High Performance Python

Chapter 1. Understanding Performant Python

Questions You’ll Be Able to Answer After This Chapter

• What are the elements of a computer’s architecture?
• What are some common alternate computer architectures?
• How does Python abstract the underlying computer architecture?
• What are some of the hurdles to making performant Python code?
• What are the different types of performance problems?

Programming computers can be thought of as moving bits of data and transforming them in special ways in order to achieve a particular result. However, these actions have a time cost. Consequently, high performance programming can be thought of as the act of minimizing these operations by either reducing the overhead (i.e., writing more efficient code) or by changing the way that we do these operations in order to make each one more meaningful (i.e., finding a more suitable algorithm).

Let’s focus on reducing the overhead in code in order to gain more insight into the actual hardware on which we are moving these bits. This may seem like a futile exercise, since Python works quite hard to abstract away direct interactions with the hardware. However, by understanding both the best way that bits can be moved in the real hardware and the ways that Python’s abstractions force your bits to move, you can make progress toward writing high performance programs in Python.

The Fundamental Computer System

The underlying components that make up a computer can be simplified into three basic parts: the computing units, ...