Mutability

Python Basics: Mutable vs Immutable Objects

Some concepts

• An object’s identity never changes once it has been created.

• An object’s type defines the possible values and operations. It is unchangeable like the identity.

• The value of some objects can change, depending on the type.

Some objects contain references to other objects, these objects are called containers (like tuple, list, or dictionary).

All variable names in Python are said to be references to the values.

Python keeps an internal counter on how many references an object has.

Once the counter goes to zero the GB in Python removes the object, thus freeing up the memory.

Immutable Objects

Every time when we try to update the value of an immutable object, a new object is created instead.

That’s when we have updated the first string it doesn’t change the value of the second. Immutable data types:

• int

• float

• decimal

• bool

• string

• tuple

• range

a = "foo"
# the variable a points to the memory address 4000
# 4000 reference count is 1

a += "!"
# 1. the new content is stored in a different memory address
# 2. the reference points to the new memory adress 4016
# 3. 4016 has one reference and 4000 another
# 4. reference to 4000 is removed and count is 0
# 5. 4000 is ready to by free by the GC

Mutable Objects

• list

• dictionary

• set

• user-defined classes

Container objects

Some objects contain references to other objects, these objects are called containers (ie, tuple, list, or dictionary). The value of an immutable container that contains a reference to a mutable object can be changed if that mutable object is changed.

However, the container is still considered immutable because when we talk about the mutability of a container only the identities of the contained objects are implied.

skills = ["Programming", "Machine Learning", "Statistics"]
person = (129392130, skills)
print(type(person))
> <class 'tuple'>

print(person)
> (129392130, ['Programming', 'Machine Learning', 'Statistics'])

skills[2] = "Maths"
print(person)
> (129392130, ['Programming', 'Machine Learning', 'Maths'])

Mutable Default Arguments

Related sources:

• Common Gotchas (The Hitchhiker’s Guide to Python!)

# Function declaration
def append_to(element, to=[]):
    to.append(element)
    return to
    
# Code execution
my_list = append_to(12)
print(my_list)

my_other_list = append_to(42)
print(my_other_list)

# Expected output
# > [12]
# > [42]

# Actual output
# > [12]
# > [12, 42]

# Solution
def append_to(element, to=None):
    if to is None:
        to = []
    to.append(element)
    return to