source: trunk/essentials/dev-lang/python/Doc/lib/libhotshot.tex@ 3368

\section{\module{hotshot} ---
         High performance logging profiler}

\declaremodule{standard}{hotshot}
\modulesynopsis{High performance logging profiler, mostly written in C.}
\moduleauthor{Fred L. Drake, Jr.}{[email protected]}
\sectionauthor{Anthony Baxter}{[email protected]}

\versionadded{2.2}


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

\begin{notice}[note]
  The \module{hotshot} module focuses on minimizing the overhead
  while profiling, at the expense of long data post-processing times.
  For common usages it is recommended to use \module{cProfile} instead.
  \module{hotshot} is not maintained and might be removed from the
  standard library in the future.
\end{notice}

\versionchanged[the results should be more meaningful than in the
past: the timing core contained a critical bug]{2.5}

\begin{notice}[warning]
  The \module{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.
\end{notice}


\begin{classdesc}{Profile}{logfile\optional{, lineevents\optional{,
                           linetimings}}}
The profiler object. The argument \var{logfile} is the name of a log
file to use for logged profile data. The argument \var{lineevents}
specifies whether to generate events for every source line, or just on
function call/return. It defaults to \code{0} (only log function
call/return). The argument \var{linetimings} specifies whether to
record timing information. It defaults to \code{1} (store timing
information).
\end{classdesc}


\subsection{Profile Objects \label{hotshot-objects}}

Profile objects have the following methods:

\begin{methoddesc}{addinfo}{key, value}
Add an arbitrary labelled value to the profile output.
\end{methoddesc}

\begin{methoddesc}{close}{}
Close the logfile and terminate the profiler.
\end{methoddesc}

\begin{methoddesc}{fileno}{}
Return the file descriptor of the profiler's log file.
\end{methoddesc}

\begin{methoddesc}{run}{cmd}
Profile an \keyword{exec}-compatible string in the script environment.
The globals from the \refmodule[main]{__main__} module are used as
both the globals and locals for the script.
\end{methoddesc}

\begin{methoddesc}{runcall}{func, *args, **keywords}
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.
\end{methoddesc}


\begin{methoddesc}{runctx}{cmd, globals, locals}
Evaluate an \keyword{exec}-compatible string in a specific environment.
The string is compiled before profiling begins.
\end{methoddesc}

\begin{methoddesc}{start}{}
Start the profiler.
\end{methoddesc}

\begin{methoddesc}{stop}{}
Stop the profiler.
\end{methoddesc}


\subsection{Using hotshot data}

\declaremodule{standard}{hotshot.stats}
\modulesynopsis{Statistical analysis for Hotshot}

\versionadded{2.2}

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

\begin{funcdesc}{load}{filename}
Load hotshot data from \var{filename}. Returns an instance
of the \class{pstats.Stats} class.
\end{funcdesc}

\begin{seealso}
  \seemodule{profile}{The \module{profile} module's \class{Stats} class}
\end{seealso}


\subsection{Example Usage \label{hotshot-example}}

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

\begin{verbatim}
>>> 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)
 .
 .
 .
\end{verbatim}