Well, I guess one moral of the story is that doing image manipulation is easier in Python than Fortran, so it's again using the right tool for the job. And I think the push for Physicists to use Python if possible is good, as the learning curve is less steep. And once you have that tool at your disposal, you might use it more often (instead of Excel).

I can see many projects being improved by providing a Python pre-processor that writes out e.g. a binary config file, the hard-code Fortran/C simulation code reads that, and spits out the simulation results, and then having a Python post-processor that does the pretty stuff at the end.

Academically, it seems that pairing CS undergrads with Physics undergrads to do e.g. a molecular dynamics (MD) course would be cool. The Physics behind MD isn't too hard, and given the right parameters the programming part would be manageable. Then again, CS undergrads aren't necessarily great programmers either...

Clean code and tests are overrated. Version control and a big eco-system is underrated. It's like maths, physicists don't understand maths, they just use it like a carpenter uses a nail without understanding metallurgy, or a programmer uses a CPU without understanding solid-state physics. And that's okay.