ddanieltan

Inspired by @simonw, I also started building, small lightweight tools

I was initially attracted by the idea that I could replace the traditional HTML, CSS, Javascript , Python (backend) project entirely in Python, but it's starting to feel like the original mix of languages might have been the simplest option all along, particularly with GenAI tools

just kidding, this is pretty cool.

And yes... I try to separate the art from the artist too when it comes to OSC.

    MaxRowsError: The number of rows in your dataset is greater than the maximum allowed (5000).

Overall, it's my preferred Python viz library although I do wish there was a better way for the Python library to better use introspection. After all, rather than

   alt.Chart(df).mark_line.encode(x="abc:Q")

That said, I'm already used to the extra syntax so still feel confident in using this library daily.

[1] https://vegafusion.io/index.html

I feel uv should provide a way to install different python versions to truly cover an end-to-end tool. The current approach of searching for existing virtualenvs of conda envs helps but I was hoping to completely remove the need for another package/dependency manager.

(Taken from the docs)

  If a --python-version is provided to pip compile (e.g., --python-version=3.7), uv will search for a Python interpreter matching that version in the following order:

  - An activated virtual environment based on the VIRTUAL_ENV environment variable.

  - An activated Conda environment based on the CONDA_PREFIX environment variable.

  - A virtual environment at .venv in the current directory, or in the nearest parent directory.

  - The Python interpreter available as, e.g., python3.7 on macOS and Linux. On Windows, uv will use the same mechanism as py --list-paths to discover all available Python interpreters, and will select the first interpreter matching the requested version.

  - The Python interpreter available as python3 on macOS and Linux, or python.exe on Windows.

1. Is the flexibility of languages used in data loaders/backend going to eventually come to the front end/ui? Or will the paradigm always be bring-your-own-language for the data loading but build your dashboard with observablejs/observable plot?

2. Considering ObservableJS is supported by Quarto, can we look forward to Observable Framework integrated with Quarto too? Or is the fact that the latest Quarto version also featured Dashboards more of a competitor to Framework?

3. Saw some comparison to Evidence.dev in the comments. I saw some shades of similarity with the markdown focused dev experience too but I recall Evidence chose Apache Echarts for their main charting library. Any thoughts of the pros/cons of Echarts vs ObservableJS/Plot?