Python

Beautiful is better than ugly. Explicit is better than implicit. Simple is better than complex. Complex is better than complicated. -- Extract from the Zen of Python

Scientific computing with python

Here is a list of packages recommended for scientific computing using python:

• Numpy : (Required) Numerical python, offers an efficient implementation of arrays and enable for fast vector computation.
• Matplotlib : The most advanced python plotting library out there.
• Pandas : Offers a neat implementation of the dataframe type, offering a lot of the capabilities of R's dataframe (filtering, joining, SQL request).
• SciPy: A lot of useful scientific routines and functions (Fourier transform, statistical distribution...)
• IPython : Interactive Python (the I is uppercase !). A much better interactive console for python, but also an excellent html notebook that enable you to do some literate programming.

References

Links:

• https://www.python.org/ - official website and documentation
• http://jakevdp.github.io/ - A good blog about scientific computing in python.

Good sources for python packaging and deployment:

• http://www.dabapps.com/blog/introduction-to-pip-and-virtualenv-python/
• http://www.scotttorborg.com/python-packaging/