class_docstr: A stemmer that uses regular expressions to identify morphological
  affixes.  Any substrings that match the regular expressions will
  be removed.
  
      >>> from nltk.stem import RegexpStemmer
      >>> st = RegexpStemmer('ing$|s$|e$|able$', min=4)
      >>> st.stem('cars')
      'car'
      >>> st.stem('mass')
      'mas'
      >>> st.stem('was')
      'was'
      >>> st.stem('bee')
      'bee'
      >>> st.stem('compute')
      'comput'
      >>> st.stem('advisable')
      'advis'
  
  :type regexp: str or regexp
  :param regexp: The regular expression that should be used to
      identify morphological affixes.
  :type min: int
  :param min: The minimum length of string to stem
code: def __repr__(self):
      return f"<RegexpStemmer: {self._regexp.pattern!r}>"
  
imports: import re
  from nltk.stem.api import StemmerI
label_desc: Use image node_id 3 for calling the RegexpStemmer obj's underlying member method code with example usage: obj.__repr__() and returns: str, self, str