So far, we have explored how to measure and improve the performance of programs by reducing the number of operations performed by the CPU through clever algorithms and more efficient machine code. In this chapter, we will shift our focus to programs where most of the time is spent waiting for resources that are much slower than the CPU, such as persistent storage and network resources.

Asynchronous programming is a programming paradigm that helps to deal with slow and unpredictable resources (such as users) and is widely used to build responsive services and user interfaces. In this chapter, we will show you how to program asynchronously in Python using techniques such as coroutines and reactive programming.

In this chapter, we will cover the following topics:

• The memory hierarchy
• Callbacks
• Futures
• Event loops
• Writing coroutines with asyncio
• Converting synchronous code to asynchronous code
• Reactive programming with RxPy
• Working with observables
• Building a memory monitor with RxPY