When it’s finished, you should have a directory with a few subdirectories in it. The whole process of setting up the virtual environment may take a minute or two. (See this article for more about using the py launcher in Windows.) On Windows, you can use py instead of python to reliably access an installed Python version. Note that you should use python3 instead of python if your system recognizes a version of Python 2 as the default Python interpreter. To create a virtual environment in a given directory, type: Likewise, you could download a standalone copy of the Python interpreter, unpack it into a folder, and use it to run scripts and packages devoted to it.

Nothing says you can’t simply unpack a Python library into a subfolder of a project and use it that way.

You want to run a “baseline” version of the Python interpreter on a system with no third-party packages, and only install third-party packages for each individual project as needed.

You want to experiment with a specific combination of packages under highly controlled circumstances, for instance to test cross-compatibility or backward compatibility.

This may be because you’re working in a highly controlled environment, such as managed hosting, or on a server where the choice of interpreter (or packages used in it) can’t be changed because of production requirements.

You’re working in a Python environment where you can’t modify the site-packages directory.

You’re developing multiple projects that depend on different versions of the same packages, or you have a project that must be isolated from certain packages because of a namespace collision.

There are a few common use cases for a virtual environment: Even large, complex packages with platform-dependent binaries can be corralled off from each other in virtual environments.

The packages installed in each virtual environment are seen only in that virtual environment and no other. Each virtual environment contains a discrete copy of the Python interpreter, including copies of its support utilities.

A virtual environment is a way to have multiple, parallel instances of the Python interpreter, each with different package sets and different configurations.

Virtualenv