Getting Python

If it’s your first time with Python, people seem to recommend Anaconda as an easy-to-use environment that includes many basic packages. Anaconda is available for Windows, Mac OS X and GNU/Linux.

For those rolling their own on unix-like systems (GNU/Linux, Mac OS X) it’s always helpful to use a virtual environment for your python installation (and even easier to use with a virtualenv-burrito), in case you accidentally trash something.

Getting a solver for linear optimisation

PyPSA passes optimisation problems for Optimal Power Flow to an external solver. PyPSA is known to work with the free software Cbc, the free software GLPK and the non-free software Gurobi (and whatever else works with Pyomo).

For Cbc, see their installation instructions. For Debian-based systems you can do simply:

sudo apt-get install coinor-cbc

For GLPK in Debian-based systems execute:

sudo apt-get install glpk-utils

and there are similar packages for other GNU/Linux distributions.

For Windows there is WinGLPK. For Mac OS X brew is your friend.

Installing PyPSA with conda

If you are using conda you can install PyPSA with:

conda install -c conda-forge pypsa

or by adding the conda-forge channel to your conda installation with:

conda config --add channels conda-forge

and then installing simply with:

conda install pypsa

Installing PyPSA 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+

Manual installation with setuptools

PyPSA relies on the following packages which are not contained in a standard Python installation:

  • numpy

  • scipy

  • pandas

  • networkx

  • pyomo

  • cartopy

It is recommended to use PyPSA with the following additional packages:

  • iPython for interactive simulations

  • plotly for interactive plotting

  • matplotlib for static plotting

  • py.test for unit testing

In a unix-based environment these packages can be obtained with the pip Python package manager:

pip install numpy scipy pandas networkx pyomo ipython

To install PyPSA, you need to download the code from the PyPSA github repository and then go to the local repository and run:

python install

Or if you want to develop/modify the code in the current directory, run:

python develop

Conservative manual installation

If you’re very conservative and don’t like package managers, you can just download the code from the PyPSA github repository and add the directory of PyPSA to your python path with e.g.:

import sys


import pypsa

Upgrade all packages to the latest versions

PyPSA is only tested with the latest stable versions of all the dependent packages. Therefore it is very important that you upgrade these packages; otherwise PyPSA may not work.

To upgrade a package such as pandas with pip, do at the command line:

pip install -U pandas

In Anaconda the user manual suggests to upgrade packages with:

conda update pandas

Upgrading PyPSA

We recommend always keeping your PyPSA installation up-to-date, since bugs get fixed and new features are added. To upgrade PyPSA with pip, do at the command line:

pip install -U pypsa

Don’t forget to read the Release Notes regarding API changes that might require you to update your code.