Python treats everything as an object, even the data types you work with daily. To write clean, bug-free code, it's crucial to understand how Python objects behave—especially when it comes to mutability and immutability.
What the Instructor Covered
1. Python Data Types – The Building Blocks
The session begins by introducing core data types under two broad categories:
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Numbers (integers, floats, etc.)
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Text (strings)
Understanding these types and how to manipulate them effectively is one of the first skills every Python developer should master.
2. Everything is an Object in Python
In Python, each object has three key properties:
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Identity → A unique memory address (checked using
id()) -
Type → Defines what kind of object it is (e.g., int, str, list)
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Value → The actual data stored in the object
3. What is Mutability?
✅ Mutable Objects
These objects can be modified after they're created.
Examples:
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list -
set -
dict
❌ Immutable Objects
Once created, these cannot be changed. Any update creates a new object in memory instead.
Examples:
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int -
float -
string -
tuple
4. Identity Matters More Than Value
The instructor stressed a powerful idea:
To understand mutability, don't just look at an object's value—always check its identity using
id().
5. Real Examples That Made It Click
To show the difference clearly, the lecture included hands-on demos like:
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Updating a number variable does not change the original object—Python creates a brand-new one in memory.
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Using an everyday analogy—such as changing the sugar amount stored in a variable—beautifully illustrates how immutable values behave like rigid containers, while mutable ones act like editable jars.
Final Takeaway
Understanding mutable and immutable objects isn’t just theory—it's the foundation of writing smart, memory-efficient Python programs. This knowledge helps you avoid unexpected behavior when modifying data, especially inside functions or loops.