loopsbest of usec per loop :\python \python loopsbest of usec per loop :\pypy\pypy- \pypy loopsbest of usec per loop [" '?'\nfor in range( ) +'?'" :\python \python loopsbest of msec per loop :\python \python loopsbest of msec per loop :\pypy\pypy- \pypy loopsbest of msec per loop as you can seein most of these testscpython is still quicker than cpython and pypy is noticeably faster than both of them--except on the last test where pypy is twice as slow as cpythonpresumably due to memory management differences on the other handtiming results are often relative at best in addition to other general timing caveats mentioned in this timeit may skew results in ways beyond our scope to explore here ( garbage collectionthere is baseline overheadwhich differs per python versionthat is ignored here (but appears trivialthis script runs very small statements that may or may not reflect real-world code (but are still validresults may occasionally vary in ways that seem random (using process time may help hereall results here are highly prone to change over time (in each new python releasein fact!in other wordsyou should draw your own conclusions from these numbersand run these tests on your pythons and machines for results more relevant to your needs to time the baseline overhead of each pythonrun timeit with no statement argumentor equivalentlywith pass statement more fun with benchmarks for more insighttry running the script on other python versions and other statement test strings the file pybench_cases py in this book' examples distribution adds more tests to see how cpython compares to how pypy' beta stacks up against its current releaseand how additional use cases fare timing iterations and pythons with timeit