gsd binaries are available in the glotzerlab-software Docker/Singularity images and in packages on conda-forge and PyPI. You can also compile gsd from source, embed gsd.c in your code, or read gsd files with a pure Python reader


Anaconda package

gsd is available on conda-forge. To install, first download and install miniconda. Then add the conda-forge channel and install gsd:

$ conda install -c conda-forge gsd

Singularity / Docker images

See the glotzerlab-software documentation for container usage information and cluster specific instructions.


Use pip to install gsd:

$ pip install gsd

Compile from source

Obtain the source

Download source releases directly from the web:

▶ curl -O

Or, clone using git:

$ git clone

Configure a virtual environment

When using a shared Python installation, create a virtual environment where you can install gsd:

$ python3 -m venv /path/to/environment --system-site-packages

Activate the environment before configuring and before executing gsd scripts:

$ source /path/to/environment/bin/activate


Other types of virtual environments (such as conda) may work, but are not thoroughly tested.

Install Prerequisites

gsd requires:

  • C compiler (tested with gcc 4.8-9.0, clang 4-9, vs2017-2019)

  • Python >= 3.5

  • numpy >= 1.9.3

  • Cython >= 0.22

Additional packages may be needed:

  • pytest >= 3.9.0 (unit tests)

  • Sphinx (documentation)

  • IPython (documentation)

  • an internet connection (documentation)

  • CMake (for development builds)

Install these tools with your system or virtual environment package manager. gsd developers have had success with pacman (arch linux), apt-get (ubuntu), Homebrew (macOS), and MacPorts (macOS):

$ your-package-manager install ipython python python-pytest python-numpy cmake cython python-sphinx python-sphinx_rtd_theme

Typical HPC cluster environments provide Python, numpy, and cmake via a module system:

$ module load gcc python cmake


Packages may be named differently, check your system’s package list. Install any -dev packages as needed.


You can install numpy and other python packages into your virtual environment:

python3 -m pip install numpy

Install with setuptools

Use pip to install the python module into your virtual environment:

$ python3 -m pip install .

Build with CMake for development

You can assemble a functional python module in the build directory. Configure with CMake and compile with make.

$ mkdir build
$ cd build
$ cmake ../
$ make

Add the build directory path to your PYTHONPATH to test gsd or build documentation:

$ export PYTHONPATH=$PYTHONPATH:/path/to/build

Run tests

Run pytest in the source directory to execute all unit tests. This requires that the compiled python module is on the python path.

$ cd /path/to/gsd
$ pytest

Build user documentation

Build the user documentation with Sphinx. IPython is required to build the documentation, as is an active internet connection. First, you need to compile and install gsd. If you compiled with CMake, add gsd to your PYTHONPATH first:

$ export PYTHONPATH=$PYTHONPATH:/path/to/build

To build the documentation:

$ cd /path/to/gsd
$ cd doc
$ make html
$ open _build/html/index.html

Using the C library

gsd is implemented in a single C file. Copy gsd/gsd.h and gsd/gsd.c into your project.

Using the pure python reader

If you only need to read files, you can skip installing and just extract the module modules gsd/ and gsd/ Together, these implement a pure Python reader for gsd and HOOMD files - no C compiler required.