scala的REPL shell的调用

最近突然对spark的spark-shell发生了兴趣
它是如何启动scala的REPL的，并且在此前写入了常用的环境变量的呢？
通过查看spark的源码，找到了SparkILoop.scala

import scala.tools.nsc.interpreter.{JPrintWriter, ILoop}

/** * A Spark-specific interactive shell. */
class SparkILoop(in0: Option[BufferedReader], out: JPrintWriter)
    extends ILoop(in0, out) {
  def this(in0: BufferedReader, out: JPrintWriter) = this(Some(in0), out)
  def this() = this(None, new JPrintWriter(Console.out, true))

  def initializeSpark() {
    intp.beQuietDuring {
      processLine(""" @transient val sc = { val _sc = org.apache.spark.repl.Main.createSparkContext() println("Spark context available as sc.") _sc } """)
      processLine(""" @transient val sqlContext = { val _sqlContext = org.apache.spark.repl.Main.createSQLContext() println("SQL context available as sqlContext.") _sqlContext } """)
      processLine("import org.apache.spark.SparkContext._")
      processLine("import sqlContext.implicits._")
      processLine("import sqlContext.sql")
      processLine("import org.apache.spark.sql.functions._")
    }
  }
  ...
}

可以看出SparkILoop继承自scala.tools.nsc.interpreter.ILoop
紧接着着看了ILoop的api doc
终于找到了启动ILoop的方法：

import scala.tools.nsc.interpreter.ILoop
import scala.tools.nsc.Settings

val loop = new ILoop
loop.process(new Settings)