Courses/Python/Operator Overloading & Custom Behaviours

Lesson 29 • Advanced

Operator Overloading & Custom Behaviours

Master operator overloading to make your classes behave like built-in types. Learn the techniques used by NumPy, PyTorch, Pandas, and SQLAlchemy to create intuitive, powerful APIs through custom operator behaviors.

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🔥 Operator Overloading & Custom Behaviours

Operator overloading lets your classes behave like built-in types:

✔ Numbers
✔ Strings
✔ Lists
✔ Dictionaries
✔ Booleans
✔ Comparisons
✔ Arithmetic
✔ Indexing
✔ Iteration

Real frameworks rely on this heavily:

NumPy → vector arithmetic
PyTorch → tensor operations
SQLAlchemy → query expressions
Pandas → Series/DataFrame math
Pathlib → path addition
Datetime → duration arithmetic

If you want to build professional-grade classes, operator overloading is mandatory.

⚙️ 1. Why Operator Overloading Exists

Python allows classes to define behavior for:

+ - * / // % **

== != < <= > >=

[] indexing

in membership

len(), bool(), iter(), call(), with

You override these by implementing "magic methods" such as:

__add__, __sub__, __mul__, __truediv__
__eq__, __lt__
__getitem__, __setitem__
__contains__, __len__, __bool__, __call__

These make your objects feel native and intuitive.

🔢 2. Overloading Arithmetic Operators

Let's build a simple 2D vector class with all arithmetic operators:

Vector Arithmetic

Try it Yourself »

Python

class Vec:
    def __init__(self, x, y):
        self.x = x
        self.y = y
    
    def __repr__(self):
        return f"Vec({self.x}, {self.y})"
    
    # Addition → __add__
    def __add__(self, other):
        return Vec(self.x + other.x, self.y + other.y)
    
    # Subtraction → __sub__
    def __sub__(self, other):
        return Vec(self.x - other.x, self.y - other.y)
    
    # Multiplication → __mul__ (scalar)
    def __mul__(self, scalar):
        return Vec(self.x * scalar, self.
...

🧠 3. Overloading String & Representation Functions

Two methods control how your objects appear in logs, REPLs, and print statements:

repr and str

Try it Yourself »

Python

class Vec:
    def __init__(self, x, y):
        self.x = x
        self.y = y
    
    # Developer view (unambiguous)
    def __repr__(self):
        return f"Vec({self.x}, {self.y})"
    
    # User-friendly view
    def __str__(self):
        return f"({self.x}, {self.y})"

v = Vec(10, 20)

# __repr__ is used by repr() and in collections
print(f"repr(v): {repr(v)}")

# __str__ is used by str() and print()
print(f"str(v): {str(v)}")
print(f"print(v):", v)

# In a list, __repr__ is used
print(f
...

🧩 4. Comparison Operators

To support sorting, filtering, searching, or ordering, implement:

__eq__ — ==
__ne__ — !=
__lt__ — <
__le__ — <=
__gt__ — >
__ge__ — >=

Comparison Operators

Try it Yourself »

Python

class Vec:
    def __init__(self, x, y):
        self.x = x
        self.y = y
    
    def __repr__(self):
        return f"Vec({self.x}, {self.y})"
    
    def magnitude(self):
        return (self.x**2 + self.y**2) ** 0.5
    
    # Compare by magnitude
    def __lt__(self, other):
        return self.magnitude() < other.magnitude()
    
    def __eq__(self, other):
        return self.x == other.x and self.y == other.y

# Test comparisons
v1 = Vec(3, 4)   # magnitude = 5
v2 = Vec(1, 1)   # 
...

📦 5. Overloading Indexing & Slicing

Indexing and Slicing

Try it Yourself »

Python

class Vec:
    def __init__(self, x, y):
        self.x = x
        self.y = y
    
    def __repr__(self):
        return f"Vec({self.x}, {self.y})"
    
    def __getitem__(self, idx):
        if isinstance(idx, slice):
            return (self.x, self.y)[idx]
        if idx == 0:
            return self.x
        if idx == 1:
            return self.y
        raise IndexError("Vec only has 2 dimensions")
    
    def __setitem__(self, idx, value):
        if idx == 0:
            self.x = val
...

🔄 6-7. Membership & Iteration

contains and iter

Try it Yourself »

Python

class Vec:
    def __init__(self, x, y):
        self.x = x
        self.y = y
    
    def __repr__(self):
        return f"Vec({self.x}, {self.y})"
    
    # Membership test (in)
    def __contains__(self, val):
        return val == self.x or val == self.y
    
    # Make iterable
    def __iter__(self):
        yield self.x
        yield self.y
    
    # Length
    def __len__(self):
        return 2

# Test
v = Vec(10, 20)

# Membership
print(f"v = {v}")
print(f"10 in v: {10 in v}")
print
...

🔥 8-9. Boolean & Call Behavior

bool and call

Try it Yourself »

Python

class Vec:
    def __init__(self, x, y):
        self.x = x
        self.y = y
    
    def __repr__(self):
        return f"Vec({self.x}, {self.y})"
    
    # Boolean behavior
    def __bool__(self):
        return bool(self.x or self.y)
    
    # Make callable
    def __call__(self, scale):
        return Vec(self.x * scale, self.y * scale)

# Test boolean
zero = Vec(0, 0)
nonzero = Vec(1, 2)

print(f"bool({zero}): {bool(zero)}")
print(f"bool({nonzero}): {bool(nonzero)}")

if nonzero:
    pr
...

⚡ 10-11. Reverse & Augmented Operators

Reverse and Augmented Operators

Try it Yourself »

Python

class Vec:
    def __init__(self, x, y):
        self.x = x
        self.y = y
    
    def __repr__(self):
        return f"Vec({self.x}, {self.y})"
    
    # Regular add
    def __add__(self, other):
        if isinstance(other, Vec):
            return Vec(self.x + other.x, self.y + other.y)
        return Vec(self.x + other, self.y + other)
    
    # Reverse add: when left operand doesn't support +
    def __radd__(self, other):
        return self.__add__(other)
    
    # Augmented add: 
...

🎯 12-13. Rich Container & Matrix Indexing

Container Behaviors

Try it Yourself »

Python

class Matrix:
    def __init__(self, rows):
        self.data = rows
    
    def __repr__(self):
        return f"Matrix({self.data})"
    
    def __len__(self):
        return len(self.data)
    
    def __iter__(self):
        for row in self.data:
            yield row
    
    def __contains__(self, item):
        return any(item in row for row in self.data)
    
    # Multi-dimensional indexing like NumPy
    def __getitem__(self, key):
        if isinstance(key, tuple):
            row, 
...

🌀 14-16. Bitwise & Context Operators

Bitwise and Context Managers

Try it Yourself »

Python

class Permission:
    """Bitwise operators for permission flags."""
    def __init__(self, value):
        self.value = value
    
    def __repr__(self):
        return f"Permission({self.value})"
    
    def __or__(self, other):
        return Permission(self.value | other.value)
    
    def __and__(self, other):
        return Permission(self.value & other.value)
    
    def __xor__(self, other):
        return Permission(self.value ^ other.value)
    
    def __invert__(self):
        ret
...

👑 17-19. DSL Building with Operators

Massive libraries rely on operator overloads to create readable "fake languages":

SQLAlchemy: User.age > 18
PyTorch: x = tensor * 3 + tensor2
Pandas: df["col"] + df["other"]
Pathlib: path = Path("home") / "user"

Building DSLs

Try it Yourself »

Python

# Simple expression DSL like SQLAlchemy
class Column:
    def __init__(self, name):
        self.name = name
    
    def __gt__(self, value):
        return f"{self.name} > {value}"
    
    def __lt__(self, value):
        return f"{self.name} < {value}"
    
    def __eq__(self, value):
        return f"{self.name} = '{value}'"

# SQLAlchemy-style expressions
User = type('User', (), {
    'age': Column('age'),
    'name': Column('name'),
    'active': Column('active')
})()

query1 = User.age 
...

🧩 20-22. Attribute Access & Delegation

Attribute Access Control

Try it Yourself »

Python

class Proxy:
    """Intercept all attribute access."""
    def __init__(self, target):
        object.__setattr__(self, '_target', target)
    
    def __getattr__(self, name):
        print(f"Getting: {name}")
        return getattr(self._target, name)
    
    def __setattr__(self, name, value):
        if name == '_target':
            object.__setattr__(self, name, value)
        else:
            print(f"Setting: {name} = {value}")
            setattr(self._target, name, value)

class Data:
...

🔥 23-24. Complete Mathematical System

Complete Vector Class

Try it Yourself »

Python

class Vec:
    """Fully overloaded 2D vector."""
    __slots__ = ('x', 'y', '__weakref__')
    
    def __init__(self, x, y):
        self.x = x
        self.y = y
    
    def __repr__(self):
        return f"Vec({self.x}, {self.y})"
    
    # Arithmetic
    def __add__(self, other):
        if isinstance(other, Vec):
            return Vec(self.x + other.x, self.y + other.y)
        return Vec(self.x + other, self.y + other)
    
    __radd__ = __add__
    
    def __sub__(self, other):
     
...

🧵 25-27. Immutable vs Mutable Design

Immutable vs Mutable

Try it Yourself »

Python

# Immutable (returns new object)
class ImmutableVec:
    __slots__ = ('_x', '_y')
    
    def __init__(self, x, y):
        object.__setattr__(self, '_x', x)
        object.__setattr__(self, '_y', y)
    
    @property
    def x(self):
        return self._x
    
    @property
    def y(self):
        return self._y
    
    def __repr__(self):
        return f"ImmutableVec({self._x}, {self._y})"
    
    def __add__(self, other):
        return ImmutableVec(self._x + other._x, self._y + other.
...

⚡ 28-30. Computation Graphs & Best Practices

Computation Graph Pattern

Try it Yourself »

Python

# TensorFlow/PyTorch-style computation graph
class Node:
    def __add__(self, other):
        return Add(self, other)
    
    def __mul__(self, other):
        return Mul(self, other)

class Var(Node):
    def __init__(self, name, value=None):
        self.name = name
        self.value = value
    
    def __repr__(self):
        return self.name

class Add(Node):
    def __init__(self, a, b):
        self.a = a
        self.b = b
    
    def __repr__(self):
        return f"({self.a} + {sel
...

🎯 Summary — You Now Understand the Full Python Operator Model

You now understand:

✔ Operator dispatching
✔ Delegation
✔ Emulating built-ins
✔ Full numerical operator suite
✔ Boolean overloading
✔ Callable objects
✔ Immutable vs mutable design
✔ DSL construction
✔ Computation graph building
✔ Best practices for errors
✔ Weakref integration

This puts you at a framework engineer level (the people who build NumPy/Pandas/PyTorch, not just use them).

📋 Quick Reference — Operator Overloading

Method	Operator
__add__(self, other)	a + b
__eq__(self, other)	a == b
__lt__(self, other)	a < b (enables sorting)
__mul__(self, other)	a * b
@functools.total_ordering	Auto-fill comparison methods

🎉 Great work! You've completed this lesson.

Your classes can now support arithmetic, comparisons, and other operators — making your APIs as intuitive as built-in Python types.

Up next: Mixins — compose reusable behaviour across multiple classes without deep inheritance chains.

Operator Overloading & Custom Behaviours

🔥 Operator Overloading & Custom Behaviours

⚙️ 1. Why Operator Overloading Exists

🔢 2. Overloading Arithmetic Operators

Vector Arithmetic

🧠 3. Overloading String & Representation Functions

__repr__ and __str__

🧩 4. Comparison Operators

Comparison Operators

📦 5. Overloading Indexing & Slicing

Indexing and Slicing

🔄 6-7. Membership & Iteration

__contains__ and __iter__

🔥 8-9. Boolean & Call Behavior

__bool__ and __call__

⚡ 10-11. Reverse & Augmented Operators

Reverse and Augmented Operators

🎯 12-13. Rich Container & Matrix Indexing

Container Behaviors

🌀 14-16. Bitwise & Context Operators

Bitwise and Context Managers

👑 17-19. DSL Building with Operators

Building DSLs

🧩 20-22. Attribute Access & Delegation

Attribute Access Control

🔥 23-24. Complete Mathematical System

Complete Vector Class

🧵 25-27. Immutable vs Mutable Design

Immutable vs Mutable

⚡ 28-30. Computation Graphs & Best Practices

Computation Graph Pattern

🎯 Summary — You Now Understand the Full Python Operator Model

📋 Quick Reference — Operator Overloading

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repr and str

contains and iter

bool and call