You will need a Python programming environment installed on your system. The first module uses a recent Python 2, but many examples will work with Python 3 as well.b The versions of the libraries used in the first module are: NumPy 1.9.2, Pandas 0.16.2, matplotlib 1.4.3, tables 3.2.2, pymongo 3.0.3, redis 2.10.3, and scikit-learn 0.16.1. As these packages are all hosted on PyPI, the Python package index, they can be easily installed with pip. To install NumPy, you would write:
$ pip install numpy If you are not using them already, we suggest you take a look at virtual environments for managing isolating Python environment on your computer. For Python 2, there are two packages of interest there: virtualenv and virtualenvwrapper. Since Python 3.3, there is a tool in the standard library called pyvenv (https://docs.python.org/3/library/venv.html), which serves the same purpose. Most libraries will have an attribute for the version, so if you already have a library installed, you can quickly check its version:
>>> import redis
>>> redis.__version__
‘2.10.3’).
While all the examples in second module can be run interactively in a Python shell. We used IPython 4.0.0 with Python 2.7.10.
For the third module, you need Python 2.7.6 or a later version installed on your operating system. For the examples in this module, Mac OS X 10.10.5’s Python default version (2.7.6) has been used. Install the prepackaged scientific Python distributions, such as Anaconda from Continuum or Enthought Python Distribution if possible