I've successfully installed iPython Notebook on a few different versions of OSX in recent months. There are quite a few methods of accomplishing this task and many of them seem quite elegant. The fact remains that installing iPyNB is not as strait forward as one might like and hopefully you find this of some utility.
This was built on a Mac running OSX 10.8.2 with the command line tools installed. I deleted my version of Xcode because it takes up a lot of space on my SSD and I am not a mac dev (at the moment). You can sign up for a free ID with Apple to get the download and there are lots of other goodies in the download area.
My system also has the package manager Homebrew installed. You could probably build everything here by hand, but why not leverage community efforts that lead to less stress, effort and error prone configuration? Install Homebrew, be happy and get to work orders of magnitude faster.
The C language ecosystem is a bit perplexing as an outsider with no real experience with the language and tool-chain. Thanks to the good people at Google, we can enter the foray with battle paint and Bluetooth keyboards. In all seriousness, I am not entirely sure why I had to do these steps with OSX Mountain Lion... but I did and you might want to follow suit.
...et cetera, et cetera...
The "fix" I came to realize after lots of head banging was Critical as ML ships with llvm-gcc-4.2. Homebrew and a lot of the software it builds do not like llvm-gcc-4.2. They make it known when they refuse to install the packages you've requested. Here is what you do:
$ sudo ln -s /usr/bin/llvm-gcc-4.2 /usr/bin/gcc-4.2
Yep, not much... but boy was that frustrating to figure out. The other story here is to download X11 via Quartz 2.7.2+, then install and symlink it in:
$ ln -s /opt/X11 /usr/X11
Now that we have that fun stuff taken care of we can install iPython Notebook and some science-y tools. To get started you should probably look into some kind of environment manager. virtualenv burrito is a good start to get up and running quickly. I know there are many ways to skin this cat: pythonbrew, virtualenv, virtualenvwrapper.
Pick one and go for it. I was weary of Pythonbrew until a few weeks ago when it became active again. I think it is the closest thing to Ruby's RVM and it worked for me in a VM. However, I wanted to try virtualenv burrito as it nicely packages virtualenv += wrapper and has performed flawlessly thus far. Seriously pick one move on.
$ mkvirtualenv ipy
Now that we have a new virtualenv, lets get installing:
$ workon ipy $ pip install ipython
Once ipython has finished installing we need to install readline
$ pip install readline
Then we install tornado for iPython Notebook
$ pip install tornado
The next item is the installation of the ZeroMQ library. Ultimately we want to install pyzmq. However, its a bit dicey using pip for reasons explained on their repo page here.
$ brew install zeromq --universal
Once that is completed we can now install pyzmq with pip:
$ pip install pyzmq
Next is the install of pygments for syntax highlights:
$ pip install pygments
After pygments installs we need to install freetype and libpng via Homebrew. The reason we want ipython is for the super awesome graphics, right? Well, you need these badboys to get super awesome graphics.
$ brew install freetype $ brew install libpng
Now time to install pyqt. I believe there is some misconception about pyqt and what is needed to install it correctly. If you followed this Sympy wiki entry you would install the QT stuff prematurely. Before I installed pyqt, I had a gander at the Homebrew formula. In it, I noticed that pyqt will download and install all the dependencies to make it work. I am telling you, Homebrew will make you happy!!!
$ brew install pyqt
YOU HAVE DONE IT!!! You now have a fully functional iPython qtconsole and notebook. I suggest installing in this order to minimize errors.
Now lets install numpy
$ pip install numpy
We need some fortran to compile scipy, so before we can install scipy we need:
$ brew install gfortran
Note: I found that homebrew would hang on the mpfr dependency. I filed a bug and it was fixed in less than 8 hours on a Sunday. That is Fucking Awesome. (not much else to say)
Now we can go get scipy:
$ pip install scipy
Some folks recommend installing matplotlib from git on ML. I took one for the team and just let it rip with pip and it worked great.
$ pip install matplotlib
These are probably the bare essentials to get started with some science. You may want to install Pandas, Sympy, stats models, pymc and others if you are a ninja. I am in the process of learning the math required to really use these libraries/modules, so I am definitely not a ninja just yet... but watch this space.
Here are some cool notebooks to play around with: