5 ms·

I've set up a mirror, should be quite a bit faster ;) http://weblava.net/ycombinator-news20080424.tar.gz http://weblava.net/ycombinator-news20080424.tar.gz

xirium 18y ago
Thank you. You may also want to mirror user data ( http://news.ycombinator.com/item?id=173045 http://news.ycombinator.com/item?id=173045 ).
- mattjaynes 18y ago
  Sure ;) http://weblava.net/ycombinator-news-profile20080424.tar.gz http://weblava.net/ycombinator-news-profile20080424.tar.gz
  - palish 18y ago
    Thank you. For what it's worth, here are additional mirrors. Posts: http://dl.getdropbox.com/u/315/programming/datasets/ycombinator-news20080424.tar.gz http://dl.getdropbox.com/u/315/programming/datasets/ycombina... Profiles: http://dl.getdropbox.com/u/315/programming/datasets/ycombinator-news-profile20080424.tar.gz http://dl.getdropbox.com/u/315/programming/datasets/ycombina...
    - xirium 18y ago
      Thank you. You also want to mirror the update utility ( http://news.ycombinator.com/item?id=173354 http://news.ycombinator.com/item?id=173354 ).
      - palish 18y ago
        You got it: http://dl.getdropbox.com/u/315/programming/datasets/ycombinator-news-update20080424.tar.gz http://dl.getdropbox.com/u/315/programming/datasets/ycombina...
- petercooper 18y ago
  If anyone wants to turn that user data into a CSV of username,age,karma, run this Ruby script in the folder with all the HTML files in it: Dir['*.html'].each do |user_file| user_data = File.read(user_file) user_name = user_file.chomp('.html') age = user_data[/created:<\/td><td>(\d+)/, 1] karma = user_data[/karma:<\/td><td>([\d\-]+)/, 1] puts "#{user_name},#{age},#{karma}" end
  - petercooper 18y ago
    Once you've done that, you can load it into Excel (or Numbers, or whatever) and play with sorting it, adding formulas, and what not. Only semi-interesting one I found was this: Top users by "karma earned per day of membership": Username Age Karma K/A ------------------------------------ dhh 1 48 48 pg 563 17544 31 oldgregg 3 87 29 nickb 429 11672 27 donw 3 52 17 pius 210 2803 13 edw519 428 5316 12 rms 427 5017 11 drm237 271 2851 10 hhm 246 2475 10 keating 10 103 10 sah 42 411 9 freax 5 45 9 further08 2 19 9 The ones who got their karma very quickly are the interesting ones to check out.

xirium 18y ago

Thank you. You may also want to mirror user data ( http://news.ycombinator.com/item?id=173045 http://news.ycombinator.com/item?id=173045 ).

mattjaynes 18y ago
Sure ;) http://weblava.net/ycombinator-news-profile20080424.tar.gz http://weblava.net/ycombinator-news-profile20080424.tar.gz
- palish 18y ago
  Thank you. For what it's worth, here are additional mirrors. Posts: http://dl.getdropbox.com/u/315/programming/datasets/ycombinator-news20080424.tar.gz http://dl.getdropbox.com/u/315/programming/datasets/ycombina... Profiles: http://dl.getdropbox.com/u/315/programming/datasets/ycombinator-news-profile20080424.tar.gz http://dl.getdropbox.com/u/315/programming/datasets/ycombina...
  - xirium 18y ago
    Thank you. You also want to mirror the update utility ( http://news.ycombinator.com/item?id=173354 http://news.ycombinator.com/item?id=173354 ).
    - palish 18y ago
      You got it: http://dl.getdropbox.com/u/315/programming/datasets/ycombinator-news-update20080424.tar.gz http://dl.getdropbox.com/u/315/programming/datasets/ycombina...
petercooper 18y ago
If anyone wants to turn that user data into a CSV of username,age,karma, run this Ruby script in the folder with all the HTML files in it: Dir['*.html'].each do |user_file| user_data = File.read(user_file) user_name = user_file.chomp('.html') age = user_data[/created:<\/td><td>(\d+)/, 1] karma = user_data[/karma:<\/td><td>([\d\-]+)/, 1] puts "#{user_name},#{age},#{karma}" end
- petercooper 18y ago
  Once you've done that, you can load it into Excel (or Numbers, or whatever) and play with sorting it, adding formulas, and what not. Only semi-interesting one I found was this: Top users by "karma earned per day of membership": Username Age Karma K/A ------------------------------------ dhh 1 48 48 pg 563 17544 31 oldgregg 3 87 29 nickb 429 11672 27 donw 3 52 17 pius 210 2803 13 edw519 428 5316 12 rms 427 5017 11 drm237 271 2851 10 hhm 246 2475 10 keating 10 103 10 sah 42 411 9 freax 5 45 9 further08 2 19 9 The ones who got their karma very quickly are the interesting ones to check out.