Download and installation

Requirements

Calliope is tested on Linux, macOS, and Windows.

Running Calliope requires four things:

1. The Python programming language, version 3.10 to 3.12.
2. A number of Python add-on modules including Pyomo, Pandas and Xarray.
3. An optimisation solver: Calliope has been tested with CBC, GLPK, Gurobi, and CPLEX. Any other solver that is compatible with Pyomo should also work.
4. The Calliope software itself.

Recommended installation method

The easiest way to get a working Calliope installation is to use the free mamba package manager, which can install all of the four things described above in a single step.

To get mamba, the most straightforward approach is to download and install the "Miniforge" distribution for your operating system.

Tip

Another option is to use the commercially developed Anaconda Python distribution, which is available for all operating systems and comes with a graphical user interface to install and manage packages. If you use the Anaconda distribution, you have to replace mamba with conda in the installation instructions below.

With the package manager installed, you can create a new environment called calliope with Calliope as well as the free and open source GLPK solver. Run the following command in a terminal or command-line window:

mamba create -n calliope -c conda-forge/label/calliope_dev -c conda-forge calliope glpk

Note

The conda-forge/label/calliope_dev channel allows you to access the pre-release of Calliope v0.7, with which this version of the documentation aligns. To install the most recent stable version of Calliope, see our v0.6.10 documentation.

This will install calliope with Python version 3.12.

To use Calliope, you need to activate the calliope environment each time

mamba activate calliope

Warning

Although possible, we do not recommend installing Calliope directly via pip (pip install calliope). Non-python binaries are not installed with pip, some of which are necessary for stable operation (e.g., libnetcdf).

Updating an existing installation

If following the recommended installation method above, the following command, assuming the mamba environment is active, will update Calliope to the newest version

mamba update -c conda-forge calliope

Choosing a solver

You cannot solve a Calliope model until you have installed a solver. The easiest solver to install is GLPK. However, we recommend to not use this solver where possible, since it performs relatively poorly (both in solution time and stability of result). Indeed, our example models use the free and open source CBC solver instead, but installing it on Windows requires an extra step. CBC (open-source) or Gurobi (commercial) are recommended for large problems, and have been confirmed to work with Calliope. The following subsections provide additional detail on how to install a solver. This list is not exhaustive; any solvers supported by Pyomo can be used.

CBC

CBC is our recommended option if you want a free and open-source solver. CBC can be installed via conda on Linux and macOS by running mamba install -c conda-forge coin-or-cbc. Windows binary packages are somewhat more difficult to install, due to limited information on the CBC website, but are included in their package releases on GitHub. The GitHub releases are more up-to-date. We recommend you download the relevant binary for CBC 2.10.11 and add cbc.exe to a directory known to PATH (e.g. an Anaconda environment 'bin' directory).

GLPK

GLPK is free and open-source, but can take too much time and/or too much memory on larger problems. GLPK can be installed from conda-forge on all platforms: mamba install glpk. It is therefore the easiest solver to have installed in your Calliope environment.

Gurobi

Gurobi is commercial but significantly faster than CBC and GLPK, which is relevant for larger problems. It needs a license to work, which can be obtained for free for academic use.

The Gurobi solver interface can be installed via conda (mamba install gurobi::gurobi).

After installing, log on to the Gurobi website and obtain a (free academic or paid commercial) license, then activate it on your system via the instructions given online (using the grbgetkey command).

Note

If using the Gurobi solver, you can also leverage the reduced time and memory consumption of our Gurobi optimisation problem backend - this circumvents Pyomo entirely.

CPLEX

Another commercial alternative is CPLEX. IBM offer academic licenses for CPLEX. Refer to the IBM website for details.