this has focused on code timing fundamentals that you can use on your own codethat apply to python benchmarking in generaland that served as common use case for developing larger examples for this book benchmarking python is broader and richer domain than so far impliedthough if you're interested in pursuing this topic furthersearch the web for links among the topics you'll findpystone py-- program designed for measuring python speed across range of code that ships with python in its lib\test directory benchmarks partially emulating the pystone testfor exampleis based on language benchmark program that was translated to python by python original creator guido van rossum it provides another way to measure the relative speeds of python implementationsand seems to generally support our findings herec:\python \lib\testcd :\python \lib\test :\python \lib\testpy - pystone py pystone( time for passes this machine benchmarks at pystones/second :\python \lib\testcd :\python \lib\test :\python \lib\testpy - pystone py pystone( time for passes this machine benchmarks at pystones/second :\python \lib\testc:\pypy\pypy- \pypy pystone py pystone( time for passes this machine benchmarks at pystones/second since it' time to wrap up this this will have to suffice as independent confirmation of our testsresults analyzing the meaning of pystone' results is left as suggested exerciseits code is not identical across and xbut appears to differ today only in terms of print operations and an initialization of global also keep in mind that benchmarking is just one of many aspects of python code analysisfor pointers on options in related domains ( testing)see ' review of python development tools function gotchas now that we've reached the end of the function storylet' review some common pitfalls functions have some jagged edges that you might not expect they're all relatively the benchmarking interlude