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  • keewis · 4 ✖

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  • Consider revising our minimum dependency version policy · 4 ✖

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778693569 https://github.com/pydata/xarray/issues/4179#issuecomment-778693569 https://api.github.com/repos/pydata/xarray/issues/4179 MDEyOklzc3VlQ29tbWVudDc3ODY5MzU2OQ== keewis 14808389 2021-02-13T23:33:52Z 2021-02-13T23:33:52Z MEMBER

ah, I seem to have missed that. Now that python has a yearly release cycle, I would extend the support window for a few months, though: with 24 months we could drop 3.8 as soon as 3.10 comes out (not sure if that's an issue in practice: projects like numba seem to take 4-5 months until they release a compatible version).

 
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   Consider revising our minimum dependency version policy 645154872
778681901 https://github.com/pydata/xarray/issues/4179#issuecomment-778681901 https://api.github.com/repos/pydata/xarray/issues/4179 MDEyOklzc3VlQ29tbWVudDc3ODY4MTkwMQ== keewis 14808389 2021-02-13T21:39:41Z 2021-02-13T21:42:56Z MEMBER

I wonder if finding a policy for all libraries is possible at all, and if maybe we should have a separate policy for python and numpy, which have a regular release cycle (every N months)?

That would mean: exactly 42 months support for python (together with packaging tools like pip and setuptools, should we depend on that) and exactly 18 months for numpy (as in "N months after the initial release we will stop supporting it"), but at least 12 or 6 months support for libraries like pandas, dask, scipy, and zarr which don't have frequent or regular releases ("the most recent minor version N months ago")

 
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   Consider revising our minimum dependency version policy 645154872
778631437 https://github.com/pydata/xarray/issues/4179#issuecomment-778631437 https://api.github.com/repos/pydata/xarray/issues/4179 MDEyOklzc3VlQ29tbWVudDc3ODYzMTQzNw== keewis 14808389 2021-02-13T15:05:46Z 2021-02-13T20:02:19Z MEMBER

actually, this version of the policy won't work: if we require the most recent python version from 42 months ago (Aug 2017) we get python 3.6, which we can't maintain because most of our dependencies won't support it anymore by the time we would be allowed to drop it. So I think we will have to find a way to work around that, either by changing the support window of python or follow NEP29 and require at least M supported versions, or something completely different.

One edge case of the rules above would be if a package has no release for more than N months and then multiple releases over the course of a few weeks.

 
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   Consider revising our minimum dependency version policy 645154872
774323783 https://github.com/pydata/xarray/issues/4179#issuecomment-774323783 https://api.github.com/repos/pydata/xarray/issues/4179 MDEyOklzc3VlQ29tbWVudDc3NDMyMzc4Mw== keewis 14808389 2021-02-05T22:31:43Z 2021-02-05T22:31:43Z MEMBER

I think we talked about this in a meeting a few weeks ago, but I'm not sure I remember correctly: was the only issue that nobody picked this up? From the comments above it seems we all agree on changing the policy to "support the latest minor version (X.Y) available N months ago" – officially

the most recent minor version (X.Y) initially published more than N months ago

 
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   Consider revising our minimum dependency version policy 645154872

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