This repository contains a series of interactive Jupyter notebooks to showcase various aspects of the book Elements of Electronic Structure Theory. You can easily open these notebooks via the MyBinder platform. Below, you can find a list of all the interactive notebooks.
Tip
- The latest version of the textbook can be obtained via this link
- For more information about the course book and other associated electronic resources, please visit this link
Note
Spot a mistake in any of the notebooks? Please raise an issue.
Note
We assume that the user is already familiar with using Python and installing packages in a development environment. The installation instructions provided below are intentionally brief and meant as a quick reference.
To run these notebooks locally, it is recommended to use Python version 3.12 or newer. First, create a virtual environment (optional but recommended):
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
Next, install all required packages using the provided requirements.txt file:
pip install -r requirements.txt
Finally, launch JupyterLab with:
jupyter lab
This will open JupyterLab in your default web browser. From there, you can navigate to and run the notebook interactively.
Note: If JupyterLab is not already installed, it will be installed automatically through the requirements file.
If you're running this notebook via mybinder.org, please be aware that the service does not always operate reliably. You may occasionally encounter issues such as "Internal Server Error", long loading times, or sluggish performance.
It's important to remember that mybinder is a free, community-supported service, and such limitations are to be expected. We should be empathetic to the fact that this generous resource is offered without cost and maintained by volunteers and open-source contributors.
The links provided below will take you to the mybinder.org website, where this notebook will be launched in a temporary online environment. No installation is needed — it's a great way to try things out quickly — but please keep in mind that performance and availability can vary.
For the best performance and stability, we recommend downloading the notebook and running it locally using JupyterLab or Jupyter Notebook on your own machine. This ensures faster load times, smoother interactivity, and a more responsive coding experience overall.