On Wed, Jul 20, 2011 at 9:25 AM, David Fraser <dav...@sjsoft.com> wrote: > > > On Wednesday, July 20, 2011, at 8:50:20 AM, "Alexander Petrov" > <alexandervpet...@gmail.com> wrote: >> [snip] >> So at this time I didn't come to some kind of decision about PyPy. >> >> On one hand in most of the cases with straitforward code/algorithms >> and "common" syntax constructs there was significant speed >> improvement. >> >> But on the other hand, for the cases where source Python code was >> "optimized" or "hacked" the time of execution was sometimes better, >> sometimes of one order... and sometimes was a cause for this topic >> discussion. :) It is not bad thing generally, the bad thing that this >> speed degradation situations are happenned unexpectedly for me. IMO >> they are the most (and may be only one) interesting from the >> PyPy-user >> viewpoint. "Where and in what cases one can expect bottlenecks". Is >> there any documented collection of such artifacts? It can be >> exceptionally useful. > > That's exactly what I would like. I also experimented with some simple tests > and came out with PyPy being twice as slow as CPython - a wiki page which > documents current areas of slowness, and potential workarounds would be > fantastic - I know these things can be improved in the future, sometimes > quickly, but it seems like the know-how about handling it in the mean time > isn't written down anywhere... > > David
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