Installation#
Getting Python#
If it is your first time with Python, we recommend conda, mamba or pip as easy-to-use package managers. They are available for Windows, Mac OS X and GNU/Linux.
It is always helpful to use dedicated conda/mamba environments or virtual environments.
Installation with conda#
If you are using conda you can install PyPSA with:
conda install -c conda-forge pypsa
Replace conda with mamba if you use this alternative.
Installing with pip#
If you have the Python package installer pip then just run:
pip install pypsa
If you’re feeling adventurous, you can also install the latest master branch from github with:
pip install git+https://github.com/PyPSA/PyPSA.git
Getting a solver#
PyPSA passes optimisation problems for System Optimization to an
external solver. PyPSA is known to work via linopy with the free software
and the non-free software, commercial software (for some of which free academic licenses are available)
An installation of PyPSA will automatically install the default solver HiGHS. For installation instructions of further solvers for your operating system, follow the links above.
Note
Commercial solvers such as Gurobi, CPLEX, and Xpress currently significantly outperform open-source solvers for large-scale problems. It might be the case that you can only retrieve solutions by using a commercial solver.
Upgrading PyPSA#
We recommend always keeping your PyPSA installation up-to-date, since bugs get fixed and new features are added. PyPSA is also only tested with the latest stable versions of all the dependent packages for the respective Python versions.
To upgrade PyPSA with pip, do at the command line:
pip install -U pypsa
To upgrade PyPSA with conda, do at the command line:
conda update pypsa
Don’t forget to read the Release Notes regarding API changes that might require you to update your code.