+
    ÖÇÜhñ  ã                   ó0   € ^ RI t ^ RIHt  ! R R]4      tR# )é    N)ÚStemmerIc                   ó:   a € ] tR t^t o RtRR ltR tR tRtV t	R# )ÚRegexpStemmeraˆ  
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                ón   € \        VR 4      '       g   \        P                  ! V4      pWn        W n        R# )ÚpatternN)ÚhasattrÚreÚcompileÚ_regexpÚ_min)ÚselfÚregexpÚmins   &&&Ú2/usr/lib/python3/dist-packages/nltk/stem/regexp.pyÚ__init__ÚRegexpStemmer.__init__*   s'   € Ü�v˜y×)Ò)Ü—Z’Z Ó'ˆFØŒØŽ	ó    c                ór   € \        V4      V P                  8  d   V# V P                  P                  R V4      # )Ú )Úlenr   r   Úsub)r   Úwords   &&r   ÚstemÚRegexpStemmer.stem0   s.   € Üˆt‹9�t—y‘yÔ ØˆKà—<‘<×#Ñ# B¨Ó-Ð-r   c                ó8   € R V P                   P                  : R2# )z<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__Ú__classdictcell__)Ú__classdict__s   @r   r   r      s   ø‡ € ñô6ò.÷<ð <r   r   )r	   Únltk.stem.apir   r   © r   r   Ú<module>r)      s   ðó 
å "ô)<�Hö )<r   