Some notes from the EuroSciPy maintainer track about Numpy 2.0

You can track the progress Numpy is making towards 2.0 and what changes are coming in numpy/numpy#24300.

Some things we should consider doing:

• pin to numpy<2 in the next releases to reduce the number of people who will install a version of scikit-learn that is incompatible with the numpy 2 version
• add some code in scikit-learn that detects that numpy 2 is installed and output a good error message for users
  • Olivier: do we really need this? Maybe the upper-bound pinning is enough.
• numpy 2 might come out at the end of 2023 or early 2024
• modify existing conda-forge packages to include a numpy<2 constraint
  • unclear if we can do this on PyPi as well
  • How to deal with upcoming Numpy 2.0 release and existing scikit-learn releases conda-forge/scikit-learn-feedstock#227
• once numpy 2.0 has been released we should build against that instead of "oldest-supported-numpy"
  • already do this now in the nightlies?
  • make sure that this works while still having 1.x.quite-old as the minimum required numpy
  • We no longer build against oldest-supported-numpy for Python 3.9 thanks to BLD: Build scikit-learn nightlies using NumPy nightlies #27735 that was merged in main before the release of scikit-learn 1.4.

cc @ogrisel