Step 1: Setup Backend pip install fastapi uvicorn websockets redis sqlalchemy pandas Step 2: Project Structure backend/ ├── main.py ├── strategy/ │ └── orb.py ├── brokers/ │ ├── angel.py │ ├── zerodha.py │ └── shoonya.py ├── websocket/ │ └── market_data.py ├── models/ ├── services/ └── utils/ Step 3: ORB Strategy Code class ORBStrategy: def __init__(self, symbol, expansion=0.13): self.symbol = symbol self.expansion = expansion self.high = None self.low = None self.mid = None self.triggered = False def calculate_range(self, candles): self.high = max(c['high'] for c in candles) self.low = min(c['low'] for c in candles) self.mid = (self.high + self.low) / 2 def get_levels(self): range_val = self.high - self.low upper = self.mid + (range_val * self.expansion) lower = self.mid - (range_val * self.expansion) return upper, lower def check_signal(self, price): upper, lower = self.get_levels() if price > upper and not self.triggered: self.triggered = True return "BUY" elif price < lower and not self.triggered: self.triggered = True return "SELL" return None 🔌 4. Market Data Integration A. Broker WebSocket (Primary) Angel One SmartAPI Zerodha Kite Connect Shoonya API B. Backup Data TwelveData WebSocket TradingView socket (unofficial) Example WebSocket Handler async def on_price_update(symbol, price): strategy = strategies[symbol] signal = strategy.check_signal(price) if signal: execute_trade(symbol, signal) 🔐 5. Broker Integration Supported Brokers: Angel One Zerodha Shoonya Features: Login via API credentials Place orders Fetch positions Fetch order book Example Order Execution def execute_trade(symbol, signal): if signal == "BUY": broker.place_order(symbol, "BUY", qty=1) elif signal == "SELL": broker.place_order(symbol, "SELL", qty=1) 📊 6. Database Design Tables Users id email broker_credentials Trades id symbol entry_price exit_price pnl status Watchlist id user_id symbols[] 📈 7. Live PnL Calculation pnl = (current_price - entry_price) * qty For SELL: pnl = (entry_price - current_price) * qty 🖥️ 8. Frontend (React) Pages Dashboard PnL Active trades Strategy status Watchlist Add/remove symbols Click → attach strategy Trading Panel Buy / Sell / Exit Strategy Start/Pause Example UI Logic 🔄 9. Real-Time Flow User logs in Broker connected WebSocket starts Market data flows Strategy calculates levels Price hits level Signal generated Order executed PnL tracked live 🧪 10. Testing Backtest ORB strategy using historical data Paper trading mode (IMPORTANT before real money) 🚀 11. Deployment Backend AWS EC2 / DigitalOcean Database AWS RDS Redis Elasticache / local Frontend Vercel / Netlify 🔒 12. Important Safety Features Max loss per trade Daily loss limit Kill switch Order retry logic ⚡ 13. Advanced Add-ons (Later) Multi-strategy engine AI-based filtering Auto position sizing Telegram alerts Trading journal analytics 🎯 Final Build Roadmap Phase 1 (Core) ✔ ORB Strategy ✔ Broker login ✔ Live data ✔ Order execution Phase 2 (UI) ✔ Dashboard ✔ Watchlist ✔ Trading panel Phase 3 (Advanced) ✔ PnL tracking ✔ Risk controls ✔ Multi-user system 💡 Reality Check (Important) This is not a small project. It’s equivalent to building a mini version of: Zerodha Kite TradingView You’ll need: Backend dev skills Market microstructure understanding Broker API handling

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