Learning about SedonaDB, GGSQL, and a little UV

Testing out two of the latest additions to the data science space

Getting Started

You should be able to clone this repository or download the zip file and run the example script to get started in Marimo with the right packages.

1. Install uv.
2. Once you are in the folder in Terminal with uv installed run the command uv run marimo edit explore.py.
3. You should see a list of Python packages being installed then your browser should pop open with a marimo script running.

Some notes on how we set up the repository

UV to start

uv continues to be my favorite way to control python and create common experiences for learners and developers. Plus it is screaming fast. This repository is built to leverage a virtual Python environment using uv.

Commands to get it set up

These have already been done in this repo.

1. Created the repo on Github and then clones
2. uv init . in the base folder
3. Then add package = false under [tool.uv] in the pyproject.toml as this will not be a package.
4. No run the following two uv commands in terminal

uv add \
"apache-sedona[db]>=1.9.0" \
"marimo[edit,recommended]>=0.23.5" \
"nbformat>=5.10.4" \
"python-lsp-server>=1.14.0" \
"ruff>=0.15.12" \
"sedona>=1.0.4" \
"vl-convert-python>=1.9.0.post1"

uv add --group dev "jupyter>=1.1.1" "pyyaml>=6.0.3"

Marimo for scripting

marimo is a next generation Python notebook that has my interest lately. Once you have this repo cloned you can start marimo with the terminal command uv run marimo edit explore.py

SedonaDB with Polars for data wrangling

• SQL - Apache Sedona
• GeoArrow has spatial parquet data that we can use.