Python is a good language, but its tooling (like
requirements.txt, and the awkward support for binaries needed for libraries like scipy, keras, etc), leaves much to be desired. And for most scientists, it’s simply not interesting using all these build tools when you just want to get coding quickly on a new machine.
The most simplest, most reliable way I’ve found to get jupyter installed is to first install docker. Then we just run a single command – but before you do so, please replace
/path/to/my/notebooks with your local directory where you have been storing notebooks.
docker run --rm -p 8888:8888 --mount type=bind,source=/path/to/my/notebooks,target=/home/jovyan/work --name my-py-notebook jupyter/scipy-notebook
You’ll see some stuff printed out, but the only thing you care about is the “Token”. Now browse to http://localhost:8888, and paste in the token into the password field. Done!
Because we bind-mounted
/path/to/my/notebooks, your notebooks will be persisted, but the docker container will be closed when you are done with it. Stop the container by typing this in a new terminal:
docker stop my-py-notebook