- Python 3 (tested on 3.9 and 3.10 )
- Libraries: look at the environment.yml configuration file
- A LP solver, even an open source one like GLPK (https://www.gnu.org/software/glpk/)
These instructions are meant to be hassle-free and do not constitute the best practices; those who know Python can look at the environment.yml file or the end of this Readme and manually install the requirements. If you don't have a solver installed on your machine, please follow the instructions to install and configure GLPK.
- Go to https://sourceforge.net/projects/winglpk/
- Download the latest version of the GLPK binaries
- Extract the contents to the folder of your choice
- Add the w64 folder from the glpk installation to the Path system variable
- Download and install the Anaconda distribution (https://www.anaconda.com/)
- Open an Anaconda command line: Start -> All apps -> Anaconda3 -> Anaconda Powershell
- Download the repository as a zip file, and extract its contents to a folder of your choice
- From the Anaconda command line, navigate to the folder where environment.yml file is located (using cd)
- Type the following command to create the environment: conda env create --name winter_school --file environment.yml
- After the command is correctly executed, Anaconda Command can be closed
- Open Jupyter: Start -> All apps -> Anaconda3 -> Jupyter (winter_school)
- Navigate to the location where you extracted the repository
- Select the 00_Python_Basics.ipynb
- Press Shift+Enter to run each cell; if the code runs without errors, you're ready for the tutorial session.
For those who know their way around with Python and do not want to make a complete installation, the required libraries are:
- numpy
- pandas
- openpyxl
- pyyaml
- matplotlib
- seaborn
- scikit-learn
- scikit-learn-extra
This is a work in progress, so feedback is greatly appreciated. Have fun!
Author: David Cardona-Vasquez
Copyright: Copyright 2023, Graz University of Technology
License: MIT
Status: Development