Recommended Configuration Using Scitools, NumPy, and SciPy

Question

I have a book called “Scientific Programming with Python (2009),” in which the sample code makes heavy use of SciTools. I am using Python 3.2 64 (thinking that the parallel installation / development environment is 2.7, more about this later), to which SciTools has not yet been ported.

Is Scitools used for many NumPy / SciPy purposes? Or what? EazyViz? I am fully reading this book and translating code into any API / module currently with 3.2. I'd rather do this than set up a Python 2.7 system.

What is your recommended setting?

Answer 1

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

Regarding support for Python 3, i.e. Numpy and Scipy, but Matplotlib is not there yet (although I think it can be supported in the development repository on github):

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

Personally, I have never used Scitools, since I prefer a lower level of control over using other libraries directly. I also stick with Python 2.7, since the full stack of scientific programming has not yet completed its migration to Python 3.

Answer 2

Also pay attention to Pandas for your digital work. It is built on top of NumPy.