So many people here explaining why Python works that way, but what's the reason for numpy to introduce its own boolean? Is the Python boolean somehow insufficient?

Data typing is important. If two types do not have the same in-memory representation but you treat them like they do, you're inviting a lot of potential bugs and security vulnerabilities to save a few characters.

ETA: The WONTFIX is absolutely the correct response here. This would allow devs to shoot themselves in the foot for no real gain, eliminating the benefit of things like mypy. Type safety is your friend and will keep you from making simple mistakes.

bool_ via Numpy is its own object, and it's fundamentally different from bool in Python (which is itself a subclass of int, whereas bool_ is not).

They are used similarly, but they're similar in the same way a fork and a spork can both be used to eat spaghetti.

I/O Issues are problems that come with the territory for scripting languages like python. Its why I prefer to use bash for scripting instead, because in bash, all I/O are strings. And if there are ever any conflicts, well that's what awk/sed/Perl are for.

Well yeah just because they kinda mean the same thing it doesn't mean that they are the same. I can wholly understand why they won't "fix" your inconvenience.

This explanation is pretty clear cut

What exactly is your use case for treating np.bool_ and bool as interchangeable? If np.bool_ isn't a subclass of bool according to Python itself, then allowing one to be used where the other is expected just seems like it would prevent mypy from noticing bugs that might arise from code that expects a bool but gets an np.bool_ (or vice versa), and can only handle one of those correctly.

mpy and numpy are opensource. You could always implement the fix you need yourself ?