Virgil Dupras <[EMAIL PROTECTED]> added the comment: I had a 54 mb hotshot profile lying around, and it is indeed very long to load, so I ran a profiling session of hotshot.stats.load(MY_BIG_FILE) with python and stdlib of r61515, and here are the results (the resulting prof file is 27 mb):
96541166 function calls in 299.936 CPU seconds Ordered by: cumulative time List reduced from 30 to 15 due to restriction <15> ncalls tottime percall cumtime percall filename:lineno(function) 1 0.000 0.000 299.936 299.936 stats.py:11(load) 1 95.089 95.089 299.936 299.936 stats.py:22(load) 27583167 51.183 0.000 61.815 0.000 log.py:95(next) 13791583 59.314 0.000 59.314 0.000 profile.py:328(trace_dispatch_return) 13791583 35.014 0.000 42.910 0.000 stats.py:54(new_frame) 13791584 40.807 0.000 40.807 0.000 profile.py:295(trace_dispatch_call) 13791583 10.632 0.000 10.632 0.000 log.py:138(_decode_location) 13791583 7.897 0.000 7.897 0.000 stats.py:87(__init__) 1 0.000 0.000 0.000 0.000 pstats.py:73(__init__) 1 0.000 0.000 0.000 0.000 pstats.py:95(init) 1 0.000 0.000 0.000 0.000 pstats.py:138(get_top_level_stats) 1 0.000 0.000 0.000 0.000 log.py:24(__init__) 1 0.000 0.000 0.000 0.000 pstats.py:117(load_stats) 1 0.000 0.000 0.000 0.000 profile.py:436(create_stats) 1 0.000 0.000 0.000 0.000 profile.py:440(snapshot_stats) 96541166 function calls in 299.936 CPU seconds Ordered by: internal time List reduced from 30 to 20 due to restriction <20> ncalls tottime percall cumtime percall filename:lineno(function) 1 95.089 95.089 299.936 299.936 stats.py:22(load) 13791583 59.314 0.000 59.314 0.000 profile.py:328(trace_dispatch_return) 27583167 51.183 0.000 61.815 0.000 log.py:95(next) 13791584 40.807 0.000 40.807 0.000 profile.py:295(trace_dispatch_call) 13791583 35.014 0.000 42.910 0.000 stats.py:54(new_frame) 13791583 10.632 0.000 10.632 0.000 log.py:138(_decode_location) 13791583 7.897 0.000 7.897 0.000 stats.py:87(__init__) 1 0.000 0.000 0.000 0.000 log.py:24(__init__) 1 0.000 0.000 0.000 0.000 profile.py:440(snapshot_stats) 1 0.000 0.000 0.000 0.000 pstats.py:138(get_top_level_stats) 30 0.000 0.000 0.000 0.000 pstats.py:484(func_std_string) 5 0.000 0.000 0.000 0.000 posixpath.py:306(normpath) 1 0.000 0.000 299.936 299.936 stats.py:11(load) 24 0.000 0.000 0.000 0.000 stats.py:80(__init__) 1 0.000 0.000 0.000 0.000 pstats.py:117(load_stats) 1 0.000 0.000 0.000 0.000 profile.py:402(simulate_call) 1 0.000 0.000 0.000 0.000 profile.py:118(_get_time_resource) 1 0.000 0.000 0.000 0.000 pstats.py:73(__init__) 1 0.000 0.000 0.000 0.000 pstats.py:95(init) 1 0.000 0.000 0.000 0.000 profile.py:166(__init__) So the bulk of the time seems to be taken by the sheer number of trace_dispatch_return and trace_dispatch_call calls. I took a quick look, but I'm not sure I can do anything to make it faster. If no one else has any idea, I suggest just closing the ticket. ---------- nosy: +vdupras ____________________________________ Tracker <[EMAIL PROTECTED]> <http://bugs.python.org/issue984219> ____________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com