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PYTHON BASICS

Learn the fundamental syntax and structure of Python

Beginner

Module 1: Python Syntax and Structure

Python is a high-level, interpreted programming language known for its simplicity and readability. It uses indentation to define code blocks instead of braces, making it easy to read and write. Every Python program follows a basic structure that helps organize code logically.

Try It Yourself:

Python

# This is a comment in Python
print("Hello, World!")  # This prints text to the console

# Variables store data
name = "SkillMynte"
age = 25

# Print variables
print("Welcome to", name)
print("Python is", age, "years old!")

# Basic arithmetic
x = 10
y = 5
sum = x + y
print("The sum of", x, "and", y, "is", sum)

# Get user input
user_name = input("What's your name? ")
print("Hello, " + user_name + "! Welcome to Python programming!")

Code Output

Key Points:

print() function displays output to the console
Comments start with # and are ignored by Python
Variables are created when you assign a value (variable = value)
Python uses indentation (spaces/tabs) to define code blocks
input() function gets user input from the keyboard
Strings can be concatenated with + operator
Python supports basic arithmetic operations: +, -, *, /

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VARIABLES & DATA TYPES

Learn about Python's data types and variable handling

Beginner

Module 2: Variables and Data Types

Python has several built-in data types to store different kinds of information. The main types are integers, floats, strings, booleans, lists, tuples, dictionaries, and sets. Understanding these data types is essential for effective Python programming.

Try It Yourself:

Python

# Integer (whole numbers)
age = 25
year = 2023

# Float (decimal numbers)
price = 19.99
temperature = 36.6

# String (text)
name = "Alice"
message = 'Hello, World!'

# Boolean (True/False)
is_student = True
is_working = False

# List (ordered, mutable collection)
fruits = ["apple", "banana", "cherry"]
numbers = [1, 2, 3, 4, 5]

# Tuple (ordered, immutable collection)
coordinates = (10, 20)
colors = ("red", "green", "blue")

# Dictionary (key-value pairs)
person = {
    "name": "John",
    "age": 30,
    "city": "New York"
}

# Set (unordered, unique elements)
unique_numbers = {1, 2, 3, 4, 5}

# Displaying values
print("Integer:", age)
print("Float:", price)
print("String:", name)
print("Boolean:", is_student)
print("List:", fruits)
print("Tuple:", coordinates)
print("Dictionary:", person)
print("Set:", unique_numbers)

# Type checking
print("Type of age:", type(age))
print("Type of name:", type(name))
print("Type of is_student:", type(is_student))

Code Output

Key Points:

Integers: Whole numbers without decimals
Floats: Numbers with decimal points
Strings: Text enclosed in single or double quotes
Booleans: True or False values
Lists: Ordered, mutable collections (can be changed)
Tuples: Ordered, immutable collections (cannot be changed)
Dictionaries: Key-value pairs for storing related data
Sets: Unordered collections of unique elements
Use type() function to check the data type of a variable

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CONTROL STRUCTURES

Learn to control program flow with conditionals and loops

Beginner

Module 3: Conditionals and Loops

Control structures allow your program to make decisions and repeat actions. Python provides if, elif, and else statements for conditional execution, and for and while loops for repetition.

Try It Yourself:

Python

# If-elif-else statements
age = 18

if age < 13:
    print("You are a child")
elif age < 20:
    print("You are a teenager")
else:
    print("You are an adult")

# For loop with range
print("\nCounting from 1 to 5:")
for i in range(1, 6):
    print(i)

# For loop with list
fruits = ["apple", "banana", "cherry"]
print("\nMy favorite fruits:")
for fruit in fruits:
    print("I like", fruit)

# While loop
print("\nCountdown from 5:")
count = 5
while count > 0:
    print(count)
    count -= 1  # Same as count = count - 1
print("Blast off!")

# Nested control structures
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
print("\nEven numbers from 1 to 10:")
for num in numbers:
    if num % 2 == 0:  # Check if number is even
        print(num, "is even")

# Break and continue
print("\nNumbers 1-10, skipping 5 and stopping at 8:")
for i in range(1, 11):
    if i == 5:
        continue  # Skip the rest of this iteration
    if i == 9:
        break     # Exit the loop entirely
    print(i)

Code Output

Key Points:

if, elif, and else control conditional execution
Indentation defines which code belongs to each block
for loops iterate over sequences (lists, strings, ranges)
while loops repeat as long as a condition is true
range(start, stop, step) generates number sequences
break exits a loop immediately
continue skips the rest of the current iteration
Comparison operators: ==, !=, <, >, <=, >=
Logical operators: and, or, not

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FUNCTIONS & MODULES

Learn to organize code with functions and modules

Intermediate

Module 4: Functions and Modules

Functions allow you to group code into reusable blocks, while modules let you organize functions and variables into separate files. This makes your code more organized, readable, and maintainable.

Try It Yourself:

Python

# Basic function definition
def greet():
    print("Hello, welcome to Python functions!")

# Function with parameters
def greet_person(name):
    print("Hello, " + name + "!")

# Function with return value
def add_numbers(a, b):
    return a + b

# Function with default parameters
def create_greeting(name, greeting="Hello"):
    return greeting + ", " + name + "!"

# Function with multiple return values
def calculate_rectangle(length, width):
    area = length * width
    perimeter = 2 * (length + width)
    return area, perimeter

# Calling functions
greet()
greet_person("Alice")
greet_person("Bob")

result = add_numbers(5, 3)
print("5 + 3 =", result)

print(create_greeting("Charlie"))
print(create_greeting("Diana", "Hi"))

area, perimeter = calculate_rectangle(4, 5)
print("Rectangle area:", area, "perimeter:", perimeter)

# Using built-in modules
import math
import random
import datetime

print("\nMath functions:")
print("Square root of 16:", math.sqrt(16))
print("Pi:", math.pi)

print("\nRandom numbers:")
print("Random integer:", random.randint(1, 10))
print("Random choice:", random.choice(["apple", "banana", "cherry"]))

print("\nDate and time:")
now = datetime.datetime.now()
print("Current date and time:", now)
print("Formatted date:", now.strftime("%Y-%m-%d %H:%M:%S"))

Code Output

Key Points:

Use def keyword to define functions
Functions can accept parameters (inputs) and return values
Parameters can have default values for optional arguments
Functions can return multiple values as tuples
Use import to include built-in or custom modules
Python has a rich standard library with useful modules
math module provides mathematical functions
random module generates random numbers
datetime module handles dates and times
Organize code into functions for reusability and clarity

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DATA STRUCTURES

Learn to work with Python's advanced data structures

Intermediate

Module 5: Advanced Data Structures

Python provides powerful built-in data structures for organizing and manipulating data efficiently. Understanding how to work with lists, dictionaries, tuples, and sets is crucial for effective Python programming.

Try It Yourself:

Python

# List operations
fruits = ["apple", "banana", "cherry"]
print("Original list:", fruits)

# Adding elements
fruits.append("orange")
fruits.insert(1, "blueberry")
print("After adding:", fruits)

# Removing elements
fruits.remove("banana")
popped = fruits.pop()
print("After removal:", fruits)
print("Popped element:", popped)

# List slicing
numbers = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
print("First 3:", numbers[:3])
print("Last 3:", numbers[-3:])
print("Middle:", numbers[3:7])
print("Every second:", numbers[::2])

# List comprehension (powerful feature!)
squares = [x**2 for x in range(1, 6)]
print("Squares:", squares)

even_squares = [x**2 for x in range(1, 11) if x % 2 == 0]
print("Even squares:", even_squares)

# Dictionary operations
student = {
    "name": "Alice",
    "age": 20,
    "major": "Computer Science",
    "grades": [85, 92, 78, 90]
}

print("\nStudent dictionary:")
print("Name:", student["name"])
print("Age:", student.get("age"))

# Adding/updating dictionary
student["year"] = "Junior"
student["age"] = 21
print("Updated student:", student)

# Dictionary iteration
print("\nStudent details:")
for key, value in student.items():
    print(f"{key}: {value}")

# Set operations
set_a = {1, 2, 3, 4, 5}
set_b = {4, 5, 6, 7, 8}

print("\nSet A:", set_a)
print("Set B:", set_b)
print("Union:", set_a | set_b)
print("Intersection:", set_a & set_b)
print("Difference (A-B):", set_a - set_b)
print("Symmetric Difference:", set_a ^ set_b)

Code Output

Key Points:

Lists are ordered, mutable collections with various methods
List slicing allows accessing subsets: list[start:stop:step]
List comprehensions provide concise way to create lists
Dictionaries store key-value pairs for fast lookups
Use dict.get(key) to safely access values
Sets store unique elements and support mathematical operations
Tuples are immutable sequences, often used for fixed data
Each data structure has specific use cases and performance characteristics
Choose the right structure based on your data access patterns

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OBJECT-ORIENTED PROGRAMMING

Learn Python's object-oriented programming concepts

Intermediate

Module 6: Object-Oriented Programming in Python

Object-Oriented Programming (OOP) is a programming paradigm that uses objects and classes to organize code. Python supports OOP concepts like classes, objects, inheritance, encapsulation, and polymorphism, making it powerful for building complex applications.

Try It Yourself:

Python

# Basic class definition
class Dog:
    # Class attribute (shared by all instances)
    species = "Canis familiaris"
    
    # Initializer (constructor)
    def __init__(self, name, age):
        # Instance attributes (unique to each instance)
        self.name = name
        self.age = age
    
    # Instance method
    def description(self):
        return f"{self.name} is {self.age} years old"
    
    # Another instance method
    def speak(self, sound):
        return f"{self.name} says {sound}"

# Creating instances (objects)
dog1 = Dog("Buddy", 5)
dog2 = Dog("Milo", 3)

print(dog1.description())
print(dog2.description())
print(dog1.speak("Woof Woof!"))
print(dog2.speak("Bark Bark!"))

print(f"Both dogs are {Dog.species}")

# Inheritance example
class Bulldog(Dog):  # Bulldog inherits from Dog
    def run(self, speed="slowly"):
        return f"{self.name} runs {speed}"

class Dachshund(Dog):
    def dig(self):
        return f"{self.name} digs a hole"

# Creating instances of child classes
bulldog = Bulldog("Spike", 4)
dachshund = Dachshund("Wiener", 2)

print(bulldog.description())
print(bulldog.run())
print(dachshund.description())
print(dachshund.dig())

# Polymorphism example
def animal_sound(animal):
    print(animal.speak("Some sound"))

animal_sound(dog1)
animal_sound(bulldog)
animal_sound(dachshund)

# Encapsulation with private attributes
class BankAccount:
    def __init__(self, owner, balance=0):
        self.owner = owner
        self._balance = balance  # Protected attribute
        self.__account_id = 12345  # Private attribute
    
    def deposit(self, amount):
        self._balance += amount
        return f"Deposited ${amount}. New balance: ${self._balance}"
    
    def withdraw(self, amount):
        if amount <= self._balance:
            self._balance -= amount
            return f"Withdrew ${amount}. New balance: ${self._balance}"
        else:
            return "Insufficient funds"
    
    def get_balance(self):
        return self._balance

# Using the BankAccount class
account = BankAccount("Alice", 1000)
print(account.deposit(500))
print(account.withdraw(200))
print(account.withdraw(2000))  # Should show insufficient funds
print(f"Current balance: ${account.get_balance()}")

Code Output

Key Points:

Classes are blueprints for creating objects
Objects are instances of classes with their own attributes
__init__ method is the constructor that initializes objects
self refers to the current instance of the class
Inheritance allows creating new classes based on existing ones
Polymorphism enables using a common interface for different types
Encapsulation hides internal implementation details
Single underscore _attribute indicates protected attributes
Double underscore __attribute indicates private attributes
OOP makes code more modular, reusable, and maintainable

PRACTICE PLAYGROUND

Experiment with what you've learned

Your Coding Playground: Try Your Own Python Code

Use this space to experiment with everything you've learned. Try combining different Python concepts and see the results in real-time! This is your sandbox to practice and explore.

Python

# Your Python code here
print("Welcome to Your Python Playground!")
print("=" * 40)

# Try creating a simple calculator
def calculator():
    print("\nSimple Calculator")
    print("1. Add")
    print("2. Subtract")
    print("3. Multiply")
    print("4. Divide")
    
    choice = input("Enter choice (1/2/3/4): ")
    num1 = float(input("Enter first number: "))
    num2 = float(input("Enter second number: "))
    
    if choice == '1':
        result = num1 + num2
        print(f"{num1} + {num2} = {result}")
    elif choice == '2':
        result = num1 - num2
        print(f"{num1} - {num2} = {result}")
    elif choice == '3':
        result = num1 * num2
        print(f"{num1} Ã— {num2} = {result}")
    elif choice == '4':
        if num2 != 0:
            result = num1 / num2
            print(f"{num1} Ã· {num2} = {result}")
        else:
            print("Error: Division by zero!")
    else:
        print("Invalid input")

# Try working with lists and loops
fruits = ["apple", "banana", "cherry", "date", "elderberry"]
print("\nFavorite fruits:")
for i, fruit in enumerate(fruits, 1):
    print(f"{i}. {fruit}")

# Try dictionary operations
student = {
    "name": "Alex",
    "age": 22,
    "courses": ["Math", "Science", "History"]
}

print("\nStudent Information:")
for key, value in student.items():
    print(f"{key.capitalize()}: {value}")

# Try a simple class
class Car:
    def __init__(self, brand, model, year):
        self.brand = brand
        self.model = model
        self.year = year
    
    def display_info(self):
        return f"{self.year} {self.brand} {self.model}"

my_car = Car("Toyota", "Camry", 2022)
print(f"\nMy car: {my_car.display_info()}")

print("\nHappy coding! Try modifying this code or writing your own!")

Code Output

Challenge Exercises:

Create a program that:
- Asks for user's name and age
- Calculates the year they were born
- Prints a personalized message
Build a number guessing game where:
- The computer picks a random number
- The user tries to guess it
- Provide hints (too high/too low)
- Count the number of attempts
Create a simple inventory system with:
- A dictionary to store items and quantities
- Functions to add, remove, and display items
- Ability to search for specific items
Design a Student class with:
- Attributes: name, age, grades
- Methods to calculate average grade
- Method to display student information
Combine all concepts into a complete application

Tips & Resources:

Use meaningful variable names for better readability
Test your code frequently with small changes
Use print statements to debug and understand program flow
Practice with Python's built-in functions:
- len(), type(), str(), int(), float()
- range(), enumerate(), zip()
- max(), min(), sum(), sorted()
For more practice, try solving coding challenges on platforms like HackerRank or LeetCode

PYTHON BASICS

Learn the fundamental syntax and structure of Python

Module 1: Python Syntax and Structure

Try It Yourself:

Key Points:

VARIABLES & DATA TYPES

Learn about Python's data types and variable handling

Module 2: Variables and Data Types

Try It Yourself:

Key Points:

CONTROL STRUCTURES

Learn to control program flow with conditionals and loops

Module 3: Conditionals and Loops

Try It Yourself:

Key Points:

FUNCTIONS & MODULES

Learn to organize code with functions and modules

Module 4: Functions and Modules

Try It Yourself:

Key Points:

DATA STRUCTURES

Learn to work with Python's advanced data structures

Module 5: Advanced Data Structures

Try It Yourself:

Key Points:

OBJECT-ORIENTED PROGRAMMING

Learn Python's object-oriented programming concepts

Module 6: Object-Oriented Programming in Python

Try It Yourself:

Key Points:

PRACTICE PLAYGROUND

Experiment with what you've learned

Your Coding Playground: Try Your Own Python Code

Challenge Exercises:

Tips & Resources:

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