🐍 PYTHON – DAY 43 STUDY MATERIAL
✨ Topic: Introduction to SQLite Database in Python
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📌 What is SQLite?

SQLite is a lightweight database that is stored in a single file.

✔ No server required
✔ Built into Python
✔ Perfect for small applications
Used in:
📱 Mobile apps
💻 Desktop apps
🧠 Prototyping databases

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🔹 Import SQLite Module

SQLite comes built-in with Python.
import sqlite3

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🔹 Creating a Database

import sqlite3
conn = sqlite3.connect("student.db")
print("Database created successfully")
This creates a file student.db

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🔹 Creating a Table

import sqlite3
conn = sqlite3.connect("student.db")
cursor = conn.cursor()
cursor.execute(""" CREATE TABLE student( id INTEGER PRIMARY KEY, name TEXT, age INTEGER ) """)
conn.commit()
conn.close()

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🔹 Inserting Data

import sqlite3
conn = sqlite3.connect("student.db")
cursor = conn.cursor()
cursor.execute("INSERT INTO student VALUES(1,'Soham',20)")
conn.commit()
conn.close()

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🔹 Reading Data

conn = sqlite3.connect("student.db")
cursor = conn.cursor()
cursor.execute("SELECT * FROM student")
rows = cursor.fetchall()
for row in rows:
print(row)

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🔹 Updating Data
cursor.execute( "UPDATE student SET age=21 WHERE id=1"

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🔹 Deleting Data
cursor.execute( "DELETE FROM student WHERE id=1" )

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🧠 Why SQLite is Useful?

✔ Build small database applications
✔ Store app data locally
✔ Practice SQL with Python

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📝 Practice Tasks – Day 43

✔ Create database file
✔ Create student table
✔ Insert 3 records
✔ Display all records
✔ Update a record

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🎯 Day 43 Goal
✔ Connect Python with database
✔ Perform CRUD operations
✔ Understand cursor & commit

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📅 Next Topic – Day 44
🔥 Building Student Management System with SQLite
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🐍 PYTHON – DAY 44 STUDY MATERIAL
✨ Mini Project: Student Management System using SQLite

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📌 Project Goal

Create a simple Student Management System that can:
✔ Add student record
✔ View student records
✔ Update student details
✔ Delete student record
Concepts Used:
✔ SQLite Database
✔ CRUD Operations
✔ Python Functions

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🗄 Step 1: Create Database & Table

import sqlite3
conn = sqlite3.connect("student.db")
cursor = conn.cursor()
cursor.execute(""" CREATE TABLE IF NOT EXISTS student( id INTEGER PRIMARY KEY, name TEXT, age INTEGER, course TEXT ) """)
conn.commit()

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➕ Step 2: Insert Student Data

def add_student(id, name, age, course):
cursor.execute( "INSERT INTO student VALUES(?,?,?,?)", (id, name, age, course) )
conn.commit()
Example:
add_student(1,"Soham",20,"Python")

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📋 Step 3: View Students

def view_students():
cursor.execute("SELECT * FROM student")
rows = cursor.fetchall()
for row in rows:
print(row)

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✏ Step 4: Update Student

def update_student(id, age):
cursor.execute( "UPDATE student SET age=? WHERE id=?", (age,id) )
conn.commit()

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❌ Step 5: Delete Student

def delete_student(id):
cursor.execute( "DELETE FROM student WHERE id=?", (id,) )
conn.commit()

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🧠 How the System Works?

1️⃣ User adds student
2️⃣ Data stored in database
3️⃣ User can view/update/delete records
Real-world concept:
✔ Database CRUD operations

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🎨 Bonus Improvements

✔ Add menu system
✔ Add input validation
✔ Connect with Tkinter GUI
✔ Export data to CSV

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📝 Practice Tasks – Day 44

✔ Create student database
✔ Insert 5 students
✔ Display all records
✔ Update one record
✔ Delete one record

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🎯 Day 44 Goal
✔ Build database project
✔ Understand CRUD operations
✔ Use SQLite with Python

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📅 Next Topic – Day 45
🔥 Web Scraping using Python (BeautifulSoup)
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🐍 PYTHON – DAY 45 STUDY MATERIAL
✨ Topic: Web Scraping using Python (BeautifulSoup)

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📌 What is Web Scraping?

Web scraping means extracting data from websites automatically using code.
Used for:
✔ Data collection
✔ Price tracking
✔ News aggregation
✔ Market research

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📦 Required Libraries

Install libraries:
pip install requests
pip install beautifulsoup4
Import in Python:
import requests
from bs4 import BeautifulSoup

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🌐 Step 1: Get Website HTML

import requests
url = "https://example.com⁠�"
response = requests.get(url)
html = response.text
print(html)
This fetches the HTML source of the webpage.

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🔎 Step 2: Parse HTML using BeautifulSoup

from bs4 import BeautifulSoup
soup = BeautifulSoup(html, "html.parser")
print(soup.title)
Extracts the title of the webpage.

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🔹 Extract Specific Data

Example: Get all headings
for heading in soup.find_all("h1"):
print(heading.text)

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🔹 Extract Links from Page

for link in soup.find_all("a"):
print(link.get("href"))

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🔹 Extract Paragraph Text

for p in soup.find_all("p"):
print(p.text)

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⚠ Important Note

Always check a website’s robots.txt before scraping.
Some websites do not allow scraping.

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🧠 Real-world Uses of Web Scraping

✔ Job listing collectors
✔ Product price trackers
✔ News aggregators
✔ Social media analysis

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📝 Practice Tasks – Day 45

✔ Fetch website HTML
✔ Extract title
✔ Extract all links
✔ Extract paragraph text

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🎯 Day 45 Goal
✔ Understand web scraping concept
✔ Use BeautifulSoup
✔ Extract structured data

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📅 Next Topic – Day 46
🔥 Automating Tasks with Python (Automation Scripts)
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PYTHON – DAY 46 STUDY MATERIAL
✨ Topic: Automating Tasks with Python

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📌 What is Automation?

Automation means using code to perform repetitive tasks automatically.
Instead of doing work manually, Python can do it faster and automatically.

Examples:
✔ Renaming multiple files
✔ Sending emails automatically
✔ Data backup scripts
✔ Auto downloading files

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📦 Useful Python Modules for Automation

✔ os → File operations
✔ shutil → File moving/copying
✔ schedule → Task scheduling
✔ smtplib → Email automation
✔ pyautogui → Keyboard & mouse automation

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📁 Example 1: List Files in Folder

import os
files = os.listdir()
for file in files:
print(file)
Shows all files in the current directory.

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✏ Example 2: Rename Multiple Files

import os
files = os.listdir()
for i, file in enumerate(files):
os.rename(file, f"file_{i}.txt")
This renames files automatically 🔥

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📂 Example 3: Copy Files Automatically

import shutil
shutil.copy("source.txt", "backup.txt")
Used for file backup automation.

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⏰ Example 4: Schedule Tasks

Install schedule library:
pip install schedule
Example:
import schedule
import time
def job():
print("Task executed")
schedule.every(5).seconds.do(job)
while True:
schedule.run_pending()
time.sleep(1)
Runs task every 5 seconds.

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🧠 Real-world Automation Examples

✔ Auto email sender
✔ Auto report generator
✔ File organizer
✔ Social media automation

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📝 Practice Tasks – Day 46

✔ List files in directory
✔ Rename files automatically
✔ Copy file backup
✔ Schedule a task

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🎯 Day 46 Goal
✔ Understand automation concept
✔ Use OS & file modules
✔ Create simple automation scripts

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📅 Next Topic – Day 47
🔥 Sending Emails using Python
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🐍 PYTHON – DAY 47 STUDY MATERIAL
✨ Topic: Sending Emails using Python

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📌 Why Send Emails with Python?

Python can automate email tasks like:
✔ Sending notifications
✔ Sending reports automatically
✔ Sending OTP messages
✔ Marketing email automation

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📦 Required Module

Python provides built-in module:
smtplib
Used to send emails using SMTP (Simple Mail Transfer Protocol).

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📧 Basic Email Sending Example

import smtplib
sender = "your_email@gmail.com"
receiver = "receiver_email@gmail.com"
password = "your_app_password"
message = "Hello! This email was sent using Python."
server = smtplib.SMTP("smtp.gmail.com", 587)
server.starttls()
server.login(sender, password)
server.sendmail(sender, receiver, message)
server.quit()
print("Email Sent Successfully ✅")

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🔐 Important: Use App Password

For Gmail you must use App Password, not your main password.

Steps:
1️⃣ Go to Google Account
2️⃣ Security → App Passwords
3️⃣ Generate password for Mail
4️⃣ Use that password in Python

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📄 Sending Email with Subject

from email.mime.text import MIMEText
message = MIMEText("Hello from Python!")
message["Subject"] = "Python Email Test"
message["From"] = sender
message["To"] = receiver

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📎 Sending Email with Attachment (Concept)

Modules used:
✔ email
✔ smtplib
✔ MIMEBase

This allows sending:
📄 PDFs
📷 Images
📊 Reports

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🧠 Real-world Uses

✔ Daily report email automation
✔ Alert systems
✔ Customer notifications
✔ Password reset emails

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📝 Practice Tasks – Day 47

✔ Send simple email
✔ Add subject line
✔ Send email to yourself
✔ Try adding attachment

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🎯 Day 47 Goal
✔ Understand SMTP
✔ Send email using Python
✔ Learn email automation basics

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📅 Next Topic – Day 48
🔥 Multithreading in Python
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🐍 PYTHON – DAY 48 STUDY MATERIAL
✨ Topic: Multithreading in Python

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📌 What is Multithreading?

Multithreading allows a program to run multiple tasks at the same time.
Instead of executing tasks one by one, Python can run them concurrently.

Example:
✔ Download multiple files simultaneously
✔ Handle multiple users in a server
✔ Perform background tasks

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⚡ Thread vs Process

Thread → Lightweight task inside a program
Process → Independent running program
Multithreading helps improve performance for many tasks.

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📦 Threading Module

Python provides built-in module:
import threading

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🔹 Creating a Thread

import threading
def task():
print("Thread is running")
t = threading.Thread(target=task)
t.start()
This starts a new thread.

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🔹 Running Multiple Threads

import threading
def task():
print("Thread executed")
t1 = threading.Thread(target=task)
t2 = threading.Thread(target=task)
t1.start()
t2.start()
Both tasks run simultaneously 🔥

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🔹 Using join()

join() makes main program wait for thread to finish.

t1.start()
t1.join()
print("Thread finished")

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🔹 Example with Delay

import threading
import time
def task():
print("Task started")
time.sleep(2)
print("Task completed")
t = threading.Thread(target=task)
t.start()
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🧠 Where Multithreading is Used?

✔ Web servers
✔ Game development
✔ File downloads
✔ Background processing

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📝 Practice Tasks – Day 48

✔ Create one thread
✔ Run two threads
✔ Use join()
✔ Add delay using time.sleep()

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🎯 Day 48 Goal
✔ Understand threading concept
✔ Create and run threads
✔ Improve program efficiency

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📅 Next Topic – Day 49
🔥 Multiprocessing in Python
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🐍 PYTHON – DAY 49 STUDY MATERIAL
✨ Topic: Multiprocessing in Python

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📌 What is Multiprocessing?

Multiprocessing means running multiple processes simultaneously using multiple CPU cores.

Unlike multithreading, each process runs independently.

Example:
✔ Video processing
✔ Large data analysis
✔ Machine learning tasks
✔ High-performance computing

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⚡ Thread vs Process

Thread → Runs inside same program memory
Process → Runs in separate memory space
Multiprocessing uses multiple CPU cores, making programs faster.

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📦 Multiprocessing Module

Python provides built-in module:
import multiprocessing

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🔹 Creating a Process

import multiprocessing
def task():
print("Process running")
p = multiprocessing.Process(target=task)
p.start()
This creates a new process.

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🔹 Running Multiple Processes

import multiprocessing
def task():
print("Process executed")
p1 = multiprocessing.Process(target=task)
p2 = multiprocessing.Process(target=task)
p1.start()
p2.start()
Both processes run in parallel 🔥

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🔹 Using join()

join() waits for process completion.
p1.start()
p1.join()
print("Process finished")

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🔹 Example with CPU Work

import multiprocessing
import time
def task():
for i in range(5):
print("Processing", i)
time.sleep(1)
p = multiprocessing.Process(target=task)
p.start()

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🧠 Where Multiprocessing is Used?

✔ Data science
✔ Machine learning
✔ Image processing
✔ Scientific computing

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📝 Practice Tasks – Day 49

✔ Create a process
✔ Run two processes
✔ Use join()
✔ Add loop processing

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🎯 Day 49 Goal
✔ Understand multiprocessing concept
✔ Run parallel processes
✔ Use multiple CPU cores

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📅 Next Topic – Day 50
🔥 Logging in Python
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🐍 PYTHON – DAY 50 STUDY MATERIAL
✨ Topic: Logging in Python

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📌 What is Logging?

Logging is used to record events that happen while a program runs.
Instead of using print() everywhere, developers use logging to track:

✔ Errors
✔ Warnings
✔ Debug information
✔ Application activity

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📦 Logging Module

Python provides a built-in module:
import logging

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🔹 Basic Logging Example

import logging
logging.basicConfig(level=logging.DEBUG)
logging.debug("Debug message")
logging.info("Information message")
logging.warning("Warning message")
logging.error("Error occurred")
logging.critical("Critical issue")

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📊 Logging Levels

DEBUG → Detailed information
INFO → General program events
WARNING → Something unexpected
ERROR → Program error
CRITICAL → Serious failure

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📁 Logging to a File

import logging
logging.basicConfig( filename="app.log", level=logging.INFO )
logging.info("Application started")
This creates a log file automatically.

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⏰ Logging with Time Format

import logging
logging.basicConfig( filename="app.log", level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s" )
logging.info("Program started")

Example output:
2026-03-16 21:45:22 - INFO - Program started

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🧠 Why Logging is Important?

✔ Debugging large programs
✔ Monitoring applications
✔ Tracking errors in production
✔ Maintaining software systems

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📝 Practice Tasks – Day 50

✔ Use logging instead of print
✔ Create log file
✔ Log errors and warnings
✔ Add time format

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🎯 Day 50 Goal
✔ Understand logging system
✔ Track application events
✔ Improve debugging skills

━━━━━━━━━━━━━━━━━━━

📅 Next Topic – Day 51
🔥 Command Line Arguments in Python
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🐍 PYTHON – DAY 51 STUDY MATERIAL
✨ Topic: Command Line Arguments in Python

━━━━━━━━━━━━━━━━━━

📌 What are Command Line Arguments?

Command line arguments allow you to pass inputs to a Python program when running it from the terminal.

Example:
python script.py Soham
Here Soham is a command line argument.

━━━━━━━━━━━━━━━━━━━

📦 Using sys Module

Python provides a built-in module:
import sys

This module allows access to command line arguments.

━━━━━━━━━━━━━━━━━━━

🔹 Basic Example

import sys
print(sys.argv)
Output example:
['script.py', 'Soham']

Explanation:
sys.argv[0] → script name
sys.argv[1] → first argument

━━━━━━━━━━━━━━━━━━━

🔹 Using Argument in Program

import sys
name = sys.argv[1]
print("Hello", name)

Run command:
python script.py Soham

Output:
Hello Soham

━━━━━━━━━━━━━━━━━━━

🔹 Multiple Arguments

import sys
a = int(sys.argv[1])
b = int(sys.argv[2])
print("Sum:", a + b)

Run:
python script.py 10 20

Output:
Sum: 30

━━━━━━━━━━━━━━━━━━━

⚠ Handling Missing Arguments

import sys
if len(sys.argv) < 2:
print("Please provide an argument")
else:
print("Argument:", sys.argv[1])

━━━━━━━━━━━━━━━━━━━

🧠 Where Command Line Arguments Are Used?

✔ Automation scripts
✔ DevOps tools
✔ System utilities
✔ Data processing scripts

━━━━━━━━━━━━━━━━━━━

📝 Practice Tasks – Day 51

✔ Print command line arguments
✔ Create greeting script
✔ Add two numbers using arguments
✔ Handle missing arguments

━━━━━━━━━━━━━━━━━━━

🎯 Day 51 Goal
✔ Understand command line inputs
✔ Use sys.argv
✔ Build simple CLI tools

━━━━━━━━━━━━━━━━━━━

📅 Next Topic – Day 52
🔥 Introduction to argparse (Professional CLI Tools)
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🐍 PYTHON – DAY 52 STUDY MATERIAL
✨ Topic: argparse – Building Professional CLI Tools
━━━━━━━━━━━━━━━━━━━

📌 What is argparse?

argparse is Python’s standard library for building command-line interfaces (CLI).
It helps you:
✔ Parse command-line arguments
✔ Show help messages automatically
✔ Validate user input
✔ Build professional CLI tools

━━━━━━━━━━━━━━━━━━━

📦 Importing argparse
import argparse

━━━━━━━━━━━━━━━━━━━

🔹 Basic Example

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("name")
args = parser.parse_args()
print("Hello", args.name)
Run command:
python script.py Soham

Output:
Hello Soham

━━━━━━━━━━━━━━━━━━━

🔹 Adding Optional Arguments

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--age", type=int)
args = parser.parse_args()
print("Age:", args.age)
Run command:
python script.py --age 20

━━━━━━━━━━━━━━━━━━━

🔹 Adding Help Description

parser = argparse.ArgumentParser( description="Simple CLI Program" )
Running this command shows help:
python script.py --help
It displays all arguments automatically 📖

━━━━━━━━━━━━━━━━━━━

🔹 Multiple Arguments Example

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("num1", type=int)
parser.add_argument("num2", type=int)
args = parser.parse_args()
print("Sum:", args.num1 + args.num2)
Run command:
python script.py 10 5
Output:
Sum: 15

━━━━━━━━━━━━━━━━━━━

🧠 Where argparse is Used?

✔ DevOps scripts
✔ Data processing tools
✔ Automation utilities
✔ Command-line applications

━━━━━━━━━━━━━━━━━━━

📝 Practice Tasks – Day 52

✔ Create CLI greeting tool
✔ Add optional argument
✔ Create CLI calculator
✔ Use help command

━━━━━━━━━━━━━━━━━━━

🎯 Day 52 Goal
✔ Understand argparse module
✔ Build professional CLI programs
✔ Improve command-line scripting skills

━━━━━━━━━━━━━━━━━━━

📅 Next Topic – Day 53
🔥 Environment Variables in Python
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🐍 PYTHON – DAY 53 STUDY MATERIAL
✨ Topic: Environment Variables in Python

━━━━━━━━━━━━━━━━━━━

📌 What are Environment Variables?

Environment variables are external values stored in the operating system that programs can access.

They are used to store:
✔ API keys
✔ Database credentials
✔ Configuration settings
✔ Secret tokens
This helps keep sensitive data secure.

━━━━━━━━━━━━━━━━━━━

📦 Using os Module

Python provides the os module to access environment variables.
import os

━━━━━━━━━━━━━━━━━━━

🔹 Reading an Environment Variable

import os
api_key = os.getenv("API_KEY")
print(api_key)
If the variable exists → value is returned
If not → returns None

━━━━━━━━━━━━━━━━━━━

🔹 Setting Environment Variable (Temporarily)

Windows:
set API_KEY=12345

Mac/Linux:
export API_KEY=12345
Then run Python program.

━━━━━━━━━━━━━━━━━━━

🔹 Providing Default Value

import os
api_key = os.getenv("API_KEY", "DefaultKey")
print(api_key)
If variable is missing → DefaultKey will be used.

━━━━━━━━━━━━━━━━━━━

📁 Using .env Files (Best Practice)

Install library:
pip install python-dotenv

Example:
API_KEY=12345
DB_PASSWORD=secret

Python code:
from dotenv import load_dotenv
import os
load_dotenv()
print(os.getenv("API_KEY"))

━━━━━━━━━━━━━━━━━━━

🧠 Why Environment Variables are Important?

✔ Secure application configuration
✔ Protect sensitive data
✔ Used in deployment & cloud platforms

━━━━━━━━━━━━━━━━━━━

📝 Practice Tasks – Day 53

✔ Create environment variable
✔ Read variable in Python
✔ Use default value
✔ Create .env file

━━━━━━━━━━━━━━━━━━━

🎯 Day 53 Goal
✔ Understand environment variables
✔ Protect sensitive information
✔ Manage application configuration

━━━━━━━━━━━━━━━━━━━

📅 Next Topic – Day 54
🔥 Introduction to REST API Development using Flask
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🐍 PYTHON – DAY 54 STUDY MATERIAL
✨ Topic: Introduction to REST API Development using Flask

━━━━━━━━━━━━━━━━━━━
📌 What is Flask?

Flask is a lightweight Python web framework used to build:
✔ Web applications
✔ REST APIs
✔ Backend services

It is simple, flexible, and widely used in Python backend development.

━━━━━━━━━━━━━━━━━━━

📦 Install Flask

pip install flask
Import in Python:
from flask import Flask

━━━━━━━━━━━━━━━━━━━

🖥 Creating First Flask App

from flask import Flask
app = Flask(name)
@app.route("/")
def home():
return "Hello, Flask API!"
app.run(debug=True)

Run the program and open browser:
http://127.0.0.1:5000

━━━━━━━━━━━━━━━━━━━

🌐 Creating API Endpoint

from flask import Flask, jsonify
app = Flask(name)
@app.route("/api")
def api():
data = {"message": "Hello API"}
return jsonify(data)
app.run(debug=True)

Output:
{ "message": "Hello API" }

━━━━━━━━━━━━━━━━━━━

🔹 Handling URL Parameters

@app.route("/user/")
def user(name):
return "Hello " + name
Example:
http://127.0.0.1:5000/user/Soham

Output:
Hello Soham

━━━━━━━━━━━━━━━━━━━

🔹 Handling JSON Request (POST)

from flask import request
@app.route("/data", methods=["POST"])
def receive():
data = request.json
return {"received": data}

━━━━━━━━━━━━━━━━━━━
🧠 Where Flask APIs Are Used?

✔ Mobile app backends
✔ Web application backends
✔ AI model APIs
✔ Microservices architecture

━━━━━━━━━━━━━━━━━━━

📝 Practice Tasks – Day 54

✔ Install Flask
✔ Create simple API
✔ Return JSON response
✔ Use URL parameter

━━━━━━━━━━━━━━━━━━━

🎯 Day 54 Goal
✔ Understand Flask framework
✔ Create simple REST API
✔ Handle requests and responses

━━━━━━━━━━━━━━━━━━━

📅 Next Topic – Day 55
🔥 Connecting Flask with Database (SQLite)
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🐍 PYTHON – DAY 55 STUDY MATERIAL
✨ Topic: Connecting Flask with SQLite Database

━━━━━━━━━━━━━━━━━━━

📌 Goal

Build a simple Flask API that stores and retrieves data from SQLite database.
Concepts used:
✔ Flask API
✔ SQLite Database
✔ JSON responses
✔ CRUD operations

━━━━━━━━━━━━━━━━━━━

📦 Import Required Modules

from flask import Flask, request, jsonify
import sqlite3
app = Flask(name)

━━━━━━━━━━━━━━━━━━━

🗄 Create Database Connection

def get_db():
conn = sqlite3.connect("student.db")
conn.row_factory = sqlite3.Row
return conn

━━━━━━━━━━━━━━━━━━━

➕ API: Add Student

@app.route("/add", methods=["POST"])
def add_student():
data = request.json
conn = get_db()
conn.execute(
"INSERT INTO student(name,age) VALUES(?,?)",
(data["name"], data["age"])
)
conn.commit()
conn.close()

return {"message": "Student added"}

━━━━━━━━━━━━━━━━━━━

📋 API: Get All Students

@app.route("/students")
def get_students():
conn = get_db()
students = conn.execute(
"SELECT * FROM student"
).fetchall()

conn.close()

return jsonify([dict(row) for row in students])

━━━━━━━━━━━━━━━━━━━

🔍 API: Get Student by ID

@app.route("/student/int:id")
def get_student(id):
conn = get_db()
student = conn.execute(
"SELECT * FROM student WHERE id=?",
(id,)
).fetchone()

conn.close()

return jsonify(dict(student))

━━━━━━━━━━━━━━━━━━━

🚀 Run Flask Application

if name == "main":
app.run(debug=True)

━━━━━━━━━━━━━━━━━━━

🧠 What You Learned Today

✔ Connect Flask with SQLite
✔ Create REST APIs with database
✔ Return JSON responses

━━━━━━━━━━━━━━━━━━━

📝 Practice Tasks – Day 55

✔ Create student API
✔ Insert student data
✔ Fetch all students
✔ Fetch student by ID
━━━━━━━━━━━━━━━━━━━

🎯 Day 55 Goal
✔ Build backend API with database
✔ Perform CRUD using Flask
✔ Understand backend architecture

━━━━━━━━━━━━━━━━━━━

📅 Next Topic – Day 56
🔥 Authentication System in Flask (Login API)
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