iPython notebook on OSX Lion

ipython notebook

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.

Dependencies

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.

System Configuration

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:

:::bash
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:

:::bash
ln -s /opt/X11 /usr/X11

iPython Install

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.

:::bash
mkvirtualenv ipy

Now that we have a new virtualenv, lets get installing:

:::bash
workon ipy
$ pip install ipython

Once ipython has finished installing we need to install readline

:::bash
pip install readline

Then we install tornado for iPython Notebook

:::bash
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.

:::bash
brew install zeromq --universal

Once that is completed we can now install pyzmq with pip:

:::bash
pip install pyzmq

Next is the install of pygments for syntax highlights:

:::bash
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.

:::bash
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!!!

:::bash
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.

Science Modules

Now lets install numpy

:::bash
pip install numpy

We need some fortran to compile scipy, so before we can install scipy we
need:

:::bash
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:

:::bash
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.

:::bash
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: