Module 1 - Introduction to Python & Setup

This module lays the foundation of Python programming. Before writing any code, you must understand what Python is, why it's popular, where it's used, and how to set up your development environment.

1. What is Python?

Python is a high-level, interpreted, general-purpose programming language created by Guido van Rossum in 1991.

Python Philosophy

Python emphasizes code readability and simplicity. The language follows the Zen of Python principle: "There should be one—and preferably only one—obvious way to do it."

Key Characteristics of Python

Simple and easy-to-learn syntax
Interpreted (no compilation required)
Dynamically typed
Object-oriented and functional programming support
Extensive standard library
Large ecosystem of third-party packages
Cross-platform compatibility

Python Use Cases

Web Development – Django, Flask, FastAPI
Data Science & AI – Pandas, NumPy, TensorFlow, PyTorch
Automation & Scripting – Task automation, DevOps
Backend Development – REST APIs, microservices
Scientific Computing – Research, simulations
Testing & QA – pytest, Selenium

Why Learn Python?

Python consistently ranks as one of the most in-demand programming languages globally. It's the language of choice for AI/ML, data science, and rapid application development.

2. Python 2 vs Python 3

Python 2 reached end-of-life on January 1, 2020. All modern development uses Python 3.

Key Differences

Feature	Python 2	Python 3
Print	`print "Hello"`	`print("Hello")`
Division	`5/2 = 2`	`5/2 = 2.5`
Unicode	ASCII default	Unicode default
Status	Deprecated	Active

Important

Only learn Python 3. Python 2 is no longer maintained and should not be used for new projects.

3. Installing Python

3.1 Official Installation

Windows:

Download from python.org
Run installer
✅ Check "Add Python to PATH"
Verify: python --version

macOS:

# Using Homebrew
brew install python3

# Verify
python3 --version

Linux (Ubuntu/Debian):

sudo apt update
sudo apt install python3 python3-pip
python3 --version

3.2 Using Anaconda (Recommended for Data Science)

Anaconda includes Python + scientific libraries pre-installed.

# Download from anaconda.com
# Verify
conda --version
python --version

4. Python Development Environment

4.1 Interactive Python (REPL)

python3
>>> print("Hello, Python!")
Hello, Python!
>>> 2 + 2
4
>>> exit()

Learning Tool

REPL (Read-Eval-Print Loop) is excellent for quick testing and learning.

4.2 Code Editors & IDEs

VS Code (Recommended for Beginners)

Free and lightweight
Python extension available
Excellent debugging support
Integrated terminal

PyCharm (Professional IDE)

Best-in-class Python IDE
Advanced refactoring
Database tools
Community Edition is free

Jupyter Notebook (Data Science)

Interactive notebooks
Perfect for data analysis
Inline visualizations
Browser-based

Other Options

Sublime Text
Atom
Vim/Neovim
Google Colab (cloud-based)

5. Setting Up VS Code for Python

Installation Steps

Install VS Code from code.visualstudio.com
Install Python Extension
- Open Extensions (Ctrl+Shift+X)
- Search "Python"
- Install official Microsoft Python extension
Configure Python Interpreter
- Press Ctrl+Shift+P
- Type "Python: Select Interpreter"
- Choose your Python installation
Create Your First File
```
# hello.py
print("Hello, Python!")
```
Run Your Code
- Press F5 or
- Right-click → Run Python File

6. Package Management with pip

pip is Python's package installer.

Basic pip Commands

# Install a package
pip install requests

# Install specific version
pip install requests==2.28.0

# Upgrade a package
pip install --upgrade requests

# Uninstall
pip uninstall requests

# List installed packages
pip list

# Show package details
pip show requests

# Install from requirements file
pip install -r requirements.txt

Creating requirements.txt

# Export current packages
pip freeze > requirements.txt

# Content example:
# requests==2.28.0
# flask==2.3.0
# numpy==1.24.0

Best Practice

Always use virtual environments to isolate project dependencies (covered in Module 3).

7. Your First Python Program

hello.py

"""
My First Python Program
Author: Your Name
Date: 2026-01-18
"""

# This is a single-line comment

def main():
    """Main function"""
    name = input("Enter your name: ")
    print(f"Hello, {name}! Welcome to Python.")
    
    # Basic calculation
    age = int(input("Enter your age: "))
    print(f"In 10 years, you will be {age + 10} years old.")

if __name__ == "__main__":
    main()

Key Concepts Introduced

Comments: # for single-line
Docstrings: """...""" for documentation
Functions: def function_name():
Input: input() function
Output: print() function
F-strings: f"text {variable}"
Type conversion: int(), str(), float()

8. Python Coding Style (PEP 8)

PEP 8 is Python's official style guide.

Essential Rules

# Good: 4 spaces indentation
def calculate_sum(a, b):
    result = a + b
    return result

# Bad: Inconsistent spacing
def calculate_sum(a,b):
  result=a+b
  return result

# Good: Descriptive names
user_name = "John"
total_price = 100

# Bad: Cryptic names
un = "John"
tp = 100

# Good: 2 blank lines before top-level functions
def function_one():
    pass


def function_two():
    pass

Naming Conventions

Type	Convention	Example
Variables	snake_case	`user_name`
Functions	snake_case	`calculate_total()`
Classes	PascalCase	`UserAccount`
Constants	UPPER_CASE	`MAX_SIZE`
Modules	lowercase	`utilities.py`

Auto-Formatting

Use tools like black or autopep8 to automatically format your code.

pip install black
black your_file.py

9. Understanding Python Execution

Interpreted Language

Source Code (.py) → Python Interpreter → Bytecode (.pyc) → Python Virtual Machine → Output

Advantages

No compilation step
Platform-independent
Rapid development
Easy debugging

Disadvantages

Slower than compiled languages (C, C++, Rust)
Not suitable for system programming
Runtime errors instead of compile-time

Performance Tip

For performance-critical code, use libraries written in C (NumPy, Pandas) or tools like PyPy, Cython, or Numba.

10. Python Standard Library

Python's strength lies in its "batteries included" philosophy.

Essential Built-in Modules

import os          # Operating system interface
import sys         # System-specific parameters
import datetime    # Date and time handling
import json        # JSON encoding/decoding
import math        # Mathematical functions
import random      # Random number generation
import re          # Regular expressions
import pathlib     # Object-oriented filesystem paths

Quick Examples

import datetime
import random
import json

# Current date and time
now = datetime.datetime.now()
print(f"Current time: {now}")

# Random number
number = random.randint(1, 100)
print(f"Random number: {number}")

# JSON handling
data = {"name": "John", "age": 30}
json_string = json.dumps(data)
print(json_string)

Summary

✅ Python is a versatile, beginner-friendly language
✅ Always use Python 3 (not Python 2)
✅ VS Code + Python extension is excellent for beginners
✅ pip manages packages and dependencies
✅ Follow PEP 8 style guidelines
✅ Python's standard library is extensive

Next Steps

In Module 2, you'll learn:

Python syntax fundamentals
Variables and data types
Basic operators
Input/output operations
Type conversions

Practice Exercises

Install Python 3 and verify with python --version
Set up VS Code with the Python extension
Write a program that asks for your name and age, then prints a personalized message
Install three packages using pip: requests, pandas, flask
Create a requirements.txt file for your project

Challenge

Write a program that:

Asks the user for two numbers
Performs addition, subtraction, multiplication, and division
Displays all results in a formatted way

1. What is Python?​

Key Characteristics of Python​

Python Use Cases​

2. Python 2 vs Python 3​

Key Differences​

3. Installing Python​

3.1 Official Installation​

3.2 Using Anaconda (Recommended for Data Science)​

4. Python Development Environment​

4.1 Interactive Python (REPL)​

4.2 Code Editors & IDEs​

VS Code (Recommended for Beginners)​

PyCharm (Professional IDE)​

Jupyter Notebook (Data Science)​

Other Options​

5. Setting Up VS Code for Python​

Installation Steps​

6. Package Management with pip​

Basic pip Commands​

Creating requirements.txt​

7. Your First Python Program​

hello.py​

Key Concepts Introduced​

8. Python Coding Style (PEP 8)​

Essential Rules​

Naming Conventions​

9. Understanding Python Execution​

Interpreted Language​

Advantages​

Disadvantages​

10. Python Standard Library​

Essential Built-in Modules​

Quick Examples​

Summary​

Next Steps​

Practice Exercises​