["python","numpy","types"]
How to determine if a number is any type of int (core or numpy, signed or not)?

I need to test whether a variable is of type int, or any of np.int*, np.uint*, preferably using a single condition (i.e. no or). After some tests, I guess that: isinstance(n, int) will only match int and np.int32 (or np.int64 depending on plateform), np.issubdtype(type(n), int) seems to match all int and np.int*, but doesn’t match np.uint*. This leads to two questions: will np.issubdtype match any kind of signed ints? Can determine in a single check whether a number is any kind of signed or unsigned int? This is about testing for integers, the test should return False for float-likes.
NumPy provides base classes that you can/should use for subtype-checking, rather than the Python types. Use np.integer to check for any instance of either signed or unsigned integers. Use np.signedinteger and np.unsignedinteger to check for signed types or unsigned types. >>> np.issubdtype(np.uint32, np.integer) True >>> np.issubdtype(np.uint32, np.signedinteger) False >>> np.issubdtype(int, np.integer) True >>> np.issubdtype(np.array([1, 2, 3]).dtype, np.integer) True All floating or complex number types will return False when tested. np.issubdtype(np.uint*, int) will always be False because the Python int is a signed type. A useful reference showing the relationship between all of these base classes is found in the documentation here.