Now that we can load some equity data, we need to load inflation data so that we're able to compute inflation-adjusted returns. It is very similar to the loading of equity data.

First, copy cpi_2017.tsv from https://github.com/PacktPublishing/Scala-Programming-Projects/blob/master/Chapter02/retirement-calculator/src/main/resources/cpi.tsv to src/test/resources. Then, create a new unit test called InflationDataSpec in the retcalc package:

package retcalc

import org.scalatest.{Matchers, WordSpec}

class InflationDataSpec extends WordSpec with Matchers {
  "InflationData.fromResource" should {
    "load CPI data from a tsv file" in {
      val data = InflationData.fromResource("cpi_2017.tsv")
      data should ===(Vector(
        InflationData("2016.09", 241.428),
        InflationData("2016.10", 241.729),
        InflationData("2016.11", 241.353),
        InflationData("2016.12", 241.432),
        InflationData("2017.01", 242.839),
        InflationData("2017.02", 243.603),
        InflationData("2017.03", 243.801),
        InflationData("2017.04", 244.524),
        InflationData("2017.05", 244.733),
        InflationData("2017.06", 244.955),
        InflationData("2017.07", 244.786),
        InflationData("2017.08", 245.519),
        InflationData("2017.09", 246.819)
      ))
    }
  }
}

Then, create the corresponding InflationData class and companion object:

package retcalc

import scala.io.Source

case class InflationData(monthId: String, value: Double)

object InflationData {
  def fromResource(resource: String): Vector[InflationData] =
    Source.fromResource(resource).getLines().drop(1).map { line =>
      val fields = line.split("	")
      InflationData(monthId = fields(0), value = fields(1).toDouble)
    }.toVector
}