🐍 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
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