README.md

metadata

title: Fnonse
emoji: 🐠
colorFrom: yellow
colorTo: purple
sdk: streamlit
sdk_version: 1.43.1
app_file: main.py
pinned: false
license: mit
short_description: FNO, stock analysis of NSE listed stocks

NSE Stock Analysis Platform 📈

A comprehensive NSE stock analysis platform built with Streamlit, providing real-time technical indicators, trading signals, and news insights for investors.

Features

• Real-time Stock Analysis: Technical indicators and interactive charts
• AI-Powered Recommendations: Smart stock recommendations based on technical analysis
• Stock Screener: Filter stocks based on custom technical criteria
• Live News Feed: Latest news for NSE stocks using Google News RSS
• Interactive Charts: Multi-timeframe analysis with various technical indicators

Technical Stack

• Frontend: Streamlit
• Data Processing: Pandas, NumPy
• Technical Analysis: Custom implementations of technical indicators
• Data Source: yfinance API
• News Feed: Google News RSS
• Visualization: Plotly

Dependencies

streamlit
pandas
numpy
plotly
yfinance
feedparser
pytz

Deployment on Hugging Face Spaces

1. Create a new Space on Hugging Face:

   • Go to huggingface.co/spaces
   • Click "Create new Space"
   • Select "Streamlit" as the SDK
   • Choose a name for your space

2. Upload the Project Files:

   • Upload all project files to your Space
   • Ensure the file structure matches the repository

3. Configure Environment:

   • The platform will automatically install dependencies
   • The app will run on the default Streamlit port

4. Access Your App:

   • Once deployed, your app will be available at: https://huggingface.co/spaces/[USERNAME]/[SPACE-NAME]

Usage

1. Stock Analysis:

   • Select a stock from the dropdown
   • Choose timeframe and interval
   • View technical indicators and signals

2. Stock Screener:

   • Set your screening criteria
   • Get filtered results based on technical indicators

3. AI Recommendations:

   • View AI-generated stock recommendations
   • Check confidence levels and recommendation basis

4. News Feed:

   • Access latest news for all NSE stocks
   • Click on news titles to read full articles

Local Development

1. Clone the repository
2. Install dependencies: pip install -r requirements.txt
3. Run the app: streamlit run main.py
4. Access at: http://localhost:5000

License

This project is licensed under the MIT License - see the LICENSE file for details.