jmalkin commented on issue #20:
URL: 
https://github.com/apache/datasketches-python/issues/20#issuecomment-1865127100

   I completed the conversion, but density showed a significant performance 
regression. Investigating, it seems like the culprit was too many vector 
conversions in ways that pybind11 can avoid through the use of thinly-wrapped 
numpy arrays -- something Nanobind doesn't do (in favor of a more 
source-agnostic model).
   
   To address that I'm just wrapping the std::vector.data() in a numpy object 
whenever we need to call the kernel. It limits us to numpy kernels (which was 
the case before) but with that change I slightly beat pybind11 times.
   
   Vector of KLL sees a slight performance regression. I have not found a 
solution there.


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