Neal Becker wrote:
I'm using multiprocessing as a crude batch queuing system, like this:import my_test_program as prog (where my_test_program has a function called 'run') def run_test (args): prog.run (args[1:]) cases = [] for t in test_conditions: args = [prog.__name__]+[more args...] cases.append (args) (leaving out details, but 'cases' will be the list of test cases to run) results = pool.map (run_test, cases)Problem is, it doesn't seem to keep all my cpus busy, even though there are more test cases than cpus. Ideas?
If they do a lot of I/O then that could be the bottleneck. -- http://mail.python.org/mailman/listinfo/python-list
