def postHDF5 (p, post_data):

  # Build the url and then create a hdf5 object
  url = 'http://{}/{}/{}/hdf5/{}/{},{}/{},{}/{},{}/'.format(SITE_HOST, p.token, ','.join(p.channels), p.resolution, *p.args)

  tmpfile = tempfile.NamedTemporaryFile ()
  fh5out = h5py.File ( tmpfile.name )
  for idx, channel_name in enumerate(p.channels):
    chan_grp = fh5out.create_group(channel_name)
    chan_grp.create_dataset("CUTOUT", tuple(post_data[idx,:].shape), post_data[idx,:].dtype, compression='gzip', data=post_data[idx,:])
    chan_grp.create_dataset("CHANNELTYPE", (1,), dtype=h5py.special_dtype(vlen=str), data=p.channel_type)
    chan_grp.create_dataset("DATATYPE", (1,), dtype=h5py.special_dtype(vlen=str), data=p.datatype)
  fh5out.close()
  tmpfile.seek(0)
  return (url, tmpfile.read())
Post data using the hdf5 interface
dataset/ETHPy150Open neurodata/ndstore/test/benchmark.py/postHDF5