A stable JSON, YAML, MsgPack, XML, etc. serialization framework based on uPickle.
weePickle exists to fulfill two promises:
- We will not break compatibility in
v1.x.y
, as enforced by MiMa. - When we release
v2.0.0
, you can use it immediately without waiting for your other library dependencies to update. We achieve this by shading.
Both weepickle-v1.jar
and weepickle-v2.jar
(in the future) will coexist on the classpath peacefully by applying shading at multiple levels.
- All artifact names are suffixed with the major version number (e.g.
-v1
), which prevents evictions. - All packages are prefixed with the major version number (e.g.
com.rallyhealth.v1
), which prevents classpath conflicts.
Shading allows libraries to depend directly on weePickle-v1 without fear of causing incompatible evictions and runtime failures.
For more background, see shading.md.
weePickle combines some of the best parts of the serialization ecosystem.
- Zero-overhead conversion of uPickle
- jackson-core: async parsing and broad format support (JSON, YAML, XML, CBOR, SMILE, Ion, etc.)
case class
support (any number of fields) through customizable macros- scala json AST interop (circe, json4s, play-json, argonaut)
- Fast serialization to/from MessagePack
libraryDependencies += "com.rallyhealth" %% "weepickle-v1" % "version"
FromJson("[1,2,3]").transform(ToScala[List[Int]]) ==> List(1, 2, 3)
FromScala(List(1, 2, 3)).transform(ToJson.string) ==> "[1,2,3]"
FromJson("[1,2,3]").transform(ToPrettyJson.string) ==>
[
1,
2,
3
]
import com.rallyhealth.weepickle.v1.WeePickle.{macroFromTo, FromTo}
case class Foo(i: Int)
object Foo {
implicit val rw: FromTo[Foo] = macroFromTo
}
FromScala(Foo(1)).transform(ToJson.string) ==> """{"i":1}"""
FromJson("""{"i":1}""").transform(ToScala[Foo]) ==> Foo(1)
libraryDependencies ++= Seq(
"com.rallyhealth" %% "weepickle-v1" % "version",
"com.rallyhealth" %% "weeyaml-v1" % "version"
)
import com.rallyhealth.weejson.v1.yaml.{FromYaml, ToYaml}
import com.rallyhealth.weejson.v1.jackson.FromJson
import java.nio.file.Files
import java.nio.file.Paths
val jsonFile = Files.newInputStream(Paths.get("file.json"))
val yamlFile = Files.newOutputStream(Paths.get("file.yml"))
FromJson(jsonFile).transform(ToYaml.outputStream(yamlFile))
XML and JSON feature sets don't translate one-to-one. The output is currently "whatever jackson does."
libraryDependencies ++= Seq(
"com.rallyhealth" %% "weepickle-v1" % "version",
"com.rallyhealth" %% "weexml-v1" % "version"
)
import com.rallyhealth.weejson.v1.xml.{FromXml, ToXml}
FromScala(Foo(1)).transform(ToXml.string) ==> """<root><i>1</i></root>"""
FromXml("""<root><i>1</i></root>""").transform(ToJson.string) ==> """{"i":"1"}"""
You can convert directly between any From
/To
types. See Zero-Overhead Tree Processing with the Visitor Pattern for how this works.
The following is a non-exhaustive map of type support:
Boolean
,Byte
,Char
,Short
,Int
,Long
,Float
,Double
Tuple
s from 1 to 22- Immutable
Seq
,List
,Vector
,Set
,SortedSet
,Option
,Array
,Maps
, and all other collections with a reasonableCanBuildFrom
implementation Duration
,Either
,Date
,Instant
,LocalDate
,LocalTime
,LocalDateTime
,OffsetDateTime
,ZonedDateTime
- Stand-alone
case class
es andcase object
s, and their generic equivalents, - Non-generic
case class
es andcase object
s that are part of asealed trait
orsealed class
hierarchy sealed trait
andsealed class
es themselves, assuming that all subclasses are picklableUUID
snull
Readability/writability is recursive: a container such as a Tuple or case class is only readable if all its contents are readable, and only writable if all its contents are writable. That means that you cannot serialize a List[Any]
, since weePickle doesn't provide a generic way of serializing Any
.
Case classes are serialized using the apply
and unapply
methods on their companion objects. This means that you can make your own classes serializable by giving them companions apply
and unapply
. sealed
hierarchies are serialized as tagged unions: whatever the serialization of the actual object, together with the fully-qualified name of its class, so the correct class in the sealed hierarchy can be reconstituted later.
Anything else is not supported by default, but you can add support using Custom Picklers.
If a field is missing upon deserialization, weePickle uses the default value if one exists.
case class Dflt(i: Int = 42)
FromJson("""{}""").transform(ToScala[Dflt]) ==> Dflt(42)
FromJson("""{"i": 999}""").transform(ToScala[Dflt]) ==> Dflt(999)
If a field at serialization time has the same value as the default, it will be written unless annotated with @dropDefault
.
FromScala(Dflt(42)).transform(ToJson.string) ==> """{"i": 42}"""
case class Dflt2(@dropDefault i: Int = 42)
FromScala(Dflt2(42)).transform(ToJson.string) ==> """{}"""
If a class is annotated with @dropDefault
, all fields with default values will not be written.
@dropDefault case class Dflt3(i: Int = 42, j: Int = 43, k: Int = 45)
FromScala(Dflt2(42, 43, 0)).transform(ToJson.string) ==> """{"k": 0}"""
Option[T]
is unwrapped when the Option is Some
(rationale):
case class Maybe1(i: Option[Int])
object Maybe1 {
implicit val rw: FromTo[Maybe1] = macroFromTo
}
FromScala(Maybe1(Some(42))).transform(ToJson.string) ==> """{"i":42}"""
FromJson("""{"i":42}""").transform(ToScala[Maybe1]) ==> Maybe1(Some(42))
None
is translated as null
(rationale):
FromScala(Maybe1(None)).transform(ToJson.string) ==> """{"i":null}"""
FromJson("""{"i":null}""").transform(ToScala[Maybe1]) ==> Maybe1(None)
FromJson("""{}""").transform(ToScala[Maybe1]) ==> Maybe1(None)
If you want to suppress the field entirely on None
, you can use Defaults.
case class Maybe2(@dropDefault i: Option[Int] = None)
FromScala(Maybe2(None)).transform(ToJson.string) ==> """{}"""
But Option
types are a special case where None
is an assumed default if a default is not provided explicitly.
So putting @dropDefault
at the class level will apply to all Option
types in the class, whether a default is provided explicitly or not.
@dropDefault case class Maybe3(i: Option[Int], j: Option[Int], k: Option[Int] = Some(0))
FromScala(Maybe3(None, None, Some(0))).transform(ToJson.string) ==> """{}"""
weePickle allows you to specify the key with which a field is serialized via a @key
annotation.
case class KeyBar(@key("hehehe") kekeke: Int)
object KeyBar{
implicit val rw: FromTo[KeyBar] = macroFromTo
}
FromScala(KeyBar(10)).transform(ToJson.string) ==> """{"hehehe":10}"""
FromJson("""{"hehehe": 10}""").transform(ToScala[KeyBar]) ==> KeyBar(10)
Sealed hierarchies are serialized as tagged values, the serialized object tagged with the full name of the instance's class:
sealed trait Outcome
case class Success(value: Int) extends Outcome
case class DeferredVictory(excuses: Seq[String]) extends Outcome
object Success {
implicit val rw: FromTo[Success] = macroFromTo
}
object DeferredVictory {
implicit val rw: FromTo[DeferredVictory] = macroFromTo
}
// order matters: the trait's companion object must come at the end for implicit resolution to work
object Outcome {
implicit val rw: FromTo[Outcome] = macroFromTo
}
FromScala(DeferredVictory(Seq("My json AST is too slow."))).transform(ToJson.string)) ==>
"""{"$type":"com.example.DeferredVictory","excuses":["My json AST is too slow."]}"""
// You can read tagged value without knowing its
// type in advance, just use type of the sealed trait
FromJson("""{"$type":"com.example.Success","value":42}""").transform(ToScala[Outcome]) ==> Success(42)
You can customize the "$type"
key and values with annotations:
@discriminator("flavor")
sealed trait Outcome
@key("s")
case class Success(value: Int) extends Outcome
@key("dv")
case class DeferredVictory(excuses: Seq[String]) extends Outcome
FromScala(Success(42)).transform(ToJson.string) ==> """{"flavor":"s",value:42}"""
object Suit extends Enumeration {
val Spades = Value("Spades")
val Hearts = Value("Hearts")
val Diamonds = Value("Diamonds")
val Clubs = Value("Clubs")
implicit val pickler = WeePickle.fromToEnumerationName(this)
}
FromScala(Suit.Spades).transform(ToJson.string) ==> """"Spades""""
FromJson(""""Spades"""").transform(ToScala[Suit.Value]) ==> Suit.Spades
weePickle leans heavily on jackson-core for interop with JSON, YAML, and most other formats. Jackson-databind is not used.
- jackson-core's JSON support is mature, widely used, and heavily optimized.
- The ecosystem of possible formats is huge: https://github.com/FasterXML/jackson#active-jackson-projects
- jackson-core has a solid track record of backward compatibility.
Internally, jackson-core uses buffer pooling to achieve some of its performance. Buffers return to the pool after calling close()
on the underlying Parser/Generator. If this doesn't happen, new buffers get allocated for each message, and performance suffers slightly.
FromJson
doesn't trust you and calls close()
automatically after writing a single json text, which covers the vast majority of use cases. If you're working with multiple json texts separated by whitespace, jackson can handle it, but you have to drop down below the high level API and remember to close the parser/generator yourself.
WeePickle includes its own AST named Value
, largely unchanged from the upstream uJson.
val obj = Obj(
"foo" -> Arr(
42,
"omg",
true
)
)
obj("foo")(0).num ==> 42
obj.toString ==> """{"foo":[42,"omg",true]}"""
obj.transform(ToPrettyJson.string) ==>
"""{
"foo": [
42,
"omg",
true
]
}"""
FromJson("""{"foo":[42,"omg",true]}""").transform(Value) ==> obj
See:
- https://com-lihaoyi.github.io/upickle/#uJson
- http://www.lihaoyi.com/post/uJsonfastflexibleandintuitiveJSONforScala.html
In JSON, null
"represents the intentional absence of any object value".
This value is regularly used and must be supported.
Scala also has a null
value, but the usage is strongly discouraged, in part because it subverts the type system
For example,
case class User(name: String)
val user = User(null)
user.name // value is null
The more equivalent value in Scala is None
.
Therefore, to support reading in JSON nulls
, set the type to Option
.
This implies that there are two ways for an Option
field to result in a None
value:
- The value was a JSON
null
- The value was missing
Writing a None to JSON will cause the field to be omitted, resulting in an asymmetric read/write.
case class User(name: Option[String])
FromJson("""{"name": null}""").transform(ToScala[User]) ==> User(None)
FromScala(User(None)).transform(ToJson.string) ==> "{}"
weePack is weePickle's MessagePack implementation, largely unchanged from the upstream uPack.
libraryDependencies += "com.rallyhealth" %% "weepack-v1" % "version"
FromMsgPack
/ToMsgPack
perform exceptionally well under benchmarks, yielding higher throughput than JSON or the official jackson-dataformat-msgpack.
java 11:
Benchmark Mode Cnt Score Error Units
ParserBench.jsonBytes thrpt 15 245.665 ± 3.202 ops/s
ParserBench.jsonString thrpt 15 213.312 ± 5.250 ops/s
ParserBench.msgpackJackson thrpt 15 205.738 ± 2.789 ops/s
ParserBench.msgpackScala thrpt 15 422.313 ± 17.172 ops/s
ParserBench.smile thrpt 15 271.947 ± 1.116 ops/s
java 11:
Benchmark Mode Cnt Score Error Units
GeneratorBench.jsonBytes thrpt 15 238.335 ± 11.777 ops/s
GeneratorBench.jsonString thrpt 15 240.125 ± 7.871 ops/s
GeneratorBench.msgpackJackson thrpt 15 181.195 ± 5.774 ops/s
GeneratorBench.msgpackScala thrpt 15 304.540 ± 2.225 ops/s
GeneratorBench.smile thrpt 15 306.462 ± 3.134 ops/s
- ScalaJS is not supported (jackson-core is java-only)
- Same macro limitations as uPickle
- XML support is still rudimentary and contributions are welcome.
See developing.md for building, testing, and IDE support.
uPickle: a simple Scala JSON and Binary (MessagePack) serialization library
If you use uPickle/weePickle and like it, please support it by donating to lihaoyi's Patreon:
Thanks to JSONTestSuite for the comprehensive collection of interesting JSON test files.