scalar= + parent+ in children showdata('parent end'scalarvectorarray[ ]= + parent+ in children the following is this script' output on windows trace through this and the code to see how it runsnotice how the changed value of the global variable is not shared by the spawned processes on windowsbut passed-in value and array objects are the final output line reflects changes made to shared memory in both the parent and spawned children--the array' final values are all because they were incremented twice in the parentand once in each of six spawned childrenthe scalar value similarly reflects changes made by both parent and childbut unlike for threadsthe global is per-process data on windowsc:\pp \system\processesmulti py parent startpid: global: value: array:[ child pid: global: value: array:[ loop (updates in parentserial childrenprocess pid: global: value: array:[ process pid: global: value: array:[ process pid: global: value: array:[ loop (updates in parentparallel childrenprocess pid: global: value: array:[ process pid: global: value: array:[ process pid: global: value: array:[ loop (updates in serial childrenparent temp pid: global: value: array:[ loop (updates in parallel childrenparent end pid: global: value: array:[ if you imagine the last test here run with much larger array and many more parallel childrenyou might begin to sense some of the power of this package for distributing work queues and subclassing finallybesides basic spawning and ipc toolsthe multiprocessing module alsoallows its process class to be subclassed to provide structure and state retention (much like threading threadbut for processesimplements process-safe queue object which may be shared by any number of processes for more general communication needs (much like queue queuebut for processesqueues support more flexible multiple client/server model example - for instancespawns three producer threads to post to shared queue and repeatedly polls for results to appear--in much the same fashion that gui might collect results in parallel with the display itselfthough here the concurrency is achieved with processes instead of threads parallel system tools