Python Programming Notes

📥 Python Assignment 2

📥 Python Assignment 1

📥 Functions Unit -3

📥 Python unit 4

📥 Python unit 5

Python Programming

Introduction

Python is a high-level, interpreted programming language known for its simplicity and readability. It is widely used for web development, data science, artificial intelligence, and automation.

1. Python Fundamentals

Basic Concepts:

• Variables and Data Types
• Operators (Arithmetic, Logical, Comparison)
• Control Flow (if, else, elif)
• Loops (for, while)

2. Functions and Modules

• Function Definition and Calling
• Parameters and Return Values
• Scope and Global Variables
• Built-in Modules
• Creating Custom Modules

3. Object-Oriented Programming

• Classes and Objects
• Inheritance
• Polymorphism
• Encapsulation
• Abstract Classes and Interfaces

4. Advanced Topics

• List Comprehensions
• Decorators
• Generators and Iterators
• Exception Handling
• Context Managers

5. Python for Data Science

• NumPy for Numerical Computing
• Pandas for Data Manipulation
• Matplotlib and Seaborn for Visualization
• Scikit-learn for Machine Learning

Detailed Python Fundamentals

Variables and Data Types

Python uses dynamic typing, meaning you don't need to declare variable types explicitly. Python automatically determines the type based on the value assigned.

Basic Data Types:

• Integers: Whole numbers (e.g., 42, -10, 0)
• Floats: Decimal numbers (e.g., 3.14, -2.5)
• Strings: Text data (e.g., "Hello", 'Python')
• Booleans: True or False values
• Lists: Ordered collections (e.g., [1, 2, 3, "hello"])
• Tuples: Immutable ordered collections (e.g., (1, 2, 3))
• Dictionaries: Key-value pairs (e.g., {"name": "John", "age": 30})
• Sets: Unordered unique collections (e.g., {1, 2, 3})

Operators in Python

Arithmetic Operators:

• Addition (+): 5 + 3 = 8
• Subtraction (-): 5 - 3 = 2
• Multiplication (*): 5 * 3 = 15
• Division (/): 5 / 2 = 2.5
• Floor Division (//): 5 // 2 = 2
• Modulus (%): 5 % 2 = 1
• Exponentiation (**): 5 ** 2 = 25

Comparison Operators:

• Equal to (==): 5 == 5 returns True
• Not equal to (!=): 5 != 3 returns True
• Greater than (>): 5 > 3 returns True
• Less than (<): 5 < 3 returns False
• Greater than or equal to (>=): 5 >= 5 returns True
• Less than or equal to (<=): 3 <= 5 returns True

Logical Operators:

• AND: Returns True if both conditions are True
• OR: Returns True if at least one condition is True
• NOT: Reverses the boolean value

Control Flow Structures

If-Else Statements: Used to execute code based on conditions.

age = 20
if age < 13:
    print("Child")
elif age < 18:
    print("Teenager")
else:
    print("Adult")

Loops:

For Loop: Iterates through a sequence

for i in range(5):
    print(i)  # Prints 0, 1, 2, 3, 4

While Loop: Executes while a condition is true

count = 0
while count < 5:
    print(count)
    count += 1

Functions and Code Organization

Function Basics

Functions are reusable blocks of code that perform specific tasks.

Function Definition:

def greet(name):
    return f"Hello, {name}!"

print(greet("Alice"))  # Output: Hello, Alice!

Parameters and Return Values:

• Parameters: Variables in the function definition
• Arguments: Values passed to the function
• Return Statement: Returns a value from the function

Scope and Variables

• Global Scope: Variables accessible throughout the program
• Local Scope: Variables accessible only within a function
• Non-local Scope: Variables in nested functions

Object-Oriented Programming (OOP)

Classes and Objects

A class is a blueprint for creating objects.

class Dog:
    def __init__(self, name, age):
        self.name = name
        self.age = age
    
    def bark(self):
        return f"{self.name} is barking!"

# Creating an object
dog = Dog("Buddy", 3)
print(dog.bark())  # Output: Buddy is barking!

Key OOP Concepts

Inheritance: Allows a class to inherit properties and methods from another class.

class Animal:
    def make_sound(self):
        pass

class Cat(Animal):
    def make_sound(self):
        return "Meow!"

Polymorphism: Different classes can have the same method name with different implementations.

Encapsulation: Bundling data and methods within a class and controlling access to them.

Abstraction: Hiding complex implementation details and showing only necessary features.

Error Handling

Try-Except Blocks

Used to catch and handle errors gracefully.

try:
    result = 10 / 0
except ZeroDivisionError:
    print("Cannot divide by zero!")
except Exception as e:
    print(f"An error occurred: {e}")
finally:
    print("This always executes")

Python Best Practices

1. Use meaningful variable names: user_age instead of ua
2. Write comments for complex code: Explain the "why" not the "what"
3. Keep functions small and focused: Each function should do one thing
4. Follow PEP 8 style guide: Python's official style conventions
5. Test your code: Write test cases for critical functionality
6. Use virtual environments: Isolate project dependencies
7. Avoid global variables: Use function parameters instead
8. Write docstrings: Document your functions and classes

Python Applications and Career Paths

Web Development

• Frameworks: Django, Flask, FastAPI
• Build: REST APIs, web applications, content management systems
• Jobs: Full-stack developer, backend engineer

Data Science

• Tools: NumPy, Pandas, Matplotlib, Scikit-learn
• Work: Data analysis, visualization, machine learning models
• Jobs: Data scientist, data analyst, ML engineer

Automation and Scripting

• Use Cases: File processing, web scraping, system administration
• Tools: Selenium, BeautifulSoup, regular expressions
• Jobs: DevOps engineer, automation specialist

Artificial Intelligence and Machine Learning

• Libraries: TensorFlow, PyTorch, Keras
• Applications: Computer vision, NLP, recommendation systems
• Jobs: ML engineer, AI researcher

Common Python Pitfalls to Avoid

1. Mutable Default Arguments: Can cause unexpected behavior
2. Not using list comprehensions: Less efficient than comprehensions
3. Global variables: Makes code harder to maintain
4. Not handling exceptions: Programs crash unexpectedly
5. Inefficient loops: Can cause performance issues with large datasets

Practice Exercises

1. Write a function to calculate factorial of a number
2. Create a class to represent a bank account with deposit/withdraw functionality
3. Read a CSV file and perform data analysis
4. Web scrape a website and store data in a database
5. Build a simple command-line game in Python

Resources for Further Learning

• Official Documentation: https://docs.python.org/
• Interactive Learning: Codecademy, DataCamp, Coursera
• Books: "Python Crash Course", "Fluent Python"
• YouTube Channels: CoreyMS, Tech With Tim, Programming with Mosh
• Practice Platforms: LeetCode, HackerRank, CodeSignal
• Decorators
• Generators
• Exception Handling
• File I/O

For more information and detailed explanations on Python concepts, refer to the study materials above.