Split many ArcGIS rasters in parallel using Python multiprocessing -

i looking split 10 images 2 parts each (20 resulting images). images 4-band (r,g,b,nir) naip imagery available this website. using arcpy package arcgis split 1 image @ time:

import arcpy, os  inws = r'd:\temp\temp_naip'  #contains ~10 .tif images outws = r'd:\temp\temp_naip_tiles'  arcpy.env.workspace = inws rasters = arcpy.listrasters()  ras in rasters:     arcpy.splitraster_management(         ras, outws,          os.path.basename(ras).split('.')[0],          split_method='number_of_tiles',          format='tiff',          num_rasters='1 2',         overlap=50, units='pixels) 

how can integrate multiprocessing module above script process, say, 4 images @ time?

btw, aware of blog post combines multiprocessing , arcpy, although examples specific vector data , cannot figure out how utilize tools process imagery.

barring resource sharing issues, converting simple for-loop multiprocessing easy multiprocessing.pool. try this:

from multiprocessing import pool import arcpy, os  inws = r'd:\temp\temp_naip'  #contains ~10 .tif images outws = r'd:\temp\temp_naip_tiles'  arcpy.env.workspace = inws     rasters = arcpy.listrasters()  def process_img(ras):     arcpy.splitraster_management(         ras, outws,          os.path.basename(ras).split('.')[0],          split_method='number_of_tiles',         format='tiff',          num_rasters='1 2',         overlap=50, units='pixels')  pool = pool(processes=4) pool.map(process_img, rasters) 

so long rasters iterable, should mappable process pool. keep in mind each process "inherit" parent process' stack, such each process use it's own copy of arcpy.env.workspace.