PYTHON CHEAT SHEET — Save This!
Most Asked Python in Tech Interviews!

====================================

Python is #1 language for AI, Data Science,
Backend & Automation roles. Master this!

====================================
DATA TYPES & BASICS

x = 10 # int
y = 3.14 # float
s = 'hello' # string
b = True # boolean
l = [1,2,3] # list (mutable)
t = (1,2,3) # tuple (immutable)
d = {'a': 1} # dictionary
st = {1,2,3} # set (unique values)

====================================
STRINGS — Most Asked!

s = 'Hello World'
s.upper() # 'HELLO WORLD'
s.lower() # 'hello world'
s.split(' ') # ['Hello', 'World']
s.replace('o','0') # 'Hell0 W0rld'
s.strip() # remove whitespace
len(s) # 11
s[0:5] # 'Hello' (slicing)
s[::-1] # reverse string!
f'Name: {s}' # f-string formatting

====================================
LIST OPERATIONS

l = [3, 1, 4, 1, 5]
l.append(9) # add to end
l.insert(0, 7) # insert at index 0
l.remove(1) # remove first '1'
l.pop() # remove last element
l.sort() # sort in place
sorted(l) # returns new sorted list
l.reverse() # reverse in place
len(l) # length of list
sum(l) # sum of all elements
max(l), min(l) # max and min value

====================================
LIST COMPREHENSION — Interviewers Love!

squares = [x**2 for x in range(10)]
# [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

evens = [x for x in range(20) if x%2==0]
# [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]

====================================
DICTIONARY TRICKS

d = {'name': 'Rahul', 'age': 22}
d['name'] # 'Rahul'
d.get('city', 'N/A') # safe get
d.keys() # all keys
d.values() # all values
d.items() # key-value pairs
d.update({'city': 'Delhi'}) # add/update

====================================
FUNCTIONS & LAMBDA

def add(a, b):
return a + b

# Lambda (one-line function)
square = lambda x: x**2
square(5) # 25

# *args and **kwargs
def greet(*names):
for name in names:
print(f'Hi {name}')

====================================
MUST-KNOW PYTHON CONCEPTS:

List vs Tuple -> mutable vs immutable
Deep vs Shallow copy -> copy.deepcopy()
Global vs Local -> variable scope
try/except -> error handling
with open() -> file handling
OOP: class, __init__, self, inheritance

====================================
TOP 5 PYTHON INTERVIEW QUESTIONS:

1. Difference: list vs tuple vs set vs dict?
2. What is a lambda function?
3. How does Python handle memory management?
4. What are decorators in Python?
5. Difference: deep copy vs shallow copy?

====================================
PRACTICE FREE ON:
HackerRank -> hackerrank.com/domains/python
LeetCode -> leetcode.com
W3Schools -> w3schools.com/python

====================================
Save this before your next interview!
Get FREE Python projects with source code:
https://t.me/Projectwithsourcecodes

Share with your placement batch!

#PythonCheatSheet #Python #PythonInterview
#DataScience #MachineLearning #PythonDeveloper
#BTech2026 #MCA2026 #BCA2026 #PlacementPrep
#CodingInterview #TechInterview #LearnPython
#ProjectWithSourceCodes #StudentsOfIndia

DSA CHEAT SHEET — Save This!
Data Structures Asked in Every Interview!

====================================

DSA is tested in ALL product company interviews!
Amazon, Google, Microsoft, Flipkart, Adobe —
ALL start with DSA rounds. Master this!

====================================
ARRAYS — Most Basic, Most Asked!

Find max/min in array -> O(n) linear scan
Reverse an array -> two pointer approach
Find duplicates -> use HashSet O(n)
Rotate array by k -> reverse technique
Two Sum problem -> HashMap O(n)
Sliding Window -> for subarray problems

====================================
STRINGS

Palindrome check -> two pointers
Anagram check -> sort both or HashMap
Longest common prefix -> vertical scan
Count vowels/consonants -> loop + set
String reversal -> s[::-1] in Python

====================================
LINKED LIST — Very Frequently Asked!

Reverse a linked list -> 3 pointer trick
Detect cycle -> Floyd's algo (slow/fast)
Find middle node -> slow/fast pointers
Merge 2 sorted lists -> compare & merge
Remove Nth node from end -> two pass

====================================
STACK & QUEUE

Stack: LIFO — use for:
-> Valid parentheses check
-> Next Greater Element
-> Undo/Redo operations

Queue: FIFO — use for:
-> BFS (level order traversal)
-> Sliding window maximum

====================================
TREES — 30% of Interview Questions!

Inorder: Left -> Root -> Right
Preorder: Root -> Left -> Right
Postorder: Left -> Right -> Root

Level Order -> use Queue (BFS)
Height of tree -> recursion
Check BST -> inorder should be sorted
LCA of two nodes -> recursive approach

====================================
SORTING ALGORITHMS

Bubble Sort -> O(n²) | Simple
Selection Sort -> O(n²) | Simple
Insertion Sort -> O(n²) | Best for small
Merge Sort -> O(nlogn) | Stable sort
Quick Sort -> O(nlogn) | In-place

For interviews: Know Merge Sort well!

====================================
SEARCHING

Linear Search -> O(n) | Unsorted array
Binary Search -> O(logn) | Sorted array only

Binary Search template:
low, high = 0, len(arr)-1
while low <= high:
mid = (low + high) // 2
if arr[mid] == target: return mid
elif arr[mid] < target: low = mid+1
else: high = mid-1

====================================
TIME COMPLEXITY QUICK REFERENCE:

O(1) -> Constant | Array index access
O(logn) -> Log | Binary search
O(n) -> Linear | Single loop
O(nlogn) -> Linearithmic | Merge sort
O(n²) -> Quadratic | Nested loops

====================================
TOP DSA PLATFORMS TO PRACTICE:
LeetCode -> leetcode.com (must!)
HackerRank -> hackerrank.com
GeeksForGeeks -> geeksforgeeks.org
Codeforces -> codeforces.com

====================================
Save this post — revise before every interview!
Get FREE projects with DSA implementation:
https://t.me/Projectwithsourcecodes

Share with your placement batch!

#DSA #DataStructures #Algorithms #LeetCode
#CodingInterview #TechInterview #Placements
#BTech2026 #MCA2026 #BCA2026 #CompetitiveCoding
#Java #Python #DSACheatSheet #FAANG
#ProjectWithSourceCodes #StudentsOfIndia

DSA CHEAT SHEET - Save This!
Data Structures Asked in Every Tech Interview!

====================================

DSA is tested at Amazon, Google, Microsoft,
Flipkart, Adobe, Uber, Swiggy — ALL of them!
Master these before your placement rounds!

====================================
ARRAYS - Most Basic, Most Asked!

Two Sum -> HashMap O(n)
Find max/min -> linear scan O(n)
Reverse array -> two pointers O(n)
Find duplicates -> HashSet O(n)
Rotate by k -> reverse technique O(n)
Subarray sum -> sliding window O(n)
Merge sorted arrays -> two pointer O(n+m)

====================================
STRINGS

Palindrome check -> two pointers O(n)
Anagram check -> sort or HashMap O(n)
Longest substring no repeat -> sliding window
String reversal -> s[::-1] in Python
Count char frequency -> HashMap O(n)

====================================
LINKED LIST - Very Frequently Asked!

Reverse linked list -> 3 pointer trick O(n)
Detect cycle -> Floyd's slow/fast O(n)
Find middle -> slow/fast pointers O(n)
Merge 2 sorted lists -> compare & link O(n)
Remove Nth from end -> two pass O(n)

====================================
STACK & QUEUE

Stack (LIFO) - use for:
-> Valid parentheses {[()]}
-> Next Greater Element
-> Undo/Redo operations

Queue (FIFO) - use for:
-> BFS (level order tree traversal)
-> Sliding window maximum

====================================
TREES - 30% of Interview Questions!

Inorder: Left Root Right
Preorder: Root Left Right
Postorder: Left Right Root
Level Order: BFS using Queue

Height of tree -> recursion O(n)
Check BST valid -> inorder sorted check
Lowest Common Ancestor -> recursive O(n)
Path sum root to leaf -> DFS O(n)

====================================
GRAPHS

BFS -> Queue, shortest path unweighted
DFS -> Stack/Recursion, path finding
Detect cycle undirected -> Union Find
Detect cycle directed -> DFS + visited
Topological Sort -> Kahn's algo (BFS)

====================================
DYNAMIC PROGRAMMING

Fibonacci -> memoization O(n)
0/1 Knapsack -> 2D DP O(n*W)
Longest Common Subsequence -> 2D DP
Coin Change -> bottom-up DP O(n*amount)
Climb Stairs -> DP same as Fibonacci

====================================
TIME COMPLEXITY QUICK REFERENCE:

O(1) Constant | Array index
O(logn) Log | Binary search
O(n) Linear | Single loop
O(nlogn) Linearithmic | Merge sort
O(n2) Quadratic | Nested loops
O(2n) Exponential | Recursion tree

====================================
TOP DSA PRACTICE PLATFORMS:
LeetCode -> leetcode.com (must!)
GeeksForGeeks -> geeksforgeeks.org
HackerRank -> hackerrank.com
Codeforces -> codeforces.com

====================================
Save this - revise before every interview!
Get FREE projects with DSA implementations:
https://t.me/Projectwithsourcecodes

Share with your placement batch!

#DSACheatSheet #DSA #DataStructures #Algorithms
#LeetCode #CodingInterview #Placements #FAANG
#BTech2026 #MCA2026 #BCA2026 #CompetitiveCoding
#Java #Python #TechInterview #DynamicProgramming
#ProjectWithSourceCodes #StudentsOfIndia

GIT CHEAT SHEET - Save This!
Commands Every Developer Must Know!

====================================

Git is asked in EVERY tech interview!
TCS, Wipro, Infosys, startups, product cos
ALL expect you to know Git. Master these!

====================================
FIRST TIME SETUP

git config --global user.name 'Your Name'
git config --global user.email 'you@email.com'
-> Run once after installing Git

====================================
STARTING A PROJECT

git init
-> Start tracking a new project folder

git clone <url>
-> Download a repo from GitHub to your PC

====================================
DAILY COMMANDS (Use Every Day!)

git status
-> See which files changed or are new

git add .
-> Stage ALL changed files for commit

git add filename.py
-> Stage one specific file only

git commit -m 'Your message here'
-> Save your staged changes permanently

git push origin main
-> Upload your commits to GitHub

git pull origin main
-> Download latest changes from GitHub

====================================
BRANCHING - Important for Team Work!

git branch
-> List all branches in your repo

git branch feature-login
-> Create a new branch called feature-login

git checkout feature-login
-> Switch to that branch

git checkout -b feature-login
-> Create AND switch in ONE command!

git merge feature-login
-> Merge branch into your current branch

git branch -d feature-login
-> Delete branch after merging

====================================
UNDO MISTAKES - Life Savers!

git restore filename.py
-> Undo unsaved changes in a file

git reset HEAD~1
-> Undo last commit but keep the changes

git revert <commit-id>
-> Safely undo a commit already pushed

git stash
-> Temporarily hide your current changes

git stash pop
-> Bring back your stashed changes

====================================
VIEWING HISTORY

git log
-> Full commit history with details

git log --oneline
-> Short commit history (one line each)

git diff
-> See exactly what changed line by line

git blame filename.py
-> See who changed which line and when

====================================
TOP 5 GIT INTERVIEW QUESTIONS:

1. What is the difference between git merge
and git rebase?
2. What is a pull request and how does it work?
3. How do you resolve a merge conflict?
4. What is git stash and when do you use it?
5. Difference between git reset and git revert?

====================================
Save this post - revise before every interview!
Get FREE projects with Git setup included:
https://t.me/Projectwithsourcecodes

Share with your placement batch!

#GitCheatSheet #Git #GitHub #VersionControl
#GitCommands #DevTools #GitBranching
#BTech2026 #MCA2026 #BCA2026 #PlacementPrep
#CodingInterview #TechInterview #OpenSource
#ProjectWithSourceCodes #StudentsOfIndia

SQL CHEAT SHEET - Save This!
Most Asked SQL in Tech Interviews!

====================================

SQL is tested in 90% of tech interviews!
TCS, Infosys, Amazon, Flipkart, Data Analyst
roles ALL require strong SQL. Master this!

====================================
BASIC QUERIES

SELECT * FROM employees;
-> Get all rows from table

SELECT name, salary FROM employees
WHERE salary > 50000;
-> Filter rows with condition

SELECT * FROM employees
ORDER BY salary DESC LIMIT 5;
-> Top 5 highest paid employees

SELECT DISTINCT department FROM employees;
-> Get unique departments only

====================================
AGGREGATE FUNCTIONS

SELECT COUNT(*) FROM employees;
-> Total number of rows

SELECT AVG(salary) FROM employees;
-> Average salary

SELECT MAX(salary), MIN(salary) FROM employees;
-> Highest and lowest salary

SELECT department, COUNT(*) as emp_count
FROM employees
GROUP BY department
HAVING COUNT(*) > 5;
-> Departments with more than 5 employees

====================================
JOINS - Most Asked in Interviews!

INNER JOIN - Only matching rows in both tables:
SELECT e.name, d.dept_name
FROM employees e
INNER JOIN departments d ON e.dept_id = d.id;

LEFT JOIN - All from left + matching right:
SELECT e.name, d.dept_name
FROM employees e
LEFT JOIN departments d ON e.dept_id = d.id;

SELF JOIN - Table joined with itself:
SELECT e1.name, e2.name AS manager
FROM employees e1
JOIN employees e2 ON e1.manager_id = e2.id;

====================================
SUBQUERIES - Asked in Advanced Rounds!

Employees earning more than average:
SELECT name FROM employees
WHERE salary > (SELECT AVG(salary) FROM employees);

2nd highest salary (Classic Question!):
SELECT MAX(salary) FROM employees
WHERE salary < (SELECT MAX(salary) FROM employees);

Nth highest salary using LIMIT:
SELECT salary FROM employees
ORDER BY salary DESC LIMIT 1 OFFSET N-1;

====================================
WINDOW FUNCTIONS - Modern SQL!

Rank employees by salary:
SELECT name, salary,
RANK() OVER (ORDER BY salary DESC) as rnk
FROM employees;

Row number within each department:
SELECT name, department,
ROW_NUMBER() OVER
(PARTITION BY department ORDER BY salary DESC)
FROM employees;

====================================
TOP 5 SQL INTERVIEW QUESTIONS:

1. Find duplicate records in a table
2. Find employees with no manager (NULL)
3. Find departments with zero employees
4. Find Nth highest salary
5. Difference between WHERE and HAVING?

====================================
PRACTICE FREE ON:
SQLZoo -> sqlzoo.net
HackerRank -> hackerrank.com/domains/sql
LeetCode -> leetcode.com/problemset/database

====================================
Save this before your next interview!
Get FREE projects with database code:
https://t.me/Projectwithsourcecodes

Share with your placement batch!

#SQLCheatSheet #SQL #MySQL #PostgreSQL
#DatabaseInterview #Joins #Subqueries #WindowFunctions
#BTech2026 #MCA2026 #BCA2026 #PlacementPrep
#DataAnalyst #BackendDeveloper #TechInterview
#ProjectWithSourceCodes #StudentsOfIndia

SYSTEM DESIGN BASICS - Save This!
Asked in Every Senior + Product Company Round!

====================================

System Design is asked at Adobe, Microsoft,
Flipkart, Razorpay, Swiggy, Uber and ALL
product companies. Learn the basics NOW!

====================================
1. SCALABILITY

Making your app handle more users over time

Vertical Scaling: Add more RAM/CPU to one server
-> Simple but has physical limits

Horizontal Scaling: Add more servers
-> Used by Google, Amazon, Netflix
-> Needs load balancer to distribute traffic

====================================
2. LOAD BALANCER

Distributes incoming requests across servers
so no single server gets overloaded.

Algorithms:
Round Robin -> requests go in rotation
Least Connections -> send to least busy server
IP Hash -> same user always hits same server

Real examples: AWS ALB, Nginx, HAProxy

====================================
3. CACHING

Store frequently accessed data in fast memory
to avoid hitting the database every time.

Redis -> most popular cache tool
CDN -> cache static files (images, CSS, JS)
near users geographically

Cache strategies:
Cache Aside -> app checks cache, then DB
Write Through -> write to cache + DB together
TTL (Time To Live) -> auto-expire cached data

====================================
4. DATABASE DESIGN

SQL (MySQL, PostgreSQL):
-> Structured data, ACID transactions
-> Use for: banking, orders, user accounts

NoSQL (MongoDB, DynamoDB):
-> Flexible schema, high write speed
-> Use for: chat messages, logs, catalogs

Database Sharding:
-> Split data across multiple DB servers
-> Used when one DB cannot handle load

Replication:
-> Master writes, Slaves read
-> Improves read performance + availability

====================================
5. MICROSERVICES vs MONOLITH

Monolith -> one big codebase, simple to start
Microservices -> split into small independent
services (User, Order, Payment, Notification)

When to use Microservices:
Large teams (each team owns one service)
Different scaling needs per service
Example: Netflix, Uber, Amazon all use it

====================================
6. MESSAGE QUEUES

Async communication between services
so they don't have to wait for each other.

Tools: Apache Kafka, RabbitMQ, AWS SQS

Example: Order placed -> Queue -> Notification
service sends email without slowing checkout!

====================================
7. CAP THEOREM

A distributed system can only guarantee 2 of 3:
C - Consistency (all nodes have same data)
A - Availability (always responds)
P - Partition Tolerance (survives network split)

Real systems choose CP or AP based on use case.

====================================
TOP 5 SYSTEM DESIGN INTERVIEW QUESTIONS:

1. Design URL Shortener (like bit.ly)
2. Design Instagram (image storage + feed)
3. Design WhatsApp (real-time messaging)
4. Design Uber (ride matching + maps)
5. Design Netflix (video streaming + CDN)

====================================
Save this - revise before product company rounds!
Get FREE system design projects:
https://t.me/Projectwithsourcecodes

Share with your placement batch!

#SystemDesign #SystemDesignInterview #LLD #HLD
#Microservices #Kafka #Redis #LoadBalancer
#BTech2026 #MCA2026 #BCA2026 #PlacementPrep
#ProductCompany #SDE2 #TechInterview #Scalability
#ProjectWithSourceCodes #StudentsOfIndia

REACT + JS CHEAT SHEET - Save This!
Most Asked in Tech Interviews!

====================================

JS ESSENTIALS:
map / filter / reduce | spread [...arr]
destructuring const {a, b} = obj
async/await + fetch | ES6 arrow functions

REACT HOOKS:
useState -> local state
useEffect -> side effects (API calls, subscriptions)
useContext -> global data without prop drilling
useRef -> DOM access, persist values
useMemo / useCallback -> performance optimization

KEY CONCEPTS: Virtual DOM, props vs state,
controlled components, lifting state up,
keys in lists, conditional rendering

====================================
TOP 5 INTERVIEW QUESTIONS:
1. What is Virtual DOM?
2. props vs state?
3. useEffect dependency array?
4. What is prop drilling?
5. Controlled vs uncontrolled components?

====================================
Save this before your next interview!
Get FREE projects with source code:
https://t.me/Projectwithsourcecodes

Share with your placement batch!

#ReactJS #JavaScript #Frontend
#PlacementPrep #TechInterview
#BTech2026 #MCA2026 #BCA2026
#ProjectWithSourceCodes #StudentsOfIndia

🚀 Advanced Coding Interview Questions with Answers (Part 1)

1️⃣ Find the Longest Substring Without Repeating Characters

👉 Given a string, find the length of the longest substring containing no duplicate characters.

def longest_unique_substring(s):
    seen = set()
    left = 0
    max_length = 0

    for right in range(len(s)):
        while s[right] in seen:
            seen.remove(s[left])
            left += 1

        seen.add(s[right])
        max_length = max(max_length, right - left + 1)

    return max_length

print(longest_unique_substring("abcabcbb"))

📌 Output:

3

⏱ Time Complexity: O(n)
💾 Space Complexity: O(n)

---

2️⃣ Find the Kth Largest Element in an Array

👉 Find the Kth largest element without completely sorting the array.

import heapq

def kth_largest(nums, k):
    heap = nums[:k]
    heapq.heapify(heap)

    for num in nums[k:]:
        if num > heap[0]:
            heapq.heapreplace(heap, num)

    return heap[0]

print(kth_largest([3, 2, 1, 5, 6, 4], 2))

📌 Output:

5

⏱ Time Complexity: O(n log k)
💾 Space Complexity: O(k)

---

3️⃣ Detect a Cycle in a Linked List

👉 Determine whether a linked list contains a cycle using Floyd's Cycle Detection Algorithm.

def has_cycle(head):
    slow = head
    fast = head

    while fast and fast.next:
        slow = slow.next
        fast = fast.next.next

        if slow == fast:
            return True

    return False

💡 The slow pointer moves one step while the fast pointer moves two steps.

⏱ Time Complexity: O(n)
💾 Space Complexity: O(1)

---

4️⃣ Find the Maximum Subarray Sum

👉 Find the contiguous subarray with the largest sum using Kadane's Algorithm.

def max_subarray_sum(nums):
    current = nums[0]
    maximum = nums[0]

    for num in nums[1:]:
        current = max(num, current + num)
        maximum = max(maximum, current)

    return maximum

print(max_subarray_sum([-2, 1, -3, 4, -1, 2, 1, -5, 4]))

📌 Output:

6

⏱ Time Complexity: O(n)
💾 Space Complexity: O(1)

---

5️⃣ Merge Overlapping Intervals

👉 Given a collection of intervals, merge all overlapping intervals.

def merge_intervals(intervals):
    intervals.sort(key=lambda x: x[0])
    merged = []

    for start, end in intervals:
        if not merged or start > merged[-1][1]:
            merged.append([start, end])
        else:
            merged[-1][1] = max(merged[-1][1], end)

    return merged

print(merge_intervals([[1, 3], [2, 6], [8, 10], [9, 12]]))

📌 Output:

[[1, 6], [8, 12]]

⏱ Time Complexity: O(n log n)
💾 Space Complexity: O(n)

---

💬 Save this for your advanced coding interview preparation!

🔥 Part 2 will cover 5 harder problems on Binary Search, Dynamic Programming, Graphs, Backtracking & Sliding Window.

#Coding #CodingInterview #Python #DSA #AdvancedCoding #Algorithms #DynamicProgramming #Graphs #Programming #TechInterview

☕️ Java Interview Questions with Answers (Part 1)
1️⃣ What is Java?
👉 Java is a high-level, object-oriented programming language designed to be portable across different platforms.
Key features:
🔹 Object-Oriented
🔹 Platform Independent
🔹 Secure
🔹 Robust
🔹 Multithreaded
🔹 Automatic Memory Management
📌 Write Once, Run Anywhere is commonly associated with Java's platform independence.
2️⃣ What is JVM?
👉 JVM stands for Java Virtual Machine. It executes Java bytecode and provides the runtime environment required to run Java applications.
📌 Basic flow:

Java Source Code
      ↓
   Compiler
      ↓
  Bytecode
      ↓
     JVM
      ↓
    Output

💡 JVM implementations are platform-specific, which allows the same Java bytecode to run on different operating systems.
3️⃣ What is the Difference Between JDK, JRE, and JVM?
👉 These three components have different roles:
🔹 JVM → Executes Java bytecode
🔹 JRE → JVM + libraries required to run Java applications
🔹 JDK → JRE/runtime components + development tools such as the Java compiler
📌 JDK → Development
📌 JRE → Running applications
📌 JVM → Executing bytecode
4️⃣ What is a Class in Java?
👉 A class is a blueprint for creating objects. It defines data and behavior through fields, methods, constructors, and other members.
Example:

class Student {
    String name;
    int age;

    void display() {
        System.out.println(name + " " + age);
    }
}

💡 Objects are created from classes.
5️⃣ What is an Object in Java?
👉 An object is an instance of a class. It contains state represented by fields and behavior provided by methods.
Example:

class Student {
    String name;

    void display() {
        System.out.println(name);
    }
}

public class Main {
    public static void main(String[] args) {
        Student s = new Student();

        s.name = "Rahul";
        s.display();
    }
}

📌 Class → Blueprint
📌 Object → Instance of the class

💬 Save this for your next Java interview preparation!

🔥 Part 2 will cover 5 important questions on Inheritance, Polymorphism, Encapsulation, Abstraction & Constructors.
#Java #JavaInterview #JavaProgramming #Programming #OOP #CodingInterview #SoftwareEngineer #InterviewQuestions #Developer #TechInterview

☕️ Java Interview Questions with Answers (Part 2)
6️⃣ What is Inheritance in Java?
👉 Inheritance allows a class to acquire fields and methods from another class. It helps create reusable and hierarchical code.
Example:

class Animal {
    void eat() {
        System.out.println("Eating");
    }
}

class Dog extends Animal {
    void bark() {
        System.out.println("Barking");
    }
}

public class Main {
    public static void main(String[] args) {
        Dog d = new Dog();

        d.eat();
        d.bark();
    }
}

📌 Dog inherits the eat() method from Animal.
7️⃣ What is Polymorphism in Java?
👉 Polymorphism means one interface or method name can represent different behaviors.
Two common forms are:
🔹 Compile-time Polymorphism → Method Overloading
🔹 Runtime Polymorphism → Method Overriding
Example of Overloading:

class Calculator {
    int add(int a, int b) {
        return a + b;
    }

    int add(int a, int b, int c) {
        return a + b + c;
    }
}

💡 The same method name add() works with different parameter lists.
8️⃣ What is Encapsulation in Java?
👉 Encapsulation means bundling data and methods together while controlling direct access to the data.
Example:

class Student {
    private int age;

    public void setAge(int age) {
        this.age = age;
    }

    public int getAge() {
        return age;
    }
}

📌 private prevents direct access from outside the class.
💡 Encapsulation helps protect object state and provides controlled access.
9️⃣ What is Abstraction in Java?
👉 Abstraction means hiding implementation details and exposing only the essential functionality.
Java supports abstraction using:
🔹 Abstract Classes
🔹 Interfaces
Example:

abstract class Animal {
    abstract void sound();

    void sleep() {
        System.out.println("Sleeping");
    }
}

class Dog extends Animal {
    void sound() {
        System.out.println("Bark");
    }
}

💡 The user of Animal does not need to know how sound() is implemented internally.
🔟 What is a Constructor in Java?
👉 A constructor is a special member used to initialize an object when it is created.
Example:

class Student {
    String name;

    Student(String name) {
        this.name = name;
    }

    void display() {
        System.out.println(name);
    }
}

public class Main {
    public static void main(String[] args) {
        Student s = new Student("Rahul");
        s.display();
    }
}

📌 Constructor name must match the class name.
💡 Constructors do not have a return type, including void.
💬 Save this for your Java interview preparation!
🔥 Part 3 will cover 5 important questions on Method Overloading, Method Overriding, this, super & static.
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