TRIQS and its applications are provided a la carte: after you have installed the TRIQS library, you will be able to easily install various TRIQS-based applications: impurity solvers, tools for DFT+DMFT calculations, etc.

This page describes the installation of the TRIQS library itself. The installation procedure of the applications is described on their respective sites, under ‘Install’.


The TRIQS project is in perpetual dynamic evolution such that we can get our developments directly to users straight out of the oven.

However, we also understand that some users may not wish to constantly update their codes, and are happy to use an older but perhaps more stable version.

To this end, we propose two options to the user:

  1. You follow the master branch in the git repository of TRIQS and all applications. This will guarantee that you are using the latest stable release including essential bug-fixes. Note that new releases might occasionally include changes of the API, which we summarize in a set of release notes. We use continuous integration to ensure that the master branch always compiles and passes all tests. This is checked for both the TRIQS library and several public (and private) applications.
  2. You use a version tag, e.g. version 2.0, for TRIQS and all applications. This guarantees complete reproducibility, while you might be missing out on the latest features and bug-fixes.

Packaged Versions of TRIQS

Ubuntu Debian packages

We provide Debian packages for the Ubuntu LTS Versions 16.04 (xenial) and 18.04 (bionic).:

sudo apt-get update && sudo apt-get install -y software-properties-common apt-transport-https curl
source /etc/lsb-release
curl -L$DISTRIB_CODENAME/public.gpg | sudo apt-key add -
sudo add-apt-repository "deb$DISTRIB_CODENAME/ /"
sudo apt-get update && sudo apt-get install -y triqs

This will install the minimal runtime packages and triqs into the system tree at /usr.


Since TRIQS version 2.1 we include cpp2py in the TRIQS debian package. If you have installed an earlier packaged version of triqs (or cpp2py) be sure to remove it before updating TRIQS to avoid package conflicts.

If you aim to compile applications against the triqs library, additional development libraries have to be installed. You should further set the following environment variable permanently:

export CPLUS_INCLUDE_PATH=/usr/include/openmpi:/usr/include/hdf5/serial/:$CPLUS_INCLUDE_PATH

For full c++2py functionality, please read the corresponding section for the Ubuntu set-up.

Anaconda (experimental)

We provide Linux and OSX packages for the Anaconda distribution. The packages are provided through the conda-forge repositories. After installing conda you can install TRIQS with:

conda install -c conda-forge triqs

See also We further provide packages for triqs_cthyb, triqs_dft_tools and triqs_tprf.


The virtualization software docker can be used to run a TRIQS environment for both Jupyter Notebook and shell access on a variety of operating systems. Once docker is installed, just pull the latest image with:

docker pull flatironinstitute/triqs

and follow the commands on the image-website.


The virtualization software singularity allows for easy set-up on cluster machines. Ask your cluster administator to install the singularity software. The TRIQS setup is then as simple as:

singularity pull docker://flatironinstitute/triqs

which will generate an image file triqs_latest.sif. You can then execute commands inside this image file, e.g.:

singularity exec triqs_latest.sif python -c "from pytriqs import *"

In order to run your code in parallel you will need to use Open MPI version 2.1.1 to match the version of the singularity image. You can then run any command in parallel, e.g.:

mpirun -np 2 singularity exec triqs_latest.sif python -c "from pytriqs.utility import mpi; print mpi.rank"

For more information on the use of singularity in conjunction with docker images please refer to the documentation.


Binder is a web-service running Jupyter notebooks for direct access. A TRIQS Jupyter notebook environment can be accessed directly at


Once your binder session is closed, your work will be lost.

Compiling TRIQS from source (Advanced)


The TRIQS library relies on a certain number of standard libraries and tools described in the list of requirements. Please pay particular attention to the C++ compilers and to Python virtual environments. Here are instructions to install these necessary libraries on two standard systems:


Please ensure that you have all the dependencies installed before proceeding further!

Installation steps

We provide hereafter the build instructions in the form of a documented bash script. You can adapt INSTALL_PREFIX, NCORES for your local settings. Note that, contrary to previous versions of TRIQS, the installation directory CMAKE_INSTALL_PREFIX is now mandatory in the cmake configuration.


# Set this variable to your desired install directory

# Set the number of cores for the compilation

# Clone the git repository of triqs
git clone triqs.src

# Use cmake to configure the triqs build process
mkdir -p && cd

# Build, test and install triqs
make -j$NCORES && make test && make install
cd ../

# Load the triqs installation into your environment
source $INSTALL_PREFIX/share/

echo "If you want to automatically load triqs into your environment,"
echo "please add the following line to your ~/.bash_profile (or ~/.zprofile):"
echo "source $INSTALL_PREFIX/share/"


Caution: The compilation of TRIQS, even if run in serial mode, can temporarily use up to 4 Gigabytes of RAM. The restrictions on the Login-Nodes of certain HPC Machines might not provide sufficient memory for the compilation. Please consider compiling within an interactive session on a Compute-Node or contact the admins of your HPC Machine.

Environment setup

TRIQS provides a small script ( to load its installation into your environment variables. Please source it with the proper replacement of INSTALL_PREFIX:

source $INSTALL_PREFIX/share/

To automate this process, please add this line to your ~/.bash_profile (or ~/.zprofile)