Recommended setup involving Scitools, NumPy, and SciPy

Question

I have a book called "Scientific Programming with Python (2009)", in which example code makes heavy use of SciTools. I use Python 3.2 64 (thinking about having a parallel install / development environment of 2.7; more on this later), to which SciTools has not yet been ported.

Has Scitools been superceded for many purposes by NumPy/SciPy? Or what? EazyViz? I'm totally okay reading through this book and translating the code into whatever API / module is current with 3.2. I'd kind of rather do that than setup a Python 2.7 system.

What is your recommended setup?

Ritaritardando

Answer 1

Scipy/Numpy is the defacto standard for scientific/numerical computing with python. The vast majority of packages are built on top of them (including Scitools). In many ways it looks like Scitools is just a connivence wrapper around Numpy/Scipy/Matplotlib.

As far as Python 3 support, Numpy and Scipy are there, but Matplotlib is not yet (although I think it may be supported in the development repo on github):

http://onpython3yet.com/packages/requirements?r=numpy%0D%0Amatplotlib%0D%0Ascipy

Personally I've never used Scitools, since I prefer the lower level control of using the other libraries directly. I also stick with Python 2.7 since the complete scientific programming stack hasn't finished its migration to Python 3 yet.

Buddha

I forgot to mention that I have Matplotlib installed for my Python 3.2 install. I'm pretty sure I picked it up here: lfd.uci.edu/~gohlke/pythonlibs – Ritaritardando

It works too. Just tested it. Now have working Python scientific computing and plotting in both the 2.7 and 3.2 setups. – Ritaritardando

+1, an overview of most of the packages can be found at numfocus. perhaps you can add this link. – Sweeting

Answer 2

Also take a look at Pandas for your numerical work. It is built on top of NumPy.

Shalloon