Working with MacPorts and Python

Date: 2022-02-12

For a number of reasons, I prefer MacPorts over Homebrew to manage packages on my macOS machines.

Working with multiple versions of Python can be a headache. In this post, I’ll describe how I use MacPorts to manage Python versions for development purposes.

For context, I’ve tried a number of different ways to manage Python on my macOS computers over the years: Anaconda, Homebrew-provided Python packages, pyenv, etc., and this is what I found works best for me.

Unlike Homebrew, MacPorts does not clutter up your /usr/local directory, by default installing packages to /opt/local instead. And unlike Anaconda, MacPorts Python packages work harmoniously with other packages on your system, and does not try to supplant your system compiler.

With that said, let’s move on to a few practical tips on using MacPorts to manage Python versions. In the following instructions, I assume that you have already installed MacPorts on your system1.

Managing multiple versions of Python and pip

To install a specific version of of Python along with the corresponding version of pip, do

where <major> and <minor> are the major and minor version number of Python that you are trying to install2. For example, if you wanted to install Python 3.10 (the latest version at the time of writing this (2022-02-12)), you would run the following command.

To activate a particular version of Python and pip, you would use the port select command. You can put the following snippet in your ~/.bash_profile3 to simplify the process.

The above snippet defines a function named activate_py that can be invoked to switch between Python versions. For example:

will activate Python 3.10 and the corresponding version of pip.

Managing packages

Python packages can either be installed within a virtual environment or system-wide. I’ll describe both methods and when to use them below.

Installing packages in virtual environments

In general, it is best to have a distinct Python virtual environment for each Python project you are working on that may have conflicting dependencies. I have the following snippet in my ~/.bash_profile to create a virtual environment in a directory called ~/.venvs (the directory will be created if it does not yet exist).

For example, if you invoke the following command:

a virtual environment named myproject will be created at ~/.venvs/myproject.

Note that if you are using Python 24, you will also need to install the appropriate version of the virtualenv package separately in order for the above snippet to function. For example, if you are using Python 2.7, you will also need to run the following command to enable the creation of Python 2.7 virtual environments:

I also have the following companion snippet in my ~/.bash_profile to quickly activate virtual environments that have been created with make_venv.

For example, invoking activate myproject at the command line will activate the myproject virtual environment, automatically pointing your python and pip invocations to the correct binaries, and bringing the packages installed within the virtual environment into scope for usage in Python scripts. Note that you must activate the virtual environment before installing packages in order to correctly isolate the package installations.

Installing packages system-wide (advanced)

If you do not anticipate working on multiple Python projects with potentially conflicting dependencies, this route might be the one for you, since you would not need to activate virtual environments every time you wanted to do anything Python-related that goes beyond Python’s standard library. However, if you are still new to juggling multiple versions of Python, I would recommend simply sticking with the virtual environment approach outlined above. It is easier to go from virtual environments to system-wide package installations than the other way around5.

Popular packages such as numpy and matplotlib have dedicated ports and can be installed system-wide by invoking:

For example, running the following command

will install numpy system-wide for the version of Python that you currently have active. If you want to check whether a port exists for a given Python package, you can use the port search command:

If you want to install a package system-wide that does not have an existing port, you can simply use pip:


  1. Ideally, you would also have removed other Python distributions that you installed yourself (e.g. the one from Python.org, Anaconda, etc.), unless you are a bit more advanced and thus adept at managing your PATH environment variable appropriately to work with multiple Python distributions.

  2. The sudo in the invocation is required if you install MacPorts to the default location (/opt/local). However, if the MacPorts root directory is somewhere else, e.g., in your home directory (e.g., ~/macports), then you may not need to prefix your invocation with sudo.

  3. If you are using zsh, put the snippet in ~/.zprofile instead.

  4. Python 2 support ended on January 1, 2020, so you really should not be using it unless you are working with legacy code that is completely unfeasible to port to Python 3.

  5. The two methods can also co-exist if you pass the command line flag --system-site-packages to the python -m venv invocation, but that is beyond the scope of this post, since it is unlikely that you will need to do this.