OTOH, consider that in the "pick the majority from 3 CPUs" approach that seems to have been used in earlier missions (as mentioned in the article) would fail the same way if two CPUs compute the same erroneous result.

I was confused at first how that could work, but then I realized that of course, with _unsigned_ integers this works fine because you cannot add a negative number...

Maybe some kind of auto-formatter?

On the other hand I often see functions like you describe - something has to be executed step-by-step (and the functionality is only used there) - where I _whish_ it was split up into separate functions, so we could have meaningful tests for each step, not only for the "whole thing".

Maybe I am just a bit burned by this particular example I ran into (where this pattern should IMO not have been used).

  class Foo:
      def __init__(self, bar):
          self.bar = bar
  
  class Bar:
      def __init__(self, foo):
          self.foo = foo

So my suggestion: Try not to have interdependent classes :D

On the other hand, I tend to take it as a hint that I should look at my module structure, and see if I can avoid the cyclic import (even if before adding type hints there was no error, there still already was a "semantic dependency"...)

I think _technically_ there is no difference - it does not matter if the worst-case-behavior is triggered by an "adversary" or by chance.

It _does_ give a different mental model though.

(Also almost swallowed my tongue saying that out loud)

Also, dataclasses feels more straightforward and less "magic" to me (in the sense that it is more or less "just" a way to avoid boilerplate for class definition, while pydantic does way more "magic" stuff like de-/serialization and validation, and adding numerous methods and attributes to the classes).

Just trace back the dict to it's origin, through all the places it can be modified, and you know what is (or could be) inside...

/s

I think the first one should be very much doable, but I am not sure how I would build the "almost complete" and the "similar colors" features.