How do you ensure consistent and robust equivalence comparisons for custom Python classes, especially when dealing with subclasses and sets?

Elegant Approaches for Equivalence Comparison in Python Classes

In Python, custom classes can implement the __eq__ and __ne__ methods to define equivalence for the == and != operators, respectively. While the traditional method of comparing dictionary attributes is straightforward, it presents certain limitations.

A More Refined Approach

Consider the following scenario:

class Number:
    def __init__(self, number):
        self.number = number

n1 = Number(1)
n2 = Number(1)

# Default comparison fails: they are different objects
assert n1 != n2

To address this issue, we can override the __eq__ method:

class Number:
    def __init__(self, number):
        self.number = number

    def __eq__(self, other):
        if isinstance(other, Number):
            return self.number == other.number
        return False

However, for Python 2, we also need to implement __ne__ to ensure commutative behavior:

class Number:
    def __init__(self, number):
        self.number = number

    def __eq__(self, other):
        if isinstance(other, Number):
            return self.number == other.number
        return False

    def __ne__(self, other):
        return not self.__eq__(other)

This ensures that n1 == n2 evaluates to True, as expected.

Subclass Equivalence

Introducing subclasses complicates equivalence comparison:

class SubNumber(Number):
    pass

n3 = SubNumber(1)

# Subclass comparison fails for classic-style classes
assert n1 == n3  # False (for classic-style classes)
assert n3 == n1  # True

# Non-commutative comparison
assert n1 != n3  # True (for classic-style classes)
assert n3 != n1  # False

For classic-style classes, the comparison method is invoked based on the first operand's type, leading to non-commutative behavior. To address this, we can return NotImplemented for unsupported operand types, which delegates the comparison to the other operand's method:

def __eq__(self, other):
    if isinstance(other, Number):
        return self.number == other.number
    return NotImplemented

Hashing and Sets

Lastly, note that sets use object identifiers for hashing, which can lead to incorrect results:

assert len(set([n1, n2, n3])) == 3  # Incorrectly reports 3 unique numbers

To resolve this, we can override the __hash__ method:

def __hash__(self):
    return hash(tuple(sorted(self.__dict__.items())))

With these enhancements, the equivalence and uniqueness behaviors become correct and consistent, ensuring robust comparisons and accurate representation in sets:

assert len(set([n1, n2, n3])) == 1
assert len(set([n1, n2, n3, n4])) == 2

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