguri\":\"http://img.geilicdn.com/taobao10000177139_425x360.jpg\",\"cag\":50006523,\"soldout\":0,\"C4\":50006523}"
val json = Json.parse(str)
println(json.write())
assert(json.asMap.size > 0)
}
}
I parsed a text file which has 1000000 json-formatted strings to in-memory Values, and then serialized the Values back to strings and restored them to another text file.
With Json4Scala, the process cost time:
27.11s user 3.80s system 123% cpu 24.950 total
With spray-json, the process cost time:
58.44s user 3.43s system 114% cpu 53.826 total
[samikrc] It is also very easy to spit out valid nested JSON from maps and other objects using this library. Example follows.
scala> :paste ./Json.scala
Pasting file ./Json.scala...
import scala.collection.mutable
defined object Json
scala> val a = Map("a"->"x", "b"->"y", "c"->Map("a"->"x", "b"->"y"), "d"->Array("a","b"))
a: scala.collection.immutable.Map[String,Object] = Map(a -> x, b -> y, c -> Map(a -> x, b -> y), d -> Array(a, b))
scala> val b = Json.Value(a)
b: Json.Value = Json$Value@4b87760e
scala> b.write()
res0: String = {"a":"x","b":"y","c":{"a":"x","b":"y"},"d":["a","b"]}