geospatial-nix VS grass

Interesting and useful work, keep it up.

However, I took a look at a few geospatial-nix packages:

- https://github.com/imincik/geospatial-nix/blob/master/pkgs/p...

- https://github.com/imincik/geospatial-nix/blob/master/pkgs/g...

But it seems like the packages are minimally tested.

Am I seeing this correctly?

For example, with postgis, I miss the 'make check';

"The above command will run through various checks and regression tests using the generated library against an actual PostgreSQL database."

https://postgis.net/docs/postgis_installation.html#idm738

https://grass.osgeo.org/

    GRASS GIS offers powerful raster, vector, and geospatial processing engines in a single integrated software suite. It includes tools for terrain and ecosystem modeling, hydrology, visualization of raster and vector data, management and analysis of geospatial data, and the processing of satellite and aerial imagery. It comes with a temporal framework for advanced time series processing and a Python API for rapid geospatial programming. GRASS GIS has been optimized for performance and large geospatial data analysis.

We haven't looked at integrating GRASS yet, as we're more interested in data display, not deep analysis. Just another example of a C/C++ library with front end bindings for Python. Numbers are crunched in C/C++, results returned to Python.

Anyone have good advice for where to learn how to use GRASS

Access: GRASS GIS