曾与蒿藜同雨露,한때 잡초와 쑥과 함께 비와 이슬을 나누던 곳이 이제는 소나무와 삼나무와 함께 서리와 눈을 견뎌내고 있다.终随松柏到冰霜.かつては雑草やヨモギと共に雨や露を分かち合っていたが、今では松やヒノキと共に霜や雪に耐えている。曾与蒿藜同雨露,Once sharing rain and dew with weeds and wormwood, now enduring frost and snow with pines and cypresses.终随松柏到冰霜.曾与蒿藜同雨露한때 잡초와 쑥과 함께 비와 이슬을 나누던 곳이 이제는 소나무와 삼나무와 함께 서리와 눈을 견뎌내고 있다.,终随松柏到冰霜.譖セ荳手珍阯懷酔髮ィ髴イ�檎サ磯囂譚セ譟丞芦蜀ー髴�曾与蒿藜同雨露,鏇句笌钂胯棞鍚岄洦闇诧紝缁堥殢鏉炬煆鍒板啺闇�终随松柏到冰霜.曾与蒿藜同雨露,한때 잡초와 쑥과 함께 비와 이슬을 나누던 곳이 이제는 소나무와 삼나무와 함께 서리와 눈을 견뎌내고 있다.终随松柏到冰霜.曾与蒿藜同雨露,终随松柏到冰霜. rahbord-ins.ir - GrazzMean-Shell
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name : wordlists.py
"""Wordlists loaded from package data.

We can treat them as part of the code for the imperative mood check, and
therefore we load them at import time, rather than on-demand.

"""
import re
import pkgutil
import snowballstemmer


#: Regular expression for stripping comments from the wordlists
COMMENT_RE = re.compile(r'\s*#.*')

#: Stemmer function for stemming words in English
stem = snowballstemmer.stemmer('english').stemWord


def load_wordlist(name):
    """Iterate over lines of a wordlist data file.

    `name` should be the name of a package data file within the data/
    directory.

    Whitespace and #-prefixed comments are stripped from each line.

    """
    text = pkgutil.get_data('pydocstyle', 'data/' + name).decode('utf8')
    for line in text.splitlines():
        line = COMMENT_RE.sub('', line).strip()
        if line:
            yield line


#: A dict mapping stemmed verbs to the imperative form
IMPERATIVE_VERBS = {stem(v): v for v in load_wordlist('imperatives.txt')}

#: Words that are forbidden to appear as the first word in a docstring
IMPERATIVE_BLACKLIST = set(load_wordlist('imperatives_blacklist.txt'))
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