I find this whole conversation confusing -- does anyone really think a substantial performance boost to cPython is not a "good thing"? Worth the work? Maybe not, but it seems that Mark, Guido, and MS think it is -- more power to them!
Anyway: potential 10% or 20% speedups in Python I believe the folks involved think they may get a factor of two speedup -- but in any case, Oscar has a point -- there is a trade-off of effort vs performance, and increasing the performance of cPython moves that trade-off point, even if just a little. I like Oscar's example, because it's got hard numbers attached to it, but the principle is the same for any time you are considering writing, or even using, a non-python library. > (2) bite the bullet and write > C (or ctypes) that can do the calculations 100x as fast as a > well-tuned Python program. > Oddly missing from this conversation is PyPy -- which can buy you a lot of performance for some types of code in pure Python, and things like Cython or numba, which can buy you a lot with slightly modified Python. All those options are why Python is very useful today -- but none of them make the case that making cPython run faster isn't a worthy goal. -CHB -- Christopher Barker, PhD (Chris) Python Language Consulting - Teaching - Scientific Software Development - Desktop GUI and Web Development - wxPython, numpy, scipy, Cython
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