Keeping Your Python Classes Equal: A Comprehensive Guide to Equivalence Methods
In Python, the eq and ne special methods provide a convenient way to define equivalence for custom classes. While the basic approach of comparing __dict__s is a viable option, it may face challenges with subclasses and interoperability with other types.
A More Robust Equivalence Handling
To address these limitations, consider a more comprehensive implementation:
class Number: def __init__(self, number): self.number = number def __eq__(self, other): if isinstance(other, Number): return self.number == other.number return NotImplemented def __ne__(self, other): x = self.__eq__(other) if x is not NotImplemented: return not x return NotImplemented def __hash__(self): return hash(tuple(sorted(self.__dict__.items()))) class SubNumber(Number): pass
This version includes:
Validation and Testing
To verify the robustness of this approach, here's a set of assertions:
n1 = Number(1) n2 = Number(1) n3 = SubNumber(1) n4 = SubNumber(4) assert n1 == n2 assert n2 == n1 assert not n1 != n2 assert not n2 != n1 assert n1 == n3 assert n3 == n1 assert not n1 != n3 assert not n3 != n1 assert not n1 == n4 assert not n4 == n1 assert n1 != n4 assert n4 != n1 assert len(set([n1, n2, n3])) == 1 assert len(set([n1, n2, n3, n4])) == 2
These assertions demonstrate the correct behavior of the equivalence methods and the consistency of hash values.
By embracing this more comprehensive approach, you can create Python classes with robust equivalence handling, ensuring reliable comparisons and accurate set and dictionary operations.
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