This started as a joke inspired by the programming language speed comparison meme, but let’s see if we can actually create a function that generates functions with arbitrary nested loops in R!

Understanding R’s Homoiconic Nature and AST Manipulation

Before we dive into the implementation, it’s essential to understand what makes this possible. R is a homoiconic language, meaning that code and data share the same representation. In R, functions are first-class objects that can be manipulated programmatically, and expressions are represented as language objects that can be constructed and modified at runtime.

R’s language objects can be constructed using base functions such as call() for creating function calls, quote() for capturing expressions without evaluation, and substitute() for template-based expression manipulation. This is exactly what we’re exploiting to create arbitrary levels of nested loops.

The Challenge

Method 1: Pure Functional AST Composition (No Loops!)

create_nested_loops_v1 <- function(n, k, action = quote(counter <- counter + 1)) {
  if (n <= 0) stop("Number of loops must be positive")
  
  # Pure functional composition using Reduce - no explicit loops!
  # Map over indices n:1 and compose AST elements
  body_expr <- Reduce(
    f = function(body, i) call("for", as.name(paste0("i", i)), call(":", 1, k), body),
    x = n:1, 
    init = action
  )
  
  # Compose complete function using call() for cleaner AST
  complete_body <- call("{", 
                       quote(counter <- 0),
                       body_expr,
                       quote(return(counter)))
  
  # Function factory pattern
  f <- function() {}
  body(f) <- complete_body
  f
}

# Test with 3 nested loops of 5 iterations each
nested_3_5 <- create_nested_loops_v1(3, 5)
cat("Generated function body:\n")
#> Generated function body:
print(nested_3_5)
#> function () 
#> {
#>     counter <- 0
#>     for (i1 in 1:5) for (i2 in 1:5) for (i3 in 1:5) counter <- counter + 
#>         1
#>     return(counter)
#> }
#> <environment: 0x5d8f12221a58>
cat("\n")
result1 <- nested_3_5()
cat("3 nested loops of 5 iterations:", result1, "total iterations\n")
#> 3 nested loops of 5 iterations: 125 total iterations
cat("Expected:", 5^3, "\n")
#> Expected: 125

Method 2: Ultra-Concise Language Object Composition

create_nested_loops_v2 <- function(n, k, action = quote(counter <- counter + 1)) {
  if (n <= 0) stop("Number of loops must be positive")
  
  # Ultra-concise: single Reduce call with lambda syntax
  f <- function() {}
  body(f) <- call("{", 
         quote(counter <- 0),
         Reduce(function(body, i) call("for", as.name(paste0("i", i)), call(":", 1, k), body), 
                n:1, action),
         quote(return(counter)))
  f
}

# Test the base R version
nested_4_3 <- create_nested_loops_v2(4, 3)
cat("Generated function body (call objects):\n")
#> Generated function body (call objects):
print(nested_4_3)
#> function () 
#> {
#>     counter <- 0
#>     for (i1 in 1:3) for (i2 in 1:3) for (i3 in 1:3) for (i4 in 1:3) counter <- counter + 
#>         1
#>     return(counter)
#> }
#> <environment: 0x5d8f10c4fe00>
cat("\n")
result2 <- nested_4_3()
cat("4 nested loops of 3 iterations:", result2, "total iterations\n")
#> 4 nested loops of 3 iterations: 81 total iterations
cat("Expected:", 3^4, "\n")
#> Expected: 81

Method 3: Codetools-Inspired AST Walking Pattern

create_nested_loops_v3 <- function(n, k, action = quote(counter <- counter + 1)) {
  if (n <= 0) stop("Number of loops must be positive")
  
  # Inspired by codetools' makeCodeWalker pattern
  # Create a "walker" that builds nested structures
  makeLoopBuilder <- function(depth, max_depth, body) {
    force(depth); force(max_depth); force(body)  # Avoid deferred evaluation
    if (depth > max_depth) return(body)
    
    # Use Tailcall for stack efficiency like in codetools
    Tailcall(makeLoopBuilder, 
             depth + 1, 
             max_depth, 
             call("for", as.name(paste0("i", depth)), call(":", 1, k), body))
  }
  
  # Build using tail recursion
  body_expr <- makeLoopBuilder(1, n, action)
  f <- function() {}
  body(f) <- call("{", quote(counter <- 0), body_expr, quote(return(counter)))
  f
}

# Test recursive approach
nested_2_10 <- create_nested_loops_v3(2, 10)
cat("Generated function (string method):\n")
#> Generated function (string method):
print(nested_2_10)
#> function () 
#> {
#>     counter <- 0
#>     for (i2 in 1:10) for (i1 in 1:10) counter <- counter + 1
#>     return(counter)
#> }
#> <environment: 0x5d8f121be620>
cat("\n")
result3 <- nested_2_10()
cat("2 nested loops of 10 iterations:", result3, "total iterations\n")
#> 2 nested loops of 10 iterations: 100 total iterations
cat("Expected:", 10^2, "\n")
#> Expected: 100

Method 4: Functional Composition with Map-Reduce Pattern

create_nested_loops_v4 <- function(n, k, action = quote(counter <- counter + 1)) {
  if (n <= 0) stop("Number of loops must be positive")
  
  # Map-Reduce pattern: Map indices to loop constructors, then Reduce to compose
  loop_constructors <- Map(
    function(i) function(body) call("for", as.name(paste0("i", i)), call(":", 1, k), body),
    n:1
  )
  
  # Reduce all constructors into final expression
  body_expr <- Reduce(function(acc, f) f(acc), loop_constructors, action)
  
  f <- function() {}
  body(f) <- call("{", quote(counter <- 0), body_expr, quote(return(counter)))
  f
}

# Test the map-reduce version
nested_mapreduce <- create_nested_loops_v4(3, 4)
cat("Generated function body (Map-Reduce method):\n")
#> Generated function body (Map-Reduce method):
print(nested_mapreduce)
#> function () 
#> {
#>     counter <- 0
#>     for (i1 in 1:4) for (i2 in 1:4) for (i3 in 1:4) counter <- counter + 
#>         1
#>     return(counter)
#> }
#> <environment: 0x5d8f0fb8d658>
cat("\n")
result_mapreduce <- nested_mapreduce()
cat("Map-Reduce pattern - 3 nested loops of 4 iterations:", result_mapreduce, "total iterations\n")
#> Map-Reduce pattern - 3 nested loops of 4 iterations: 64 total iterations
cat("Expected:", 4^3, "\n")
#> Expected: 64

Method 5: Point-Free Functional Style (Ultimate Conciseness)

create_nested_loops_v5 <- function(n, k, action = quote(counter <- counter + 1)) {
  if (n <= 0) stop("Number of loops must be positive")
  
  # Point-free style: compose functions without explicit intermediate variables
  # Using functional composition patterns in base R
  f <- function() {}
  indices <- n:1
  body_expr <- Reduce(function(body, i) call("for", as.name(paste0("i", i)), call(":", 1, k), body), 
                     indices, action)
  body(f) <- call("{", quote(counter <- 0), body_expr, quote(return(counter)))
  f
}

# Even more concise one-liner version
create_loops_oneliner <- function(n, k, action = quote(counter <- counter + 1)) {
  f <- function() {}
  body(f) <- call("{", quote(counter <- 0),
    Reduce(function(b, i) call("for", as.name(paste0("i", i)), call(":", 1, k), b), n:1, action),
    quote(return(counter)))
  f
}

# Test point-free version
nested_pointfree <- create_nested_loops_v5(2, 5)
cat("Generated function body (Point-free method):\n")
#> Generated function body (Point-free method):
print(nested_pointfree)
#> function () 
#> {
#>     counter <- 0
#>     for (i1 in 1:5) for (i2 in 1:5) counter <- counter + 1
#>     return(counter)
#> }
#> <environment: 0x5d8f120ed988>
cat("\n")
result_pointfree <- nested_pointfree()
cat("Point-free style - 2 nested loops of 5 iterations:", result_pointfree, "total iterations\n")
#> Point-free style - 2 nested loops of 5 iterations: 25 total iterations
cat("Expected:", 5^2, "\n")
#> Expected: 25

# Test the one-liner
cat("\n=== Testing the one-liner version ===\n")
#> 
#> === Testing the one-liner version ===
oneliner_func <- create_loops_oneliner(4, 2)
oneliner_result <- oneliner_func()
cat("One-liner - 4 nested loops of 2 iterations:", oneliner_result, "total iterations\n")
#> One-liner - 4 nested loops of 2 iterations: 16 total iterations
cat("Expected:", 2^4, "\n")
#> Expected: 16

Method 6: Codetools-Inspired Walker Pattern (Zero Loops!)

# Inspired by codetools' makeCodeWalker - build AST without any loops!
create_walker_loops <- function(n, k, action = quote(counter <- counter + 1)) {
  if (n <= 0) stop("Number of loops must be positive")
  
  # Create a "walker" pattern like in codetools
  makeLoopWalker <- function(indices) {
    # Use Map to transform each index into a loop constructor function
    constructors <- Map(function(i) function(body) call("for", as.name(paste0("i", i)), call(":", 1, k), body), indices)
    
    # Compose all constructors using functional composition
    function(init_body) Reduce(function(acc, f) f(acc), constructors, init_body)
  }
  
  # Apply the walker pattern
  walker <- makeLoopWalker(n:1)
  body_expr <- walker(action)
  
  f <- function() {}
  body(f) <- call("{", quote(counter <- 0), body_expr, quote(return(counter)))
  f
}

# Test walker pattern
cat("=== Testing codetools-inspired walker pattern ===\n")
#> === Testing codetools-inspired walker pattern ===
nested_walker <- create_walker_loops(5, 2)
cat("Generated function body (Walker pattern):\n")
#> Generated function body (Walker pattern):
print(nested_walker)
#> function () 
#> {
#>     counter <- 0
#>     for (i1 in 1:2) for (i2 in 1:2) for (i3 in 1:2) for (i4 in 1:2) for (i5 in 1:2) counter <- counter + 
#>         1
#>     return(counter)
#> }
#> <environment: 0x5d8f13b21d30>
cat("\n")
result_walker <- nested_walker()
cat("Walker pattern - 5 nested loops of 2 iterations:", result_walker, "total iterations\n")
#> Walker pattern - 5 nested loops of 2 iterations: 32 total iterations
cat("Expected:", 2^5, "\n")
#> Expected: 32

# Show the elegance - create 10 nested loops with zero explicit loops in our code!
cat("\n=== Demonstrating zero-loop creation of 10 nested loops ===\n")
#> 
#> === Demonstrating zero-loop creation of 10 nested loops ===
ten_loops <- create_walker_loops(10, 2)
ten_result <- ten_loops()
cat("Created 10 nested loops without using ANY loops in our generator code!\n")
#> Created 10 nested loops without using ANY loops in our generator code!
cat("Result:", ten_result, "iterations\n")
#> Result: 1024 iterations
cat("Expected:", 2^10, "\n")
#> Expected: 1024

Performance Comparison: Functional vs Traditional Approaches

# Traditional approach (for comparison)
static_3_loops <- function(k) {
  counter <- 0
  for (i1 in 1:k) {
    for (i2 in 1:k) {
      for (i3 in 1:k) {
        counter <- counter + 1
      }
    }
  }
  return(counter)
}

# Create all our functional variants
k <- 50
dynamic_v1 <- create_nested_loops_v1(3, k)
dynamic_v2 <- create_nested_loops_v2(3, k)
dynamic_v3 <- create_nested_loops_v3(3, k)
dynamic_v4 <- create_nested_loops_v4(3, k)
dynamic_v5 <- create_nested_loops_v5(3, k)
dynamic_v6 <- create_walker_loops(3, k)
dynamic_oneliner <- create_loops_oneliner(3, k)

# Performance comparison
if (requireNamespace("microbenchmark", quietly = TRUE)) {
  library(microbenchmark)
  
  benchmark_results <- microbenchmark(
    static = static_3_loops(k),
    functional_v1 = dynamic_v1(),
    ultra_concise_v2 = dynamic_v2(),
    tailcall_v3 = dynamic_v3(),
    mapreduce_v4 = dynamic_v4(),
    pointfree_v5 = dynamic_v5(),
    walker_v6 = dynamic_v6(),
    oneliner = dynamic_oneliner(),
    times = 100
  )
  
  print(benchmark_results)
  
  cat("\n=== Performance Analysis ===\n")
  cat("All functional approaches avoid explicit loops in the generator code!\n")
  cat("The point-free and one-liner versions are particularly elegant.\n")
  
} else {
  # Simple timing if microbenchmark not available
  cat("=== Simple Timing Comparison ===\n")
  
  timing_test <- function(name, func, iterations = 100) {
    start_time <- Sys.time()
    for(i in 1:iterations) func()
    end_time <- Sys.time()
    time_diff <- as.numeric(end_time - start_time, units = "secs")
    cat(sprintf("%-20s: %.4f seconds\n", name, time_diff))
    time_diff
  }
  
  timing_test("Static (traditional)", function() static_3_loops(k))
  timing_test("Functional v1", dynamic_v1)
  timing_test("Ultra-concise v2", dynamic_v2)
  timing_test("Tailcall v3", dynamic_v3)
  timing_test("Map-Reduce v4", dynamic_v4)
  timing_test("Point-free v5", dynamic_v5)
  timing_test("Walker v6", dynamic_v6)
  timing_test("One-liner", dynamic_oneliner)
}
#> Unit: milliseconds
#>              expr       min        lq      mean    median        uq       max
#>            static  3.698305  4.267651  5.011830  4.868740  5.330950  17.76706
#>     functional_v1  3.730084  4.285182  5.370850  4.892242  5.559541  32.06804
#>  ultra_concise_v2  3.752712  4.140611  5.107915  4.758671  5.330671  34.69009
#>       tailcall_v3  3.614775  4.266394  5.227520  4.725810  5.473845  29.84136
#>      mapreduce_v4 26.077337 29.195854 33.521531 31.800027 34.784030 116.71344
#>      pointfree_v5 25.775204 29.498268 32.715182 32.107573 34.919627  52.74099
#>         walker_v6  3.616871  4.195576  5.488486  4.715788  5.201744  65.56944
#>          oneliner  3.609468  4.306971  5.288202  4.824461  5.387277  38.83797
#>  neval
#>    100
#>    100
#>    100
#>    100
#>    100
#>    100
#>    100
#>    100
#> 
#> === Performance Analysis ===
#> All functional approaches avoid explicit loops in the generator code!
#> The point-free and one-liner versions are particularly elegant.

cat("\n=== Code Conciseness Analysis ===\n")
#> 
#> === Code Conciseness Analysis ===
cat("Method 2 (Ultra-concise): ~4 lines of actual logic\n")
#> Method 2 (Ultra-concise): ~4 lines of actual logic
cat("One-liner version: Entire function generator in 1 expression!\n")
#> One-liner version: Entire function generator in 1 expression!
cat("Walker pattern: Zero explicit loops, maximum functional composition\n")
#> Walker pattern: Zero explicit loops, maximum functional composition

Advanced: Matrix Builder with Zero-Loop Construction

# Create a matrix builder using pure functional composition
create_matrix_builder <- function(rows, cols) {
  # Action: result[i1, i2] <- i1 * i2 (no loops in construction!)
  action <- call("<-", 
                call("[", quote(result), quote(i1), quote(i2)),
                call("*", quote(i1), quote(i2)))
  
  # Build nested loops using pure functional composition
  specs <- list(list(var = "i1", max = rows), list(var = "i2", max = cols))
  body_expr <- Reduce(
    function(body, spec) call("for", as.name(spec$var), call(":", 1, spec$max), body),
    rev(specs),
    action
  )
  
  # Complete function using functional pipeline
  f <- function() {}
  body(f) <- call("{",
         call("<-", quote(result), call("matrix", 0, nrow = rows, ncol = cols)),
         body_expr,
         quote(return(result)))
  f
}

# Test matrix builder (created without any explicit loops!)
matrix_builder <- create_matrix_builder(4, 5)
cat("Generated matrix builder function body:\n")
#> Generated matrix builder function body:
print(matrix_builder)
#> function () 
#> {
#>     result <- matrix(0, nrow = 4, ncol = 5)
#>     for (i1 in 1:4) for (i2 in 1:5) result[i1, i2] <- i1 * i2
#>     return(result)
#> }
#> <environment: 0x5d8f12c74ef8>
cat("\n")
my_matrix <- matrix_builder()
print(my_matrix)
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]    1    2    3    4    5
#> [2,]    2    4    6    8   10
#> [3,]    3    6    9   12   15
#> [4,]    4    8   12   16   20

The Ultimate Test: Generating the 1 Billion Iteration Function

# WARNING: Don't actually run this unless you have time to kill!
# This would create the equivalent of the benchmark from the meme

create_billion_iteration_function <- function() {


  k <- 10^9 
  n <- 1
  
  cat("Creating function with", n, "nested loops of", k, "iterations each\n")
  cat("Total iterations:", k^n, "\n")
  
  create_nested_loops_v1(n, k)
}

# Generate but don't run (for your sanity)
billion_func <- create_billion_iteration_function()
cat("Function created! (But we won't run it...)\n")

Conclusion: The Art of Loop-Free Loop Generation

Achievement Unlocked: We’ve created nested loops without using ANY loops in our generators! 🎯

🔧 Technical Mastery Demonstrated:

📊 Code Golf Results:

🎭 The Philosophical Achievement:

We’ve achieved the programming equivalent of M.C. Escher’s “Drawing Hands” - loops creating loops without being loops themselves!

🏆 The Ultimate Meta-Programming Truth:

R’s homoiconic nature means we can treat code as data, manipulate ASTs as regular objects, and compose complex nested structures through pure functional programming - all without writing a single explicit loop to generate unlimited nested loops!

This isn’t just about avoiding loops for the sake of it - it’s about demonstrating that R’s functional programming capabilities can elegantly solve problems that seem to require imperative constructs.

R doesn’t just compete in the nested loop olympics - it redefines the game entirely! 🚀

# One final demonstration: The ultimate meta-achievement
cat("🎯 FINAL DEMONSTRATION: Creating 6 nested loops with ZERO loops in our code!\n\n")
#> 🎯 FINAL DEMONSTRATION: Creating 6 nested loops with ZERO loops in our code!

# Using our most elegant approach
ultimate_func <- create_loops_oneliner(6, 3)
cat("Generated function structure analysis:\n")
#> Generated function structure analysis:
cat("- Created via: Pure functional composition\n")
#> - Created via: Pure functional composition
cat("- Generator loops used: 0\n") 
#> - Generator loops used: 0
cat("- Target loops created: 6\n")
#> - Target loops created: 6
cat("- Code lines in generator: 1\n\n")
#> - Code lines in generator: 1

ultimate_result <- ultimate_func()
cat("🔥 RESULT:", ultimate_result, "total iterations\n")
#> 🔥 RESULT: 729 total iterations
cat("✅ EXPECTED:", 3^6, "\n")
#> ✅ EXPECTED: 729
cat("🎉 SUCCESS: Math checks out!\n\n")
#> 🎉 SUCCESS: Math checks out!

cat("🏆 ACHIEVEMENT: We've officially created loops without using loops!\n")
#> 🏆 ACHIEVEMENT: We've officially created loops without using loops!
cat("🤯 This is the programming equivalent of pulling yourself up by your bootstraps!\n")
#> 🤯 This is the programming equivalent of pulling yourself up by your bootstraps!

More Ridiculous Test: 1000 NESTED LOOPS Function (Zero-Loop Construction!)

# The TRULY ridiculous test - 1000 NESTED LOOPS created with ZERO explicit loops!
# Using pure functional composition - the ultimate meta-programming achievement!

cat("🚀 === ULTIMATE CHALLENGE: 1000 NESTED LOOPS with ZERO-LOOP CONSTRUCTION ===\n")
#> 🚀 === ULTIMATE CHALLENGE: 1000 NESTED LOOPS with ZERO-LOOP CONSTRUCTION ===
cat("Creating a function with 1000 levels of nesting using pure functional programming!\n")
#> Creating a function with 1000 levels of nesting using pure functional programming!
cat("Generator method: Point-free functional composition (no loops whatsoever)\n\n")
#> Generator method: Point-free functional composition (no loops whatsoever)

# Use our most concise approach for maximum elegance
cat("🔧 Building AST for 1000 nested loops using pure functional composition...\n")
#> 🔧 Building AST for 1000 nested loops using pure functional composition...
thousand_loops_func <- create_loops_oneliner(1000, 1)

cat("📊 Generated function analysis:\n")
#> 📊 Generated function analysis:
func_str <- deparse(body(thousand_loops_func))
cat("- AST lines generated:", length(func_str), "\n")
#> - AST lines generated: 6
cat("- Generator loops used: 0 (pure functional composition!)\n")
#> - Generator loops used: 0 (pure functional composition!)
cat("- Object size:", format(object.size(thousand_loops_func), units = "Kb"), "\n")
#> - Object size: 657.7 Kb
cat("- Nesting depth: 1000 levels\n")
#> - Nesting depth: 1000 levels
cat("- Construction method: One-liner functional composition\n\n")
#> - Construction method: One-liner functional composition

cat("🎯 Sample of generated AST structure:\n")
#> 🎯 Sample of generated AST structure:
cat("First 3 lines:\n", paste(func_str[1:3], collapse = "\n"), "\n")
#> First 3 lines:
#>  {
#>     counter <- 0
#>     for (i1 in 1:1) for (i2 in 1:1) for (i3 in 1:1) for (i4 in 1:1) for (i5 in 1:1) for (i6 in 1:1) for (i7 in 1:1) for (i8 in 1:1) for (i9 in 1:1) for (i10 in 1:1) for (i11 in 1:1) for (i12 in 1:1) for (i13 in 1:1) for (i14 in 1:1) for (i15 in 1:1) for (i16 in 1:1) for (i17 in 1:1) for (i18 in 1:1) for (i19 in 1:1) for (i20 in 1:1) for (i21 in 1:1) for (i22 in 1:1) for (i23 in 1:1) for (i24 in 1:1) for (i25 in 1:1) for (i26 in 1:1) for (i27 in 1:1) for (i28 in 1:1) for (i29 in 1:1) for (i30 in 1:1) for (i31 in 1:1) for (i32 in 1:1) for (i33 in 1:1) for (i34 in 1:1) for (i35 in 1:1) for (i36 in 1:1) for (i37 in 1:1) for (i38 in 1:1) for (i39 in 1:1) for (i40 in 1:1) for (i41 in 1:1) for (i42 in 1:1) for (i43 in 1:1) for (i44 in 1:1) for (i45 in 1:1) for (i46 in 1:1) for (i47 in 1:1) for (i48 in 1:1) for (i49 in 1:1) for (i50 in 1:1) for (i51 in 1:1) for (i52 in 1:1) for (i53 in 1:1) for (i54 in 1:1) for (i55 in 1:1) for (i56 in 1:1) for (i57 in 1:1) for (i58 in 1:1) for (i59 in 1:1) for (i60 in 1:1) for (i61 in 1:1) for (i62 in 1:1) for (i63 in 1:1) for (i64 in 1:1) for (i65 in 1:1) for (i66 in 1:1) for (i67 in 1:1) for (i68 in 1:1) for (i69 in 1:1) for (i70 in 1:1) for (i71 in 1:1) for (i72 in 1:1) for (i73 in 1:1) for (i74 in 1:1) for (i75 in 1:1) for (i76 in 1:1) for (i77 in 1:1) for (i78 in 1:1) for (i79 in 1:1) for (i80 in 1:1) for (i81 in 1:1) for (i82 in 1:1) for (i83 in 1:1) for (i84 in 1:1) for (i85 in 1:1) for (i86 in 1:1) for (i87 in 1:1) for (i88 in 1:1) for (i89 in 1:1) for (i90 in 1:1) for (i91 in 1:1) for (i92 in 1:1) for (i93 in 1:1) for (i94 in 1:1) for (i95 in 1:1) for (i96 in 1:1) for (i97 in 1:1) for (i98 in 1:1) for (i99 in 1:1) for (i100 in 1:1) for (i101 in 1:1) for (i102 in 1:1) for (i103 in 1:1) for (i104 in 1:1) for (i105 in 1:1) for (i106 in 1:1) for (i107 in 1:1) for (i108 in 1:1) for (i109 in 1:1) for (i110 in 1:1) for (i111 in 1:1) for (i112 in 1:1) for (i113 in 1:1) for (i114 in 1:1) for (i115 in 1:1) for (i116 in 1:1) for (i117 in 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1:1) for (i784 in 1:1) for (i785 in 1:1) for (i786 in 1:1) for (i787 in 1:1) for (i788 in 1:1) for (i789 in 1:1) for (i790 in 1:1) for (i791 in 1:1) for (i792 in 1:1) for (i793 in 1:1) for (i794 in 1:1) for (i795 in 1:1) for (i796 in 1:1) for (i797 in 1:1) for (i798 in 1:1) for (i799 in 1:1) for (i800 in 1:1) for (i801 in 1:1) for (i802 in 1:1) for (i803 in 1:1) for (i804 in 1:1) for (i805 in 1:1) for (i806 in 1:1) for (i807 in 1:1) for (i808 in 1:1) for (i809 in 1:1) for (i810 in 1:1) for (i811 in 1:1) for (i812 in 1:1) for (i813 in 1:1) for (i814 in 1:1) for (i815 in 1:1) for (i816 in 1:1) for (i817 in 1:1) for (i818 in 1:1) for (i819 in 1:1) for (i820 in 1:1) for (i821 in 1:1) for (i822 in 1:1) for (i823 in 1:1) for (i824 in 1:1) for (i825 in 1:1) for (i826 in 1:1) for (i827 in 1:1) for (i828 in 1:1) for (i829 in 1:1) for (i830 in 1:1) for (i831 in 1:1) for (i832 in 1:1) for (i833 in 1:1) for (i834 in 1:1) for (i835 in 1:1) for (i836 in 1:1) for (i837 in 1:1) for (i838 in 1:1) for (i839 in 1:1) for (i840 in 1:1) for (i841 in 1:1) for (i842 in 1:1) for (i843 in 1:1) for (i844 in 1:1) for (i845 in 1:1) for (i846 in 1:1) for (i847 in 1:1) for (i848 in 1:1) for (i849 in 1:1) for (i850 in 1:1) for (i851 in 1:1) for (i852 in 1:1) for (i853 in 1:1) for (i854 in 1:1) for (i855 in 1:1) for (i856 in 1:1) for (i857 in 1:1) for (i858 in 1:1) for (i859 in 1:1) for (i860 in 1:1) for (i861 in 1:1) for (i862 in 1:1) for (i863 in 1:1) for (i864 in 1:1) for (i865 in 1:1) for (i866 in 1:1) for (i867 in 1:1) for (i868 in 1:1) for (i869 in 1:1) for (i870 in 1:1) for (i871 in 1:1) for (i872 in 1:1) for (i873 in 1:1) for (i874 in 1:1) for (i875 in 1:1) for (i876 in 1:1) for (i877 in 1:1) for (i878 in 1:1) for (i879 in 1:1) for (i880 in 1:1) for (i881 in 1:1) for (i882 in 1:1) for (i883 in 1:1) for (i884 in 1:1) for (i885 in 1:1) for (i886 in 1:1) for (i887 in 1:1) for (i888 in 1:1) for (i889 in 1:1) for (i890 in 1:1) for (i891 in 1:1) for (i892 in 1:1) for (i893 in 1:1) for (i894 in 1:1) for (i895 in 1:1) for (i896 in 1:1) for (i897 in 1:1) for (i898 in 1:1) for (i899 in 1:1) for (i900 in 1:1) for (i901 in 1:1) for (i902 in 1:1) for (i903 in 1:1) for (i904 in 1:1) for (i905 in 1:1) for (i906 in 1:1) for (i907 in 1:1) for (i908 in 1:1) for (i909 in 1:1) for (i910 in 1:1) for (i911 in 1:1) for (i912 in 1:1) for (i913 in 1:1) for (i914 in 1:1) for (i915 in 1:1) for (i916 in 1:1) for (i917 in 1:1) for (i918 in 1:1) for (i919 in 1:1) for (i920 in 1:1) for (i921 in 1:1) for (i922 in 1:1) for (i923 in 1:1) for (i924 in 1:1) for (i925 in 1:1) for (i926 in 1:1) for (i927 in 1:1) for (i928 in 1:1) for (i929 in 1:1) for (i930 in 1:1) for (i931 in 1:1) for (i932 in 1:1) for (i933 in 1:1) for (i934 in 1:1) for (i935 in 1:1) for (i936 in 1:1) for (i937 in 1:1) for (i938 in 1:1) for (i939 in 1:1) for (i940 in 1:1) for (i941 in 1:1) for (i942 in 1:1) for (i943 in 1:1) for (i944 in 1:1) for (i945 in 1:1) for (i946 in 1:1) for (i947 in 1:1) for (i948 in 1:1) for (i949 in 1:1) for (i950 in 1:1) for (i951 in 1:1) for (i952 in 1:1) for (i953 in 1:1) for (i954 in 1:1) for (i955 in 1:1) for (i956 in 1:1) for (i957 in 1:1) for (i958 in 1:1) for (i959 in 1:1) for (i960 in 1:1) for (i961 in 1:1) for (i962 in 1:1) for (i963 in 1:1) for (i964 in 1:1) for (i965 in 1:1) for (i966 in 1:1) for (i967 in 1:1) for (i968 in 1:1) for (i969 in 1:1) for (i970 in 1:1) for (i971 in 1:1) for (i972 in 1:1) for (i973 in 1:1) for (i974 in 1:1) for (i975 in 1:1) for (i976 in 1:1) for (i977 in 1:1) for (i978 in 1:1) for (i979 in 1:1) for (i980 in 1:1) for (i981 in 1:1) for (i982 in 1:1) for (i983 in 1:1) for (i984 in 1:1) for (i985 in 1:1) for (i986 in 1:1) for (i987 in 1:1) for (i988 in 1:1) for (i989 in 1:1) for (i990 in 1:1) for (i991 in 1:1) for (i992 in 1:1) for (i993 in 1:1) for (i994 in 1:1) for (i995 in 1:1) for (i996 in 1:1) for (i997 in 1:1) for (i998 in 1:1) for (i999 in 1:1) for (i1000 in 1:1) counter <- counter +
cat("...\n")
#> ...
cat("Last 3 lines:\n", paste(func_str[(length(func_str)-2):length(func_str)], collapse = "\n"), "\n\n")
#> Last 3 lines:
#>          1
#>     return(counter)
#> }

# Execute the monster
cat("⚡ Executing 1000-nested-loops function (created without loops)...\n")
#> ⚡ Executing 1000-nested-loops function (created without loops)...
start_time <- Sys.time()
thousand_result <- thousand_loops_func()
end_time <- Sys.time()

execution_time <- round(as.numeric(end_time - start_time, units = "secs") * 1000, 2)

cat("🏆 RESULTS:\n")
#> 🏆 RESULTS:
cat("- Iterations completed:", thousand_result, "\n")
#> - Iterations completed: 1
cat("- Expected result:", 1^1000, "(each loop runs once)\n")
#> - Expected result: 1 (each loop runs once)
cat("- Execution time:", execution_time, "milliseconds\n")
#> - Execution time: 7.33 milliseconds
cat("- Call stack depth: 1000 levels\n\n")
#> - Call stack depth: 1000 levels

cat("🎉 SUCCESS: We executed 1000 nested loops created via zero-loop construction!\n")
#> 🎉 SUCCESS: We executed 1000 nested loops created via zero-loop construction!
cat("🤯 Meta-achievement: Used functional programming to avoid loops while creating loops!\n")
#> 🤯 Meta-achievement: Used functional programming to avoid loops while creating loops!
cat("🏅 This demonstrates R's ultimate metaprogramming power!\n")
#> 🏅 This demonstrates R's ultimate metaprogramming power!

Dynamic Nested Loop Function Generator in R

Creating Functions with N Nested Loops of K Iterations