html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/3222#issuecomment-537747198,https://api.github.com/repos/pydata/xarray/issues/3222,537747198,MDEyOklzc3VlQ29tbWVudDUzNzc0NzE5OA==,1217238,2019-10-03T01:25:35Z,2019-10-03T01:25:35Z,MEMBER,"I think targeting 12 months of support for SciPy/pandas would be a
reasonable goal.

On Wed, Oct 2, 2019 at 2:48 PM Maximilian Roos <notifications@github.com>
wrote:

> Overall this is awesome, thanks @crusaderky
> <https://github.com/crusaderky>
>
> One minor question: do we need to support 24 months of pandas & scipy
> releases? These change their API faster than numpy, and I can't imagine
> there's a wide audience for people that a) need the very latest xarray and
> b) are using pandas released in 2017.
> I would vote to dramatically cut that, to something like the last two
> minor releases or 6 months. But could imagine two-three minor releases or
> 12 months being more palatable.
>
> —
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","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,481250429
https://github.com/pydata/xarray/issues/3222#issuecomment-537137922,https://api.github.com/repos/pydata/xarray/issues/3222,537137922,MDEyOklzc3VlQ29tbWVudDUzNzEzNzkyMg==,1217238,2019-10-01T17:18:08Z,2019-10-01T17:18:08Z,MEMBER,"Thanks for putting this together -- this looks good to me!

We can revise if any of they cause us trouble. In particular, pandas has the most stability issues, so it might be a little annoying to try to maintain two years of support.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,481250429
https://github.com/pydata/xarray/issues/3222#issuecomment-535152107,https://api.github.com/repos/pydata/xarray/issues/3222,535152107,MDEyOklzc3VlQ29tbWVudDUzNTE1MjEwNw==,1217238,2019-09-25T18:28:51Z,2019-09-25T18:28:51Z,MEMBER,"it would be nice to try to follow the guidelines in NEP-29: https://numpy.org/neps/nep-0029-deprecation_policy.html
","{""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,481250429
https://github.com/pydata/xarray/issues/3222#issuecomment-521771614,https://api.github.com/repos/pydata/xarray/issues/3222,521771614,MDEyOklzc3VlQ29tbWVudDUyMTc3MTYxNA==,1217238,2019-08-15T19:45:08Z,2019-08-15T19:45:08Z,MEMBER,"> Today I tried downgrading dask in the py37 environment to dask=1.1.2, which is 6 months old...

Yikes, we should fix this.

It has not been hard to ensure that older version of NumPy and pandas work. The key thing is CI tests that verify things as PR goes in. If work-arounds for old versions are hard, then we bump minimum required dependencies.

Probably the best place to start would be adding a CI build with pinned versions of the oldest required versions that works today, and then looking if there are simple fixes that will let us downgrade project like dask. It's not worth a huge effort, but it's not very user friendly for everything to broken with old versions of optional dependencies either.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,481250429