def get_fingerprints(self, node):
res = []
text = normalize(get_text_and_tail(node)).strip()
if node.tag == 'a' and 'href' in node.attrib:
res = [(node.tag, node.attrib['href'], '', '')]
if text:
res += [(node.tag, a, node.attrib[a], text) for a in node.attrib]
if node.tag == 'a':
res += [(node.tag, '', '', text)]
if not res:
res = [(node.tag, '', '', text)]
else:
if 'style' in node.attrib:
tmp = re.findall(r'background-image:[ ]*url\((http[^)]+)', node.attrib['style'])
if tmp:
res += [('style', tmp[0])]
return res
def get_fingerprints(self, node):
res = []
text = normalize(get_text_and_tail(node)).strip()
if node.tag == 'a' and 'href' in node.attrib:
res = [(node.tag, node.attrib['href'], '', '')]
if text:
res += [(node.tag, a, node.attrib[a], text) for a in node.attrib]
if node.tag == 'a':
res += [(node.tag, '', '', text)]
if not res:
res = [(node.tag, '', '', text)]
else:
if 'style' in node.attrib:
tmp = re.findall(r'background-image:[ ]*url\((http[^)]+)',
node.attrib['style'])
if tmp:
res += [('style', tmp[0])]
return res
def process(self, url, tree, remove_visuals, exclude_data):
self.remove_bad_xpaths_from_tree(tree)
if self.detected_language is None:
self.detected_language = get_language(
tree, self.url_to_headers_mapping[url], self.domain)
# print('language: {}'.format(self.detected_language))
# pre_text_content = normalize('\n'.join([get_text_and_tail(x) for x in tree.iter()]))
# author has to be attempted before duplicate removal, since an author is
# likely to occur more often
self.domain_nodes_dict.remove_template(tree)
hardest_authors, not_hardest_authors, text_hard_authors, text_soft_authors, meta_authors = get_author(
tree, self.detected_language)
self.domain_nodes_dict.remove_author(tree)
title = getRuleTitle(tree)
# filter duplicate images by src
ok_imgs = get_images(tree)
titleind = ()
imginds = []
contentinds = []
# such as title, date and later author
link_eles = [link[0] for link in tree.iterlinks()
if link[0].tag == 'a' and link[2] and
link[2].startswith(self.domain) and
get_text_and_tail(link[0]).strip()]
linkinds = []
for num, node in enumerate(tree.iter()):
if node in ok_imgs:
imginds.append((node, num))
elif normalize(get_text_and_tail(node)) == title:
titleind = (node, num)
elif get_text_and_tail(node).strip():
if node in link_eles:
linkinds.append((node, num))
contentinds.append((node, num))
# Cleanup trash for visual'
if remove_visuals:
if node.tag == 'input':
node.set('type', 'hidden')
elif node.tag == 'a' and not get_text_and_tail(node).strip():
for att in node.attrib:
node.set(att, '')
if node.tag == 'img':
node.set('alt', '')
if node.attrib and 'background-image' in node.attrib:
node.set('background-image', '')
if not titleind:
# fuzzy token text / title matching
title_set = set(title.split())
for num, node in enumerate(tree.iter()):
text_content = get_text_and_tail(node)
if text_content and len(text_content) < 500:
text_set = set(text_content.split())
if fscore(title_set, text_set) > 0.5:
titleind = (node, num)
break
if titleind:
sortedimgs = sorted(imginds, key=lambda x: abs(x[1] - titleind[1]))
else:
sortedimgs = []
images = []
for x in sortedimgs:
val = None
if 'src' in x[0].attrib:
val = x[0].attrib['src']
elif 'content' in x[0].attrib:
val = x[0].attrib['content']
elif 'style' in x[0].attrib:
tmp = re.findall(r'background-image:[ ]*url\((http[^)]+)', x[0].attrib['style'])
if tmp:
val = tmp[0]
if val is not None and val not in images:
images.append(val)
author = ''
author_node_index = None
date = "1970-01-01"
if titleind:
date = get_dates(tree, titleind, self.detected_language)
# excluding soft dates (meta, they wont work anyway)
for at in [hardest_authors, not_hardest_authors, text_hard_authors, text_soft_authors]:
if at:
author, author_node_index = sorted(
at, key=lambda x: abs(x[1] - titleind[1]))[0]
break
if not author and meta_authors:
for ma in meta_authors:
author = ma
break
if author_node_index is not None:
for num, node in enumerate(tree.iter()):
if num == author_node_index:
break
# It goes wrong when some year is mentioned in the title, then it removes title
# print('removing author content', node.text)
node.text = ''
node.tail = ''
cleaned_html = lxml.html.tostring(tree).decode('utf8')
body_content = self.get_content(cleaned_html)
if not body_content:
body_content = []
title_len = len(title)
title_tokens = set(title.split())
len_title_tokens = len(title_tokens)
last_text_node_num = get_last_text_non_a_node(tree)
for num, x in enumerate(tree.iter()):
txt = normalize(get_text_and_tail(x))
if txt:
if num < titleind[1]:
# print('removed pre-title', txt)
x.text = ''
x.tail = ''
continue
if last_text_node_num > 0 and num > last_text_node_num:
# print('removed post-content', txt)
x.text = ''
continue
n = len(txt)
# remove title
txt_tokens = set(txt.split())
n_matching = len(txt_tokens & title_tokens)
if (n < title_len * 3 and n_matching / len(txt_tokens) > 0.3 and
n_matching / len_title_tokens > 0.3):
# print('removed!', txt)
continue
body_content.append(txt)
links = [x.attrib['href'] for x in tree.xpath('//a')
if 'href' in x.attrib and
x.attrib['href'].startswith(self.domain) and
self.should_save(x.attrib['href'])]
money_amounts = money.find('\n'.join(body_content), 1000) + money.find(title, 1000)
data = {'title': title,
'body': body_content,
'images': images,
'publish_date': str(date),
'author': author,
'cleaned': cleaned_html,
'language': self.detected_language,
'url': url,
'domain': self.domain,
'money': money_amounts,
'summary': '',
'related': get_sorted_links(links, url)[:5]}
if 'overwrite_values_by_xpath' in self.config:
for k, v in self.config['overwrite_values_by_xpath'].items():
new = tree.xpath(v)
data[k] = new[0] if isinstance(new, list) else new
filtered_data = {k: v for k, v in data.items() if k not in exclude_data}
return filtered_data