issue_comments: 536772940

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https://github.com/pydata/xarray/issues/3222#issuecomment-536772940 https://api.github.com/repos/pydata/xarray/issues/3222 536772940 MDEyOklzc3VlQ29tbWVudDUzNjc3Mjk0MA== 6213168 2019-09-30T22:08:27Z 2019-09-30T22:08:27Z MEMBER

Revised proposal (in parenthesis: minimum version if this policy were to be applied right now):

  • Python: NEP-29; 42 months (>=3.6)
  • numpy: NEP-29; 24 months (>=1.14)
  • pandas: 24 months (>=0.20)
  • scipy: 24 months (>=0.19)
  • NEP18 packages (sparse, pint, etc.): very latest available only, at least until the technology has reasonably matured across the whole ecosystem. This extends to dask when used in conjunction with any of these packages. numpy >=1.17. A very recent version of pandas may also be required if necessary.
  • all other packages: 6 months or the latest available in the anaconda (not conda-forge) repository if it exists, whatever is older.

Note: patch versions are not pinned. This means that the minimum python version that is guaranteed to work is actually 3.6.7 or 3.6.9, not 3.6.0.

What are people's thoughts?

It may also be a cool idea to write a script that parses the requirements yml files and generates .rst documentation out of them.

 
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