Python Training , study and exam guide
1 Introduction to Python
1.1 What is Python?
1.2 History of Python
1.3 Features of Python
1.4 Python Applications
1.5 Setting up the Python Environment
1.6 Running Your First Python Program
2 Python Basics
2.1 Python Syntax and Indentation
2.2 Variables and Data Types
2.2 1 Numbers
2.2 2 Strings
2.2 3 Lists
2.2 4 Tuples
2.2 5 Sets
2.2 6 Dictionaries
2.3 Operators
2.3 1 Arithmetic Operators
2.3 2 Comparison Operators
2.3 3 Logical Operators
2.3 4 Assignment Operators
2.3 5 Membership Operators
2.3 6 Identity Operators
2.4 Input and Output
2.4 1 Input Function
2.4 2 Output Function
2.5 Comments
2.5 1 Single-line Comments
2.5 2 Multi-line Comments
3 Control Flow
3.1 Conditional Statements
3.1 1 If Statement
3.1 2 If-Else Statement
3.1 3 Elif Statement
3.1 4 Nested If Statements
3.2 Loops
3.2 1 For Loop
3.2 2 While Loop
3.2 3 Nested Loops
3.3 Loop Control Statements
3.3 1 Break Statement
3.3 2 Continue Statement
3.3 3 Pass Statement
4 Functions
4.1 Defining Functions
4.2 Function Arguments
4.2 1 Positional Arguments
4.2 2 Keyword Arguments
4.2 3 Default Arguments
4.2 4 Variable-length Arguments
4.3 Return Statement
4.4 Lambda Functions
4.5 Scope of Variables
4.5 1 Local Variables
4.5 2 Global Variables
4.6 Recursion
5 Data Structures
5.1 Lists
5.1 1 List Operations
5.1 2 List Methods
5.1 3 List Comprehensions
5.2 Tuples
5.2 1 Tuple Operations
5.2 2 Tuple Methods
5.3 Sets
5.3 1 Set Operations
5.3 2 Set Methods
5.4 Dictionaries
5.4 1 Dictionary Operations
5.4 2 Dictionary Methods
5.5 Advanced Data Structures
5.5 1 Stacks
5.5 2 Queues
5.5 3 Linked Lists
6 Modules and Packages
6.1 Importing Modules
6.2 Creating Modules
6.3 Standard Library Modules
6.3 1 Math Module
6.3 2 Random Module
6.3 3 DateTime Module
6.4 Creating Packages
6.5 Installing External Packages
7 File Handling
7.1 Opening and Closing Files
7.2 Reading from Files
7.2 1 read()
7.2 2 readline()
7.2 3 readlines()
7.3 Writing to Files
7.3 1 write()
7.3 2 writelines()
7.4 File Modes
7.5 Working with CSV Files
7.6 Working with JSON Files
8 Exception Handling
8.1 Try and Except Blocks
8.2 Handling Multiple Exceptions
8.3 Finally Block
8.4 Raising Exceptions
8.5 Custom Exceptions
9 Object-Oriented Programming (OOP)
9.1 Classes and Objects
9.2 Attributes and Methods
9.3 Constructors and Destructors
9.4 Inheritance
9.4 1 Single Inheritance
9.4 2 Multiple Inheritance
9.4 3 Multilevel Inheritance
9.5 Polymorphism
9.6 Encapsulation
9.7 Abstraction
10 Working with Libraries
10.1 NumPy
10.1 1 Introduction to NumPy
10.1 2 Creating NumPy Arrays
10.1 3 Array Operations
10.2 Pandas
10.2 1 Introduction to Pandas
10.2 2 DataFrames and Series
10.2 3 Data Manipulation
10.3 Matplotlib
10.3 1 Introduction to Matplotlib
10.3 2 Plotting Graphs
10.3 3 Customizing Plots
10.4 Scikit-learn
10.4 1 Introduction to Scikit-learn
10.4 2 Machine Learning Basics
10.4 3 Model Training and Evaluation
11 Web Development with Python
11.1 Introduction to Web Development
11.2 Flask Framework
11.2 1 Setting Up Flask
11.2 2 Routing
11.2 3 Templates
11.2 4 Forms and Validation
11.3 Django Framework
11.3 1 Setting Up Django
11.3 2 Models and Databases
11.3 3 Views and Templates
11.3 4 Forms and Authentication
12 Final Exam Preparation
12.1 Review of Key Concepts
12.2 Practice Questions
12.3 Mock Exams
12.4 Exam Tips and Strategies
4 6 Recursion Explained

4 6 Recursion Explained

Key Concepts

Recursion in Python is a technique where a function calls itself to solve a problem. The key concepts include:

1. Base Case

The base case is the condition that stops the recursion. It is essential to have a base case to prevent infinite recursion.

Example:

def factorial(n):
    if n == 0:
        return 1  # Base case
    else:
        return n * factorial(n - 1)  # Recursive case

print(factorial(5))  # Output: 120
    

2. Recursive Case

The recursive case is where the function calls itself with a modified argument, moving closer to the base case.

Example:

def fibonacci(n):
    if n <= 1:
        return n  # Base case
    else:
        return fibonacci(n - 1) + fibonacci(n - 2)  # Recursive case

print(fibonacci(6))  # Output: 8
    

3. Stack Overflow

Stack overflow occurs when the recursion depth exceeds the available memory, leading to a crash. It is crucial to ensure that the base case is reachable.

Example of a problematic recursive function:

def infinite_recursion(n):
    return infinite_recursion(n)  # No base case, leads to stack overflow

# Uncommenting the next line will cause a stack overflow
# infinite_recursion(1)
    

4. Practical Applications

Recursion is useful for solving problems that can be broken down into smaller, similar subproblems. Examples include tree traversal, sorting algorithms, and mathematical computations.

Example: Tree traversal using recursion

class Node:
    def __init__(self, value):
        self.value = value
        self.left = None
        self.right = None

def inorder_traversal(node):
    if node:
        inorder_traversal(node.left)
        print(node.value)
        inorder_traversal(node.right)

# Creating a simple binary tree
root = Node(1)
root.left = Node(2)
root.right = Node(3)
root.left.left = Node(4)
root.left.right = Node(5)

inorder_traversal(root)  # Output: 4 2 5 1 3
    

Putting It All Together

By understanding and using recursion effectively, you can solve complex problems in a structured and elegant manner. Ensure that your recursive functions have a clear base case to avoid stack overflow and make your code more robust.

Example: Recursive function to reverse a string

def reverse_string(s):
    if len(s) == 0:
        return s  # Base case
    else:
        return reverse_string(s[1:]) + s[0]  # Recursive case

print(reverse_string("hello"))  # Output: olleh