17 Essential Python Scripts for Automating Everyday Tasks
An extensive guide presents 17 practical Python scripts covering file management, web scraping, email handling, Excel processing, database interaction, system tasks, image editing, network automation, data cleaning, PDF manipulation, GUI automation, testing, cloud services, finance, and natural language processing, enabling readers to streamline workflows and boost productivity.
This article introduces a collection of 17 Python scripts designed to automate a wide range of routine tasks, helping developers and IT professionals improve efficiency across multiple domains.
1. File Management – Sort files by extension and remove empty folders.
# Python script to sort files in a directory by their extension
import os
from shutil import move
def sort_files(directory_path):
for filename in os.listdir(directory_path):
if os.path.isfile(os.path.join(directory_path, filename)):
file_extension = filename.split('.')[-1]
destination_directory = os.path.join(directory_path, file_extension)
if not os.path.exists(destination_directory):
os.makedirs(destination_directory)
move(os.path.join(directory_path, filename), os.path.join(destination_directory, filename))It also includes a script to delete empty directories:
# Python script to remove empty folders in a directory
import os
def remove_empty_folders(directory_path):
for root, dirs, files in os.walk(directory_path, topdown=False):
for folder in dirs:
folder_path = os.path.join(root, folder)
if not os.listdir(folder_path):
os.rmdir(folder_path)2. Web Scraping – Extract data from websites and download images in bulk.
# Python script for web scraping to extract data from a website
import requests
from bs4 import BeautifulSoup
def scrape_data(url):
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')
# Your code here to extract relevant data from the website3. Text Processing – Count words, find‑replace, and generate random text.
# Python script to count words in a text file
def count_words(file_path):
with open(file_path, 'r') as f:
text = f.read()
word_count = len(text.split())
return word_count4. Email Automation – Send personalized emails and attachments.
# Python script to send personalized emails to a list of recipients
import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
def send_personalized_email(sender_email, sender_password, recipients, subject, body):
server = smtplib.SMTP('smtp.gmail.com', 587)
server.starttls()
server.login(sender_email, sender_password)
for recipient_email in recipients:
message = MIMEMultipart()
message['From'] = sender_email
message['To'] = recipient_email
message['Subject'] = subject
message.attach(MIMEText(body, 'plain'))
server.sendmail(sender_email, recipient_email, message.as_string())
server.quit()5. Excel Automation – Read/write spreadsheets and perform basic analysis.
# Python script to read and write data to an Excel spreadsheet
import pandas as pd
def read_excel(file_path):
df = pd.read_excel(file_path)
return df
def write_to_excel(data, file_path):
df = pd.DataFrame(data)
df.to_excel(file_path, index=False)6. Database Interaction – Connect to SQLite (or other DBs) and execute queries.
# Python script to connect to a database and execute queries
import sqlite3
def connect_to_database(database_path):
connection = sqlite3.connect(database_path)
return connection
def execute_query(connection, query):
cursor = connection.cursor()
cursor.execute(query)
result = cursor.fetchall()
return result7. Social Media Automation – Post to Twitter and Facebook using respective APIs.
# Python script to automate posting on Twitter and Facebook
from twython import Twython
import facebook
def post_to_twitter(api_key, api_secret, access_token, access_token_secret, message):
twitter = Twython(api_key, api_secret, access_token, access_token_secret)
twitter.update_status(status=message)
def post_to_facebook(access_token, message):
graph = facebook.GraphAPI(access_token)
graph.put_object(parent_object='me', connection_name='feed', message=message)8. System Tasks – Manage processes and schedule jobs with cron.
# Python script to manage system processes
import psutil
def get_running_processes():
return [p.info for p in psutil.process_iter(['pid', 'name', 'username'])]
def kill_process_by_name(process_name):
for p in psutil.process_iter(['pid', 'name', 'username']):
if p.info['name'] == process_name:
p.kill()9. Image Automation – Resize, crop, watermark, and create thumbnails.
# Python script to resize and crop images
from PIL import Image
def resize_image(input_path, output_path, width, height):
image = Image.open(input_path)
resized_image = image.resize((width, height), Image.ANTIALIAS)
resized_image.save(output_path)
def crop_image(input_path, output_path, left, top, right, bottom):
image = Image.open(input_path)
cropped_image = image.crop((left, top, right, bottom))
cropped_image.save(output_path)10‑17. Additional sections cover network automation, data cleaning, PDF operations, GUI automation, testing (unittest & Selenium), cloud services (AWS, Google Drive), finance automation, and natural language processing (sentiment analysis, summarization, translation), each accompanied by concise example code.
Overall, the guide serves as a practical toolbox for automating repetitive tasks, reducing manual effort, and enhancing productivity across development, operations, and data‑centric workflows.
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