When splitting your task into multiple jobs, you’ll need a way to merge the output files. ROOT allows you to merge files using the hadd program. It finds the histograms and trees from multiple ROOT files and merges them, resulting in a single ROOT file.

As I started to move away from ROOT into the Python environment, I kind of missed hadd. So I wrote a script that emulates it to merge numpy arrays from multiple .npz files. It can be used in the following way (I named the script as hadd_npz.py):

python hadd_npz.py out_add.npz out_*.npz

The script (hadd_npz.py):

#!/usr/bin/env python

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import numpy as np
import os
import six

class Hadd(object):
  """Merge arrays from multiple .npz files.

  It emulates the interface of the utility 'hadd' in ROOT
  (see <https://root.cern.ch/how/how-merge-histogram-files>).
  def __init__(self):
    self.d = {}
    self.dout = {}

  def process(self, target, source, force=False):
    print('hadd Target file: {}'.format(target))

    if not force:
      if os.path.isfile(target):
        msg = 'hadd error opening target file (does {} exist?).\n'.format(target)
        msg += 'Pass "-f" argument to force re-creation of output file.'
        raise ValueError(msg)

    # Loop over the source files
    for i, s in enumerate(source):
      print('hadd Source file {}: {}'.format(i + 1, s))
      with np.load(s) as loaded:
        # Insert the keys
        if i == 0:
          for k in loaded.files:
            self.d[k] = []
        # Keep the arrays
        for k in loaded.files:

    # Merge arrays via np.hstack() or np.vstack()
    for k, v in six.iteritems(self.d):
      print('array: {}'.format(k))
      if v[0].ndim == 0:
        vv = np.array(v)
      elif v[0].ndim == 1:
        vv = np.hstack(v)
      elif v[0].ndim == 2:
        vv = np.vstack(v)
      elif v[0].ndim == 3:
        vv = np.dstack(v)
        vv = np.concatenate(v, axis=-1)
      self.dout[k] = vv

    # Write to the target file
    np.savez_compressed(target, **self.dout)

# Main
if __name__ == '__main__':
  import argparse
  parser = argparse.ArgumentParser(description='hadd for npz files.')
  parser.add_argument('-f', '--force', action='store_true', help='Force write the target file')
  parser.add_argument('target', help='target file')
  parser.add_argument('source', nargs='+', help='source files')
  args = parser.parse_args()

  hadd = Hadd()
  hadd.process(args.target, args.source, force=args.force)