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To do performance optimization in this sort of application, this is about as well as I have been able to manage in python. I will say perl with NYTProf seems to be significantly better for data, but this is servicable. I tried yappi, but it goes wildly inaccurate with this codebase. Because of the eventlet plumbing, cProfile is still pretty misleading. Best strategy seems to be review cumulative time with a healthy grain of salt around the top items until you get down to info that makes sense. For example, trampoline unfairly gets a great deal of the 'blame' by taking on nearly all the activity. internal time seems to miss a great deal of important information.
19 lines
358 B
Python
19 lines
358 B
Python
import sys
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import os
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path = os.path.dirname(os.path.realpath(__file__))
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path = os.path.realpath(os.path.join(path, '..'))
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sys.path.append(path)
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from confluent import main
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#import cProfile
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#import time
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#p = cProfile.Profile(time.clock)
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#p.enable()
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#try:
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main.run()
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#except:
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# pass
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#p.disable()
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#p.print_stats(sort='cumulative')
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#p.print_stats(sort='time')
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