How to access Python for doing scientific computing

 

 

 

The material in this document is taken from Appendix H.1 in the book A Primer on Scientific Programming with Python, 4th edition, by the same author, published by Springer, 2014.

Installing software on your laptop: Mac OS X and Windows

There are various possibilities for installing the software on a Mac OS X or Windows platform:

  1. Use .dmg (Mac) or .exe (Windows) files to install individual packages
  2. Use Homebrew or MacPorts to install packages (Mac only)
  3. Use a pre-built rich environment for scientific computing in Python:
  4. Use a virtual machine running Ubuntu:
Alternative 1 is the obvious and perhaps simplest approach, but usually requires quite some competence about the operating system as a long-term solution when you need many more Python packages than the basic three. This author is not particularly enthusiastic about Alternative 2. If you anticipate to use Python extensively in your work, I strongly recommend operating Python on an Ubuntu platform and going for Alternative 4 because that is the easiest and most flexible way to build and maintain your own software ecosystem. Alternative 3 is recommended for those who are uncertain about the future needs for Python and think Alternative 4 is too complicated. My preference is to use Anaconda for the Python installation and Spyder (comes with Anaconda) as a graphical interface with editor, an output area, and flexible ways of running Python programs.