`pip install numpy` does not install the most optimal build for a given platform, or e.g. MKL or BLAS -linked packages. `pip install numpy-mkl` is not the offi

`pip install numpy` does not install the most optimal build for a given platform, or e.g. MKL or BLAS -linked packages. `pip install numpy-mkl` is not the official way as those binary wheels are built by a third-party. From https://news.ycombinator.com/item?id=37808036 https://news.ycombinator.com/item?id=37808036 : > conda-forge maintainer docs > Switching BLAS implementation: https://conda-forge.org/docs/maintainer/knowledge_base.html#switching-blas-implementation https://conda-forge.org/docs/maintainer/knowledge_base.html#... rattler-build supports CPU levels and CUDA levels. Thus conda-forge packages may be more performant on modern CPUs and GPUs than the average PyPI package: https://news.ycombinator.com/item?id=41306658 https://news.ycombinator.com/item?id=41306658