Slim down dependencies

I was chatting with @jorisvandenbossche at the dask developer meeting last week and he mentioned that gdal is only required for fiona which handles the IO parts of geopandas.

Since gdal is known to be a pain to install, it’d be nice if geopandas were split into two conda packages geopandas-core and geopandas. geopandas-core would include all the dependencies except fiona, and geopandas would include fiona, geopandas-core and all the current dependencies.

For pip installs there could be more subsets of dependencies, but the full install would be pip install geoviews[complete].

This pattern had been established in dask and other projects (such as geoviews).

[knaaptime]

I guess this is why i’m confused… If you have conda at your disposal, then installing gdal is trivial, no? The trouble comes from installing fiona from pip and handling gdal manually.

so if the root of the problem is that gdal/fiona are difficult to install with pip, why is it useful to create another conda package without gdal?

[jorisvandenbossche]

so if the root of the problem is that gdal/fiona are difficult to install with pip, why is it useful to create another conda package without gdal?

To still answer this (very lately), I see two main reasons: 1) even with conda, installing gdal/fiona is still the package that can give problems from time to time (given the many c dependencies, it most easily gives channel conflicts, or some temporary error if one of the packages gets updated, or …), 2) more importantly, it gives a large install size, and if you don’t need gdal/fiona, the geopandas-base package gives you the option to get a lighter env (which can be useful in cases where size matters, eg in containers, AWS lambda, …)