DEV Community: Aruna

Day 6 : SQL

Aruna — Wed, 17 Dec 2025 18:22:48 +0000

Practice Day (SELECT, WHERE, ORDER BY, LIMIT)

1. Sample Table for Practice
employees

emp_id	emp_name	department	salary	city
1	Ravi	IT	45000	Chennai
2	Priya	HR	38000	Coimbatore
3	Arjun	IT	52000	Bangalore
4	Meena	Finance	41000	Chennai
5	Karthik	IT	30000	Madurai
6	Anu	HR	36000	Chennai

2. Practice Queries with Solutions

Q1: Display all employee details
SELECT * FROM employees;

Q2: Display employee name and salary
SELECT emp_name, salary FROM employees;

Q3: Display employees with salary greater than 40000
SELECT * FROM employees
WHERE salary > 40000;

Q4: Display IT department employees
SELECT * FROM employees
WHERE department = 'IT';

Q5: Display employees from Chennai city
SELECT * FROM employees
WHERE city = 'Chennai';

Q6: Display employees whose name starts with 'A'
SELECT * FROM employees
WHERE emp_name LIKE 'A%';

Q7: Display employees with salary between 35000 and 45000
SELECT * FROM employees
WHERE salary BETWEEN 35000 AND 45000;

Q8: Display employees in IT or HR department
SELECT * FROM employees
WHERE department IN ('IT', 'HR');

Q9: Display top 3 highest paid employees
SELECT * FROM employees
ORDER BY salary DESC
LIMIT 3;

Q10: Display employees sorted by name
SELECT * FROM employees
ORDER BY emp_name ASC;

Revision, Quiz & Interview Preparation

1. Revision Summary (Day 1–5)

✔ SQL basics & databases
✔ CREATE, INSERT, SELECT
✔ WHERE clause
✔ Operators
✔ ORDER BY & LIMIT

2. SQL Quiz (Test Yourself)
Q1: Which keyword removes duplicate values?
A) UNIQUE
B) DISTINCT ✅
C) DIFFERENT
Q2: Which clause filters rows?
A) SELECT
B) WHERE ✅
C) ORDER BY
Q3: Default order in ORDER BY?
A) DESC
B) ASC ✅
Q4: Which operator checks a range?
A) IN
B) BETWEEN ✅
Q5: Which clause limits rows?
A) LIMIT ✅
B) WHERE

3. Common Interview Questions (Beginner)
Q: Difference between WHERE and HAVING?
WHERE filters rows
HAVING filters groups (after GROUP BY)
Q: What is DISTINCT?
Removes duplicate value
Q: Can ORDER BY be used without SELECT?
No

4. Real-Time Scenario Questions
*Find top 5 salary employees
*Find employees from specific city
*Filter records using multiple conditions
*Sort employee data for reports

5.Self-Assessment Task
Create a table students with:

student_id
student_name
marks
city

✔ Insert 5 records
✔ Write queries:

Top 2 highest marks
Students from Chennai
Marks between 60 and 90

Day 5: SQL

Aruna — Tue, 16 Dec 2025 15:16:48 +0000

ORDER BY, LIMIT & Sorting Data

1. What is ORDER BY?
The ORDER BY clause is used to sort the result set.

Default sorting → Ascending (ASC)
Can sort by one or multiple columns

2. ORDER BY Syntax
SELECT column1, column2
FROM table_name
ORDER BY column_name [ASC | DESC];

3. Sorting in Ascending Order (ASC)
SELECT emp_name, salary
FROM employees
ORDER BY salary;
Same as:
ORDER BY salary ASC;

4. Sorting in Descending Order (DESC)
SELECT emp_name, salary
FROM employees
ORDER BY salary DESC;

5. Sorting by Multiple Columns
SELECT emp_name, department, salary
FROM employees
ORDER BY department ASC, salary DESC;

6. ORDER BY with WHERE
SELECT emp_name, salary
FROM employees
WHERE department = 'IT'
ORDER BY salary DESC;

7. LIMIT Clause
Used to restrict number of rows returned.
SELECT * FROM employees
LIMIT 5;

8. LIMIT with OFFSET
Used for pagination.
SELECT * FROM employees
LIMIT 5 OFFSET 5;

9. LIMIT with ORDER BY (Most Important)
Used to find Top / Bottom records.
Top 3 highest salaries:
SELECT emp_name, salary
FROM employees
ORDER BY salary DESC
LIMIT 3;

Lowest salary:
SELECT emp_name, salary
FROM employees
ORDER BY salary ASC
LIMIT 1;

10. Using Column Position in ORDER BY
SELECT emp_name, salary
FROM employees
ORDER BY 2 DESC;

Day 4: SQL

Aruna — Mon, 15 Dec 2025 15:08:29 +0000

Filtering Data Using WHERE Clause & Operators

1. What is WHERE Clause?
The WHERE clause is used to filter rows that meet a specific condition.
Without it, SELECT returns all rows.
Syntax:
SELECT column1, column2
FROM table_name
WHERE condition;

2. Comparison Operators
Used to compare values.

Operator	Description	Example
=	Equal to	salary = 35000
!= or <>	Not equal	age <> 25
>	Greater than	salary > 30000
<	Less than	age < 30
>=	Greater or equal	salary >= 40000
<=	Less or equal	age <= 22

Example:
SELECT * FROM employees
WHERE salary > 35000;

3. Logical Operators
Combine multiple conditions.
| Operator | Description | Example |
| -------- | -------------------- | -------------------------------------- |
| AND | Both conditions true | salary > 35000 AND department = 'IT' |
| OR | Any condition true | department = 'IT' OR department = 'HR' |
| NOT | Negates condition | NOT department = 'HR' |

Example:
SELECT * FROM employees
WHERE department = 'IT' AND salary > 35000;

4. Pattern Matching with LIKE
Search for patterns in text columns.

Pattern	Description
%	Any number of characters
_	Single character

Examples:
-- Names starting with 'R'
SELECT * FROM employees
WHERE emp_name LIKE 'R%';
-- Names ending with 'a'
SELECT * FROM employees
WHERE emp_name LIKE '%a';
-- Names with 4 letters
SELECT * FROM employees
WHERE emp_name LIKE '____';

5. Filtering with BETWEEN
Select values within a range.
SELECT * FROM employees
WHERE salary BETWEEN 35000 AND 42000;

6. Filtering with IN
Select values from a list.
SELECT * FROM employees
WHERE department IN ('IT', 'HR');

7. Filtering with IS NULL / IS NOT NULL
Check for missing values.
SELECT * FROM employees
WHERE department IS NULL;
SELECT * FROM employees
WHERE department IS NOT NULL;

Day 3: SQL

Aruna — Sun, 14 Dec 2025 14:29:15 +0000

SELECT Statement & DISTINCT Clause

1. What is SELECT Statement?
The SELECT statement is used to retrieve data from a table.
It is the most important and frequently used SQL command.

2. Basic SELECT Syntax
SELECT column_name
FROM table_name;

3. Select All Columns (*)
Fetches all columns from a table.
SELECT * FROM employees;
* means all columns

4. Select Specific Columns
Retrieve only required columns.
SELECT emp_name, salary
FROM employees;

5. Column Aliases (AS)
Used to give temporary names to columns in output.
SELECT emp_name AS Name, salary AS Salary
FROM employees;
Alias without AS:
SELECT emp_name Name, salary Salary
FROM employees;

6. SELECT with Expressions
You can perform calculations inside SELECT.
SELECT emp_name, salary * 12 AS Annual_Salary
FROM employees;

7. DISTINCT Keyword
Used to remove duplicate values from results.
Example Table: employees

emp_id	emp_name	department
1	Ravi	IT
2	Priya	HR
3	Karthik	IT
4	Anu	HR

Without DISTINCT:
SELECT department FROM employees;
Result:
IT
HR
IT
HR

With DISTINCT:
SELECT DISTINCT department FROM employees;
Result:
IT
HR

8. DISTINCT with Multiple Columns
Distinct combination of columns.
SELECT DISTINCT department, emp_name
FROM employees;

9. SELECT with ORDER BY (Intro)
SELECT emp_name, salary
FROM employees
ORDER BY salary;
Descending order:
ORDER BY salary DESC;

Day 2:SQL

Aruna — Sun, 14 Dec 2025 11:25:33 +0000

Database Structure, Data Types & Table Basics

1. Database Structure Recap
A Relational Database contains:

Database
Tables
Rows (Records)
Columns (Fields) Example: Database → school Table → students Columns → student_id, name, age, city

2. SQL Data Types (VERY IMPORTANT)

Numeric Data Types
| Data Type | Description | Example |
| ------------ | --------------- | ------- |
| INT | Whole numbers | 10, 25 |
| BIGINT | Large integers | 1000000 |
| DECIMAL(p,s) | Decimal numbers | 99.50 |

String / Character Data Types
| Data Type | Description | Example |
| ---------- | -------------------- | ------- |
| CHAR(n) | Fixed-length text | 'A' |
| VARCHAR(n) | Variable-length text | 'Aruna' |
| TEXT | Large text | Address |

Date & Time Data Types
| Data Type | Description | Example |
| --------- | ----------- | ------------------- |
| DATE | YYYY-MM-DD | 2025-01-10 |
| TIME | HH:MM:SS | 10:30:00 |
| DATETIME | Date + Time | 2025-01-10 10:30:00 |

3. CREATE TABLE with Data Types
Defines table structure clearly.
CREATE TABLE employees (
emp_id INT,
emp_name VARCHAR(50),
salary DECIMAL(10,2),
join_date DATE
);

4. Viewing Table Structure
DESCRIBE table
DESCRIBE employees;
SHOW TABLES
SHOW TABLES;

5. INSERT Data (Detailed)
Insert single row:
INSERT INTO employees
(emp_id, emp_name, salary, join_date)
VALUES (101, 'Ravi', 35000.50, '2024-06-15');
Insert multiple rows:
INSERT INTO employees VALUES
(102, 'Priya', 42000.00, '2024-07-01'),
(103, 'Karthik', 38000.75, '2024-08-10');

6. SELECT Basics (More Detail)
Select all columns:
SELECT * FROM employees;
Select specific columns:
SELECT emp_name, salary FROM employees;

7. Table Naming Rules

Use meaningful names
Avoid SQL keywords
Use lowercase / underscore employee_details-correct select, table-not correct

Day 2:Python Programming

Aruna — Sun, 14 Dec 2025 11:10:26 +0000

Database Structure, Data Types & Table Basics

1. Database Structure Recap
A Relational Database contains:

Database
Tables
Rows (Records)
Columns (Fields) Example: Database → school Table → students Columns → student_id, name, age, city

2. SQL Data Types (VERY IMPORTANT)

3. CREATE TABLE with Data Types
Defines table structure clearly.
CREATE TABLE employees (
emp_id INT,
emp_name VARCHAR(50),
salary DECIMAL(10,2),
join_date DATE
);

4. Viewing Table Structure
DESCRIBE table
DESCRIBE employees;
SHOW TABLES
SHOW TABLES;

6. SELECT Basics (More Detail)
Select all columns:
SELECT * FROM employees;
Select specific columns:
SELECT emp_name, salary FROM employees;

7. Table Naming Rules

Use meaningful names
Avoid SQL keywords
Use lowercase / underscore employee_details-correct select, table-not correct

Day 2:Python Programming

Aruna — Sun, 14 Dec 2025 10:52:23 +0000

Database Structure, Data Types & Table Basics

1. Database Structure Recap
A Relational Database contains:

Database
Tables
Rows (Records)
Columns (Fields) Example: Database → school Table → students Columns → student_id, name, age, city

2. SQL Data Types (VERY IMPORTANT)

3. CREATE TABLE with Data Types
Defines table structure clearly.
CREATE TABLE employees (
emp_id INT,
emp_name VARCHAR(50),
salary DECIMAL(10,2),
join_date DATE
);

4. Viewing Table Structure
DESCRIBE table
DESCRIBE employees;
SHOW TABLES
SHOW TABLES;

6. SELECT Basics (More Detail)
Select all columns:
SELECT * FROM employees;
Select specific columns:
SELECT emp_name, salary FROM employees;

7. Table Naming Rules

Use meaningful names
Avoid SQL keywords
Use lowercase / underscore employee_details-correct select, table-not correct

SQL – Day1

Aruna — Fri, 12 Dec 2025 15:51:25 +0000

Introduction to Databases & SQL Basics

1. What is SQL?
SQL = Structured Query Language
It is used to store, manage, and retrieve data from relational databases.

SQL allows you to:

Create databases
Create tables
Insert data
Update and delete data
Fetch data using queries

2. What is a Database?
A database is a collection of organised data.
Types of Databases:
1.Relational Database (RDBMS)

Data stored in tables
Uses SQL
Examples: MySQL, PostgreSQL, Oracle, SQL Server 2.NoSQL Database
Non-table structure (JSON, Key-Value, Document)
Examples: MongoDB, Cassandra

3. What is a Table?
A table is a structure inside a database that stores data in:

Rows → each entry (record)
Columns → attributes (name, age, phone)

Example Table:Students

student_id	name	age	city
1	Arun	21	Chennai
2	Priya	22	Coimbatore
3	Karthi	23	Madurai

4. What is a Schema?
A schema is the blueprint/structure of a database.
It defines:

Number of tables
Columns
Data types
Relationships

SQL Commands

CREATE DATABASE
Used to create a new database.
CREATE DATABASE school;

USE DATABASE
Select the database to work inside.
USE school;

CREATE TABLE
Create a table with columns and data types.
CREATE TABLE students (
student_id INT,
name VARCHAR(50),
age INT,
city VARCHAR(50)
);

INSERT DATA
Insert records into the table.
INSERT INTO students (student_id, name, age, city)
VALUES (1, 'Arun', 21, 'Chennai');

Multiple insert:
INSERT INTO students VALUES
(2, 'Priya', 22, 'Coimbatore'),
(3, 'Karthi', 23, 'Madurai');

SELECT Data
Retrieve data from a table.
Fetch all columns
SELECT * FROM students;
Fetch specific columns:
SELECT name, city FROM students;

Day 21:Python Programming

Aruna — Thu, 11 Dec 2025 14:22:26 +0000

Python Automation

1. Python File Automation (os, shutil)
Create a new file
f = open("sample.txt", "w")
f.write("Hello")
f.close()
Read file
with open("sample.txt", "r") as f:
print(f.read())
Append data
with open("sample.txt", "a") as f:
f.write("\nNew line added")

2. OS Module (Very Important)
import os
Create folder
os.mkdir("backup")
Create multiple folders
os.makedirs("project/logs")
List files
print(os.listdir())
Rename file
os.rename("sample.txt", "data.txt")
Delete file
os.remove("data.txt")
Remove folder
os.rmdir("backup")

3. shutil Module
Advanced file handling.
import shutil
Copy file
shutil.copy("file1.txt", "backup/file1.txt")
Copy folder
shutil.copytree("project", "project_backup")
Delete folder
shutil.rmtree("project_backup")

4. Automating Downloads
With requests module:
import requests
url = "https://example.com/file.pdf"
r = requests.get(url)
with open("file.pdf", "wb") as f:
f.write(r.content)

5. Web Scraping Automation (BeautifulSoup)
Install:
pip install requests beautifulsoup4
Scraping Example
import requests
from bs4 import BeautifulSoup
url = "https://www.example.com"
html = requests.get(url).text
soup = BeautifulSoup(html, "html.parser")
title = soup.find("h1").text
print(title)

6. API Automation
Using weather API example:
import requests
url = "https://api.openweathermap.org/data/2.5/weather?q=Chennai&appid=API_KEY"
data = requests.get(url).json()
print(data["weather"][0]["main"])

7. Send Email Using Python
SMTP Email Automation
import smtplib
from email.mime.text import MIMEText
sender = "you@gmail.com"
password = "yourpassword"
receiver = "test@gmail.com"
msg = MIMEText("Hello, this is automated mail")
msg["Subject"] = "Test Email"
msg["From"] = sender
msg["To"] = receiver
server = smtplib.SMTP("smtp.gmail.com", 587)
server.starttls()
server.login(sender, password)
server.sendmail(sender, receiver, msg.as_string())
server.quit()

8. Scheduling Automation Scripts
Windows Task Scheduler

Open Task Scheduler
Create Basic Task
Choose frequency (daily/hourly)
Choose “Start a program” → select python.exe & your script Linux Cron Job Open cron: crontab -e Run script every 5 minutes: */5 * * * * python3 /home/user/script.py

9. DevOps Real-Time Automation Examples
A. Server Health Monitoring Script
import psutil
print("CPU:", psutil.cpu_percent())
print("RAM:", psutil.virtual_memory().percent)

B. Log File Monitoring
with open("/var/log/syslog") as log:
for line in log:
if "error" in line.lower():
print("Error found:", line)

C. Automate File Backup
import shutil
source = "data/"
dest = "backup/"
shutil.copytree(source, dest, dirs_exist_ok=True)
print("Backup complete")

D. Check Website Status
import requests
url = "https://google.com"
res = requests.get(url)
if res.status_code == 200:
print("Website Up")
else:
print("Website Down")

E. Auto-Restart Service (Linux)
import os
status = os.system("systemctl is-active --quiet nginx")
if status != 0:
os.system("systemctl restart nginx")

10. JSON Automation (Data Processing)
import json
f = open("data.json")
data = json.load(f)
print(data["name"])

11. CSV Automation
import csv
with open("data.csv") as f:
reader = csv.reader(f)
for row in reader:
print(row)

Day 20: Python Programming

Aruna — Wed, 10 Dec 2025 13:01:59 +0000

Multithreading & Multiprocessing

Topics Covered

Process vs Thread
Multithreading
Thread class
Synchronization (Lock)
Multiprocessing
CPU-bound vs I/O-bound
Real-time & DevOps use cases

1. Process vs Thread
Process

Independent program
Separate memory
Slower creation
Uses CPU heavily

Thread

Part of a process
Shared memory
Faster execution
Lightweight

One process can have multiple threads

2. CPU-bound vs I/O-bound Tasks
I/O-bound (Best for Multithreading)

File read/write
API calls
Network operations
Sleep

CPU-bound (Best for Multiprocessing)

Calculations
Image processing
ML tasks

3. Multithreading
Used to run multiple tasks concurrently.
Python module:
import threading

4. Create a Thread (Basic Example)
import threading
def task():
print("Thread task running")
t = threading.Thread(target=task)
t.start()

5. Multiple Threads Example
import threading
def job(name):
print("Task:", name)
t1 = threading.Thread(target=job, args=("A",))
t2 = threading.Thread(target=job, args=("B",))
t1.start()
t2.start()

6. Thread with Loop
import threading
def numbers():
for i in range(5):
print(i)
t = threading.Thread(target=numbers)
t.start()

7. Join Threads
join() waits for thread to finish.
t1.start()
t1.join()
print("Main program ends")

8. Multithreading Example (I/O-Bound)
import threading
import time
def download(file):
print("Downloading", file)
time.sleep(2)
print("Completed", file)
files = ["A", "B", "C"]
threads = []
for f in files:
t = threading.Thread(target=download, args=(f,))
t.start()
threads.append(t)
for t in threads:
t.join()
print("All downloads complete")

9. Thread Synchronization (Lock)
Used to avoid data inconsistency.
import threading
lock = threading.Lock()
count = 0
def increment():
global count
for i in range(1000):
lock.acquire()
count += 1
lock.release()
t1 = threading.Thread(target=increment)
t2 = threading.Thread(target=increment)
t1.start()
t2.start()
t1.join()
t2.join()
print(count)

10. Why Lock is Required?
*Without lock → Race condition
*With lock → Safe shared data access

11. Multiprocessing
Uses multiple CPU cores.
Python module:
import multiprocessing

12. Multiprocessing Example
from multiprocessing import Process
def task():
print("Process running")
p = Process(target=task)
p.start()

13. Multiple Processes Example
from multiprocessing import Process
import os
def work():
print("Process ID:", os.getpid())
p1 = Process(target=work)
p2 = Process(target=work)
p1.start()
p2.start()

14. Multiprocessing with Join
p1.start()
p2.start()
p1.join()
p2.join()
print("Main process completed")

15. When NOT to Use Multithreading?
CPU-intensive tasks
*Heavy mathematical calculation
➡ Python has **GIL (Global Interpreter Lock)*
➡ Blocks true parallel CPU execution

16. Multithreading vs Multiprocessing

Feature	Multithreading	Multiprocessing
Memory	Shared	Separate
Speed	Fast I/O	Fast CPU
GIL	Affected	Not affected
Use case	I/O tasks	CPU tasks

17. Real-Time DevOps Use Case
Running multiple server health checks
import threading
import time
def check_server(server):
print("Checking", server)
time.sleep(1)
print(server, "UP")
servers = ["Server1", "Server2", "Server3"]
for s in servers:
threading.Thread(target=check_server, args=(s,)).start()

Day 19 : Python Programming

Aruna — Tue, 09 Dec 2025 12:40:34 +0000

Advanced Python (Full Content)

Topics Covered

Iterators
Generators
Decorators
Closures
Map, Filter, Reduce
*args & **kwargs (Advanced usage)

1. Iterators in Python
An iterator is an object that contains a sequence of values and can be traversed one by one.
Examples:

list
tuple
string
set

Iterator Example
nums = [1, 2, 3, 4]
it = iter(nums)
print(next(it))
print(next(it))

Using Iterator in for loop
for x in nums:
print(x)

Custom Iterator Class
class Count:
def init(self, max):
self.num = 1
self.max = max
def iter(self):
return self
def next(self):
if self.num <= self.max:
val = self.num
self.num += 1
return val
else:
raise StopIteration
c = Count(5)
for i in c:
print(i)

2. Generators
A generator is a function that returns values one at a time using yield.
*Memory efficient
*Faster than list for large data

Generator Example
def numbers():
yield 1
yield 2
yield 3
for n in numbers():
print(n)

Generator with Loop
def even(n):
for i in range(2, n+1, 2):
yield i
for x in even(10):
print(x)

Difference: return vs yield

return	yield
Ends function	Pauses function
Returns single value	Returns multiple values
Not memory efficient	Memory efficient

3. Decorators
A decorator is a function that modifies another function without changing its code.
Used for:

Logging
Authentication
Timing
Access control

Simple Decorator Example
def my_decorator(func):
def wrapper():
print("Before function")
func()
print("After function")
return wrapper
@my_decorator
def hello():
print("Hello World")
hello()

Decorator with Arguments
def smart_divide(func):
def wrapper(a, b):
if b == 0:
print("Cannot divide by zero")
else:
func(a, b)
return wrapper
@smart_divide
def divide(a, b):
print(a / b)
divide(10, 2)
divide(10, 0)

4. Closures
A closure is a function inside another function that remembers outer variable values.

Closure Example
def outer(x):
def inner(y):
return x + y
return inner
add5 = outer(5)
print(add5(3))

5. map(), filter(), reduce()

Used for functional programming.
map() – Apply function to all elements
nums = [1, 2, 3, 4]
result = list(map(lambda x: x*x, nums))
print(result)

filter() – Select elements
nums = [1, 2, 3, 4, 5]
even = list(filter(lambda x: x % 2 == 0, nums))
print(even)

reduce() – Combine elements
from functools import reduce
nums = [1, 2, 3, 4]
total = reduce(lambda a, b: a+b, nums)
print(total)

6. *args & **kwargs (Advanced)
**args – Multiple positional arguments*
def total(*args):
return sum(args)
print(total(1, 2, 3, 4))

kwargs – Multiple keyword arguments
def details(**kwargs):
for k, v in kwargs.items():
print(k, v)
details(name="Aruna", role="DevOps")

Function with args + kwargs
def func(a, b, *args, **kwargs):
print(a, b)
print(args)
print(kwargs)
func(1, 2, 3, 4, name="Python")

7. Real-Time Use Case (DevOps)
Execution Time Decorator
import time
def timer(func):
def wrapper():
start = time.time()
func()
end = time.time()
print("Execution time:", end-start)
return wrapper
@timer
def task():
time.sleep(2)
task()

Day 18: Python programming

Aruna — Mon, 08 Dec 2025 17:38:34 +0000

*Abstraction & Interface *

1. What is Abstraction?
Abstraction means showing only essential details and hiding implementation.
Real life example:

Driving a car → you only use steering, brake, accelerator
Engine working → hidden

2. Why Abstraction is Needed?
✔ Reduces complexity
✔ Improves security
✔ Improves maintainability
✔ Forces standard structure
✔ Used in real projects

3. Abstract Class
An abstract class:

Cannot create object
Can contain abstract & normal methods
Must be inherited In Python we use abc module.

4. Abstract Base Class (ABC)
from abc import ABC, abstractmethod
Abstract Method
A method without body; must be implemented by child class.

5. Example – Abstract Class
from abc import ABC, abstractmethod
class Shape(ABC):
@abstractmethod
def area(self):
pass

Cannot create object:
s = Shape() # Error

6. Implement Abstract Method in Child Class
class Square(Shape):
def init(self, side):
self.side = side
def area(self):
return self.side * self.side
sq = Square(5)
print(sq.area())

7. Multiple Abstract Methods
class Vehicle(ABC):
@abstractmethod
def start(self):
pass
@abstractmethod
def stop(self):
pass

8. Interface in Python
Python does not have interface keyword like Java.
Abstract class with only abstract methods behaves like an interface.

9. Interface Example
class Bank(ABC):
@abstractmethod
def deposit(self, amt):
pass
@abstractmethod
def withdraw(self, amt):
pass

10. Implementing Interface
class SBI(Bank):
def deposit(self, amt):
print("Deposit:", amt)

def withdraw(self, amt):
    print("Withdraw:", amt)

b = SBI()
b.deposit(5000)
b.withdraw(2000)

11. Abstract Class with Normal Methods
class Employee(ABC):
def office_rules(self):
print("Office time 9AM - 6PM")
@abstractmethod
def salary(self):
pass

12. Child Class Implementation
class Developer(Employee):
def salary(self):
print("Salary: 40,000")
d = Developer()
d.office_rules()
d.salary()

13. Important Rules of Abstraction
✔ Cannot create object of abstract class
✔ All abstract methods must be implemented
✔ Use ABC + abstractmethod
✔ Abstract class may have normal methods
✔ Used for code standards

14. Real-Time Example – Payment System
class Payment(ABC):
@abstractmethod
def pay(self, amount):
pass
class GooglePay(Payment):
def pay(self, amount):
print("Paid", amount, "using GooglePay")
class PhonePe(Payment):
def pay(self, amount):
print("Paid", amount, "using PhonePe")

15. Why Interface/Abstraction in Projects?
✔ Multiple developers work together
✔ Fixed method structure
✔ Easy to update or extend
✔ Safer code
✔ Cleaner architecture