9 Python Scripts That Automate My Everyday Tasks

Most of us spend hours every week on tasks a computer should be doing: renaming files, resizing images for blog posts, copying data between CSVs and spreadsheets, and sending the same kind of email to the same people with only a few words changed. Each takes five or ten minutes. Across a week, that's hours.

Python scripts can take over the boring parts. Some save 30 seconds. Others save an hour every single week. Once they're written they just work: run them, grab your chai, come back to a finished task.

Here are 9 practical scripts, with full code you can copy, modify, and start running today. Each one is self-contained, so you can drop it into a .py file and go. Where one needs a third-party library, the pip install command is noted.

1. File organizer by extension

My Downloads folder used to look like a warzone. This script scans a folder and moves each file into a subfolder based on its extension, so the PDFs, the screenshots and the random .zip files from three months ago each end up in their own place instead of piled together.

The code

import os
import shutil
from pathlib import Path

def organize_folder(target_dir):
    """Organize files into subfolders based on their extension."""
    target_path = Path(target_dir)

    if not target_path.exists():
        print(f"Directory {target_dir} does not exist.")
        return

    extension_map = {
        'Images': ['.jpg', '.jpeg', '.png', '.gif', '.bmp', '.svg', '.webp'],
        'Documents': ['.pdf', '.doc', '.docx', '.txt', '.xlsx', '.xls', '.pptx', '.csv'],
        'Videos': ['.mp4', '.mkv', '.avi', '.mov', '.wmv', '.flv'],
        'Audio': ['.mp3', '.wav', '.flac', '.aac', '.ogg'],
        'Archives': ['.zip', '.rar', '.7z', '.tar', '.gz'],
        'Code': ['.py', '.js', '.ts', '.html', '.css', '.java', '.cpp', '.c'],
        'Installers': ['.exe', '.msi', '.dmg', '.deb', '.rpm'],
    }

    # Reverse map: extension -> folder name
    ext_to_folder = {}
    for folder, extensions in extension_map.items():
        for ext in extensions:
            ext_to_folder[ext] = folder

    moved_count = 0
    for item in target_path.iterdir():
        if item.is_file():
            ext = item.suffix.lower()
            folder_name = ext_to_folder.get(ext, 'Others')
            dest_folder = target_path / folder_name
            dest_folder.mkdir(exist_ok=True)

            dest_file = dest_folder / item.name
            if dest_file.exists():
                # Add a number suffix to avoid overwriting
                base = item.stem
                counter = 1
                while dest_file.exists():
                    dest_file = dest_folder / f"{base}_{counter}{ext}"
                    counter += 1

            shutil.move(str(item), str(dest_file))
            moved_count += 1
            print(f"Moved: {item.name} -> {folder_name}/")

    print(f"\nDone! Moved {moved_count} files.")

if __name__ == "__main__":
    folder = input("Enter the folder path to organize: ").strip()
    organize_folder(folder)

How to use it

It runs as a scheduled task on my Windows machine every Sunday evening. By Monday the folder is pristine. cron on Linux or launchd on macOS works too. The extension map is easy to customize: add categories or move file types around to match how you think about your files.

2. Bulk image resizer

When I'm writing blog posts or preparing presentations, I constantly need to resize batches of images to a specific width. Doing it one at a time is painful. This script handles a whole folder in seconds.

The code

from PIL import Image
from pathlib import Path

def resize_images(input_dir, output_dir, max_width=800):
    """Resize all images in a folder to a maximum width, preserving aspect ratio."""
    input_path = Path(input_dir)
    output_path = Path(output_dir)
    output_path.mkdir(parents=True, exist_ok=True)

    supported = {'.jpg', '.jpeg', '.png', '.bmp', '.webp'}

    for img_file in input_path.iterdir():
        if img_file.suffix.lower() in supported:
            with Image.open(img_file) as img:
                if img.width > max_width:
                    ratio = max_width / img.width
                    new_height = int(img.height * ratio)
                    img_resized = img.resize((max_width, new_height), Image.LANCZOS)
                else:
                    img_resized = img.copy()

                output_file = output_path / img_file.name
                img_resized.save(output_file, quality=85, optimize=True)
                print(f"Resized: {img_file.name} ({img.width}x{img.height} -> {img_resized.width}x{img_resized.height})")

if __name__ == "__main__":
    src = input("Source folder: ").strip()
    dest = input("Output folder: ").strip()
    width = int(input("Max width (default 800): ").strip() or "800")
    resize_images(src, dest, width)

You'll need Pillow for this:

pip install Pillow

quality=85 with optimize=True is a good balance between file size and visual quality. Below 80 you start seeing compression artifacts, especially on photographs. Going lower isn't worth it.

3. Automated email sender

A weekly status email is a classic example: same recipients, same format, only the bullet points change. This script uses Python's built-in smtplib to send HTML emails through Gmail.

The code

import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
from datetime import datetime

def send_email(sender, password, recipient, subject, body_html):
    """Send an HTML email via Gmail SMTP."""
    msg = MIMEMultipart('alternative')
    msg['From'] = sender
    msg['To'] = recipient
    msg['Subject'] = subject

    html_part = MIMEText(body_html, 'html')
    msg.attach(html_part)

    with smtplib.SMTP_SSL('smtp.gmail.com', 465) as server:
        server.login(sender, password)
        server.send_message(msg)
        print(f"Email sent to {recipient}")

if __name__ == "__main__":
    SENDER = "your.email@gmail.com"
    APP_PASSWORD = "your-16-char-app-password"  # Use Gmail App Password, NOT your regular password

    today = datetime.now().strftime("%B %d, %Y")

    updates = [
        "Completed the API refactoring for the payment module",
        "Fixed 3 critical bugs reported by QA team",
        "Started working on the dashboard redesign",
    ]

    bullet_points = "".join(f"<li>{item}</li>" for item in updates)

    html_body = f"""
    <html>
    <body style="font-family: Arial, sans-serif; line-height: 1.6;">
        <h2>Weekly Status Update - {today}</h2>
        <p>Hi Team,</p>
        <p>Here is my update for this week:</p>
        <ul>{bullet_points}</ul>
        <p>Best regards,<br>Anurag</p>
    </body>
    </html>
    """

    send_email(SENDER, APP_PASSWORD, "team@company.com", f"Weekly Update - {today}", html_body)

Never put your real Gmail password in the script. Go to Google Account settings, enable 2-Step Verification, and generate an App Password, then put that 16-character code into the script, ideally read from an environment variable rather than typed into the file, because hardcoding credentials is terrible practice even for personal scripts that you swear nobody else will ever see.

4. Web scraper for price tracking

I've tracked gadget prices on Amazon and Flipkart for months with this script. It fetches the product page, pulls out the current price, and logs it to a CSV. Then it alerts me when the price drops below my target.

The code

import requests
from bs4 import BeautifulSoup
import csv
from datetime import datetime
from pathlib import Path

def get_price(url, headers):
    """Scrape product price from a webpage."""
    response = requests.get(url, headers=headers)
    soup = BeautifulSoup(response.content, 'html.parser')

    # Amazon India price selector
    price_element = soup.select_one('span.a-price-whole')
    if price_element:
        price_text = price_element.get_text().replace(',', '').replace('.', '').strip()
        return int(price_text)

    # Flipkart price selector (fallback)
    price_element = soup.select_one('div._30jeq3')
    if price_element:
        price_text = price_element.get_text().replace('₹', '').replace(',', '').strip()
        return int(price_text)

    return None

def track_price(url, product_name, target_price):
    """Track price and log to CSV."""
    headers = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 '
                       '(KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36',
        'Accept-Language': 'en-IN,en;q=0.9',
    }

    price = get_price(url, headers)
    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M")

    if price:
        log_file = Path("price_log.csv")
        file_exists = log_file.exists()

        with open(log_file, 'a', newline='') as f:
            writer = csv.writer(f)
            if not file_exists:
                writer.writerow(['Timestamp', 'Product', 'Price (INR)', 'Target', 'Below Target'])
            writer.writerow([timestamp, product_name, price, target_price, price <= target_price])

        print(f"[{timestamp}] {product_name}: ₹{price:,}")

        if price <= target_price:
            print(f"  ALERT: Price is at or below your target of ₹{target_price:,}!")
            return True
    else:
        print(f"Could not fetch price for {product_name}")

    return False

if __name__ == "__main__":
    products = [
        {
            'url': 'https://www.amazon.in/dp/PRODUCT_ID',
            'name': 'Sony WH-1000XM5',
            'target': 22000
        },
    ]

    for product in products:
        track_price(product['url'], product['name'], product['target'])

You'll need:

pip install requests beautifulsoup4

Scrapers break whenever a site changes its HTML. I check this script every couple of weeks and update the CSS selectors if needed. Be respectful too, and don't hit the same page hundreds of times an hour. Once a day via cron has been fine.

5. PDF merger

This one combines multiple PDF files into one, which I need surprisingly often for invoices, scanned documents, and project reports. Order is up to you.

The code

from PyPDF2 import PdfMerger
from pathlib import Path

def merge_pdfs(pdf_list, output_filename="merged_output.pdf"):
    """Merge multiple PDF files into one."""
    merger = PdfMerger()

    for pdf_path in pdf_list:
        path = Path(pdf_path)
        if path.exists() and path.suffix.lower() == '.pdf':
            merger.append(str(path))
            print(f"Added: {path.name}")
        else:
            print(f"Skipped (not found or not PDF): {pdf_path}")

    merger.write(output_filename)
    merger.close()
    print(f"\nMerged PDF saved as: {output_filename}")

def merge_folder(folder_path, output_filename="merged_output.pdf"):
    """Merge all PDFs in a folder, sorted by filename."""
    folder = Path(folder_path)
    pdf_files = sorted(folder.glob("*.pdf"))

    if not pdf_files:
        print("No PDF files found in the folder.")
        return

    print(f"Found {len(pdf_files)} PDF files:")
    for f in pdf_files:
        print(f"  - {f.name}")

    merge_pdfs([str(f) for f in pdf_files], output_filename)

if __name__ == "__main__":
    choice = input("Merge (1) specific files or (2) entire folder? ").strip()

    if choice == '1':
        files = input("Enter PDF file paths (comma-separated): ").strip().split(',')
        files = [f.strip() for f in files]
        output = input("Output filename (default: merged_output.pdf): ").strip() or "merged_output.pdf"
        merge_pdfs(files, output)
    else:
        folder = input("Enter folder path: ").strip()
        output = input("Output filename (default: merged_output.pdf): ").strip() or "merged_output.pdf"
        merge_folder(folder, output)

Install the dependency:

pip install PyPDF2

merge_folder is the one you'll use most. It picks up all PDFs in alphabetical order. Name files with numeric prefixes like 01_intro.pdf, 02_chapter1.pdf and the order takes care of itself.

6. CSV to Excel converter with formatting

Raw CSVs are ugly. When I share data with non-technical colleagues, I convert it to a formatted Excel file with styled headers, auto-adjusted column widths, and alternating row colours.

The code

import pandas as pd
from openpyxl import load_workbook
from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
from pathlib import Path

def csv_to_excel(csv_path, output_path=None):
    """Convert CSV to a formatted Excel file."""
    csv_file = Path(csv_path)
    if output_path is None:
        output_path = csv_file.with_suffix('.xlsx')

    # Read CSV
    df = pd.read_csv(csv_file)

    # Write to Excel
    df.to_excel(output_path, index=False, sheet_name='Data')

    # Now apply formatting
    wb = load_workbook(output_path)
    ws = wb['Data']

    # Header styling
    header_font = Font(bold=True, color="FFFFFF", size=11)
    header_fill = PatternFill(start_color="2563EB", end_color="2563EB", fill_type="solid")
    header_alignment = Alignment(horizontal="center", vertical="center")
    thin_border = Border(
        left=Side(style='thin'),
        right=Side(style='thin'),
        top=Side(style='thin'),
        bottom=Side(style='thin')
    )

    for cell in ws[1]:
        cell.font = header_font
        cell.fill = header_fill
        cell.alignment = header_alignment
        cell.border = thin_border

    # Auto-adjust column widths
    for column in ws.columns:
        max_length = 0
        column_letter = column[0].column_letter
        for cell in column:
            if cell.value:
                max_length = max(max_length, len(str(cell.value)))
            cell.border = thin_border
        adjusted_width = min(max_length + 4, 50)
        ws.column_dimensions[column_letter].width = adjusted_width

    # Alternate row coloring
    light_fill = PatternFill(start_color="F0F7FF", end_color="F0F7FF", fill_type="solid")
    for row_idx, row in enumerate(ws.iter_rows(min_row=2, max_row=ws.max_row), start=2):
        if row_idx % 2 == 0:
            for cell in row:
                cell.fill = light_fill

    wb.save(output_path)
    print(f"Formatted Excel file saved: {output_path}")

if __name__ == "__main__":
    csv_file = input("Enter CSV file path: ").strip()
    csv_to_excel(csv_file)

Dependencies:

pip install pandas openpyxl

The output looks far more professional than it has any right to, and people will assume you're using an expensive reporting tool rather than a short Python script.

7. System backup script

This creates compressed backups of important folders and keeps only the last N, so it doesn't eat all your disk space. Everyone should run something like it.

The code

import shutil
from pathlib import Path
from datetime import datetime

def create_backup(source_dirs, backup_root, max_backups=5):
    """Create a timestamped compressed backup of specified directories."""
    backup_root = Path(backup_root)
    backup_root.mkdir(parents=True, exist_ok=True)

    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")

    for source in source_dirs:
        source_path = Path(source)
        if not source_path.exists():
            print(f"Source not found, skipping: {source}")
            continue

        folder_name = source_path.name
        archive_name = f"{folder_name}_{timestamp}"
        archive_path = backup_root / archive_name

        print(f"Backing up: {source_path} ...")
        shutil.make_archive(
            str(archive_path),
            'zip',
            root_dir=str(source_path.parent),
            base_dir=source_path.name
        )

        archive_size = Path(f"{archive_path}.zip").stat().st_size / (1024 * 1024)
        print(f"  Created: {archive_name}.zip ({archive_size:.1f} MB)")

    # Cleanup old backups
    cleanup_old_backups(backup_root, max_backups)

def cleanup_old_backups(backup_root, max_backups):
    """Remove old backups, keeping only the most recent ones per source folder."""
    all_zips = sorted(backup_root.glob("*.zip"), key=lambda f: f.stat().st_mtime, reverse=True)

    # Group by source folder name (everything before the timestamp)
    from collections import defaultdict
    groups = defaultdict(list)
    for zip_file in all_zips:
        # Extract the folder name part (before _YYYYMMDD_HHMMSS)
        parts = zip_file.stem.rsplit('_', 2)
        if len(parts) >= 3:
            group_name = parts[0]
        else:
            group_name = zip_file.stem
        groups[group_name].append(zip_file)

    for group_name, files in groups.items():
        if len(files) > max_backups:
            for old_file in files[max_backups:]:
                old_file.unlink()
                print(f"  Removed old backup: {old_file.name}")

if __name__ == "__main__":
    folders_to_backup = [
        r"C:\Users\anurag\Documents\Projects",
        r"C:\Users\anurag\Documents\Notes",
        r"C:\Users\anurag\Desktop\WorkFiles",
    ]

    backup_destination = r"D:\Backups"

    create_backup(folders_to_backup, backup_destination, max_backups=5)
    print("\nBackup complete!")

It uses only the standard library. Schedule it nightly, for example at 11 PM via Windows Task Scheduler or cron. max_backups=5 keeps the five most recent backups per folder and deletes older ones automatically, so you set it up once and forget about it.

8. WhatsApp message scheduler (concept)

Automating WhatsApp is a gray area. WhatsApp doesn't officially support bots for personal accounts, and unofficial APIs can get your number banned. This concept script using pywhatkit is still handy for one-off scheduled messages, as long as you use it responsibly.

The code

import pywhatkit as kit
from datetime import datetime, timedelta

def schedule_whatsapp_message(phone_number, message, send_time=None):
    """
    Schedule a WhatsApp message using pywhatkit.
    phone_number should include country code (e.g., +91XXXXXXXXXX)
    send_time is a datetime object; if None, sends 2 minutes from now.
    """
    if send_time is None:
        send_time = datetime.now() + timedelta(minutes=2)

    hour = send_time.hour
    minute = send_time.minute

    print(f"Scheduling message to {phone_number} at {hour:02d}:{minute:02d}")
    print(f"Message: {message}")

    kit.sendwhatmsg(
        phone_no=phone_number,
        message=message,
        time_hour=hour,
        time_min=minute,
        wait_time=15,
        tab_close=True
    )
    print("Message sent successfully!")

if __name__ == "__main__":
    # Example: Send birthday wishes at midnight
    schedule_whatsapp_message(
        phone_number="+919876543210",
        message="Happy Birthday! 🎂 Wishing you an amazing year ahead!",
        send_time=datetime(2026, 2, 15, 0, 0)  # Feb 15 at midnight
    )

pip install pywhatkit

It works by opening WhatsApp Web in your browser and typing the message for you, so you need to be logged into WhatsApp Web with your computer running at the scheduled time. It isn't elegant. For birthday wishes, it works. Anything serious? Use the WhatsApp Business API, the official route.

9. Password generator

Yes, password managers can generate passwords. Sometimes, though, you need a quick batch of strong ones for test accounts, temporary access, or offline storage, and this script generates them with customizable rules.

The code

import secrets
import string
from typing import Optional

def generate_password(
    length: int = 20,
    uppercase: bool = True,
    lowercase: bool = True,
    digits: bool = True,
    special: bool = True,
    exclude_ambiguous: bool = True,
    min_uppercase: int = 1,
    min_digits: int = 1,
    min_special: int = 1
) -> str:
    """Generate a cryptographically secure password."""

    chars = ""
    if lowercase:
        chars += string.ascii_lowercase
    if uppercase:
        chars += string.ascii_uppercase
    if digits:
        chars += string.digits
    if special:
        chars += "!@#$%^&*()-_=+[]{}|;:,.<>?"

    if exclude_ambiguous:
        ambiguous = "0OoIl1"
        chars = ''.join(c for c in chars if c not in ambiguous)

    if not chars:
        raise ValueError("At least one character type must be enabled")

    # Keep generating until all minimums are met
    while True:
        password = ''.join(secrets.choice(chars) for _ in range(length))

        has_upper = sum(1 for c in password if c in string.ascii_uppercase) >= min_uppercase
        has_digit = sum(1 for c in password if c in string.digits) >= min_digits
        has_special = sum(1 for c in password if c in "!@#$%^&*()-_=+[]{}|;:,.<>?") >= min_special

        if has_upper and has_digit and has_special:
            return password

def generate_batch(count: int = 10, **kwargs) -> list:
    """Generate multiple passwords."""
    return [generate_password(**kwargs) for _ in range(count)]

if __name__ == "__main__":
    print("=== Password Generator ===\n")

    count = int(input("How many passwords? (default 5): ").strip() or "5")
    length = int(input("Password length? (default 20): ").strip() or "20")

    passwords = generate_batch(count=count, length=length)

    print(f"\nGenerated {count} passwords ({length} chars each):\n")
    for i, pwd in enumerate(passwords, 1):
        print(f"  {i}. {pwd}")

    # Calculate entropy
    import math
    charset_size = 72  # approximate usable charset after ambiguous removal
    entropy = length * math.log2(charset_size)
    print(f"\n  Estimated entropy: {entropy:.0f} bits")
    print(f"  (128+ bits is considered very strong)")

It uses Python's secrets module rather than random. That matters. random isn't cryptographically secure because it relies on a predictable pseudorandom number generator, while secrets pulls from your OS's cryptographic random source, so the passwords are truly unpredictable. The exclude_ambiguous flag removes characters like 0/O and 1/l/I that look alike in many fonts, which is a lifesaver when you have to read a password aloud or type it by hand.

How I keep them organized

All my automation scripts live in one folder, ~/scripts/, with a simple naming convention:

Script	Filename	Schedule
File Organizer	`organize_downloads.py`	Weekly (Sunday 8 PM)
Image Resizer	`resize_images.py`	On demand
Email Sender	`weekly_update.py`	Weekly (Friday 5 PM)
Price Tracker	`track_prices.py`	Daily (9 AM)
PDF Merger	`merge_pdfs.py`	On demand
CSV to Excel	`csv_to_xlsx.py`	On demand
System Backup	`backup.py`	Daily (11 PM)
WhatsApp Scheduler	`wa_schedule.py`	On demand
Password Generator	`gen_passwords.py`	On demand

Scheduled scripts run through Windows Task Scheduler on Windows or cron on Linux and macOS. A good editor helps. Our best VS Code extensions for 2026 list includes several that noticeably speed up Python development. Send all output to log files so you can check when something goes wrong:

# Example cron entry (Linux)
0 9 * * * /usr/bin/python3 /home/anurag/scripts/track_prices.py >> /home/anurag/scripts/logs/price_tracker.log 2>&1

Tips I've learned the hard way

Keep scripts simple. The best automation scripts are the ones you can read six months later and understand immediately, so resist the urge to over-engineer them.

Add error handling. A script that crashes silently is worse than no script, so at minimum wrap the main logic in a try-except and log the error somewhere, even if it is only a plain text file sitting in the same folder as the script itself.

Prefer pathlib over os.path. It's cleaner, and there's almost no reason to use os.path.join() anymore when Path(folder) / "subfolder" / "file.txt" exists.

Store secrets properly. Use environment variables or a .env file with python-dotenv for API keys, passwords, and other sensitive data, and never hardcode them, even for "personal use only." Habits matter more than intent.

Put your scripts under version control. I keep my scripts folder in a private Git repo. It's saved me more than once. If you're not comfortable with Git yet, our Git and GitHub mastery guide covers everything you'd need.

Start with whatever annoys you

Automation pays back fast. A script like the file organizer takes maybe 30 minutes to write and keeps saving time for years, and a price tracker catches deals you'd otherwise miss.

You don't need to be an advanced Python developer to write scripts like these. Most of them are plain loops, conditionals and file operations plus a few well-chosen libraries. Python has a library for almost anything you'd want to automate. That's a big reason it consistently tops the charts among the most popular programming languages. If you're running scripts on a Linux server, our Linux for developers guide covers the command-line basics that make managing cron jobs much easier.

Pick the task that annoys you most, the one where you think "ugh, I have to do this again?" That's your first automation candidate. Write it. Test it a few times, then schedule it or keep it within reach. Once you've had that specific satisfaction of a task finishing while you were making coffee, you'll start noticing automation opportunities everywhere. It's a little addictive.

1. File organizer by extension

The code

import os
import shutil
from pathlib import Path

def organize_folder(target_dir):
    """Organize files into subfolders based on their extension."""
    target_path = Path(target_dir)

    if not target_path.exists():
        print(f"Directory {target_dir} does not exist.")
        return

    extension_map = {
        'Images': ['.jpg', '.jpeg', '.png', '.gif', '.bmp', '.svg', '.webp'],
        'Documents': ['.pdf', '.doc', '.docx', '.txt', '.xlsx', '.xls', '.pptx', '.csv'],
        'Videos': ['.mp4', '.mkv', '.avi', '.mov', '.wmv', '.flv'],
        'Audio': ['.mp3', '.wav', '.flac', '.aac', '.ogg'],
        'Archives': ['.zip', '.rar', '.7z', '.tar', '.gz'],
        'Code': ['.py', '.js', '.ts', '.html', '.css', '.java', '.cpp', '.c'],
        'Installers': ['.exe', '.msi', '.dmg', '.deb', '.rpm'],
    }

    # Reverse map: extension -> folder name
    ext_to_folder = {}
    for folder, extensions in extension_map.items():
        for ext in extensions:
            ext_to_folder[ext] = folder

    moved_count = 0
    for item in target_path.iterdir():
        if item.is_file():
            ext = item.suffix.lower()
            folder_name = ext_to_folder.get(ext, 'Others')
            dest_folder = target_path / folder_name
            dest_folder.mkdir(exist_ok=True)

            dest_file = dest_folder / item.name
            if dest_file.exists():
                # Add a number suffix to avoid overwriting
                base = item.stem
                counter = 1
                while dest_file.exists():
                    dest_file = dest_folder / f"{base}_{counter}{ext}"
                    counter += 1

            shutil.move(str(item), str(dest_file))
            moved_count += 1
            print(f"Moved: {item.name} -> {folder_name}/")

    print(f"\nDone! Moved {moved_count} files.")

if __name__ == "__main__":
    folder = input("Enter the folder path to organize: ").strip()
    organize_folder(folder)

How to use it

2. Bulk image resizer

The code

from PIL import Image
from pathlib import Path

def resize_images(input_dir, output_dir, max_width=800):
    """Resize all images in a folder to a maximum width, preserving aspect ratio."""
    input_path = Path(input_dir)
    output_path = Path(output_dir)
    output_path.mkdir(parents=True, exist_ok=True)

    supported = {'.jpg', '.jpeg', '.png', '.bmp', '.webp'}

    for img_file in input_path.iterdir():
        if img_file.suffix.lower() in supported:
            with Image.open(img_file) as img:
                if img.width > max_width:
                    ratio = max_width / img.width
                    new_height = int(img.height * ratio)
                    img_resized = img.resize((max_width, new_height), Image.LANCZOS)
                else:
                    img_resized = img.copy()

                output_file = output_path / img_file.name
                img_resized.save(output_file, quality=85, optimize=True)
                print(f"Resized: {img_file.name} ({img.width}x{img.height} -> {img_resized.width}x{img_resized.height})")

if __name__ == "__main__":
    src = input("Source folder: ").strip()
    dest = input("Output folder: ").strip()
    width = int(input("Max width (default 800): ").strip() or "800")
    resize_images(src, dest, width)

You'll need Pillow for this:

pip install Pillow

quality=85 with optimize=True is a good balance between file size and visual quality. Below 80 you start seeing compression artifacts, especially on photographs. Going lower isn't worth it.

3. Automated email sender

A weekly status email is a classic example: same recipients, same format, only the bullet points change. This script uses Python's built-in smtplib to send HTML emails through Gmail.

The code

import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
from datetime import datetime

def send_email(sender, password, recipient, subject, body_html):
    """Send an HTML email via Gmail SMTP."""
    msg = MIMEMultipart('alternative')
    msg['From'] = sender
    msg['To'] = recipient
    msg['Subject'] = subject

    html_part = MIMEText(body_html, 'html')
    msg.attach(html_part)

    with smtplib.SMTP_SSL('smtp.gmail.com', 465) as server:
        server.login(sender, password)
        server.send_message(msg)
        print(f"Email sent to {recipient}")

if __name__ == "__main__":
    SENDER = "your.email@gmail.com"
    APP_PASSWORD = "your-16-char-app-password"  # Use Gmail App Password, NOT your regular password

    today = datetime.now().strftime("%B %d, %Y")

    updates = [
        "Completed the API refactoring for the payment module",
        "Fixed 3 critical bugs reported by QA team",
        "Started working on the dashboard redesign",
    ]

    bullet_points = "".join(f"<li>{item}</li>" for item in updates)

    html_body = f"""
    <html>
    <body style="font-family: Arial, sans-serif; line-height: 1.6;">
        <h2>Weekly Status Update - {today}</h2>
        <p>Hi Team,</p>
        <p>Here is my update for this week:</p>
        <ul>{bullet_points}</ul>
        <p>Best regards,<br>Anurag</p>
    </body>
    </html>
    """

    send_email(SENDER, APP_PASSWORD, "team@company.com", f"Weekly Update - {today}", html_body)

4. Web scraper for price tracking

The code

import requests
from bs4 import BeautifulSoup
import csv
from datetime import datetime
from pathlib import Path

def get_price(url, headers):
    """Scrape product price from a webpage."""
    response = requests.get(url, headers=headers)
    soup = BeautifulSoup(response.content, 'html.parser')

    # Amazon India price selector
    price_element = soup.select_one('span.a-price-whole')
    if price_element:
        price_text = price_element.get_text().replace(',', '').replace('.', '').strip()
        return int(price_text)

    # Flipkart price selector (fallback)
    price_element = soup.select_one('div._30jeq3')
    if price_element:
        price_text = price_element.get_text().replace('₹', '').replace(',', '').strip()
        return int(price_text)

    return None

def track_price(url, product_name, target_price):
    """Track price and log to CSV."""
    headers = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 '
                       '(KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36',
        'Accept-Language': 'en-IN,en;q=0.9',
    }

    price = get_price(url, headers)
    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M")

    if price:
        log_file = Path("price_log.csv")
        file_exists = log_file.exists()

        with open(log_file, 'a', newline='') as f:
            writer = csv.writer(f)
            if not file_exists:
                writer.writerow(['Timestamp', 'Product', 'Price (INR)', 'Target', 'Below Target'])
            writer.writerow([timestamp, product_name, price, target_price, price <= target_price])

        print(f"[{timestamp}] {product_name}: ₹{price:,}")

        if price <= target_price:
            print(f"  ALERT: Price is at or below your target of ₹{target_price:,}!")
            return True
    else:
        print(f"Could not fetch price for {product_name}")

    return False

if __name__ == "__main__":
    products = [
        {
            'url': 'https://www.amazon.in/dp/PRODUCT_ID',
            'name': 'Sony WH-1000XM5',
            'target': 22000
        },
    ]

    for product in products:
        track_price(product['url'], product['name'], product['target'])

You'll need:

pip install requests beautifulsoup4

5. PDF merger

This one combines multiple PDF files into one, which I need surprisingly often for invoices, scanned documents, and project reports. Order is up to you.

The code

from PyPDF2 import PdfMerger
from pathlib import Path

def merge_pdfs(pdf_list, output_filename="merged_output.pdf"):
    """Merge multiple PDF files into one."""
    merger = PdfMerger()

    for pdf_path in pdf_list:
        path = Path(pdf_path)
        if path.exists() and path.suffix.lower() == '.pdf':
            merger.append(str(path))
            print(f"Added: {path.name}")
        else:
            print(f"Skipped (not found or not PDF): {pdf_path}")

    merger.write(output_filename)
    merger.close()
    print(f"\nMerged PDF saved as: {output_filename}")

def merge_folder(folder_path, output_filename="merged_output.pdf"):
    """Merge all PDFs in a folder, sorted by filename."""
    folder = Path(folder_path)
    pdf_files = sorted(folder.glob("*.pdf"))

    if not pdf_files:
        print("No PDF files found in the folder.")
        return

    print(f"Found {len(pdf_files)} PDF files:")
    for f in pdf_files:
        print(f"  - {f.name}")

    merge_pdfs([str(f) for f in pdf_files], output_filename)

if __name__ == "__main__":
    choice = input("Merge (1) specific files or (2) entire folder? ").strip()

    if choice == '1':
        files = input("Enter PDF file paths (comma-separated): ").strip().split(',')
        files = [f.strip() for f in files]
        output = input("Output filename (default: merged_output.pdf): ").strip() or "merged_output.pdf"
        merge_pdfs(files, output)
    else:
        folder = input("Enter folder path: ").strip()
        output = input("Output filename (default: merged_output.pdf): ").strip() or "merged_output.pdf"
        merge_folder(folder, output)

Install the dependency:

pip install PyPDF2

merge_folder is the one you'll use most. It picks up all PDFs in alphabetical order. Name files with numeric prefixes like 01_intro.pdf, 02_chapter1.pdf and the order takes care of itself.

6. CSV to Excel converter with formatting

Raw CSVs are ugly. When I share data with non-technical colleagues, I convert it to a formatted Excel file with styled headers, auto-adjusted column widths, and alternating row colours.

The code

import pandas as pd
from openpyxl import load_workbook
from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
from pathlib import Path

def csv_to_excel(csv_path, output_path=None):
    """Convert CSV to a formatted Excel file."""
    csv_file = Path(csv_path)
    if output_path is None:
        output_path = csv_file.with_suffix('.xlsx')

    # Read CSV
    df = pd.read_csv(csv_file)

    # Write to Excel
    df.to_excel(output_path, index=False, sheet_name='Data')

    # Now apply formatting
    wb = load_workbook(output_path)
    ws = wb['Data']

    # Header styling
    header_font = Font(bold=True, color="FFFFFF", size=11)
    header_fill = PatternFill(start_color="2563EB", end_color="2563EB", fill_type="solid")
    header_alignment = Alignment(horizontal="center", vertical="center")
    thin_border = Border(
        left=Side(style='thin'),
        right=Side(style='thin'),
        top=Side(style='thin'),
        bottom=Side(style='thin')
    )

    for cell in ws[1]:
        cell.font = header_font
        cell.fill = header_fill
        cell.alignment = header_alignment
        cell.border = thin_border

    # Auto-adjust column widths
    for column in ws.columns:
        max_length = 0
        column_letter = column[0].column_letter
        for cell in column:
            if cell.value:
                max_length = max(max_length, len(str(cell.value)))
            cell.border = thin_border
        adjusted_width = min(max_length + 4, 50)
        ws.column_dimensions[column_letter].width = adjusted_width

    # Alternate row coloring
    light_fill = PatternFill(start_color="F0F7FF", end_color="F0F7FF", fill_type="solid")
    for row_idx, row in enumerate(ws.iter_rows(min_row=2, max_row=ws.max_row), start=2):
        if row_idx % 2 == 0:
            for cell in row:
                cell.fill = light_fill

    wb.save(output_path)
    print(f"Formatted Excel file saved: {output_path}")

if __name__ == "__main__":
    csv_file = input("Enter CSV file path: ").strip()
    csv_to_excel(csv_file)

Dependencies:

pip install pandas openpyxl

The output looks far more professional than it has any right to, and people will assume you're using an expensive reporting tool rather than a short Python script.

7. System backup script

This creates compressed backups of important folders and keeps only the last N, so it doesn't eat all your disk space. Everyone should run something like it.

The code

import shutil
from pathlib import Path
from datetime import datetime

def create_backup(source_dirs, backup_root, max_backups=5):
    """Create a timestamped compressed backup of specified directories."""
    backup_root = Path(backup_root)
    backup_root.mkdir(parents=True, exist_ok=True)

    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")

    for source in source_dirs:
        source_path = Path(source)
        if not source_path.exists():
            print(f"Source not found, skipping: {source}")
            continue

        folder_name = source_path.name
        archive_name = f"{folder_name}_{timestamp}"
        archive_path = backup_root / archive_name

        print(f"Backing up: {source_path} ...")
        shutil.make_archive(
            str(archive_path),
            'zip',
            root_dir=str(source_path.parent),
            base_dir=source_path.name
        )

        archive_size = Path(f"{archive_path}.zip").stat().st_size / (1024 * 1024)
        print(f"  Created: {archive_name}.zip ({archive_size:.1f} MB)")

    # Cleanup old backups
    cleanup_old_backups(backup_root, max_backups)

def cleanup_old_backups(backup_root, max_backups):
    """Remove old backups, keeping only the most recent ones per source folder."""
    all_zips = sorted(backup_root.glob("*.zip"), key=lambda f: f.stat().st_mtime, reverse=True)

    # Group by source folder name (everything before the timestamp)
    from collections import defaultdict
    groups = defaultdict(list)
    for zip_file in all_zips:
        # Extract the folder name part (before _YYYYMMDD_HHMMSS)
        parts = zip_file.stem.rsplit('_', 2)
        if len(parts) >= 3:
            group_name = parts[0]
        else:
            group_name = zip_file.stem
        groups[group_name].append(zip_file)

    for group_name, files in groups.items():
        if len(files) > max_backups:
            for old_file in files[max_backups:]:
                old_file.unlink()
                print(f"  Removed old backup: {old_file.name}")

if __name__ == "__main__":
    folders_to_backup = [
        r"C:\Users\anurag\Documents\Projects",
        r"C:\Users\anurag\Documents\Notes",
        r"C:\Users\anurag\Desktop\WorkFiles",
    ]

    backup_destination = r"D:\Backups"

    create_backup(folders_to_backup, backup_destination, max_backups=5)
    print("\nBackup complete!")

8. WhatsApp message scheduler (concept)

The code

import pywhatkit as kit
from datetime import datetime, timedelta

def schedule_whatsapp_message(phone_number, message, send_time=None):
    """
    Schedule a WhatsApp message using pywhatkit.
    phone_number should include country code (e.g., +91XXXXXXXXXX)
    send_time is a datetime object; if None, sends 2 minutes from now.
    """
    if send_time is None:
        send_time = datetime.now() + timedelta(minutes=2)

    hour = send_time.hour
    minute = send_time.minute

    print(f"Scheduling message to {phone_number} at {hour:02d}:{minute:02d}")
    print(f"Message: {message}")

    kit.sendwhatmsg(
        phone_no=phone_number,
        message=message,
        time_hour=hour,
        time_min=minute,
        wait_time=15,
        tab_close=True
    )
    print("Message sent successfully!")

if __name__ == "__main__":
    # Example: Send birthday wishes at midnight
    schedule_whatsapp_message(
        phone_number="+919876543210",
        message="Happy Birthday! 🎂 Wishing you an amazing year ahead!",
        send_time=datetime(2026, 2, 15, 0, 0)  # Feb 15 at midnight
    )

pip install pywhatkit

9. Password generator

The code

import secrets
import string
from typing import Optional

def generate_password(
    length: int = 20,
    uppercase: bool = True,
    lowercase: bool = True,
    digits: bool = True,
    special: bool = True,
    exclude_ambiguous: bool = True,
    min_uppercase: int = 1,
    min_digits: int = 1,
    min_special: int = 1
) -> str:
    """Generate a cryptographically secure password."""

    chars = ""
    if lowercase:
        chars += string.ascii_lowercase
    if uppercase:
        chars += string.ascii_uppercase
    if digits:
        chars += string.digits
    if special:
        chars += "!@#$%^&*()-_=+[]{}|;:,.<>?"

    if exclude_ambiguous:
        ambiguous = "0OoIl1"
        chars = ''.join(c for c in chars if c not in ambiguous)

    if not chars:
        raise ValueError("At least one character type must be enabled")

    # Keep generating until all minimums are met
    while True:
        password = ''.join(secrets.choice(chars) for _ in range(length))

        has_upper = sum(1 for c in password if c in string.ascii_uppercase) >= min_uppercase
        has_digit = sum(1 for c in password if c in string.digits) >= min_digits
        has_special = sum(1 for c in password if c in "!@#$%^&*()-_=+[]{}|;:,.<>?") >= min_special

        if has_upper and has_digit and has_special:
            return password

def generate_batch(count: int = 10, **kwargs) -> list:
    """Generate multiple passwords."""
    return [generate_password(**kwargs) for _ in range(count)]

if __name__ == "__main__":
    print("=== Password Generator ===\n")

    count = int(input("How many passwords? (default 5): ").strip() or "5")
    length = int(input("Password length? (default 20): ").strip() or "20")

    passwords = generate_batch(count=count, length=length)

    print(f"\nGenerated {count} passwords ({length} chars each):\n")
    for i, pwd in enumerate(passwords, 1):
        print(f"  {i}. {pwd}")

    # Calculate entropy
    import math
    charset_size = 72  # approximate usable charset after ambiguous removal
    entropy = length * math.log2(charset_size)
    print(f"\n  Estimated entropy: {entropy:.0f} bits")
    print(f"  (128+ bits is considered very strong)")

How I keep them organized

All my automation scripts live in one folder, ~/scripts/, with a simple naming convention:

Script	Filename	Schedule
File Organizer	`organize_downloads.py`	Weekly (Sunday 8 PM)
Image Resizer	`resize_images.py`	On demand
Email Sender	`weekly_update.py`	Weekly (Friday 5 PM)
Price Tracker	`track_prices.py`	Daily (9 AM)
PDF Merger	`merge_pdfs.py`	On demand
CSV to Excel	`csv_to_xlsx.py`	On demand
System Backup	`backup.py`	Daily (11 PM)
WhatsApp Scheduler	`wa_schedule.py`	On demand
Password Generator	`gen_passwords.py`	On demand

# Example cron entry (Linux)
0 9 * * * /usr/bin/python3 /home/anurag/scripts/track_prices.py >> /home/anurag/scripts/logs/price_tracker.log 2>&1

Tips I've learned the hard way

Keep scripts simple. The best automation scripts are the ones you can read six months later and understand immediately, so resist the urge to over-engineer them.

Prefer pathlib over os.path. It's cleaner, and there's almost no reason to use os.path.join() anymore when Path(folder) / "subfolder" / "file.txt" exists.

Start with whatever annoys you

Automation pays back fast. A script like the file organizer takes maybe 30 minutes to write and keeps saving time for years, and a price tracker catches deals you'd otherwise miss.

1. File organizer by extension

The code

How to use it

2. Bulk image resizer

The code

3. Automated email sender

The code

4. Web scraper for price tracking

The code

5. PDF merger

The code

6. CSV to Excel converter with formatting

The code

7. System backup script

The code

8. WhatsApp message scheduler (concept)

The code

9. Password generator

The code

How I keep them organized

Tips I've learned the hard way

Start with whatever annoys you

Anurag Sinha

Stay Ahead in Tech

Comments (0)

Leave a Comment

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1. File organizer by extension

The code

How to use it

2. Bulk image resizer

The code

3. Automated email sender

The code

4. Web scraper for price tracking

The code

5. PDF merger

The code

6. CSV to Excel converter with formatting

The code

7. System backup script

The code

8. WhatsApp message scheduler (concept)

The code

9. Password generator

The code

How I keep them organized

Tips I've learned the hard way

Start with whatever annoys you

Anurag Sinha

Stay Ahead in Tech

Comments (0)

Leave a Comment

Related Articles

API Design: REST and GraphQL Patterns That Scale

DSA Roadmap for Placements: What Matters in 2026

Redis Caching: Speed Up Your App in Practice