Learn Python by Building Data Science Applications

Best Practices and Python Performance

After going through the preceding chapters and learning various things about Python, we have come to the last chapter. Here, we want to discuss some general strategies that you can implement and how to write code that works faster, is cleaner, and is easier to maintain. These approaches can be used for data-oriented code—or any other type of code, for that matter.

This chapter is split into three parts. The first section will discuss how you can analyze and speed up your code, the second section will cover best practices for maintaining your code so that you'll code faster and cleaner, and in the third and final section, we'll go through a brief overview of the non-Python technologies that you might find ...