dhan_automate.py

import requests
import time
import pandas as pd
from websocket import create_connection

# DhanHQ API Credentials (replace with your credentials)
API_KEY = "your_api_key"
ACCESS_TOKEN = "your_access_token"
BASE_URL = "https://api.dhan.co"

# User-Defined Variables
USER_INPUT_STOCKS = 3  # Number of top stocks to trade
DEFAULT_LOT_SIZE = 1  # Default lot size
TRAILING_STOP_LOSS_PERCENT = 20  # Default trailing stop loss percentage
EXIT_TIME = "15:25:00"  # Exit all positions before market closes

# Fetch Top Gainers and Losers
def fetch_top_stocks():
    url = f"{BASE_URL}/market-data/top-gainers-losers"
    headers = {"Authorization": f"Bearer {ACCESS_TOKEN}"}
    response = requests.get(url, headers=headers).json()
    gainers = response['data']['gainers'][:10]  # Fetch top 10 gainers
    losers = response['data']['losers'][:10]  # Fetch top 10 losers
    return gainers, losers

# Determine Market Trend
def determine_market_trend(gainers, losers):
    avg_gainers = sum([float(stock['percentageChange']) for stock in gainers]) / len(gainers)
    avg_losers = sum([float(stock['percentageChange']) for stock in losers]) / len(losers)
    return "bullish" if avg_gainers > abs(avg_losers) else "bearish"

# Check First Two 5-Minute Candles
def check_candles(stock_symbol):
    url = f"{BASE_URL}/market-data/candlestick/{stock_symbol}/5m"
    headers = {"Authorization": f"Bearer {ACCESS_TOKEN}"}
    response = requests.get(url, headers=headers).json()
    candles = response['data']['candles'][-2:]  # Last two 5-minute candles
    if len(candles) < 2:
        return False  # Not enough data to evaluate
    return all(candle['close'] > candle['open'] for candle in candles)  # Example for bullish trend

# Place Option Order
def place_order(stock_symbol, option_type, lot_size):
    url = f"{BASE_URL}/orders"
    headers = {"Authorization": f"Bearer {ACCESS_TOKEN}"}
    payload = {
        "symbol": stock_symbol,
        "transactionType": "BUY",
        "orderType": "MARKET",
        "quantity": lot_size,
        "productType": "INTRADAY",
        "optionType": option_type  # 'CE' for Call, 'PE' for Put
    }
    response = requests.post(url, json=payload, headers=headers).json()
    return response

# Monitor Trailing Stop Loss
def monitor_trailing_stop_loss(trade_id, entry_price, stop_loss_percent):
    current_stop_loss = entry_price * (1 - stop_loss_percent / 100)
    while True:
        # Fetch live price
        url = f"{BASE_URL}/market-data/price/{trade_id}"
        headers = {"Authorization": f"Bearer {ACCESS_TOKEN}"}
        response = requests.get(url, headers=headers).json()
        live_price = float(response['data']['lastTradedPrice'])

        # Update trailing stop loss
        if live_price > entry_price:
            entry_price = live_price
            current_stop_loss = entry_price * (1 - stop_loss_percent / 100)

        # Exit if stop loss is hit
        if live_price <= current_stop_loss:
            exit_trade(trade_id)
            break

        # Exit if time is close to market close
        if time.strftime("%H:%M:%S") >= EXIT_TIME:
            exit_trade(trade_id)
            break

        time.sleep(10)  # Wait for 10 seconds before the next check

# Exit Trade
def exit_trade(trade_id):
    url = f"{BASE_URL}/orders/{trade_id}/cancel"
    headers = {"Authorization": f"Bearer {ACCESS_TOKEN}"}
    response = requests.post(url, headers=headers).json()
    print(f"Trade exited: {response}")

# Main Logic
def main():
    gainers, losers = fetch_top_stocks()
    trend = determine_market_trend(gainers, losers)
    stocks_to_trade = gainers if trend == "bullish" else losers

    traded_stocks = 0
    for stock in stocks_to_trade:
        if traded_stocks >= USER_INPUT_STOCKS:
            break
        symbol = stock['symbol']
        if check_candles(symbol):
            option_type = "CE" if trend == "bullish" else "PE"
            response = place_order(symbol, option_type, DEFAULT_LOT_SIZE)
            print(f"Order placed for {symbol}: {response}")

            # Monitor trailing stop loss
            entry_price = float(response['data']['price'])
            trade_id = response['data']['tradeId']
            monitor_trailing_stop_loss(trade_id, entry_price, TRAILING_STOP_LOSS_PERCENT)
            traded_stocks += 1

if __name__ == "__main__":
    main()