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.
PyPSA passes optimisation problems for :doc:`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.
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
PyPSA relies on the following packages which are not contained in a standard Python installation:
- numpy
- scipy
- pandas
- networkx
- pyomo
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
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
PyPSA is only tested with the latest stable versions of all the dependent packages (pandas, pyomo, networkx, etc.). 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
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 pandas
Don't forget to read the :doc:`release_notes` regarding API changes that might require you to update your code.