5. Python Objects | Dive into Python Object based Data Model
In this tutorial, we’ll explore a *fundamental concept in Python*: everything in Python is an *object*. This is one of the core principles that makes Python different from other programming languages like Java or C++.
You’ll learn:
Why we write programs: instructions to operate on data
Different types of data in Python: integers, strings, lists, and more
Why every piece of data in Python is stored as an **object**, not as a raw value
Difference between raw values (in Java/C) vs objects (in Python)
Internal structure of Python objects (ID, type, value, reference count)
The role of *classes in Python objects* (e.g., int, str)
Using the `type()` function to identify object types
Examples with integers, strings, lists, and operations
Why even evaluated expressions (like `10 + 20`) produce Python objects
Python’s *integer caching* for values from `-5` to `256` and how it improves performance
How objects exist only temporarily in memory (RAM) during execution
Why understanding objects is crucial for advanced topics like immutability, references, lists, and OOP
By the end, you’ll have a strong foundation in how Python treats data, which will make advanced concepts easier to learn later on.
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Key Topics Covered
Python objects explained
Values vs objects: Java vs Python comparison
Object structure: ID, type, value, reference count
Python `type()` function
Object creation during program execution
Integer caching in Python (-5 to 256 explained)
Memory management in Python
Why “everything is an object” in Python
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Timestamps
0:00 Introduction: Why we write programs
0:37 Examples of different data types in Python
1:19 All data is stored as objects
2:00 Raw value vs object explained
2:40 Structure of a Python object (ID, type, value, reference count)
3:50 Role of classes (int, str, list)
4:40 Demo: printing integers and strings with `print()`
5:51 Using `type()` to check object type
6:52 Performing operations on objects (addition, concatenation)
7:59 Why even expressions produce objects
8:57 Memory: objects created in RAM, deleted after execution
9:43 Integer caching (-5 to 256 optimization)
11:20 Assigning objects to variables for reuse
11:37 What’s next: Variables in Python
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