🚍 Bus App

A full-stack transit app featuring a Django REST framework and a Multi-threaded Kivy mobile interface.

A Reliable transit apps require robust front-end logic. I built this UK Bus Tracker (v1) as a Proof of Concept to demonstrate a mobile-ready UI (Kivy) capable of processing transit data. To ensure a consistent demo experience without API rate-limiting, v1 utilizes a mocked data engine that simulates real-world bus arrivals.

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📱 App Gallery

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🚀 Features

• 26/26 Passing Unit Tests✅
• Mocked Time - (Proof of concept)
• Multi-threaded Kivy UI
• Django REST Framework Backend (Scalable app structure)

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📦 Installation

1. Clone the repository and install:

git clone https://github.com/reory/bus_app.git
cd bus_app
pip install -r requirements.txt
python manage.py migrate

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Usage

This project requires both the backend and frontend to be running simultaneously.

1. Start the backend:

    python manage.py runserver 

2. Start the frontend: cd frontend

   python main.py

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Project Structure

bus_app/
├── api/                  # Main API Gateway & GTFS Imports
├── bus_backend/          # Project Core
│   ├── apps/             # Modular Business Logic
│   │   ├── notifications/# User alerts & notifications
│   │   ├── realtime/     # Live bus tracking data
│   │   ├── routes/       # GTFS route & stop management
│   │   └── users/        # Custom user models & auth
│   └── settings.py       # Global configuration
├── frontend/             # Kivy Mobile Application
├── tests/                # 26 Unit tests (Backend & Frontend)
├── manage.py             # Django management script
└── main.py               # Kivy entry point

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Testing🚦

The project includes a comprehensive suite of 17 tests covering models, serializers, and the Kivy UI logic.

To run the tests:

pytest

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Technologies Used

• Python 3.x
• Django (REST framework)
• Kivy (UI Framework)
• Pytest (Testing)
• Celery (Task scheduling)

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🛣️ Roadmap Features

• Synthetic GTFS Generator (Faker) The Goal: Build a localized data factory to simulate a bustling city transit network. The Tech: Use faker.providers.address to generate realistic street name bus stops (e.g., "Main St & 4th Ave") and clamp random lat/long coordinates within a tight boundary to simulate a dense downtown core.

• Rust-Powered Schedule Matrix Compiler The Goal: Generate millions of realistic, connected schedule times without melting your CPU. The Tech: Pass your synthetic faker stop lists into a Rust + PyO3 extension. Let Rust handle the heavy loop calculations to instantly generate sequential arrival and departure times (StopTime rows) for thousands of simulated trips.

• Multi-Stop Journey Planner The Goal: Give the app actual point-A to point-B routing capabilities. The Tech: Implement pathfinding algorithms (like Dijkstra’s or Connection Scan) on the backend to calculate the fastest multi-stop trips.

• Offline Spatial Caching The Goal: Keep the app functional when cellular data drops out. The Tech: Embed a lightweight SQLite cache on the Kivy client to store and render route shapes and stop layouts completely offline.

• WebSocket Push Alerts The Goal: Notify riders of sudden route delays instantly. The Tech: Use Django Channels to maintain live WebSocket connections, pushing urgent service disruptions directly to the Kivy UI.

• Personalized Dashboards The Goal: Let users see their daily commute countdown immediately. The Tech: Build a "Favorites" schema allowing users to pin specific stop IDs directly to the launch screen, skipping the route menus entirely.

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Notes

• Version 1.0 Initial release.
• 26 passing unit tests.
• Ensure the Django backend is running before starting the Kivy frontend.

Built By Roy Peters Click here for contact details 😁