Installing scientific computing packages for Python in Mac OS X

There are several options for installation Python and related packages in Mac OS X, two of which are described here. (A third option, not described here, is to piggyback off the built-in version of Python that exists in /usr/bin/python.) For an overview see: github.

Option 1. Enthought Python bundle

Enthought, Inc. has made available the Python Enthought Distribution, which bundles the Python interpreter (version 2.7.3) along with many useful packages for scientific computing (and, fortunately, most of what we need for the computational methods course).

Although you will not need everything provided in the Enthought bundle, the one-stop shopping (almost) is useful and quick. Download the package from the download page, follow the installation instructions, and complain (politely, of course) to Enthought if something goes awry.

The only thing missing from the Enthought distribution is Visual. Unfortunately Visual and Enthought do not play that well with one-another. Here is a hack which makes things work: -- stolen from (

Let me know if you come up with a better approach (I am willing to bet that instead of using easy_install you could just reinstall enthought, but I haven't checked).

Another thing you might want to do is update IPython. Enthought has a command line tool for doing this. Just type "enpkg ipython". Alternatively, download IPython, unpack the archive, and from that directory type "python install --user" -- the user flag means that it will be set up in your directory rather than the root directory. Consequently you will not need to enter your root password, and it will not mess anything up.

Option 2: Fink

Installing useful third-party software under Mac OS X is greatly simplified by Fink, a port of the Debian Linux apt and dpkg systems for package management. This option is useful if (a) you already have Fink running on your Mac OS X system, or (b) you will want to install other, non-Python-related packages that are also available through Fink.

Download Fink (from and install it. Optionally there is a separate program, called FinkCommander, that provides a graphical interface to Fink, but it is easy enough to use Fink from the command line. Fink manages dependencies, and will prompt you to install other packages if necessary. It installs everything it needs in the directory /sw.

Fink packages

Some of the packages listed below are classified by fink as "unstable". This does not make them unusable, but reflects rather that they have been tested less than the stable packages. Configure fink to "use unstable packages" so that these can be located. This can also be done - after fink has been installed - by editing the file /sw/etc/fink.conf and adding to the list of allowed Trees the "unstable/main" tree, so that your Trees line looks something like this: Trees: local/main stable/main stable/crypto unstable/main


The core python package: even though OS X comes with python preinstalled, you'll want to install a python package in fink; python27 is the most recent that works with Scipy. Subsequent to this, fink will install all other python-related packages in /sw/lib/python27/site-packages.


SciPy, which contains many useful algorithms for integrating ODEs, optimizing functions, etc. Note that the web site contains information on building SciPy under Mac OS X. The build via fink proposed here seems generally more reliable and manages all the various dependencies that one would otherwise need to worry about.


VPython or Visual Python, a 3D graphics environment


Matplotlib, a MATLAB-inspired plotting package


Python Imaging Library (PIL), useful for creating and manipulating images.


ImageMagick (fink package: imagemagick) provides utilities for manipulating images. Currently we are using the "display" utility to draw image files on the screen. The ImageMagick display utility (and probably many other pieces of ImageMagick) requires XWindows (e.g., Apple's X11, or Xfree86 under fink). Installing Apple's X11 opens a world of functionality, but if you're reluctant to do so, there is a workaround for displaying images. Apple's Preview application will display image files; instead of calling "display filename" to use ImageMagick's display, call "open /Applications/ filename" (even if this is being done in a system call within python).