Python provides many libraries and frameworks that facilitate high-performance computations. However, doing parallel programming with Python can be quite insidious due to the Global Interpreter Lock (GIL). 

In fact, the most widespread and widely used Python interpreter, CPython, is developed in the C programming language. The CPython interpreter needs GIL for thread-safe operations. The use of GIL implies that you will encounter a global lock when you attempt to access any Python objects contained within threads. And only one thread at a time can acquire the lock for a Python object or C API. 

Fortunately, things are not so serious, because, outside the realm of GIL, we can freely use parallelism. This category includes all the topics that we will discuss in the next chapters, including multiprocessing, distributed computing, and GPU computing.

So, Python is not really multithreaded. But what is a thread? What is a process? In the following sections, we will introduce these two fundamental concepts and how they are addressed by the Python programming language.