title: python multiprocessing apply_async only uses one process
body: <p>I have a script that includes opening a file from a list and then doing something to the text within that file. I'm using python multiprocessing and Pool to try to parallelize this operation. A abstraction of the script is below:</p>
  
  <pre><code>import os
  from multiprocessing import Pool
  
  results = []
  def testFunc(files):
      for file in files:
          print "Working in Process #%d" % (os.getpid())
          #This is just an illustration of some logic. This is not what I'm actually doing.
          for line in file:
              if 'dog' in line:
                  results.append(line)
  
  if __name__=="__main__":
      p = Pool(processes=2)
      files = ['/path/to/file1.txt', '/path/to/file2.txt']
      results = p.apply_async(testFunc, args = (files,))
      results2 = results.get()
  </code></pre>
  
  <p>When I run this the print out of the process id is the same for each iteration. Basically what I'm trying to do is take each element of the input list and fork it out to a separate process, but it seems like one process is doing all of the work. </p>