202 points | by mscolnick4 天前
The Godot docs mention coi-serviceworker; https://github.com/orgs/community/discussions/13309 :
gzuidhof/coi-serviceworker: https://github.com/gzuidhof/coi-serviceworker :
> Cross-origin isolation (COOP and COEP) through a service worker for situations in which you can't control the headers (e.g. GH pages)
CF Pages' free unlimited bandwidth and gitops-style deploy might solve for apps that require more than the 100GB software cap of free bandwidth GH has for open source projects.
These are two separate features:
1) marimo.app + github.com/path/to/nb.ipynb does run on marimo.app infra. this is what the Show HN was about
2) separately, you can use the marimo CLI to export assets to deploy to GitHub page: `marimo export html-wasm notebook.py -o output_dir --mode run` which can then can be uploaded to GH pages. This does not find all the data in your repo, so you would need to stick any data you was to access in a /public folder for your site. More docs here: https://docs.marimo.io/guides/exporting/?h=marimo+export+htm...
That would be most useful imho !
The data sharing is awesome. I previously used Google Colab to share runnable code with non-dev coworkers, but their file support requires some kludges to get it working decently.
I know I should just RTFM, but are you all working on tools to embed/cross-compile/emulate non-python binaries in here? I know this is not a good approach, but as a researcher I would love to shut down my server infrastructure and just use 3-4 crusty old binaries I rely on directly in the browser.
I really like Observable as well, but I've found it difficult to find robust and broad numerical libraries in javascript like what Python has.
I would love for this type of tool to redefine how we do science. It would be amazing if many scientific papers included both their data and the code in an interactive environment with zero installs and configuration. Plus when discussing a paper you could "fork" it and explore different analysis options live which for many fields would be totally feasible to do in the browser.
notebooks vs research code are sometimes very separate, very difficult to directly reproduce. A big difficultly with "working out of the box, shared in browser" is that weights, training, inference, simulations- are all still very compute intensive.
BUT the nice thing about a stateless notebook, is that you can precompute values- and cache them. I've been really excited about expanding marimo's caching system, and would love to get to a point whether sharing a notebook means being able to run the research yourself without some big setup dance.
> Notebooks created from GitHub links have the entire contents of the repository mounted into the notebook's filesystem. This lets you work with files using regular Python file I/O!
Could BusyBox sh compiled to WASM (maybe on emscripten-forge) work with files on this same filesystem?
"Opening a GitHub remote with vscode.dev requires GitHub login? #237371" ... but it works with Marimo and JupyterLite: https://github.com/microsoft/vscode/issues/237371
Does Marimo support local file system access?
jupyterlab-filesystem-access only works with Chrome?: https://github.com/jupyterlab-contrib/jupyterlab-filesystem-...
vscode-marimo: https://github.com/marimo-team/vscode-marimo
"Normalize and make Content frontends and backends extensible #315" https://github.com/jupyterlite/jupyterlite/issues/315
"ENH: Pluggable Cloud Storage provider API; git, jupyter/rtc" https://github.com/jupyterlite/jupyterlite/issues/464
Jupyterlite has read only access to GitHub repos without login, but vscode.dev does not.
Anyways, nbreproduce wraps repo2docker and there's also a repo2jupyterlite.
nbreproduce builds a container to run an .ipynb with: https://github.com/econ-ark/nbreproduce
container2wasm wraps vscode-container-wasm: https://github.com/ktock/vscode-container-wasm
container2wasm: https://github.com/ktock/container2wasm
https://www.reddit.com/r/Python/comments/1huxrs6/python_runn...
Wondering why they don't separate concerns here.