Summary: in this tutorial, you’ll learn about Python virtual environments.
Why do you need Python virtual environments?
Python stores all system packages in a folder that you specify when installing Python.
Typically, most system packages locate at subfolders of a path specified in the
To find this path, you can import the
sys module and display it as follows:
>>> import sys
It’ll show something like this:
When you use pip to install third-party packages, Python stores these packages in a different folder specified by the
>>> import site
It returns something like:
Code language: JSON / JSON with Comments (json)
If you have several projects that use only standard library, you’ll be fine.
However, it’ll be a problem when you have some projects that use third-party packages.
Suppose you have two projects that use different versions of a library.
Since there’s only one location to store the third-party packages, you cannot store different versions at the same time.
Of course, you can use pip to switch between versions by installing/uninstalling a package. But it will be time-consuming and won’t scale.
This is where virtual environments come into play.
What is a virtual environment?
Python uses virtual environments to create an isolated environment for every project.
In other words, each project will have its own directory to store the third-party packages.
In case you have multiple projects that use different versions of a package, you can store them in separate folders (or virtual environments).
Python 3 includes the virtual environment module (
venv) as a standard library. To create a virtual environment for a project, you use the
In the next tutorial, you’ll learn how to:
- Install pipenv to manage virtual environments.
- Create a development workflow using virtual environments.
- A Python virtual environment creates an isolated environment for a Python project.
- Use pipenv tool to manage virtual environments.