code: def start_python_worker(scheduler_address):
      dask.config.set({"distributed.worker.daemon": False})
  
      async def do_work():
          async with dask.distributed.Nanny(
              scheduler_ip=scheduler_address,
              nthreads=1,
              lifetime=35,  # automatically shut down the worker so this loop ends
              memory_limit=0,  # Disable memory management as it is done by Auto-sklearn itself
          ) as worker:
              await worker.finished()
  
      asyncio.get_event_loop().run_until_complete(do_work())
  
file_path: auto-sklearn/examples/60_search/example_parallel_manual_spawning_python.py
imports: import asyncio
  import multiprocessing
  import time
  import dask
  import dask.distributed
  import sklearn.datasets
  import sklearn.metrics
  from autosklearn.classification import AutoSklearnClassifier
  from autosklearn.constants import MULTICLASS_CLASSIFICATION
label_desc: Use image node_id 1 for calling a global function with example usage: start_python_worker(scheduler_address) without return types