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"I am specifically looking for Numpy-like libraries and designs"

Why would one bottleneck a design with polyglot stacks even before a single line of code was implemented? This sounds like naive nonsense.

"What did you mean by this? ... Python"

Python was never designed to handle threads or parallelism properly, and has performance issues Numpy tries to address though its wrapped C/C++ libraries.

Python became 30 years of spiral development, and implodes into a new implementation every so often. Depending on the use-case it may prove appropriate, but never optimal. =)



I was wondering about libraries that do Numpy-like things, not libraries implemented like Numpy.


There are many native packages and wrapper scaffold libraries like Numpy. It will depend on your problem domain, but Julia often transparently supports its broadcast operator on most core data-structure math ("using LinearAlgebra" and the like).

https://gist.github.com/AlexanderFabisch/6343090 (small feature comparison list, but ignore the incorrect opinions)

https://sciml.ai/

https://fluxml.ai/Flux.jl/stable/gpu/

https://alan-turing-institute.github.io/MLJ.jl/dev/about_mlj...




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