Whether you are reading this book as a computational biologist or a Python programmer, you
will probably relate to the "explosive growth, exciting times" expression. The recent growth of
Python is strongly connected with its status as the main programming language for big data.
On the other hand, the deluge of data in biology, mostly from genomics and proteomics makes
bioinformatics one of the forefront applications of data science. There is a massive need for
bioinformaticians to analyze all this data; of course, one of the main tools is Python. We will
not only talk about the programming language, but also the whole community and software
ecology behind it. When you choose Python to analyze your data, you will also get an extensive
set of libraries, ranging from statistical analysis to plotting, parallel programming, machine
learning, and bioinformatics. However, when you choose Python, you expect more than
this; the community has a tradition of providing good documentation, reliable libraries, and
frameworks. It is also friendly and supportive of all its participants.