AlgoTradeIND

AlgoTradeIND is a stock trading web application that provides real-time price updates using WebSockets and technical indicator-based trading signals. The app supports trading on both the NASDAQ (US) and Nifty Fifty (India) markets, ensuring that signals are generated according to their respective market timings.

Features

• Live Stock Price Updates: Utilizes yliveticker WebSocket connections for real-time data.
• Signal Generation: Uses yfinance to analyze 60 days of historical data and generate buy/sell signals.
• Responsive UI: Built with TailwindCSS (installed locally) for a modern and clean interface.
• Paper Trading: Practice buying and selling stocks based on dynamically generated trading signals.

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Usage

• Live price updates and signal generation are available even without the database setup.
• If you only need real-time stock prices and trading signals, you can skip the database setup.
• For full paper trading functionality, complete the admin panel setup and user account creation.

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Getting Started

1. Clone the Repository

mkdir AlgoTradeIND
git clone https://github.com/nestcub/AlgoTradeIND.git
cd AlgoTradeIND

2. Set Up Python Virtual Environment

Create and activate a virtual environment:

python -m venv venv
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate

Install dependencies:

pip install -r requirements.txt

3. Set Up SQLite Database [ Skip to step 4 to avoid current database setup]

Run the following commands to set up the database:

python manage.py makemigrations
python manage.py migrate

Create a superuser for accessing the Django admin panel:

python manage.py createsuperuser

Follow the prompts to set up a username, email, and password.

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4. Set Up TailwindCSS

Open a new terminal in the project directory and run:

npm install

This will install necessary TailwindCSS dependencies and create a node_modules folder.

Start the TailwindCSS build process:

npm run dev

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5. Start the Django Server

Go back to the terminal where the Python virtual environment is activated and run:

python manage.py runserver

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6. Configure the Admin Panel [Skip this step if skipped step 3]

1. Open your browser and go to:

   http://127.0.0.1:8000/admin/
   

2. Log in with the superuser credentials you created.
3. Create a user, add it to accounts in the admin panel.

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7. Update views.py [Skip this step if skipped step 3]

Modify the following line in views.py to match the username you created in the admin panel.
This line appears twice in different functions:

dummy_user = User.objects.get(username='test1')  # Change 'test1' to your created username

Once updated, you can now run the paper trading model.

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Tech Stack

• Backend: Django, WebSockets (yliveticker), yfinance
• Frontend: Django Templates, TailwindCSS
• Database: SQLite (default) or PostgreSQL (optional)

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Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository
2. Create a new branch (feature-branch)
3. Commit your changes
4. Open a pull request

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