lsst-rsp

User-facing Python classes and functions for use in the RSP environment. Learn more at https://lsst-rsp.lsst.io

Install from PyPI:

pip install lsst-rsp

but, really, lsst-rsp is only useful inside an RSP JupyterLab container.

See below for how to test new versions within such a container.

lsst-rsp is developed by Rubin Observatory at https://github.com/lsst-sqre/lsst-rsp.

Developing lsst-rsp

The best way to start contributing to lsst-rsp is by cloning this repository, creating a virtual environment, and running the make init command:

git clone https://github.com/lsst-sqre/lsst-rsp.git
cd lsst-rsp
make init

You can run tests and build documentation with tox:

tox

To learn more about the individual environments:

tox -av

Developing lsst-rsp on the RSP

The LSST kernel in the RSP sciplat-lab image already has a release version of lsst-rsp in it. Therefore, there is some setup you need to do in order to create a development environment you can use. Specifically, you need to create a virtualenv for the editable lsst-rsp, install tox and pre-commit for its test machinery, and then create a JupyterLab kernel pointing to it.

Open a terminal session:

VENV="lsst_rsp"
mkdir -p ${HOME}/venvs
python -m venv ${HOME}/venvs/${VENV}
. ${HOME}/venvs/${VENV}/bin/activate
mkdir -p ${HOME}/src
cd ${HOME}/src
git clone https://github.com/lsst-sqre/lsst-rsp # or git@github.com:lsst-sqre/lsst-rsp.git if you prefer
cd lsst-rsp
make init
pip install ipykernel
python -m ipykernel install --user --name=${VENV}

Now you will need to shut down your lab and get a new container image. That's because the process your Lab interface is running inside doesn't know about the new kernel--but once you restart the Lab container, it will.

Once you're in your new container, you will notice that you have a new kernel named lsst_rsp.

Now you've got an editable version installed in your custom kernel, and you can still run all the usual tox environments too.

If you start a notebook with your custom kernel,

import lsst.rsp

lsst.rsp.__version__

will show you your development version. Note that you will still need to restart the kernel to pick up changes you make to your copy of lsst_rsp.

Uninstalling a development version from the RSP

Open a terminal window.

. $HOME/venvs/lsst_rsp/bin/activate
jupyter kernelspec uninstall lsst_rsp
y
deactivate

Shut down and restart your notebook as before. When you come back in, in a terminal window:

rm -rf $HOME/venvs/lsst_rsp

You will need to remove the virtualenv directory after restarting the Lab container, because otherwise JupyterLab will be holding some files open because it still believes it has a kernel there.