Installation
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+https://github.com/PyPSA/PyPSA.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 setup.py install
Or if you want to develop/modify the code in the current directory, run:
python setup.py 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
sys.path.append("path/to/PyPSA")
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.