Python for Finance: Analyze Big Financial Data

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Chapter 2. Infrastructure and Tools


Infrastructure is much more important than architecture.

— Rem Koolhaas

You could say infrastructure is not everything, but without infrastructure everything can be


nothing — be it in the real world or in technology. What do we mean then by


infrastructure? In principle, it is those hardware and software components that allow the


development and execution of a simple Python script or more complex Python


applications.


However, this chapter does not go into detail with regard to hardware infrastructure, since


all Python code and examples should be executable on almost any hardware.


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Nor does it


discuss different operating systems, since the code should be executable on any operating


system on which Python, in principle, is available. This chapter rather focuses on the


following topics:


Deployment


How can I make sure to have everything needed available in a consistent fashion to


deploy Python code and applications? This chapter introduces Anaconda, a Python


distribution that makes deployment quite efficient, as well as the Python Quant


Platform, which allows for a web- and browser-based deployment.


Tools


Which tools shall I use for (interactive) Python development and data analytics? The


chapter introduces two of the most popular development environments for Python,


namely IPython and Spyder.


There is also Appendix A, on:


Best practices


Which best practices should I follow when developing Python code? The appendix


briefly reviews fundamentals of, for example, Python code syntax and


documentation.

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