Note: if you prefer to use your system’s globally installed packages and to install from Hackage, see the section below. If you run into any issues see the support page.
The easiest way to get started on Linux or OS X is using Stack and its built-in Nix support:
$ git clone http://github.com/tweag/HaskellR
$ cd HaskellR
$ git tag -l # list releases
$ git checkout v<latest-release> # skip if you want the master branch
$ stack --nix build
You can make passing --nix to all Stack commands implicit by adding
nix:
enable: true
to your stack.yaml. Alternatively, use Docker, which like Nix
obviates the need to install any dependencies globally on your system:
$ stack --docker build
If you’d rather use your system’s globally installed packages, here are the system dependencies we rely on:
R version 3.0.2 or later (3.1 or later required for test suite).OS X users: use Homebrew to install dependencies, e.g.
$ brew update
$ brew tap homebrew/science
$ brew install r zeromq
$ pip install ipython # Only needed for IHaskell support
Windows users: Only inline-r and H are supported (no Jupyter
support yet). After installing R somewhere on your system, you’ll need
to pass additional flags when building and installing, as in the
following example:
$ stack build H --extra-lib-dirs=C:\R\bin\i386 --extra-include-dirs=C:\R\include
Once the system dependencies are installed, you can install H or the Jupyter kernel as below.
You can launch the H interactive environment locally:
$ stack [--nix|--docker] exec H
But you can also install it user-globally to ~/.local/bin:
$ stack build --copy-bins H
Make sure to include the installation directory in your PATH. On
UNIX systems:
$ export PATH=~/.local/bin:$PATH
H is a very basic interactive environment. It is easy to install. If you would like a more featureful environment, HaskellR includes a plugin for Jupyter’s IHaskell kernel. Since the latter depends on a number of system libraries that may or may not be installed using exactly the right configuration by your distribution, on Linux and OS X it is recommended to use Stack’s Nix or Docker support to get reliable installs.
$ stack [--docker|--nix] exec ihaskell install
Now, you can open a new Jupyter notebook in your browser using
$ stack [--docker|--nix] exec jupyter notebook
After launching the Jupyter notebook server you can visit
http://localhost:8888/notebooks/IHaskell/examples/tutorial-ihaskell-inline-r.ipynb
in your browser for an interactive tutorial, which is available in static form here.