Application-level isolation versus system-level isolation

The easiest and most lightweight approach to isolation is to use application-level virtual environments. These focus on isolating the Python interpreter and the packages available within it. Such environments are very easy to set up, and are very often just enough to ensure proper isolation during the development of small projects and packages.

Unfortunately, in some cases, this may not be enough to ensure enough consistency and reproducibility. Despite the fact that software written in Python is usually considered very portable, it is still very easy to run into issues that occur only on selected systems or even specific distributions of such systems (for example, Ubuntu versus Gentoo). This is very common in large and complex projects, especially if they depend on compiled Python extensions or internal components of the hosting operating system. 

In such cases, system-level isolation is a good addition to the workflow. This kind of approach usually tries to replicate and isolate complete operating systems with all of its libraries and crucial system components, either with classical system virtualization tools (for example, VMWare, Parallels, and VirtualBox) or container systems (for example, Docker and Rocket). Some of the available solutions that provide that kind of isolation are explained later in this chapter.

Let's take a look at Python's venv in the next section.