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Advantages of Python 3.6+ codebase:
- f-strings (on exceptions mostly, but yay!)
- insertion-ordered dict (in 3.6, it's an implementation detail, but who's gonna change that?)
- Supports
Pathlikeobjects which will help us get rid of some helpers. - Typings, which we are planning to start using. (with support for variable annotations)
- We will be supporting 3 versions (right now, it's 4)
- Per download stats, 3.8 has overtaken 3.5 and number is quite low.
Regarding 5, Numpy and most of the data-science tools follow NEP29, by which they are on course to drop Python3.6 next month. Conda has already dropped support for Python3.5.
And, with the release of python 3.9, there will be a new version every year (with 5 years of support). Do we need to support all actively supported Python versions?
/cc @iterative/engineering
pmrowla, efiop and MatthieuBizien
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