Real-Time Stock Market Visualizer

A real-time stock market visualization tool built using the Fyers WebSocket API and Python.

This application:

• Fetches historical OHLCV (Open, High, Low, Close, Volume) market data
• Streams real-time live market ticks
• Dynamically updates candlestick charts in real-time

The project demonstrates:

• Real-time market data streaming
• Candlestick generation from live ticks
• Volume reconstruction using cumulative exchange volume
• Financial data visualization using Python

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📈 What is a Candlestick Chart?

A candlestick chart is one of the most commonly used chart types in financial markets.

Each candle represents price activity over a fixed interval of time (1 minute in this project).

A single candle contains:

Component	Meaning
Open	Price at the beginning of the interval
High	Highest traded price during the interval
Low	Lowest traded price during the interval
Close	Price at the end of the interval
Volume	Number of shares/contracts traded

Candlestick charts help traders visualize:

• Market trends
• Momentum
• Volatility
• Reversal patterns
• Buying/Selling pressure

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⚡ Features

• Real-time WebSocket-based market updates
• Historical + live data synchronization
• Dynamic candlestick creation
• Real-time volume bars
• Automatic candle updates every second
• Timezone-aware timestamps (IST)
• Memory-efficient rolling candle window
• Live matplotlib animation

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🛠 Technologies Used

Technology	Purpose
Python	Core programming language
Pandas	Data manipulation
Matplotlib	Plotting engine
mplfinance	Financial charting
Fyers API v3	Market data access
WebSocket	Real-time streaming
pytz	Timezone handling

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📂 Project Structure

project/
│
├── autoLogin.py
├── configuration.py
├── credentials.py
├── historicalData.py
├── main.py
├── newCandlestick.py
├── plot.py
├── requirements.txt
├── LICENSE
└── README.md

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📦 Requirements

Install dependencies using:

pip install -r requirements.txt

Example requirements.txt:

pandas
matplotlib
mplfinance
pytz
fyers-apiv3

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🔑 API Setup

To run this project you need:

• A Fyers trading account
• API credentials
• Access token

Generate the access token using:

python autoLogin.py

Note: Due to SEBI guidelines, a new access token must be generated daily.

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▶️ Running the Program

Run:

python main.py

The application will:

• Fetch historical market data
• Connect to the live WebSocket stream
• Open a real-time updating candlestick chart

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🧠 How Volume Reconstruction Works

The WebSocket feed provides:

• Total traded volume for the entire trading session

However, candlestick charts require:

• Volume traded during each candle interval

This project reconstructs candle volume using:

Incremental Volume = Current Total Volume - Previous Total Volume

This is similar to how professional market data systems process exchange feeds.

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⏱ Timeframe

Current configuration:

• 1-minute candles

Can be extended to:

• 5-minute candles
• 15-minute candles
• Hourly candles
• Daily candles

Note: Refer to Fyers API documentation for supported resolutions.

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📊 Example Use Cases

• Real-time market monitoring
• Algorithmic trading dashboards
• Market microstructure analysis
• Quantitative finance projects
• Trading strategy visualization
• Educational demonstrations

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⚠️ Important Notes

• Internet connection is required
• Market must be open for live updates
• Access tokens expire periodically
• Designed primarily for educational and visualization purposes

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🚀 Future Improvements

Potential upgrades:

• Technical indicators (EMA, VWAP, RSI)
• Multi-timeframe charts
• Persistent database storage
• Multi-symbol support
• GUI improvements
• Thread-safe architecture
• Strategy backtesting integration
• Order book visualization

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👨‍💻 Author

Vaibhav Saxena

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📜 License

This project is intended for educational and personal use.