I have been trying to connect Spyder to a docker container running on a remote server and failing time and again. Here is a quick diagram of what I am trying to achieve:
Currently I am launching the docker container on the remote machine through ssh with
docker run --runtime=nvidia -it --rm --shm-size=2g -v /home/timo/storage:/storage -v /etc/passwd:/etc/passwd -v /etc/group:/etc/group --ulimit memlock=-1 -p 8888:8888 --ipc=host ufoym/deepo:all-jupyter
so I am forwarding on port 8888. Then inside the docker container I am running
jupyter notebook --no-browser --ip=0.0.0.0 --port=8888 --allow-root --notebook-dir='/storage'
OK, now for the Spyder part – As per the instructions here, I go to
~/.local/share/jupyter/runtime, where I find the following files:
kernel-ada17ae4-e8c3-4e17-9f8f-1c029c56b4f0.json nbserver-11-open.html nbserver-21-open.html notebook_cookie_secret kernel-e81bc397-05b5-4710-89b6-2aa2adab5f9c.json nbserver-11.json nbserver-21.json
Not knowing which one to take, I copy them all to my local machine.
I now go to Consoles->Connect to an Existing Kernel, which gives me the “Connect to an Existing Kernel” window which I fill out as so (of course using my actual remote IP address):
(here I have chosen the first of the json files for
Connection info:). I hit enter and Spyder goes dark and crashes.
This happens regardless of which connection info file I choose. So, my questions are:
1: Am I doing all of this correctly? I have found lots of instructions for how to connect to remote servers, but not so far for specifically connecting to a jupyter notebook on a docker on a remote server.
2: If yes, then what else can I do to troubleshoot the issues I am encountering?
I should also note that I have no problems connecting to the Jupyter Notebook through the browser on my local machine. It’s just that I would prefer to be working with Spyder as my IDE.
Many thanks in advance!