Working with JSON

Json values are supported through codecs which encode/decode values to json strings. However, third-party libraries are needed for actual json parsing/printing. Currently, Circe is supported. To use, add the following dependency to your project:

"com.softwaremill.tapir" %% "tapir-json-circe" % "0.7.4"

Next, import the package (or extend the TapirJsonCirce trait, see MyTapir):

import tapir.json.circe._

This will bring into scope Codecs which, given an in-scope circe Encoder/Decoder and a SchemaFor, will create a codec using the json media type. Circe includes a couple of approaches to generating encoders/decoders (manual, semi-auto and auto), so you may choose whatever suits you.

For example, to automatically generate a JSON codec for a case class:

import tapir._
import tapir.json.circe._
import io.circe.generic.auto._

case class Book(author: String, title: String, year: Int)

val bookInput: EndpointIO[Book] = jsonBody[Book]

To add support for other JSON libraries, see the sources for the Circe codec (which is just a couple of lines of code).

Schemas

To create a json codec automatically, not only a circe Encoder/Decoder is needed, but also an implicit SchemaFor[T] value, which provides a mapping between a type T and its schema. A schema-for value contains a single schema: Schema field.

For custom types, schemas are derived automatically using Magnolia, given that schemas are defined for all of the case class’s fields. It is possible to configure the automatic derivation to use snake-case, kebab-case or a custom field naming policy, by providing an implicit tapir.generic.Configuration value:

implicit val customConfiguration: Configuration =
  Configuration.default.withSnakeCaseMemberNames

Alternatively, SchemaFor values can be defined by hand, either for whole case classes, or only for some of its fields. For example, here we state that the schema for MyCustomType is a String:

implicit val schemaForMyCustomType: SchemaFor[MyCustomType] = SchemaFor(Schema.SString)