Description
Problem
subplots() defaults to auto-squeezing the returned Axes array (returning a single array when one is requested, returning a 1D array when a single row or single column is requested), likely for practicality, but this makes dynamic layouts pretty annoying: if you write axs = fig.subplots(m, n) where m and n are somehow dynamically computed (based on some dataset characteristics) and then later plan to use axs[i, j], you basically have an IndexError waiting to happen unless you can be certain that m and n are never 1. Of course one can remember to always write subplots(..., squeeze=False), but that's a bit verbose.
Proposed Solution
My preferred solution would probably have been to make the default m and n not 1, but None, so that None means "1 in that direction, and squeeze that direction" whereas 1 just means 1 (without squeezing). This would have fixed most common cases, e.g. if you write subplots() you get a single axes, subplots(3) or subplots(nrows=3) or subplots(ncols=3) you get a 1D array, subplots(m, n) (where m and n are dynamically computed variables) you always get a 2D array. I think in practice the main back-incompatibility of this proposal that occurs in real life is subplots(1, 3) (single row, likely not so uncommon), which would typically have to be written subplots(None, 3) or subplots(ncols=3) or fig, (axs,) = subplots(3) (for the additional unpacking).
Assuming that this backcompat breakage is not acceptable (it likely is not), one alternative would be to change the signature of subplots() to also support taking a single 2-tuple as argument (rather than nrows and ncols separately, and make subplots((m, n)) never squeeze the input. (Likely we wouldn't bother supporting m or n being None, in that case.) Then it would be OK to retrain my muscle memory to just always add an extra pair of parentheses when calling subplots.