code: def run_optimizer():
      global optimizers_config
      config = optimizers_config.pop()
      name = config["name"]
      colour = config["colour"]
  
      register_data = {}
      max_target = None
      for _ in range(10):
          status = name + " wants to register: {}.\n".format(
              register_data
          )
  
          resp = requests.post(
              url="http://localhost:9009/bayesian_optimization",
              json=register_data,
          ).json()
          target = black_box_function(**resp)
  
          register_data = {
              "params": resp,
              "target": target,
          }
  
          if max_target is None or target > max_target:
              max_target = target
  
          status += name + " got {} as target.\n".format(target)
          status += name + " will to register next: {}.\n".format(
              register_data
          )
          print(colour(status), end="\n")
  
      global results
      results.append((name, max_target))
      print(colour(name + " is done!"), end="\n\n")
  
file_path: BayesianOptimization/examples/async_optimization.py
imports: import time
  import random
  from bayes_opt import BayesianOptimization
  from bayes_opt.util import UtilityFunction, Colours
  import asyncio
  import threading
label_desc: Use image node_id 3 for calling a global function with example usage: run_optimizer() without return types