On 07/20/2011 08:50 AM, Alexander Petrov wrote:
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.
Another point is that PyPy considers these programs performance bugs to
be fixed. So the situation you describe will likely change in the
future. Of course some perform unpredictability will always remain, that
goes with a JIT somewhat.
Carl Friedrich
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