The open source stuff is mostly really fidgety and works correctly with a rather narrow set of inputs. To make most libraries be actually easily usable for a wide range of inputs is a tremendous amount of work.

The core of them mostly do the thing they claim to do, but if you feed them data that's just slightly off, then it'll break in interesting ways.

Speaking based on a lot of experience[1]. Nothing in the geospatial or environmental data world is easy and there will always be an unexpected problem lurking right behind the corner, regardless of how many of them you've already fixed or worked around.

Still, the complexity of the problem space also makes it fascinating. As an example, the definition and measurement of something that's seemingly very simple: mean seal level is actually tremendously complicated if you think about it. The Wikipedia article talks about averaging over decades of measurements to get it right for example.

[1] I'm a part of the team behind https://data.planetos.com/datasets