new_contents: #!/usr/bin/env python
  import os
  import sys
  import re
  ''' ideally you get a set of good hits from QA when they release a site to production
      Most things aren't ideal, so here's a way to simply separate likely good from likely bad
      based on http status return codes
  '''
  
  inputfile=sys.argv[1]
  goodfile=open('{0}.good'.format(inputfile),'wb')
  badfile=open('{0}.bad'.format(inputfile),'wb')
  
  
  apachequotedfieldsre=re.compile(r'''"(.*?)"''')     #get fields delimited by ""
  apachestatusre=re.compile(r''' ([0-9]{3}) ''')      #get 3 digit http status field
  
  for line in open(inputfile).readlines():
      if len(apachestatusre.findall(line))>0:
          if int(apachestatusre.findall(line)[0])<400:
              goodfile.write('{0}\n'.format(apachequotedfieldsre.findall(line)[0].replace('GET ',''))) #url only.
          else:
              #write HTTP verb, status code and url to help our machine learning.
              badfile.write('{0} {1}\n'.format( int(apachestatusre.findall(line)[0]), ' '.join(apachequotedfieldsre.findall(line)[0:1])))
  
  goodfile.close()
  badfile.close()
subject: add simple script to parse apache logs by http status code into good/bad