jupyterlite
starboard-notebook
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jupyterlite | starboard-notebook | |
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19 | 10 | |
3,551 | 1,163 | |
1.8% | - | |
8.9 | 3.8 | |
10 days ago | 20 days ago | |
TypeScript | TypeScript | |
BSD 3-clause "New" or "Revised" License | Mozilla Public License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
jupyterlite
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SymPy: Symbolic Mathematics in Python
The JupyterLite Python-compiled-to-WASM build has NumPy, SciPy, matplotlib, and SymPy installed; so you can do computer algebra with SymPy in a browser tab.
https://github.com/jupyterlite/jupyterlite/tree/main/py/jupy... :
> Initial support for interactive visualization libraries such as: altair, bqplot, ipywidgets, matplotlib, and plotly
- Vscode.dev: Local Development with Cloud Tools
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Show HN: Ipython-GPT, a Jupyter/IPython Interface to Chat GPT
https://jupyterlite.readthedocs.io/en/latest/howto/extension... :
> We recommend checking out how to create a server extension first
From https://github.com/jupyterlite/jupyterlite/issues/237#issuec... re: 'micropip':
%pip install $@
- Show HN: Classic FPS Wolfenstein 3D brought in the browser via Emscripten
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Jupyterlab Desktop
Agreed that would be a killer feature. Unzip this package and get a functional Python + Jupyter + scientific (numpy, pandas, scipy, matplotlib) environment.
I have been on-and-off teaching some people Python and the initial setup on-ramp is horrible. Ok, so install Python, now ignore-this-for-now-complications: create a "virtualenv", use this thing called "pip", install these half-dozen things to get a basic notebook (Jupyter + scipy things), install these other half-dozen quality of life things, you should probably also have "conda" for the future, etc. That's a lot of nonsense for someone I am trying to show an alternative to Excel.
My shortcut, "You want to try Python?" approach has been to start with JupyterLite[0] where I can immediately get people coding and delay that pain.
- Show HN: A 100% free and interactive Python course for coding beginners
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Hacker News top posts: Nov 29, 2022
JupyterLite: a JupyterLab distribution that runs in the browser\ (45 comments)
- JupyterLite is a JupyterLab distribution that runs in the browser
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LibreOffice running natively in a browser via WebAssembly
Jupyter runs natively in the browser now with JupyterLite: https://github.com/jupyterlite/jupyterlite It can use a native browser JS kernel, or some languages that have been converted to run in the browser with WASM (including a full python environment called pyodide).
VS Code also runs natively in the browser now: https://code.visualstudio.com/blogs/2021/10/20/vscode-dev This uses a Chrome only (for now) filesystem access API to give the browser access to your native files--you can edit them entirely in the browser with nothing happening on a server.
- Turns Jupyter notebooks into standalone web applications and dashboards
starboard-notebook
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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?
What are some alternatives?
pyodide - Pyodide is a Python distribution for the browser and Node.js based on WebAssembly
panel - Panel: The powerful data exploration & web app framework for Python
xeus-cling - Jupyter kernel for the C++ programming language
TiddlyWiki - A self-contained JavaScript wiki for the browser, Node.js, AWS Lambda etc.
brython - Brython (Browser Python) is an implementation of Python 3 running in the browser
streamlit - Streamlit — A faster way to build and share data apps.
unofficial-observablehq-compiler - An unofficial compiler for Observable notebook syntax
Transcrypt - Python 3.9 to JavaScript compiler - Lean, fast, open! -
userscript-github-repository-categories - Categorize GitHub repositories by matching repository names with regular expressions
hal9ai - Hal9 — Data apps powered by code and LLMs [Moved to: https://github.com/hal9ai/hal9]
dev - Development repository for the CodeMirror editor project