ó <żCVc@s\ddlmZddlZddlmZddlmZedefd„ƒYƒZdS(i˙˙˙˙(tunicode_literalsN(tStemmerI(tpython_2_unicode_compatiblet RegexpStemmercBs,eZdZdd„Zd„Zd„ZRS(uä 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 icCs7t|dƒs!tj|ƒ}n||_||_dS(Nupattern(thasattrtretcompilet_regexpt_min(tselftregexptmin((sb/private/var/folders/cc/xm4nqn811x9b50x1q_zpkmvdjlphkp/T/pip-build-FUwmDn/nltk/nltk/stem/regexp.pyt__init__+s cCs0t|ƒ|jkr|S|jjd|ƒSdS(Nu(tlenRRtsub(R tword((sb/private/var/folders/cc/xm4nqn811x9b50x1q_zpkmvdjlphkp/T/pip-build-FUwmDn/nltk/nltk/stem/regexp.pytstem2scCsd|jjS(Nu(Rtpattern(R ((sb/private/var/folders/cc/xm4nqn811x9b50x1q_zpkmvdjlphkp/T/pip-build-FUwmDn/nltk/nltk/stem/regexp.pyt__repr__8s(t__name__t __module__t__doc__R RR(((sb/private/var/folders/cc/xm4nqn811x9b50x1q_zpkmvdjlphkp/T/pip-build-FUwmDn/nltk/nltk/stem/regexp.pyRs  (t __future__RRt nltk.stem.apiRt nltk.compatRR(((sb/private/var/folders/cc/xm4nqn811x9b50x1q_zpkmvdjlphkp/T/pip-build-FUwmDn/nltk/nltk/stem/regexp.pyt s