Best way to run multiple Python processes without overloading CPU or disk i/o

python at python at
Wed Dec 3 05:21:30 CET 2008

Is there a cross-platform way to launch multiple Python processes
and monitor CPU usage and disk i/o so that the maximum number of
independent processes can be running at all times without
overloading their environment? By process I mean independent
application sessions vs. multiple threads of a single
application. I'm looking for suggestions on what Python modules
and/or techniques to use to maximize the number of processes I
can run on my system over a multi-day period.
Background: I have a large collection of data analysis scripts
that can run independently of one another. These scripts read
very large log files in a sequential manner and calculate
specific statistics. These scripts are hosted on a 8 core 64-bit
server with 48G of memory that is dedicated to running these
scripts. I am looking for a way to write a master script that
monitors system CPU and disk i/o and when there is capacity
launch another script from a pool of scripts so that I'm getting
max utilization from my hardware, eg. so that I'm running the max
number of scripts I can at any one point in time without
overwhelming the system.
The server in question is currently running Windows 2008
Enterprise, but I have the option to switch to a 64-bit version
of Linux if there are benefits to doing so.
Thank you,
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