How to use the konlpy.tag.Hannanum function in konlpy

def hannanum_instance():
    from konlpy import init_jvm
    from konlpy.tag import Hannanum
    init_jvm()
    h = Hannanum()
    return h

def get_tags(text, ntags=50, multiplier=10):
    h = Hannanum()
    nouns = h.nouns(text)
    count = Counter(nouns)
    return [{ 'color': color(), 'tag': n, 'size': c*multiplier }\
                for n, c in count.most_common(ntags)]

def get_tags(text, ntags=50, multiplier=10):
    h = Hannanum()
    nouns = h.nouns(text)
    count = Counter(nouns)
    return [{ 'color': color(), 'tag': n, 'size': c*multiplier }\
                for n, c in count.most_common(ntags)]

def get_tokenizer(tokenizer_name):
    if tokenizer_name == "komoran":
        tokenizer = Komoran()
    elif tokenizer_name == "okt":
        tokenizer = Okt()
    elif tokenizer_name == "mecab":
        tokenizer = Mecab()
    elif tokenizer_name == "hannanum":
        tokenizer = Hannanum()
    elif tokenizer_name == "kkma":
        tokenizer = Kkma()
    elif tokenizer_name == "khaiii":
        tokenizer = KhaiiiApi()
    else:
        tokenizer = Mecab()
    return tokenizer

def __init__(self, on_han=False, on_twitter=False, on_mecab=False):    # maybe move to init of analysis_app

        """
        Allocate kkma or twitter diction instance
        :param on_han: han instance
        :param on_twitter: twitter instance
        :param on_mecab: mecab instance
        """
        if on_han is True:
            self.han = Hannanum()
        if on_twitter is True:
            self.twitter = Twitter()
        # if on_mecab is True: