30 Python Scripts for Everyday Automation

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30 Python Scripts for Everyday Automation
30 Python Scripts for Everyday Automation

30 Python Scripts for Everyday Automation

Introduction to Everyday Automation

Imagine waking up to find that all your repetitive tasks—renaming files, sending emails, tracking expenses—are already done for you. Sounds like a dream, right? Well, this is where Python steps in. Python, with its simplicity and versatility, has become the go-to tool for automating everyday tasks. Whether you’re a seasoned developer or a complete beginner, Python offers a world of possibilities to streamline your life.

Python’s role in automation isn’t just about saving time. It’s about improving productivity, reducing errors, and allowing you to focus on what really matters. From managing files to controlling smart devices at home, automation through Python is like having a personal assistant that never sleeps.

In this guide, we’re going to explore 51 Python scripts that can automate everyday tasks, making your life easier one line of code at a time. I’ll break these scripts into categories so you can find what’s most useful for your needs. Let’s dive in and see how Python can transform your daily workflow.

Script Categories

Python is flexible enough to handle a variety of tasks, and I've grouped these scripts into practical categories to help you navigate them more easily. Whether you need to manage files, automate emails, or even control devices in your home, these categories will show you Python’s versatility.

1. File Management

Organizing files can be a pain. But with Python, you can turn a long, tedious process into something that takes just a few seconds. Here are three scripts that will get your files under control.

Renaming Files in Bulk

Tired of renaming files one by one? This Python script allows you to rename hundreds or even thousands of files in minutes. Whether it’s adding a date to a file’s name or changing file extensions, Python can handle it.

import os

def bulk_rename(directory, new_name):
    for count, filename in enumerate(os.listdir(directory)):
        file_extension = filename.split(".")[-1]
        new_filename = f"{new_name}_{count}.{file_extension}"
        os.rename(os.path.join(directory, filename), os.path.join(directory, new_filename))

bulk_rename("/path/to/your/files", "new_filename")

Organizing Downloads Folder

Your downloads folder can get cluttered fast. This script automatically organizes your downloads by file type, sorting them into folders like “Images,” “Documents,” and “Videos.”

import os
import shutil

def organize_downloads(download_folder):
    file_types = {
        'Images': ['.jpg', '.jpeg', '.png', '.gif'],
        'Documents': ['.pdf', '.docx', '.txt'],
        'Videos': ['.mp4', '.mkv', '.avi'],
    }

    for filename in os.listdir(download_folder):
        file_extension = os.path.splitext(filename)[1]
        for folder, extensions in file_types.items():
            if file_extension in extensions:
                folder_path = os.path.join(download_folder, folder)
                if not os.path.exists(folder_path):
                    os.makedirs(folder_path)
                shutil.move(os.path.join(download_folder, filename), folder_path)

organize_downloads("/path/to/downloads")

File Format Conversion

Need to convert a bunch of files from one format to another? This script can convert text files to PDF, images from PNG to JPG, or even audio files from WAV to MP3. No more manual file conversions!

from fpdf import FPDF

def txt_to_pdf(txt_file, pdf_file):
    pdf = FPDF()
    pdf.add_page()
    pdf.set_font("Arial", size=12)

    with open(txt_file, 'r') as file:
        for line in file:
            pdf.cell(200, 10, txt=line.encode('latin-1', 'replace').decode('latin-1'), ln=1)

    pdf.output(pdf_file)

txt_to_pdf("example.txt", "output.pdf")

2. Data Handling

Data is everywhere, and with Python, you can make sense of it. These scripts will help you collect, process, and manage data like a pro.

Web Scraping for Data Collection

Want to collect data from websites without manually copying and pasting? This script grabs data from a webpage and stores it in a CSV file.

import requests
from bs4 import BeautifulSoup
import csv

def scrape_website(url, output_csv):
    response = requests.get(url)
    soup = BeautifulSoup(response.text, 'html.parser')

    rows = []
    for item in soup.find_all('div', class_='data-item'):
        title = item.find('h2').text
        description = item.find('p').text
        rows.append([title, description])

    with open(output_csv, 'w', newline='') as file:
        writer = csv.writer(file)
        writer.writerow(["Title", "Description"])
        writer.writerows(rows)

scrape_website("https://example.com", "output.csv")

Automating Excel Reports

Manually updating Excel reports can be a headache. This script reads data from a CSV file and updates an Excel sheet automatically.

import pandas as pd

def update_excel_report(csv_file, excel_file, sheet_name):
    data = pd.read_csv(csv_file)
    with pd.ExcelWriter(excel_file, mode='a', if_sheet_exists='replace') as writer:
        data.to_excel(writer, sheet_name=sheet_name, index=False)

update_excel_report("data.csv", "report.xlsx", "Monthly Report")

Database Backups

Backing up databases is crucial, but it’s easy to forget. This script automates the process for MySQL databases, so you never have to worry about losing data.

import os
import time

def backup_database(host, user, password, db_name, backup_dir):
    timestamp = time.strftime('%Y%m%d-%H%M%S')
    backup_filename = f"{db_name}_backup_{timestamp}.sql"
    os.system(f"mysqldump -h {host} -u {user} -p{password} {db_name} > {backup_dir}/{backup_filename}")

backup_database("localhost", "root", "password", "my_database", "/path/to/backup")

3. Email Automation

Handling emails manually takes too much time. Let Python take over with these automation scripts.

Automated Email Responses

Why respond to every email manually when you can automate it? This script sends automatic responses to specific types of emails.

import smtplib
from email.message import EmailMessage

def send_auto_response(to_email, subject, body):
    msg = EmailMessage()
    msg.set_content(body)
    msg["Subject"] = subject
    msg["From"] = "your_email@example.com"
    msg["To"] = to_email

    with smtplib.SMTP("smtp.example.com", 587) as server:
        server.starttls()
        server.login("your_email@example.com", "your_password")
        server.send_message(msg)

send_auto_response("recipient@example.com", "Thanks for reaching out", "Your email has been received!")

Bulk Email Sending with Personalization

Sending bulk emails? This script personalizes each email by grabbing names from a list and sending them individually.

import smtplib
from email.message import EmailMessage

def send_bulk_emails(contact_list, subject, body_template):
    with smtplib.SMTP("smtp.example.com", 587) as server:
        server.starttls()
        server.login("your_email@example.com", "your_password")

        for contact in contact_list:
            msg = EmailMessage()
            msg["Subject"] = subject
            msg["From"] = "your_email@example.com"
            msg["To"] = contact["email"]
            body = body_template.format(name=contact["name"])
            msg.set_content(body)
            server.send_message(msg)

contacts = [
    {"name": "John", "email": "john@example.com"},
    {"name": "Jane", "email": "jane@example.com"}
]

send_bulk_emails(contacts, "Hello {name}!", "Hi {name}, just wanted to reach out!")

Email Parsing for Data Extraction

Need to extract data from emails? This script parses incoming emails and extracts important data like order numbers or customer information.

import imaplib
import email

def extract_email_data(email_address, password, criteria='ALL'):
    mail = imaplib.IMAP4_SSL("imap.example.com")
    mail.login(email_address, password)
    mail.select("inbox")

    result, data = mail.search(None, criteria)
    email_ids = data[0].split()

    for email_id in email_ids:
        result, email_data = mail.fetch(email_id, "(RFC822)")
        raw_email = email_data[0][1].decode("utf-8")
        msg = email.message_from_string(raw_email)

        if msg.is_multipart():
            for part in msg.walk():
                if part.get_content_type() == "text/plain":
                    print(part.get_payload(decode=True))
        else:
            print(msg.get_payload(decode=True))

extract_email_data("your_email@example.com", "your_password", '(SUBJECT "Order Confirmation")')

4. System Monitoring

Don’t wait until something breaks. With these scripts, you can monitor your system’s health and get alerts before things go wrong.

System Resource Monitoring

Keep an eye on your system’s resources—like CPU, memory, and disk usage—with this monitoring script.

import psutil

def monitor_system_resources():
    cpu = psutil.cpu_percent(interval=1)
    memory = psutil.virtual_memory().percent
    disk = psutil.disk_usage('/').percent

    print(f"CPU Usage: {cpu}%")
    print(f"Memory Usage: {memory}%")
    print(f"Disk Usage: {disk}%")

monitor_system_resources()

Automated Log Analysis

Logs can provide valuable insights into your system’s performance. This script automatically scans logs for keywords and sends alerts if something goes wrong.

import re

def scan_logs(log_file, keywords):
    with open(log_file, 'r') as file:
        for line in file:
            if any(keyword in line for keyword in keywords):
                print(f"Alert: {line.strip()}")

scan_logs("/path/to/logfile.log", ["ERROR", "WARNING", "CRITICAL"])

Disk Space Alerts

Running out of disk space can cause major issues. This script monitors your disk usage and sends an alert if space runs low.

import shutil
import smtplib
from email.message import EmailMessage

def check_disk_space(threshold, alert_email):
    total, used, free = shutil.disk_usage("/")
    free_percent = (free / total) * 100

    if free_percent < threshold:
        msg = EmailMessage()
        msg.set_content(f"Warning: Disk space is below {threshold}%")
        msg["Subject"] = "Disk Space Alert"
        msg["From"] = "alert@example.com"
        msg["To"] = alert_email

        with smtplib.SMTP("smtp.example.com", 587) as server:
            server.starttls()
            server.login("alert@example.com", "password")
            server.send_message(msg)

check_disk_space(20, "admin@example.com")

5. Task Scheduling

Let Python handle your scheduling needs. Whether it’s setting reminders or automating calendar events, these scripts have you covered.

Automating Calendar Events

This script automatically adds events to your Google Calendar so you can stay organized without lifting a finger.

from google.oauth2 import service_account
from googleapiclient.discovery import build

def create_calendar_event(summary, start_time, end_time):
    credentials = service_account.Credentials.from_service_account_file('credentials.json')
    service = build('calendar', 'v3', credentials=credentials)

    event = {
        'summary': summary,
        'start': {'dateTime': start_time, 'timeZone': 'America/New_York'},
        'end': {'dateTime': end_time, 'timeZone': 'America/New_York'},
    }

    event = service.events().insert(calendarId='primary', body=event).execute()
    print(f"Event created: {event.get('htmlLink')}")

create_calendar_event("Meeting with Bob", "2024-11-20T09:00:00-05:00", "2024-11-20T10:00:00-05:00")

Scheduled Reminders via Notifications

Need a reminder to take breaks or drink water? This script sends scheduled notifications to your desktop.

import time
from plyer import notification

def send_notification(title, message, interval):
    while True:
        notification.notify(
            title=title,
            message=message,
            timeout=10
        )
        time.sleep(interval)

send_notification("Break Time", "Take a 5-minute break", 3600)

Task Automation with Cron Jobs

For Linux users, you can automate scripts with cron. This example shows how to schedule a Python script to run every day at 9 a.m.

# Open your cron tab
crontab -e

# Add this line to schedule your Python script
0 9 * * * /usr/bin/python3 /path/to/your/script.py

6. Social Media Management

Managing social media accounts can be overwhelming, but with Python, you can automate everything from posting to reporting.

Automating Posts on Multiple Platforms

This script posts updates to both Twitter and Facebook simultaneously, saving you time and effort.

import tweepy
from facebook import GraphAPI

def post_to_social_media(message):
    # Twitter
    twitter_auth = tweepy.OAuth1UserHandler("API_KEY", "API_SECRET", "ACCESS_TOKEN", "ACCESS_SECRET")
    twitter_api = tweepy.API(twitter_auth)
    twitter_api.update_status(status=message)

    # Facebook
    fb_api = GraphAPI(access_token="FACEBOOK_ACCESS_TOKEN")
    fb_api.put_object(parent_object='me', connection_name='feed', message=message)

post_to_social_media("Hello world! Automating my social media posts with Python.")

Content Scheduling Scripts

Scheduling content is key to maintaining a consistent social media presence. This script schedules posts for later, ensuring you stay active without being glued to your phone.

import tweepy
import time
from datetime import datetime

def schedule_tweet(message, post_time):
    twitter_auth = tweepy.OAuth1UserHandler("API_KEY", "API_SECRET", "ACCESS_TOKEN", "ACCESS_SECRET")
    twitter_api = tweepy.API(twitter_auth)

    while True:
        if datetime.now() >= post_time:
            twitter_api.update_status(status=message)
            break
        time.sleep(60)

schedule_tweet("Scheduled Tweet: Hello World!", datetime(2024, 11, 17, 14, 0))

Analytics Reporting for Engagement

Tracking social media performance is crucial if you want to grow your audience and understand what’s working. This Python script collects engagement data—such as likes, retweets, and comments—from your social media accounts and compiles a report.

Here’s an example of how you can track Twitter engagement using the Tweepy library:

import tweepy

def get_twitter_engagement(api_key, api_secret, access_token, access_secret, username):
    auth = tweepy.OAuth1UserHandler(api_key, api_secret, access_token, access_secret)
    api = tweepy.API(auth)

    # Fetch the user's timeline (last 10 tweets)
    tweets = api.user_timeline(screen_name=username, count=10)

    for tweet in tweets:
        retweets = tweet.retweet_count
        likes = tweet.favorite_count
        print(f"Tweet: {tweet.text}")
        print(f"Retweets: {retweets}, Likes: {likes}")
        print("-" * 50)

get_twitter_engagement('API_KEY', 'API_SECRET', 'ACCESS_TOKEN', 'ACCESS_SECRET', 'your_username')

This script fetches the last 10 tweets from a specified user and displays the engagement metrics for each one, giving you a quick snapshot of how your content is performing.

7. Web Development Utilities

Web developers often need to automate tasks to make their workflow efficient. Python can be a powerful ally here, handling everything from testing to deployment.

Automated Testing Scripts

Testing is a critical part of web development, but it can be tedious. This script automates browser-based testing using Selenium, ensuring that your web app works as expected across different environments.

from selenium import webdriver
from selenium.webdriver.common.keys import Keys

def automated_test_website(url):
    driver = webdriver.Chrome(executable_path='/path/to/chromedriver')

    # Open the website
    driver.get(url)

    # Check the title of the page
    assert "Expected Title" in driver.title

    # Find an element and interact with it
    elem = driver.find_element_by_name("q")
    elem.clear()
    elem.send_keys("Python Automation")
    elem.send_keys(Keys.RETURN)

    # Verify search results
    assert "No results found." not in driver.page_source

    driver.quit()

automated_test_website("http://example.com")

Selenium allows you to simulate user interactions with your website, such as clicking buttons and filling out forms, which helps you ensure everything works smoothly before deploying updates.

Deployment Automation

Deploying a web application manually can be time-consuming, not to mention prone to mistakes. This Python script automates the deployment process using Fabric, a tool that simplifies SSH-based command execution.

from fabric import Connection

def deploy():
    with Connection('user@server.com') as c:
        c.run('git pull origin main')
        c.run('pip install -r requirements.txt')
        c.run('python manage.py migrate')
        c.run('sudo systemctl restart gunicorn')

deploy()

This script connects to your server, pulls the latest code from Git, installs any new dependencies, runs migrations, and restarts the application server—all with a single command.

Content Optimization Tools

Optimizing your website’s content for SEO can be a painstaking process. This script scans your web pages for metadata, ensuring that every page has the necessary SEO elements like title tags and meta descriptions.

from bs4 import BeautifulSoup
import requests

def check_seo(url):
    response = requests.get(url)
    soup = BeautifulSoup(response.text, 'html.parser')

    title_tag = soup.find('title')
    meta_description = soup.find('meta', attrs={'name': 'description'})

    if not title_tag:
        print(f"Missing title tag on {url}")
    else:
        print(f"Title: {title_tag.text}")

    if not meta_description:
        print(f"Missing meta description on {url}")
    else:
        print(f"Meta Description: {meta_description['content']}")

check_seo("https://example.com")

This tool ensures that every page on your website is SEO-friendly by checking for essential metadata. You can easily extend this script to include more advanced SEO checks, like keyword density or alt text for images.

8. Home Automation

Python isn’t just for your computer—it can also help you control devices around your home. Here are some scripts that can automate your smart home.

Controlling Smart Devices

This script interacts with smart devices like lights, thermostats, and security cameras, allowing you to control them from your Python code using the pyHS100 library.

from pyHS100 import SmartPlug

def toggle_smart_plug(ip_address, state):
    plug = SmartPlug(ip_address)
    if state == 'on':
        plug.turn_on()
    elif state == 'off':
        plug.turn_off()

# Example usage
toggle_smart_plug("192.168.1.100", "on")

By integrating this script with a voice assistant or a schedule, you can control your devices without lifting a finger.

Automated Security Systems

Security cameras and motion sensors can be automated with Python. This script triggers an alert if motion is detected by a PIR sensor connected to a Raspberry Pi.

import RPi.GPIO as GPIO
import time
import smtplib
from email.message import EmailMessage

GPIO.setmode(GPIO.BCM)
PIR_PIN = 7
GPIO.setup(PIR_PIN, GPIO.IN)

def send_alert_email():
    msg = EmailMessage()
    msg.set_content("Motion detected!")
    msg["Subject"] = "Security Alert"
    msg["From"] = "your_email@example.com"
    msg["To"] = "recipient@example.com"

    with smtplib.SMTP("smtp.example.com", 587) as server:
        server.starttls()
        server.login("your_email@example.com", "password")
        server.send_message(msg)

try:
    print("PIR Module Test (CTRL+C to exit)")
    time.sleep(2)
    print("Ready")

    while True:
        if GPIO.input(PIR_PIN):
            print("Motion Detected!")
            send_alert_email()
            time.sleep(5)
        time.sleep(0.1)

except KeyboardInterrupt:
    print("Quit")
    GPIO.cleanup()

This simple motion detection system can notify you via email whenever motion is detected, adding an extra layer of security to your home.

Energy Usage Monitoring

Want to keep track of your home’s energy consumption? This script collects data from smart plugs and generates a report on how much energy each device is using.

from pyHS100 import SmartPlug

def monitor_energy_usage(ip_address):
    plug = SmartPlug(ip_address)
    energy = plug.get_emeter_realtime()
    print(f"Current Power Consumption: {energy['power']}W")
    print(f"Total Energy Used: {energy['total']}kWh")

monitor_energy_usage("192.168.1.100")

This script helps you identify which devices are consuming the most power, so you can make informed decisions about reducing energy usage and saving on your electricity bill.

9. Personal Finance

Managing your finances can be tedious, but Python can help you automate tasks like tracking expenses or paying bills. Here are some scripts to make your financial life easier.

Expense Tracking and Reporting

Keeping track of your expenses is essential for budgeting. This script reads transactions from a CSV file (like one exported from your bank) and categorizes them, generating a report of your spending.

import csv

def track_expenses(csv_file):
    categories = {}
    with open(csv_file, newline='') as file:
        reader = csv.DictReader(file)
        for row in reader:
            category = row['Category']
            amount = float(row['Amount'])
            if category in categories:
                categories[category] += amount
            else:
                categories[category] = amount

    for category, total in categories.items():
        print(f"{category}: ${total:.2f}")

track_expenses("transactions.csv")

This script helps you stay on top of your spending by summarizing how much you've spent in each category, such as “Food,” “Transportation,” and “Entertainment.”

Automated Bill Payments

Never miss a bill payment again! This script logs into your bank’s website and schedules payments automatically, using Selenium to simulate a user’s actions.

from selenium import webdriver

def automate_bill_payment(bank_url, username, password, payee, amount):
    driver = webdriver.Chrome(executable_path='/path/to/chromedriver')
    driver.get(bank_url)

    # Log in
    driver.find_element_by_id('username').send_keys(username)
    driver.find_element_by_id('password').send_keys(password)
    driver.find_element_by_id('login-button').click()

    # Navigate to bill payment page
    driver.find_element_by_id('pay-bills').click()
    driver.find_element_by_id('payee').send_keys(payee)
    driver.find_element_by_id('amount').send_keys(amount)
    driver.find_element_by_id('pay-button').click()

    driver.quit()

automate_bill_payment("https://yourbank.com", "your_username", "your_password", "electric_company", "100.00")

This script automates the process of logging in, selecting the payee, entering the amount, and confirming the payment—taking the hassle out of bill management.

Investment Portfolio Monitoring

Keep an eye on your investment portfolio with this Python script, which retrieves stock prices and calculates your total portfolio value.

import yfinance as yf

def monitor_portfolio(stocks):
    total_value = 0
    for symbol, shares in stocks.items():
        stock = yf.Ticker(symbol)
        price = stock.history(period='1d')['Close'][0]
        stock_value = price * shares
        total_value += stock_value
        print(f"{symbol}: ${price:.2f} x {shares} = ${stock_value:.2f}")
    print(f"Total Portfolio Value: ${total_value:.2f}")

portfolio = {
    "AAPL": 10,
    "GOOGL": 5,
    "TSLA": 2,
}

monitor_portfolio(portfolio)

This script pulls the latest stock prices using the yfinance library and calculates the total value of your portfolio, helping you track your investments in real-time.

10. Learning and Development

Python can also help you grow professionally by automating tasks related to learning and development. Here are some scripts that can support your personal growth.

Automating Code Reviews

Code reviews are a vital part of software development, but they can be time-consuming. This script checks for common issues in a codebase, such as PEP 8 violations, using the flake8 library.

pip install flake8
import os

def auto_code_review(directory):
    os.system(f"flake8 {directory}")

auto_code_review("/path/to/codebase")

This script runs a static analysis on your code to check for style guide violations, helping you clean up your code before submitting it for a formal review.

Setting Up Study Reminders

Studying for exams or learning new skills can be challenging without a consistent schedule. This script sends you reminders via email to stick to your study plan.

import smtplib
from email.message import EmailMessage
import time

def send_study_reminder(subject, message, to_email, interval):
    msg = EmailMessage()
    msg.set_content(message)
    msg["Subject"] = subject
    msg["From"] = "your_email@example.com"
    msg["To"] = to_email

    while True:
        with smtplib.SMTP("smtp.example.com", 587) as server:
            server.starttls()
            server.login("your_email@example.com", "your_password")
            server.send_message(msg)
        time.sleep(interval)

send_study_reminder("Time to Study!", "Don't forget to review your Python notes.", "recipient@example.com", 86400)

This script sends daily email reminders, ensuring that you stay on track with your study goals.

Generating Study Materials

Need some flashcards to help you study? This script generates a set of flashcards from a CSV file containing questions and answers, helping you prepare for exams or learn new concepts.

import csv

def generate_flashcards(csv_file):
    with open(csv_file, newline='') as file:
        reader = csv.DictReader(file)
        for row in reader:
            question = row['Question']
            answer = row['Answer']
            input(f"Question: {question}\nPress Enter to see the answer...")
            print(f"Answer: {answer}\n")

generate_flashcards("flashcards.csv")

This script turns any list of questions and answers into an interactive study tool, letting you quiz yourself on the topics you’re learning.

Highlighting Unique Scripts

Now that we’ve covered a wide variety of automation scripts, let’s take a closer look at a few standout examples that showcase Python’s potential for creative problem-solving:

  1. Expense Tracking Script: This script not only tracks your expenses but also categorizes them, giving you a clear picture of where your money is going. It’s particularly useful for budgeting and financial planning.
  2. Automated Social Media Posting: With this script, you can post to multiple platforms at once, saving hours of time. The ability to schedule posts in advance is a game changer for anyone managing a social media presence.
  3. Home Security Automation: Using a simple Raspberry Pi and a PIR sensor, this script turns your home into a smart, automated security system. You can easily expand this setup to include additional sensors or notifications.

Practical Implementation Tips

Before you start automating everything, there are a few practical tips to keep in mind:

  • Start Small: Don’t try to automate everything at once. Pick one task that you do frequently and automate that first. Once you’ve got that working, you can move on to more complex scripts.
  • Test Thoroughly: Always test your scripts thoroughly, especially those that interact with external services like email or social media. You don’t want to accidentally spam your followers or send out incorrect emails.
  • Error Handling: Make sure to include error handling in your scripts. For example, if an API request fails, your script should be able to handle that gracefully instead of crashing.
  • Keep It Simple: The goal of automation is to save time, not to create overly complex systems that are hard to maintain. Keep your scripts as simple as possible.

Community Contributions

One of the best things about Python is its large, active community. There are countless developers out there creating and sharing automation scripts. Here’s how you can get involved:

  • Share Your Scripts: If you’ve created a useful Python script, share it with others! Post it to GitHub, write a blog post about it, or share it on social media.
  • Explore Open-Source Projects: There are plenty of open-source Python projects related to automation. Contributing to these projects is a great way to learn and give back to the community.
  • Collaborate with Others: Don’t be afraid to collaborate with other developers. Not only will you learn from them, but you’ll also be able to create even more powerful scripts by combining your efforts.

Python Scripts for Everyday Automation Conclusion

The power of automation is truly transformative, and Python makes it easier than ever to take advantage of it. Whether you’re looking to save time, reduce errors, or simply automate the mundane tasks in your life, the 51 scripts we’ve covered can help you get started.

Take the time to explore these scripts and think about how they can be integrated into your daily routines. With Python at your side, you’ll be able to automate everything from file management to social media posting—and much, much more.

Now it’s your turn. What task will you automate first?

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