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- # Natural Language Toolkit: Stemmers
- #
- # Copyright (C) 2001-2019 NLTK Project
- # Author: Trevor Cohn <tacohn@cs.mu.oz.au>
- # Edward Loper <edloper@gmail.com>
- # Steven Bird <stevenbird1@gmail.com>
- # URL: <http://nltk.org/>
- # For license information, see LICENSE.TXT
- from __future__ import unicode_literals
- import re
- from nltk.stem.api import StemmerI
- from nltk.compat import python_2_unicode_compatible
- @python_2_unicode_compatible
- class RegexpStemmer(StemmerI):
- """
- 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
- """
- def __init__(self, regexp, min=0):
- if not hasattr(regexp, 'pattern'):
- regexp = re.compile(regexp)
- self._regexp = regexp
- self._min = min
- def stem(self, word):
- if len(word) < self._min:
- return word
- else:
- return self._regexp.sub('', word)
- def __repr__(self):
- return '<RegexpStemmer: {!r}>'.format(self._regexp.pattern)
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