mirror of
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71 lines
2.7 KiB
Python
71 lines
2.7 KiB
Python
#!/usr/bin/env python
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# vim:fileencoding=UTF-8:ts=4:sw=4:sta:et:sts=4:ai
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from __future__ import with_statement
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__license__ = 'GPL v3'
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__copyright__ = '2009, Kovid Goyal <kovid@kovidgoyal.net>'
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__docformat__ = 'restructuredtext en'
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from calibre.web.feeds.news import BasicNewsRecipe
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from calibre.ebooks.BeautifulSoup import BeautifulSoup
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class KellogFaculty(BasicNewsRecipe):
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title = 'Kellog Faculty Blogs'
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__author__ = 'Kovid Goyal'
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description = 'Blogs of the Kellog School of Management Faculty'
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no_stylesheets = True
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encoding = 'utf-8'
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language = 'en'
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remove_tags_before = {'name':'h2'}
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remove_tags_after = {'class':'col-two-text'}
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def parse_index(self):
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soup = self.index_to_soup('http://www.kellogg.northwestern.edu/Faculty/Blogroll.aspx')
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feeds, articles = [], []
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feed_title = None
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main = soup.find(id='bodyCopy')
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for tag in main.findAll(['h3', 'div']):
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if tag.name == 'h3':
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title = self.tag_to_string(tag).capitalize()
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a = tag.find('a', href=True)
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if articles and feed_title:
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feeds.append((feed_title, articles))
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articles = []
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# Keep only blogs hosted on the Kellog servers
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feed_title = title if a and 'insight.kellog' in a['href'] else None
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elif tag.name == 'div' and tag.get('class', '') == 'rssfeed':
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script = tag.find('script', src=True)
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text = \
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self.browser.open(script['src']).read().replace('document.write(',
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'')[:-2]
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text = eval(text)
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asoup = BeautifulSoup(text)
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for tag in asoup.findAll('div',
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attrs={'class':'rssincl-entry'}):
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title = self.tag_to_string(tag.find(attrs={'class':'rssincl-itemtitle'}))
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try:
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desc = self.tag_to_string(tag.find(attrs={'class':'rssincl-itemdesc'}))
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except:
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desc = ''
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url = tag.find('a', href=True)['href']
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articles.append({
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'title':title.strip(), 'url':url, 'description':desc.strip(), 'date':''
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})
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return feeds
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def postprocess_html(self, soup, first_fetch):
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for tag in soup.findAll(style=True):
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del tag['style']
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head = soup.find('head')
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if head is not None:
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for p in head.findAll('p'): p.extract()
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for meta in soup.findAll('meta', attrs={'name':'description'}): meta.extract()
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for t in head.findAll(text=True): t.extract()
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return soup
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