Overview

For a long time, I struggled with last-minute travel. Whether for business or family, sudden trips meant scrambling for intercity bus tickets—often on the same day or the next. But like many Iranians, I faced a common issue: by the time you check, all the tickets are gone.

And yet, I knew this wasn't always the end of the story. Canceled tickets pop up randomly. The real challenge? Catching them faster than everyone else.
So I thought to myself: why not automate this?

The Problem

When you're chasing canceled tickets, you're stuck in a brutal loop:

  • Refreshing ticket pages every few seconds

  • Hoping someone cancels their seat

  • Competing with others doing the exact same thing

  • Missing out while you're asleep, away, or simply distracted

Even though websites like Safar724 made booking easier, they didn’t notify users of cancellations. That's when the idea hit me: let’s build a bot to watch the site for me—nonstop, day and night.

The Solution

I developed a web application named Ticketyab that:

  • Takes your origin, destination, date, time range, and phone number

  • Uses Selenium with headless Chrome to monitor [Safar724] in real-time

  • Sends you an SMS alert via Faraz SMS the moment a ticket appears in your desired window

  • Runs on a Linux server so you don’t even need your laptop online

From an architecture point of view, it's powered by:

  • Django (for backend and admin panel)

  • Selenium (for automated browsing & dynamic scraping)

  • PostgreSQL / SQLite (for search records)

  • Faraz SMS API (for instant mobile notifications)

I even built a simple UI so users can submit their search parameters through a browser. No CLI, no technical setup required.

What This Project Demonstrates

Besides being useful in real life, this project showcases several important skills:

  • End-to-End Full Stack Automation

  • Real-Time Scraping of JavaScript-heavy websites

  • Headless Browser Deployment on Ubuntu Server

  • Django Forms, Views, Admin, and Background Tasks

  • Secure API usage (via .env and token-based services)

  • User-oriented design & notification-based UX

It also demonstrates an important mindset for data scientists and developers:
💡 Don't just analyze problems. Build things that solve them.

Try it or Fork it

Want to explore the code or build on it?

👉 View the GitHub Repository
👉 Connect with me on LinkedIn

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