from data.model import Trade from collections import defaultdict import math def _apply_break_even_if_triggered(position, candle, strategy): if not position: return if not getattr(strategy, "use_break_even", False): return if position.get("break_even_armed"): return trigger_rr = float(getattr(strategy, "be_trigger_rr", 1.0) or 0.0) if trigger_rr <= 0: return is_long = position["direction"] == "long" entry = position["entry_price"] risk_distance = max(position.get("risk_distance", 0.0), 0.0) if risk_distance <= 0: return trigger_price = entry + (risk_distance * trigger_rr) if is_long else entry - (risk_distance * trigger_rr) reached_trigger = candle.high >= trigger_price if is_long else candle.low <= trigger_price if reached_trigger: position["stop_loss"] = entry position["break_even_armed"] = True def _apply_partial_tp_if_triggered(position, candle, strategy): if not position: return if not getattr(strategy, "use_partial_tp", False): return if position.get("partial_taken"): return trigger_rr = float(getattr(strategy, "partial_tp_rr", 1.0) or 0.0) if trigger_rr <= 0: return partial_pct = float(getattr(strategy, "partial_tp_percent", 0.0) or 0.0) if partial_pct <= 0: return close_fraction = min(max(partial_pct / 100.0, 0.0), 1.0) remaining_fraction = max(position.get("remaining_fraction", 1.0), 0.0) if remaining_fraction <= 0: position["partial_taken"] = True return close_fraction = min(close_fraction, remaining_fraction) if close_fraction <= 0: return is_long = position["direction"] == "long" entry = position["entry_price"] risk_distance = max(position.get("risk_distance", 0.0), 0.0) if risk_distance <= 0: return trigger_price = entry + (risk_distance * trigger_rr) if is_long else entry - (risk_distance * trigger_rr) reached_trigger = candle.high >= trigger_price if is_long else candle.low <= trigger_price if not reached_trigger: return lot_size = max(position.get("lot_size", 0.0), 0.0) price_move = (trigger_price - entry) if is_long else (entry - trigger_price) realized_piece = price_move * lot_size * close_fraction position["realized_pnl"] = position.get("realized_pnl", 0.0) + realized_piece position["remaining_fraction"] = max(0.0, remaining_fraction - close_fraction) position["partial_taken"] = True def run_backtest(candles, strategy, starting_balance, risk_reward=1.0, max_daily_loss=0.0, max_consecutive_losses=0, risk_pct=1.0): trades = [] position = None consecutive_losses = 0 daily_pnl = defaultdict(float) if hasattr(strategy, "prepare"): strategy.prepare(candles) for i, candle in enumerate(candles): if position: _apply_partial_tp_if_triggered(position, candle, strategy) _apply_break_even_if_triggered(position, candle, strategy) is_long = position["direction"] == "long" sl, tp = position["stop_loss"], position["take_profit"] hit_sl = candle.low <= sl if is_long else candle.high >= sl hit_tp = candle.high >= tp if is_long else candle.low <= tp if hit_sl or hit_tp: exit_price = sl if hit_sl else tp price_move = (exit_price - position["entry_price"]) if is_long else (position["entry_price"] - exit_price) lot_size = max(position.get("lot_size", 0.0), 0.0) remaining_fraction = max(position.get("remaining_fraction", 1.0), 0.0) remaining_pnl = price_move * lot_size * remaining_fraction pnl = position.get("realized_pnl", 0.0) + remaining_pnl initial_risk = max(position.get("initial_risk_amount", 0.0), 1e-12) r_multiple = pnl / initial_risk trades.append(Trade( enter_time=position["enter_time"], enter_price=position["entry_price"], direction=position["direction"], exit_time=candle.time_open, exit_price=exit_price, pnl=pnl, r_multiple=r_multiple, partial_tp_taken=bool(position.get("partial_taken", False)), partial_tp_realized_pnl=float(position.get("realized_pnl", 0.0) or 0.0), )) position = None if pnl <= 0: consecutive_losses += 1 else: consecutive_losses = 0 daily_pnl[candle.time_open.date()] += pnl if position is None: if max_consecutive_losses > 0 and consecutive_losses >= max_consecutive_losses: continue if max_daily_loss > 0: loss_limit = starting_balance * (max_daily_loss / 100) if daily_pnl[candle.time_open.date()] <= -loss_limit: continue signal = strategy.check_signal(candles, i) if signal is not None: is_long = signal.direction == "BUY" entry = signal.entry_price sl = signal.stop_loss sl_distance = abs(entry - sl) if ( sl_distance <= 0 or not math.isfinite(sl_distance) or not math.isfinite(entry) or not math.isfinite(sl) or risk_pct <= 0 ): continue risk_amount = starting_balance * (risk_pct / 100) if risk_amount <= 0 or not math.isfinite(risk_amount): continue lot_size = risk_amount / sl_distance if lot_size <= 0 or not math.isfinite(lot_size): continue tp = entry + (sl_distance * risk_reward) if is_long else entry - (sl_distance * risk_reward) position = { "direction": "long" if is_long else "short", "entry_price": entry, "enter_time": candle.time_open, "stop_loss": sl, "take_profit": tp, "risk_distance": sl_distance, "lot_size": lot_size, "break_even_armed": False, "partial_taken": False, "remaining_fraction": 1.0, "realized_pnl": 0.0, "initial_risk_amount": risk_amount, } return trades def run_backtest_stream(candles, strategy, starting_balance, risk_reward=1.0, max_daily_loss=0.0, max_consecutive_losses=0, risk_pct=1.0): position = None consecutive_losses = 0 daily_pnl = defaultdict(float) total = len(candles) if hasattr(strategy, "prepare"): strategy.prepare(candles) yield {"type": "start", "total_candles": total} progress_interval = max(1, total // 50) for i, candle in enumerate(candles): if i % progress_interval == 0: yield {"type": "progress", "processed_candles": i, "total_candles": total} if position: _apply_partial_tp_if_triggered(position, candle, strategy) _apply_break_even_if_triggered(position, candle, strategy) is_long = position["direction"] == "long" sl, tp = position["stop_loss"], position["take_profit"] hit_sl = candle.low <= sl if is_long else candle.high >= sl hit_tp = candle.high >= tp if is_long else candle.low <= tp if hit_sl or hit_tp: exit_price = sl if hit_sl else tp price_move = (exit_price - position["entry_price"]) if is_long else (position["entry_price"] - exit_price) lot_size = max(position.get("lot_size", 0.0), 0.0) remaining_fraction = max(position.get("remaining_fraction", 1.0), 0.0) remaining_pnl = price_move * lot_size * remaining_fraction pnl = position.get("realized_pnl", 0.0) + remaining_pnl initial_risk = max(position.get("initial_risk_amount", 0.0), 1e-12) r_multiple = pnl / initial_risk trade = Trade( enter_time=position["enter_time"], enter_price=position["entry_price"], direction=position["direction"], exit_time=candle.time_open, exit_price=exit_price, pnl=pnl, r_multiple=r_multiple, partial_tp_taken=bool(position.get("partial_taken", False)), partial_tp_realized_pnl=float(position.get("realized_pnl", 0.0) or 0.0), ) position = None if pnl <= 0: consecutive_losses += 1 else: consecutive_losses = 0 daily_pnl[candle.time_open.date()] += pnl yield {"type": "trade", "trade": trade, "processed_candles": i, "total_candles": total} if position is None: if max_consecutive_losses > 0 and consecutive_losses >= max_consecutive_losses: continue if max_daily_loss > 0: loss_limit = starting_balance * (max_daily_loss / 100) if daily_pnl[candle.time_open.date()] <= -loss_limit: continue signal = strategy.check_signal(candles, i) if signal is not None: is_long = signal.direction == "BUY" entry = signal.entry_price sl = signal.stop_loss sl_distance = abs(entry - sl) if ( sl_distance <= 0 or not math.isfinite(sl_distance) or not math.isfinite(entry) or not math.isfinite(sl) or risk_pct <= 0 ): continue risk_amount = starting_balance * (risk_pct / 100) if risk_amount <= 0 or not math.isfinite(risk_amount): continue lot_size = risk_amount / sl_distance if lot_size <= 0 or not math.isfinite(lot_size): continue tp = entry + (sl_distance * risk_reward) if is_long else entry - (sl_distance * risk_reward) position = { "direction": "long" if is_long else "short", "entry_price": entry, "enter_time": candle.time_open, "stop_loss": sl, "take_profit": tp, "risk_distance": sl_distance, "lot_size": lot_size, "break_even_armed": False, "partial_taken": False, "remaining_fraction": 1.0, "realized_pnl": 0.0, "initial_risk_amount": risk_amount, } yield {"type": "done", "total_candles": total}