Problem of the Day
A new programming or logic puzzle every Mon-Fri

Problem of the Day has a large overlap with the Reddit community. Let's put that overlap to use and create a program that counts the number of total subreddits. You can use this API https://www.reddit.com/dev/api#GET_subreddits_new to traverse the Reddit database.

Comments:

• Kevin Benton - 9 years, 10 months ago

  This takes forever to complete because of API rate-limiting. Here is a python solution that uses multiple coroutines to connect multiple times but the server is actually the limiting factor here:

  import eventlet
  import json
  import random
  import requests
  
  
  # use different front-ends (found from dns lookup)
  # so crawlers aren't hitting the same server all
  # of the time.
  reddit_addresses = [
      '198.41.209.140',
      '198.41.208.141',
      '198.41.209.141',
      '198.41.208.142',
      '198.41.208.140',
      '198.41.209.139',
      '198.41.209.138',
      '198.41.209.142',
      '198.41.209.136',
      '198.41.208.139',
      '198.41.208.138',
      '198.41.208.143',
      '198.41.209.143',
      '198.41.209.137',
      '198.41.208.137'
  ]
  
  
  def get_next_data(after, sort_order='new', retries=10):
      url = 'http://%s/subreddits/%s.json?limit=100' % (
          random.choice(reddit_addresses), sort_order
      )
      if after:
          url += '&after=%s' % after
      try:
          r = requests.get(url, headers={'User-Agent': '%030x' % random.randrange(16**30),
                                         'Host': 'www.reddit.com'})
          d = json.loads(r.text)['data']
      except:
          try:
              print 'json loading of following failed: %s' % r.text
          except:
              print 'failed to connect %s' % r
          if not retries:
              return None
          return get_next_data(after, sort_order, retries-1)
      return d
  
  
  def crawl_until_duplicate_or_end(subreddits, after):
      while True:
          d = get_next_data(after)
          after = d['after']
          names = set(map(lambda x: x['data']['display_name'], d['children']))
          print names
          # keep going if any members are unique
          if names.issubset(subreddits):
              return names
          subreddits.update(names)
          print "new set size %s" % len(subreddits)
          if not after:
              return names
  
  
  def multicrawl_names(names):
      # use eventlet to bound number of crawlers
      pool = eventlet.greenpool.GreenPool(size=len(reddit_addresses))
      results = []
      for n in names:
          results.append(pool.spawn(crawl_until_duplicate_or_end, subreddits, n))
      return map(lambda r: r.wait(), results)
  
  
  if __name__ == '__main__':
      # seed workers using popular subreddits. then work by age from each one
      # until it hits a point where another has already crawled
  
      top = get_next_data(None, sort_order='popular')
      top_names = map(lambda x: x['data']['name'], top['children'])
      top_names.append('programming')
      subreddits = set()
      ends = multicrawl_names(top_names)
      sanity_count = 0
      # everything should be crawled, but retry the ends again to verify
      while sanity_count != len(subreddits):
          sanity_count = len(subreddits)
          map(multicrawl_names, ends)
      print "found %s total subreddits" % len(subreddits)
  

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• Max Burstein - 9 years, 10 months ago

  Yea since I don't think you can guess the hash it makes it tough to do in parallel.

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• Kevin Benton - 9 years, 10 months ago

  Forgot to put the estimate this stopped (or got blocked at). 510149 subreddits.

  Seems kinda low based on the ages of the ones that were going by in the output around 300k.

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