Basic Examples

#!/usr/bin/env python3
"""
Simple test of RLXBT SDK

Note: This example requires either:
1. Development build with `--features offline_license` (no license required)
2. Production build with valid license key (set RLX_LICENSE_KEY env var or pass to Backtester)

Get your license at https://rlxbt.com/pricing
"""

import sys
import os
import pandas as pd
import numpy as np

from rlxbt import Strategy, Backtester, load_data


class SimpleMAStrategy(Strategy):
    """Simple Moving Average Crossover Strategy"""

    def __init__(self, fast_period=10, slow_period=20):
        super().__init__()
        self.fast_period = fast_period
        self.slow_period = slow_period

    def generate_signals(self, data: pd.DataFrame) -> pd.DataFrame:
        close = data["close"]

        # Calculate indicators
        fast_ma = close.rolling(window=self.fast_period).mean()
        slow_ma = close.rolling(window=self.slow_period).mean()

        # Generate signals
        signals = np.zeros(len(data), dtype=int)

        # Long when fast > slow
        signals[fast_ma > slow_ma] = 1
        # Short when fast < slow
        signals[fast_ma < slow_ma] = -1

        df = pd.DataFrame(index=data.index)
        df["signal"] = signals

        return df


def run_test():
    print("🚀 Running Simple Test")

    # Check for license key (optional in dev builds)
    license_key = os.environ.get("RLX_LICENSE_KEY")
    if license_key:
        print(f"🔑 Using license key: {license_key[:20]}...")
    else:
        print("ℹ️  No license key set (OK for development builds)")

    # Load data
    data_path = "data/BTCUSDT_1h_with_indicators.csv"
    data = load_data(data_path)
    print(f"📊 Loaded {len(data)} bars")

    # Create strategy
    strategy = SimpleMAStrategy(fast_period=10, slow_period=20)

    # Create backtester
    backtester = Backtester(
        initial_capital=10000.0,
        license_key=license_key,
    )

    # Run backtest
    results = backtester.run(strategy, data)

    # Print results
    print("\n📊 Results:")
    print(f"Total Return: {results['total_return']:.2%}")
    print(f"Sharpe Ratio: {results['sharpe_ratio']:.2f}")
    print(f"Max Drawdown: {results['max_drawdown']:.2%}")
    print(f"Total Trades: {results['total_trades']}")
    print(f"Win Rate: {results['win_rate']:.2%}")


if __name__ == "__main__":
    run_test()

class MAWithStops(Strategy):
    def generate_signals(self, data: pd.DataFrame) -> pd.DataFrame:
        close = data["close"]
        fast_ma = close.rolling(10).mean()
        slow_ma = close.rolling(20).mean()

        df = pd.DataFrame(index=data.index)
        df["signal"] = np.where(fast_ma > slow_ma, 1, 
                         np.where(fast_ma < slow_ma, -1, 0))
        
        # Add dynamic stop loss and take profit
        df["stop_loss"] = np.where(
            df["signal"] == 1,
            close * 0.98,  # 2% below for longs
            close * 1.02   # 2% above for shorts
        )
        df["take_profit"] = np.where(
            df["signal"] == 1,
            close * 1.04,  # 4% above for longs
            close * 0.96   # 4% below for shorts
        )
        
        return df