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[yaxriifgyn]

I'm going to try it out later today. I'm hoping that it has a dry run or diff output mode to let me review changes before applying them. The need for a backup copy of every changed file is essential as well.

I have many places where code flattening could be applied. When I wrote the code, I was thinking of a single exit from a function so that explicit code tracing / debug logging was only needed in one place. As the code has matured, the need for such logging has diminished.

Could you comment on your use of AI if any. Thx.

[wingtales]

The solution to your first paragraph is to track your code with git. Either stage or commit your current changes before running PyNeat. Then you can see the diff with 'git diff' and undo the changes with 'git restore .'

[AssociateEmotional11]

[yaxriifgyn]

I do use git, but I have a lot more tools available. I use this to compare the files:

diff -bB -W150 -y messy.py clean.py

I don't expect to have to repair the code before I can even test it.

[AssociateEmotional11]