Elegant parallelization in GRASS

parallelizer.py

#!/usr/bin/env python
# This script is derived from GPL 2+ code
# Cudos to Hamish for providing the example it's based on.
# Also see the following link for an example of parallelization
# using the multiprocessing library.
# https://trac.osgeo.org/grass/browser/grass/trunk/scripts/i.landsat.rgb/i.landsat.rgb.py

import os
import grass.script as grass

# Have user set number of workers. Here an example of 4 has been set
workers = 4
# This is only a set of examples for r.slope.aspect jobs where the maps are
# named serially.
jobs = range(20)

# Check if workers are already being used
if workers is 1 and "WORKERS" in os.environ:
    workers = int(os.environ["WORKERS"])
if workers < 1:
    workers = 1

# Initialize process dictionary
proc = {}

# Loop over jobs
for i in range(jobs):
    # Insert job into dictinoary to keep track of it
    proc[i] = grass.start_command('r.slope.aspect',
                                  elevation='elev_' + str(i),
                                  slope='slope_' + str(i))
    # If the workers are used up, wait for all of them from the last group to
    # finish.
    if i % workers is 0:
        for j in range(workers):
            proc.[i - j].wait()

# Make sure all workers are finished.
for i in range(jobs):
    if proc[i].wait() is not 0:
        grass.fatal(_('Problem running analysis on evel_' + str(i) + '.')

(note to other githubbers: this is derived from GPL 2+ code --Hamish)

For the record: an example for the actual way of using "multiprocessing" in GRASS GIS Python scripts is available here: https://trac.osgeo.org/grass/browser/grass/trunk/scripts/i.colors.enhance/i.colors.enhance.py