new_contents: from numpy.random.mtrand import uniform
  from netCDF4_classic import Dataset
  import os
  
  ndim = 100000
  array = uniform(size=(ndim,))
  
  def write_netcdf(filename,zlib,least_significant_digit,data,dtype='f8',shuffle=False,chunking='seq'):
      file = Dataset(filename,'w')
      file.createDimension('n', ndim)
      foo = file.createVariable('data', dtype,('n'),zlib=zlib,least_significant_digit=least_significant_digit,shuffle=shuffle,chunking=chunking)
      foo[:] = data
      file.close()
      file = Dataset(filename)
      data = file.variables['data'][:]
      print data[0:4]
  
  # uncompressed.
  filename = 'uncompressed.nc'
  least_significant_digit = None
  zlib = False
  write_netcdf(filename,zlib,least_significant_digit,array)
  print 'size of uncompressed.nc (no compression) = ',os.stat('uncompressed.nc').st_size
  
  # compressed (lossless, no shuffle).
  filename = 'lossless.nc'
  least_significant_digit = None
  zlib = True
  write_netcdf(filename,zlib,least_significant_digit,array)
  print 'size of lossless.nc (lossless compression, no shuffle) = ',os.stat('lossless.nc').st_size
  
  # compressed (lossless, shuffle).
  filename = 'lossless_s.nc'
  least_significant_digit = None
  zlib = True
  write_netcdf(filename,zlib,least_significant_digit,array,shuffle=True)
  print 'size of lossless_s.nc (lossless compression, with shuffle) = ',os.stat('lossless.nc').st_size
  
  # compressed (lossy, 3 digits, no shuffle).
  filename = 'lossy3.nc'
  least_significant_digit = 3
  zlib = True
  write_netcdf(filename,zlib,least_significant_digit,array)
  print 'size of lossy3.nc (lossy compression, 3 digits, no shuffle) = ',os.stat('lossy3.nc').st_size
  
  # compressed (lossy, 3 digits, with shuffle).
  filename = 'lossy3s.nc'
  least_significant_digit = 3
  zlib = True
  write_netcdf(filename,zlib,least_significant_digit,array,shuffle=True)
  print 'size of lossy3s.nc (lossy compression, 3 digits, shuffle) = ',os.stat('lossy3s.nc').st_size
  
subject: test for compression filters.