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starboard-notebook reviews and mentions
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JupyterLite is a JupyterLab distribution that runs in the browser
The format is only partially invented, it follows Jupytext [0], but adds support for cell metadata. There is no obvious way to get that in fenced codeblocks, especially with the ability to spread it over multiple lines so it plays well with version control.
One more consideration is that it's not "Markdown with code blocks interspersed", one might as well use plaintext or AsciiDoc.
Of course there are tradeoffs.. I wish I had more time to work on it.
[0]: https://github.com/gzuidhof/starboard-notebook/blob/master/d...
Yes. Last commit was 5 months ago [1]. Seems like a great idea though.
What I don't like it is that they invented yet another markdown syntax for code cells - it is the opening bracket # %[python] with no closing bracket.
There already is a popular markdown code cell syntax of [2]
```python
```
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A fast SQLite PWA notebook for CSV files
This is really wonderful! The discussion about lay people's knowledge of sql reminded me that the Pandas API is often useful for non-sql folk. Likewise there are some projects similar to dirtylittlesql to bring Python data manipulation to the browser.
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Turns Jupyter notebooks into standalone web applications and dashboards
You could consider an in browser notebook to get your cost down to near nothing - it depends a bit on what kind of tasks your students do whether they fit in the browser (one wouldn't train a large neural network in one for instance)
There's Starboard (which I'm building, it's built specifically for the browser and can integrate into a larger app deeply) and JupyterLite (the closest you will get to JupyterLab in the browser), either can be a good choice depending on your requirements. Both use Pyodide for the Python runtime.
[1]: https://github.com/gzuidhof/starboard-notebook, demo: https://starboard.gg
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Enabling COOP/COEP without touching the server
A few examples of web-applications that have this problem are in-browser video converters using ffmpeg.wasm, a web-based notebook that supports Python and multithreaded Emscripten applications.
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I want to learn D3. I don’t want to learn Observable. Is that ok? (2019-2021)
As someone building an in-browser notebook I have a lot of opinions on notebook environments. Notebooks serve different purposes, sometimes the notebook itself is the end-goal because the author is creating an interactive tutorial or explaining a complex concept with a bunch of visualizations. Observable is a fantastic tool for that, and the kind-of-Javascript reactive programming system it is built on is a great fit for that.
Outside of that use-case, I think notebooks are great for the first 20% of the effort that gets 80% of the work done. If it turns out one also needs to do the other 80% of the effort to get the last 20%, it is time to "graduate" away from a notebook. For instance if I am participating in a Kaggle machine learning competition I may train my first models in a Jupyter notebook for quick iteration on ideas, but when I settle onto a more rigid pipeline and infra, I will move to plain Python files that I can test and collaborate on.
This "graduation" from notebook to the "production/serious" environment should be straightforward, which means there shouldn't be too much magic in the notebook without me opting into it. Documentation in my eyes is not so different, I should be able to copy the examples easily into my JS project without knowing specifics of Observable and adapt it to my problem. Saying "don't be lazy and just learn Observable", or "you must learn D3 itself properly to be able to use it anyway" is not helpful. Observable being a closed, walled garden doesn't help: not being able to author notebooks without using their closed source editor is a liability that I can totally understand makes it a non-starter for some companies and individuals.
I think it's ok to plug my own project: It's called Starboard [1] and is truly open source [2]. It's built on different principles: it's hackable, extendable, embeddable, shareable, and easy to check into git (i.e. I try to take what makes the web so great and put that in a notebook environment). You write vanilla JS/ES/Python/HTML/CSS, but you can also import your own more advanced cell types. Here's an example which actually introduces an Observable cell type [3] which is built upon the Observable runtime (which is open source) and an unofficial compiler package [4]. I would be happy for the D3 examples to be expressed in these really-close-to-vanilla JS notebooks, but I can convince the maintainers to do so.
[1]: https://starboard.gg
[2]: https://github.com/gzuidhof/starboard-notebook
[3]: https://starboard.gg/gz/open-source-observablehq-nfwK2VA
[4]: https://github.com/asg017/unofficial-observablehq-compiler
- Show HN: A simple JavaScript notebook in one file
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Pyodide: Python for the Browser
If you want to play with Pyodide in a web notebook you can try Starboard [1][2].
A sibling comment introduces JupyterLite and Brython, which are Jupyer-but-in-the-browser, whereas with Starboard I'm trying to create what Jupyter would have been if it were designed for the browser first.
As it's all static and in-browser, you can embed a notebook (or multiple) in a blog post for instance to power interactive examples. The bundle size is a lot smaller than JupyerLite for the initial load - it's more geared towards fitting into existing websites than being a complete IDE like JupyerLab.
- Ask HN: What personal tools are you the most proud of making?
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A note from our sponsor - InfluxDB
www.influxdata.com | 17 Apr 2024
Stats
gzuidhof/starboard-notebook is an open source project licensed under Mozilla Public License 2.0 which is an OSI approved license.
The primary programming language of starboard-notebook is TypeScript.
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