Understanding Mutability and Multiple Variable Assignment to Class Objects in Python

Published: 19 August 2025
on channel: vlogize

Explore how Python handles `mutable` and `immutable` objects through variable assignment and class objects, and learn the crucial differences.
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Understanding Mutability and Multiple Variable Assignment to Class Objects in Python

In the world of Python programming, understanding how variables and objects interact, especially in the context of mutability, can be quite perplexing. This guide aims to clear up any confusion surrounding these concepts and demonstrate their significance when working with classes in Python. Below, we’ll delve into the core differences between mutable and immutable objects, and explain how multiple variable assignments behave based on these properties.

The Confusion Between Immutability and Variable Assignment

The misconception often lies in the assumptions we make about variable assignments when working with different data types. It’s vital to establish that immutability vs mutability is not the sole concern. What truly matters is whether you are mutating an object or merely reassigning a reference.

Immutable Objects

When we assign variable names to immutable objects, such as integers or strings, we are not creating copies of the object:

[[See Video to Reveal this Text or Code Snippet]]

Here, both a and b reference the same immutable object (1). If we were to alter a after this assignment, it simply points a to a new integer, leaving b unchanged:

[[See Video to Reveal this Text or Code Snippet]]

Mutable Objects

In contrast, mutable objects like lists or dictionaries can be changed in place:

[[See Video to Reveal this Text or Code Snippet]]

Both my_list and another_list will reflect the changes made, as they reference the same mutable object.

How Class Objects Affect Mutability

When working with class objects in Python, the distinction between mutability and assignment becomes even more intriguing. Let's explore two examples to illustrate this:

Example 1: Node Class

[[See Video to Reveal this Text or Code Snippet]]

In the above code:

Both slow and fast are assigned to reference the same Node object, head.

However, if we change the fast variable to point to another node (fast = fast.next.next), we do not mutate the object. Instead, we are simply changing the reference of fast. Thus the original head, slow, and the modified fast refer to different objects after this reassignment.

Example 2: Dummy Class

[[See Video to Reveal this Text or Code Snippet]]

Here, p1 and p2 both reference the same Dummy instance. When we update p1.val, we mutate the internal state of the Dummy instance. Therefore, both p1 and p2 now reflect the new value. This shows that the previous shared reference resulted in a mutable change, even though val itself is an immutable integer.

Summary: Reassignment vs. Mutation

When discussing variables and their assignments in Python, it's crucial to differentiate between reference reassignment (which affects what an identifier points to) and mutation (which affects what the object itself contains). To sum up:

Reassignment changes what object a variable references:

[[See Video to Reveal this Text or Code Snippet]]

Mutation refers to changing the object's internal state without changing its reference:

[[See Video to Reveal this Text or Code Snippet]]

Understanding these concepts will empower you to write better, more efficient Python code without falling into common pitfalls. Feel confident in your multiple variable assignments and embrace the powerful nature of Python's object handling!

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