1. Python Introduction

• What is Python? (Interpreted, high-level, general-purpose)

• History of Python (Guido van Rossum, Python 2 EOL in 2020)

• Python 2 vs. Python 3 (key differences, print() vs print, Unicode)

• Features: Dynamic typing, indentation-based syntax, cross-platform

• Use Cases: Web Dev (Django/Flask), Data Science (Pandas), AI/ML (TensorFlow), Automation

2. Python Installation and Setup

• Install Python 3.12+ (Windows/macOS/Linux)

• IDE Setup: PyCharm vs VS Code vs Jupyter Notebook

• Virtual Environments: venv and pip basics

• Hello World: Script execution in IDE and terminal

3. Python Execution Model

• Interpreter Workflow: .py → Bytecode → PVM (Python Virtual Machine)

• Interactive Shell: REPL (Read-Eval-Print Loop)

• .pyc Files: Bytecode caching for faster execution

4. Data Types

• Primitive: int, float, bool, str, None

• Composite:

  • Mutable: list, dict, set

  • Immutable: tuple, frozenset, bytes

• Type Checking: type(), isinstance()

5. Variables and Scope

• Variable Assignment: Dynamic typing (a = 10 vs a = "hello")

• Scope:

  • Local: Inside functions

  • Global: global keyword

  • Nonlocal: Nested functions (nonlocal keyword)

• Object Identity: id() function, is operator

6. Operators and Keywords

• Arithmetic: +, //, **, %

• Comparison: ==, is, in

• Logical: and, or, not

• Walrus Operator: := (Python 3.8+)

• Keywords: async, await, yield, lambda

7. Identifiers and PEP8

• Rules: No symbols except _, case-sensitive

• PEP8 Conventions:

  • snake_case for variables/functions

  • CamelCase for classes

  • UPPER_CASE for constants

8. First Python Program

9. Command-Line Execution

10. Python Internals

• Garbage Collection: Reference counting, cyclic garbage collector

• Memory Optimization: Interning (a = 10; b = 10 → a is b → True)

11. Script Automation

12. Control Flow

13. OOP in Python

• Class Definition

• Four Pillars:

  1. Encapsulation: _protected and __private vars

  2. Inheritance: class ElectricCar(Car):

  3. Polymorphism: Method overriding

  4. Abstraction: ABC (Abstract Base Classes)

14. Advanced OOP

• Multiple Inheritance: class Child(Parent1, Parent2):

• Diamond Problem: MRO (Method Resolution Order)

• Magic Methods: __str__, __add__, __len__

• Mixins: Reusable utility classes

15. Exception Handling

16. Data Structures

• Lists: nums = [1, 2, 3], slicing, list comprehensions

• Tuples: Immutable coordinates = (4, 5)

• Dictionaries: user = {"name": "Alice", "age": 30}

• Sets: unique = {1, 2, 3}

17. File Handling

• Reading/Writing Files

• Modes: r, w, a, rb (binary)

• CSV/JSON: csv and json modules

18. Modules and Packages

• Creating Modules: math_utils.py → import math_utils

• Standard Library: os, sys, datetime, random

• Third-Party Packages: pip install numpy

19. Functional Programming

• Lambda: square = lambda x: x ** 2

• Map/Filter/Reduce

• Decorators:

20. Concurrency

21. Modern Python Features

22. Final Project Ideas

• Web Scraper: requests + BeautifulSoup

• REST API: FastAPI or Flask

• Data Analysis: Pandas + Matplotlib