Chapter 7: Multiprocessing, Multithreading, and Asynchronous Programming

We can write efficient and optimized code for faster execution time, but there is always a limit to the amount of resources available for the processes running our programs. However, we can still improve application execution time by executing certain tasks in parallel on the same machine or across different machines. This chapter will cover parallel processing or concurrency in Python for the applications running on a single machine. We will cover parallel processing using multiple machines in the next chapter. In this chapter, we focus on the built-in support available in Python for the implementation of parallel processing. We will start with the multithreading in Python followed by discussing the multiprocessing. After that, we will discuss how we can design responsive systems using asynchronous programming. For each of the approaches, we will design and discuss a case study of implementing a concurrent application...