title: Create Great Parser - Extract Relevant Text From HTML/Blogs
body: <p>I'm trying to create a generalized HTML parser that works well on Blog Posts. I want to point my parser at the specific entrie's URL and get back clean text of the post itself. My basic approach (from python) has been to use a combination of BeautifulSoup / Urllib2, which is okay, but it assumes you know the proper tags for the blog entry. Does anyone have any better ideas?</p>
  
  <p>Here are some thoughts maybe someone could expand upon, that I don't have enough knowledge/know-how yet to implement.</p>
  
  <ol>
  <li><p>The unix program 'lynx' seems to parse blog posts especially well - what parser do they use, or how could this be utilized?</p></li>
  <li><p>Are there any services/parsers that automatically remove junk ads, etc?</p></li>
  <li><p>In this case, i had a vague notion that it may be an okay assumption that blog posts  are usually contained in a certain defining tag with class="entry" or something similar. Thus, it may be possible to create an algorithm that found the enclosing tags with the most clean text between them - any ideas on this?</p></li>
  </ol>
  
  <p>Thanks!</p>