Pythonic way to Implement Data Types (Python 2.7)

The majority of my programming experience has been with C++. Inspired by Bjarne Stroustrup's talk here, one of my favorite programming techniques is "type-rich" programming; the development of new robust data-types that will not only reduce the amount of code I have to write by wrapping functionality into the type (for example vector addition, instead of newVec.x = vec1.x + vec2.x; newVec.y = ... etc, we can just use newVec = vec1 + vec2) but will also reveal problems in your code at compile time through the strong type system.

A recent project I have undertaken in Python 2.7 requires integer values that have upper and lower bounds. My first instinct is to create a new data type (class) that will have all the same behavior as a normal number in python, but will always be within its (dynamic) boundary values.

class BoundInt:
    def __init__(self, target = 0, low = 0, high = 1):
        self.lowerLimit = low
        self.upperLimit = high
        self._value = target
        self._balance()

    def _balance(self):
        if (self._value > self.upperLimit):
            self._value = self.upperLimit
        elif (self._value < self.lowerLimit):
            self._value = self.lowerLimit
        self._value = int(round(self._value))

    def value(self):
        self._balance()
        return self._value

    def set(self, target):
        self._value = target
        self._balance()

    def __str__(self):
        return str(self._value)

This is a good start, but it requires accessing the meat of these BoundInt types like so

x = BoundInt()
y = 4
x.set(y)           #it would be nicer to do something like x = y
print y            #prints "4"
print x            #prints "1"
z = 2 + x.value()  #again, it would be nicer to do z = 2 + x
print z