title: Python Simple Loop Parallelization Jupyter Notebook
body: <p>I am trying to parallelize a simple python loop using Jupyter Notebook. I tried to use <code>Pool</code> but it just hangs forever and I have to kill the notebook to stop it.</p>
  
  <pre><code>def process_frame(f):
      new_dict = dict()
      pc_dict = calculate_area(fl)
      for key in pc_dict:
          if key not in new_dict:
              new_dict[key] = 0
          new_dict[key] = float(sum(pc_dict[key]))
      full_pc_dict[fl] = new_dict
  </code></pre>
  
  <p><code>frames_list = [0, 1, 2, 3, 4, 5, 6]</code></p>
  
  <p>I want to <code>process_frame</code> for each frame in the <code>frames_list</code>.</p>
  
  <p>Note that the final outcome should be a dict with all the outputs from <code>process_frame</code>. I don't know if appending it at the end of the function may be a good idea. </p>
  
  <p>Any suggestion on how to do this using Jupyter Notebook? Also, is it possible to have <code>tqdm</code> working with this parallel processing?</p>
  
  <p>Kind regards</p>