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A lot of Data Science work in Python is based on Numpy. If you look at the GitHub repo, 30% of the code is C: https://github.com/numpy/numpy
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CodeRabbit
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If you want to look at machine learning, 60% of Tensorflow is in C++: https://github.com/tensorflow/tensorflow
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Numba plugs into LLVM JIT API, Tensorflow is written in C++, PyTorch core is C++, NumPy integrates BLAS libraries written in C and Fortran.
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Numba plugs into LLVM JIT API, Tensorflow is written in C++, PyTorch core is C++, NumPy integrates BLAS libraries written in C and Fortran.
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Numba plugs into LLVM JIT API, Tensorflow is written in C++, PyTorch core is C++, NumPy integrates BLAS libraries written in C and Fortran.
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So, the thing that's handling lower-level stuff is separate from the application server. So, you can pick a performant server, like Bjoern to host a WSGI application, like Django. Bjoern is 60% C. Just like Numpy and Tensorflow that I mentioned before.
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Nutrient
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For an end-to-end solution, in my experience FastAPI is more than quick enough for APIs that I am writing. If I need an actual website (rendered HTML) then I'd typically just grab Django because it's easy.
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