Julia heavily makes use of multiple dispatch among with other convenient type related features much more complex than Python, to a point where they are often abused and sometimes have uncaught edge cases. It makes the language very powerful but has its downsides.

And to be fair to Python, static analysis has come a very long way and the CPython interpreter makes far fewer complex assumptions than the Julia compiler. It’s also fairly strongly typed as well, so I’ve found that challenges with the type system cause more issues with packaging and maintenance than it does correctness.

Indeed Python is relatively simple language. It also adheres to the principle of least astonishment and dynamic types are used towards this goal. Finally it does not mind making large changes to the language.

With Python most of the time when you have an unexpected result with the language or a library it is often a matter of realizing "OK that's the way it works", and moving on with your work. The language and libraries strive so much to always return sensible results that they are fewer instances when you would call a behavior a bug.