code: def main():
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "frameworks",
          nargs="+",
          choices=["mp", "fiber", "pyspark", "ray", "ipyparallel"],
          help="frameworks to benchmark",
      )
      parser.add_argument(
          "-t",
          "--total-duration",
          type=int,
          default=1,
          help="total running time",
      )
  
      parser.add_argument(
          "-d",
          "--task-duration",
          type=float,
          default=None,
          choices=[0.001, 0.01, 0.1, 1],
          help="task duration in ms",
      )
  
      args = parser.parse_args()
  
      workers = 5
  
      max_duration = args.total_duration
  
      results = {}
      frameworks = args.frameworks
  
      for framework in frameworks:
          results[framework] = []
          results[framework + "_seq"] = []
  
      if "pyspark" in frameworks:
          from pyspark import SparkContext
          import pyspark
  
          sc = SparkContext()
          conf = pyspark.SparkConf().setAll([("spark.cores.max", 5)])
          sc.stop()
          sc = pyspark.SparkContext(conf=conf)
  
      if "ray" in frameworks:
          import ray
  
          ray.init()
  
      if "fiber" in frameworks:
          import fiber.pool
  
          fiber_pool = fiber.Pool(workers)
  
      if "ipyparallel" in frameworks:
          print("before popen")
          # ipp_controller = subprocess.Popen(["ipcontroller", "--ip", "*"])
          print("after popen")
          import atexit
          import signal
          import os
  
          # atexit.register(ipp_controller.kill)
          pids = spawn_workers(workers)
          for pid in pids:
              atexit.register(os.kill, pid, signal.SIGKILL)
          time.sleep(4)
  
      for i in range(4):
          factor = 10**i
          duration = 1 / factor
          if args.task_duration is not None:
              print(
                  args.task_duration,
                  duration,
                  type(args.task_duration),
                  type(duration),
              )
              if args.task_duration != duration:
                  continue
          tasks = int(max_duration * workers / duration)
  
          print(
              "Benchmarking {} workers with {} tasks each takes {} "
              "seconds".format(workers, tasks, duration)
          )
  
          # sequential tests (simulating RL)
          if "mp" in frameworks:
              elapsed = bench_mp_seq(tasks, workers, duration, True)
              results["mp_seq"].append(
                  {"task_duration": duration, "elapsed": elapsed}
              )
              print("mp_seq", elapsed)
  
          if "fiber" in frameworks:
              elapsed = bench_fiber_seq(
                  tasks, workers, duration, True, pool=fiber_pool
              )
              results["fiber_seq"].append(
                  {"task_duration": duration, "elapsed": elapsed}
              )
              print("fiber_seq", elapsed)
  
          if "pyspark" in frameworks:
              elapsed = bench_spark_seq(
                  tasks, workers, duration, warmup=True, sc=sc
              )
              results["pyspark_seq"].append(
                  {"task_duration": duration, "elapsed": elapsed}
              )
              print("pyspark_seq", elapsed)
  
          if "ray" in frameworks:
              elapsed = bench_ray_seq(
                  tasks, workers, duration, warmup=True
              )
              results["ray_seq"].append(
                  {"task_duration": duration, "elapsed": elapsed}
              )
              print("ray_seq", elapsed)
  
          if "ipyparallel" in frameworks:
              elapsed = bench_ipp_seq(
                  tasks, workers, duration, warmup=True
              )
              results["ipyparallel_seq"].append(
                  {"task_duration": duration, "elapsed": elapsed}
              )
              print("ipyparallel_seq", elapsed)
  
          # batch tests (simulating ES)
          """
          if "mp" in frameworks:
              elapsed = bench_mp(tasks, workers, duration, True)
              results["mp"].append({"task_duration": duration,
                                    "elapsed": elapsed})
              print("mp", elapsed)
  
          if "fiber" in frameworks:
              elapsed = bench_fiber(tasks, workers, duration, True,
                                    pool=fiber_pool)
              results["fiber"].append({"task_duration": duration,
                                       "elapsed": elapsed})
              print("fiber", elapsed)
  
          if "pyspark" in frameworks:
              elapsed = bench_spark(tasks, workers, duration, warmup=True, sc=sc)
              results["pyspark"].append({"task_duration": duration,
                                         "elapsed": elapsed})
              print("pyspark", elapsed)
  
          if "ray" in frameworks:
              elapsed = bench_ray(tasks, workers, duration, warmup=True)
              results["ray"].append({"task_duration": duration,
                                     "elapsed": elapsed})
              print("ray", elapsed)
          """
  
      pprint(results)
  
imports: import time
  import fiber
  import multiprocessing
  import logging
  import subprocess
  import argparse
  from pprint import pprint
label_desc: Use image node_id 15 for calling a global function with example usage: main() without return types