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# Code Interpreter
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The Code Interpreter provides the core functionality for compiling, executing, and managing Scala code within the REPL environment. It handles code compilation, execution, variable management, and introspection capabilities.
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## Capabilities
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### SparkIMain Class
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The core interpreter class that handles all aspects of code interpretation including compilation, execution, and state management.
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```scala { .api }
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/**
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 * Core interpreter for Spark REPL handling code compilation and execution
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 * @param initialSettings Scala compiler settings
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 * @param out Output writer for results and errors
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 * @param propagateExceptions Whether to propagate exceptions to caller
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 */
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@DeveloperApi
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class SparkIMain(
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  initialSettings: Settings,
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  val out: JPrintWriter,
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  propagateExceptions: Boolean = false
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) extends SparkImports with Logging { imain =>
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  /**
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   * Constructor with default settings
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   */
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  def this() = this(new Settings())
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  /**
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   * Constructor with custom settings
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   */
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  def this(settings: Settings) = this(settings, new NewLinePrintWriter(new ConsoleWriter, true))
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}
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```
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**Core Properties:**
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```scala { .api }
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/**
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 * Output directory for compiled classes
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 */
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@DeveloperApi
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lazy val getClassOutputDirectory: File
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/**
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 * The underlying Scala compiler instance
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 */
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@DeveloperApi  
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lazy val global: Global
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/**
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 * Code wrapper used for execution context
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 */
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@DeveloperApi
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def executionWrapper: String
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/**
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 * Whether compilation errors were reported
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 */
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@DeveloperApi
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def isReportingErrors: Boolean
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```
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### Initialization
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Methods for initializing the interpreter and preparing it for code execution.
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```scala { .api }
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/**
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 * Initialize the interpreter synchronously
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 * Must be called before using interpretation methods
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 */
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@DeveloperApi
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def initializeSynchronous(): Unit
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```
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**Usage Example:**
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```scala
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import org.apache.spark.repl.SparkIMain
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val interpreter = new SparkIMain()
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interpreter.initializeSynchronous()
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// Now ready for code interpretation
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```
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### Code Execution
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Core methods for interpreting and compiling Scala code.
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```scala { .api }
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/**
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 * Interpret a line of Scala code
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 * @param line Scala code to interpret
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 * @return Result indicating success, error, or incomplete input
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 */
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@DeveloperApi
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def interpret(line: String): IR.Result
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/**
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 * Interpret code with synthetic naming (internal use)
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 * @param line Scala code to interpret
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 * @return Result indicating success, error, or incomplete input
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 */
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@DeveloperApi
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def interpretSynthetic(line: String): IR.Result
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/**
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 * Compile source files
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 * @param sources Variable number of SourceFile instances
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 * @return Boolean indicating compilation success
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 */
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@DeveloperApi
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def compileSources(sources: SourceFile*): Boolean
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/**
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 * Compile a string of Scala code
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 * @param code Scala code to compile
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 * @return Boolean indicating compilation success
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 */
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@DeveloperApi
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def compileString(code: String): Boolean
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```
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**Usage Examples:**
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```scala
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import org.apache.spark.repl.SparkIMain
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import scala.tools.nsc.interpreter.{Results => IR}
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val interpreter = new SparkIMain()
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interpreter.initializeSynchronous()
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// Interpret simple expressions
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val result1 = interpreter.interpret("val x = 42")
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result1 match {
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  case IR.Success => println("Successfully defined x")
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  case IR.Error => println("Error in code")
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  case IR.Incomplete => println("Code is incomplete")
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}
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// Interpret complex code
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val result2 = interpreter.interpret("""
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  def fibonacci(n: Int): Int = {
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    if (n <= 1) n else fibonacci(n-1) + fibonacci(n-2)
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  }
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""")
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// Compile string directly
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val compiled = interpreter.compileString("case class Person(name: String, age: Int)")
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```
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### Code Analysis
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Methods for parsing and analyzing code structure without execution.
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```scala { .api }
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/**
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 * Parse Scala code into Abstract Syntax Tree
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 * @param line Scala code to parse
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 * @return Optional list of Tree nodes representing parsed code
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 */
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@DeveloperApi
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def parse(line: String): Option[List[Tree]]
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/**
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 * Get symbol information for a line of code
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 * @param code Scala code to analyze
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 * @return Symbol representing the code
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 */
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@DeveloperApi
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def symbolOfLine(code: String): Symbol
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/**
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 * Get type information for an expression
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 * @param expr Scala expression to analyze
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 * @param silent Whether to suppress error messages
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 * @return Type information for the expression
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 */
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@DeveloperApi
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def typeOfExpression(expr: String, silent: Boolean = true): Type
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```
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**Usage Examples:**
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```scala
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val interpreter = new SparkIMain()
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interpreter.initializeSynchronous()
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// Parse code structure
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val parsed = interpreter.parse("val x: Int = 42")
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parsed.foreach(trees => println(s"Parsed ${trees.length} tree nodes"))
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// Get type information
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val exprType = interpreter.typeOfExpression("List(1, 2, 3)")
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println(s"Expression type: $exprType")
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```
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### Variable Management
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Methods for binding variables and managing the interpreter's variable namespace.
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```scala { .api }
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/**
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 * Bind a variable to the interpreter namespace
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 * @param name Variable name
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 * @param boundType Type of the variable as string
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 * @param value Value to bind
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 * @param modifiers List of modifiers (e.g., "lazy", "implicit")
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 * @return Result indicating binding success
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 */
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@DeveloperApi
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def bind(name: String, boundType: String, value: Any, modifiers: List[String] = Nil): IR.Result
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/**
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 * Direct variable binding without wrapper
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 * @param name Variable name
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 * @param boundType Type of the variable as string  
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 * @param value Value to bind
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 * @return Result indicating binding success
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 */
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@DeveloperApi
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def directBind(name: String, boundType: String, value: Any): IR.Result
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/**
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 * Rebind an existing variable with new value
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 * @param p NamedParam containing name and value
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 * @return Result indicating rebinding success
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 */
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@DeveloperApi
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def rebind(p: NamedParam): IR.Result
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/**
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 * Add import statements to the interpreter
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 * @param ids Variable number of import strings
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 * @return Result indicating import success
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 */
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@DeveloperApi
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def addImports(ids: String*): IR.Result
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```
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**Usage Examples:**
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```scala
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val interpreter = new SparkIMain()
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interpreter.initializeSynchronous()
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// Bind variables
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val bindResult = interpreter.bind("myList", "List[Int]", List(1, 2, 3, 4, 5))
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val directResult = interpreter.directBind("pi", "Double", 3.14159)
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// Add imports
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val importResult = interpreter.addImports("scala.util.Random", "java.time.LocalDateTime")
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// Check results
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if (bindResult == IR.Success) {
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  println("Successfully bound myList")
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}
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```
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### State Management
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Methods for managing the interpreter's state and lifecycle.
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```scala { .api }
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/**
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 * Reset the interpreter state, clearing all definitions
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 */
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@DeveloperApi
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def reset(): Unit
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/**
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 * Close the interpreter and clean up resources
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 */
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@DeveloperApi
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def close(): Unit
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```
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### Introspection
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Methods for inspecting the current state of defined names, symbols, and variables.
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```scala { .api }
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/**
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 * Get all defined names in the interpreter
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 * @return List of all defined names
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@DeveloperApi
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def allDefinedNames: List[Name]
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/**
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 * Get all defined term names
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 * @return List of defined term names
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@DeveloperApi
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def definedTerms: List[TermName]
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/**
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 * Get all defined type names
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 * @return List of defined type names
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@DeveloperApi
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def definedTypes: List[TypeName]
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/**
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 * Get all defined symbols as a set
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 * @return Set of defined symbols
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@DeveloperApi
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def definedSymbols: Set[Symbol]
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/**
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 * Get all defined symbols as a list
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 * @return List of defined symbols
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 */
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@DeveloperApi
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def definedSymbolList: List[Symbol]
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/**
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 * Get user-defined term names (excluding res0, res1, etc.)
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 * @return List of user-defined term names
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@DeveloperApi
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def namedDefinedTerms: List[TermName]
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/**
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 * Get the name of the most recent result variable
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 * @return Most recent result variable name
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@DeveloperApi
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def mostRecentVar: String
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/**
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 * Get recent compiler warnings
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 * @return List of warning tuples (position, message)
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 */
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@DeveloperApi
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def lastWarnings: List[(Position, String)]
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```
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**Usage Examples:**
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```scala
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val interpreter = new SparkIMain()
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interpreter.initializeSynchronous()
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// Define some variables
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interpreter.interpret("val x = 42")
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interpreter.interpret("def square(n: Int) = n * n")
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interpreter.interpret("case class Point(x: Int, y: Int)")
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// Inspect defined names
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val allNames = interpreter.allDefinedNames
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val terms = interpreter.definedTerms
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val types = interpreter.definedTypes
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val userTerms = interpreter.namedDefinedTerms
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println(s"All names: ${allNames.mkString(", ")}")
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println(s"Terms: ${terms.mkString(", ")}")
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println(s"Types: ${types.mkString(", ")}")
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println(s"User terms: ${userTerms.mkString(", ")}")
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// Get most recent result
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val recentVar = interpreter.mostRecentVar
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println(s"Most recent variable: $recentVar")
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```
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### Value Access
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Methods for accessing values, types, and runtime information of defined terms.
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```scala { .api }
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/**
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 * Get the runtime value of a term
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 * @param id Term identifier
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 * @return Optional runtime value
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@DeveloperApi
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def valueOfTerm(id: String): Option[AnyRef]
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/**
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 * Get the runtime class of a term
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 * @param id Term identifier
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 * @return Optional Java class
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@DeveloperApi
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def classOfTerm(id: String): Option[JClass]
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/**
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 * Get the compile-time type of a term
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 * @param id Term identifier
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 * @return Type information
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@DeveloperApi
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def typeOfTerm(id: String): Type
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/**
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 * Get the symbol of a term
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 * @param id Term identifier
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 * @return Symbol information
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@DeveloperApi
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def symbolOfTerm(id: String): Symbol
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/**
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 * Get both runtime class and type information
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 * @param id Term identifier
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 * @return Optional tuple of (Java class, Type)
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@DeveloperApi
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def runtimeClassAndTypeOfTerm(id: String): Option[(JClass, Type)]
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/**
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 * Get the runtime type of a term
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 * @param id Term identifier
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 * @return Runtime type information
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@DeveloperApi
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def runtimeTypeOfTerm(id: String): Type
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```
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**Usage Examples:**
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```scala
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val interpreter = new SparkIMain()
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interpreter.initializeSynchronous()
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// Define a variable
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interpreter.interpret("val numbers = List(1, 2, 3, 4, 5)")
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// Access its value and type information
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val value = interpreter.valueOfTerm("numbers")
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val clazz = interpreter.classOfTerm("numbers")
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val tpe = interpreter.typeOfTerm("numbers")
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value.foreach(v => println(s"Value: $v"))
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clazz.foreach(c => println(s"Class: ${c.getName}"))
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println(s"Type: $tpe")
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// Check runtime information
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val runtimeInfo = interpreter.runtimeClassAndTypeOfTerm("numbers")
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runtimeInfo.foreach { case (runtimeClass, runtimeType) =>
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  println(s"Runtime class: ${runtimeClass.getName}")
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  println(s"Runtime type: $runtimeType")
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}
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```
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### Code Generation
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Methods for working with generated names and code paths.
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```scala { .api }
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/**
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 * Get the real generated name for a REPL-defined name
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 * @param simpleName Simple name used in REPL
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 * @return Optional real generated name
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 */
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@DeveloperApi
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def generatedName(simpleName: String): Option[String]
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/**
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 * Get the full path to access a name
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 * @param name Name to get path for
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 * @return Full access path
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 */
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@DeveloperApi
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def pathToName(name: Name): String
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```
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### Execution Control
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Methods for controlling output and execution behavior.
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```scala { .api }
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/**
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 * Execute code block while suppressing normal output
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 * @param body Code block to execute
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 * @return Result of code block execution
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 */
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@DeveloperApi
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def beQuietDuring[T](body: => T): T
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/**
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 * Execute code block while masking all output
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 * @param operation Code block to execute  
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 * @return Result of code block execution
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 */
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@DeveloperApi
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def beSilentDuring[T](operation: => T): T
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/**
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 * Set custom execution wrapper code
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 * @param code Wrapper code string
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 */
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@DeveloperApi
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def setExecutionWrapper(code: String): Unit
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/**
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 * Clear the execution wrapper
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 */
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@DeveloperApi
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def clearExecutionWrapper(): Unit
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```
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### Classpath Management
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Methods for managing the interpreter's classpath.
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```scala { .api }
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/**
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 * Add URLs to the interpreter's classpath
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 * @param urls Variable number of URL instances
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 */
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@DeveloperApi
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def addUrlsToClassPath(urls: URL*): Unit
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```
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**Usage Example:**
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```scala
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import java.net.URL
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val interpreter = new SparkIMain()
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interpreter.initializeSynchronous()
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// Add JARs to classpath
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val jarUrl = new URL("file:///path/to/library.jar")
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interpreter.addUrlsToClassPath(jarUrl)
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// Now can use classes from the JAR
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interpreter.interpret("import com.example.SomeClass")
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```
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## Integration Patterns
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### Complete Interpreter Usage
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```scala
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import org.apache.spark.repl.SparkIMain
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import scala.tools.nsc.interpreter.{Results => IR}
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import java.net.URL
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// Create and initialize interpreter
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val interpreter = new SparkIMain()
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interpreter.initializeSynchronous()
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// Add external dependencies
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val externalJar = new URL("file:///path/to/spark-sql.jar")  
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interpreter.addUrlsToClassPath(externalJar)
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// Execute code
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val result = interpreter.interpret("""
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  import org.apache.spark.sql.SparkSession
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  val spark = SparkSession.builder()
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    .appName("REPL Session")
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    .master("local[*]")
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    .getOrCreate()
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""")
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if (result == IR.Success) {
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  // Access the created SparkSession
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  val sparkSession = interpreter.valueOfTerm("spark")
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  println(s"SparkSession created: $sparkSession")
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  // Get information about defined variables
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  val definedTerms = interpreter.namedDefinedTerms
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  println(s"User-defined terms: ${definedTerms.mkString(", ")}")
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}
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// Clean up
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interpreter.close()
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```