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

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

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.

I suggest passing a tuple of types to python isinstance() built-in function. And regarding to your question about np.issubtype() it doesn't match any kind of signed ints, it determine if a class is a subclass of a second class. And since all of integer types (int8, int32, etc.) are subclasses of int it will return True if you pass any of these type along with int.

Here is an example:

>>> a = np.array([100])>>> >>> np.issubdtype(type(a[0]), int)True>>> isinstance(a[0], (int, np.uint))True>>> b = np.array([100], dtype=uint64)>>> >>> isinstance(b[0], (int, np.uint))True

Also, as a more generic approach (is not appropriate when you only want to match some specific types) you can use np.isreal():

>>> np.isreal(a[0])True>>> np.isreal(b[0])True>>> np.isreal(2.4) # This might not be the result you wantTrue>>> np.isreal(2.4j)False