docstr: MovieLens data format container as a different size of MovieLens data file
  has a different format
  
  Args:
      sep (str): Rating data delimiter
      path (str): Rating data path within the original zip file
      has_header (bool): Whether the rating data contains a header line or not
      item_sep (str): Item data delimiter
      item_path (str): Item data path within the original zip file
      item_has_header (bool): Whether the item data contains a header line or not
docstr_tok: ["MovieLens","data","format","container","as","a","different","size","of","MovieLens","data","file","has","a","different","format","Args",":","sep","(","str",")",":","Rating","data","delimiter","path","(","str",")",":","Rating","data","path","within","the","original","zip","file","has_header","(","bool",")",":","Whether","the","rating","data","contains","a","header","line","or","not","item_sep","(","str",")",":","Item","data","delimiter","item_path","(","str",")",":","Item","data","path","within","the","original","zip","file","item_has_header","(","bool",")",":","Whether","the","item","data","contains","a","header","line","or","not"]
code: def __init__(
      self,
      sep,
      path,
      has_header=False,
      item_sep=None,
      item_path=None,
      item_has_header=False,
  ):
      """MovieLens data format container as a different size of MovieLens data file
      has a different format
  
      Args:
          sep (str): Rating data delimiter
          path (str): Rating data path within the original zip file
          has_header (bool): Whether the rating data contains a header line or not
          item_sep (str): Item data delimiter
          item_path (str): Item data path within the original zip file
          item_has_header (bool): Whether the item data contains a header line or not
      """
  
      # Rating file
      self._sep = sep
      self._path = path
      self._has_header = has_header
  
      # Item file
      self._item_sep = item_sep
      self._item_path = item_path
      self._item_has_header = item_has_header
  
imports: import os
  import re
  import random
  import shutil
  import warnings
  import pandas
  from typing import Optional
  from zipfile import ZipFile
  from recommenders.datasets.download_utils import maybe_download, download_path
  from recommenders.utils.notebook_utils import is_databricks
  from recommenders.utils.constants import DEFAULT_HEADER, DEFAULT_ITEM_COL, DEFAULT_USER_COL, DEFAULT_RATING_COL, DEFAULT_TIMESTAMP_COL, DEFAULT_TITLE_COL, DEFAULT_GENRE_COL
  import pandera
  import pandera.extensions
  from pandera import Field
  from pandera.typing import Series
label_desc: Use image node_id 1 to create a new _DataFormat object  with example: obj = _DataFormat(sep, path, has_header, item_sep, item_path, item_has_header)