Concurrency is the ability to run two or more tasks in the same time span, whether they are parallel or not. Python provides many tools to implement concurrency and asynchronous behaviors: threads, coroutines, and processes. While some of them don't allow real parallelism due to their design (coroutines), or due to a Global Interpreter Lock (threads), they are very easy to use and can be leveraged to perform parallel I/O operations or to interleave functions with minimum effort. When real parallelism is required, multiprocessing is easy enough in Python to be a viable solution for any kind of software.
This chapter will cover the most common ways to achieve concurrency in Python, will show you how to perform asynchronous tasks that will wait in the background for certain conditions, and how to share data between processes.
