The hardship of porting from 2 to 3 very much depends on how critical the software is. Porting 1000 lines of python 2 that deals with files encoded in various ways where it’s impossible to test all edge cases and where a failure might lead to huge liability charges is hard not because it’s hard to run 2to3 and do some random tests, but because you don’t know what you have missed. And still, a 300k lines of code project might be fine to just run 2to3 on and then find the bugs as you go. It’s a matter of context.

The problem was that you could only port once all the libraries you use had ported, but libraries didn't want to commit to abandoning Python 2 quickly.

I have a pretty nasty example here:

https://news.ycombinator.com/item?id=25890126

How do I regression test five different pieces of DAQ hardware? My best plan is to pull them working systems and deal with them missing. I don’t think it’s a good use of resources to buy extra DAQ cards just for a regression test bed.

Regardless of that, moving from python 2.5 to 2.7 is not trivial because not all used libraries were even updated to 2.7 from 2.5. Some that were broke backwards compatibility. How far do I have to bend backward just to get in the right place to update to python 3? I see many comments trivializing the effort needed to update to python 3 because they know of narrow use cases and expect large amounts of resources to maintain code. That isn’t the reality for most users.