Shared resources and data races

One of the major things we need to guard against when implementing concurrency in your applications is race conditions. These race conditions can cripple our applications, and cause bugs that are hard to debug and even harder to fix. In order to prevent these issues, we need to both understand how these race conditions occur and how we can guard against them using the synchronization primitives we'll be covering in this chapter.

Understanding synchronization and the basic primitives that are available to you is vital if you are to create thread-safe, high-performance programs in Python. Thankfully, we have numerous different synchronization primitives available to us in the threading Python module that can help us in a number of different concurrent situations.

In this section, I'll be giving you a brief overview of all of the synchronization primitives available to you as well as a few simple examples of how you can use these within your programs. By the end of it, you should be able to implement your own concurrent Python programs that can access resources in a thread-safe way.