layout | title |
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docs |
Custom codecs |
If you want to write your own codec instead of using automatic or semi-automatic derivation, you can do so in a couple of ways.
Firstly, you can write a new Encoder[A]
and Decoder[A]
from scratch:
import io.circe.{ Decoder, Encoder, HCursor, Json }
class Thing(val foo: String, val bar: Int)
implicit val encodeFoo: Encoder[Thing] = new Encoder[Thing] {
final def apply(a: Thing): Json = Json.obj(
("foo", Json.fromString(a.foo)),
("bar", Json.fromInt(a.bar))
)
}
implicit val decodeFoo: Decoder[Thing] = new Decoder[Thing] {
final def apply(c: HCursor): Decoder.Result[Thing] =
for {
foo <- c.downField("foo").as[String]
bar <- c.downField("bar").as[Int]
} yield {
new Thing(foo, bar)
}
}
But in many cases you might find it more convenient to piggyback on top of the decoders that are
already available. For example, a codec for java.time.Instant
might look like this:
import io.circe.{ Decoder, Encoder }
import java.time.Instant
import scala.util.Try
implicit val encodeInstant: Encoder[Instant] = Encoder.encodeString.contramap[Instant](_.toString)
implicit val decodeInstant: Decoder[Instant] = Decoder.decodeString.emapTry { str =>
Try(Instant.parse(str))
}
If you are using custom codecs and an older versions of scala (below 2.12) and you get errors like
this value flatMap is not a member of io.circe.Decoder.Result[Option[String]]
or
value map is not a member of io.circe.Decoder.Result[Option[String]]
then you need to use the
following import: import cats.syntax.either._
to fix this.
If you need to encode/decode Map[K, V]
where K
is not String
(or Symbol
, Int
, Long
, etc.),
you need to provide a KeyEncoder
and/or KeyDecoder
for your custom key type.
For example:
import io.circe._, io.circe.syntax._
case class Foo(value: String)
implicit val fooKeyEncoder: KeyEncoder[Foo] = new KeyEncoder[Foo] {
override def apply(foo: Foo): String = foo.value
}
val map = Map[Foo, Int](
Foo("hello") -> 123,
Foo("world") -> 456
)
val json = map.asJson
implicit val fooKeyDecoder: KeyDecoder[Foo] = new KeyDecoder[Foo] {
override def apply(key: String): Option[Foo] = Some(Foo(key))
}
json.as[Map[Foo, Int]]
It's often necessary to work with keys in your JSON objects that aren't idiomatic case class member names in Scala. While the standard generic derivation doesn't support this use case, the experimental circe-generic-extras module does provide two ways to transform your case class member names during encoding and decoding.
In many cases the transformation is as simple as going from camel case to snake case, in which case all you need is a custom implicit configuration:
import io.circe.generic.extras._, io.circe.syntax._
implicit val config: Configuration = Configuration.default.withSnakeCaseMemberNames
@ConfiguredJsonCodec case class User(firstName: String, lastName: String)
User("Foo", "McBar").asJson
In other cases you may need more complex mappings. These can be provided as a function:
import io.circe.generic.extras._, io.circe.syntax._
implicit val config: Configuration = Configuration.default.copy(
transformMemberNames = {
case "i" => "my-int"
case other => other
}
)
@ConfiguredJsonCodec case class Bar(i: Int, s: String)
Bar(13, "Qux").asJson
Since this is a common use case, we also support for mapping member names via an annotation:
import io.circe.generic.extras._, io.circe.syntax._
implicit val config: Configuration = Configuration.default
@ConfiguredJsonCodec case class Bar(@JsonKey("my-int") i: Int, s: String)
Bar(13, "Qux").asJson
It's worth noting that if you don't want to use the experimental generic-extras module, the
completely unmagical forProductN
version isn't really that much of a burden:
import io.circe.Encoder, io.circe.syntax._
case class User(firstName: String, lastName: String)
case class Bar(i: Int, s: String)
implicit val encodeUser: Encoder[User] =
Encoder.forProduct2("first_name", "last_name")(u => (u.firstName, u.lastName))
implicit val encodeBar: Encoder[Bar] =
Encoder.forProduct2("my-int", "s")(b => (b.i, b.s))
User("Foo", "McBar").asJson
Bar(13, "Qux").asJson
While this version does involve a bit of boilerplate, it only requires circe-core, and may have slightly better runtime performance in some cases.