I do not know why numpy would be built again (maybe scipy has other version requirements?), but I can report on a way how to install scipy and scikit-learn.

# later in the process it installs using setuptools Here apparently we had no wheel available, so we have to build it ourselves with setuptools running setup.py. Here we are downloading a pre-built wheel that has very few limitations: it works for any version of python 3, for any os, for any architecture (like amd64 or arm64): click-8.0.3-p圓-none-any.whl Collecting click>=7.0

Building the wheel ourselves takes more cpu time, and is generally less reliable but works in this case. This happens because the authors don't publish a prebuilt wheel to Pipy, but more and more people are adding this to their CI (github actions) workflow. Or, if no prebuilt wheel exists (sad) then we download a tar.gz and build it ourselves. Note on Pipy: we usually download either a pre-built wheel (yay, this is excellent for reliable distribution and ensuring compatability). Successfully installed scikit-learn-1.0.1 scipy-1.7.3 Installing collected packages: scipy, scikit-learn Building wheels for collected packages: scikit-learnīuilding wheel for scikit-learn (pyproject.toml). Pip downloaded the source from Pipy, then built the wheel targeting MacOS X 12.0, and arm64 (apple silicon): scikit_learn-1.0.1-cp38-cp38-macosx_12_0_arm64.whl. Worked great on Apple Silicon M1 🎉 Extra details about how Pip works Just first brew install openblas - it has instructions for different processors ( wikipedia) brew install openblasĮxport OPENBLAS=$(/opt/homebrew/bin/brew -prefix openblas)Įxport CFLAGS='-falign-functions=8 $'

Conda install sklearn