Stock Market Price Tracker
About
This Real-Time Stock Market Price Checker is a web app made with Django and some cool backend stuff like Celery and Django-Channels. It lets you see live stock prices without even logging in, and it updates the data in real-time using WebSockets.The whole thing is built with clean code and is ready to use in real projects. It was made in India and is a solid starting point for anyone who wants to make or add live stock tracking features to a bigger app or website.
Project Overview
| Project Name | Stock Market Real-Time Price Tracker |
|---|---|
| Language/s Used | Python, HTML, CSS, JavaScript |
| Database | SQLite |
| Type | Web Application |
Download New Real Time Projects :-Click here
Available Features
- No Authentication Required: Users can start tracking stocks immediately without signing up or logging in.
- Stock Selection: Select one or multiple stocks to watch.
- Real-Time Price Updates: Prices refresh in real-time using WebSockets.
- Stock Detail View: Each stock includes an option to view additional details.
- Session Tracking: Tracks selected stocks using Django sessions temporarily.
- Admin Access: Includes a test admin panel to explore session storage behavior.
- WebSocket-Powered Live Data: Implements Django-Channels for live communication.
- Queued Background Tasks: Celery with celery-beat schedules data fetching.
- Scalable Design: Modular backend design for future extension.
Technologies Used
- Django – Backend web framework.
- Celery – Handles background task management.
- Celery-Beat – Scheduler for periodic tasks.
- Redis/Memurai – Message broker and channel layer backend.
- Django-Channels – WebSocket-based real-time data delivery.
- SQLite – Temporary session and data storage.
- Django Template Language (DTL) – For dynamic frontend rendering.
- JavaScript – Adds interactivity and enhances real-time functionality.
- Bootstrap 5 – For responsive and polished UI design.
- FontAwesome – For professional-grade icons.
- HTML/CSS – For structuring and styling templates.
How to Run This Application on Local Server (Windows)
⚠️ First, create and activate a virtual environment:
Create virtual environment
python -m venv env
Activate it (for Command Prompt)
env\Scripts\activate
Then run the following commands in separate terminals:
- Run the Django Development Server:
python manage.py runserver - Start the Celery Worker:
celery -A stockmarket.celery worker –pool=solo -l info - Start the Celery Beat Scheduler:
celery -A stockmarket beat -l INFO - (Optional) Purge Old Tasks in the Queue:
celery -A stockmarket purge -f
Admin Credentials (For Testing Purpose)
- Admin Username:
admin - Admin Password:
admin
We have projects Available in all languages:–Click Here
django stock market app github stock price-prediction using machine learning github stock price prediction using django real time stock price prediction project real-time stock-price-prediction github
django trading app stock price prediction website stock price prediction system real time stock market price tracker using django github real time stock market price tracker using django python real time stock market price tracker using django pdf real time stock market price tracker using django free django stock market app github django stock market app githu bstock price prediction using django stock price prediction using machine learning github django trading app real time stock price prediction project
stock price tracker github stock price prediction using machine learning project report pdf stock price prediction website stock market price tracker using django github stock market price tracker using django using python stock market price tracker using django python stock market price tracker using django pdf stock market price tracker using django free stock market price tracker using django example
