Perhaps paradoxically it is easier to maintain a gigantic Python code base than it is to maintain one that is small or medium sized.

The reasoning, a gigantic code base means infrastructure and tooling investment will obviously pay off. It probably even means you get one or more dedicated resources of this sort. Whereas a small to medium sized codebase might bump into some of the same issues as a larger code base but not justify such investments.