How to use the textstat.textstat.textstat.flesch_kincaid_grade function in textstat

def decide_if_assigned_threshold(self, person, threshold):
        reading_levels = {}
        for my_product in person.all_products:
            text = ""
            if my_product.title:
                text += u" " + my_product.title
            if my_product.get_abstract_using_mendeley():
                text += u" " + my_product.get_abstract_using_mendeley()

            # only do if at least three words between periods,
            # otherwise textstat library prints too many Not Enough Words error messages
            if text:
                sentences = text.split(".")
                if any([len(sentence.split())>3 for sentence in sentences]):
                    try:
                        grade_level = textstat.flesch_kincaid_grade(text)
                        # print u"grade level is {} for {}; text: {}".format(grade_level, my_product.doi, text)
                        if grade_level > 0:
                            # is sometimes negative, strangely.  examples in ethan's profile
                            reading_levels[my_product.doi] = grade_level
                    except TypeError:  #if text is too short it thows this
                        pass

        if reading_levels.values():
            average_reading_level = sum(reading_levels.values()) / float(len(reading_levels))
            self.candidate_badge.value = average_reading_level
            self.assigned = True

def get_feat_readability_metrics(self):
        # https://github.com/shivam5992/textstat

        try:
            test_data = self.webscrap.get_body()
            out = []
            out.append(textstat.flesch_reading_ease(test_data))
            out.append(textstat.smog_index(test_data))
            out.append(textstat.flesch_kincaid_grade(test_data))
            out.append(textstat.coleman_liau_index(test_data))
            out.append(textstat.automated_readability_index(test_data))
            out.append(textstat.dale_chall_readability_score(test_data))
            out.append(textstat.difficult_words(test_data))
            out.append(textstat.linsear_write_formula(test_data))
            out.append(textstat.gunning_fog(test_data))
            #out.append(textstat.text_standard(test_data))
            return out, False

        except Exception as e:
            config.logger.error(repr(e))
            return MISSING_FEATURE * 9, True

def _get_reading_stats(no_code_text):
    """
    Returns reading level information
    :param no_code_text: String to analyse
    :return: list of details
    """
    group_by = 'Reading Level Analysis '
    results = []
    results.append(TextFeature('Flesch Reading Ease', textstat.flesch_reading_ease(no_code_text), group_by))        # higher is better, scale 0 to 100
    results.append(TextFeature('Flesch-Kincaid Grade Level', textstat.flesch_kincaid_grade(no_code_text), group_by))
    try:
        results.append(TextFeature('The Fog Scale (Gunning FOG formula)', textstat.gunning_fog(no_code_text), group_by))
    except IndexError:  # Not sure why, but this test throws this error sometimes
        results.append(TextFeature('The Fog Scale (Gunning FOG formula)', "Undetermined", group_by))
    try:
        results.append(TextFeature('The SMOG Index', textstat.smog_index(no_code_text), group_by))
    except IndexError:  # Not sure why, but this test throws this error sometimes
        results.append(TextFeature('The SMOG Index', "Undetermined", group_by))
    results.append(TextFeature('Automated Readability Index', textstat.automated_readability_index(no_code_text), group_by))
    results.append(TextFeature('The Coleman-Liau Index', textstat.coleman_liau_index(no_code_text), group_by))
    try:
        results.append(TextFeature('Linsear Write Formula', textstat.linsear_write_formula(no_code_text), group_by))
    except IndexError:
        results.append(TextFeature('Linsear Write Formula', "Undetermined", group_by))
    try:
        results.append(TextFeature('Dale Chall Readability Score', textstat.dale_chall_readability_score(no_code_text), group_by))