Sep VS Fiona

Pretty sure the C performance would have been trivially matched by C# were it to be ported there.

While not XML (which does not see much love from the community to surprise of HN), gigabytes per second of parsing throughput are reached for CSV without sacrificing UX: https://github.com/nietras/Sep?tab=readme-ov-file#packageass...

If you ever need to parse CSV really fast and happen to know C#, there is an incredible vectorized parser for that: https://github.com/nietras/Sep/

Your issue is that you're using the default (old) binding to GDAL, based on Fiona [0].

You need to use pyogrio [1], its vectorized counterpart, instead. Make sure you use `engine="pyogrio"` when calling `to_file` [2]. Fiona does a loop in Python, while pyogrio is exclusively compiled. So pyogrio is usually about 10-15x faster than fiona. Soon, in pyogrio version 0.8, it will be another ~2-4x faster than pyogrio is now [3].

[0]: https://github.com/Toblerity/Fiona

[1]: https://github.com/geopandas/pyogrio

[2]: https://geopandas.org/en/stable/docs/reference/api/geopandas...

[3]: https://github.com/geopandas/pyogrio/pull/346

As has been said the definition of a GIS dev is far from written in stone, but to chime in from a personal standpoint: most of what I do is data wrangling/analysis with shapely/geopandas for vectors (or pygeos / fiona for performance when data volumes get large, but seeing as Shapely 2.0 just got released one can likely skip this part) + rasterio for rasters as well as parallelising these tasks for performance if needed (ray is great for that) and then performing machine learning learning against the data (mostly with sklearn and torch).

TypeError 10 refers to (https://github.com/Toblerity/Fiona/blob/master/fiona/_geometry.pyx):