Install GDAL via a Python wheel

[brianhelba]

No description provided.

[brianhelba]

https://github.com/girder/large_image_wheels#geodjango

[brianhelba]

I think this is an improvement, as I'd like to get towards a place where system libraries aren't required, as this makes deployment much easier and more portable. It also aligns with 12 Factor: Dependencies, as we want all of our application dependencies to be defined within our Python lockfile, rather than implicitly depending on system versions that we may not always have full control over.

I need help testing this and need help understanding exactly where GDAL is being required from (so we can make sure that the installed wheel satisfies the usage).

[BryonLewis]

I need help testing this and need help understanding exactly where GDAL is being required from (so we can make sure that the installed wheel satisfies the usage).

So we used to have a tile server for the spectrograms until we converted to using side-by-side JPEGS.

The other case is in the creation of the GRTS Cell Ids. This is a 10x10km grid across the North America that is used by USGS with their NABat project to identify locations of bats. They originally provided this to us as a large CSV with a tons of rows to be ingested. It's quicker to utilize the shapefiles and process them for ingestion (like 2 minutes vs the 15-20 for the CSV they gave us)
./core/managment/commands/loadGRTS.py or docker compose run --rm django ./manage.py loadGRTS

[BryonLewis]

I wiped my local DB and tested this specifically with a new DB and the loadGRTS management command to use geopandas to process the shapefiles. Everything worked properly.
Additionally, tested the spectrogram creation (even though this should no longer have any dependency on GDAL) and that worked properly as well.

Thanks for the links to Notion and Large Image for background information.