WASM-powered codespaces for Python notebooks on GitHub
Hi HN! Last year, we shared marimo [1], an open-source reactive notebook for Python with support for execution through WebAssembly [2]. We wanted to share something new: you can now run marimo and Jupyter notebooks directly from GitHub in a Wasm-powered, codespace-like environment. What makes this powerful is that we mount the GitHub repository's contents as a filesystem in the notebook, making it really easy to share notebooks with data. All you need to do is prepend 'marimo.app' to any Python notebook on GitHub. Some examples: - Jupyter Notebook:…
In plain words
Marimo is an open-source reactive Python notebook environment that runs directly in web browsers using WebAssembly. It allows users to view and execute both marimo and Jupyter notebooks from GitHub repositories without installation, with the repository's files accessible as a mounted filesystem. Users can access notebooks by prepending 'marimo.app' to any GitHub notebook URL, and Jupyter notebooks are automatically converted to marimo format. It is designed for Python developers and data scientists who want to share and run notebooks collaboratively online.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hi HN! Last year, we shared marimo [1], an open-source reactive notebook for Python with support for execution through WebAssembly [2]. We wanted to share something new: you can now run marimo and Jupyter notebooks directly from GitHub in a Wasm-powered, codespace-like environment. What makes this powerful is that we mount the GitHub repository's contents as a filesystem in the notebook, making it really easy to share notebooks with data. All you need to do is prepend 'marimo.app' to any Python notebook on GitHub. Some examples: - Jupyter Notebook: https://marimo.app/github.com/jakevdp/PythonDataScienceHandb... - marimo notebook: https://marimo.app/github.com/marimo-team/marimo/blob/07e8d1... Jupyter notebooks are automatically converted into marimo notebooks using basic static analysis and source code transformations. Our conversion logic assumes the notebook was meant to be run top-down, which is usually but not always true [3]. It can convert many notebooks, but there are still some edge cases. We implemented the filesystem mount using our own FUSE-like adapter that links the GitHub repository’s contents to the Python filesystem, leveraging Emscripten’s filesystem API. The file tree is loaded on startup to avoid waterfall requests when reading many directories deep, but loading the file contents is lazy. For example, when you write Python that looks like ```python with open("./data/cars.csv") as f: print(f.read()) # or import pandas as pd pd.read_csv("./data/cars.csv") ``` behind the scenes, you make a request [4] to https://raw.githubusercontent.com/<org>/<repo>/main/data/car.... Docs: https://docs.marimo.io/guides/publishing/playground/#open-no... [1] https://github.com/marimo-team/marimo [2] https://news.ycombinator.com/item?id=39552882 [3] https://blog.jetbrains.com/datalore/2020/12/17/we-downloaded... [4] We technically proxy it through the playground https://marimo.app to fix CORS issues and GitHub rate-limiting.
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