The Python Script That Replaced 3 SaaS Tools for Me
How I cut recurring costs by automating what startups charge $30/month for
Most developers (me included) fall into the trap of signing up for SaaS tools that promise “automation.” Task reminders, notifications, simple data exports — all for $10 to $30 per month. Over time, that adds up. One weekend, I decided to test a theory: could I replace some of these with Python scripts? The answer turned out to be yes. What used to cost me $50/month is now handled by a 70-line Python script running in the background.
Here’s the breakdown of how I built it and how you can do the same.
1. The Problem: SaaS Bloat I was paying for three different services:
- A to-do app with email reminders
- A CSV-to-Google-Sheets sync tool
- A Slack alert bot
Each one seemed “cheap,” but together, they were costing me more than my actual server hosting. The kicker? They all did things Python can handle easily.
2. Setting Up the Python Environment The best part is you don’t need heavy frameworks. Just a few libraries: pip install pandas gspread oauth2client python-telegram-bot schedule
- pandas → handle CSV/Excel data
- gspread + oauth2client → connect with Google Sheets
- python-telegram-bot → send notifications
- schedule → run tasks at intervals
3. Core Automation Logic Here’s the heart of the script. It takes a local CSV, cleans it, and pushes it to Google Sheets automatically:
import pandas as pd
import gspread
from oauth2client.service_account import ServiceAccountCredentials
def sync_csv_to_sheets(csv_path, sheet_name):
# Authorize Google Sheets
scope = ["https://spreadsheets.google.com/feeds",
"https://www.googleapis.com/auth/drive"]
creds = ServiceAccountCredentials.from_json_keyfile_name("creds.json", scope)
client = gspread.authorize(creds)
# Read CSV and upload
df = pd.read_csv(csv_path)
sheet = client.open(sheet_name).sheet1
sheet.clear()
sheet.update([df.columns.values.tolist()] + df.values.tolist())
print("CSV synced to Google Sheets ✅")
This single function replaces a $15/month CSV-sync SaaS.
4. Adding Notifications with Telegram Instead of Slack or email reminders, I used Telegram for free notifications.
from telegram import Bot
def send_notification(message):
bot = Bot(token="YOUR_TELEGRAM_BOT_TOKEN")
chat_id = "YOUR_CHAT_ID"
bot.send_message(chat_id=chat_id, text=message)
Now the script not only updates data but also alerts me instantly when a sync finishes.
5. Scheduling the Tasks I didn’t want to run it manually every day. The schedule library keeps it lightweight:
import schedule, time
def job():
sync_csv_to_sheets("data.csv", "My Data Sheet")
send_notification("Data sync completed!")
schedule.every().day.at("09:00").do(job)
while True:
schedule.run_pending()
time.sleep(1)
That’s it — a full automation system running daily, with no SaaS middleman.
6. Deployment: Keeping It Running I run this script on a cheap VPS using cron jobs (Linux) or Task Scheduler (Windows). For example, with cron:
0 9 * * * /usr/bin/python3 /home/user/auto_sync.py
Now the automation runs every morning, without me ever touching it.
7. Real Savings and Reliability
- CSV Sync SaaS: $15/month → Python script: free
- Slack Notification Bot: $10/month → Telegram: free
- To-do Email Reminder: $12/month → Python scheduled alerts: free
That’s $37/month saved — or $444/year. For a script I wrote in under two hours.
8. Why Building Small Python Tools Is Underrated This wasn’t some giant “startup idea.” It was a tiny script that solved my problem first. Over time, I added features (like filtering rows before syncing) and shared it with a few friends, who now run their own versions.
Instead of paying for SaaS bloat, I get the reliability of owning my own workflow — and it feels way better. 💡 If you’ve got even basic Python skills, try this: pick one SaaS tool you pay for and see if a 50-line script can replace it. You’ll be surprised how often the answer is yes.
Read the full article here: https://python.plainenglish.io/the-python-script-that-replaced-3-saas-tools-for-me-a184d9aa984d