On Wednesday, November 9, 2016 at 5:03:30 AM UTC-8, BartC wrote: > On 05/11/2016 17:10, Mr. Wrobel wrote: > > > 1. What I have found is modified python interpreter - pypy - > > http://pypy.org that does not require any different approach to develop > > your code. > > > > 2. And: Gpu based computing powered by Nvidia (NumbaPro compiler): > > https://developer.nvidia.com/how-to-cuda-python > > Nice Mandelbrot benchmark link in that article. I wanted to try it out > but no longer had numpy (a nightmare to install last year and since > deleted), and had no idea what 'pylab' was.
Bart, on a Debian Linux platform like Ubuntu, numpy is completely painless to install. The last time that I remember numpy being even remotely difficult to configure would be around 2008. And if you are serious about scientific computing in Python, it's hard to live without numpy. Pylab is an interface to the matplotlib graphing library, which is designed to be familiar to Matlab users. I never use pylab, but I consider matplotlib to be essential. -- https://mail.python.org/mailman/listinfo/python-list
