code: def _executor(self, file_path: Path):
      file_path = Path(file_path)
  
      # some symbol_field values such as TRUE, NA are decoded as True(bool), NaN(np.float) by pandas default csv parsing.
      # manually defines dtype and na_values of the symbol_field.
      default_na = (
          pd._libs.parsers.STR_NA_VALUES
      )  # pylint: disable=I1101
      symbol_na = default_na.copy()
      symbol_na.remove("NA")
      columns = pd.read_csv(file_path, nrows=0).columns
      df = pd.read_csv(
          file_path,
          dtype={self._symbol_field_name: str},
          keep_default_na=False,
          na_values={
              col: symbol_na
              if col == self._symbol_field_name
              else default_na
              for col in columns
          },
      )
  
      df = self._normalize_obj.normalize(df)
      if df is not None and not df.empty:
          if self._end_date is not None:
              _mask = pd.to_datetime(
                  df[self._date_field_name]
              ) <= pd.Timestamp(self._end_date)
              df = df[_mask]
          df.to_csv(
              self._target_dir.joinpath(file_path.name), index=False
          )
  
imports: import abc
  import time
  import datetime
  import importlib
  from pathlib import Path
  from typing import Type, Iterable
  from concurrent.futures import ProcessPoolExecutor
  import pandas
  from tqdm import tqdm
  from loguru import logger
  from joblib import Parallel, delayed
  from qlib.utils import code_to_fname
label_desc: Use image node_id 2 for calling the Normalize obj's underlying member method code with example usage: obj._executor(file_path) without return types