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)
#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_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 run(self, book, **kwargs):
doc = book.plaintext
isbn = 'isbn' in book.metadata and book.metadata['isbn'][0]
url = 'https://atlas-fab.lexile.com/free/books/' + str(isbn)
headers = {'accept': 'application/json; version=1.0'}
lexile = requests.get(url, headers=headers)
# Checks if lexile exists for ISBN. If doesn't exist value remains 'None'.
# If lexile does exist but no age range, value will be 'None'.
# If no ISBN, value will be 'None'.
if lexile.status_code == 200:
lexile_work = lexile.json()['data']['work']
self.lexile_min_age = str(lexile_work['min_age'])
self.lexile_max_age = str(lexile_work['max_age'])
try:
r = Readability(doc)
fk = r.flesch_kincaid()
s = r.smog()
self.readability_fk_score = fk.score
self.readability_s_score = s.score
# If less than 100 words
except ReadabilityException:
pass
import requests
from bs4 import BeautifulSoup
from readability import Readability
response = requests.get('http://127.0.0.1/demo')
rtext = "The result is a number that corresponds with a U.S. grade level. The sentence, The Australian platypus is seemingly a hybrid of a mammal and reptilian creature is an 11.3 as it has 24 syllables and 13 words. The different weighting factors for words per sentence and syllables per word in each scoring system mean that the two schemes are not directly comparable and cannot be converted. The grade level formula emphasises sentence length over word length. By creating one-word strings with hundreds of random characters, grade levels may be attained that are hundreds of times larger than high school completion in the United States. Due to the formula's construction, the score does not have an upper bound."
robj = Readability(rtext)
html = response.text
obj = BeautifulSoup(html,'lxml')
def getTagCount(c):
ct = obj.find_all(c)
print("Count of '"+c+"' Tag is :" + str(len(ct)))
print ct
if response.status_code == 200:
print('Connection Success!\n')
elif response.status_code == 404:
print('Not Found.\n')
getTagCount('a')
#print len(rtext.split())
fk = robj.flesch_kincaid()
s = robj.smog()
print "\nFlesch Kincaid Readabiity Score : "+str(fk.score)
print "Flesch Kincaid Readabiity Grade Level : "+str(fk.grade_level)
#print "SMOG Readabiity Score : "+str(s.score)
#print "SMOG Readabiity Grade Level : "+str(s.grade_level)
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)
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)
def get_readability(content):
r = Readability(content)
try:
return r.smog().score
except ReadabilityException:
return None
from readability import Readability
path = "IAEA_output"
str = ""
with open(path, encoding="utf-8") as f:
for line in f.readlines():
str = line
r = Readability(str)
fk = r.flesch_kincaid()
print(fk.score)
print(fk.grade_level)
s = r.smog()
print(s.score)
print(s.grade_level)
dc = r.dale_chall()
print(dc.score)
print(dc.grade_levels)
cl = r.coleman_liau()
print(cl.score)
print(cl.grade_level)
gf = r.gunning_fog()
print(gf.score)
print(gf.grade_level)
# lw = r.linsear_write()
# print(lw.score)
# print(lw.grade_level)
def __smog(r: Readability) -> float:
try:
lvl = r.smog(all_sentences = True).grade_level
return float(lvl)
except ReadabilityException:
return None
