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xarray 0.11 release #2505

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shoyer opened this issue Oct 24, 2018 · 21 comments
Closed
5 tasks done

xarray 0.11 release #2505

shoyer opened this issue Oct 24, 2018 · 21 comments

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@shoyer
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shoyer commented Oct 24, 2018

We should really get a release candidate out soon for xarray 0.11, which will fix a lot of IO issues with dask (e.g., #2503).

Deprecation cycles to finish first:

Deprecation cycles to start (optional)

These were everything tagged with the "0.11" milestone.

@pydata/xarray anything else to add?

@dcherian
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dcherian commented Oct 24, 2018

These PRs seem to be almost done (it'd be nice to get some of these in):
#2470 (fill_value in shift)
#2449 (to_iris, from_iris)
#2207 (something about chunksizes)
#2415 (test for 1D object indexing)
#2413 (positional arguments for groupby apply)

@rabernat
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rabernat commented Oct 24, 2018

Would be nice to get #2487 finished before release. (zarr chunking bug)

@max-sixty
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I'll do Iterating over a Dataset iterates only over its data_vars

@dcherian
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Oooh we're supposed to remove .T as an alias for .transpose() #1232. finally!

@jhamman
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jhamman commented Oct 25, 2018

Would it make sense to add a deprecation warning for Python2 users in this release (xref #1876). Chances are, 0.12 will come after Jan-2019 when we're slated to drop Python2 support.

@shoyer
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shoyer commented Oct 25, 2018

Would it make sense to add a deprecation warning for Python2 users in this release (xref #1876). Chances are, 0.12 will come after Jan-2019 when we're slated to drop Python2 support.

I agree, this will probably be the last major xarray release with Python 2 support. But I don't think there's much to be gained by adding a warning -- Python 2 users know the end is near.

@jhamman
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jhamman commented Oct 25, 2018

Python 2 users know the end is near.

Based on recent experience, I'm not quite as confident here 😄

@fmaussion
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Did any other library have a warning for this? I think that if we follow the lead of ipython, matplotlib and https://python3statement.org/ then all we have to do is make 0.12 non-installable on py2, and py2 users will stick to 0.11 ad vitam æternam.

It would be quite mean to have them listen to a warning all the time they import xarray on top of that 😄

ipython docs have a big warning banner though

@shoyer
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shoyer commented Oct 25, 2018

@spencerkclark and other climate scientists: should we switch the default behavior to use cftime for non-standard calendars in 0.11? (see #2437)

@spencerkclark
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should we switch the default behavior to use cftime for non-standard calendars in 0.11?

I would be +1 on this; as evidenced by #2437 it has become increasingly confusing/error-prone to use non-standard/out-of-range dates without CFTimeIndex enabled. That said, since not everything is enabled yet (namely resample and plotting), I'd be sympathetic to those who would rather wait a bit longer.

@shoyer
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shoyer commented Oct 26, 2018

@spencerkclark I also think this is probably a good idea. If you have time, it would be great if you could put together a PR to switch the behavior.

@spencerkclark
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@shoyer sure thing, barring feedback from others, I'll try and put a PR together tomorrow.

@shoyer
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shoyer commented Oct 30, 2018

Another deprecation cycle to finish would be the old resample() syntax.

@dcherian
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dcherian commented Oct 30, 2018

(commented on wrong issue)

@shoyer
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shoyer commented Nov 3, 2018

Another deprecation cycle to finish would be the old resample() syntax.

I got started on this one...

@jhamman
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jhamman commented Nov 7, 2018

I'm observing that our checklist seems to be complete. Are we blocked on any outstanding issues?

@shoyer
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shoyer commented Nov 7, 2018 via email

@shoyer
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shoyer commented Nov 7, 2018

I just tagged the release and uploaded it to pypi. RTD and conda forge should follow soon automatically.

@jhamman
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jhamman commented Nov 7, 2018

Thanks @shoyer!

@jhamman jhamman closed this as completed Nov 7, 2018
@jhamman
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jhamman commented Nov 7, 2018

Related and something I could use feedback from @pydata/xarray on: should we drop optional deps from the conda-forge build: conda-forge/xarray-feedstock#37

@shoyer
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shoyer commented Nov 7, 2018

Generally I always favor the most granular dependency specifications, but this seems like something conda-forge could decide as a matter of policy. If they don't want to rule on a general policy, then yes let's drop optional conda deps to match pypi.

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