How to Automate Your Daily Tasks with Python: 5 Advanced Scripts for Real Productivity

Description

Repetitive tasks kill productivity. But Python can help you automate powerful workflows that truly save time — from tracking expenses and summarizing news to AI-powered email responses. Here are 5 practical automation scripts that can transform your daily life!

1. AI-Powered Email Responder (ChatGPT + Gmail API)

Tired of manually replying to common emails? Let Python read your emails and auto-generate responses using ChatGPT!

Code:

import openai
import imaplib
import email
import smtplib
openai.api_key = "YOUR_OPENAI_API_KEY"
# Step 1: Connect to Gmail Inbox
mail = imaplib.IMAP4_SSL("imap.gmail.com")
mail.login("your_email@gmail.com", "your_app_password")
mail.select("inbox")
_, search_data = mail.search(None, "UNSEEN")
email_ids = search_data[0].split()
for e_id in email_ids:
    _, data = mail.fetch(e_id, "(RFC822)")
    raw_email = data[0][1]
    msg = email.message_from_bytes(raw_email)
    sender = msg["From"]
    subject = msg["Subject"]
    # Step 2: Generate AI Response
    prompt = f"Reply professionally to this email:\nSubject: {subject}\n{msg.get_payload(decode=True)}"
    response = openai.ChatCompletion.create(
        model="gpt-4",
        messages=[{"role": "user", "content": prompt}]
    )
    reply = response["choices"][0]["message"]["content"]
    # Step 3: Send Response
    with smtplib.SMTP("smtp.gmail.com", 587) as server:
        server.starttls()
        server.login("your_email@gmail.com", "your_app_password")
        email_msg = f"Subject: RE: {subject}\n\n{reply}"
        server.sendmail("your_email@gmail.com", sender, email_msg)
print("AI responses sent!")

🔹 Use Case: Automates email responses for common queries (customer support, HR, sales).
🔹 Why it’s useful: Saves hours of responding to repetitive emails.

2. Automated Expense Tracker (Google Sheets API + OCR for Receipts)

Manually logging expenses? Use Python to scan receipts, extract text using OCR, and log expenses to Google Sheets.

Code:

import pytesseract
import cv2
import gspread
from oauth2client.service_account import ServiceAccountCredentials
# Step 1: Extract text from receipt
img = cv2.imread("receipt.jpg")
text = pytesseract.image_to_string(img)
# Step 2: Extract amount and vendor details
import re
amount = re.findall(r"\$\d+\.\d{2}", text)  # Extracts price in "$xx.xx" format
vendor = text.split("\n")[0]  # First line usually has vendor name
# Step 3: Log to Google Sheets
scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"]
creds = ServiceAccountCredentials.from_json_keyfile_name("your_google_api.json", scope)
client = gspread.authorize(creds)
sheet = client.open("Expense Tracker").sheet1
sheet.append_row([vendor, amount[0]])
print("Expense logged successfully!")

🔹 Use Case: Automates tracking of daily expenses by scanning receipts and saving data in Google Sheets.
🔹 Why it’s useful: Saves time manually entering expenses and keeps financial records updated.

3. AI-Powered Daily News Summarizer

Want to stay updated with news without reading long articles? This script fetches top news, summarizes them using AI, and emails you a daily digest.

Code:

import requests
import openai
import smtplib
openai.api_key = "YOUR_OPENAI_API_KEY"
news_api_key = "YOUR_NEWSAPI_KEY"
# Step 1: Fetch Top News
url = f"https://newsapi.org/v2/top-headlines?country=us&apiKey={news_api_key}"
response = requests.get(url).json()
articles = response["articles"][:5]
news_text = "\n\n".join([f"{a['title']}\n{a['description']}" for a in articles])
# Step 2: Summarize News
summary = openai.ChatCompletion.create(
    model="gpt-4",
    messages=[{"role": "user", "content": f"Summarize the following news articles:\n\n{news_text}"}]
)["choices"][0]["message"]["content"]
# Step 3: Email Summary
email_msg = f"Subject: Daily News Digest\n\n{summary}"
with smtplib.SMTP("smtp.gmail.com", 587) as server:
    server.starttls()
    server.login("your_email@gmail.com", "your_app_password")
    server.sendmail("your_email@gmail.com", "recipient@example.com", email_msg)
print("Daily news digest sent!")

🔹 Use Case: Sends you a one-paragraph summary of top news daily.
🔹 Why it’s useful: Saves time from reading long articles.

4. YouTube Video to Podcast Converter

Want to listen to YouTube videos as audio podcasts? This script downloads a video, extracts audio, and saves it as an MP3.

Code:

from pytube import YouTube
from moviepy.editor import *
# Step 1: Download YouTube Video
video_url = "https://www.youtube.com/watch?v=YourVideoID"
yt = YouTube(video_url)
video = yt.streams.filter(only_audio=True).first()
video.download(filename="video.mp4")
# Step 2: Convert to MP3
clip = AudioFileClip("video.mp4")
clip.write_audiofile("podcast.mp3")
print("Podcast saved!")

🔹 Use Case: Converts YouTube videos into audio podcasts for offline listening.
🔹 Why it’s useful: Saves time watching long videos — listen instead.

5. Auto-Backup Important Files to Google Drive

Never lose important files again! This script monitors a folder and backs up new/updated files to Google Drive automatically.

Code:

from pydrive.auth import GoogleAuth
from pydrive.drive import GoogleDrive
import os
# Step 1: Authenticate Google Drive
gauth = GoogleAuth()
gauth.LocalWebserverAuth()
drive = GoogleDrive(gauth)
# Step 2: Upload New Files
folder_path = "C:/Users/YourName/Documents"
for file_name in os.listdir(folder_path):
    file_path = os.path.join(folder_path, file_name)
    gfile = drive.CreateFile({"title": file_name})
    gfile.SetContentFile(file_path)
    gfile.Upload()
print("Backup completed!")

🔹 Use Case: Auto-backs up important files to Google Drive.
🔹 Why it’s useful: Protects against accidental file loss.

Conclusion

🚀 These automation scripts go beyond basic tasks — they:
✅ Automate emails with AI responses
✅ Track expenses without manual entry
✅ Summarize news for quick updates
✅ Convert YouTube to podcasts
✅ Backup important files

🔥Which automation script will you try first? Let me know in the comments!🔥

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