Installation

Prerequisites: python 3 (>3.3), and Jupyter 4 (with all dependencies).

The current alpha release version of the lambda notebook is 0.6.4, download the source here: https://github.com/rawlins/lambda-notebook/archive/v0.6.4.zip

After you install, I highly recommend installing a full version of MathJax and switching renderers. Instructions here: MathJax installation.

Installation via anaconda+download (all platforms, recommended for the current version)

Warning, this is a ~400MB download and the process can take a bit of time, so I don't recommend doing it in class (or the like).

1. Install Anaconda. This provides all the prerequisites for the lambda notebook.
2. Install the lambda notebook from github, e.g. by downloading from the link above or the master at https://github.com/rawlins/lambda-notebook/archive/master.zip, or by cloning the repository locally.
3. Run "lambda_notebook.py" in the install directory. On some systems you should be able to just double-click on this, or double click on "lambda_notebook.command" (mac), or on "lambda_notebook.cmd" (windows). On linux you should just run it from the command line.

Installation via pip+download (all platforms, recommended for the current version if you're comfortable with the command line)

1. First, install current Python 3 via http://www.python.org/. See http://ipython.org/install.html for more on installing IPython.
2. From the command line, use pip to install IPython/Jupyter. It is best to do this by calling pip3 to make it explicitly python3. More on installing Jupyter: http://jupyter.readthedocs.org/en/latest/install.html * Basically, run: pip3 install jupyter * Note that to successfully finish installing, this method may require a compiler. If you get an error message partway through the process, Jupyter notebook probably won't work. * On OS X, this probably means you need to install the command line tools via XCode (a free install from the app store). Or try anaconda.
3. Install the lambda notebook from github, e.g. by downloading from the link above or the master at https://github.com/rawlins/lambda-notebook/archive/master.zip, or by cloning the repository locally.
4. At the command line in the lambda_notebook directory, run python3 lambda_notebook.py, which will install the kernel and launch a notebook pointed at a directory with the pre-installed notebooks.

Installation via a self-contained download (mac only, easy, but very outdated)

On 10.8 or later, download lambda notebook alpha version 0.5, from https://github.com/rawlins/lambda-notebook/releases/download/v0.5/Lambda.Notebook-0.5.dmg. Open the dmg and drag the app to your Applications folder (or wherever you'd like it). You may need to enable it in gatekeeper. (See the README.txt for more details.)

On 10.6 or 10.7, you can get a (very untested) dmg here.

Other installation methods

• You can install the dependencies via your OS's package manager, such as macports. This is not recommended, as it may lead to out of date versions of Jupyter.
• If you are technically inclined and prefer virtualization, the lambda notebook can be installed with docker pull rawlins/lambda-notebook. This also (at the moment) pulls the jupyter datascience-notebook, so it is a very large pull, ~5GB. See https://github.com/rawlins/ling-docker for more information.