Ë
    çÍ:jñ  ã                   ó.   — d dl Z d dlmZ  G d„ de«      Zy)é    N)ÚStemmerIc                   ó$   — e Zd ZdZdd„Zd„ Zd„ Zy)ÚRegexpStemmeraä  
    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                 ób   — t        |d«      st        j                  |«      }|| _        || _        y )NÚpattern)ÚhasattrÚreÚcompileÚ_regexpÚ_min)ÚselfÚregexpÚmins      úe/home/mcse/projects/srt_converter/srt-converter-venv/lib/python3.12/site-packages/nltk/stem/regexp.pyÚ__init__zRegexpStemmer.__init__*   s(   € Ü�v˜yÔ)Ü—Z‘Z Ó'ˆFØˆŒØˆ�	ó    c                 ón   — t        |«      | j                  k  r|S | j                  j                  d|«      S )NÚ )Úlenr   r   Úsub)r   Úwords     r   ÚstemzRegexpStemmer.stem0   s.   € Üˆt‹9�t—y‘yÒ ØˆKà—<‘<×#Ñ# B¨Ó-Ð-r   c                 ó6   — d| j                   j                  ›d�S )Nz<RegexpStemmer: ú>)r   r   )r   s    r   Ú__repr__zRegexpStemmer.__repr__6   s   € Ø! $§,¡,×"6Ñ"6Ð!9¸Ð;Ð;r   N)r   )Ú__name__Ú
__module__Ú__qualname__Ú__doc__r   r   r   © r   r   r   r      s   „ ñó6ò.ó<r   r   )r	   Únltk.stem.apir   r   r    r   r   ú<module>r"      s   ðó 
å "ô)<�Hõ )<r   