This repository contains a simple web application for stock market prediction. The application is built using Flask, HTML, and Bootstrap. It provides an interface for viewing different stock indices and is designed to be a starting point for building more advanced stock prediction tools. It is purely made for a college project.
The Stock Market Prediction web app is a basic web application that allows users to view various stock market indices. It currently supports the following indices:
- Nifty 50
- Nifty Bank
- Nifty Financial Services
- Reliance
In addition to the current features, the project has future plans for expansion, including the following:
- Integration of Machine Learning Models for Prediction ๐ค
- Displaying Charts and Visualizations ๐
- Incorporating Tradingview Technical Analysis ๐
The application's user interface is minimal and user-friendly, thanks to the Bootstrap framework. Users can access different indices through the navigation menu on the left-hand side of the web page.
To run this application locally, follow these steps:
-
Clone this repository to your local machine:
git clone https://github.com/AdityaDKale/GarnetMarketEngine.git
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Navigate to the project directory:
cd GarnetMarketEngine/
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Install the required dependencies (Flask):
pip install -r requirements.txt
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Navigate to src folder:
cd src
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Run the following commands in succession:
python model_creation.py
python prediction.py
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Return to base directory:
cd ..
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Run the Flask application:
python main.py
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Open a web browser and visit
http://localhost:81
to view the web application. (Kept on host=0.0.0.0 and port=81 for easy replit setup) -
For accurate predictions run predictions.py daily.
- Upon running the application, you will be directed to the home page displaying the available stock market indices.
- Click on an index name in the navigation menu to view the corresponding stock index page.
- Explore the application to get a basic idea of its functionality.
The following dependencies are used in this project:
- Flask: A micro web framework for Python.
- Bootstrap: A popular HTML, CSS, and JavaScript framework for building responsive and mobile-first web applications.
- Lightweight Charts: Framework to plot charts.
- Keras: For machine learning framework.
Contributions to this project are welcome. If you have any ideas or improvements you'd like to see implemented, please open an issue or submit a pull request.
This project is licensed under the MIT License - see the LICENSE file for details. ๐