Dynamic Typing

Overview

Python is dynamically typed — a variable can hold any type and types are checked at runtime, not compile time. This makes Python fast to write but requires careful validation in production systems.

Syntax

python

x = 42          # int
x = "hello"     # now a str — no error
x = [1, 2, 3]   # now a list

# Check type at runtime
type(x)         # <class 'list'>
isinstance(x, list)  # True

Common Pitfalls

Dynamic typing is NOT the same as weak typing — Python is strongly typed (5 + '5' raises TypeError).
Use type hints (def func(x: int) -> str) for documentation and static analysis with mypy.
Interview tip: Mention that Python's type system is 'duck typing' — if an object has the right methods, it works regardless of its class.

Real-World Example

Function that behaves differently based on input type

example

python

def double(value):
    if isinstance(value, str):
        return value * 2      # "hi" → "hihi"
    elif isinstance(value, (int, float)):
        return value * 2      # 5 → 10
    raise TypeError(f"Unsupported type: {type(value)}")

print(double("hi"))   # hihi
print(double(5))      # 10

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