# Python for Fortran programmers 8: Looking ahead

This series of posts were not a Python tutorial, just some tips for those Fortran programmers who are learning python. Once you know the basics of Python, you can focus on extensions useful to scientists.

The most essential one is Numpy, which gives python the ability to work efficiently with arrays. If you install Numpy, it is worth also installing Scipy. Scipy includes a wealth of algorithms that you probably need but you don’t want to code. From Fourier transforms and splines to minimizations and numerical integrations. There are excellent tutorials for both Numpy and Scipy and a good place to start is at http://www.scipy.org/.

Remember that although you can translate a Fortran code almost line by line into Python, the resulting code will not be optimal, neither for clarity nor efficiency. Learn to be Pythonic:

http://www.cafepy.com/article/be_pythonic/

http://blog.startifact.com/posts/older/what-is-pythonic.html

Use dictionaries, use sets, use list comprehension, and even consider using classes! Remember that almost everything is iterable in Python.

This is my last post for the series *Python for Fortran programmers*, but I will continue writing about Python tools that I find useful for my research. I hope they will also help other computational chemists and biophysicists.

Ramon,

Congratulations for this series of very interesting posts. I guess the real challenge for a “Fortran programmer” is to embrace the pythonic way of coding. It makes little sense to simply switch semantics and maintaining the structure.

Looking forward for future projects,