code: def download_file_and_extract(
      local_cache_path: str = ".", file_split: str = "train"
  ) -> None:
      """Download and extract the test_utils files
  
      Args:
          local_cache_path (str [optional]) -- Directory to cache files to.
              Defaults to current working directory (default: {"."})
          file_split {str} -- [description] (default: {"train"})
      """
      file_name = URL.split("/")[-1]
      maybe_download(URL, file_name, local_cache_path)
  
      if not os.path.exists(
          os.path.join(local_cache_path, DATA_FILES[file_split])
      ):
          extract_zip(
              os.path.join(local_cache_path, file_name),
              local_cache_path,
          )
  
imports: import os
  import pandas
  from notebooks.test_utils.utils_data_shared import maybe_download, extract_zip
label_desc: Use image node_id 1 for calling a global function with example usage: download_file_and_extract(local_cache_path, file_split) without return types