@inline def apply[M[_]: CollectionType, T: ClassTag: FlatReader]()

in core/src/main/scala/com/spotify/featran/FlatExtractor.scala [108:135]

• 14 lines of code
• 1 McCabe index (conditional complexity)

  @inline def apply[M[_]: CollectionType, T: ClassTag: FlatReader](
    settings: M[String]
  ): FlatExtractor[M, T] = new FlatExtractor[M, T](settings)

  /**
   * Another useful operation is to use the Spec and Information we have to map from the Scala
   * Object to read the data directly from the intermediate format for parsing
   *
   * @param spec
   *   Current FeatureSpec
   * @tparam T
   *   The intermediate format where the data is stored
   * @tparam X
   *   The Input Scala Object
   * @return
   *   FeatureSpec for the intermediate format
   */
  @nowarn(
    "msg=evidence parameter evidence.* of type scala.reflect.ClassTag\\[.\\] .* is never used"
  )
  def flatSpec[T: ClassTag: FlatReader, X: ClassTag](spec: FeatureSpec[X]): FeatureSpec[T] = {
    val features = spec.features.map { feature =>
      val t = feature.transformer.asInstanceOf[Transformer[Any, _, _]]
      new Feature(feature.transformer.flatRead, feature.default, t)
        .asInstanceOf[Feature[T, _, _, _]]
    }
    new FeatureSpec[T](features, spec.crossings)
  }