Now, other tests are failing

1. confidence interval computed with scipy.stats.bootstrap, test pass for scipy <= 1.9.3, but fails on newer versions of scipy >= 1.10.0. Probably the test is not reliable enough.
2. The distributed metric test fails, looks similar to Evaluate fails to acquire lock interrupting single-node multi-GPU training #540, several breakages due to recent datasets  #542. Test is passing with filelock <= 3.11.0.

I would appreciate any thoughts @lhoestq

Cool, thansk for updating :) Maybe we should also update setup.py to require python >= 3.8 as well. The scipy test can surely be fixed using numpy.testing.assert_almost_equal or something like that, if you want to fix it in this PR

I'm a bit less sure about the filelock issue, we can leave that for later.

Regarding scipy, adding tolerance would be not enough, because the current confidence interval in tests (0.3333, 0.6666), but after scipy update we have (0.3355, 1.0).
We can either update the test range and fix the scipy above 1.10.0 or just fix scipy under 1.9.3.

Ah yes indeed. We should align with the latest scipy

Ok, I fixed scipy version, the only failing test is for the distributed metrics.
Do you have any ideas on how to fix it without downgrading filelock or should we add a constraint to the version?
@lhoestq maybe you can tag anyone else who can help?