code: def get_batch_commands(filename, n_per_job=1):
      """Print the commands needed to run the given batch data file headless
  
      filename - the name of a Batch_data.h5 file. The file should group image sets.
  
      The output assumes that the executable, "CellProfiler", can be used
      to run the command from the shell. Alternatively, the output could be
      run through a utility such as "sed":
  
      CellProfiler --get-batch-commands Batch_data.h5 | sed s/CellProfiler/farm_job.sh/
      """
      path = os.path.expanduser(filename)
  
      m = Measurements(filename=path, mode="r")
  
      image_numbers = m.get_image_numbers()
  
      if m.has_feature(IMAGE, GROUP_NUMBER):
          group_numbers = m[
              IMAGE,
              GROUP_NUMBER,
              image_numbers,
          ]
  
          group_indexes = m[
              IMAGE,
              GROUP_INDEX,
              image_numbers,
          ]
  
          if numpy.any(group_numbers != 1) and numpy.all(
              (group_indexes[1:] == group_indexes[:-1] + 1)
              | (
                  (group_indexes[1:] == 1)
                  & (group_numbers[1:] == group_numbers[:-1] + 1)
              )
          ):
              #
              # Do -f and -l if more than one group and group numbers
              # and indices are properly constructed
              #
              bins = numpy.bincount(group_numbers)
  
              cumsums = numpy.cumsum(bins)
  
              prev = 0
  
              for i, off in enumerate(cumsums):
                  if off == prev:
                      continue
  
                  print(
                      "CellProfiler -c -r -p %s -f %d -l %d"
                      % (filename, prev + 1, off)
                  )
  
                  prev = off
      else:
          metadata_tags = m.get_grouping_tags_or_metadata()
  
          if (
              len(metadata_tags) == 1
              and metadata_tags[0] == "ImageNumber"
          ):
              for i in range(0, len(image_numbers), n_per_job):
                  first = image_numbers[i]
                  last = image_numbers[
                      min(i + n_per_job - 1, len(image_numbers) - 1)
                  ]
                  print(
                      "CellProfiler -c -r -p %s -f %d -l %d"
                      % (filename, first, last)
                  )
          else:
              # LoadData w/ images grouped by metadata tags
              groupings = m.get_groupings(metadata_tags)
  
              for grouping in groupings:
                  group_string = ",".join(
                      [
                          "%s=%s" % (k, v)
                          for k, v in list(grouping[0].items())
                      ]
                  )
  
                  print(
                      "CellProfiler -c -r -p %s -g %s"
                      % (filename, group_string)
                  )
      return
  
imports: import io
  import json
  import logging
  import logging.config
  import optparse
  import os
  import os.path
  import re
  import sys
  import tempfile
  import urllib.parse
  import h5py
  import matplotlib
  import numpy
  import pkg_resources
  from cellprofiler_core.constants.measurement import EXPERIMENT
  from cellprofiler_core.constants.measurement import GROUP_INDEX
  from cellprofiler_core.constants.measurement import GROUP_NUMBER
  from cellprofiler_core.constants.measurement import IMAGE
  from cellprofiler_core.constants.pipeline import M_PIPELINE, EXIT_STATUS
  from cellprofiler_core.measurement import Measurements
  from cellprofiler_core.object import ObjectSet
  from cellprofiler_core.pipeline import LoadException
  from cellprofiler_core.pipeline import Pipeline
  from cellprofiler_core.preferences import get_image_set_file
  from cellprofiler_core.preferences import get_temporary_directory
  from cellprofiler_core.preferences import set_conserve_memory
  from cellprofiler_core.preferences import set_force_bioformats
  from cellprofiler_core.preferences import set_allow_schema_write
  from cellprofiler_core.preferences import set_always_continue
  from cellprofiler_core.preferences import set_awt_headless
  from cellprofiler_core.preferences import set_data_file
  from cellprofiler_core.preferences import set_default_image_directory
  from cellprofiler_core.preferences import set_default_output_directory
  from cellprofiler_core.preferences import set_headless
  from cellprofiler_core.preferences import set_image_set_file
  from cellprofiler_core.preferences import set_plugin_directory
  from cellprofiler_core.preferences import set_temporary_directory
  from cellprofiler_core.preferences import set_widget_inspector
  from cellprofiler_core.utilities.core.workspace import is_workspace_file
  from cellprofiler_core.utilities.hdf5_dict import HDF5FileList
  from cellprofiler_core.utilities.java import start_java, stop_java
  from cellprofiler_core.utilities.measurement import load_measurements
  from cellprofiler_core.utilities.zmq import join_to_the_boundary
  from cellprofiler_core.worker import aw_parse_args
  from cellprofiler_core.worker import main
  from cellprofiler_core.workspace import Workspace
  from cellprofiler_core.reader import activate_readers
label_desc: Use image node_id 8 for calling a global function with example usage: get_batch_commands(filename, n_per_job) without return types