PYTHON – DAY 46 STUDY MATERIAL
✨ Topic: Automating Tasks with Python
━━━━━━━━━━━━━━━━━━━
📌 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
━━━━━━━━━━━━━━━━━━━
📦 Useful Python Modules for Automation
✔ os → File operations
✔ shutil → File moving/copying
✔ schedule → Task scheduling
✔ smtplib → Email automation
✔ pyautogui → Keyboard & mouse automation
━━━━━━━━━━━━━━━━━━━
📁 Example 1: List Files in Folder
import os
files = os.listdir()
for file in files:
print(file)
Shows all files in the current directory.
━━━━━━━━━━━━━━━━━━━
✏ 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 🔥
━━━━━━━━━━━━━━━━━━━
📂 Example 3: Copy Files Automatically
import shutil
shutil.copy("source.txt", "backup.txt")
Used for file backup automation.
━━━━━━━━━━━━━━━━━━━
⏰ 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.
━━━━━━━━━━━━━━━━━━━
🧠 Real-world Automation Examples
✔ Auto email sender
✔ Auto report generator
✔ File organizer
✔ Social media automation
━━━━━━━━━━━━━━━━━━━
📝 Practice Tasks – Day 46
✔ List files in directory
✔ Rename files automatically
✔ Copy file backup
✔ Schedule a task
━━━━━━━━━━━━━━━━━━━
🎯 Day 46 Goal
✔ Understand automation concept
✔ Use OS & file modules
✔ Create simple automation scripts
━━━━━━━━━━━━━━━━━━━
📅 Next Topic – Day 47
🔥 Sending Emails using Python
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
✨ Topic: Automating Tasks with Python
━━━━━━━━━━━━━━━━━━━
📌 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
━━━━━━━━━━━━━━━━━━━
📦 Useful Python Modules for Automation
✔ os → File operations
✔ shutil → File moving/copying
✔ schedule → Task scheduling
✔ smtplib → Email automation
✔ pyautogui → Keyboard & mouse automation
━━━━━━━━━━━━━━━━━━━
📁 Example 1: List Files in Folder
import os
files = os.listdir()
for file in files:
print(file)
Shows all files in the current directory.
━━━━━━━━━━━━━━━━━━━
✏ 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 🔥
━━━━━━━━━━━━━━━━━━━
📂 Example 3: Copy Files Automatically
import shutil
shutil.copy("source.txt", "backup.txt")
Used for file backup automation.
━━━━━━━━━━━━━━━━━━━
⏰ 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.
━━━━━━━━━━━━━━━━━━━
🧠 Real-world Automation Examples
✔ Auto email sender
✔ Auto report generator
✔ File organizer
✔ Social media automation
━━━━━━━━━━━━━━━━━━━
📝 Practice Tasks – Day 46
✔ List files in directory
✔ Rename files automatically
✔ Copy file backup
✔ Schedule a task
━━━━━━━━━━━━━━━━━━━
🎯 Day 46 Goal
✔ Understand automation concept
✔ Use OS & file modules
✔ Create simple automation scripts
━━━━━━━━━━━━━━━━━━━
📅 Next Topic – Day 47
🔥 Sending Emails using Python
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
🐍 PYTHON – DAY 47 STUDY MATERIAL
✨ Topic: Sending Emails using Python
━━━━━━━━━━━━━━━━━━━
📌 Why Send Emails with Python?
Python can automate email tasks like:
✔ Sending notifications
✔ Sending reports automatically
✔ Sending OTP messages
✔ Marketing email automation
━━━━━━━━━━━━━━━━━━━
📦 Required Module
Python provides built-in module:
smtplib
Used to send emails using SMTP (Simple Mail Transfer Protocol).
━━━━━━━━━━━━━━━━━━━
📧 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 ✅")
━━━━━━━━━━━━━━━━━━━
🔐 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
━━━━━━━━━━━━━━━━━━━
📄 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
━━━━━━━━━━━━━━━━━━━
📎 Sending Email with Attachment (Concept)
Modules used:
✔ email
✔ smtplib
✔ MIMEBase
This allows sending:
📄 PDFs
📷 Images
📊 Reports
━━━━━━━━━━━━━━━━━━━
🧠 Real-world Uses
✔ Daily report email automation
✔ Alert systems
✔ Customer notifications
✔ Password reset emails
━━━━━━━━━━━━━━━━━━━
📝 Practice Tasks – Day 47
✔ Send simple email
✔ Add subject line
✔ Send email to yourself
✔ Try adding attachment
━━━━━━━━━━━━━━━━━━━
🎯 Day 47 Goal
✔ Understand SMTP
✔ Send email using Python
✔ Learn email automation basics
━━━━━━━━━━━━━━━━━━━
📅 Next Topic – Day 48
🔥 Multithreading in Python
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
✨ Topic: Sending Emails using Python
━━━━━━━━━━━━━━━━━━━
📌 Why Send Emails with Python?
Python can automate email tasks like:
✔ Sending notifications
✔ Sending reports automatically
✔ Sending OTP messages
✔ Marketing email automation
━━━━━━━━━━━━━━━━━━━
📦 Required Module
Python provides built-in module:
smtplib
Used to send emails using SMTP (Simple Mail Transfer Protocol).
━━━━━━━━━━━━━━━━━━━
📧 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 ✅")
━━━━━━━━━━━━━━━━━━━
🔐 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
━━━━━━━━━━━━━━━━━━━
📄 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
━━━━━━━━━━━━━━━━━━━
📎 Sending Email with Attachment (Concept)
Modules used:
✔ smtplib
✔ MIMEBase
This allows sending:
📄 PDFs
📷 Images
📊 Reports
━━━━━━━━━━━━━━━━━━━
🧠 Real-world Uses
✔ Daily report email automation
✔ Alert systems
✔ Customer notifications
✔ Password reset emails
━━━━━━━━━━━━━━━━━━━
📝 Practice Tasks – Day 47
✔ Send simple email
✔ Add subject line
✔ Send email to yourself
✔ Try adding attachment
━━━━━━━━━━━━━━━━━━━
🎯 Day 47 Goal
✔ Understand SMTP
✔ Send email using Python
✔ Learn email automation basics
━━━━━━━━━━━━━━━━━━━
📅 Next Topic – Day 48
🔥 Multithreading in Python
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
🐍 PYTHON – DAY 48 STUDY MATERIAL
✨ Topic: Multithreading in Python
━━━━━━━━━━━━━━━━━━━
📌 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
━━━━━━━━━━━━━━━━━━━
⚡ Thread vs Process
Thread → Lightweight task inside a program
Process → Independent running program
Multithreading helps improve performance for many tasks.
━━━━━━━━━━━━━━━━━━━
📦 Threading Module
Python provides built-in module:
import threading
━━━━━━━━━━━━━━━━━━━
🔹 Creating a Thread
import threading
def task():
print("Thread is running")
t = threading.Thread(target=task)
t.start()
This starts a new thread.
━━━━━━━━━━━━━━━━━━━
🔹 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 🔥
━━━━━━━━━━━━━━━━━━━
🔹 Using join()
join() makes main program wait for thread to finish.
t1.start()
t1.join()
print("Thread finished")
━━━━━━━━━━━━━━━━━━━
🔹 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()
━━━━━━━━━━━━━━━━━━━
🧠 Where Multithreading is Used?
✔ Web servers
✔ Game development
✔ File downloads
✔ Background processing
━━━━━━━━━━━━━━━━━━━
📝 Practice Tasks – Day 48
✔ Create one thread
✔ Run two threads
✔ Use join()
✔ Add delay using time.sleep()
━━━━━━━━━━━━━━━━━━━
🎯 Day 48 Goal
✔ Understand threading concept
✔ Create and run threads
✔ Improve program efficiency
━━━━━━━━━━━━━━━━━━━
📅 Next Topic – Day 49
🔥 Multiprocessing in Python
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
✨ Topic: Multithreading in Python
━━━━━━━━━━━━━━━━━━━
📌 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
━━━━━━━━━━━━━━━━━━━
⚡ Thread vs Process
Thread → Lightweight task inside a program
Process → Independent running program
Multithreading helps improve performance for many tasks.
━━━━━━━━━━━━━━━━━━━
📦 Threading Module
Python provides built-in module:
import threading
━━━━━━━━━━━━━━━━━━━
🔹 Creating a Thread
import threading
def task():
print("Thread is running")
t = threading.Thread(target=task)
t.start()
This starts a new thread.
━━━━━━━━━━━━━━━━━━━
🔹 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 🔥
━━━━━━━━━━━━━━━━━━━
🔹 Using join()
join() makes main program wait for thread to finish.
t1.start()
t1.join()
print("Thread finished")
━━━━━━━━━━━━━━━━━━━
🔹 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()
━━━━━━━━━━━━━━━━━━━
🧠 Where Multithreading is Used?
✔ Web servers
✔ Game development
✔ File downloads
✔ Background processing
━━━━━━━━━━━━━━━━━━━
📝 Practice Tasks – Day 48
✔ Create one thread
✔ Run two threads
✔ Use join()
✔ Add delay using time.sleep()
━━━━━━━━━━━━━━━━━━━
🎯 Day 48 Goal
✔ Understand threading concept
✔ Create and run threads
✔ Improve program efficiency
━━━━━━━━━━━━━━━━━━━
📅 Next Topic – Day 49
🔥 Multiprocessing in Python
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
🐍 PYTHON – DAY 49 STUDY MATERIAL
✨ Topic: Multiprocessing in Python
━━━━━━━━━━━━━━━━━━━
📌 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
━━━━━━━━━━━━━━━━━━━
⚡ Thread vs Process
Thread → Runs inside same program memory
Process → Runs in separate memory space
Multiprocessing uses multiple CPU cores, making programs faster.
━━━━━━━━━━━━━━━━━━━
📦 Multiprocessing Module
Python provides built-in module:
import multiprocessing
━━━━━━━━━━━━━━━━━━━
🔹 Creating a Process
import multiprocessing
def task():
print("Process running")
p = multiprocessing.Process(target=task)
p.start()
This creates a new process.
━━━━━━━━━━━━━━━━━━━
🔹 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 🔥
━━━━━━━━━━━━━━━━━━━
🔹 Using join()
join() waits for process completion.
p1.start()
p1.join()
print("Process finished")
━━━━━━━━━━━━━━━━━━━
🔹 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()
━━━━━━━━━━━━━━━━━━━
🧠 Where Multiprocessing is Used?
✔ Data science
✔ Machine learning
✔ Image processing
✔ Scientific computing
━━━━━━━━━━━━━━━━━━━
📝 Practice Tasks – Day 49
✔ Create a process
✔ Run two processes
✔ Use join()
✔ Add loop processing
━━━━━━━━━━━━━━━━━━━
🎯 Day 49 Goal
✔ Understand multiprocessing concept
✔ Run parallel processes
✔ Use multiple CPU cores
━━━━━━━━━━━━━━━━━━━
📅 Next Topic – Day 50
🔥 Logging in Python
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
✨ Topic: Multiprocessing in Python
━━━━━━━━━━━━━━━━━━━
📌 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
━━━━━━━━━━━━━━━━━━━
⚡ Thread vs Process
Thread → Runs inside same program memory
Process → Runs in separate memory space
Multiprocessing uses multiple CPU cores, making programs faster.
━━━━━━━━━━━━━━━━━━━
📦 Multiprocessing Module
Python provides built-in module:
import multiprocessing
━━━━━━━━━━━━━━━━━━━
🔹 Creating a Process
import multiprocessing
def task():
print("Process running")
p = multiprocessing.Process(target=task)
p.start()
This creates a new process.
━━━━━━━━━━━━━━━━━━━
🔹 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 🔥
━━━━━━━━━━━━━━━━━━━
🔹 Using join()
join() waits for process completion.
p1.start()
p1.join()
print("Process finished")
━━━━━━━━━━━━━━━━━━━
🔹 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()
━━━━━━━━━━━━━━━━━━━
🧠 Where Multiprocessing is Used?
✔ Data science
✔ Machine learning
✔ Image processing
✔ Scientific computing
━━━━━━━━━━━━━━━━━━━
📝 Practice Tasks – Day 49
✔ Create a process
✔ Run two processes
✔ Use join()
✔ Add loop processing
━━━━━━━━━━━━━━━━━━━
🎯 Day 49 Goal
✔ Understand multiprocessing concept
✔ Run parallel processes
✔ Use multiple CPU cores
━━━━━━━━━━━━━━━━━━━
📅 Next Topic – Day 50
🔥 Logging in Python
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
🐍 PYTHON – DAY 50 STUDY MATERIAL
✨ Topic: Logging in Python
━━━━━━━━━━━━━━━━━━━
📌 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
━━━━━━━━━━━━━━━━━━━
📦 Logging Module
Python provides a built-in module:
import logging
━━━━━━━━━━━━━━━━━━━
🔹 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")
━━━━━━━━━━━━━━━━━━━
📊 Logging Levels
DEBUG → Detailed information
INFO → General program events
WARNING → Something unexpected
ERROR → Program error
CRITICAL → Serious failure
━━━━━━━━━━━━━━━━━━━
📁 Logging to a File
import logging
logging.basicConfig( filename="app.log", level=logging.INFO )
logging.info("Application started")
This creates a log file automatically.
━━━━━━━━━━━━━━━━━━━
⏰ 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
━━━━━━━━━━━━━━━━━━━
🧠 Why Logging is Important?
✔ Debugging large programs
✔ Monitoring applications
✔ Tracking errors in production
✔ Maintaining software systems
━━━━━━━━━━━━━━━━━━━
📝 Practice Tasks – Day 50
✔ Use logging instead of print
✔ Create log file
✔ Log errors and warnings
✔ Add time format
━━━━━━━━━━━━━━━━━━━
🎯 Day 50 Goal
✔ Understand logging system
✔ Track application events
✔ Improve debugging skills
━━━━━━━━━━━━━━━━━━━
📅 Next Topic – Day 51
🔥 Command Line Arguments in Python
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
✨ Topic: Logging in Python
━━━━━━━━━━━━━━━━━━━
📌 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
━━━━━━━━━━━━━━━━━━━
📦 Logging Module
Python provides a built-in module:
import logging
━━━━━━━━━━━━━━━━━━━
🔹 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")
━━━━━━━━━━━━━━━━━━━
📊 Logging Levels
DEBUG → Detailed information
INFO → General program events
WARNING → Something unexpected
ERROR → Program error
CRITICAL → Serious failure
━━━━━━━━━━━━━━━━━━━
📁 Logging to a File
import logging
logging.basicConfig( filename="app.log", level=logging.INFO )
logging.info("Application started")
This creates a log file automatically.
━━━━━━━━━━━━━━━━━━━
⏰ 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
━━━━━━━━━━━━━━━━━━━
🧠 Why Logging is Important?
✔ Debugging large programs
✔ Monitoring applications
✔ Tracking errors in production
✔ Maintaining software systems
━━━━━━━━━━━━━━━━━━━
📝 Practice Tasks – Day 50
✔ Use logging instead of print
✔ Create log file
✔ Log errors and warnings
✔ Add time format
━━━━━━━━━━━━━━━━━━━
🎯 Day 50 Goal
✔ Understand logging system
✔ Track application events
✔ Improve debugging skills
━━━━━━━━━━━━━━━━━━━
📅 Next Topic – Day 51
🔥 Command Line Arguments in Python
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
🐍 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)
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
✨ 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)
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
🐍 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
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
✨ 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
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
🚀 Top 2 Full Stack Python Django Project with MySQL Database
We offer a complete collection of 2 modern Full Stack Python Django web applications developed using Django, HTML, CSS, JavaScript, and MySQL/SQLite database connectivity. These projects are perfect for computer science students, final-year projects, freelancers, and portfolio building.
🖥️ Code: https://rzp.io/rzp/pydjango-1
🖼️ Output Preview: https://youtu.be/234fQQRKy7E
🌐 Included Projects
1. AI Resume Analyzer & Job Matcher
2. Smart Study Planner with AI
📦 What You Will Get (For Each Project):
• Full Python Source Code (Python Djnago+ MySQL)
• MySQL Database File (.sql)
• Output Screenshots / UI Preview
• Project Documentation (Detailed Report)
• PowerPoint Presentation (PPT)
• User Manual (Step-by-Step Guide)
• README File (Installation + Setup Instructions)
• Well-Structured and Easy-to-Understand Code
Follow For More !
We offer a complete collection of 2 modern Full Stack Python Django web applications developed using Django, HTML, CSS, JavaScript, and MySQL/SQLite database connectivity. These projects are perfect for computer science students, final-year projects, freelancers, and portfolio building.
🖥️ Code: https://rzp.io/rzp/pydjango-1
🖼️ Output Preview: https://youtu.be/234fQQRKy7E
🌐 Included Projects
1. AI Resume Analyzer & Job Matcher
2. Smart Study Planner with AI
📦 What You Will Get (For Each Project):
• Full Python Source Code (Python Djnago+ MySQL)
• MySQL Database File (.sql)
• Output Screenshots / UI Preview
• Project Documentation (Detailed Report)
• PowerPoint Presentation (PPT)
• User Manual (Step-by-Step Guide)
• README File (Installation + Setup Instructions)
• Well-Structured and Easy-to-Understand Code
Follow For More !
🐍 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
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
✨ 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
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
🚀 Top 2 Full Stack Python Django Project with MySQL Database
We offer a complete collection of 2 modern Full Stack Python Django web applications developed using Django, HTML, CSS, JavaScript, and MySQL/SQLite database connectivity. These projects are perfect for computer science students, final-year projects, freelancers, and portfolio building.
🖥️ Code: https://rzp.io/rzp/pydjango-2
🖼️ Output Preview: https://youtu.be/3OvYLoQS2jM
🌐 Included Projects
1. Fake News Detection Platform
2. Online Code Judge System
📦 What You Will Get (For Each Project):
• Full Python Source Code (Python Djnago+ MySQL)
• MySQL Database File (.sql)
• Output Screenshots / UI Preview
• Project Documentation (Detailed Report)
• PowerPoint Presentation (PPT)
• User Manual (Step-by-Step Guide)
• README File (Installation + Setup Instructions)
• Well-Structured and Easy-to-Understand Code
Follow For More !
We offer a complete collection of 2 modern Full Stack Python Django web applications developed using Django, HTML, CSS, JavaScript, and MySQL/SQLite database connectivity. These projects are perfect for computer science students, final-year projects, freelancers, and portfolio building.
🖥️ Code: https://rzp.io/rzp/pydjango-2
🖼️ Output Preview: https://youtu.be/3OvYLoQS2jM
🌐 Included Projects
1. Fake News Detection Platform
2. Online Code Judge System
📦 What You Will Get (For Each Project):
• Full Python Source Code (Python Djnago+ MySQL)
• MySQL Database File (.sql)
• Output Screenshots / UI Preview
• Project Documentation (Detailed Report)
• PowerPoint Presentation (PPT)
• User Manual (Step-by-Step Guide)
• README File (Installation + Setup Instructions)
• Well-Structured and Easy-to-Understand Code
Follow For More !
🐍 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)
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
✨ 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)
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
🐍 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)
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
✨ 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)
✨ Stay Connected | Keep Coding
🚀 TechByWebCoder
Forwarded from Tech by WebCoder
🚀 Programming Roadmaps & Notes Bundle 💻
Get complete guides and notes with detailed explanations:
📘 Android Development Guide (195 Pages)
📘 Artificial Intelligence Guide (126 Pages)
📘 Cloud Computing Guide (171 Pages)
📘 CSS Complete Notes (165 Pages)
📘 DBMS Complete Guide (199 Pages)
📘 HTML Complete Notes (141 Pages)
📘 Java Complete Notes (182 Pages)
📘 PHP Complete Notes (154 Pages)
📘 Python Complete Notes (171 Pages)
📘 React.js Complete Notes (200 Pages)
📘 SQL Complete Notes (129 Pages)
🔥 Includes Step-by-Step Learning Roadmaps + 20+ Programming eBooks
✅ Perfect for Students, Beginners & Developers
✅ Easy PDF Format
✅ Instant Access
💰 Buy Now :- https://rzp.io/rzp/roadmap-1
Get complete guides and notes with detailed explanations:
📘 Android Development Guide (195 Pages)
📘 Artificial Intelligence Guide (126 Pages)
📘 Cloud Computing Guide (171 Pages)
📘 CSS Complete Notes (165 Pages)
📘 DBMS Complete Guide (199 Pages)
📘 HTML Complete Notes (141 Pages)
📘 Java Complete Notes (182 Pages)
📘 PHP Complete Notes (154 Pages)
📘 Python Complete Notes (171 Pages)
📘 React.js Complete Notes (200 Pages)
📘 SQL Complete Notes (129 Pages)
🔥 Includes Step-by-Step Learning Roadmaps + 20+ Programming eBooks
✅ Perfect for Students, Beginners & Developers
✅ Easy PDF Format
✅ Instant Access
💰 Buy Now :- https://rzp.io/rzp/roadmap-1
Forwarded from Tech by WebCoder
🚀 TOP 5 PROJECT COMBO PACK
We offer a complete collection of modern Web Applications, Full Stack Projects, Java Desktop Applications, and React Portfolio Themes developed using the latest technologies like HTML, CSS, JavaScript, React.js, Python Django, Java Swing, MySQL, and SQLite.
🖥️ Code: https://rzp.io/rzp/5combo-1
🖼️ Output Preview: https://youtube.com/playlist?list=PLSEwuxyDOS8vef66gvunbZTSPmRFz7FZj&si=f_v7pGVTtUP_kahr
Project Overview :-
• Full Stack Python Django Web Applications (2 project)
• Java Swing GUI Desktop Applications (5 project)
• React.js Portfolio Themes (5 project)
• Frontend Web Application Projects (10 project)
• Html-Css-Js Project (10 project)
Follow For More !
We offer a complete collection of modern Web Applications, Full Stack Projects, Java Desktop Applications, and React Portfolio Themes developed using the latest technologies like HTML, CSS, JavaScript, React.js, Python Django, Java Swing, MySQL, and SQLite.
🖥️ Code: https://rzp.io/rzp/5combo-1
🖼️ Output Preview: https://youtube.com/playlist?list=PLSEwuxyDOS8vef66gvunbZTSPmRFz7FZj&si=f_v7pGVTtUP_kahr
Project Overview :-
• Full Stack Python Django Web Applications (2 project)
• Java Swing GUI Desktop Applications (5 project)
• React.js Portfolio Themes (5 project)
• Frontend Web Application Projects (10 project)
• Html-Css-Js Project (10 project)
Follow For More !
🚀 Top 2 Full Stack Python Django Project with MySQL Database
We offer a complete collection of 2 modern Full Stack Python Django web applications developed using Django, HTML, CSS, JavaScript, and MySQL/SQLite database connectivity. These projects are perfect for computer science students, final-year projects, freelancers, and portfolio building.
🖥️ Code: https://rzp.io/rzp/pydjango-3
🖼️ Output Preview: https://youtu.be/MMJ8nBTe3N0
🌐 Included Projects
1. AI Code Explainer for Students
2. AI Technical Interview Simulator
📦 What You Will Get (For Each Project):
• Full Python Source Code (Python Djnago+ MySQL)
• MySQL Database File (.sql)
• Output Screenshots / UI Preview
• Project Documentation (Detailed Report)
• PowerPoint Presentation (PPT)
• User Manual (Step-by-Step Guide)
• README File (Installation + Setup Instructions)
• Well-Structured and Easy-to-Understand Code
Follow For More !
We offer a complete collection of 2 modern Full Stack Python Django web applications developed using Django, HTML, CSS, JavaScript, and MySQL/SQLite database connectivity. These projects are perfect for computer science students, final-year projects, freelancers, and portfolio building.
🖥️ Code: https://rzp.io/rzp/pydjango-3
🖼️ Output Preview: https://youtu.be/MMJ8nBTe3N0
🌐 Included Projects
1. AI Code Explainer for Students
2. AI Technical Interview Simulator
📦 What You Will Get (For Each Project):
• Full Python Source Code (Python Djnago+ MySQL)
• MySQL Database File (.sql)
• Output Screenshots / UI Preview
• Project Documentation (Detailed Report)
• PowerPoint Presentation (PPT)
• User Manual (Step-by-Step Guide)
• README File (Installation + Setup Instructions)
• Well-Structured and Easy-to-Understand Code
Follow For More !