Python Memory Concepts

What is Memory in Python?

Memory is the physical or virtual space where Python stores data (objects) while a program is running. Every value you create—whether a number, a string, or a list—occupies a specific spot in your RAM.

Variables & References

In Python, a variable does not actually store the value itself. Instead, it stores a reference or the memory address where the value is located.

# When you write:
a = 10

# Internally:
# 1. An object '10' is created in memory.
# 2. Variable 'a' points to the address of '10'.

Memory Address & Identity

Python provides built-in tools to inspect where objects are located in memory and whether two variables point to the same location.

The id() Function

The id() function returns a unique integer representing the memory address of the object.

x = 100
print(id(x))  # Output: A large unique number like 14072382

Identity Operators: 'is' vs '=='

a = [1, 2, 3]
b = [1, 2, 3]

print(a == b) # True (Same content)
print(a is b) # False (Different memory locations)

Memory Optimization (Interning)

Python uses a technique called Interning to save memory. For small integers (usually -5 to 256) and certain strings, Python reuses the same memory location for different variables with the same value.

# Same Value -> Same Memory
x = 10
y = 10
print(x is y) # True (Optimization at work)

# Different Value -> Different Memory
m = 500
n = 500
print(m is n) # False (Memory is not shared for larger numbers)

Mutable vs Immutable

How Python handles memory during updates depends on whether the object is Mutable (can change) or Immutable (cannot change).

1. Mutable Objects (Lists, Dicts, Sets)

The value can be changed without changing the memory address.

arr = [1, 2]
print(id(arr)) # Address X

arr.append(3)
print(id(arr)) # Still Address X (Address didn't change)

2. Immutable Objects (Int, Float, String, Tuple)

The value cannot be changed. If you "update" it, Python creates a brand new object in a new memory location.

age = 20
print(id(age)) # Address A

age = age + 1
print(id(age)) # Address B (New memory created!)

Garbage Collection

Python features automatic memory management. When an object in memory no longer has any variables pointing to it, it becomes "garbage."

• Trash Cleanup: Python's Garbage Collector (GC) automatically deletes these objects to free up RAM.
• Reference Counting: Python keeps track of how many references point to an object. When the count hits 0, the object is deleted.

x = [1, 2, 3] # Object created
x = None      # The list [1, 2, 3] now has 0 references. 
              # It will be removed by Garbage Collection.

Quick Revision Table

Summary of core memory concepts for quick reference and exam preparation.

Exam One-Liners:

• Variable: A label pointing to a location in memory.
• Interning: Reusing memory for small common values.
• Reference: The link between a variable name and the object in the heap.