(expression=default_pattern, stoplist=STOP_WORDS,
                     minsize=2, maxsize=None, gaps=False, stemfn=stem,
                     ignore=None, cachesize=50000)
return chain | StemFilter(stemfn=stemfn, ignore=ignore,
                              cachesize=cachesize)
Composes a RegexTokenizer with a lower case filter, an optional stop
    filter, and a stemming filter.

    >>> ana = StemmingAnalyzer()
    >>> [token.text for token in ana("Testing is testing and testing")]
    ["test", "test", "test"]

    :param expression: The regular expression pattern to use to extract tokens.
    :param stoplist: A list of stop words. Set this to None to disable
        the stop word filter.
    :param minsize: Words smaller than this are removed from the stream.
    :param maxsize: Words longer that this are removed from the stream.
    :param gaps: If True, the tokenizer *splits* on the expression, rather
        than matching on the expression.
    :param ignore: a set of words to not stem.
    :param cachesize: the maximum number of stemmed words to cache. The larger
        this number, the faster stemming will be but the more memory it will
        use. Use None for no cache, or -1 for an unbounded cache.
Composes a RegexTokenizer with a lower case filter, an optional stop
    filter, and a stemming filter.
Composes a RegexTokenizer with a lower case filter an optional stop filter and a stemming filter .
def StemmingAnalyzer(expression=default_pattern, stoplist=STOP_WORDS,
                     minsize=2, maxsize=None, gaps=False, stemfn=stem,
                     ignore=None, cachesize=50000):
    """Composes a RegexTokenizer with a lower case filter, an optional stop
    filter, and a stemming filter.

    >>> ana = StemmingAnalyzer()
    >>> [token.text for token in ana("Testing is testing and testing")]
    ["test", "test", "test"]

    :param expression: The regular expression pattern to use to extract tokens.
    :param stoplist: A list of stop words. Set this to None to disable
        the stop word filter.
    :param minsize: Words smaller than this are removed from the stream.
    :param maxsize: Words longer that this are removed from the stream.
    :param gaps: If True, the tokenizer *splits* on the expression, rather
        than matching on the expression.
    :param ignore: a set of words to not stem.
    :param cachesize: the maximum number of stemmed words to cache. The larger
        this number, the faster stemming will be but the more memory it will
        use. Use None for no cache, or -1 for an unbounded cache.
    """

    ret = RegexTokenizer(expression=expression, gaps=gaps)
    chain = ret | LowercaseFilter()
    if stoplist is not None:
        chain = chain | StopFilter(stoplist=stoplist, minsize=minsize,
                                   maxsize=maxsize)
    return chain | StemFilter(stemfn=stemfn, ignore=ignore,
                              cachesize=cachesize)
def StemmingAnalyzer ( expression = default_pattern , stoplist = STOP_WORDS , minsize = 2 , maxsize = None , gaps = False , stemfn = stem , ignore = None , cachesize = 50000 ) : ret = RegexTokenizer ( expression = expression , gaps = gaps ) chain = ret | LowercaseFilter ( ) if stoplist is not None : chain = chain | StopFilter ( stoplist = stoplist , minsize = minsize , maxsize = maxsize ) return chain | StemFilter ( stemfn = stemfn , ignore = ignore , cachesize = cachesize )