DoobieHelpers.scala

object DoobieHelpers {

  /*
   * See: https://tpolecat.github.io/doobie-0.2.0/10-Custom-Mappings.html
   *
   * Some modern databases support a json column type that can store structured data as a JSON document, along with
   * various SQL extensions to allow querying and selecting arbitrary sub-structures. So an obvious thing we might
   * want to do is provide a mapping from Scala model objects to JSON columns, via some kind of JSON serialization
   * library.
   *
   * We can construct a Meta instance for the argonaut Json type by using the Meta.other constructor, which constructs
   * a direct object mapping via JDBC's .getObject and .setObject. In the case of PostgreSQL the JSON values are
   * marshalled via the PGObject type, which encapsulates an uninspiring (String, String) pair representing the schema
   * type and its string value.
   */

  implicit val JsonMeta: Meta[Json] =
    Meta.other[PGobject]("json").nxmap[Json](
      a => Parse.parse(a.getValue).leftMap[Json](sys.error).merge, // failure raises an exception
      a => new PGobject <| (_.setType("json")) <| (_.setValue(a.nospaces))
    )

  /*
   * Given this mapping to and from Json we can construct a further mapping to any type that has a CodecJson instance.
   * The nxmap constrains us to reference types and requires a TypeTag for diagnostics, so the full type constraint
   * is A >: Null : CodecJson: TypeTag. On failure we throw an exception; this indicates a logic or schema problem.
   */
  def codecMeta[A >: Null : DecodeJson : EncodeJson : TypeTag]: Meta[A] = {
    Meta[Json].nxmap[A](x => {
        x.as[A].result.fold(p => {
          sys.error(p._1)
        }, identity)
      },
      _.asJson
    )

  }

  /*
   * Tells Doobie how to work with Joda Time instants.
   */

//  implicit val JodaInstantMeta = codecMeta[Instant]

  implicit val DateTimeMeta: Meta[Instant] =
    Meta[java.sql.Timestamp].nxmap(
      ts => new Instant(ts.getTime),
      dt => new java.sql.Timestamp(dt.getMillis)
    )

}