To run the AiiDAlab for teaching on your local machine, we recommend to have Docker and Python installed. Since the instructions depend on the operating system, please select the appropriate section below.
-
Docker. To install Docker, please follow the instructions available on the Docker website for Linux or Mac.
-
Git. Usually, Git is already installed on Linux and Mac. If not, please install it using the package manager of your operating system. For instance, on Ubuntu, you can install Git by running the following command:
sudo apt update && sudo apt install git
On Mac, you can install Git using Homebrew:
brew install git
- Python. Python is also quite often pre-installed on Linux and Mac. If this is not the case, we recommend installing Python through Conda the minimal installed named Miniconda. The installation instructions are available on the Conda website.
- Docker. The Docker Desktop for Windows can be installed from the Docker website.
There is an important step when working on Windows: after downloading and installing Docker (note: Docker Desktop may prompt you to turn on WSL 2 during installation. Read the information displayed on the screen and turn on the WSL 2 feature to continue), open Docker.app, select "without login", answer a couple of survey questions and then move to the settings, Resources, Advanced, check that "You are using the WSL2 backend" is there, then in "Resources --> WSL integration" activate the "Ubuntu" flag (note: if the flag is still not there, repeat this check after the next step).
- Git and Python. Instead of installing Git and Python separately, we recommend installing the Windows Subsystem for Linux (WSL) and using the Ubuntu distribution. First, you should make sure that you have WSL 2 running. Once this is set, open PowerShell as an administrator and run the following commands:
wsl --set-default-version 2
wsl --install -d ubuntu
After this is completed, please open the Ubuntu WSL terminal from the start menu and execute:
sudo apt update && sudo apt install python3-pip
At this point you can decide to either use a pre-compiled image from the GitHub Container Registry (ghcr.io) or to build the image locally.
The latter approach is recommended if you run on a machine with a different architecture than x86_64
(e.g. ARM, e.g. Macbook Pro with M* processor).
The following sub-sections require to enter the commands in a terminal (Mac/Linux) or in the Ubuntu WSL terminal (on Windows).
To download the pre-compiled image from the GitHub Container Registry, please run the following command:
docker pull ghcr.io/nanotech-empa/aiidalab-for-teaching:main
Warning
The docker pull
command might not work. To fix that, you need to authenticate to GitHub first:
docker login ghcr.io -u <github-username>
Password: <your-token>
The access token can be created here. While creating it, please make sure to enable the following permissions:
* write:packages
* read:packages
* delete:packages
To rename the image to aiidalab/teaching
, please run the following command:
docker tag ghcr.io/nanotech-empa/aiidalab-for-teaching:main aiidalab/teaching
First, make sure the Docker Desktop is running.
Enter a folder where you want to keep the aiidalab-for-teaching repository (cd /path/to/your/folder
) and run the following command:
git clone https://github.com/nanotech-empa/aiidalab-for-teaching.git
Then enter the repository folder (cd aiidalab-for-teaching
) and build the container by running the following command:
execute:
docker build -t aiidalab/teaching .
To install aiidalab-launch, please run the following command in your terminal:
pip install aiidalab-launch
Once the container is built/downloaded, you can create a new profile with aiidalab-launch:
aiidalab-launch profile add teaching
with the following content:
port = 8891
default_apps = [ "mfa-cscs", "quantum-espresso",]
system_user = "jovyan"
image = "aiidalab/teaching"
home_mount = "aiidalab_teaching_home"
extra_mounts = []
aiidalab-launch start --profile teaching
aiidalab-launch stop --profile teaching
After the container is stopped, you can remove it by running the following command:
docker rm aiidalab_teaching
Also, you should remove the volume that contains all your data.
docker volume rm aiidalab_teaching_home