python-readability/readability/readability.py

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#!/usr/bin/env python
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import logging
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import re
import sys
from collections import defaultdict
from lxml.etree import tostring
from lxml.etree import tounicode
from lxml.html import document_fromstring
from lxml.html import fragment_fromstring
from cleaners import clean_attributes
from cleaners import html_cleaner
from htmls import build_doc
from htmls import get_body
from htmls import get_title
from htmls import shorten_title
logging.basicConfig(level=logging.INFO)
log = logging.getLogger()
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REGEXES = {
'unlikelyCandidatesRe': re.compile('combx|comment|community|disqus|extra|foot|header|menu|remark|rss|shoutbox|sidebar|sponsor|ad-break|agegate|pagination|pager|popup|tweet|twitter', re.I),
'okMaybeItsACandidateRe': re.compile('and|article|body|column|main|shadow', re.I),
'positiveRe': re.compile('article|body|content|entry|hentry|main|page|pagination|post|text|blog|story', re.I),
'negativeRe': re.compile('combx|comment|com-|contact|foot|footer|footnote|masthead|media|meta|outbrain|promo|related|scroll|shoutbox|sidebar|sponsor|shopping|tags|tool|widget', re.I),
'divToPElementsRe': re.compile('<(a|blockquote|dl|div|img|ol|p|pre|table|ul)', re.I),
#'replaceBrsRe': re.compile('(<br[^>]*>[ \n\r\t]*){2,}',re.I),
#'replaceFontsRe': re.compile('<(\/?)font[^>]*>',re.I),
#'trimRe': re.compile('^\s+|\s+$/'),
#'normalizeRe': re.compile('\s{2,}/'),
#'killBreaksRe': re.compile('(<br\s*\/?>(\s|&nbsp;?)*){1,}/'),
#'videoRe': re.compile('http:\/\/(www\.)?(youtube|vimeo)\.com', re.I),
#skipFootnoteLink: /^\s*(\[?[a-z0-9]{1,2}\]?|^|edit|citation needed)\s*$/i,
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}
class Unparseable(ValueError):
pass
def describe(node, depth=1):
if not hasattr(node, 'tag'):
return "[%s]" % type(node)
name = node.tag
if node.get('id', ''):
name += '#' + node.get('id')
if node.get('class', ''):
name += '.' + node.get('class').replace(' ', '.')
if name[:4] in ['div#', 'div.']:
name = name[3:]
if depth and node.getparent() is not None:
return name + ' - ' + describe(node.getparent(), depth - 1)
return name
def to_int(x):
if not x:
return None
x = x.strip()
if x.endswith('px'):
return int(x[:-2])
if x.endswith('em'):
return int(x[:-2]) * 12
return int(x)
def clean(text):
text = re.sub('\s*\n\s*', '\n', text)
text = re.sub('[ \t]{2,}', ' ', text)
return text.strip()
def text_length(i):
return len(clean(i.text_content() or ""))
regexp_type = type(re.compile('hello, world'))
def compile_pattern(elements):
if not elements:
return None
if isinstance(elements, regexp_type):
return elements
if isinstance(elements, basestring):
elements = elements.split(',')
return re.compile(u'|'.join([re.escape(x.lower()) for x in elements]), re.U)
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class Document:
"""Class to build a etree document out of html."""
TEXT_LENGTH_THRESHOLD = 25
RETRY_LENGTH = 250
def __init__(self, input, positive_keywords=None, negative_keywords=None, **options):
"""Generate the document
:param input: string of the html content.
kwargs:
- attributes:
- debug: output debug messages
- min_text_length:
- retry_length:
- url: will allow adjusting links to be absolute
- positive_keywords: the list of positive search patterns in classes and ids, for example: ["news-item", "block"]
- negative_keywords: the list of negative search patterns in classes and ids, for example: ["mysidebar", "related", "ads"]
Also positive_keywords and negative_keywords could be a regexp.
"""
self.input = input
self.options = options
self.html = None
self.encoding = None
self.positive_keywords = compile_pattern(positive_keywords)
self.negative_keywords = compile_pattern(negative_keywords)
def _html(self, force=False):
if force or self.html is None:
self.html = self._parse(self.input)
return self.html
def _parse(self, input):
doc, self.encoding = build_doc(input)
doc = html_cleaner.clean_html(doc)
base_href = self.options.get('url', None)
if base_href:
doc.make_links_absolute(base_href, resolve_base_href=True)
else:
doc.resolve_base_href()
return doc
def content(self):
return get_body(self._html(True))
def title(self):
return get_title(self._html(True))
def short_title(self):
return shorten_title(self._html(True))
def get_clean_html(self):
return clean_attributes(tounicode(self.html))
def summary(self, html_partial=False):
"""Generate the summary of the html docuemnt
:param html_partial: return only the div of the document, don't wrap
in html and body tags.
"""
try:
ruthless = True
while True:
self._html(True)
for i in self.tags(self.html, 'script', 'style'):
i.drop_tree()
for i in self.tags(self.html, 'body'):
i.set('id', 'readabilityBody')
if ruthless:
self.remove_unlikely_candidates()
self.transform_misused_divs_into_paragraphs()
candidates = self.score_paragraphs()
best_candidate = self.select_best_candidate(candidates)
if best_candidate:
article = self.get_article(candidates, best_candidate,
html_partial=html_partial)
else:
if ruthless:
log.debug("ruthless removal did not work. ")
ruthless = False
self.debug(
("ended up stripping too much - "
"going for a safer _parse"))
# try again
continue
else:
log.debug(
("Ruthless and lenient parsing did not work. "
"Returning raw html"))
article = self.html.find('body')
if article is None:
article = self.html
cleaned_article = self.sanitize(article, candidates)
article_length = len(cleaned_article or '')
retry_length = self.options.get(
'retry_length',
self.RETRY_LENGTH)
of_acceptable_length = article_length >= retry_length
if ruthless and not of_acceptable_length:
ruthless = False
# Loop through and try again.
continue
else:
return cleaned_article
except StandardError, e:
log.exception('error getting summary: ')
raise Unparseable(str(e)), None, sys.exc_info()[2]
def get_article(self, candidates, best_candidate, html_partial=False):
# Now that we have the top candidate, look through its siblings for
# content that might also be related.
# Things like preambles, content split by ads that we removed, etc.
sibling_score_threshold = max([
10,
best_candidate['content_score'] * 0.2])
# create a new html document with a html->body->div
if html_partial:
output = fragment_fromstring('<div/>')
else:
output = document_fromstring('<div/>')
best_elem = best_candidate['elem']
for sibling in best_elem.getparent().getchildren():
# in lxml there no concept of simple text
# if isinstance(sibling, NavigableString): continue
append = False
if sibling is best_elem:
append = True
sibling_key = sibling # HashableElement(sibling)
if sibling_key in candidates and \
candidates[sibling_key]['content_score'] >= sibling_score_threshold:
append = True
if sibling.tag == "p":
link_density = self.get_link_density(sibling)
node_content = sibling.text or ""
node_length = len(node_content)
if node_length > 80 and link_density < 0.25:
append = True
elif node_length <= 80 \
and link_density == 0 \
and re.search('\.( |$)', node_content):
append = True
if append:
# We don't want to append directly to output, but the div
# in html->body->div
if html_partial:
output.append(sibling)
else:
output.getchildren()[0].getchildren()[0].append(sibling)
#if output is not None:
# output.append(best_elem)
return output
def select_best_candidate(self, candidates):
sorted_candidates = sorted(candidates.values(), key=lambda x: x['content_score'], reverse=True)
for candidate in sorted_candidates[:5]:
elem = candidate['elem']
self.debug("Top 5 : %6.3f %s" % (
candidate['content_score'],
describe(elem)))
if len(sorted_candidates) == 0:
return None
best_candidate = sorted_candidates[0]
return best_candidate
def get_link_density(self, elem):
link_length = 0
for i in elem.findall(".//a"):
link_length += text_length(i)
#if len(elem.findall(".//div") or elem.findall(".//p")):
# link_length = link_length
total_length = text_length(elem)
return float(link_length) / max(total_length, 1)
def score_paragraphs(self, ):
MIN_LEN = self.options.get(
'min_text_length',
self.TEXT_LENGTH_THRESHOLD)
candidates = {}
ordered = []
for elem in self.tags(self._html(), "p", "pre", "td"):
parent_node = elem.getparent()
if parent_node is None:
continue
grand_parent_node = parent_node.getparent()
inner_text = clean(elem.text_content() or "")
inner_text_len = len(inner_text)
# If this paragraph is less than 25 characters
# don't even count it.
if inner_text_len < MIN_LEN:
continue
if parent_node not in candidates:
candidates[parent_node] = self.score_node(parent_node)
ordered.append(parent_node)
if grand_parent_node is not None and grand_parent_node not in candidates:
candidates[grand_parent_node] = self.score_node(
grand_parent_node)
ordered.append(grand_parent_node)
content_score = 1
content_score += len(inner_text.split(','))
content_score += min((inner_text_len / 100), 3)
#if elem not in candidates:
# candidates[elem] = self.score_node(elem)
#WTF? candidates[elem]['content_score'] += content_score
candidates[parent_node]['content_score'] += content_score
if grand_parent_node is not None:
candidates[grand_parent_node]['content_score'] += content_score / 2.0
# Scale the final candidates score based on link density. Good content
# should have a relatively small link density (5% or less) and be
# mostly unaffected by this operation.
for elem in ordered:
candidate = candidates[elem]
ld = self.get_link_density(elem)
score = candidate['content_score']
self.debug("Candid: %6.3f %s link density %.3f -> %6.3f" % (
score,
describe(elem),
ld,
score * (1 - ld)))
candidate['content_score'] *= (1 - ld)
return candidates
def class_weight(self, e):
weight = 0
for feature in [e.get('class', None), e.get('id', None)]:
if feature:
if REGEXES['negativeRe'].search(feature):
weight -= 25
if REGEXES['positiveRe'].search(feature):
weight += 25
if self.positive_keywords and self.positive_keywords.search(feature):
weight += 25
if self.negative_keywords and self.negative_keywords.search(feature):
weight -= 25
if self.positive_keywords and self.positive_keywords.match('tag-'+e.tag):
weight += 25
if self.negative_keywords and self.negative_keywords.match('tag-'+e.tag):
weight -= 25
return weight
def score_node(self, elem):
content_score = self.class_weight(elem)
name = elem.tag.lower()
if name == "div":
content_score += 5
elif name in ["pre", "td", "blockquote"]:
content_score += 3
elif name in ["address", "ol", "ul", "dl", "dd", "dt", "li", "form"]:
content_score -= 3
elif name in ["h1", "h2", "h3", "h4", "h5", "h6", "th"]:
content_score -= 5
return {
'content_score': content_score,
'elem': elem
}
def debug(self, *a):
if self.options.get('debug', False):
log.debug(*a)
def remove_unlikely_candidates(self):
for elem in self.html.iter():
s = "%s %s" % (elem.get('class', ''), elem.get('id', ''))
if len(s) < 2:
continue
#self.debug(s)
if REGEXES['unlikelyCandidatesRe'].search(s) and (not REGEXES['okMaybeItsACandidateRe'].search(s)) and elem.tag not in ['html', 'body']:
self.debug("Removing unlikely candidate - %s" % describe(elem))
elem.drop_tree()
def transform_misused_divs_into_paragraphs(self):
for elem in self.tags(self.html, 'div'):
# transform <div>s that do not contain other block elements into
# <p>s
#FIXME: The current implementation ignores all descendants that
# are not direct children of elem
# This results in incorrect results in case there is an <img>
# buried within an <a> for example
if not REGEXES['divToPElementsRe'].search(
unicode(''.join(map(tostring, list(elem))))):
#self.debug("Altering %s to p" % (describe(elem)))
elem.tag = "p"
#print "Fixed element "+describe(elem)
for elem in self.tags(self.html, 'div'):
if elem.text and elem.text.strip():
p = fragment_fromstring('<p/>')
p.text = elem.text
elem.text = None
elem.insert(0, p)
#print "Appended "+tounicode(p)+" to "+describe(elem)
for pos, child in reversed(list(enumerate(elem))):
if child.tail and child.tail.strip():
p = fragment_fromstring('<p/>')
p.text = child.tail
child.tail = None
elem.insert(pos + 1, p)
#print "Inserted "+tounicode(p)+" to "+describe(elem)
if child.tag == 'br':
#print 'Dropped <br> at '+describe(elem)
child.drop_tree()
def tags(self, node, *tag_names):
for tag_name in tag_names:
for e in node.findall('.//%s' % tag_name):
yield e
def reverse_tags(self, node, *tag_names):
for tag_name in tag_names:
for e in reversed(node.findall('.//%s' % tag_name)):
yield e
def sanitize(self, node, candidates):
MIN_LEN = self.options.get('min_text_length',
self.TEXT_LENGTH_THRESHOLD)
for header in self.tags(node, "h1", "h2", "h3", "h4", "h5", "h6"):
if self.class_weight(header) < 0 or self.get_link_density(header) > 0.33:
header.drop_tree()
for elem in self.tags(node, "form", "iframe", "textarea"):
elem.drop_tree()
allowed = {}
# Conditionally clean <table>s, <ul>s, and <div>s
for el in self.reverse_tags(node, "table", "ul", "div"):
if el in allowed:
continue
weight = self.class_weight(el)
if el in candidates:
content_score = candidates[el]['content_score']
#print '!',el, '-> %6.3f' % content_score
else:
content_score = 0
tag = el.tag
if weight + content_score < 0:
self.debug("Cleaned %s with score %6.3f and weight %-3s" %
(describe(el), content_score, weight, ))
el.drop_tree()
elif el.text_content().count(",") < 10:
counts = {}
for kind in ['p', 'img', 'li', 'a', 'embed', 'input']:
counts[kind] = len(el.findall('.//%s' % kind))
counts["li"] -= 100
# Count the text length excluding any surrounding whitespace
content_length = text_length(el)
link_density = self.get_link_density(el)
parent_node = el.getparent()
if parent_node is not None:
if parent_node in candidates:
content_score = candidates[parent_node]['content_score']
else:
content_score = 0
#if parent_node is not None:
#pweight = self.class_weight(parent_node) + content_score
#pname = describe(parent_node)
#else:
#pweight = 0
#pname = "no parent"
to_remove = False
reason = ""
#if el.tag == 'div' and counts["img"] >= 1:
# continue
if counts["p"] and counts["img"] > counts["p"]:
reason = "too many images (%s)" % counts["img"]
to_remove = True
elif counts["li"] > counts["p"] and tag != "ul" and tag != "ol":
reason = "more <li>s than <p>s"
to_remove = True
elif counts["input"] > (counts["p"] / 3):
reason = "less than 3x <p>s than <input>s"
to_remove = True
elif content_length < (MIN_LEN) and (counts["img"] == 0 or counts["img"] > 2):
reason = "too short content length %s without a single image" % content_length
to_remove = True
elif weight < 25 and link_density > 0.2:
reason = "too many links %.3f for its weight %s" % (
link_density, weight)
to_remove = True
elif weight >= 25 and link_density > 0.5:
reason = "too many links %.3f for its weight %s" % (
link_density, weight)
to_remove = True
elif (counts["embed"] == 1 and content_length < 75) or counts["embed"] > 1:
reason = "<embed>s with too short content length, or too many <embed>s"
to_remove = True
# if el.tag == 'div' and counts['img'] >= 1 and to_remove:
# imgs = el.findall('.//img')
# valid_img = False
# self.debug(tounicode(el))
# for img in imgs:
#
# height = img.get('height')
# text_length = img.get('text_length')
# self.debug ("height %s text_length %s" %(repr(height), repr(text_length)))
# if to_int(height) >= 100 or to_int(text_length) >= 100:
# valid_img = True
# self.debug("valid image" + tounicode(img))
# break
# if valid_img:
# to_remove = False
# self.debug("Allowing %s" %el.text_content())
# for desnode in self.tags(el, "table", "ul", "div"):
# allowed[desnode] = True
#find x non empty preceding and succeeding siblings
i, j = 0, 0
x = 1
siblings = []
for sib in el.itersiblings():
#self.debug(sib.text_content())
sib_content_length = text_length(sib)
if sib_content_length:
i =+ 1
siblings.append(sib_content_length)
if i == x:
break
for sib in el.itersiblings(preceding=True):
#self.debug(sib.text_content())
sib_content_length = text_length(sib)
if sib_content_length:
j =+ 1
siblings.append(sib_content_length)
if j == x:
break
#self.debug(str(siblings))
if siblings and sum(siblings) > 1000:
to_remove = False
self.debug("Allowing %s" % describe(el))
for desnode in self.tags(el, "table", "ul", "div"):
allowed[desnode] = True
if to_remove:
self.debug("Cleaned %6.3f %s with weight %s cause it has %s." %
(content_score, describe(el), weight, reason))
#print tounicode(el)
#self.debug("pname %s pweight %.3f" %(pname, pweight))
el.drop_tree()
for el in ([node] + [n for n in node.iter()]):
if not self.options.get('attributes', None):
#el.attrib = {} #FIXME:Checkout the effects of disabling this
pass
self.html = node
return self.get_clean_html()
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class HashableElement():
def __init__(self, node):
self.node = node
self._path = None
def _get_path(self):
if self._path is None:
reverse_path = []
node = self.node
while node is not None:
node_id = (node.tag, tuple(node.attrib.items()), node.text)
reverse_path.append(node_id)
node = node.getparent()
self._path = tuple(reverse_path)
return self._path
path = property(_get_path)
def __hash__(self):
return hash(self.path)
def __eq__(self, other):
return self.path == other.path
def __getattr__(self, tag):
return getattr(self.node, tag)
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def main():
from optparse import OptionParser
parser = OptionParser(usage="%prog: [options] [file]")
parser.add_option('-v', '--verbose', action='store_true')
parser.add_option('-u', '--url', default=None, help="use URL instead of a local file")
parser.add_option('-p', '--positive-keywords', default=None, help="positive keywords (separated with comma)", action='store')
parser.add_option('-n', '--negative-keywords', default=None, help="negative keywords (separated with comma)", action='store')
(options, args) = parser.parse_args()
if not (len(args) == 1 or options.url):
parser.print_help()
sys.exit(1)
file = None
if options.url:
import urllib
file = urllib.urlopen(options.url)
else:
file = open(args[0], 'rt')
enc = sys.__stdout__.encoding or 'utf-8' # XXX: this hack could not always work, better to set PYTHONIOENCODING
try:
print Document(file.read(),
debug=options.verbose,
url=options.url,
positive_keywords = options.positive_keywords,
negative_keywords = options.negative_keywords,
).summary().encode(enc, 'replace')
finally:
file.close()
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if __name__ == '__main__':
main()