def html2text(html):
cleaner = Cleaner()
cleaner.javascript = True # This is True because we want to activate the javascript filter
cleaner.style = True
cleaner.scripts = True
cleaner.comments = True
cleaner.links = True
cleaner.meta = True
cleaner.page_structure = True
cleaner.processing_instructions = True
cleaner.forms = True
cleaner.add_nofollow = True
#html = unicodedata.normalize('NFKD', html).encode('ascii','ignore')
try:
document = lxml.html.document_fromstring(html)
c = cleaner.clean_html(document)
html = lxml.html.tostring(c)
soup = BeautifulSoup(html, 'lxml')
parsed_text = soup.get_text()
if (len(parsed_text) > MINSIZE_CHARSDOC):
return parsed_text.lower()
else:
return None
except:
return None
def f_parse(args):
def isAlphabet(word):
alphabet = [
'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'j', 'k', 'i', 'l', 'm',
'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'x', 'y', 'w', 'z',
'à', 'è', 'é', 'ì', 'í', 'ò', 'ó', 'ù', 'ú'
]
guard = True
for t in word:
if t not in alphabet:
guard = False
return guard
loc = args[0]
corpuses = args[1]
MINSIZE_WORD = 4
MAXSIZE_WORD = 15
MINSIZE_CHARSDOC = 100
MINSIZE_WORDSDOC = 50
cleaner = Cleaner()
cleaner.javascript = True # This is True because we want to activate the javascript filter
cleaner.style = True
cleaner.scripts = True
cleaner.comments = True
cleaner.links = True
cleaner.meta = True
cleaner.page_structure = True
cleaner.processing_instructions = True
cleaner.forms = True
cleaner.add_nofollow = True
ret = []
for document in corpuses:
#html = unicodedata.normalize('NFKD', html).encode('ascii','ignore')
if len(document) > 0:
try:
document = lxml.html.document_fromstring(document)
c = cleaner.clean_html(document)
html = lxml.html.tostring(c)
soup = BeautifulSoup(html, 'lxml')
parsed_text = soup.get_text()
if (len(parsed_text) > MINSIZE_CHARSDOC):
parsed_text = parsed_text.lower()
tokenizer = RegexpTokenizer(r'\w+')
# create English stop words list
en_stop = get_stop_words('en')
it_stop = get_stop_words('it')
sp_stop = get_stop_words('es')
ge_stop = get_stop_words('de')
fr_stop = get_stop_words('fr')
# Create p_stemmer of class PorterStemmer
#p_stemmer = PorterStemmer()
# clean and tokenize document string
tokens = tokenizer.tokenize(parsed_text)
# remove stop words from tokens
stopped_tokens1 = [i for i in tokens if not i in en_stop]
stopped_tokens2 = [
i for i in stopped_tokens1 if not i in it_stop
]
stopped_tokens3 = [
i for i in stopped_tokens2 if not i in sp_stop
]
stopped_tokens4 = [
i for i in stopped_tokens3 if not i in ge_stop
]
stopped_tokens5 = [
i for i in stopped_tokens4 if not i in fr_stop
]
for word in stopped_tokens5:
if not any(char.isdigit() for char in word):
if len(word) > 1:
#check if the word has the alphabet character
if isAlphabet(word):
ret.append(word)
except:
print('Exception : Document empty')
return [loc, ret]
from django import template
from django.utils.safestring import mark_safe
import lxml.html
from lxml.html.clean import Cleaner
register = template.Library()
cleaner = Cleaner()
cleaner.safe_attrs = lxml.html.defs.safe_attrs | {'style'}
cleaner.add_nofollow = True
@register.filter(name='xss_safe')
def xss_safe(value):
return mark_safe(cleaner.clean_html(value))