ó
    ¯Éiñ  ã                   ó.   • S SK r S SKJr   " S S\5      rg)é    N)ÚStemmerIc                   ó.   • \ rS rSrSrSS jrS rS rSrg)	ÚRegexpStemmeré   aˆ  
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
c                 ój   • [        US5      (       d  [        R                  " U5      nXl        X l        g )NÚpattern)ÚhasattrÚreÚcompileÚ_regexpÚ_min)ÚselfÚregexpÚmins      ÚJ/home/james-whalen/.local/lib/python3.13/site-packages/nltk/stem/regexp.pyÚ__init__ÚRegexpStemmer.__init__*   s'   € Üv˜y×)Ñ)Ü—Z’Z Ó'ˆFØŒØ	ó    c                 óp   • [        U5      U R                  :  a  U$ U R                  R                  SU5      $ )NÚ )Úlenr   r   Úsub)r   Úwords     r   ÚstemÚRegexpStemmer.stem0   s.   € Üˆt‹9t—y‘yÓ ØˆKà—<‘<×#Ñ# B¨Ó-Ð-r   c                 ó8   • SU R                   R                  < S3$ )Nz<RegexpStemmer: Ú>)r   r   )r   s    r   Ú__repr__ÚRegexpStemmer.__repr__6   s   € Ø! $§,¡,×"6Ñ"6Ñ!9¸Ð;Ð;r   )r   r   N)r   )	Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__r   r   r   Ú__static_attributes__© r   r   r   r      s   † ñô6ò.õ<r   r   )r
   Únltk.stem.apir   r   r&   r   r   Ú<module>r(      s   ðó 
å "ô)<Hõ )<r   