27.5. hotshot â€” High performance logging profiler — Python v2.6.2 documentation

27.5. `hotshot` — High performance logging profilerÂ¶

New in version 2.2.

This module provides a nicer interface to the _hotshot C module. Hotshot is a replacement for the existing profile module. As it’s written mostly in C, it should result in a much smaller performance impact than the existing profile module.

Note

The hotshot module focuses on minimizing the overhead while profiling, at the expense of long data post-processing times. For common usage it is recommended to use cProfile instead. hotshot is not maintained and might be removed from the standard library in the future.

Changed in version 2.5: The results should be more meaningful than in the past: the timing core contained a critical bug.

Note

The hotshot profiler does not yet work well with threads. It is useful to use an unthreaded script to run the profiler over the code you’re interested in measuring if at all possible.

class hotshot.Profile(logfile[, lineevents[, linetimings]])Â¶: The profiler object. The argument logfile is the name of a log file to use for logged profile data. The argument lineevents specifies whether to generate events for every source line, or just on function call/return. It defaults to 0 (only log function call/return). The argument linetimings specifies whether to record timing information. It defaults to 1 (store timing information).

27.5.1. Profile ObjectsÂ¶

Profile objects have the following methods:

Profile.addinfo(key, value)Â¶: Add an arbitrary labelled value to the profile output.

Profile.close()Â¶: Close the logfile and terminate the profiler.

Profile.fileno()Â¶: Return the file descriptor of the profiler’s log file.

Profile.run(cmd)Â¶: Profile an exec-compatible string in the script environment. The globals from the __main__ module are used as both the globals and locals for the script.

Profile.runcall(func, *args, **keywords)Â¶: Profile a single call of a callable. Additional positional and keyword arguments may be passed along; the result of the call is returned, and exceptions are allowed to propagate cleanly, while ensuring that profiling is disabled on the way out.

Profile.runctx(cmd, globals, locals)Â¶: Evaluate an exec-compatible string in a specific environment. The string is compiled before profiling begins.

Profile.start()Â¶: Start the profiler.

Profile.stop()Â¶: Stop the profiler.

27.5.2. Using hotshot dataÂ¶

New in version 2.2.

This module loads hotshot profiling data into the standard pstats Stats objects.

hotshot.stats.load(filename)Â¶: Load hotshot data from filename. Returns an instance of the pstats.Stats class.

27.5.3. Example UsageÂ¶

Note that this example runs the python “benchmark” pystones. It can take some time to run, and will produce large output files.

>>> import hotshot, hotshot.stats, test.pystone
>>> prof = hotshot.Profile("stones.prof")
>>> benchtime, stones = prof.runcall(test.pystone.pystones)
>>> prof.close()
>>> stats = hotshot.stats.load("stones.prof")
>>> stats.strip_dirs()
>>> stats.sort_stats('time', 'calls')
>>> stats.print_stats(20)
         850004 function calls in 10.090 CPU seconds

   Ordered by: internal time, call count

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    3.295    3.295   10.090   10.090 pystone.py:79(Proc0)
   150000    1.315    0.000    1.315    0.000 pystone.py:203(Proc7)
    50000    1.313    0.000    1.463    0.000 pystone.py:229(Func2)
 .
 .
 .