In this chapter, we learned about concurrency and parallelism. We saw how threads and processes help in achieving one and the other. We explored the nature of threads and the issues that they expose us to: race conditions and deadlocks.

We learned how to solve those issues by using locks and careful resource management. We also learned how to make threads communicate and share data, and we talked about the scheduler, which is that part of the operating system that decides which thread will run at any given time. We then moved to processes, and explored a bunch of their properties and characteristics.

Following the initial theoretical part, we learned how to implement threads and processes in Python. We dealt with multiple threads and processes, fixed race conditions, and learned workarounds to stop threads without leaving any resource open by mistake. We also explored IPC, and used queues to exchange messages between processes and threads. We also played with events and barriers, which are some of the tools provided by the standard library to control the flow of execution in a non-deterministic environment.

After all these introductory examples, we deep dived into three case examples, which showed how to solve the same problem using different approaches: single-thread, multithread, multiprocess, and asyncio.

We learned about mergesort and how, in general, divide and conquer algorithms are easy to parallelize.

We learned about sudoku, and explored a nice solution that uses a little bit of artificial intelligence to run an efficient algorithm, which we then ran in different serial and parallel modes.

Finally, we saw how to download random pictures from a website, using serial, multiprocess, and asyncio code. The latter was by far the hardest piece of code in the whole book, and its presence in the chapter serves as a reminder, or some sort of milestone that will encourage the reader to learn Python well, and deeply.

Now we'll move on to much simpler, and mostly project-oriented chapters, where we get a taste of different real-world applications in different contexts.