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Polymorphism in Python

Polymorphism means "many forms" — the same interface works with different types. In Python, polymorphism is natural because of duck typing: if an object has the right method, it works regardless of its class.

Built-in Polymorphism

# len() works on any object with __len__
print(len("hello"))      # 5 (string)
print(len([1, 2, 3]))    # 3 (list)
print(len({"a": 1}))     # 1 (dict)

# + operator behaves differently based on type
print(3 + 5)             # 8 (addition)
print("Hello" + " World") # "Hello World" (concatenation)
print([1, 2] + [3, 4])   # [1, 2, 3, 4] (list merge)

# for loop works on any iterable
for item in [1, 2, 3]: pass      # list
for char in "Python": pass       # string
for key in {"a": 1, "b": 2}: pass  # dict keys

Polymorphism with Inheritance

# Different classes share the same method name
class Shape:
    def area(self):
        raise NotImplementedError

    def describe(self):
        return f"{type(self).__name__}: area = {self.area():.2f}"

class Circle(Shape):
    def __init__(self, radius):
        self.radius = radius

    def area(self):
        import math
        return math.pi * self.radius ** 2

class Rectangle(Shape):
    def __init__(self, width, height):
        self.width = width
        self.height = height

    def area(self):
        return self.width * self.height

class Triangle(Shape):
    def __init__(self, base, height):
        self.base = base
        self.height = height

    def area(self):
        return 0.5 * self.base * self.height

# Polymorphic function — works with ANY shape
def total_area(shapes):
    return sum(s.area() for s in shapes)

shapes = [Circle(5), Rectangle(3, 4), Triangle(6, 8)]
for s in shapes:
    print(s.describe())
# Circle: area = 78.54
# Rectangle: area = 12.00
# Triangle: area = 24.00

print(f"Total: {total_area(shapes):.2f}")  # Total: 114.54

Duck Typing

# "If it walks like a duck and quacks like a duck, it is a duck"
# Python does not check the class — it checks if the method exists

class Dog:
    def speak(self):
        return "Woof!"

class Cat:
    def speak(self):
        return "Meow!"

class Robot:
    def speak(self):
        return "Beep boop!"

# No common parent class needed — just the same method name
def make_them_speak(things):
    for thing in things:
        print(thing.speak())

make_them_speak([Dog(), Cat(), Robot()])
# Woof!
# Meow!
# Beep boop!

# Practical: anything with .read() works as a "file-like object"
class StringStream:
    def __init__(self, text):
        self.text = text
        self.pos = 0

    def read(self, n=-1):
        if n == -1:
            result = self.text[self.pos:]
            self.pos = len(self.text)
        else:
            result = self.text[self.pos:self.pos + n]
            self.pos += n
        return result

# Works with any function expecting a file-like object
def process_stream(stream):
    content = stream.read()
    return content.upper()

print(process_stream(StringStream("hello world")))  # HELLO WORLD

Polymorphism with Protocols (Python 3.8+)

# Protocols formalize duck typing with type hints
from typing import Protocol

class Drawable(Protocol):
    def draw(self) -> str: ...

class Button:
    def draw(self) -> str:
        return "[Button]"

class TextBox:
    def draw(self) -> str:
        return "[____TextBox____]"

class Checkbox:
    def draw(self) -> str:
        return "[x] Checkbox"

# Type-safe polymorphism — no inheritance needed
def render_ui(widgets: list[Drawable]) -> None:
    for widget in widgets:
        print(widget.draw())

render_ui([Button(), TextBox(), Checkbox()])
# [Button]
# [____TextBox____]
# [x] Checkbox

Method Overriding vs Overloading

# OVERRIDING: child replaces parent method (Python supports this)
class Animal:
    def sound(self):
        return "..."

class Dog(Animal):
    def sound(self):  # overrides Animal.sound()
        return "Woof!"

# OVERLOADING: same method name, different parameters
# Python does NOT support traditional overloading
# Instead, use default arguments or *args
class Calculator:
    def add(self, *args):
        return sum(args)

calc = Calculator()
print(calc.add(1, 2))        # 3
print(calc.add(1, 2, 3, 4))  # 10

# Or use singledispatch for type-based dispatch
from functools import singledispatch

@singledispatch
def format_value(value):
    return str(value)

@format_value.register(int)
def _(value):
    return f"{value:,}"

@format_value.register(float)
def _(value):
    return f"{value:.2f}"

@format_value.register(list)
def _(value):
    return f"[{len(value)} items]"

print(format_value(1000000))    # 1,000,000
print(format_value(3.14159))    # 3.14
print(format_value([1,2,3]))    # [3 items]

• Polymorphism lets the same code work with different types — write flexible, reusable functions.
• Python uses duck typing: the object's methods matter, not its class hierarchy.
• Use method overriding in child classes to customize behavior while keeping the same interface.
• Use Protocol (typing module) to formalize duck typing with type hints.
• Use @singledispatch for type-based function overloading in Python.