class_docstr: Basic functionality for NLP handlers.
class_docstr_tok: ["Basic","functionality","for","NLP","handlers","."]
docstr: Deal with incoming requests.
docstr_tok: ["Deal","with","incoming","requests","."]
code: def post(self):
      """Deal with incoming requests."""
      body = tornado.escape.json_decode(self.request.body)
  
      try:
          self._bo.register(
              params=body["params"],
              target=body["target"],
          )
          print(
              "BO has registered: {} points.".format(
                  len(self._bo.space)
              ),
              end="\n\n",
          )
      except KeyError:
          pass
      finally:
          suggested_params = self._bo.suggest(self._uf)
  
      self.write(json.dumps(suggested_params))
  
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 1 for calling the BayesianOptimizationHandler obj's underlying member method code with example usage: obj.post() without return types