I am extending the functionalities of a Python list and I would like to include a method to normalize a vector to the [0, 1] range, by using element-wise operations. I came out with this solution, but find that using two classes does not seem clean. The main motivation for using two classes is that the output of data - min(data) from normalize() returns a Python list (due to how __sub__() was implemented), and that native list does not seem to have __truediv__() implemented.

How can I achieve the normalize() method and avoid the creation of the intermediate _BaseList class? The project I am working on has very constrained memory and I cannot use Numpy.

class _BaseList(list):     def __init__(self, data):         super().__init__(data)      def __sub__(self, value):         if type(value) in (int, float):             return [elem - value for elem in self]         elif type(value) is list and len(value) == len(self):             return [a - b for a, b in zip(value, self)]      def __truediv__(self, value):         if type(value) in (int, float):             return [elem / value for elem in self]         elif type(value) is list and len(value) == len(self):             return [a / b for a, b in zip(value, self)]   class Array(_BaseList):      def __init__(self, data=None):         super().__init__(data)      def normalize(self):         print(type(self))         return _BaseList((self - min(self))) / float(max(self) - min(self))