Exemple #1
0
def main():
    path='/home/shuo/Documents/AI_learning/LearningQ/data/teded/teded_crawled_data/'
    analysis=text_analysis()
    analysis.read_relation(path)
    #analysis.get_mintues()
    analysis.read_videoinfo(path)
    questions=analysis.gather_question()
    question=analysis.video_question
    #for item in question:
    #    print(question[item]['quizzes'][0].keys())
    """
    self.video_question[title]: video_link', 'video_title_length', 'video_description', 'quizzes', 'video_youtube_link
    quizzes: quiz_description', 'question_type', 'quiz_options', 'hint', 'answer'
    multiple-choices open-ended
    """
    scripts=analysis.gather_transcripts(path)
    stats_scripts(scripts)
    temp_dic=analysis.build_question_transcripts(path)

   # analysis.stats_scripts()
    temp=[]
    for item in temp_dic:
        for quiz in  temp_dic[item]['questions']:
            if quiz['question_type']=='multiple-choices':
                temp.append(temp_dic[item])
                break
    q=0
    for d in temp:
        for question in d['questions']:
            xxx=len(question['quiz_description'].split('.'))
            q+=xxx

    nlp = en_core_web_sm.load()
    #n_e=0
    total_r=0
    n=0
    for title in scripts:
        #sentences=scripts[title].split('\n')
        #e=NER(sentences,nlp)
        if len(scripts[title].split(' '))>=100:

            n+=1
            r = Readability(scripts[title])
            total_r+=r.flesch().score
        #n_e+=e
    #print(n_e)
    print(total_r)
    print(n)
    print(total_r/n)
Exemple #2
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 def doc_to_readability(doc_str) -> ArrayField:
     if len(doc_str) < 10:
         return ArrayField(np.zeros(7))
     str_to_read = doc_str
     try:
         while len(str_to_read.split()) < 150:
             str_to_read += " " + doc_str
         r = Readability(str_to_read)
         r_scores = [
             r.flesch_kincaid().score,
             r.flesch().score,
             r.gunning_fog().score,
             r.coleman_liau().score,
             r.dale_chall().score,
             r.ari().score,
             r.linsear_write().score
         ]
         return ArrayField(np.array(r_scores))
     except ReadabilityException:
         return ArrayField(np.zeros(7))
Exemple #3
0

#------------------
# Readability
#------------------

st.header('Readability')

# Context 
passage = st.text_area("Candidate Bible Passage (English)", value='', 
        max_chars=None, key='readability_passage')

# Calculate readability
r = Readability(passage)

# Display readability
data = [
        ['Flesch-Kincaid Score', r.flesch_kincaid().score],
        ['Flesch Reading Ease', r.flesch().ease],
        ['Dale Chall Readability Score', r.dale_chall().score],
        ['Automated Readability Index Score', r.ari().score],
        ['Coleman Liau Index', r.coleman_liau().score],
        ['Gunning Fog', r.gunning_fog().score],
        ['Linsear Write', r.linsear_write().score],
        ['Spache Readability Formula', r.spache().score]
        ]
df = pd.DataFrame(data, columns=['Readability Metric', 'Value'])
if st.button('Assess Readability', key=None):
    st.write(df)

Exemple #4
0
class ReadabilityTest(unittest.TestCase):
    def setUp(self):
        text = """
        In linguistics, the Gunning fog index is a readability test for English writing. The index estimates the years of formal education a person needs to understand the text on the first reading. For instance, a fog index of 12 requires the reading level of a United States high school senior (around 18 years old). The test was developed in 1952 by Robert Gunning, an American businessman who had been involved in newspaper and textbook publishing.
        The fog index is commonly used to confirm that text can be read easily by the intended audience. Texts for a wide audience generally need a fog index less than 12. Texts requiring near-universal understanding generally need an index less than 8.
        """
        self.readability = Readability(text)

    def test_ari(self):
        r = self.readability.ari()
        print(r)
        self.assertEqual(9.551245421245422, r.score)
        self.assertEqual(['10'], r.grade_levels)
        self.assertEqual([15, 16], r.ages)

    def test_coleman_liau(self):
        r = self.readability.coleman_liau()
        print(r)
        self.assertEqual(10.673162393162393, r.score)
        self.assertEqual('11', r.grade_level)

    def test_dale_chall(self):
        r = self.readability.dale_chall()
        print(r)
        self.assertEqual(9.32399010989011, r.score)
        self.assertEqual(['college'], r.grade_levels)

    def test_flesch(self):
        r = self.readability.flesch()
        print(r)
        self.assertEqual(51.039230769230784, r.score)
        self.assertEqual(['10', '11', '12'], r.grade_levels)
        self.assertEqual('fairly_difficult', r.ease)

    def test_flesch_kincaid(self):
        r = self.readability.flesch_kincaid()
        print(r)
        self.assertEqual(10.125531135531137, r.score)
        self.assertEqual('10', r.grade_level)

    def test_gunning_fog(self):
        r = self.readability.gunning_fog()
        print(r)
        self.assertEqual(12.4976800976801, r.score)
        self.assertEqual('12', r.grade_level)

    def test_linsear_write(self):
        r = self.readability.linsear_write()
        print(r)
        self.assertEqual(11.214285714285714, r.score)
        self.assertEqual('11', r.grade_level)

    def test_smog(self):
        text = """
        In linguistics, the Gunning fog index is a readability test for English writing. The index estimates the years of formal education a person needs to understand the text on the first reading. For instance, a fog index of 12 requires the reading level of a United States high school senior (around 18 years old). The test was developed in 1952 by Robert Gunning, an American businessman who had been involved in newspaper and textbook publishing.
        The fog index is commonly used to confirm that text can be read easily by the intended audience. Texts for a wide audience generally need a fog index less than 12. Texts requiring near-universal understanding generally need an index less than 8.
        """
        text = ' '.join(text for i in range(0, 5))

        readability = Readability(text)
        r = readability.smog()

        print(r)
        self.assertEqual(12.516099999999998, r.score)
        self.assertEqual('13', r.grade_level)

    def test_spache(self):
        r = self.readability.spache()
        print(r)
        self.assertEqual(7.164945054945054, r.score)
        self.assertEqual('7', r.grade_level)

    def test_print_stats(self):
        stats = self.readability.statistics()
        self.assertEqual(562, stats['num_letters'])
        self.assertEqual(117, stats['num_words'])
        self.assertEqual(7, stats['num_sentences'])
        self.assertEqual(20, stats['num_polysyllabic_words'])
Exemple #5
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def main():
    # Read and normalise input text
    content = sys.stdin.read()
    tu = TextUtility(content)
    cleanText = tu.normalizeText()

    #removedInfrequent = tu.tokenizeAndRemoveCommonWords(4)
    #print("Without frequent words: ", removedInfrequent)

    #Readability measures
    print("\n*** Readability ***")
    readability = Readability(content)
    Kincaid = readability.kincaid()
    sys.stdout.write('Kincaid (school grade level): %f\n' % (Kincaid))

    ARI_score = readability.ari()
    sys.stdout.write('ARI (school grade level): %f\n' % (ARI_score))

    ColemanLiau = readability.colemanLiau()
    sys.stdout.write('ColemanLiau (school grade level): %f\n' % (ColemanLiau))

    Flesch = readability.flesch()
    sys.stdout.write('Flesch: 0=12th grade, 100=4th grade %f\n' % (Flesch))

    Fog = readability.fog()
    sys.stdout.write('Fog: grade level: %f\n' % (Fog))

    SMOG = readability.smog()
    sys.stdout.write('SMOG: years of education needed to comprehend: %f\n' %
                     (SMOG))

    print("\n*** Lexical Diversity ***")
    diversity = LexicalDiversity(content)
    yulei = diversity.yulei()
    sys.stdout.write('Yule I Lexical Diversity: %f\n' % yulei)

    word_entropy = diversity.calcWordEntropy()
    sys.stdout.write('Word entropy: %f \n' % (word_entropy))

    synonym_suggestions = diversity.recommendSynonyms(90, 3)
    sys.stdout.write(
        '\nHere are some synonyms for frequently occuring words:\n')
    for word in synonym_suggestions.keys():
        print(word, synonym_suggestions[word])

    print("\n*** Description ***")
    word_probability = WordProbability(content)
    hashtags = word_probability.hashtagSuggestions(99)
    sys.stdout.write('Hashtag suggestions %s\n' % hashtags)

    tfidf = word_probability.tfidf(5)
    print("tfidf: ", tfidf)

    entrSyl = diversity.entropySyllable(5)
    entrSylWords = [entry[0] for entry in entrSyl]
    print("sylEntropy: ", entrSylWords)

    summary = word_probability.summary(55)
    sys.stdout.write('\nSummary %s\n' % summary)

    print("\n*** Search/Plagarism ***")
    plagarism = TextSearch()
    txt = content
    pat = "empowers consumers to take control"
    setPat = {"empowers consumers", "a million bank acc", "Contact UsPrivacy "}

    plg = plagarism.rabinKarp(setPat, txt)
    sys.stdout.write('Rabin-Karp found pattern at %s \n' % str(plg))

    #wildSearch = 'tsfd;lkasdi*ghasd'
    wildSearch = 'the*est'
    #empowers consumers to take control of their financial
    #wildSearch = 'empowers c*to take*of their financial'
    #wildSearch = 'consumers*take control of their'
    wild = plagarism.wildCardSearch(wildSearch, txt)
    sys.stdout.write('Wildcard search found %s \n' % str(wild))

    print("\n*** Cliche Detection ***")
    plagarism.findCliches(content)
Exemple #6
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class ReadabilityTest(unittest.TestCase):
    def setUp(self):
        text = """
        “On a June day sometime in the early 1990s, encouraged by his friend and fellow economist Jörgen Weibull, Abhijit went swimming in the Baltic. He leaped in and instantly jumped out—he claims that his teeth continued to chatter for the next three days. In 2018, also in June, we went to the Baltic in Stockholm, several hundred miles farther north than the previous encounter. This time it was literally child’s play; our children frolicked in the water.
        Wherever we went in Sweden, the unusually warm weather was a topic of conversation. It was probably a portent of something everyone felt, but for the moment it was hard not to be quite delighted with the new opportunities for outdoor life it offered.”. 
        """
        self.readability = Readability(text)

    def test_ari(self):
        r = self.readability.ari()
        print(r)
        self.assertEqual(9.551245421245422, r.score)
        self.assertEqual(['10'], r.grade_levels)
        self.assertEqual([15, 16], r.ages)

    def test_coleman_liau(self):
        r = self.readability.coleman_liau()
        print(r)
        self.assertEqual(10.673162393162393, r.score)
        self.assertEqual('11', r.grade_level)

    def test_dale_chall(self):
        r = self.readability.dale_chall()
        print(r)
        self.assertEqual(9.32399010989011, r.score)
        self.assertEqual(['college'], r.grade_levels)

    def test_flesch(self):
        r = self.readability.flesch()
        print(r)
        self.assertEqual(51.039230769230784, r.score)
        self.assertEqual(['10', '11', '12'], r.grade_levels)
        self.assertEqual('fairly_difficult', r.ease)

    def test_flesch_kincaid(self):
        r = self.readability.flesch_kincaid()
        print(r)
        self.assertEqual(10.125531135531137, r.score)
        self.assertEqual('10', r.grade_level)

    def test_gunning_fog(self):
        r = self.readability.gunning_fog()
        print(r)
        self.assertEqual(12.4976800976801, r.score)
        self.assertEqual('12', r.grade_level)

    def test_linsear_write(self):
        r = self.readability.linsear_write()
        print(r)
        self.assertEqual(11.214285714285714, r.score)
        self.assertEqual('11', r.grade_level)

    def test_smog(self):
        text = """
        “On a June day sometime in the early 1990s, encouraged by his friend and fellow economist Jörgen Weibull, Abhijit went swimming in the Baltic. He leaped in and instantly jumped out—he claims that his teeth continued to chatter for the next three days. In 2018, also in June, we went to the Baltic in Stockholm, several hundred miles farther north than the previous encounter. This time it was literally child’s play; our children frolicked in the water.
        Wherever we went in Sweden, the unusually warm weather was a topic of conversation. It was probably a portent of something everyone felt, but for the moment it was hard not to be quite delighted with the new opportunities for outdoor life it offered.”. 
        """
        text = ' '.join(text for i in range(0, 5))

        readability = Readability(text)

        #Test SMOG with 30 sentences
        r1 = readability.smog()

        #Test SMOG with all sentences
        r2 = readability.smog(all_sentences=True)

        print("all_sentences=False: %s ; all_sentences=True: %s" % (r1, r2))
        self.assertEqual(12.516099999999998, r1.score)
        self.assertEqual('13', r1.grade_level)

        self.assertEqual(12.785403640627713, r2.score)
        self.assertEqual('13', r2.grade_level)

    def test_spache(self):
        r = self.readability.spache()
        print(r)
        self.assertEqual(7.164945054945054, r.score)
        self.assertEqual('7', r.grade_level)

    def test_print_stats(self):
        stats = self.readability.statistics()
        self.assertEqual(562, stats['num_letters'])
        self.assertEqual(117, stats['num_words'])
        self.assertEqual(7, stats['num_sentences'])
        self.assertEqual(20, stats['num_polysyllabic_words'])
class ReadabilityAnalyser:
    def __init__(self, text):
        self.readability = Readability(text)
        self.FLESCH_KINCAID = ['score', 'grade_level']
        self.FLESCH_EASE = ['score', 'ease', 'grade_level']
        self.DALE_CHALL = ['score', 'grade_level']
        self.ARI = ['score', 'grade_level', 'ages']
        self.CLI = ['score', 'grade_level']
        self.GUNNING_FOG = ['score', 'grade_level']
        self.SMOG = ['score', 'grade_level']
        self.SPACHE = ['score', 'grade_level']
        self.LINSEAR_WRITE = ['score', 'grade_level']
        self.values_index = self.initialize_value_index_array()

    def initialize_value_index_array(self):
        values_index = dict()
        values_index["flesch_kincaid"] = self.FLESCH_KINCAID
        values_index["flesch_ease"] = self.FLESCH_EASE
        values_index["dale_chall"] = self.DALE_CHALL
        values_index["ari"] = self.ARI
        values_index["cli"] = self.CLI
        values_index["gunning_fog"] = self.GUNNING_FOG
        values_index["smog_all"] = self.SMOG
        values_index["smog"] = self.SMOG
        values_index["spache"] = self.SPACHE
        values_index["linsear_write"] = self.LINSEAR_WRITE
        return values_index

    def flesch_kincaid(self, content, error_ignore=True):
        try:
            record = dict()
            fk = self.readability.flesch_kincaid()
            record['score'] = fk.score
            record['grade_level'] = fk.grade_level
            content["flesch_kincaid"] = record
        except ReadabilityException as e:
            if not error_ignore:
                content["flesch_kincaid"] = str(e)
                print(e)

    def flesch_ease(self, content, error_ignore=True):
        try:
            record = dict()
            flesch_ease = self.readability.flesch()
            record['score'] = flesch_ease.score
            record['ease'] = flesch_ease.ease
            record['grade_levels'] = flesch_ease.grade_levels
            content['flesch_ease'] = record
        except ReadabilityException as e:
            if not error_ignore:
                content['flesch_ease'] = str(e)
                print(e)

    def dale_chall(self, content, error_ignore=True):
        try:
            record = dict()
            dale_chall = self.readability.dale_chall()
            record['score'] = dale_chall.score
            record['grade_level'] = dale_chall.grade_levels
            content['dale_chall'] = record
        except ReadabilityException as e:
            if not error_ignore:
                content['dale_chall'] = str(e)
                print(e)

    def automated_readability_index(self, content, error_ignore=True):
        try:
            record = dict()
            ari = self.readability.ari()
            record['score'] = ari.score
            record['grade_level'] = ari.grade_levels
            record['ages'] = ari.ages
            content['ari'] = record
        except ReadabilityException as e:
            if not error_ignore:
                content['ari'] = str(e)
                print(e)

    def coleman_liau_index(self, content, error_ignore=True):
        try:
            record = dict()
            coleman_liau = self.readability.coleman_liau()
            record['score'] = coleman_liau.score
            record['grade_level'] = coleman_liau.grade_level
            content['cli'] = record
            print(record)
        except ReadabilityException as e:
            print(e)
            if not error_ignore:
                content['cli'] = str(e)
                print(e)

    def gunning_fog_index(self, content, error_ignore=True):
        try:
            record = dict()
            gunning_fog = self.readability.gunning_fog()
            record['score'] = gunning_fog.score
            record['grade_level'] = gunning_fog.grade_level
            content['gunning_fog'] = record
        except ReadabilityException as e:
            if not error_ignore:
                content['gunning_fog'] = str(e)
                print(e)

    def smog(self, content, all_sentences=False, error_ignore=True):
        record = dict()
        try:
            if all_sentences:
                smog = self.readability.smog(all_sentences=all_sentences)
                record['score'] = smog.score
                record['grade_level'] = smog.grade_level
                content['smog_all'] = record
            else:
                smog = self.readability.smog()
                record['score'] = smog.score
                record['grade_level'] = smog.grade_level
                content['smog'] = record
        except ReadabilityException as e:
            print(e)
            print(error_ignore)
            if not error_ignore:
                if all_sentences:
                    content['smog_all'] = str(e)
                else:
                    content['smog'] = str(e)
                print(e)

    def spache_readability_formula(self, content, error_ignore=True):
        try:
            record = dict()
            spache = self.readability.spache()
            record['score'] = spache.score
            record['grade_level'] = spache.grade_level
            content['spache'] = record
        except ReadabilityException as e:
            if not error_ignore:
                content['spache'] = str(e)
                print(e)

    def linsear_write(self, content, error_ignore=True):
        try:
            record = dict()
            linsear_write = self.readability.linsear_write()
            record['score'] = linsear_write.score
            record['grade_level'] = linsear_write.grade_level
            content['linsear_write'] = record
        except ReadabilityException as e:
            if not error_ignore:
                content['linsear_write'] = str(e)
                print(e)

    @staticmethod
    def check_readability_from_file(input_json_file, output_json_file):
        result = []
        json_file = load_as_json(input_json_file)
        for record in json_file:
            analyser = ReadabilityAnalyser(record['text'])
            analysed_file_record = dict()
            analysed_file_record['file'] = record['file']
            analysed_file_record['category'] = record['category']
            analyser.flesch_kincaid(analysed_file_record)
            analyser.flesch_ease(analysed_file_record)
            analyser.dale_chall(analysed_file_record)
            analyser.automated_readability_index(analysed_file_record)
            analyser.coleman_liau_index(analysed_file_record)
            analyser.gunning_fog_index(analysed_file_record)
            analyser.smog(analysed_file_record)
            analyser.smog(analysed_file_record, True)
            analyser.spache_readability_formula(analysed_file_record)
            analyser.linsear_write(analysed_file_record)
            result.append(analysed_file_record)
        save_as_json(result, output_json_file)

    def check_readability(self, use_methods=None, errors_included=True):
        result_analysis = dict()
        if use_methods is None or 'flesch_kincaid' in use_methods:
            self.flesch_kincaid(result_analysis,
                                error_ignore=not errors_included)
        if use_methods is None or 'flesch_ease' in use_methods:
            self.flesch_ease(result_analysis, error_ignore=not errors_included)
        if use_methods is None or 'dale_chall' in use_methods:
            self.dale_chall(result_analysis, error_ignore=not errors_included)
        if use_methods is None or 'ari' in use_methods:
            self.automated_readability_index(result_analysis,
                                             error_ignore=not errors_included)
        if use_methods is None or 'cli' in use_methods:
            self.coleman_liau_index(result_analysis,
                                    error_ignore=not errors_included)
        if use_methods is None or 'gunning_fog' in use_methods:
            self.gunning_fog_index(result_analysis,
                                   error_ignore=not errors_included)
        if use_methods is None or 'smog' in use_methods:
            self.smog(result_analysis, error_ignore=not errors_included)
        if use_methods is None or 'smog_all' in use_methods:
            self.smog(result_analysis, True, error_ignore=not errors_included)
        if use_methods is None or 'spache' in use_methods:
            self.spache_readability_formula(result_analysis,
                                            error_ignore=not errors_included)
        if use_methods is None or 'linsear_write' in use_methods:
            self.linsear_write(result_analysis,
                               error_ignore=not errors_included)
        return result_analysis

    @staticmethod
    def initialize_basic_dict(categories, values, process_category=True):
        record = dict()
        for value in values:
            record = ReadabilityAnalyser.initialize_dict(record, value)
        if process_category:
            for category in categories:
                record[category] = ReadabilityAnalyser.initialize_basic_dict(
                    categories, values, False)
        return record

    @staticmethod
    def initialize_dict(record, value):
        record['min_' + value] = 999999999
        record['max_' + value] = -999999999
        record['sum_' + value] = 0
        record['avg_' + value] = 0
        record['freq_' + value] = 0
        record['skipped_' + value] = 0
        return record

    def initialize_values(self, statistic, categories):
        statistic["flesch_kincaid"] = self.initialize_basic_dict(
            categories, self.FLESCH_KINCAID)
        statistic["flesch_ease"] = self.initialize_basic_dict(
            categories, self.FLESCH_EASE)
        statistic["dale_chall"] = self.initialize_basic_dict(
            categories, self.DALE_CHALL)
        statistic["ari"] = self.initialize_basic_dict(categories, self.ARI)
        statistic["cli"] = self.initialize_basic_dict(categories, self.CLI)
        statistic["gunning_fog"] = self.initialize_basic_dict(
            categories, self.GUNNING_FOG)
        statistic["smog_all"] = self.initialize_basic_dict(
            categories, self.SMOG)
        statistic["smog"] = self.initialize_basic_dict(categories, self.SMOG)
        statistic["spache"] = self.initialize_basic_dict(
            categories, self.SPACHE)
        statistic["linsear_write"] = self.initialize_basic_dict(
            categories, self.LINSEAR_WRITE)
        statistic['indexes'] = [
            "flesch_kincaid", "flesch_ease", "dale_chall", "ari", "cli",
            "gunning_fog", "smog_all", "smog", "spache", "linsear_write"
        ]
        statistic['categories'] = categories

    @staticmethod
    def fill_min_max_sum_category(index, value_index, statistics,
                                  readability_index, category):
        if index[value_index] < statistics[readability_index][category][
                'min_' + value_index]:
            statistics[readability_index][category][
                'min_' + value_index] = index[value_index]
        if index[value_index] > statistics[readability_index][category][
                'max_' + value_index]:
            statistics[readability_index][category][
                'max_' + value_index] = index[value_index]
        statistics[readability_index][category]['sum_' + value_index] = \
            statistics[readability_index][category]['sum_' + value_index] + index[value_index]

    @staticmethod
    def fill_min_max_sum_category_value(value, value_index, statistics,
                                        readability_index, category):
        if value < statistics[readability_index][category]['min_' +
                                                           value_index]:
            statistics[readability_index][category]['min_' +
                                                    value_index] = value
        if value > statistics[readability_index][category]['max_' +
                                                           value_index]:
            statistics[readability_index][category]['max_' +
                                                    value_index] = value
        statistics[readability_index][category]['sum_' + value_index] = \
            statistics[readability_index][category]['sum_' + value_index] + value

    @staticmethod
    def fill_min_max_sum(index, value_index, statistics, readability_index):
        if index[value_index] < statistics[readability_index]['min_' +
                                                              value_index]:
            statistics[readability_index]['min_' +
                                          value_index] = index[value_index]
        if index[value_index] > statistics[readability_index]['max_' +
                                                              value_index]:
            statistics[readability_index]['max_' +
                                          value_index] = index[value_index]
        statistics[readability_index]['sum_' + value_index] = \
            statistics[readability_index]['sum_' + value_index] + index[value_index]

    @staticmethod
    def fill_min_max_sum_value(value, value_index, statistics,
                               readability_index):
        if value < statistics[readability_index]['min_' + value_index]:
            statistics[readability_index]['min_' + value_index] = value
        if value > statistics[readability_index]['max_' + value_index]:
            statistics[readability_index]['max_' + value_index] = value
        statistics[readability_index]['sum_' + value_index] = \
            statistics[readability_index]['sum_' + value_index] + value

    @staticmethod
    def cast_to_float(value):
        try:
            return float(value)
        except ValueError:
            return None
        except TypeError:
            return None

    def record_analysis(self, record, statistics):
        for readability_index in statistics['indexes']:
            if 'category' in record:
                category = record['category']
                if readability_index in record:
                    index = record[readability_index]
                    for value_index in self.values_index[readability_index]:
                        if value_index in index:
                            obtained_value = ReadabilityAnalyser.cast_to_float(
                                index[value_index])

                            if obtained_value is not None:
                                index[value_index] = obtained_value
                                ReadabilityAnalyser.fill_min_max_sum_category(
                                    index, value_index, statistics,
                                    readability_index, category)
                                if 'freq_' + value_index not in statistics[
                                        readability_index][category]:
                                    statistics[readability_index][category][
                                        'freq_' + value_index] = 0
                                statistics[readability_index][category]['freq_' + value_index] = \
                                    statistics[readability_index][category]['freq_' + value_index] + 1
                            elif isinstance(index[value_index], list):
                                for rec in index[value_index]:

                                    if value_index not in statistics[
                                            readability_index][category]:
                                        statistics[readability_index][
                                            category][value_index] = dict()
                                    if isinstance(rec, str):
                                        if 'freq_' + rec not in statistics[
                                                readability_index][category][
                                                    value_index]:
                                            statistics[readability_index][
                                                category][value_index]['freq_'
                                                                       +
                                                                       rec] = 0
                                        statistics[readability_index][category][value_index]['freq_' + rec] = \
                                            statistics[readability_index][category][value_index]['freq_' + rec] + 1
                                    else:
                                        ReadabilityAnalyser.fill_min_max_sum_category_value(
                                            rec, value_index, statistics,
                                            readability_index, category)
                                        if 'freq_' + value_index not in \
                                                statistics[readability_index][category][value_index]:
                                            statistics[readability_index][
                                                category]['freq_' +
                                                          value_index] = 0
                                        statistics[readability_index][category]['freq_' + value_index] = \
                                            statistics[readability_index][category]['freq_' + value_index] + 1
                            elif isinstance(index[value_index], str):
                                rec = index[value_index]
                                if value_index not in statistics[
                                        readability_index][category]:
                                    statistics[readability_index][category][
                                        value_index] = dict()
                                if 'freq_' + rec not in statistics[
                                        readability_index][category][
                                            value_index]:
                                    statistics[readability_index][category][
                                        value_index]['freq_' + rec] = 0
                                statistics[readability_index][category][value_index]['freq_' + rec] = \
                                    statistics[readability_index][category][value_index]['freq_' + rec] + 1
                            else:
                                print("Uncategorized: " +
                                      str(index[value_index]))

                            statistics[readability_index][category]['freq_' + value_index] = \
                                statistics[readability_index][category]['freq_' + value_index] + 1
                        else:
                            statistics[readability_index][category]['skipped_' + value_index] = \
                                statistics[readability_index][category]['skipped_' + value_index] + 1
                else:
                    for value_index in self.values_index[readability_index]:
                        statistics[readability_index][category]['skipped_' + value_index] = \
                            statistics[readability_index][category]['skipped_' + value_index] + 1
            else:
                print("THIS: " + record)

            if readability_index in record:
                index = record[readability_index]
                for value_index in self.values_index[readability_index]:
                    if value_index in index:
                        obtained_value = ReadabilityAnalyser.cast_to_float(
                            index[value_index])

                        if obtained_value is not None:
                            index[value_index] = float(index[value_index])
                            ReadabilityAnalyser.fill_min_max_sum(
                                index, value_index, statistics,
                                readability_index)
                            if 'freq_' + value_index not in statistics[
                                    readability_index]:
                                statistics[readability_index]['freq_' +
                                                              value_index] = 0
                            statistics[readability_index]['freq_' + value_index] = \
                                statistics[readability_index]['freq_' + value_index] + 1
                        elif isinstance(index[value_index], list):
                            for rec in index[value_index]:
                                if value_index not in statistics[
                                        readability_index]:
                                    statistics[readability_index][
                                        value_index] = dict()

                                if isinstance(rec, str):
                                    # print(value_index + " " + str(index[value_index]))
                                    if 'freq_' + rec not in statistics[
                                            readability_index][value_index]:
                                        statistics[readability_index][
                                            value_index]['freq_' + rec] = 0
                                    statistics[readability_index][value_index]['freq_' + rec] = \
                                        statistics[readability_index][value_index]['freq_' + rec] + 1
                                else:
                                    ReadabilityAnalyser.fill_min_max_sum_value(
                                        rec, value_index, statistics,
                                        readability_index)
                                    if 'freq_' + value_index not in statistics[
                                            readability_index][value_index]:
                                        statistics[readability_index][
                                            'freq_' + value_index] = 0
                                    statistics[readability_index]['freq_' + value_index] = \
                                        statistics[readability_index]['freq_' + value_index] + 1
                        elif isinstance(index[value_index], str):
                            rec = index[value_index]
                            if value_index not in statistics[
                                    readability_index]:
                                statistics[readability_index][
                                    value_index] = dict()
                            if 'freq_' + rec not in statistics[
                                    readability_index][value_index]:
                                statistics[readability_index][value_index][
                                    'freq_' + rec] = 0
                            statistics[readability_index][value_index]['freq_' + rec] = \
                                statistics[readability_index][value_index]['freq_' + rec] + 1
                        else:
                            print("Uncategorized: " + str(index[value_index]))

                        statistics[readability_index]['freq_' + value_index] = \
                            statistics[readability_index]['freq_' + value_index] + 1
                    else:
                        statistics[readability_index]['skipped_' + value_index] = \
                            statistics[readability_index]['skipped_' + value_index] + 1
            else:
                for value_index in self.values_index[readability_index]:
                    statistics[readability_index]['skipped_' + value_index] = \
                        statistics[readability_index]['skipped_' + value_index] + 1

    def count_average(self, statistics):
        for readability_index in statistics['indexes']:
            for value_index in self.values_index[readability_index]:
                if statistics[readability_index]['sum_' + value_index] != 0:
                    statistics[readability_index]['avg_' + value_index] = \
                        statistics[readability_index]['sum_' + value_index] / statistics[readability_index][
                            'freq_' + value_index]
                else:
                    statistics[readability_index]['sum_' + value_index] = 0
                for category in statistics['categories']:
                    if statistics[readability_index][category][
                            'sum_' + value_index] != 0:
                        statistics[readability_index][category]['avg_' + value_index] = \
                            statistics[readability_index][category]['sum_' + value_index] / \
                            statistics[readability_index][category]['freq_' + value_index]
                    else:
                        statistics[readability_index][category][
                            'sum_' + value_index] = 0

    def analyse_readability_file(self, readability_file, categories):
        statistic = dict()
        self.initialize_values(statistic, categories)

        file = load_as_json(readability_file)
        for record in file:
            self.record_analysis(record, statistic)

        self.count_average(statistic)
        return statistic

    def analyse_readability_file_save_results(self, readability_file,
                                              output_statistics_file,
                                              categories):
        statistics = self.analyse_readability_file(readability_file,
                                                   categories)
        save_as_json(statistics, output_statistics_file)

to lay thee out upon the couch , and make 
 the wonder plain , and i blang and rear 
 and strange the love of all the war the stream 
 when the goddest from the shill belied 
 for heart of starchous and his warrall 
 and lack the must of the strange of love 
 the shall pare , the far should was every 
 where the world spoke the storn she parts 
 who faither paunts parture let the last of streams 
 and art his was a wings of love and dead 
 for strength and men world of the pressing 
 love god the scorn , and will with the store 
 and sleep , while chose with stare while our change 
 and the long which strand , for the glorious bear.'''

r = Readability(text)
fk = r.flesch_kincaid()
fkk = r.flesch()



print("Score:  "fk.score)
print("Grade Level:  "fk.grade_level)


#30-50	score ensures  :
#difficult to read, best understood by college graduates
#so this ensures sonnet readebality.
#(source: https://yoast.com/flesch-reading-ease-score/ )
l_gunning_fog = []
l_coleman_liau = []
l_dale_chall = []
l_ari = []
l_linsear_write = []
l_spache = []
l_flesch_ease = []

for i in os.listdir(PATH):
    if not i.startswith('.'):
        if i not in l_not_use:
            with open(PATH + i, 'r') as f:
                text = f.read()
                r = Readability(clean(text))
                s1 = r.flesch_kincaid()
                s2 = r.flesch()
                s3 = r.gunning_fog()
                s4 = r.coleman_liau()
                s5 = r.dale_chall()
                s6 = r.ari()
                s7 = r.linsear_write()
                # r.smog()
                s8 = r.spache()
                l_flesch_kincaid.append(s1.score)
                l_flesch.append(s2.score)
                l_flesch_ease.append(s2.ease)
                l_gunning_fog.append(s3.score)
                l_coleman_liau.append(s4.score)
                l_dale_chall.append(s5.score)
                l_ari.append(s6.score)
                l_linsear_write.append(s7.score)