class_docstr: Dataset based on paragraphs from Wikipedia in 230+ languages.
  
  Source: https://zenodo.org/record/841984
  
  References:
      Thoma, Martin. "The WiLI benchmark dataset for written language identification."
      arXiv preprint arXiv:1801.07779 (2018).
class_docstr_tok: ["Dataset","based","on","paragraphs","from","Wikipedia","in","230+","languages",".","Source",":","https",":","\/\/zenodo.org\/record\/841984","References",":","Thoma",",","Martin",".","``","The","WiLI","benchmark","dataset","for","written","language","identification",".","''","arXiv","preprint","arXiv:1801.07779","(","2018",")","."]
docstr: Args:
      force: If True, always download a new copy of the dataset; otherwise,
          only download dataset if it doesn't already exist on disk.
docstr_tok: ["Args",":","force",":","If","True",",","always","download","a","new","copy","of","the","dataset",";","otherwise",",","only","download","dataset","if","it","does","n't","already","exist","on","disk","."]
code: def download(self, force: bool = False):
      """
      Args:
          force: If True, always download a new copy of the dataset; otherwise,
              only download dataset if it doesn't already exist on disk.
      """
      fpath = tio.download_file(
          self.download_url, dirpath=self.data_dir, force=force
      )
      if fpath:
          tio.unpack_archive(fpath, extract_dir=self.data_dir)
  
imports: from __future__ import annotations
  import logging
  import operator
  import pathlib
  import random
  import re
  from typing import Dict, Iterable, List, Optional, Set, Tuple
  from cytoolz import itertoolz
  import textacy
  import textacy.utils
  from textacy import io
label_desc: Use image node_id 2 for calling the Wili2018Dataset obj's underlying member method code with example usage: obj.download(force) without return types