Add Sleep Sort Algorithm in R

sorting_algorithms/sleep_sort.r

@@ -0,0 +1,97 @@
+# Sleep sort in R:
+
+# SleepSort is a (mostly humorous) sorting algorithm that launches one task per
+# element, sleeps proportional to the element's value, then outputs the value
+# upon waking. The values are observed in order of their completion times.
+#
+# This implementation targets Windows compatibility by using a PSOCK cluster
+# from the 'parallel' package and leveraging file modification times to capture
+# the order in which tasks finish.
+#
+# Notes:
+# - Works for numeric vectors. Negative values are supported by offsetting so
+#   all sleep times are non-negative (relative to the minimum value).
+# - Large values can cause long sleep times; use 'scale' to control delay.
+# - This is for educational/demonstration purposes and not recommended for
+#   production sorting.
+
+sleep.sort <- function(elements.vec, scale = 0.01, max.workers = NULL) {
+  # Handle trivial cases
+  n <- length(elements.vec)
+  if (n <= 1) return(elements.vec)
+  if (!is.numeric(elements.vec)) stop("sleep.sort: elements.vec must be numeric")
+
+  # Shift to make non-negative delays and avoid negative sleep
+  min.val <- min(elements.vec)
+  offset <- if (min.val < 0) -min.val else 0
+
+  # Cap scale to a reasonable positive number
+  if (!is.numeric(scale) || scale <= 0) stop("sleep.sort: 'scale' must be positive numeric")
+
+  # Determine number of workers
+  if (is.null(max.workers)) {
+    # Conservative default
+    max.workers <- max(1L, min(4L, n))
+  }
+
+  # Prepare an output directory to record completion times
+  outdir <- file.path(tempdir(), paste0("sleep_sort_", as.integer(runif(1) * 1e9)))
+  dir.create(outdir, recursive = TRUE, showWarnings = FALSE)
+
+  # Worker function: sleep then write value to a unique file
+  worker_fun <- function(v, idx, scale, offset, outdir) {
+    delay <- (v + offset) * scale
+    # Add a tiny jitter to reduce ties on duplicates finishing at the exact same time
+    delay <- delay + (idx %% 13) * 1e-4
+    if (delay < 0) delay <- 0
+    Sys.sleep(delay)
+    out.path <- file.path(outdir, paste0("task_", idx, ".txt"))
+    # Write the original value
+    write(as.character(v), file = out.path)
+    TRUE
+  }
+
+  # Attempt parallel execution; on failure, fall back to base sort
+  result <- try({
+    # Create cluster
+    cl <- parallel::makeCluster(max.workers)
+    on.exit({try(parallel::stopCluster(cl), silent = TRUE)}, add = TRUE)
+
+    # Export needed objects
+    parallel::clusterExport(cl, varlist = c("elements.vec", "scale", "offset", "outdir", "worker_fun"), envir = environment())
+
+    # Schedule one task per element
+    parallel::parLapply(cl, seq_along(elements.vec), function(i) {
+      v <- elements.vec[i]
+      worker_fun(v, i, scale, offset, outdir)
+    })
+
+    # All tasks finished; list files and sort by modification time (completion order)
+    files <- list.files(outdir, full.names = TRUE, pattern = "^task_\\d+\\.txt$")
+    if (length(files) != n) {
+      # In rare cases, the filesystem may lag; simple retry loop
+      tries <- 0
+      while (tries < 50 && length(files) != n) {
+        Sys.sleep(0.02)
+        files <- list.files(outdir, full.names = TRUE, pattern = "^task_\\d+\\.txt$")
+        tries <- tries + 1
+      }
+    }
+    info <- file.info(files)
+    ord <- order(info$mtime, na.last = NA)
+    as.numeric(vapply(files[ord], function(f) as.numeric(readLines(f, n = 1L)), numeric(1)))
+  }, silent = TRUE)
+
+  if (inherits(result, "try-error")) {
+    # Fallback: base sort to keep function usable without parallel
+    # (This does not simulate sleep behavior.)
+    return(sort(elements.vec))
+  }
+
+  return(result)
+}
+
+# Example:
+# sleep.sort(c(3, 1, 4, 2, 5), scale = 0.05)
+# Possible output (order of completion):
+# [1] 1 2 3 4 5