new_contents: 
  """
      Demonstrates how to use h5py with the multiprocessing module.
  
      This module implements a simple multi-process program to generate
      Mandelbrot set images.  It uses a process pool to do the computations,
      and a single process to save the results to file.
  
      Importantly, only one process actually reads/writes the HDF5 file.
      Remember that when a process is fork()ed, the child inherits the HDF5
      state from its parent, which can be dangerous if you already have a file
      open.  Trying to interact with the same file on disk from multiple
      processes results in undefined behavior.
  
      If matplotlib is available, the program will read from the HDF5 file and
      display an image of the fractal in a window.  To re-run the calculation,
      delete the file "mandelbrot.hdf5".
  
  """
  
  from __future__ import print_function
  
  import numpy as np
  import multiprocessing as mp
  import h5py
  
  # === Parameters for Mandelbrot calculation ===================================
  
  NX = 512
  NY = 512
  ESCAPE = 1000
  
  XSTART = -0.16070135 - 5e-8
  YSTART =  1.0375665 -5e-8
  XEXTENT = 1.0E-7
  YEXTENT = 1.0E-7
  
  xincr = XEXTENT*1.0/NX
  yincr = YEXTENT*1.0/NY
  
  # === Functions to compute set ================================================
  
  def compute_escape(pos):
      """ Compute the number of steps required to escape from a point on the
      complex plane """
      z = 0+0j;
      for i in xrange(ESCAPE):
          z = z**2 + pos
          if abs(z) > 2:
              break
      return i
  
  def compute_row(xpos):
      """ Compute a 1-D array containing escape step counts for each y-position.
      """
      a = np.ndarray((NY,), dtype='i')
      for y in xrange(NY):
          pos = complex(XSTART,YSTART) + complex(xpos, y*yincr)
          a[y] = compute_escape(pos)
      return a
  
  # === Functions to run process pool & visualize ===============================
  
  def run_calculation():
      """ Begin multi-process calculation, and save to file """
  
      print("Creating %d-process pool" % mp.cpu_count())
  
      pool = mp.Pool(mp.cpu_count())
  
      f = h5py.File('mandelbrot.hdf5','w')
  
      print("Creating output dataset with shape %s x %s" % (NX, NY))
  
      dset = f.create_dataset('mandelbrot', (NX,NY), 'i')
      dset.attrs['XSTART'] = XSTART
      dset.attrs['YSTART'] = YSTART
      dset.attrs['XEXTENT'] = XEXTENT
      dset.attrs['YEXTENT'] = YEXTENT
      
      result = pool.imap(compute_row, (x*xincr for x in xrange(NX)))
  
      for idx, arr in enumerate(result):
          if idx%25 == 0: print("Recording row %s" % idx)
          dset[idx] = arr
  
      print("Closing HDF5 file")
  
      f.close()
  
      print("Shutting down process pool")
  
      pool.close()
      pool.join()
  
  def visualize_file():
      """ Open the HDF5 file and display the result """
      try:
          import pylab as p
      except ImportError:
          print("Whoops! Matplotlib is required to view the fractal.")
          raise
  
      f = h5py.File('mandelbrot.hdf5','r')
      dset = f['mandelbrot']
      a = dset[...]
      p.imshow(a.transpose())
  
      print("Displaying fractal. Close window to exit program.")
      try:
          p.show()
      finally:
          f.close()
  
  if __name__ == '__main__':
      if not h5py.is_hdf5('mandelbrot.hdf5'):
          run_calculation()
      else:
          print('Fractal found in "mandelbrot.hdf5". Delete file to re-run calculation.')
      visualize_file()
  
  
  
  
subject: Add examples folder