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Small, fast and easy-to-use JSON library for Scala.
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Small, fast and easy-to-use JSON library for Scala.


Oh why? Why must JSON parsing be so challenging in Scala? First you must download tons of dependencies, then remember to use right package imports (for implicit conversions) and/or implicit formats. C'mon! JSON has only six valid data types (+ null). It's not rocket science.

Zeison tries to simplify the JSON parsing, management and rendering so that you don't need to know any implicit values or conversions. Under the hood, it uses jawn for parsing so it is fast too.

Zeison is extremely lightweight - binaries (including jawn-parser) require under 150KB of space.


To use Zeison in you project, add the following line to your build.sbt

libraryDependencies += "org.tsers.zeison" %% "zeison" % "0.8.0"

All methods and types are inside object org.tsers.zeison.Zeison so in order to use them in your code, you must add the following import

import org.tsers.zeison.Zeison
// or if you want to use methods without "Zeison." prefix
import org.tsers.zeison.Zeison._


Zeison API is designed to be extremely simple so that all its features can be demonstrated with one hundred LOC.


// parse: (String) => JValue
// parse: (InputStream) => JValue
val data = Zeison.parse("""
                        | {
                        |   "messages": ["tsers", "TSERS"],
                        |   "meta": {
                        |     "numKeys": 2,
                        |     "active": true,
                        |     "score": 0.6
                        |   },
                        |   "response": null
                        | }""".stripMargin)

JSON operations

// type checking
// .isInt .isStr .isBool .isDouble .isArray .isObject .isNull .isDefined
assert(data.meta.numKeys.isInt == true)

// value extraction
assert(data.meta.numKeys.toInt == 2)
assert( == true)
assert(data.meta.score.toDouble == 0.6)
assert(data.meta.toMap.get("numKeys").map(_.toInt) == Some(2)) // .toMap => Map[String, JValue]
assert(data.messages.toSeq.head.toStr == "tsers")              // .toSeq => Seq[JValue]

// object/array traversal
assert(data("meta")("numKeys") == data.meta.numKeys)
assert(data.messages(0).toStr == "tsers")

// iterable behaviour (=> Iterable[JValue])
assert( == Set("tsers", "TSERS"))
assert(data.meta.toSet == Set(data.meta)) // all objects and primitives are handled as single value iterable
assert(data.response.toSet == Set.empty)  // all null values and undefined values are handled as empty iterable

// undefined values and optional extraction
assert(data.meta.numKeys.isDefined == true)
assert(data.non_existing.isDefined == false)
assert(data.messages(-1).isDefined == false)
assert(data.messages(10).isDefined == false)
assert( == Some(2))  // .toOption => Option[JValue]
assert(data.non_existing.toOption == None)
assert(data.response.toOption == None)

// runtime errors
assert(Try(data.messages.toInt).isSuccess == false)         // bad type cast
assert(Try(data.non_existing.toInt).isSuccess == false)     // undefined has no value
assert(Try(data.non_existing.sub_field).isSuccess == false) // undefined has no member x

// JSON creation
// ATTENTION: Zeison is NOT an object mapper!
// Only JSON primitive values, Scala Iterables/Maps and Zeison's JValue types are
// accepted - other types cause runtime exception
val obj = Zeison.toJson(Map(
  "msg"    -> "tsers!",
  "meta"   -> data.meta,
  "primes" -> Seq(1,2,3,5)
// or shortcuts for objects and arrays
val justObj = Zeison.toJObject("foo" -> "bar", "tsers" -> 1)
val justArr = Zeison.toJArray(1, 2, 3, "tsers", obj)

// immutable field adding
// .copy(..) works for JSON objects - other types cause runtime exception
val metaWithNewFields = obj.meta.copy("foo" -> "bar", "lol" -> "bal")
assert(metaWithNewFields != obj.meta)
assert( == "bar")
assert(metaWithNewFields.numKeys.toInt == 2)

// immutable field modification
val modifiedScore = obj.meta.copy("score" -> "tsers")
assert(modifiedScore.score.toStr == "tsers")
assert(modifiedScore.numKeys.toInt == 2)

// immutable field removal
val removedScore = obj.meta.copy("score" -> Zeison.JUndefined)
assert(removedScore.score.isDefined == false)
assert(removedScore.numKeys.isDefined == true)

// object merging (shallow!)
val merged = Zeison.toJson(obj.toMap ++ data.toMap)



Custom types

Some libraries (for example Casbah) enable non-standard JSON types. To support these libraries, Zeison provides a way to define simple custom data types that can be built, extracted and rendered from JSON objects.

def toISO8601(date: Date) = {
  val sdf = new SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ssz") { setTimeZone(TimeZone.getTimeZone("UTC")) }
  sdf.format(date).replaceAll("UTC$", "+00:00")
case class JDate(value: Date) extends Zeison.JCustom {
  override def valueAsJson: String = "\"" + toISO8601(value) + "\""

val now    = new Date()
val custom = Zeison.toJson(Map("createdAt" -> JDate(now)))

assert(Zeison.render(custom) == s"""{"createdAt":"${toISO8601(now)}"}""")
assert([Date] == now)



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