3. Set up the environment

3. Set up the environment#

1. Get the course material#

Download (or “clone”) the course repository (meaning “course folder”) from GitHub. In a terminal, navigate to a folder where you want to put the course folder. You can use cd to change the current folder, for example cd ~ to go to your home folder.

Warning

Clone into a folder that is not synced to the cloud: not Documents or Desktop if those live in OneDrive or iCloud, and not a Dropbox folder. The environment is several gigabytes in many thousands of files, and a sync client can interrupt installation or make it much slower. Your home folder is a suitable location.

So, unless you choose a different directory than your home folder, run:

cd ~

Then run the following command to clone the repository:

git clone https://github.com/bsse-scf/lab_course_image_analysis.git

Now you have a folder lab_course_image_analysis with the course material. Change into that folder:

cd lab_course_image_analysis

What is a repository?

A repository is a folder that contains files and a history of changes to those files. It is usually hosted on a service like GitHub, and for this course, it contains the course material, including notebooks, scripts, and data. You can think of it as a “course folder” that you can download and update.

2. Install the environment#

From inside the repository folder, run the following command:

pixi install

This builds the environment. It downloads around 3 GB and takes some minutes to complete. If the connection drops, run the same command again and it continues where it left off.

Already have conda?

If you already have Anaconda or Miniconda installed, leave it as is — pixi does not interact with it. Just make sure you run the course from a plain terminal, not from within an activated conda environment, and in JupyterLab always pick the Python 3 (ipykernel) kernel that appears by default rather than any other kernel you may have registered before.

3. Run a test to verify the environment works#

From inside the repository folder, run:

pixi run test-nb

The output should be green and say “7 passed”. If you see any errors, please let the tutors know.

4. Start Jupyter Lab#

JupyterLab is the main interface for the course. From inside the repository folder, run:

pixi run jupyter lab

Tip

pixi run <something> always runs the command inside the environment defined in the current directory. For those who are used to using conda, this is similar to running commands in an activated environment. You never need to “activate” anything, and you should not pip install into it: if a package is missing, it belongs in the pixi configuration.

How to start and stop JupyterLab

Starting:

Run from inside the repository folder:

pixi run jupyter lab

Stopping:

  • Close the browser tab

  • Press Ctrl-C in the terminal where you started JupyterLab

  • Confirm with y and Enter

  • If this doesn’t work, hit Ctrl-C several times

  • Optionally close the terminal window

Next: download the example data.