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5 Practical Python Scripts for Everyday Tasks: Boost Productivity with Automation

Python’s simplicity and vast ecosystem of libraries make it ideal for automating repetitive tasks. Whether you’re a developer, data analyst, or casual user, these 5 scripts solve common problems efficiently. Let’s dive into each with code examples and use cases.

  1. File Organizer: Sort Files by Extension Problem: Cluttered downloads or desktop folders with mixed file types (PDFs, images, docs). Solution: A script that automatically moves files into subfolders based on their extensions.

python
import os
import shutil

def organize_files(directory):
# Supported file types and their target folders
folders = {
'images': ['.jpg', '.jpeg', '.png', '.gif'],
'documents': ['.pdf', '.docx', '.txt'],
'archives': ['.zip', '.rar', '.tar'],
'code': ['.py', '.js', '.html', '.css']
}

# Create folders if they don't exist

for folder in folders.keys():

    os.makedirs(os.path.join(directory, folder), exist_ok=True)


  
  
  Move files




for filename in os.listdir(directory):

    file_path = os.path.join(directory, filename)

    if os.path.isfile(file_path):

        for folder, extensions in folders.items():

            if any(filename.lower().endswith(ext) for ext in extensions):

                shutil.move(file_path, os.path.join(directory, folder, filename))

                break
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Usage

organize_files(r'C:\Users\YourName\Downloads') # Replace with your path
Key Features:

Uses os and shutil for file operations.
Handles multiple file types with a dictionary.
Skips directories and only moves files.

  1. Web Scraper: Extract Product Prices from E-commerce Sites Problem: Manually checking prices across multiple websites is time-consuming. Solution: A script that scrapes product prices using requests and BeautifulSoup.

python
import requests
from bs4 import BeautifulSoup

def scrape_prices(url, product_class):
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
}

try:

    response = requests.get(url, headers=headers)

    soup = BeautifulSoup(response.text, 'html.parser')

    prices = soup.find_all(class_=product_class)  # Adjust selector as needed



for price in prices[:5]:  # Print first 5 results
    print(f"Price: {price.get_text(strip=True)}")






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except Exception as e:

    print(f"Error scraping {url}: {e}")
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Example: Scrape Amazon (adjust class name)

scrape_prices('https://www.amazon.com/s?k=laptop', 'a-price-whole')
Key Features:

Includes a User-Agent header to avoid blocking.
Uses CSS selectors to target price elements.
Error handling for robustness.
Note: Always check a website’s robots.txt and terms of service before scraping.

  1. PDF Merger: Combine Multiple PDFs into One Problem: Merging PDFs manually with Adobe Acrobat is tedious. Solution: A script using PyPDF2 to merge files in seconds.

python
from PyPDF2 import PdfMerger
import os

def merge_pdfs(folder_path, output_filename):
merger = PdfMerger()

for filename in os.listdir(folder_path):

    if filename.lower().endswith('.pdf'):

        file_path = os.path.join(folder_path, filename)

        merger.append(file_path)


merger.write(os.path.join(folder_path, output_filename))

merger.close()

print(f"Merged PDF saved as {output_filename}")
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Usage

merge_pdfs(r'C:\Users\YourName\Documents\PDFs', 'combined.pdf')
Key Features:

Processes all PDFs in a folder recursively.
Preserves original page order.
Lightweight alternative to GUI tools.

  1. Auto Email Sender: Send Personalized Emails at Scale Problem: Sending hundreds of emails manually is error-prone. Solution: A script using smtplib and email.mime to automate bulk emails.

python
import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
import pandas as pd

def send_bulk_emails(csv_path, subject, template):
# Load recipient data (e.g., name, email)
df = pd.read_csv(csv_path)

# SMTP settings (replace with your credentials)

smtp_server = 'smtp.gmail.com'

smtp_port = 587

sender_email = 'your_email@gmail.com'

password = 'your_password'  # Use environment variables in production!


with smtplib.SMTP(smtp_server, smtp_port) as server:

    server.starttls()

    server.login(sender_email, password)




for _, row in df.iterrows():
    msg = MIMEMultipart()
    msg['From'] = sender_email
    msg['To'] = row['email']
    msg['Subject'] = subject

    # Personalize email body
    body = template.format(name=row['name'])
    msg.attach(MIMEText(body, 'plain'))

    server.send_message(msg)
    print(f"Sent to {row['email']}")






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Example usage

template = """Hi {name},

Thank you for your interest in our service!

Best regards,
Team"""

send_bulk_emails('recipients.csv', 'Welcome Offer', template)
Key Features:

Uses Pandas for CSV handling.
Supports HTML/plain text emails.
Secure TLS encryption for SMTP.
Security Tip: Store credentials in environment variables or a .env file.

  1. Password Generator: Create Strong, Random Passwords Problem: Weak passwords compromise security. Solution: A script generating cryptographically secure passwords with secrets.

python
import secrets
import string

def generate_password(length=12, use_symbols=True):
chars = string.ascii_letters + string.digits
if use_symbols:
chars += '!@#$%^&*'

password = ''.join(secrets.choice(chars) for _ in range(length))

return password
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Generate and print 5 passwords

for _ in range(5):
print(generate_password())
Key Features:

Uses secrets (safer than random for cryptography).
Customizable length and symbol inclusion.
No external dependencies.
Conclusion: Why Automate with Python?
These scripts demonstrate Python’s power in solving everyday problems:

File Organizer: Saves hours of manual sorting.
Web Scraper: Enables price tracking without ads.
PDF Merger: Replaces expensive software.
Email Sender: Streamlines marketing campaigns.
Password Generator: Enhances cybersecurity.
Next Steps:

Modify scripts to fit your workflow (e.g., add GUI with tkinter).
Schedule tasks with cron (Linux) or Task Scheduler (Windows).
Explore libraries like openpyxl (Excel), selenium (browser automation), or fastapi (API development).
Happy automating! 🚀

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