nbodykit is an open source project and Python package providing a set of algorithms useful in the analysis of cosmological datasets from N-body simulations and large-scale structure surveys.

Driven by the optimism regarding the abundance and availability of large-scale computing resources in the future, the development of nbodykit distinguishes itself from other similar software packages (i.e., nbodyshop, pynbody, yt, xi) by focusing on :

• a unified treatment of simulation and observational datasets by insulating algorithms from data containers
• reducing wall-clock time by scaling to thousands of cores
• deployment and availability on large, super-computing facilities
• an interactive user interface that performs as well in a Jupyter notebook as on super-computing machines

All algorithms are parallel and run with Message Passing Interface (MPI).

We perform integrated tests of the code, including all built-in algorithms, in a miniconda environment for Python 2.7, 3.5, and 3.6.

The official documentation is hosted on ReadTheDocs at http://nbodykit.readthedocs.org/.

Users can dive right into an interactive cookbook of example recipes using binder. We've compiled a set of Jupyter notebooks to help users learn nbodykit by example — just click the launch button below to get started!

Users can also view a static version of the cookbook recipes in the documentation.

We recommend using the Anaconda distribution of Python. To obtain the dependencies and install a package on OSX or Linux, use

$ conda install -c bccp nbodykit

We are considering support for Windows, but this depends on the status of mpi4py.

On the Cori and Edison machines at NERSC, we maintain a nightly conda build of the latest stable release of nbodykit. See the documentation for using nbodykit on NERSC for more details.