Pro-Level Python Automation Projects You Need to Try

Welcome back, Automation Explorer…

You’ve mastered the basics and now it’s time to take things to the next level… real-world scripts that automate your life, business, or DevOps workflows.

This is Part 2 of Life’s Too Short for Repetitive Tasks — Let Python Automation Help

In this blog, we’ll build:

• Log into websites like a bot

• Upload files to Google Drive

• Build our own mini ChatGPT

• Post on Twitter automatically

…and more real-world scripts used by pros and power users

And don't worry — each example includes an explanation of the what, why, and how**..** so even if you're still learning, you'll come out of this as a legit automation wizard. 🧙‍♂️

Let’s go pro. 🚀👇

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1. Auto-Login to Websites Using Selenium

Selenium is a browser automation tool that simulates clicks, typing, and form submissions.

from selenium import webdriver
from selenium.webdriver.common.by import By

driver = webdriver.Chrome()
driver.get("https://example.com/login")

driver.find_element(By.ID, "username").send_keys("your_user")
driver.find_element(By.ID, "password").send_keys("your_pass")
driver.find_element(By.ID, "submit").click()

What it does:
This script opens up a browser window, types our username and password into a login page, and clicks the login button… just like we would do manually.

Why it’s useful:
Tired of typing login credentials every day for your work dashboard, college portal, or attendance system? This script can handle that for you.

How it works:
Python uses a library called selenium which controls our web browser (like Chrome or Firefox) by simulating keystrokes and clicks. We just tell it which fields to fill and which button to press.

✅ Use Case: Auto-login to dashboards, internal portals, attendance systems.

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2. Backup Files to Google Drive

This script uses the Google Drive API to upload files.

from pydrive.auth import GoogleAuth
from pydrive.drive import GoogleDrive

gauth = GoogleAuth()
gauth.LocalWebserverAuth()
drive = GoogleDrive(gauth)

file = drive.CreateFile({'title': 'backup.txt'})
file.SetContentFile('backup.txt')
file.Upload()

What it does:
Uploads any file from our computer (like a .txt, .csv, or .pdf) directly to our Google Drive account.

Why it’s useful:
Perfect for backing up reports, logs, or documents without opening our browser.

How it works:
Python uses a tool called PyDrive, which talks to Google Drive through its API (Application Programming Interface). We authorize the script once, and it can upload or update files anytime.

✅ Use Case: Automate backups, sync reports or exports to the cloud.

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3. Real-Time Dashboard from Excel Data

Let Python read your Excel file and visualize it.

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_excel("sales.xlsx")
df.groupby("Region")["Amount"].sum().plot(kind='bar')
plt.show()

What it does:
Reads data from an Excel sheet and automatically creates a visual chart (like a bar graph) from that data.

Why it’s useful:
If we deal with sales reports, surveys, or student data, this script helps us turn numbers into visuals quickly… no need to manually build charts in Excel.

How it works:
Python uses pandas to read the spreadsheet and matplotlib to draw the chart. It groups our data based on a category (like region or department) and visualizes totals or trends.

✅ Use Case: Dashboards for finance, sales, or reports.

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4. AI Chatbot with OpenAI API

Make your own chatbot using OpenAI's Chat API.

import openai

openai.api_key = "your-api-key"

response = openai.ChatCompletion.create(
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Tell me a joke"}]
)

print(response['choices'][0]['message']['content'])

What it does:
Creates a mini ChatGPT chatbot that we can talk to through our Python script.

Why it’s useful:
We can build our own assistant to answer questions, generate content, or even automate replies to common queries.

How it works:
We send our input to OpenAI’s servers using their API. The response we get back is what ChatGPT would say. It’s just like talking to AI (through ChatGPT, Gemini, Copilot) but through our own code!

✅ Use Case: Custom assistants, helpdesks, AI tools.

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5. Monitor Website Changes and Send Alerts

import requests

url = "https://example.com/product"
response = requests.get(url)
current = response.text

with open("previous.txt", "r") as f:
    old = f.read()

if current != old:
    print("Website has changed!")

with open("previous.txt", "w") as f:
    f.write(current)

What it does:
Checks if a webpage has changed since the last time we looked at it (like a product page, job listing, or news update).

Why it’s useful:
Get notified when prices drop, job openings go live, or stock comes back — without manually refreshing the page every 10 minutes.

How it works:
Python downloads the webpage text and compares it to the version saved last time. If anything’s different, it tells us something has changed.

✅ Use Case: Track product prices, job boards, event changes.

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6. Automate Git Commit & Push

import os

os.system("git add .")
os.system("git commit -m 'Automated commit'")
os.system("git push origin main")

What it does:
Automatically stages our code changes, creates a Git commit, and pushes it to GitHub.

Why it’s useful:
If we use Git for version control (which we should), this saves time when we’re constantly updating our code. Ideal for automation workflows or backup routines.

How it works:
Python uses system commands to run Git actions behind the scenes, so we don’t have to type them manually in the terminal.

✅ Use Case: Auto-backup code, CI/CD scripting.

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7. Extract Attachments from Emails

import imaplib, email

mail = imaplib.IMAP4_SSL("imap.gmail.com")
mail.login("your_email", "your_password")
mail.select("inbox")

typ, data = mail.search(None, 'ALL')
for num in data[0].split():
    typ, msg_data = mail.fetch(num, '(RFC822)')
    msg = email.message_from_bytes(msg_data[0][1])
    if msg.get_content_maintype() == 'multipart':
        for part in msg.walk():
            if part.get_filename():
                with open(part.get_filename(), 'wb') as f:
                    f.write(part.get_payload(decode=True))

What it does:
Connects to our email inbox, finds emails with attachments, and downloads those attachments to your computer.

Why it’s useful:
You can auto-save invoices, reports, or any files sent to your inbox — especially useful for repetitive or scheduled reports.

How it works:
Python uses a library called imaplib to access your mailbox and email to read the message. It loops through all the messages and saves any attached files it finds.

✅ Use Case: Automatically collect invoices, reports, or logs.

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8. Auto-Post to Twitter (X) Using Tweepy

import tweepy

auth = tweepy.OAuth1UserHandler(api_key, api_secret, access_token, access_secret)
api = tweepy.API(auth)

api.update_status("This is an automated tweet from Python!")

What it does:
Posts a tweet on your Twitter account without you even opening the Twitter app.

Why it’s useful:
Use it to schedule daily tweets, run a Twitter bot, or share updates automatically when something happens (like “new blog published!”).

How it works:
We authenticate our script using your Twitter app credentials, and then the tweepy library lets Python send tweets for us.

✅ Use Case: Auto-posting, content scheduling, bots.

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9. Monitor System Resource Usage

import psutil

print("CPU:", psutil.cpu_percent())
print("RAM:", psutil.virtual_memory().percent)
print("Disk:", psutil.disk_usage('/').percent)

What it does:
Shows us our system's CPU, RAM, and disk usage — basically, a mini task manager in your terminal.

Why it’s useful:
If we run servers, game on our PC, or train AI models, knowing how much memory or CPU is being used helps prevent crashes and slowdowns.

How it works:
Python uses a library called psutil to grab live system stats and prints them out so we can monitor usage in real time or log it.

✅ Use Case: Monitor server health, performance alerts.

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10. Clean Up Old Files Automatically

import os
import time

folder = "/path/to/cleanup"
now = time.time()
for f in os.listdir(folder):
    path = os.path.join(folder, f)
    if os.stat(path).st_mtime < now - 30 * 86400:
        os.remove(path)

What it does:
Deletes old files from a folder, like log files older than 30 days.

Why it’s useful:
Keeps our folders clean and avoids disk space issues. Great for cleanup scripts in development, backups, or temporary folders.

How it works:
Python checks the “last modified time” of every file and deletes the ones that are older than a certain number of days.

✅ Use Case: Log rotation, temp cleanup, auto-delete old files.

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We just Leveled Up our Python Automation Skills…

We’ve now explored how Python can handle,

• Web automation (Selenium)

• Cloud uploads (Google Drive API)

• Email parsing and attachments

• Git and deployment automation

• System health tracking

• Twitter bot posts

• File cleanup routines

By mastering these scripts, we've unlocked…

• API integrations

• Web browser automation

• File I/O

• Dashboarding

These scripts aren’t just cool — they’re actually useful in daily tech jobs, personal projects, DevOps workflows, or content creation pipelines.

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We now have the skillset to:

• Build our own automation suite

• Save hours of repetitive work every week

• Impress clients, managers, or even ourself

🧠 Challenge for you: Pick any 2 automation ideas from above, add logging + email alerts, and schedule them using cron or task scheduler.

Keep automating, and write less, do more.
Python 🤝 Productivity