old_contents: import random
  import hashlib
  import bisect
  
  
  transparent_pixel = (
      'GIF89a'
      '\x01\x00\x01\x00\x80\x00\x00\xff\xff\xff\x00\x00\x00!\xf9\x04'
      '\x00\x00\x00\x00\x00,\x00\x00\x00\x00\x01\x00\x01\x00\x00\x02'
      '\x02D\x01\x00;')
  
  
  def pixel_tag(path):
      return '<img src="%s" alt="" />' % path
  
  
  def nonce():
      """
      Return a random nonce.
      """
      r = random.random()
      return hashlib.sha1('%.66f' % r).hexdigest()
  
  
  def nonrandom_choice(s, seq):
      """
      Pick an element from ``seq`` according to the value of string ``s``.
      Guaranteed to be deterministic, tries to be uniform.
      """
      return random.Random(s).choice(seq)
  
  
  def nonrandom(s, n):
      """
      Return a deterministic but pseudo-random number between 0 and ``n``.
      """
      return random.Random(s).random() * n
  
  
  def choose_population(s, populations=None):
      """
      Randomly pick an element from populations according to type.
      """
      # Uniform distribution between True, False
      if populations is None:
          return nonrandom_choice(s, (True, False))
  
      # Uniform distribution over populations
      if isinstance(populations, list):
          return nonrandom_choice(s, populations)
  
      # Weighted distribution over populations
      if isinstance(populations, dict):
          pop_name = []
          pop_mass = []
          running_mass = 0
          for name, mass in populations.iteritems():
              if mass > 0:
                  pop_name.append(name)
                  pop_mass.append(running_mass)
                  running_mass += mass
  
          if running_mass == 0:
              raise ValueError("Need at least one option with probability > 0")
  
          r = nonrandom(s, running_mass)
          i = bisect.bisect(pop_mass, r) - 1
          return pop_name[i]
  
      raise ValueError("Invalid population description")
  
new_contents: import os
  import random
  import hashlib
  import bisect
  
  
  transparent_pixel = (
      'GIF89a'
      '\x01\x00\x01\x00\x80\x00\x00\xff\xff\xff\x00\x00\x00!\xf9\x04'
      '\x00\x00\x00\x00\x00,\x00\x00\x00\x00\x01\x00\x01\x00\x00\x02'
      '\x02D\x01\x00;')
  
  
  def pixel_tag(path):
      return '<img src="%s" alt="" />' % path
  
  
  def nonce():
      """
      Return a random nonce, 160 bits long as a hex string.
      """
      return os.urandom(20).encode('hex')
  
  
  def nonrandom_choice(s, seq):
      """
      Pick an element from ``seq`` according to the value of string ``s``.
      Guaranteed to be deterministic, tries to be uniform.
      """
      return random.Random(s).choice(seq)
  
  
  def nonrandom(s, n):
      """
      Return a deterministic but pseudo-random number between 0 and ``n``.
      """
      return random.Random(s).random() * n
  
  
  def choose_population(s, populations=None):
      """
      Randomly pick an element from populations according to type.
      """
      # Uniform distribution between True, False
      if populations is None:
          return nonrandom_choice(s, (True, False))
  
      # Uniform distribution over populations
      if isinstance(populations, list):
          return nonrandom_choice(s, populations)
  
      # Weighted distribution over populations
      if isinstance(populations, dict):
          pop_name = []
          pop_mass = []
          running_mass = 0
          for name, mass in populations.iteritems():
              if mass > 0:
                  pop_name.append(name)
                  pop_mass.append(running_mass)
                  running_mass += mass
  
          if running_mass == 0:
              raise ValueError("Need at least one option with probability > 0")
  
          r = nonrandom(s, running_mass)
          i = bisect.bisect(pop_mass, r) - 1
          return pop_name[i]
  
      raise ValueError("Invalid population description")
  
subject: use os.urandom() for visitor id nonce