Mutable and Immutable Objects

An object's mutability determines whether its contents can be changed after creation.

Immutable example — id() stays same only for the same object

x = 10
print(id(x))
x = x + 5      # creates a NEW int object; x now points elsewhere
print(id(x))   # different id

s = "hello"
print(id(s))
s = s + " world"   # a brand-new string object is created
print(id(s))       # different id — original "hello" is unchanged in memory

Mutable example — id() stays the SAME after in-place change

lst = [1, 2, 3]
print(id(lst))
lst.append(4)        # modifies the SAME list object in place
print(id(lst))       # same id
print(lst)            # [1, 2, 3, 4]

Why it matters — function arguments and aliasing

def modify_list(lst):
    lst.append(100)     # mutates the caller's list too!

a = [1, 2, 3]
modify_list(a)
print(a)   # [1, 2, 3, 100] -- the original list changed

def modify_number(n):
    n += 100             # rebinds the local n; caller's variable unaffected

x = 5
modify_number(x)
print(x)   # 5 -- unchanged, int is immutable

Aliasing pitfall with mutable objects

a = [1, 2, 3]
b = a            # b is an ALIAS, not a copy — both point to the same list
b.append(4)
print(a)         # [1, 2, 3, 4] -- a changed too!

c = a.copy()     # creates an independent copy
c.append(99)
print(a)         # [1, 2, 3, 4] -- unaffected by changes to c

Summary

• Immutable objects are safe to share; mutable objects require care (copy explicitly to avoid unintended side effects).
• Tuples are immutable, but a tuple containing a list can still have that inner list mutated.