def crawl(self, crawl_candidate):
article = Article()
parse_candidate = self.get_parse_candidate(crawl_candidate)
raw_html = self.get_html(crawl_candidate, parse_candidate)
if raw_html is None:
return article
doc = self.get_document(raw_html)
extractor = self.get_extractor()
document_cleaner = self.get_document_cleaner()
output_formatter = self.get_output_formatter()
# article
article.final_url = parse_candidate.url
article.link_hash = parse_candidate.link_hash
article.raw_html = raw_html
article.doc = doc
article.raw_doc = deepcopy(doc)
article.title = extractor.get_title(article)
# TODO
# article.publish_date = config.publishDateExtractor.extract(doc)
# article.additional_data = config.get_additionaldata_extractor.extract(doc)
article.meta_lang = extractor.get_meta_lang(article)
article.meta_favicon = extractor.get_favicon(article)
article.meta_description = extractor.get_meta_description(article)
article.meta_keywords = extractor.get_meta_keywords(article)
article.canonical_link = extractor.get_canonical_link(article)
article.domain = extractor.get_domain(article.final_url)
article.tags = extractor.extract_tags(article)
# # before we do any calcs on the body itself let's clean up the document
article.doc = document_cleaner.clean(article)
# big stuff
article.top_node = extractor.calculate_best_node(article)
if article.top_node is not None:
# video handeling
video_extractor = self.get_video_extractor(article)
video_extractor.get_videos()
# image handeling
if self.config.enable_image_fetching:
image_extractor = self.get_image_extractor(article)
article.top_image = image_extractor.get_best_image(
article.raw_doc, article.top_node)
# post cleanup
article.top_node = extractor.post_cleanup(article.top_node)
# clean_text
article.cleaned_text = output_formatter.get_formatted_text(article)
# cleanup tmp file
self.relase_resources(article)
# extract video info
video_info = self.get_video_info_extractor(article).get_video_info()
if video_info:
article.additional_data['video_info'] = video_info
return article
def crawl(self, crawl_candidate):
article = Article()
parse_candidate = self.get_parse_candidate(crawl_candidate)
raw_html = self.get_html(crawl_candidate, parse_candidate)
if raw_html is None:
return article
doc = self.get_document(raw_html)
extractor = self.get_extractor()
document_cleaner = self.get_document_cleaner()
output_formatter = self.get_output_formatter()
# article
article.final_url = parse_candidate.url
article.link_hash = parse_candidate.link_hash
article.raw_html = raw_html
article.doc = doc
article.raw_doc = deepcopy(doc)
article.title = extractor.get_title(article)
# TODO
# article.publish_date = config.publishDateExtractor.extract(doc)
# article.additional_data = config.get_additionaldata_extractor.extract(doc)
article.meta_lang = extractor.get_meta_lang(article)
article.meta_favicon = extractor.get_favicon(article)
article.meta_description = extractor.get_meta_description(article)
article.meta_keywords = extractor.get_meta_keywords(article)
article.canonical_link = extractor.get_canonical_link(article)
article.domain = extractor.get_domain(article.final_url)
article.tags = extractor.extract_tags(article)
# # before we do any calcs on the body itself let's clean up the document
article.doc = document_cleaner.clean(article)
# big stuff
article.top_node = extractor.calculate_best_node(article)
if article.top_node is not None:
# video handeling
video_extractor = self.get_video_extractor(article)
video_extractor.get_videos()
# image handeling
if self.config.enable_image_fetching:
image_extractor = self.get_image_extractor(article)
article.top_image = image_extractor.get_best_image(article.raw_doc, article.top_node)
# post cleanup
article.top_node = extractor.post_cleanup(article.top_node)
# clean_text
article.cleaned_text = output_formatter.get_formatted_text(article)
# cleanup tmp file
self.relase_resources(article)
# extract video info
video_info = self.get_video_info_extractor(article).get_video_info()
if video_info:
article.additional_data['video_info'] = video_info
return article
def _goose_cleaned_text(cls, html, page_html):
article = Article()
article.raw_html = html
article.raw_doc = page_html
article.doc = article.raw_doc
goose_extractor = ContentExtractor(Configuration(), article)
goose_cleaner = DocumentCleaner(Configuration(), article)
goose_formatter = OutputFormatter(Configuration(), article)
# goose_image_extractor = ImageExtractor(Configuration(), article) use
article.doc = goose_cleaner.clean()
article.top_node = goose_extractor.calculate_best_node()
if article.top_node is not None:
article.top_node = goose_extractor.post_cleanup()
article.cleaned_text = goose_formatter.get_formatted_text()
return article.cleaned_text
def _goose_cleaned_text(cls, html, page_html):
article = Article()
article.raw_html = html
article.raw_doc = page_html
article.doc = article.raw_doc
goose_extractor = ContentExtractor(Configuration(), article)
goose_cleaner = DocumentCleaner(Configuration(), article)
goose_formatter = OutputFormatter(Configuration(), article)
# goose_image_extractor = ImageExtractor(Configuration(), article) use
try:
article.doc = goose_cleaner.clean()
article.top_node = goose_extractor.calculate_best_node()
if article.top_node is not None:
article.top_node = goose_extractor.post_cleanup()
article.cleaned_text = goose_formatter.get_formatted_text()
except UnicodeDecodeError, e:
article.top_node = None
def crawl(self, crawl_candidate):
article = Article()
parse_candidate = self.get_parse_candidate(crawl_candidate)
raw_html = self.get_html(crawl_candidate, parse_candidate)
if raw_html is None:
return article
charset = get_charset(raw_html)
raw_html = raw_html.decode(charset, 'ignore')
pattern = re.compile("[\u4e00-\u9fa5]")
if 'GB2312 GBK GB18030'.find(charset.upper()) != -1 \
or pattern.search(raw_html) is not None:
self.config.stopwords_class = StopWordsChinese
print("中文")
raw_html = clean_tags(raw_html, ['SOHUADCODE', 'script', 'style'])
if charset != 'utf-8':
raw_html = replace_meta_charset(raw_html)
raw_html = force_meta(raw_html)
doc = self.get_document(parse_candidate.url, raw_html)
extractor = self.get_extractor()
document_cleaner = self.get_document_cleaner()
output_formatter = self.get_output_formatter()
# article
article.final_url = parse_candidate.url
article.link_hash = parse_candidate.link_hash
article.raw_html = raw_html
article.doc = doc
article.raw_doc = deepcopy(doc)
article.title = extractor.get_title(article)
# TODO
# article.publish_date = config.publishDateExtractor.extract(doc)
# article.additional_data = config.get_additionaldata_extractor.extract(doc)
article.meta_lang = extractor.get_meta_lang(article)
article.meta_favicon = extractor.get_favicon(article)
article.meta_description = extractor.get_meta_description(article)
article.meta_keywords = extractor.get_meta_keywords(article)
article.canonical_link = extractor.get_canonical_link(article)
article.domain = extractor.get_domain(article.final_url)
article.tags = extractor.extract_tags(article)
# before we do any calcs on the body itself let's clean up the document
article.doc = document_cleaner.clean(article)
# import lxml.html
# lxml.html.open_in_browser(article.doc)
# big stuff
article.top_node = extractor.calculate_best_node(article)
if article.top_node is None:
article.top_node = doc
if article.top_node is not None:
# video handeling
video_extractor = self.get_video_extractor(article)
video_extractor.get_videos()
# image handeling
if self.config.enable_image_fetching:
image_extractor = self.get_image_extractor(article)
article.top_image = image_extractor.get_best_image(
article.raw_doc, article.top_node)
# post cleanup
# article.top_node = extractor.post_cleanup(article.top_node)
# clean_text
article.cleaned_text = output_formatter.get_formatted_text(article)
# import lxml.html
# lxml.html.open_in_browser(article.top_node)
# article.cleaned_text = self.parser.nodeToString(article.top_node)
if article.meta_description is None:
article.meta_description = text_content(
article.cleaned_text)[:150]
# cleanup tmp file
self.relase_resources(article)
return article
def crawl(self, crawl_candidate):
article = Article()
parse_candidate = self.get_parse_candidate(crawl_candidate)
raw_html = self.get_html(crawl_candidate, parse_candidate)
if raw_html is None:
return article
charset = get_charset(raw_html)
raw_html = raw_html.decode(charset, 'ignore')
pattern = re.compile("[\u4e00-\u9fa5]")
if 'GB2312 GBK GB18030'.find(charset.upper()) != -1 \
or pattern.search(raw_html) is not None:
self.config.stopwords_class = StopWordsChinese
print("中文")
raw_html = clean_tags(raw_html, ['SOHUADCODE', 'script', 'style'])
if charset != 'utf-8':
raw_html = replace_meta_charset(raw_html)
raw_html = force_meta(raw_html)
doc = self.get_document(parse_candidate.url, raw_html)
extractor = self.get_extractor()
document_cleaner = self.get_document_cleaner()
output_formatter = self.get_output_formatter()
# article
article.final_url = parse_candidate.url
article.link_hash = parse_candidate.link_hash
article.raw_html = raw_html
article.doc = doc
article.raw_doc = deepcopy(doc)
article.title = extractor.get_title(article)
# TODO
# article.publish_date = config.publishDateExtractor.extract(doc)
# article.additional_data = config.get_additionaldata_extractor.extract(doc)
article.meta_lang = extractor.get_meta_lang(article)
article.meta_favicon = extractor.get_favicon(article)
article.meta_description = extractor.get_meta_description(article)
article.meta_keywords = extractor.get_meta_keywords(article)
article.canonical_link = extractor.get_canonical_link(article)
article.domain = extractor.get_domain(article.final_url)
article.tags = extractor.extract_tags(article)
# before we do any calcs on the body itself let's clean up the document
article.doc = document_cleaner.clean(article)
# import lxml.html
# lxml.html.open_in_browser(article.doc)
# big stuff
article.top_node = extractor.calculate_best_node(article)
if article.top_node is None:
article.top_node = doc
if article.top_node is not None:
# video handeling
video_extractor = self.get_video_extractor(article)
video_extractor.get_videos()
# image handeling
if self.config.enable_image_fetching:
image_extractor = self.get_image_extractor(article)
article.top_image = image_extractor.get_best_image(
article.raw_doc, article.top_node)
# post cleanup
# article.top_node = extractor.post_cleanup(article.top_node)
# clean_text
article.cleaned_text = output_formatter.get_formatted_text(article)
# import lxml.html
# lxml.html.open_in_browser(article.top_node)
# article.cleaned_text = self.parser.nodeToString(article.top_node)
if article.meta_description is None:
article.meta_description = text_content(
article.cleaned_text)[:150]
# cleanup tmp file
self.relase_resources(article)
return article
