How to Master Python Automation Scripts for Daily Workflow (15 Free & Ready-to-Run Scripts)

pip install pyperclip psutil schedule tweepy beautifulsoup4

python script_name.py

import time
import pyperclip

clipboard_history = []

def clipboard_tracker():
    recent = ""
    while True:
        current = pyperclip.paste()
        if current != recent and current.strip():
            recent = current
            clipboard_history.append(current)
            print(f"Copied: {current[:40]}...")
        time.sleep(1)

clipboard_tracker()

import subprocess, re, json, base64

def export_wifi_pwds(enc_file='wifi_pwds.enc'):
    profiles = subprocess.check_output('netsh wlan show profiles', shell=True).decode()
    names = re.findall("All User Profile\s*:\s(.*)", profiles)
    credentials = {}
    for name in names:
        info = subprocess.check_output(f'netsh wlan show profile "{name.strip()}" key=clear', shell=True).decode()
        pwd = re.search("Key Content\s*:\s(.*)", info)
        credentials[name.strip()] = pwd.group(1) if pwd else None
    encoded = base64.b64encode(json.dumps(credentials).encode())
    with open(enc_file, 'wb') as f:
        f.write(encoded)
    print(f"Saved encrypted Wi-Fi credentials to {enc_file}")

export_wifi_pwds()

import os, shutil
from datetime import datetime

def organize_screenshots(src, cloud_sync_dir):
    files = [f for f in os.listdir(src) if "screenshot" in f.lower()]
    for f in files:
        date_folder = datetime.fromtimestamp(os.path.getctime(os.path.join(src, f))).strftime("%Y-%m-%d")
        dest_folder = os.path.join(src, date_folder)
        os.makedirs(dest_folder, exist_ok=True)
        shutil.move(os.path.join(src, f), os.path.join(dest_folder, f))
        shutil.copytree(dest_folder, os.path.join(cloud_sync_dir, date_folder), dirs_exist_ok=True)
        print(f"Moved {f} and synced to cloud")

organize_screenshots('/path/to/screenshots', '/path/to/cloud-sync')

import os, shutil

def sort_desktop():
    desktop = os.path.join(os.path.expanduser("~"), "Desktop")
    types = {'Images': ['.png', '.jpg', '.jpeg', '.gif'], 'Docs': ['.pdf', '.docx', '.txt'], 'Media': ['.mp4', '.mp3']}
    for f in os.listdir(desktop):
        if os.path.isfile(os.path.join(desktop, f)):
            ext = os.path.splitext(f)[1].lower()
            category = next((k for k,v in types.items() if ext in v), 'Others')
            dest = os.path.join(desktop, category)
            os.makedirs(dest, exist_ok=True)
            shutil.move(os.path.join(desktop, f), os.path.join(dest, f))
            print(f"Moved {f} to {category}")

sort_desktop()

import speech_recognition as sr
import os

def offline_voice_control():
    recognizer = sr.Recognizer()
    with sr.Microphone() as mic:
        print("Say a command...")
        audio = recognizer.listen(mic)
    try:
        command = recognizer.recognize_sphinx(audio)  # offline recognition
        print(f"Command: {command}")
        if "open browser" in command:
            os.system("start chrome")
        elif "open editor" in command:
            os.system("notepad")
    except Exception as e:
        print(f"Error: {e}")

offline_voice_control()

import os
from sklearn.feature_extraction.text import TfidfVectorizer

def rename_files_by_keywords(folder):
    files = [f for f in os.listdir(folder) if f.endswith('.txt')]
    contents = []
    for file in files:
        with open(os.path.join(folder, file)) as f:
            contents.append(f.read())
    vectorizer = TfidfVectorizer(stop_words='english', max_features=5)
    X = vectorizer.fit_transform(contents)
    keywords = vectorizer.get_feature_names_out()
    for i, file in enumerate(files):
        name = "_".join(keywords)
        new_name = f"{name}_{i}.txt"
        os.rename(os.path.join(folder, file), os.path.join(folder, new_name))
        print(f"Renamed {file} to {new_name}")

rename_files_by_keywords('/path/to/text/files')

import psutil
import time

def predict_battery():
    while True:
        bat = psutil.sensors_battery()
        if bat.power_plugged:
            print("Charging... You can unplug soon.")
        else:
            time_left = (bat.percent / 100) * 180  # simplified: 3 hours at 100%
            print(f"Battery at {bat.percent}%. Approx. {int(time_left)} minutes left.")
            if bat.percent < 20:
                print("⚠️ Warning: Charge soon!")
        time.sleep(300)

predict_battery()

def offline_grammar_suggest(text):
    # This is a placeholder for offline NLP grammar check integration
    suggestions = ["Consider changing passive voice.", "Rewrite this sentence for clarity."]
    print("Suggestions:")
    for s in suggestions:
        print("-", s)

offline_grammar_suggest("This are an example text.")

import re

def alert_expenses(file):
    with open(file) as f:
        for line in f:
            if "debited" in line.lower():
                amount = re.findall(r'INR\s?[\d,]+', line)
                if amount:
                    amt_val = int(amount[0].replace("INR ", "").replace(",", ""))
                    if amt_val > 10000:
                        print(f"High expense alert: {amount[0]} - {line.strip()}")

alert_expenses('bank_sms.txt')

from ics import Calendar
import smtplib
from email.mime.text import MIMEText

def send_event_digest(ics_file, recipient):
    with open(ics_file) as f:
        calendar = Calendar(f.read())
    events = [f"{e.name} at {e.begin.humanize()}" for e in calendar.events]
    body = "\n".join(events) or "No upcoming events."
    msg = MIMEText(body)
    msg['Subject'] = "Your Daily Meeting Digest"
    msg['From'] = "[email protected]"
    msg['To'] = recipient

    server = smtplib.SMTP_SSL('smtp.gmail.com', 465)
    server.login('[email protected]', 'password')
    server.send_message(msg)
    server.quit()

send_event_digest('calendar.ics', '[email protected]')

import os
from http.server import SimpleHTTPRequestHandler, HTTPServer

def themed_gallery(folder, port=8000):
    os.chdir(folder)
    print(f"Serving {folder} at http://localhost:{port}")
    HTTPServer(('localhost', port), SimpleHTTPRequestHandler).serve_forever()

themed_gallery('/path/to/photos')

from sklearn.feature_extraction.text import CountVectorizer

def extract_action_items(filepath):
    with open(filepath) as f:
        text = f.read()
    vect = CountVectorizer(stop_words='english')
    tokens = vect.fit_transform([text])
    words = vect.get_feature_names_out()
    actions = [word for word in words if word.startswith('action') or word.startswith('todo')]
    print("Action items:", actions)

extract_action_items('meeting_notes.txt')

import tweepy
from datetime import datetime, timedelta
import time

def schedule_tweet(text, delay_seconds=60):
    client = tweepy.Client(bearer_token='YOUR_TOKEN')
    time.sleep(delay_seconds)
    client.create_tweet(text=text)
    print("Tweet posted!")

schedule_tweet("Hello, automation!", 10)

import requests
from bs4 import BeautifulSoup
import csv

def scrape_products(url, csv_file):
    r = requests.get(url)
    soup = BeautifulSoup(r.text, 'html.parser')
    products = []
    for item in soup.select('.product'):
        name = item.select_one('.name').text
        price = item.select_one('.price').text
        products.append([name, price])
    with open(csv_file, 'w', newline='') as f:
        writer = csv.writer(f)
        writer.writerow(['Product Name', 'Price'])
        writer.writerows(products)
    print("Scraping complete!")

scrape_products('https://example.com/products', 'products.csv')

from textblob import TextBlob

def auto_reply(email_text):
    sentiment = TextBlob(email_text).sentiment.polarity
    if sentiment < -0.2:
        reply = "Sorry to hear about your issues. We’ll get back to you ASAP."
    else:
        reply = "Thanks for reaching out! We appreciate your message."
    print("Reply to send:", reply)

auto_reply("I'm very disappointed with the service.")