def _get_data_file_preprocessing_code(file: File) -> Optional[str]:
  """Returns the code to explore the data file."""

  def _get_normalized_file_name(file_name: str) -> str:
    var_name, _ = os.path.splitext(file_name)
    # Replace non-alphanumeric characters with underscores
    var_name = re.sub(r'[^a-zA-Z0-9_]', '_', var_name)

    # If the filename starts with a digit, prepend an underscore
    if var_name[0].isdigit():
      var_name = '_' + var_name
    return var_name

  if file.mime_type not in _DATA_FILE_UTIL_MAP:
    return

  var_name = _get_normalized_file_name(file.name)
  loader_code = _DATA_FILE_UTIL_MAP[file.mime_type].loader_code_template.format(
      filename=file.name
  )
  return f"""
{_DATA_FILE_HELPER_LIB}

# Load the dataframe.
{var_name} = {loader_code}

# Use `explore_df` to guide my analysis.
explore_df({var_name})
"""
Returns the code to explore the data file.
src/google/adk/flows/llm_flows/_code_execution.py