Python Programming
Table of content:
- What Is Python? An Introduction
- What Is The History Of Python?
- Key Features Of The Python Programming Language
- Who Uses Python?
- Basic Characteristics Of Python Programming Syntax
- Why Should You Learn Python?
- Applications Of Python Language
- Advantages And Disadvantages Of Python
- Some Useful Python Tips & Tricks For Efficient Programming
- Python 2 Vs. Python 3: Which Should You Learn?
- Python Libraries
- Conclusion
- Frequently Asked Questions
Table of content:
- Python At A Glance
- Key Features of Python Programming
- Applications of Python
- Bonus: Interesting features of different programming languages
- Summing up...
- FAQs regarding Python
Table of content:
- What Is Python IDLE?
- What Is Python Shell & Its Uses?
- Primary Features Of Python IDLE
- How To Use Python IDLE Shell? Setting Up Your Python Environment
- How To Work With Files In Python IDLE?
- How To Execute A File In Python IDLE?
- Improving Workflow In Python IDLE Software
- Debugging In Python IDLE
- Customizing Python IDLE
- Code Examples
- Conclusion
- Frequently Asked Questions (FAQs)
Table of content:
- What Is A Variable In Python?
- Creating And Declaring Python Variables
- Rules For Naming Python Variables
- How To Print Python Variables?
- How To Delete A Python Variable?
- Various Methods Of Variables Assignment In Python
- Python Variable Types
- Python Variable Scope
- Concatenating Python Variables
- Object Identity & Object References Of Python Variables
- Reserved Words/ Keywords & Python Variable Names
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is A String In Python?
- Creating String In Python
- How To Create Multiline Python Strings?
- Reassigning Python Strings
- Accessing Characters Of Python Strings
- How To Update Or Delete A Python String?
- Reversing A Python String
- Formatting Python Strings
- Concatenation & Comparison Of Python Strings
- Python String Operators
- Python String Functions
- Escape Sequences In Python Strings
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is Python Namespace?
- Lifetime Of Python Namespace
- Types Of Python Namespace
- The Built-In Namespace In Python
- The Global Namespace In Python
- The Local Namespace In Python
- The Enclosing Namespace In Python
- Variable Scope & Namespace In Python
- Python Namespace Dictionaries
- Changing Variables Out Of Their Scope & Python Namespace
- Best Practices Of Python Namespace
- Conclusion
- Frequently Asked Questions
Table of content:
- What Are Relational Operators In Python?
- Type Of Relational Operators In Python
- Equal-To Relational Operator In Python
- Greater Than Relational Operator In Python
- Less-Than Relational Operator In Python
- Not Equal-To Relational Operator In Python
- Greater-Than Or Equal-To Relational Operator In Python
- Less-Than Or Equal-To Relational Operator In Python
- Why And When To Use Relational Operators?
- Precedence & Associativity Of Relational Operators In Python
- Advantages & Disadvantages Of Relational Operators In Python
- Real-World Applications Of Relational Operators In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- What Are Logical Operators In Python?
- The AND Python Logical Operator
- The OR Python Logical Operator
- The NOT Python Logical Operator
- Short-Circuiting Evaluation Of Python Logical Operators
- Precedence of Logical Operators In Python
- How Does Python Calculate Truth Value?
- Final Note On How AND & OR Python Logical Operators Work
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is The Print() Function In Python?
- How Does The print() Function Work In Python?
- How To Print Single & Multi-line Strings In Python?
- How To Print Built-in Data Types In Python?
- Print() Function In Python For Values Stored In Variables
- Print() Function In Python With sep Parameter
- Print() Function In Python With end Parameter
- Print() Function In Python With flush Parameter
- Print() Function In Python With file Parameter
- How To Remove Newline From print() Function In Python?
- Use Cases Of The print() Function In Python
- Understanding Print Statement In Python 2 Vs. Python 3
- Conclusion
- Frequently Asked Questions
Table of content:
- Working Of Normal Print() Function
- The New Line Character In Python
- How To Print Without Newline In Python | Using The End Parameter
- How To Print Without Newline In Python 2.x? | Using Comma Operator
- How To Print Without Newline In Python 3.x?
- How To Print Without Newline In Python With Module Sys
- The Star Pattern(*) | How To Print Without Newline & Space In Python
- How To Print A List Without Newline In Python?
- How To Remove New Lines In Python?
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is A Python For Loop?
- How Does Python For Loop Work?
- When & Why To Use Python For Loops?
- Python For Loop Examples
- What Is Rrange() Function In Python?
- Nested For Loops In Python
- Python For Loop With Continue & Break Statements
- Python For Loop With Pass Statement
- Else Statement In Python For Loop
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is Python While Loop?
- How Does The Python While Loop Work?
- How To Use Python While Loops For Iterations?
- Control Statements In Python While Loop With Examples
- Python While Loop With Python List
- Infinite Python While Loop in Python
- Python While Loop Multiple Conditions
- Nested Python While Loops
- Conclusion
- Frequently Asked Questions
Table of content:
- What Are Conditional If-Else Statements In Python?
- Types Of If-Else Statements In Python
- If Statement In Python
- If-Else Statement In Python
- Nested If-Else Statement In Python
- Elif Statement In Python
- Ladder If-Elif-Else Statement In Python
- Short Hand If-Statement In Python
- Short Hand If-Else Statement In Python
- Operators & If-Esle Statement In Python
- Other Statements With If-Else In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is Control Structure In Python?
- Types Of Control Structures In Python
- Sequential Control Structures In Python
- Decision-Making Control Structures In Python
- Repetition Control Structures In Python
- Benefits Of Using Control Structures In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- What Are Python Libraries?
- How Do Python Libraries Work?
- Standard Python Libraries (With List)
- Important Python Libraries For Data Science
- Important Python Libraries For Machine & Deep Learning
- Other Important Python Libraries You Must Know
- Working With Third-Party Python Libraries
- Troubleshooting Common Issues with Python Libraries
- Python Libraries In Larger Projects
- Importance Of Python Libraries
- Conclusion
- Frequently Asked Questions
Table of content:
- What Are Python Functions?
- How To Create/ Define Functions In Python?
- How To Call A Python Function?
- Types Of Python Functions Based On Parameters & Return Statement
- Rules & Best Practices For Naming Python Functions
- Basic Types of Python Functions
- The Return Statement In Python Functions
- Types Of Arguments In Python Functions
- Docstring In Python Functions
- Passing Parameters In Python Functions
- Python Function Variables | Scope & Lifetime
- Advantages Of Using Python Functions
- Recursive Python Function
- Anonymous/ Lambda Function In Python
- Nested Functions In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- What Are Python Built-In Functions?
- Mathematical Python Built-In Functions
- Python Built-In Functions For Strings
- Input/ Output Built-In Functions In Python
- List & Tuple Python Built-In Functions
- File Handling Python Built-In Functions
- Python Built-In Functions For Dictionary
- Type Conversion Python Built-In Functions
- Basic Python Built-In Functions
- List Of Python Built-In Functions (Alphabetical)
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is A round() Function In Python?
- How Does Python round() Function Work?
- Python round() Function If The Second Parameter Is Missing
- Python round() Function If The Second Parameter Is Present
- Python round() Function With Negative Integers
- Python round() Function With Math Library
- Python round() Function With Numpy Module
- Round Up And Round Down Numbers In Python
- Truncation Vs Rounding In Python
- Practical Applications Of Python round() Function
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is Python pow() Function?
- Python pow() Function Example
- Python pow() Function With Modulus (Three Parameters)
- Python pow() Function With Complex Numbers
- Python pow() Function With Floating-Point Arguments And Modulus
- Python pow() Function Implementation Cases
- Difference Between Inbuilt-pow() And math.pow() Function
- Conclusion
- Frequently Asked Questions
Table of content:
- Python max() Function With Objects
- Examples Of Python max() Function With Objects
- Python max() Function With Iterable
- Examples Of Python max() Function With Iterables
- Potential Errors With The Python max() Function
- Python max() Function Vs. Python min() Functions
- Conclusion
- Frequently Asked Questions
Table of content:
- What Are Strings In Python?
- What Are Python String Methods?
- List Of Python String Methods For Manipulating Case
- List Of Python String Methods For Searching & Finding
- List Of Python String Methods For Modifying & Transforming
- List Of Python String Methods For Checking Conditions
- List Of Python String Methods For Encoding & Decoding
- List Of Python String Methods For Stripping & Trimming
- List Of Python String Methods For Formatting
- Miscellaneous Python String Methods
- List Of Other Python String Operations
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is Python String?
- The Need For Python String Replacement
- The Python String replace() Method
- Multiple Replacements With Python String.replace() Method
- Replace A Character In String Using For Loop In Python
- Python String Replacement Using Slicing Method
- Replace A Character At a Given Position In Python String
- Replace Multiple Substrings With The Same String In Python
- Python String Replacement Using Regex Pattern
- Python String Replacement Using List Comprehension & Join() Method
- Python String Replacement Using Callback With re.sub() Method
- Python String Replacement With re.subn() Method
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is String Slicing In Python?
- How Indexing & String Slicing Works In Python
- Extracting All Characters Using String Slicing In Python
- Extracting Characters Before & After Specific Position Using String Slicing In Python
- Extracting Characters Between Two Intervals Using String Slicing In Python
- Extracting Characters At Specific Intervals (Step) Using String Slicing In Python
- Negative Indexing & String Slicing In Python
- Handling Out-of-Bounds Indices In String Slicing In Python
- The slice() Method For String Slicing In Python
- Common Pitfalls Of String Slicing In Python
- Real-World Applications Of String Slicing
- Conclusion
- Frequently Asked Questions
Table of content:
- Introduction To Python List
- How To Create A Python List?
- How To Access Elements Of Python List?
- Accessing Multiple Elements From A Python List (Slicing)
- Access List Elements From Nested Python Lists
- How To Change Elements In Python Lists?
- How To Add Elements To Python Lists?
- Delete/ Remove Elements From Python Lists
- How To Create Copies Of Python Lists?
- Repeating Python Lists
- Ways To Iterate Over Python Lists
- How To Reverse A Python List?
- How To Sort Items Of Python Lists?
- Built-in Functions For Operations On Python Lists
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is List Comprehension In Python?
- Incorporating Conditional Statements With List Comprehension In Python
- List Comprehension In Python With range()
- Filtering Lists Effectively With List Comprehension In Python
- Nested Loops With List Comprehension In Python
- Flattening Nested Lists With List Comprehension In Python
- Handling Exceptions In List Comprehension In Python
- Common Use Cases For List Comprehensions
- Advantages & Disadvantages Of List Comprehension In Python
- Best Practices For Using List Comprehension In Python
- Performance Considerations For List Comprehension In Python
- For Loops & List Comprehension In Python: A Comparison
- Difference Between Generator Expression & List Comprehension In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is A List In Python?
- How To Find Length Of List In Python?
- For Loop To Get Python List Length (Naive Approach)
- The len() Function To Get Length Of List In Python
- The length_hint() Function To Find Length Of List In Python
- The sum() Function To Find The Length Of List In Python
- The enumerate() Function To Find Python List Length
- The Counter Class From collections To Find Python List Length
- The List Comprehension To Find Python List Length
- Find The Length Of List In Python Using Recursion
- Comparison Between Ways To Find Python List Length
- Conclusion
- Frequently Asked Questions
Table of content:
- List of Methods To Reverse A Python List
- Python Reverse List Using reverse() Method
- Python Reverse List Using the Slice Operator ([::-1])
- Python Reverse List By Swapping Elements
- Python Reverse List Using The reversed() Function
- Python Reverse List Using A for Loop
- Python Reverse List Using While Loop
- Python Reverse List Using List Comprehension
- Python Reverse List Using List Indexing
- Python Reverse List Using The range() Function
- Python Reverse List Using NumPy
- Comparison Of Ways To Reverse A Python List
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is Indexing In Python?
- The Python List index() Function
- How To Use Python List index() To Find Index Of A List Element
- The Python List index() Method With Single Parameter (Start)
- The Python List index() Method With Start & Stop Parameters
- What Happens When We Use Python List index() For An Element That Doesn't Exist
- Python List index() With Nested Lists
- Fixing IndexError Using The Python List index() Method
- Python List index() With Enumerate()
- Real-world Examples Of Python List index() Method
- Difference Between find() And index() Method In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- How To Remove Elements From List In Python?
- The remove() Method To Remove Element From Python List
- The pop() Method To Remove Element From List In Python
- The del Keyword To Remove Element From List In Python
- The clear() Method To Remove Elements From Python List
- List Comprehensions To Conditionally Remove Element From List In Python
- Key Considerations For Removing Elements From Python Lists
- Why We Need to Remove Elements From Python List
- Performance Comparison Of Methods To Remove Element From List In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- How To Remove Duplicates From A List In Python?
- The set() Function To Remove Duplicates From Python List
- Remove Duplicates From Python List Using For Loop
- Using List Comprehension Remove Duplicates From Python List
- Remove Duplicates From Python List Using enumerate() With List Comprehension
- Dictionary & fromkeys() Method To Remove Duplicates From Python List
- Remove Duplicates From Python List Using in, not in Operators
- Remove Duplicates From Python List Using collections.OrderedDict.fromkeys()
- Remove Duplicates From Python List Using Counter with freq.dist() Method
- The del Keyword Remove Duplicates From Python List
- Remove Duplicates From Python List Using DataFrame
- Remove Duplicates From Python List Using pd.unique and np.unipue
- Remove Duplicates From Python List Using reduce() function
- Comparative Analysis Of Ways To Remove Duplicates From Python List
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is Python List & How To Access Elements?
- What Is IndexError: List Index Out Of Range & Its Causes In Python?
- Understanding Indexing Behavior In Python Lists
- How to Prevent/ Fix IndexError: List Index Out Of Range In Python
- Handling IndexError Gracefully Using Try-Except
- Debugging Tips For IndexError: List Index Out Of Range Python
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is the Python sort() List Method?
- Sorting In Ascending Order Using The Python sort() List Method
- How To Sort Items In Descending Order Using Python sort() List Method
- Custom Sorting Using The Key Parameter Of Python sort() List Method
- Examples Of Python sort() List Method
- What Is The sorted() List Method In Python
- Differences Between sorted() And sort() List Methods In Python
- When To Use sorted() & When To Use sort() List Method In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is A List In Python?
- What Is A String In Python?
- Why Convert Python List To String?
- How To Convert List To String In Python?
- The join() Method To Convert Python List To String
- Convert Python List To String Through Iteration
- Convert Python List To String With List Comprehension
- The map() Function To Convert Python List To String
- Convert Python List to String Using format() Function
- Convert Python List To String Using Recursion
- Enumeration Function To Convert Python List To String
- Convert Python List To String Using Operator Module
- Python Program To Convert String To List
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is The Python List append() Method?
- Adding Elements To A Python List Using append()
- Populate A Python List Using append()
- Adding Different Data Types To Python List Using append()
- Adding A List To Python List Using append()
- Nested Lists With Python List append() Method
- Practical Use Cases Of Python List append() Method
- How append() Method Affects List Performance
- Avoiding Common Mistakes When Using Python List append()
- Comparing extend() With append() Python List Method
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is A Linked List In Python?
- Types Of Linked Lists In Python
- How To Create A Linked List In Python
- How To Traverse A Linked List In Python & Retrieve Elements
- Inserting Elements In A Linked List In Python
- Deleting Elements From A Linked List In Python
- Update A Node Of Linked List In Python
- Reversing A Linked List In Python
- Calculating Length Of A Linked List In Python
- Comparing Arrays And Linked Lists In Python
- Advantages & Disadvantages Of Linked List In Python
- When To Use Linked Lists Over Other Data Structures
- Practical Applications Of Linked Lists In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is Extend In Python?
- Extend In Python With List
- Extend In Python With String
- Extend In Python With Tuple
- Extend In Python With Set
- Extend In Python With Dictionary
- Other Methods To Extend A List In Python
- Difference Between append() and extend() In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is Recursion In Python?
- Key Components Of Recursive Functions In Python
- Implementing Recursion In Python
- Recursion Vs. Iteration In Python
- Tail Recursion In Python
- Infinite Recursion In Python
- Advantages Of Recursion In Python
- Disadvantages Of Recursion In Python
- Best Practices For Using Recursion In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is Type Conversion In Python?
- Types Of Type Conversion In Python
- Implicit Type Conversion In Python
- Explicit Type Conversion In Python
- Functions Used For Explicit Data Type Conversion In Python
- Important Type Conversion Tips In Python
- Benefits Of Type Conversion In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is Scope In Python?
- Local Scope In Python
- Global Scope In Python
- Nonlocal (Enclosing) Scope In Python
- Built-In Scope In Python
- The LEGB Rule For Python Scope
- Python Scope And Variable Lifetime
- Best Practices For Managing Python Scope
- Conclusion
- Frequently Asked Questions
Table of content:
- Understanding The Continue Statement In Python
- How Does Continue Statement Work In Python?
- Python Continue Statement With For Loops
- Python Continue Statement With While Loops
- Python Continue Statement With Nested Loops
- Python Continue With If-Else Statement
- Difference Between Pass and Continue Statement In Python
- Practical Applications Of Continue Statement In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- What Are Control Statements In Python?
- Types Of Control Statements In Python
- Conditional Control Statements In Python
- Loop Control Statements In Python
- Control Flow Altering Statements In Python
- Exception Handling Control Statements In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- Understanding Python Flow Control
- Break Statement In Python
- Examples Of Break Statements In Python
- Continue Statement In Python
- Examples Of Continue Statements In Python
- Using Break and Continue Statements In A Single Program
- Difference Between Break And Continue Statements In Python
- When To Use Which Statement In Python?
- Conclusion
- Frequently Asked Questions
Table of content:
- Difference Between Mutable And Immutable Data Types in Python
- What Is Mutable Data Type In Python?
- Types Of Mutable Data Types In Python
- What Are Immutable Data Types In Python?
- Types Of Immutable Data Types In Python
- Key Similarities Between Mutable And Immutable Data Types In Python
- When To Use Mutable Vs Immutable In Python?
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is A List?
- What Is A Tuple?
- Difference Between List And Tuple In Python (Comparison Table)
- Syntax Difference Between List And Tuple In Python
- Mutability Difference Between List And Tuple In Python
- Other Difference Between List And Tuple In Python
- List Vs. Tuple In Python | Methods
- When To Use Tuples Over Lists?
- Key Similarities Between Tuples And Lists In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is Inheritance In Python?
- Python Inheritance Syntax
- Parent Class In Python Inheritance
- Child Class In Python Inheritance
- The __init__() Method In Python Inheritance
- The super() Function In Python Inheritance
- Method Overriding In Python Inheritance
- Types Of Inheritance In Python
- Special Functions In Python Inheritance
- Advantages & Disadvantages Of Inheritance In Python
- Common Use Cases For Inheritance In Python
- Best Practices for Implementing Inheritance in Python
- Avoiding Common Pitfalls in Python Inheritance
- Conclusion
- Frequently Asked Questions
Table of content:
- Introduction to Python
- Downloading & Installing Python, IDLE, Tkinter, NumPy & PyGame
- Creating A New Python Project
- How To Write Python Hello World Program In Python?
- Way To Write The Hello, World! Program In Python
- The Hello, World! Program In Python Using Class
- The Hello, World! Program In Python Using Function
- Print Hello World 5 Times Using A For Loop
- Conclusion
- Frequently Asked Questions
Table of content:
- Algorithm Of Python Program To Add To Numbers
- Standard Program To Add Two Numbers In Python
- Python Program To Add Two Numbers With User-defined Input
- The add() Method In Python Program To Add Two Numbers
- Python Program To Add Two Numbers Using Lambda
- Python Program To Add Two Numbers Using Function
- Python Program To Add Two Numbers Using Recursion
- Python Program To Add Two Numbers Using Class
- How To Add Multiple Numbers In Python?
- Add Multiple Numbers In Python With User Input
- Time Complexities Of Python Programs To Add Two Numbers
- Conclusion
- Frequently Asked Questions
Table of content:
- Swapping in Python
- Swapping Two Variables Using A Temporary Variable
- Swapping Two Variables Using The Comma Operator In Python
- Swapping Two Variables Using The Arithmetic Operators (+,-)
- Swapping Two Variables Using The Arithmetic Operators (*,/)
- Swapping Two Variables Using The XOR(^) Operator
- Swapping Two Variables Using Bitwise Addition and Subtraction
- Swap Variables In A List
- Conclusion
- Frequently Asked Questions (FAQs)
Table of content:
- What Is A Quadratic Equation? How To Solve It?
- How To Write A Python Program To Solve Quadratic Equations?
- Python Program To Solve Quadratic Equations Directly Using The Formula
- Python Program To Solve Quadratic Equations Using The Complex Math Module
- Python Program To Solve Quadratic Equations Using Functions
- Python Program To Solve Quadratic Equations & Find Number Of Solutions
- Python Program To Plot Quadratic Functions
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is Decimal Number System?
- What Is Binary Number System?
- What Is Octal Number System?
- What Is Hexadecimal Number System?
- Python Program to Convert Decimal to Binary, Octal, And Hexadecimal Using Built-In Function
- Python Program To Convert Decimal To Binary Using Recursion
- Python Program To Convert Decimal To Octal Using Recursion
- Python Program To Convert Decimal To Hexadecimal Using Recursion
- Python Program To Convert Decimal To Binary Using While Loop
- Python Program To Convert Decimal To Octal Using While Loop
- Python Program To Convert Decimal To Hexadecimal Using While Loop
- Convert Decimal To Binary, Octal, And Hexadecimal Using String Formatting
- Python Program To Convert Binary, Octal, And Hexadecimal String To A Number
- Complexity Comparison Of Python Programs To Convert Decimal To Binary, Octal, And Hexadecimal
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is A Square Root?
- Python Program To Find The Square Root Of A Number
- The pow() Function In Python Program To Find The Square Root Of Given Number
- Python Program To Find Square Root Using The sqrt() Function
- The cmath Module & Python Program To Find The Square Root Of A Number
- Python Program To Find Square Root Using The Exponent Operator (**)
- Python Program To Find Square Root With A User-Defined Function
- Python Program To Find Square Root Using A Class
- Python Program To Find Square Root Using Binary Search
- Python Program To Find Square Root Using NumPy Module
- Conclusion
- Frequently Asked Questions
Table of content:
- Understanding the Logic Behind the Conversion of Kilometers to Miles
- Steps To Write Python Program To Convert Kilometers To Miles
- Python Program To Convert Kilometer To Miles Without Function
- Python Program To Convert Kilometer To Miles Using Function
- Python Program to Convert Kilometer To Miles Using Class
- Tips For Writing Python Program To Convert Kilometer To Miles
- Conclusion
- Frequently Asked Questions
Table of content:
- Why Build A Calculator Program In Python?
- Prerequisites To Writing A Calculator Program In Python
- Approach For Writing A Calculator Program In Python
- Simple Calculator Program In Python
- Calculator Program In Python Using Functions
- Creating GUI Calculator Program In Python Using Tkinter
- Conclusion
- Frequently Asked Questions
Table of content:
- The Calendar Module In Python
- Prerequisites For Writing A Calendar Program In Python
- How To Write And Print A Calendar Program In Python
- Calendar Program In Python To Display A Month
- Calendar Program In Python To Display A Year
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is The Fibonacci Series?
- Pseudocode Code For Fibonacci Series Program In Python
- Generating Fibonacci Series In Python Using Naive Approach (While Loop)
- Fibonacci Series Program In Python Using The Direct Formula
- How To Generate Fibonacci Series In Python Using Recursion?
- Generating Fibonacci Series In Python With Dynamic Programming
- Fibonacci Series Program In Python Using For Loop
- Generating Fibonacci Series In Python Using If-Else Statement
- Generating Fibonacci Series In Python Using Arrays
- Generating Fibonacci Series In Python Using Cache
- Generating Fibonacci Series In Python Using Backtracking
- Fibonacci Series In Python Using Power Of Matix
- Complexity Analysis For Fibonacci Series Programs In Python
- Applications Of Fibonacci Series In Python & Programming
- Conclusion
- Frequently Asked Questions
Table of content:
- Different Ways To Write Random Number Generator Python Programs
- Random Module To Write Random Number Generator Python Programs
- The Numpy Module To Write Random Number Generator Python Programs
- The Secrets Module To Write Random Number Generator Python Programs
- Understanding Randomness and Pseudo-Randomness In Python
- Common Issues and Solutions in Random Number Generation
- Applications of Random Number Generator Python
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is A Factorial?
- Algorithm Of Program To Find Factorial Of A Number In Python
- Pseudocode For Factorial Program in Python
- Factorial Program In Python Using For Loop
- Factorial Program In Python Using Recursion
- Factorial Program In Python Using While Loop
- Factorial Program In Python Using If-Else Statement
- The math Module | Factorial Program In Python Using Built-In Factorial() Function
- Python Program to Find Factorial of a Number Using Ternary Operator(One Line Solution)
- Python Program For Factorial Using Prime Factorization Method
- NumPy Module | Factorial Program In Python Using numpy.prod() Function
- Complexity Analysis Of Factorial Programs In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- What Is Palindrome In Python?
- Check Palindrome In Python Using While Loop (Iterative Approach)
- Check Palindrome In Python Using For Loop And Character Matching
- Check Palindrome In Python Using The Reverse And Compare Method (Python Slicing)
- Check Palindrome In Python Using The In-built reversed() And join() Methods
- Check Palindrome In Python Using Recursion Method
- Check Palindrome In Python Using Flag
- Check Palindrome In Python Using One Extra Variable
- Check Palindrome In Python By Building Reverse, One Character At A Time
- Complexity Analysis For Palindrome Programs In Python
- Real-World Applications Of Palindrome In Python
- Conclusion
- Frequently Asked Questions
Table of content:
- Best Python Books For Beginners
- Best Python Books For Intermediate Level
- Best Python Books For Experts
- Best Python Books To Learn Algorithms
- Audiobooks of Python
- Best Books To Learn Python And Code Like A Pro
- To Learn Python Libraries
- Books To Provide Extra Edge In Python
- Python Project Ideas - Reference
Python Inheritance | Components, Usage & Types (+Code Examples)
Inheritance is a cornerstone of object-oriented programming (OOP) that enables a class to derive attributes and methods from another class. In Python, this mechanism facilitates code reuse and the creation of a logical class hierarchy, enhancing the modularity and maintainability of code.
In this article, we will discuss everything you need to know about Python inheritance, its components, types of inheritance in Python, and more, with examples.
What Is Inheritance In Python?
First things first, a class serves as a blueprint for creating objects, encapsulating data, and the functions that operate on that data. This bundling of data (attributes) and behaviors (methods) allows for the creation of objects with specific properties and functionalities.
Inheritance enables the creation of a new class, known as a child or derived class, that inherits attributes and methods from an existing class, referred to as the parent or base class. This mechanism allows the child class to utilize, extend, or modify the functionalities defined in the parent class, promoting code reuse and logical organization.
Real-World Analogy:
Consider a general blueprint for a vehicle, which includes common features like wheels, an engine, and seats. Specific types of vehicles, such as cars and motorcycles, can be seen as specialized versions of this general blueprint. They inherit common features but also have unique characteristics. In this analogy:
- The general vehicle blueprint represents the parent class.
- The specific vehicles (car, motorcycle) represent child classes that inherit from the parent class.
The "is-a" Relationship:
In OOP, the "is-a" relationship signifies that an object of a child class is also an instance of the parent class. For example, a car "is a" vehicle, and a motorcycle "is a" vehicle. This relationship allows child classes to inherit and, if necessary, override or extend the functionalities of the parent class.
Python Inheritance Syntax
Defining inheritance in Python programming involves specifying the parent class in parentheses when creating the child class. The basic syntax is:
class ParentClass:
# Parent class code
class ChildClass(ParentClass):
# Child class code
In this structure:
- ParentClass is the existing class whose attributes and methods are to be inherited.
- ChildClass is the new class that inherits from ParentClass.
The syntax for Python inheritance establishes a relationship where ChildClass inherits the properties and behaviors of ParentClass, allowing for code reuse and logical organization.
In the following sections, we will explore how to implement parent and child classes, utilize special methods like __init__() and super(), and understand various types of inheritance in Python.
Parent Class In Python Inheritance
In Python, a parent class (also known as a base or superclass) is the class from which other classes, called child classes, inherit attributes and methods.
- The parent class encapsulates common functionality that can be shared across multiple child classes, promoting code reuse and a logical class hierarchy.
- Note that any class can be a parent class (even a class that inherits from another can be a parent class to some other.)
Example: Defining A Parent Class
In the simple Python program example below we have illustrated how to define a parent class named Person that includes attributes for first name and last name, along with a method to display the full name.
Code Example:
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Output:
Shivani Goyal
Code Explanation:
In the simple Python code example:
- We define a class Person using the class keyword, with the class body indented after the class name.
- Inside the class, we define an __init__() method that initializes the first_name and last_name attributes when a new Person object is created.
- We also define a display_name() that uses the print() function with the f-string formatting to display the full name of the person by combining the first and last names.
- Then, we create an instance of the Person class, passing the values “Shivani” and “Goyal” for the two attributes.
- This invoked the constructor, i.e., the __init__() method that initializes the attributes.
- After that, we call the display_name() method on the person object, which prints the information to the console.
By defining common attributes and methods in the parent class, we establish a foundation that child classes can inherit and build upon, reducing redundancy and enhancing code maintainability.
Adding Attributes & Methods To Parent Class | Python Inheritance
A parent class can include various attributes and methods that encapsulate shared behaviors and properties. For instance, we can extend the Person class in the example above to include an age attribute and a method to display a greeting. The Python program example below contains the revised parent class definition and its usage.
Code Example:
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Output:
Shivani Goyal
Hello, my name is Shivani Goyal and I am 30 years old.
Code Explanation:
In the Python code example:
- We define the Person class just like before, but time we have an additional attribute age in the __init__() constructor.
- We also define an additional method greet(), which takes an object of the class and uses the f-string to format the information before printing it to the console.
- Then, we create an object of the Person class, person and pass an additional value 30 for the age variable.
- As a result, when we call the greet() method on the person object, it uses values of all three attributes and prints it to the console.
By enriching the parent class with additional attributes and methods, we provide a robust base that child classes can inherit, ensuring consistency and reducing code duplication across related classes.
Child Class In Python Inheritance
In Python, a child class (also known as a derived or subclass) is a class that inherits attributes and methods from another class, referred to as the parent class. This Python inheritance allows the child class to utilize the existing functionality of the parent class and, if necessary, introduce its own unique attributes or methods.
Example: Defining A Child Class
Continuing with our previous example, let's define a child class named Employee that inherits from the Person parent class. In the basic Python program example below, we have the same Person class and have defined a child class with an additional attribute, employee_id, and the display() method.
Code Example:
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Output:
Employee ID: U12345
Shivani Goyal
Age: 28
Code Explanation:
In the basic Python code example:
- We define a child class, Employee, that inherits from the Person class, allowing it to access the attributes and methods defined in Person.
- Inside this class, we define the __init__() method that overrides the constructor method from the Person class (we will discuss overriding in a later section).
- The method initializes the inherited attributes (first_name, last_name, age) using the super() function to call the constructor of the Person class and adds a new attribute, employee_id.
- We also define a function display_employee_details(), which displays the employee's ID, full name, and age.
- Inside, we use the print() function to display the employee ID, then the display_name() method from the parent class.
- And then again, we display the age using the print() function, which by default includes a newline character and prints the information in the next line.
- Next, we can create an instance of the Employee class called employee passing the string values “Shivani”, “Goyal”, “U12345” for attributes first name, last name, ID, and value 30 for age.
- We use this employee object to call the display_empoyee_details() method which prints the information to the console.
In this example, the Employee class inherits common attributes and methods from the Person class, such as first_name, last_name, age, and display_name(). Additionally, it introduces a new attribute, employee_id, and a method, display_employee_details(), specific to the Employee class.
This demonstrates how inheritance promotes code reuse and allows for the extension of existing functionality in a hierarchical class structure. In the following sections, we will explore the __init__() method and other components of a class and Python inheritance.
The __init__() Method In Python Inheritance
In Python, the __init__() method, known as the constructor, is automatically invoked when a new instance of a class is created.
- It initializes the object's attributes, setting up the necessary state for the object.
- When dealing with inheritance, it's crucial to ensure that the __init__() method of the parent class is properly invoked to initialize its attributes in the child class.
- A child class can override the __init__() method of its parent class to add its own attributes (like in the example above).
Let’s look at an example Python program that illustrates the use of __init__() methods and how the child class overrides it. We will continue with the previous examples, i.e., consider a parent class Person and a child class Employee that inherits from Person.
Code Example:
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Code Explanation:
In the example Python code:
- The Person class's __init__() method initializes the first_name, last_name, and age attributes.
- The Employee class inherits from Person and introduces an additional attribute, employee_id.
- Within the Employee class's __init__() method, super().__init__(first_name, last_name, age) calls the parent class's constructor to initialize the inherited attributes.
- Just like in the previous example, we create an instance of the Employee class.
- We then use three print() functions to display the information as needed.
In this example, the Employee class's __init__() method ensures that the Person class's constructor is invoked, properly initializing the inherited attributes. This practice maintains the integrity of the object's state and leverages the initialization logic defined in the parent class.
Note: If the child class defines its own __init__() method without calling the parent class's __init__(), the inherited attributes may not be initialized correctly. Therefore, using super() to invoke the parent class's constructor is a recommended practice in Python inheritance. So, let’s take a closer look at the super() function.
The super() Function In Python Inheritance
In Python, the super() function provides a mechanism to access methods and properties of a parent class from within a child class. This is particularly useful in inheritance hierarchies, allowing child classes to extend or modify the behavior of parent classes without directly referencing them. Here is why we need to use the super() method to invoke the constructor (and other methods) of the parent class:
- Code Reusability: It enables child classes to reuse code from parent classes, promoting the DRY (Don't Repeat Yourself) principle.
- Avoiding Redundancy: Without super(), we would need to explicitly call the parent class's methods, leading to more verbose and less maintainable code.
- Maintainability: By avoiding hard-coded references to parent classes, super() facilitates easier maintenance and refactoring.
- Multiple Inheritance: In scenarios involving multiple inheritance, super() ensures that the correct method from the appropriate parent class is called, adhering to the method resolution order (MRO).
Example: Using super() in a Child Class
Let's consider a parent class Person and a child class Employee that inherits from Person. We'll use super() to call the parent class's __init__ method.
Code Example:
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Code Explanation:
In the sample Python program:
- In the Employee class's __init__ method, super().__init__(first_name, last_name, age) calls the __init__ method of the Person class. This initializes the inherited attributes first_name, last_name, and age.
- By using super(), we avoid directly referencing the parent class, making the code more maintainable and adaptable to changes in the class hierarchy.
By utilizing super(), developers can write cleaner, more maintainable, and extensible code, effectively managing complex inheritance hierarchies in Python.
Method Overriding In Python Inheritance
In Python, method overriding occurs when a subclass provides a specific implementation for a method that is already defined in its superclass. This allows the subclass to modify or extend the behavior of the inherited method to suit its specific needs.
- Same Method Signature: The overriding method in the subclass must have the same name and parameters as the method in the superclass.
- Inheritance Relationship: Method overriding is possible only when there is an inheritance relationship between classes.
Example: Method Overriding In Action (Python Inheritance)
Consider a superclass Person and a subclass Employee that overrides a method from the superclass:
Code Example:
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Output:
Employee ID: U12345
Name: Shivani Goyal
Code Explanation:
In the sample Python code:
- The Employee class overrides the display_info method of the Person class to include the employee_id attribute.
- Within the overridden method, super().display_info() is called to invoke the display_info method of the superclass, ensuring that the full name is displayed.
By overriding methods, subclasses can tailor inherited behavior to meet specific requirements, enhancing the flexibility and functionality of object-oriented programming in Python.
Types Of Inheritance In Python
Python supports several types of inheritance, each serving different design purposes. In this section, we will discuss the 5 different types of inheritance with examples.
Single Inheritance In Python
Single inheritance enables a derived class to inherit properties and behaviors from a single-parent class. This is the most straightforward form of inheritance, facilitating a clear and simple class hierarchy.
Code Example:
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Inheritance Hierarchy:
Person
└── Employee
In this hierarchy, the Employee is the child class inheriting from the parent class Person. The Employee class gains access to the display_name method of the Person class, promoting code reuse and logical organization.
Multiple Inheritance In Python
Multiple inheritance allows a child class to inherit from more than one parent class. This enables the child class to combine functionalities of multiple base classes, providing a way to create complex behaviors by aggregating features from various sources.
Code Example:
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Inheritance Hierarchy:
Flyer Swimmer
\ /
Duck
Here, Duck inherits from both Flyer and Swimmer, combining the abilities to fly and swim. While multiple inheritance offers flexibility, it can introduce complexity, such as method resolution conflicts. Python addresses these issues using the Method Resolution Order (MRO), which determines the order in which base classes are searched when executing a method.
Multilevel Inheritance In Python
In multilevel inheritance, a class is derived from another class, which is also derived from another class, forming a top-to-bottom chain of inheritance. This type of inheritance models a hierarchical relationship where each level adds more specific functionality.
Code Example:
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Inheritance Hierarchy:
LivingBeing
└── Animal
└── Dog
In this structure, Dog inherits from Animal, which in turn inherits from LivingBeing. This multilevel hierarchy allows each subclass to build upon the functionality of its superclass, creating a clear lineage of behaviors.
Hierarchical Inheritance In Python
Hierarchical inheritance occurs when multiple child classes inherit from the same parent class. This pattern is useful for defining common behaviors in a base class and then extending or modifying those behaviors in each subclass.
Code Example:
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Inheritance Hierarchy:
Vehicle
/ \
Car Motorcycle
In this scenario, both Car and Motorcycle inherit from Vehicle, sharing the start_engine() method while implementing their own specific methods. This approach promotes code reuse and logical grouping of related classes.
Hybrid Inheritance In Python
Hybrid inheritance is a combination of multiple inheritance types, such as single, multiple, multilevel, and hierarchical inheritance. It allows for complex relationships by combining these inheritance patterns, enabling a more intricate and flexible class hierarchy. However, hybrid inheritance can introduce complexity and ambiguity, which Python manages using the Method Resolution Order (MRO).
Code Example:
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Inheritance Hierarchy:
LivingBeing
/ \
Animal Bird
\ /
Bat
Code Explanation:
In this example, LivingBeing is the base class with a method live(). Both Animal and Bird classes inherit from LivingBeing, adding their specific methods, move() and fly(), respectively. The Bat class inherits from both Animal and Bird, combining the behaviors of moving and flying, and introduces its own method, hang_upside_down().
This structure demonstrates hybrid inheritance by combining multiple inheritance patterns:
- Hierarchical Inheritance: Both Animal and Bird classes inherit from the single base class LivingBeing.
- Multiple Inheritance: The Bat class inherits from both Animal and Bird classes.
By utilizing hybrid inheritance, the Bat class can access methods from all its parent classes, showcasing a complex yet organized class hierarchy. However, it's essential to manage such complexity carefully to avoid potential issues like the diamond problem, where ambiguity arises in the inheritance hierarchy. Python's MRO helps resolve such ambiguities by determining the order in which base classes are searched when executing a method.
Special Functions In Python Inheritance
In Python, special methods—often referred to as "magic methods" or "dunder methods" (short for "double underscore")—are predefined/built-in Python functions that enable classes to implement and customize behavior for built-in operations.
- These methods allow objects to interact with Python's syntax and built-in functions in a natural and intuitive way.
- When dealing with inheritance, special methods are inherited just like regular methods.
- This means that a subclass can override these methods to modify or extend their behavior. For instance, if a parent class defines the __init__ method, a subclass can override it to provide additional initialization steps. However, if the subclass does not override a special method, it inherits the implementation from the parent class.
Common Special Methods Used With Python Inheritance
- __init__(self): Constructor method, called when a new instance is created.
- __str__(self): Called by the string method str() and print() to return a string representation of the object.
- __repr__(self): Called by the repr() function and used in the interpreter to represent the object.
- __add__(self, other): Called when the + operator is used between two objects.
- __eq__(self, other): Called by the relational equality operator (==) to compare two objects for equality.
Code Example:
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Code Explanation:
In this example, the Vehicle class defines the __init__ and __str__ special methods.
- The Car subclass inherits from Vehicle and overrides the __str__ method to provide a more detailed string representation.
- The super().__str__() call within the Car class allows it to include the string representation from the Vehicle class, enhancing the output without duplicating code.
By leveraging special methods in Python inheritance, you can create classes that integrate seamlessly with Python's syntax and built-in functions, leading to more readable and maintainable code.
Advantages & Disadvantages Of Inheritance In Python
Inheritance is a fundamental concept in object-oriented programming (OOP) that allows a class to inherit attributes and methods from another class. In Python, inheritance promotes code reuse and establishes a hierarchical relationship between classes. However, like any programming construct, it comes with its own set of advantages and disadvantages.
Advantages |
Disadvantages |
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Common Use Cases For Inheritance In Python
Inheritance in Python is commonly used to model hierarchical relationships, promote code reuse, and extend functionalities in various domains. Here are some common use cases:
- Code Reusability: Python inheritance enables the creation of new classes that reuse code from existing classes, reducing redundancy and promoting efficient code management. For instance, a base class defining generic database operations can be inherited by specific derived classes for different types of databases.
- Modularity and Organization: By establishing a hierarchy of classes, inheritance helps in organizing code into logical structures. This modular approach makes the codebase easier to understand and maintain.
- Polymorphism: Inheritance facilitates polymorphism, allowing objects of different classes to be treated uniformly through a common interface. This flexibility enables writing more adaptable and generic code.
- Extending Functionality: Derived classes can extend the functionality of base classes by adding new attributes and methods. This allows developers to build upon existing code and create specialized classes with additional features or behavior.
- Frameworks and Libraries: Python inheritance is widely used in frameworks and libraries to provide customizable functionality. Developers can inherit from predefined classes in the framework or Python library and override or extend their methods to suit their specific needs.
- GUI Frameworks: Python inheritance allows for the creation of a base class with common attributes and methods in graphical user interface (GUI) frameworks. This can be extended by subclasses representing specific GUI elements like buttons, text boxes, and labels. This approach promotes code reuse and a clear hierarchical structure.
- Payment Processing Systems: Inheritance can be utilized in payment processing systems where a base class defines common payment methods, and subclasses implement specific processing logic for different payment types such as credit cards, PayPal, or bank transfers.
- Game Development: In game development, Python inheritance allows for the creation of a base class representing general game entities, with subclasses defining specific behaviors for different types of characters, enemies, or non-playable characters (NPCs).
- File I/O Systems: Inheritance can be applied in applications dealing with multiple file formats by creating a base class for file handling and extending it with subclasses that implement methods for reading and writing specific file types like text files, CSV files, or JSON files.
By leveraging inheritance, developers can create more organized, maintainable, and scalable codebases, leading to more efficient development processes and robust applications.
Best Practices for Implementing Inheritance in Python
Here are a few best practices to follow to ensure that you use Python inheritance effectively and maintainably:
- Use Inheritance to Model "Is-A" Relationships: Inheritance should represent a clear "is-a" relationship between the parent and child classes. If a class does not logically fit as a subtype of another, inheritance may not be appropriate.
- Avoid Deep Inheritance Hierarchies: Deep inheritance chains can become complex and difficult to manage. Aim for shallow hierarchies to maintain clarity and ease of maintenance.
- Prefer Composition Over Inheritance When Appropriate: In some cases, composition (having objects contain instances of other classes) can be more appropriate than inheritance, especially when the relationship is better described as "has-a" rather than "is-a." This approach can lead to more flexible and decoupled designs.
- Override Methods Carefully: When overriding methods in a subclass, ensure that the new implementation is compatible with the base class's interface and does not introduce unexpected behavior.
- Utilize the super() Function Wisely: The super() function allows a subclass to call methods from its parent class. Use it judiciously to avoid unintended side effects, especially in complex inheritance hierarchies.
- Be Aware of the Method Resolution Order (MRO): In multiple inheritance scenarios, Python determines the order in which base classes are considered using the MRO. Understanding MRO is crucial to avoid conflicts and ensure that the correct method is called.
- Document Inheritance Hierarchies Clearly: Clearly document the relationships and responsibilities of classes in an inheritance hierarchy to aid in understanding and maintaining the codebase.
Avoiding Common Pitfalls in Python Inheritance
While inheritance offers many advantages, it's important to be aware of potential pitfalls:
- Tight Coupling: Inheritance can tightly couple subclasses to their parent classes, making changes in the parent class potentially disruptive to all subclasses. This can lead to maintenance challenges.
- The Diamond Problem: In multiple inheritance, if two parent classes have a method with the same name, and a subclass inherits from both, it can lead to ambiguity in which method is called. Understanding and managing the MRO is essential to resolve such conflicts.
- Overusing Inheritance: Not every relationship should be modeled with inheritance. Overusing inheritance can lead to complex and fragile code. Evaluate whether inheritance is the most appropriate design pattern for your scenario.
By adhering to these best practices and being mindful of common pitfalls, you can effectively leverage inheritance in Python to create clean, maintainable, and efficient code.
Conclusion
Python inheritance mechanism offers a robust framework for code reuse and the creation of hierarchical relationships between classes, promoting code reuse, and enhancing modularity.
- By understanding and applying inheritance appropriately, developers can build more efficient and maintainable object-oriented systems.
- It's essential to balance the use of inheritance with other design principles, such as composition, to achieve optimal code structure and flexibility.
- By adhering to best practices—such as modeling clear "is-a" relationships, avoiding deep inheritance hierarchies, and considering composition over inheritance when appropriate—you can harness the full potential of inheritance while maintaining code clarity and flexibility.
- Being mindful of common pitfalls, like tight coupling and the diamond problem, will further enhance the robustness and maintainability of your object-oriented designs.
Frequently Asked Questions
Q1. What is inheritance in Python?
Inheritance in Python allows a class (child class) to inherit attributes and methods from another class (parent class). This promotes code reuse and establishes a hierarchical relationship between classes.
Q2. How do I create a child class in Python?
To create a child class, define a new class and specify the parent class in parentheses:
class ChildClass(ParentClass):
# class body
This syntax enables the child class to inherit all attributes and methods from the parent class.
Q3. What is the super() function, and how is it used?
The super() function returns a proxy object that represents the parent classes. It's commonly used to call methods from the parent class within a child class, facilitating method overriding and ensuring that the parent class's methods are properly invoked.
class ChildClass(ParentClass):
def __init__(self):
super().__init__()
# additional initialization
Q4. Can a child class override methods from the parent class?
Yes, a child class can override methods from the parent class by defining a method with the same name. This allows the child class to provide a specific implementation of the method.
class ParentClass:
def greet(self):
print("Hello from Parent")
class ChildClass(ParentClass):
def greet(self):
print("Hello from Child")
obj = ChildClass()
obj.greet() # Output: Hello from Child
Q5. What is multiple inheritance, and how does it work in Python?
Multiple inheritance allows a class to inherit from more than one parent class. In Python, this is achieved by specifying multiple parent classes in the class definition:
class ClassA:
# class body
class ClassB:
# class body
class ChildClass(ClassA, ClassB):
# class body
Python uses the Method Resolution Order (MRO) to determine the order in which base classes are considered when searching for a method.
Q6. What is the Method Resolution Order (MRO) in Python?
The Method Resolution Order (MRO) is the order in which base classes are searched when executing a method. Python uses the C3 linearization algorithm to determine the MRO, ensuring a consistent and predictable method lookup. You can view the MRO of a class using the mro() method:
class ChildClass(ParentClass):
pass
print(ChildClass.mro())
By now, you must know how to use Python inheritance to write efficient programs. Here are a few more articles you must explore:
- Python IDLE | The Ultimate Beginner's Guide With Images & Codes
- Python input() Function (+Input Casting & Handling With Examples)
- If-Else Statement In Python | All Conditional Statements + Examples
- Python Modules | Definition, Usage, Lists & More (+Code Examples)
- Python Namespace & Variable Scope Explained (With Code Examples)
- Python Assert Keyword | Types, Uses, Best Practices (+Code Examples)
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