用circe解析数组

Question

我有一个json，例如：

[
    [
        "Service ID",
        "VARCHAR",
        1,
        12
    ],
    [
        "Operation",
        "VARCHAR",
        2,
        12
    ],
    [
        "Start Date",
        "VARCHAR",
        3,
        12
    ],
    [
        "End Date",
        "VARCHAR",
        4,
        12
    ],
    [
        "Agent Position",
        "VARCHAR",
        5,
        12
    ],
    [
        "Customer ID",
        "VARCHAR",
        6,
        12
    ],
    [
        "Product",
        "VARCHAR",
        7,
        12
    ],
    [
        "Service Type",
        "VARCHAR",
        8,
        12
    ],
    [
        "Agent",
        "VARCHAR",
        9,
        12
    ]
]

我想在那里按摩/映射为一个案例类

{
"schema": [
    {
        "COLUMN_NAME":"Service ID",
        "DATA_TYPE":"VARCHAR",
        "ORDINAL_POSITION":1,
        "JDBC_DATA_TYPE12":12
    },
    {
        "COLUMN_NAME":"Operation",
        "DATA_TYPE":"VARCHAR",
        "ORDINAL_POSITION":2,
        "JDBC_DATA_TYPE12":12
    },
    {
        "COLUMN_NAME":"Start Date",
        "DATA_TYPE":"VARCHAR",
        "ORDINAL_POSITION":3,
        "JDBC_DATA_TYPE12":12
    },
    {
        "COLUMN_NAME":"End Date",
        "DATA_TYPE":"VARCHAR",
        "ORDINAL_POSITION":4,
        "JDBC_DATA_TYPE12":12
    },
    {
        "COLUMN_NAME":"Agent Position",
        "DATA_TYPE":"VARCHAR",
        "ORDINAL_POSITION":5,
        "JDBC_DATA_TYPE12":12
    },
    {
        "COLUMN_NAME":"Customer ID",
        "DATA_TYPE":"VARCHAR",
        "ORDINAL_POSITION":6,
        "JDBC_DATA_TYPE12":12
    },
    {
        "COLUMN_NAME":"Product",
        "DATA_TYPE":"VARCHAR",
        "ORDINAL_POSITION":7,
        "JDBC_DATA_TYPE12":12
    },
    {
        "COLUMN_NAME":"Service Type",
        "DATA_TYPE":"VARCHAR",
        "ORDINAL_POSITION":8,
        "JDBC_DATA_TYPE12":12
    },
    {
        "COLUMN_NAME":"Agent",
        "DATA_TYPE":"VARCHAR",
        "ORDINAL_POSITION":9,
        "JDBC_DATA_TYPE12":12
    }
    ]
}

我试着遵循：Decoding structured JSON arrays with circe in Scala作为一种建议，但是有些方法已经不存在了，比如deleteGoRight等等。

我尝试过这样的尝试：

implicit val decoder: Decoder[Schema] = { (hCursor: HCursor) =>
    for {
      colName <- hCursor.as[String]
      colNameC = hCursor.delete
      dtype <- colNameC.right.as[String]
      dtypeC = colNameC.delete
      pos <- dtypeC.right.as[Double]
      posC = dtypeC.delete
      jtype <- posC.right.as[Double]
    } yield Schema(colName, dtype, pos, jtype) }

  parser.decode[List[Schema]]("""["Service Type","VARCHAR",8,12]""") match {
    case Right(applicants) => println(applicants)
    case Left(ex) => println(s"Oops something is wrong with decoding value ${ex}")
  }

但它无法解码，这些错误很难解释。

Answer 1

可以在downN上使用HCursor方法访问列表中的特定元素。

import io.circe.parser.decode
import io.circe.{Decoder, HCursor, _}

object Main extends App {

  val payload =
    """[
      |    [
      |        "Service ID",
      |        "VARCHAR",
      |        1,
      |        12
      |    ],
      |    [
      |        "Operation",
      |        "VARCHAR",
      |        2,
      |        12
      |    ]
      |]""".stripMargin


  val schemas: Either[Error, List[Schema]] = decode[List[Schema]](payload)
  println(schemas)
}

case class Schema(name: String, dataType: String, position: Int, jdbcType: Int)

object Schema {

  implicit val schemaDecoder: Decoder[Schema] = (c: HCursor) => for {
    name <- c.downN(0).as[String]
    dataType <- c.downN(1).as[String]
    position <- c.downN(2).as[Int]
    jdbcType <- c.downN(3).as[Int]
  } yield Schema(name, dataType, position, jdbcType)
}