Minimum set of comparing operators to override

Python Operator Overloading: The Minimum Set for Comparison

Understand which comparison operators you need to override in Python to ensure your custom objects behave as expected, covering __eq__, __lt__, and functools.total_ordering.

When creating custom classes in Python, you often want instances of these classes to be comparable. This means defining how Python should evaluate expressions like obj1 == obj2 or obj1 < obj2. Python achieves this through special methods, often called 'dunder' methods (due to their double underscores, e.g., __eq__). Overriding these methods allows you to dictate the comparison logic for your objects.

The Core Comparison Operators: __eq__ and __lt__

At a minimum, to enable comprehensive comparison for your custom objects, you typically need to implement __eq__ (equality) and __lt__ (less than). These two methods form the foundation upon which all other rich comparison operators can be derived. Python's functools.total_ordering decorator can then automatically fill in the rest.

flowchart TD
    A["Custom Class"] --> B{"Implement `__eq__`"}
    A --> C{"Implement `__lt__`"}
    B & C --> D["Apply `@functools.total_ordering`"]
    D --> E["All Rich Comparisons (==, !=, <, <=, >, >=) Available"]
    subgraph Derived Operators
        E --> F["__ne__ (from __eq__)"]
        E --> G["__le__ (from __eq__ and __lt__)"]
        E --> H["__gt__ (from __lt__)"]
        E --> I["__ge__ (from __eq__ and __lt__)"]
    end

Derivation of Python comparison operators from __eq__ and __lt__ using total_ordering.

Let's break down why these two are crucial:

• __eq__(self, other): This method defines what it means for two objects to be equal (==). If you don't implement it, Python's default behavior is to compare object identities (i.e., id(self) == id(other)), which is rarely what you want for custom data types. It should return True if the objects are equal, False otherwise, or NotImplemented if the comparison is not supported for the given other type.

• __lt__(self, other): This method defines what it means for one object to be less than another (<). This is the primary method for establishing an ordering. If you implement __lt__, functools.total_ordering can then infer __le__, __gt__, and __ge__.

Leveraging functools.total_ordering

The functools.total_ordering decorator is a powerful tool that simplifies the implementation of rich comparison operators. If a class defines __eq__ and one of __lt__, __le__, __gt__, or __ge__, this decorator will automatically supply the remaining comparison methods. This significantly reduces boilerplate code and ensures consistency across all comparison operations.

from functools import total_ordering

@total_ordering
class MyObject:
    def __init__(self, value):
        self.value = value

    def __eq__(self, other):
        if not isinstance(other, MyObject):
            return NotImplemented
        return self.value == other.value

    def __lt__(self, other):
        if not isinstance(other, MyObject):
            return NotImplemented
        return self.value < other.value

# Example Usage:
obj1 = MyObject(10)
obj2 = MyObject(20)
obj3 = MyObject(10)

print(f"obj1 == obj3: {obj1 == obj3}") # True (from __eq__)
print(f"obj1 != obj2: {obj1 != obj2}") # True (from total_ordering)
print(f"obj1 < obj2: {obj1 < obj2}")   # True (from __lt__)
print(f"obj2 > obj1: {obj2 > obj1}")   # True (from total_ordering)
print(f"obj1 <= obj3: {obj1 <= obj3}") # True (from total_ordering)
print(f"obj2 >= obj1: {obj2 >= obj1}") # True (from total_ordering)

Implementing __eq__ and __lt__ with functools.total_ordering.

Why Not Just __eq__ and __ne__?

While __eq__ and __ne__ (not equal) are often implemented together, they only cover equality comparisons. They do not provide any ordering information. If you need to sort objects, use them in sets/dictionaries (which rely on hashing and equality), or perform range checks, you'll need the ordering operators. __ne__ can actually be automatically derived from __eq__ (if __eq__ returns True, __ne__ returns False, and vice-versa), so explicitly implementing __ne__ is often redundant if __eq__ is present.

Summary of Comparison Operators

Here's a quick reference for the rich comparison operators and their relationships:

Python Rich Comparison Operators

By implementing __eq__ and __lt__ and applying @total_ordering, you provide a robust and complete set of comparison capabilities for your custom Python objects with minimal code.