Josh Rosenberg <shadowranger+pyt...@gmail.com> added the comment:
This has nothing to do with properties, it's 100% about using augmented assignment with numpy arrays and mixed types. An equivalent reproducer is: a = np.array([1,2,3]) # Implicitly of dtype np.int64 a += 0.5 # Throws the same error, no properties involved The problem is that += is intended to operate in-place on mutable types, numpy arrays *are* mutable types (unlike normal integers in Python), you're trying to compute a result that can't be stored in a numpy array of integers, and numpy isn't willing to silently make augmented assignment with incompatible types make a new copy with a different dtype (they *could* do this, but it would lead to surprising behavior, like += on the *same* numpy array either operating in place or creating a new array with a different dtype and replacing the original based on the type on the right-hand side). The short form is: If your numpy computation is intended to produce a new array with a different data type, you can't use augmented assignment. And this isn't a bug in CPython in any event; it's purely about the choices (reasonable ones IMO) numpy made implementing their __iadd__ overload. ---------- nosy: +josh.r resolution: -> not a bug stage: -> resolved status: open -> closed _______________________________________ Python tracker <rep...@bugs.python.org> <https://bugs.python.org/issue45333> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
