updates

Backend/venv/lib/python3.12/site-packages/nltk/stem/wordnet.py

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+# Natural Language Toolkit: WordNet stemmer interface
+#
+# Copyright (C) 2001-2025 NLTK Project
+# Author: Steven Bird <stevenbird1@gmail.com>
+#         Edward Loper <edloper@gmail.com>
+#         Eric Kafe <kafe.eric@gmail.com>
+# URL: <https://www.nltk.org/>
+# For license information, see LICENSE.TXT
+
+
+class WordNetLemmatizer:
+    """
+    WordNet Lemmatizer
+
+    Provides 3 lemmatizer modes: _morphy(), morphy() and lemmatize().
+
+    lemmatize() is a permissive wrapper around _morphy().
+    It returns the shortest lemma found in WordNet,
+    or the input string unchanged if nothing is found.
+
+    >>> from nltk.stem import WordNetLemmatizer as wnl
+    >>> print(wnl().lemmatize('us', 'n'))
+    u
+
+    >>> print(wnl().lemmatize('Anythinggoeszxcv'))
+    Anythinggoeszxcv
+
+    """
+
+    def _morphy(self, form, pos, check_exceptions=True):
+        """
+        _morphy() is WordNet's _morphy lemmatizer.
+        It returns a list of all lemmas found in WordNet.
+
+        >>> from nltk.stem import WordNetLemmatizer as wnl
+        >>> print(wnl()._morphy('us', 'n'))
+        ['us', 'u']
+        """
+        from nltk.corpus import wordnet as wn
+
+        return wn._morphy(form, pos, check_exceptions)
+
+    def morphy(self, form, pos=None, check_exceptions=True):
+        """
+        morphy() is a restrictive wrapper around _morphy().
+        It returns the first lemma found in WordNet,
+        or None if no lemma is found.
+
+        >>> from nltk.stem import WordNetLemmatizer as wnl
+        >>> print(wnl().morphy('us', 'n'))
+        us
+
+        >>> print(wnl().morphy('catss'))
+        None
+        """
+        from nltk.corpus import wordnet as wn
+
+        return wn.morphy(form, pos, check_exceptions)
+
+    def lemmatize(self, word: str, pos: str = "n") -> str:
+        """Lemmatize `word` by picking the shortest of the possible lemmas,
+        using the wordnet corpus reader's built-in _morphy function.
+        Returns the input word unchanged if it cannot be found in WordNet.
+
+        >>> from nltk.stem import WordNetLemmatizer as wnl
+        >>> print(wnl().lemmatize('dogs'))
+        dog
+        >>> print(wnl().lemmatize('churches'))
+        church
+        >>> print(wnl().lemmatize('aardwolves'))
+        aardwolf
+        >>> print(wnl().lemmatize('abaci'))
+        abacus
+        >>> print(wnl().lemmatize('hardrock'))
+        hardrock
+
+        :param word: The input word to lemmatize.
+        :type word: str
+        :param pos: The Part Of Speech tag. Valid options are `"n"` for nouns,
+            `"v"` for verbs, `"a"` for adjectives, `"r"` for adverbs and `"s"`
+            for satellite adjectives.
+        :type pos: str
+        :return: The shortest lemma of `word`, for the given `pos`.
+        """
+        lemmas = self._morphy(word, pos)
+        return min(lemmas, key=len) if lemmas else word
+
+    def __repr__(self):
+        return "<WordNetLemmatizer>"