I have a question to NumPy experts. Consider a NumPy scalar: c = np.arange(3.0).sum(). If I try to multiply it with a custom sequence like e.g.

class S:
    
    def __init__(self, lst):
        self.lst = lst
        
    def __len__(self):
        return len(self.lst)
    
    def __getitem__(self, s):
        return self.lst[s]

c = np.arange(3.0).sum()
s = S([1, 2, 3])

print(c * s)

it works and I get: array([3., 6., 9.]).

However, I can’t do so with a list. For instance, if I inherit S from list and try it, this does not work anymore

class S(list):
    
    def __init__(self, lst):
        self.lst = lst
        
    def __len__(self):
        return len(self.lst)
    
    def __getitem__(self, s):
        return self.lst[s]

c = np.arange(3.0).sum()
s = S([1, 2, 3])

print(c * s)

and I get “can’t multiply sequence by non-int of type ‘numpy.float64′”.

So how does NumPy distinguish between the two cases?

I am asking because I want to prevent such behavior for my “S” class without inheriting from list.