Writing scripts that involve spatial data often gets messy fast, because of the number of formats, plethora of tools, and volume of data.

Jupyter and similar notebook environments help with some of these problems, but can tend to favor one language at a time, and require a GUI or other environment for execution rather than a single "script".

In this talk we introduce a new experimental console-based tool -- samaki -- which provides

• a simple text format for combining source code and tools from multiple languages

• a flow for iteratively generating files in many data formats that are interdependent

• a mechanism for adding bespoke visualization and other tooling during the coding lifecycle

And we look at examples of using this fast flow for doing things like pulling from OpenStreetMap, manipulating geoJSON, analyzing with DuckDB, leveraging PostGIS and using LLMs judiciously.

https://github.com/bduggan/raku-samaki

https://raku.land/zef:bduggan/App::samaki