I am trying to create a Seq of methods that will operate on a Spark DataFrame. Currently I am explicitly creating this Seq at runtime:
val allFuncs: Seq[DataFrame => DataFrame] = Seq(func1, func2, func3)
def func1(df: DataFrame): DataFrame = {}
def func2(df: DataFrame): DataFrame = {}
def func3(df: DataFrame): DataFrame = {}
I added functionality that allows developers to add an annotation and I'm creating a Seq of MethodMirrors from it like so, but I'd like getMyFuncs
to return a Seq[(DataFrame => DataFrame)]
:
def getMyFuncs(): Seq[(DataFrame => DataFrame)] = {
// Gets anything with the @MyFunc annotation
val listOfAnnotations = typeOf[T].members.flatMap(f => f.annotations.find(_.tree.tpe =:= typeOf[MyFunc]).map((f, _))).toList
val rm = runtimeMirror(this.getClass.getClassLoader)
val instanceMirror = rm.reflect(this)
listOfAnnotations.map(annotation => instanceMirror.reflectMethod(annotation._1.asMethod)).toSeq
}
@MyFunc
def func1(df: DataFrame): DataFrame = {}
@MyFunc
def func2(df: DataFrame): DataFrame = {}
@MyFunc
def func3(df: DataFrame): DataFrame = {}
However, the Seq returned by getMyFuncs
is a Seq[reflect.runtime.universe.MethodMirror]
, not Seq[(DataFrame => DataFrame)]
. Which is expected, but not the output I need. Is there any way to convert the MethodMirrors into a Scala function?
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