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  • Modify _encode_datetime_with_cftime for compatibility with cftime > 1.4.0 · 2 ✖

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774684442 https://github.com/pydata/xarray/pull/4871#issuecomment-774684442 https://api.github.com/repos/pydata/xarray/issues/4871 MDEyOklzc3VlQ29tbWVudDc3NDY4NDQ0Mg== spencerkclark 6628425 2021-02-07T14:36:50Z 2021-02-07T15:08:17Z MEMBER

Thanks @mathause -- indeed the timings are pretty similar.

Before: ``` In [1]: import xarray as xr

In [2]: times = xr.cftime_range("2000", periods=1000).values

In [3]: units = "days since 2000-01-01"

In [4]: calendar = "gregorian"

In [5]: %%timeit ...: xr.coding.times._encode_datetime_with_cftime(times, units, calendar)

15.5 ms ± 170 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) ```

After: ``` In [1]: import xarray as xr

In [2]: times = xr.cftime_range("2000", periods=1000).values

In [3]: units = "days since 2000-01-01"

In [4]: calendar = "gregorian"

In [5]: %%timeit ...: xr.coding.times._encode_datetime_with_cftime(times, units, calendar)

14.9 ms ± 160 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) ```

 
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   Modify _encode_datetime_with_cftime for compatibility with cftime > 1.4.0 802737682
774670187 https://github.com/pydata/xarray/pull/4871#issuecomment-774670187 https://api.github.com/repos/pydata/xarray/issues/4871 MDEyOklzc3VlQ29tbWVudDc3NDY3MDE4Nw== mathause 10194086 2021-02-07T12:57:53Z 2021-02-07T12:57:53Z MEMBER

LGTM - did you check if that makes it slower? (Probably not as vectorize is also a for loop under to hood).

I think the failures are #4873 and #4865

 
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   Modify _encode_datetime_with_cftime for compatibility with cftime > 1.4.0 802737682

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