> As an example - I want numpy for client work. For my clients (the main > being a physics company that is replacing Fortran with Python) numpy > is at the heart of their simulations. However - numpy is used with > matplotlib and pyCUDA and parts of scipy. If basic tools like FFT > aren't available *and compatible* (i.e. not new implementations but > running on tried, trusted and consistent C libs) then there'd be > little reason to use pypy+numpy. pyCUDA could be a longer term goal > but matplotlib would be essential.
Hi David, Fijal. I'll reply to this earlier post as the overnight discussion doesn't seem to have a good place to add this. Someone else (I can't find a name) posted this nice summary: http://blog.streamitive.com/2011/10/17/numpy-isnt-about-fast-arrays/ which mostly echoes my position. Does anyone have a guestimate of the size of the active numpy user community minus the scipy/extensions community. I.e. the size of the community that might benefit from pypy-numpy (excluding those that use scipy etc who couldn't benefit for a [long] while)? At EuroSciPy it felt as though many people used numpy+scipy (noting that it was a scipy conference). At EuroPython there were a number of talks that used numpy but mostly they used other C or extension components (e.g. pyCUDA, Theano, visualisation tools). i. -- Ian Ozsvald (A.I. researcher) i...@ianozsvald.com http://IanOzsvald.com http://MorConsulting.com/ http://StrongSteam.com/ http://SocialTiesApp.com/ http://TheScreencastingHandbook.com http://FivePoundApp.com/ http://twitter.com/IanOzsvald _______________________________________________ pypy-dev mailing list pypy-dev@python.org http://mail.python.org/mailman/listinfo/pypy-dev
