Python venv: how to create, activate, and delete

Let’s look at how to use the Python venv, short for Python virtual environment or virtualenv. You will learn how to create a venv, activate and deactivate it, delete it, and how a venv works internally. If you want to know why a venv is so useful, please read our introduction page on virtual environments first.

Creating a Python venv

There are several ways to create a Python virtual environment, depending on the Python version you are running.

Before you read on, I want you to point you to another tool, called pipenv. It combines the functionality of tools that you are about to learn; virtualenv and pip. Further on in this chapter, I will describe pipenv in detail.

Python 3.4 and above

If you are running Python 3.4+, you can use the venv module baked into Python:

$ python -m venv [directory]

This command will create a venv in the specified directory and copy pip and easy_install into it too.

All other Python versions

The alternative that works for any Python version is using the virtualenv package. You may need to install it first, system-wide, with:

$ sudo pip install virtualenv

Once installed, you can create a virtual environment with:

$ virtualenv [directory]

Python venv activation

Linux and MacOS venv activation

On Linux and MacOS, we activate our virtual environment with the source command. If you created your venv in the myvenv directory, the command would be:

$ source myvenv/bin/activate

Windows venv activation

To activate your venv on Windows, you need to run a script that gets installed by venv, like so:

C:\> env\Scripts\activate.bat

That’s it! We’re ready to rock! You can now install packages with pip, but I advise you to keep reading to understand the venv better first. Hang tight, as we’ll get to pip very soon.

How a Python venv works

When you activate a virtual environment, your PATH variable is changed. On Linux and MacOS, you can see it for yourself by printing the path with echo $PATH. On Windows, use echo %PATH%. In my case, on Windows, it looks like this:

/Users/erik/myvenv/bin:/usr/local/bin:/usr/bin:/bin:etcetera

As you can see, the bin directory of my venv is put in front of everything else, effectively overriding all the system-wide Python software. This works because when you enter a command that can’t be found in the current working directory, your OS starts looking at all the paths in the PATH variable. If your venv is there first, the OS will look there first before looking at system-wide directories like /usr/bin.

If you take a look inside the directory of your venv (in this case: myvenv), you’ll see something like this:

A Python venv directory tree
Virtualenv directory tree

You can see that:

  • The Python command is made available both as python and python3, and the version is pinned to the version with which you created the venv by creating a symlink to it.
  • All packages you install end up in the site-packages directory.
  • Activation scripts are generated for multiple shell types (bash, csh, fish)
  • Pip is made available under the names pip and pip3

Deactivate the Python venv

If you are done working on your project, it’s a good habit to deactivate its venv. Without deactivating it, all other Python code you execute will also run inside of it.

Luckily, deactivating your virtual environment couldn’t be simpler. Just enter this: deactivate. It works the same on all operating systems.

Deleting a Python venv

There’s no special command to delete a virtual environment if you used virtualenv or python -m venv to create your virtual environment, you gave it a directory to create this environment in. If you want to delete this venv, simply deactivate it (see above), and then remove the directory.

However, in case you used another tool to create the venv, chances are there is a special command. For example, if you used Pipenv, you can use the following command to delete the current venv:

pipenv --rm

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About the author

Erik is the owner of Python Land and the author of many of the articles and tutorials on this website. He's been working as a professional software developer for 25 years, and he holds a Master of Science degree in computer science. His favorite language of choice: Python!