Description
Originally posted at #644 (comment), but updated slightly
Just bringing up the topic of whether we should follow NEP 29 — Recommend Python and Numpy version support as a community policy standard as noted before in #340 (comment). This would mean dropping support for Python 3.6.
In practice, we'll need to follow in the footsteps of our dependent packages:
- pandas 1.2 dropped Python 3.6 at Drop Python 3.6 support pandas-dev/pandas#35214
- xarray is less aggressive, they're thinking about it at Consider revising our minimum dependency version policy pydata/xarray#4179
Some options we can take are:
- Agressive option - Let PyGMT v0.2.x be the last version series to support Python 3.6, and state that PyGMT v0.3.0 requires Python 3.7 or newer.
- Less aggressive option - Still support Python 3.6 for PyGMT v0.3.0 (but maybe drop it from our test suite entirely to save on CI resources).
Does it mean that users cannot install pygmt via
pip install pygmt
orconda install pygmt
if they're still using Python 3.6? Or they can still install it, but there is no guarantee that all PyGMT functionalities work well with Python 3.6?
It will be quite hard to support four minor versions of Python (3.6, 3.7, 3.8, 3.9), especially for the conda
packages where there is a separate build for each one (unless we can work out how to get a 'noarch' build). We could still allow pip install pygmt
Python 3.6 (with no support guarantees, i.e. no CI checks), but it will become a maintenance burden when our dependency packages (numpy, pandas, xarray) move on.
There's no rush to do all this, since Python 3.9 is just released, and there are some libraries still to catch up. Even matplotlib (who has more maintainers) is dropping Python 3.6 for their v3.4 (see matplotlib/matplotlib#17662) so it's worth thinking about following NEP 29 for PyGMT v0.3.0.
Originally posted by @weiji14 in #644 (comment)
Are you willing to help implement and maintain this feature? Yes