Python virtual environments create isolated contexts to keep dependencies required by different projects separate so they don't interfere with other projects or system-wide packages. The other use case that magnifies the importance of using Python virtual environments is when you’re working on managed servers or production environments where you can’t modify the system-wide packages because of specific requirements. This would lead to compatibility issues because Python cannot simultaneously use multiple versions of the same package. For example, imagine working on two different data visualization projects that use the matplotlib package, one using version 2.2 and the other using version 3.5. The importance of Python virtual environments becomes apparent when we have various Python projects on the same machine that depend on different versions of the same packages. Why Are Python Virtual Environments Important?

As the illustration above shows, a virtual environment is a folder tree containing a specific Python version, third-party libraries, and other scripts thus, there is no limitation on the number of virtual environments on a system because they are just folders containing some files. The figure above illustrates what you have on your system when we create multiple Python virtual environments. Thus, we can create multiple virtual environments with different Python versions, plus different libraries or the same libraries in different versions.

These virtual environments are isolated from the other virtual environments, which means any changes on dependencies installed in a virtual environment don’t affect the dependencies of the other virtual environments or the system-wide libraries. What Are Python Virtual Environments?Ī Python virtual environment consists of two essential components: the Python interpreter that the virtual environment runs on and a folder containing third-party libraries installed in the virtual environment. Note: that this tutorial is mainly for macOS and Linux users however, Windows users should also be able to follow along. If you need to install Python on Mac, refer to the tutorial Getting Python Up and Running on Mac. How to use Python virtual environments in VS Code.How to install packages in virtual environments and reproduce them on other systems.How to create, activate, deactivate, and delete virtual environments.The benefits of working in virtual environments.In this tutorial, we'll learn about Python virtual environments, the benefits of using virtual environments, and how to work inside virtual environments.Īfter you finish this tutorial, you’ll understand the following:

Python venv