code: def test_use_existing_experiment_by_id(tmpdir: py.path.local) -> None:
      tracking_uri = f"file:{tmpdir}"
      mlflow.set_tracking_uri(tracking_uri)
      experiment_id = mlflow.create_experiment("foo")
  
      mlflow_kwargs = {"experiment_id": experiment_id}
      mlflc = MLflowCallback(
          tracking_uri=tracking_uri,
          create_experiment=False,
          mlflow_kwargs=mlflow_kwargs,
      )
      study = optuna.create_study()
  
      for _ in range(10):
          study.optimize(_objective_func, n_trials=1, callbacks=[mlflc])
  
      mlfl_client = MlflowClient(tracking_uri)
      experiment_list = mlfl_client.search_experiments()
      assert len(experiment_list) == 1
  
      experiment = experiment_list[0]
      assert experiment.experiment_id == experiment_id
      assert experiment.name == "foo"
  
      runs = mlfl_client.search_runs(experiment_id)
      assert len(runs) == 10
  
imports: from typing import Callable
  from typing import List
  from typing import Optional
  from typing import Tuple
  from typing import Union
  import numpy
  import py
  import pytest
  import optuna
  from optuna._imports import try_import
  from optuna.integration.mlflow import MLflowCallback
label_desc: Use image node_id 6 for calling a global function with example usage: test_use_existing_experiment_by_id(tmpdir) without return types