class_docstr: Transformation that leverage pre-defined spelling mistake dictionary to
  simulate spelling mistake.
  
  https://arxiv.org/ftp/arxiv/papers/1812/1812.04718.pdf
docstr: Get a list of transformed tokens. Default one word replace one char.
  
  :param str word: token word to transform.
  :param int n: number of transformed tokens to generate.
  :param kwargs:
  :return: candidate list
docstr_tok: ["Get","a","list","of","transformed","tokens",".","Default","one","word","replace","one","char",".",":","param","str","word",":","token","word","to","transform",".",":","param","int","n",":","number","of","transformed","tokens","to","generate",".",":","param","kwargs",":",":","return",":","candidate","list"]
code: def _get_candidates(self, word, n=1, **kwargs):
      r"""
      Get a list of transformed tokens. Default one word replace one char.
  
      :param str word: token word to transform.
      :param int n: number of transformed tokens to generate.
      :param kwargs:
      :return: candidate list
  
      """
      return self.sample_num(self.rules.predict(word), n)
  
file_path: textflint/textflint/generation/transformation/UT/spelling_error.py
imports: from ...transformation import WordSubstitute
  from ....common.settings import SPELLING_ERROR_DIC
  from ....common.utils.install import download_if_needed
label_desc: Use image node_id 4 for calling the SpellingError obj's underlying member method code with example usage: obj._get_candidates(word, n) and returns: self