Marimo behind Jupyter / JupyterHub about marimo HOT 6 OPEN

Love the project! Addresses many issues I have with Jupyter.

Another important use-case where having the backend running remotely is in cloud computing contexts where it make sense to keep the compute located close to the data. Both for efficiency and security reasons.

For example we run a JupyterHub setup in AWS that spawns per user pods on demand. Our users then access the Juptyer notebooks in their browser while accessing many Tb of data on S3 / EFS that would be slow and costly to process if the notebook was running locally.

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All that jupyter-*-proxy packages are based on https://github.com/jupyterhub/jupyter-server-proxy project. For example, there are proxy packages for R Shiny, Theia IDE, RStudio, Pluto.jl... I think, creating jupyter-marimo-proxy will make sense later, when marimo will be able to edit more notebooks simultaneously. For now, I am using jupyterhub on remote VPS for editing helper python files. In jupyter terminal I can run marimo edit.. or marimo run.. commands. We have options for specifying host and port already.

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In the short term, this will slow down our developer velocity since its another environment combination that will need to be test, supported, maintained.

Unless there is a neat solution to support this without sacrificing developer velocity, I not sure this would be supported (at least in core).

Taking a step back: why do you want to do this?

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I understand perfectly that's an important task to achieve that and your team bandwidth is limited.
Such a solution will make it possible to edit python files on a VPS without the need to have Python running on your computer. Moreover it could possibly open the multi user features that some other users are requesting (this part will be even harder as you will have to provide isolated environment for each user)

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Ah got it. I appreciate you explaining the importance of the feature

from marimo.

My pleasure!

If you want to try this kind of solution quickly with Pluto... here is a docker-compose.yml file for that purpose

version: '3.3'
services:
  jupyter_scipy_notebook:
    image: quay.io/jupyter/scipy-notebook:2024-02-24
    ports:
      - 10000:8888
    volumes:
      - ./local_dir:/home/jovyan/work
      - ~/data:/home/jovyan/data
      - ./certs/private.key:/etc/ssl/notebook/notebook.key
      - ./certs/certificate.crt:/etc/ssl/notebook/notebook.crt
    command: "start-notebook.py \
      --ServerApp.keyfile=/etc/ssl/notebook/notebook.key \
      --ServerApp.certfile=/etc/ssl/notebook/notebook.crt"
    #restart: unless-stopped
    restart: always

and run it using docker compose up (you probably won't need keyfile and certfile as it's not for production (no SSL)

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