Bug Cleanup

backend/api/routes.py

@@ -10,7 +10,7 @@ from fastapi import FastAPI, HTTPException, Query
 from fastapi.responses import StreamingResponse
 from fastapi.middleware.cors import CORSMiddleware
 from pydantic import BaseModel, Field
-from indicators.sessions import set_timezone
+
 BACKEND_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
 if BACKEND_DIR not in sys.path:
     sys.path.insert(0, BACKEND_DIR)
@@ -141,13 +141,29 @@ def _get_candles_for_timeframe(dataset_id, timeframe):
 
 
 def _build_strategy(
-    session, lookback, ob_age, atr_mult, use_fvg, use_ob,
+    session="new_york",
-    proximity_pct, sweep, sweep_lookback,
+    lookback=5,
-    min_gap_size, impulse_multiplier, require_unmitigated_fvg,
+    ob_age=50,
-    require_bos_confluence, min_ob_size, require_fvg_ob_confluence,
+    atr_mult=1.5,
-    asian_sweep_only, day_filter,
+    use_fvg=True,
-    use_break_even=False, be_trigger_rr=1.0,
+    use_ob=True,
-    use_partial_tp=False, partial_tp_rr=1.0, partial_tp_percent=50.0,
+    proximity_pct=0.3,
+    sweep=True,
+    sweep_lookback=10,
+    min_gap_size=0.0,
+    impulse_multiplier=0.0,
+    require_unmitigated_fvg=True,
+    require_bos_confluence=False,
+    min_ob_size=0.0,
+    require_fvg_ob_confluence=False,
+    asian_sweep_only=False,
+    day_filter=None,
+    use_break_even=False,
+    be_trigger_rr=1.0,
+    use_partial_tp=False,
+    partial_tp_rr=1.0,
+    partial_tp_percent=50.0,
+    timezone="est",
 ):
     return ICTStrategy(
         session=session,
@@ -172,6 +188,7 @@ def _build_strategy(
         use_partial_tp=use_partial_tp,
         partial_tp_rr=partial_tp_rr,
         partial_tp_percent=partial_tp_percent,
+        timezone=timezone,
     )
 
 
@@ -189,12 +206,28 @@ def _trade_payload(trade):
     }
 
 
-def _stats_payload(trades, rr):
+def _stats_payload(trades, rr, starting_balance=10000.0):
     total_pnl = sum(t.pnl for t in trades)
     winners = [t for t in trades if t.pnl > 0]
     losers = [t for t in trades if t.pnl <= 0]
     partial_tp_trades = [t for t in trades if getattr(t, "partial_tp_taken", False)]
     partial_tp_realized_total = sum(float(getattr(t, "partial_tp_realized_pnl", 0.0) or 0.0) for t in partial_tp_trades)
+    pnls = [t.pnl for t in trades]
+    returns = [(p / starting_balance) for p in pnls] if starting_balance > 0 else []
+    mean_return = (sum(returns) / len(returns)) if returns else 0.0
+    variance = (sum((r - mean_return) ** 2 for r in returns) / len(returns)) if returns else 0.0
+    std_dev = variance ** 0.5
+    sharpe_ratio = ((mean_return / std_dev) * (len(returns) ** 0.5)) if std_dev > 0 else 0.0
+
+    equity_points = _build_equity_points(trades, starting_balance=starting_balance)
+    peak = equity_points[0] if equity_points else starting_balance
+    max_drawdown_pct = 0.0
+    for value in equity_points:
+        if value > peak:
+            peak = value
+        drawdown_pct = ((peak - value) / peak) * 100 if peak > 0 else 0.0
+        if drawdown_pct > max_drawdown_pct:
+            max_drawdown_pct = drawdown_pct
     return {
         "total_trades": len(trades),
         "winners": len(winners),
@@ -208,6 +241,8 @@ def _stats_payload(trades, rr):
         "partial_tp_rate": (len(partial_tp_trades) / len(trades) * 100) if trades else 0,
         "partial_tp_realized_total": partial_tp_realized_total,
         "partial_tp_realized_avg": (partial_tp_realized_total / len(partial_tp_trades)) if partial_tp_trades else 0,
+        "sharpe_ratio": round(sharpe_ratio, 6),
+        "max_drawdown_pct": round(max_drawdown_pct, 6),
     }
 
 
@@ -310,7 +345,7 @@ def _risk_metrics(trades, starting_balance=10000.0):
     sortino = (mean_pnl / downside_dev) * (trade_count ** 0.5) if downside_dev > 0 else 0.0
 
     equity_points = _build_equity_points(trades, starting_balance=starting_balance)
-    peak = equity_points[0]
+    peak = equity_points[0] if equity_points else starting_balance
     max_drawdown_pct = 0.0
     for value in equity_points:
         if value > peak:
@@ -319,8 +354,9 @@ def _risk_metrics(trades, starting_balance=10000.0):
         if drawdown_pct > max_drawdown_pct:
             max_drawdown_pct = drawdown_pct
 
-    calmar = (net_pnl / max_drawdown_pct) if max_drawdown_pct > 0 else 0.0
+    calmar = ((net_pnl / starting_balance) * 100 / max_drawdown_pct) if max_drawdown_pct > 0 else 0.0
-    recovery = (net_pnl / max_drawdown_pct) if max_drawdown_pct > 0 else 0.0
+    drawdown_amount = starting_balance * (max_drawdown_pct / 100) if max_drawdown_pct > 0 else 0.0
+    recovery = (net_pnl / drawdown_amount) if drawdown_amount > 0 else 0.0
 
     if trade_count < 80:
         trade_score = max(0.0, trade_count / 80)
@@ -524,10 +560,7 @@ def get_backtest(
     max_consecutive_losses: int = 0,
 ):
     dataset_id = _resolve_dataset(dataset)
-    if "MT5" in dataset.upper():
+    timezone = "mt5" if "MT5" in dataset.upper() else "est"
-        set_timezone("mt5")
-    else:
-        set_timezone("est")
     candles = _get_candles_for_timeframe(dataset_id, timeframe)
 
     strategy = _build_strategy(
@@ -541,6 +574,7 @@ def get_backtest(
          asian_sweep_only=asian_sweep_only, day_filter=day_filter,
          use_break_even=use_break_even, be_trigger_rr=be_trigger_rr,
          use_partial_tp=use_partial_tp, partial_tp_rr=partial_tp_rr, partial_tp_percent=partial_tp_percent,
+        timezone=timezone,
      )
     trades = run_backtest(
         candles, strategy, 10000, risk_reward=rr,
@@ -551,7 +585,7 @@ def get_backtest(
     return {
         "trades": [_trade_payload(t) for t in trades],
         "candle_times": [c.time_open.isoformat() for c in candles],
-        "stats": _stats_payload(trades, rr),
+        "stats": _stats_payload(trades, rr, starting_balance=10000.0),
     }
 
 
@@ -585,6 +619,7 @@ def backtest_monte_carlo(req: MonteCarloRequest):
 @app.post("/api/optimize")
 def get_optimize(req: OptimizeRequest):
     dataset_id = _resolve_dataset(req.dataset)
+    timezone = "mt5" if "MT5" in dataset_id.upper() else "est"
     candles = _get_candles_for_timeframe(dataset_id, req.timeframe)
 
     session_list = req.sessions
@@ -709,6 +744,7 @@ def get_optimize(req: OptimizeRequest):
                 use_partial_tp=params["use_partial_tp"],
                 partial_tp_rr=params["partial_tp_rr"],
                 partial_tp_percent=params["partial_tp_percent"],
+                timezone=timezone,
             )
             trades = run_backtest(candles, strategy, 10000, risk_reward=params["rr"])
 
@@ -815,6 +851,7 @@ def get_optimize_monte_carlo(
     ruin_drawdown_pct: float = Query(default=20.0, ge=0.0, le=100.0),
 ):
     dataset_id = _resolve_dataset(dataset)
+    timezone = "mt5" if "MT5" in dataset_id.upper() else "est"
     candles = _get_candles_for_timeframe(dataset_id, timeframe)
 
     strategy = _build_strategy(
@@ -840,6 +877,7 @@ def get_optimize_monte_carlo(
         partial_tp_rr=partial_tp_rr,
         partial_tp_percent=partial_tp_percent,
         day_filter=None,
+        timezone=timezone,
     )
     trades = run_backtest(candles, strategy, 10000, risk_reward=rr)
     trade_r_multiples = [getattr(t, "r_multiple", 0.0) for t in trades]
@@ -948,6 +986,7 @@ def stream_backtest(
     max_consecutive_losses: int = 0,
 ):
     dataset_id = _resolve_dataset(dataset)
+    timezone = "mt5" if "MT5" in dataset_id.upper() else "est"
     candles = _get_candles_for_timeframe(dataset_id, timeframe)
 
     strategy = _build_strategy(
@@ -961,6 +1000,7 @@ def stream_backtest(
          asian_sweep_only=asian_sweep_only, day_filter=day_filter,
          use_break_even=use_break_even, be_trigger_rr=be_trigger_rr,
          use_partial_tp=use_partial_tp, partial_tp_rr=partial_tp_rr, partial_tp_percent=partial_tp_percent,
+          timezone=timezone,
      )
 
     def _sse(data):
@@ -993,7 +1033,7 @@ def stream_backtest(
                     yield _sse({
                         "type": "trade",
                         "trade": _trade_payload(trade),
-                        "stats": _stats_payload(streamed_trades, rr),
+                        "stats": _stats_payload(streamed_trades, rr, starting_balance=10000.0),
                         "processed_candles": event["processed_candles"],
                         "total_candles": event["total_candles"],
                     })
@@ -1002,7 +1042,7 @@ def stream_backtest(
                     yield _sse({
                         "type": "done",
                         "trades": [_trade_payload(t) for t in streamed_trades],
-                        "stats": _stats_payload(streamed_trades, rr),
+                        "stats": _stats_payload(streamed_trades, rr, starting_balance=10000.0),
                         "duration_ms": round(duration_ms, 1),
                         "candle_times": [c.time_open.isoformat() for c in candles],
                     })

backend/data/loader.py

@@ -1,4 +1,3 @@
-print("File is running")
 import pandas as pd
 from data.model import Candle
 

backend/data/model.py

@@ -28,3 +28,5 @@ class Trade:
     exit_price: float
     pnl: float
     r_multiple: float = 0.0
+    partial_tp_taken: bool = False
+    partial_tp_realized_pnl: float = 0.0

backend/engine/backtester.py

@@ -30,18 +30,66 @@ def _apply_break_even_if_triggered(position, candle, strategy):
         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_tp_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
+
+    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)
+    if lot_size <= 0:
+        return
+
+    partial_pct = min(partial_pct, 100.0)
+    partial_lot = lot_size * (partial_pct / 100.0)
+    if partial_lot <= 0:
+        return
+
+    price_move = (trigger_price - entry) if is_long else (entry - trigger_price)
+    partial_pnl = price_move * partial_lot
+
+    position["lot_size"] = max(lot_size - partial_lot, 0.0)
+    position["partial_tp_taken"] = True
+    position["partial_tp_realized_pnl"] = position.get("partial_tp_realized_pnl", 0.0) + partial_pnl
+
+
 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)
+    equity = float(starting_balance)
     if hasattr(strategy, "prepare"):
         strategy.prepare(candles)
 
     for i, candle in enumerate(candles):
         if position:
             _apply_break_even_if_triggered(position, candle, strategy)
+            _apply_partial_tp_if_triggered(position, candle, strategy)
 
             is_long = position["direction"] == "long"
             sl, tp = position["stop_loss"], position["take_profit"]
@@ -53,7 +101,8 @@ def run_backtest(candles, strategy, starting_balance, risk_reward=1.0,
                 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)
-                pnl = price_move * lot_size
+                partial_pnl = float(position.get("partial_tp_realized_pnl", 0.0) or 0.0)
+                pnl = (price_move * lot_size) + partial_pnl
                 risk_distance = max(position.get("risk_distance", 0.0), 1e-12)
                 r_multiple = price_move / risk_distance
 
@@ -65,8 +114,11 @@ def run_backtest(candles, strategy, starting_balance, risk_reward=1.0,
                     exit_price=exit_price,
                     pnl=pnl,
                     r_multiple=r_multiple,
+                    partial_tp_taken=bool(position.get("partial_tp_taken", False)),
+                    partial_tp_realized_pnl=partial_pnl,
                 ))
                 position = None
+                equity += pnl
 
                 if pnl <= 0:
                     consecutive_losses += 1
@@ -76,6 +128,8 @@ def run_backtest(candles, strategy, starting_balance, risk_reward=1.0,
                 daily_pnl[candle.time_open.date()] += pnl
 
         if position is None:
+            if equity <= 0:
+                continue
             if max_consecutive_losses > 0 and consecutive_losses >= max_consecutive_losses:
                 continue
             if max_daily_loss > 0:
@@ -99,7 +153,7 @@ def run_backtest(candles, strategy, starting_balance, risk_reward=1.0,
                 ):
                     continue
 
-                risk_amount = starting_balance * (risk_pct / 100)
+                risk_amount = equity * (risk_pct / 100)
                 if risk_amount <= 0 or not math.isfinite(risk_amount):
                     continue
 
@@ -118,8 +172,35 @@ def run_backtest(candles, strategy, starting_balance, risk_reward=1.0,
                     "risk_distance": sl_distance,
                     "lot_size": lot_size,
                     "break_even_armed": False,
+                    "partial_tp_taken": False,
+                    "partial_tp_realized_pnl": 0.0,
                 }
 
+    if position and candles:
+        last_candle = candles[-1]
+        is_long = position["direction"] == "long"
+        exit_price = last_candle.close
+        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)
+        partial_pnl = float(position.get("partial_tp_realized_pnl", 0.0) or 0.0)
+        pnl = (price_move * lot_size) + partial_pnl
+        risk_distance = max(position.get("risk_distance", 0.0), 1e-12)
+        r_multiple = price_move / risk_distance
+
+        trades.append(Trade(
+            enter_time=position["enter_time"],
+            enter_price=position["entry_price"],
+            direction=position["direction"],
+            exit_time=last_candle.time_open,
+            exit_price=exit_price,
+            pnl=pnl,
+            r_multiple=r_multiple,
+            partial_tp_taken=bool(position.get("partial_tp_taken", False)),
+            partial_tp_realized_pnl=partial_pnl,
+        ))
+        equity += pnl
+        daily_pnl[last_candle.time_open.date()] += pnl
+
     return trades
 
 
@@ -129,6 +210,7 @@ def run_backtest_stream(candles, strategy, starting_balance, risk_reward=1.0,
     consecutive_losses = 0
     daily_pnl = defaultdict(float)
     total = len(candles)
+    equity = float(starting_balance)
 
     if hasattr(strategy, "prepare"):
         strategy.prepare(candles)
@@ -143,6 +225,7 @@ def run_backtest_stream(candles, strategy, starting_balance, risk_reward=1.0,
 
         if position:
             _apply_break_even_if_triggered(position, candle, strategy)
+            _apply_partial_tp_if_triggered(position, candle, strategy)
 
             is_long = position["direction"] == "long"
             sl, tp = position["stop_loss"], position["take_profit"]
@@ -154,7 +237,8 @@ def run_backtest_stream(candles, strategy, starting_balance, risk_reward=1.0,
                 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)
-                pnl = price_move * lot_size
+                partial_pnl = float(position.get("partial_tp_realized_pnl", 0.0) or 0.0)
+                pnl = (price_move * lot_size) + partial_pnl
                 risk_distance = max(position.get("risk_distance", 0.0), 1e-12)
                 r_multiple = price_move / risk_distance
 
@@ -166,8 +250,11 @@ def run_backtest_stream(candles, strategy, starting_balance, risk_reward=1.0,
                     exit_price=exit_price,
                     pnl=pnl,
                     r_multiple=r_multiple,
+                    partial_tp_taken=bool(position.get("partial_tp_taken", False)),
+                    partial_tp_realized_pnl=partial_pnl,
                 )
                 position = None
+                equity += pnl
 
                 if pnl <= 0:
                     consecutive_losses += 1
@@ -179,6 +266,8 @@ def run_backtest_stream(candles, strategy, starting_balance, risk_reward=1.0,
                 yield {"type": "trade", "trade": trade, "processed_candles": i, "total_candles": total}
 
         if position is None:
+            if equity <= 0:
+                continue
             if max_consecutive_losses > 0 and consecutive_losses >= max_consecutive_losses:
                 continue
             if max_daily_loss > 0:
@@ -202,7 +291,7 @@ def run_backtest_stream(candles, strategy, starting_balance, risk_reward=1.0,
                 ):
                     continue
 
-                risk_amount = starting_balance * (risk_pct / 100)
+                risk_amount = equity * (risk_pct / 100)
                 if risk_amount <= 0 or not math.isfinite(risk_amount):
                     continue
 
@@ -221,6 +310,34 @@ def run_backtest_stream(candles, strategy, starting_balance, risk_reward=1.0,
                     "risk_distance": sl_distance,
                     "lot_size": lot_size,
                     "break_even_armed": False,
+                    "partial_tp_taken": False,
+                    "partial_tp_realized_pnl": 0.0,
                 }
 
+    if position and candles:
+        last_candle = candles[-1]
+        is_long = position["direction"] == "long"
+        exit_price = last_candle.close
+        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)
+        partial_pnl = float(position.get("partial_tp_realized_pnl", 0.0) or 0.0)
+        pnl = (price_move * lot_size) + partial_pnl
+        risk_distance = max(position.get("risk_distance", 0.0), 1e-12)
+        r_multiple = price_move / risk_distance
+
+        trade = Trade(
+            enter_time=position["enter_time"],
+            enter_price=position["entry_price"],
+            direction=position["direction"],
+            exit_time=last_candle.time_open,
+            exit_price=exit_price,
+            pnl=pnl,
+            r_multiple=r_multiple,
+            partial_tp_taken=bool(position.get("partial_tp_taken", False)),
+            partial_tp_realized_pnl=partial_pnl,
+        )
+        equity += pnl
+        daily_pnl[last_candle.time_open.date()] += pnl
+        yield {"type": "trade", "trade": trade, "processed_candles": total, "total_candles": total}
+
     yield {"type": "done", "total_candles": total}

backend/indicators/sessions.py

@@ -22,36 +22,42 @@ SESSIONS_MT5 = {
 _active_sessions = SESSIONS_EST
 
 
+def get_sessions_for_tz(tz="est"):
+    if tz and tz.lower() in ("mt5", "utc+2", "server"):
+        return SESSIONS_MT5
+    return SESSIONS_EST
+
+
 def set_timezone(tz="est"):
     global _active_sessions
-    if tz.lower() in ("mt5", "utc+2", "server"):
+    _active_sessions = get_sessions_for_tz(tz)
-        _active_sessions = SESSIONS_MT5
-    else:
-        _active_sessions = SESSIONS_EST
 
 
-def in_session(candle_time, session_name):
+def in_session(candle_time, session_name, sessions_map=None):
     if session_name == "all":
         return True
-    if session_name not in _active_sessions:
+    active = sessions_map or _active_sessions
+    if session_name not in active:
         return True
 
     t = candle_time.time()
-    start, end = _active_sessions[session_name]
+    start, end = active[session_name]
     if start > end:
         return t >= start or t < end
     return start <= t < end
 
 
-def get_session(candle_time):
+def get_session(candle_time, sessions_map=None):
-    for name in _active_sessions:
+    active = sessions_map or _active_sessions
-        if in_session(candle_time, name):
+    for name in active:
+        if in_session(candle_time, name, sessions_map=active):
             return name
     return "off_hours"
 
 
-def filter_by_session(candles, session_name):
+def filter_by_session(candles, session_name, sessions_map=None):
-    return [c for c in candles if in_session(c.time_open, session_name)]
+    active = sessions_map or _active_sessions
+    return [c for c in candles if in_session(c.time_open, session_name, sessions_map=active)]
 
 
 def in_day_filter(candle_time, allowed_days):
@@ -60,8 +66,9 @@ def in_day_filter(candle_time, allowed_days):
     return candle_time.weekday() in allowed_days
 
 
-def get_asian_range(candles):
+def get_asian_range(candles, sessions_map=None):
-    asian = filter_by_session(candles, "asian")
+    active = sessions_map or _active_sessions
+    asian = filter_by_session(candles, "asian", sessions_map=active)
     if not asian:
         return None
     return {

backend/optimize_categorical.py

@@ -0,0 +1,29 @@
+from data.loader import load_candles, resample_candles
+from engine.backtester import run_backtest
+from strategies.categorical_strategy import CategoricalStrategy
+
+candles_1m = load_candles("data/gbpjpy_jan.csv")
+candles_5m = resample_candles(candles_1m, period=5)
+
+best_pnl = float("-inf")
+best_params = None
+
+for lookback in [10, 15, 20, 30, 40, 50]:
+    for threshold in [0.2, 0.3, 0.4, 0.5, 0.7, 1.0]:
+        for atr_mult in [0.3, 0.4, 0.5, 0.6, 0.7]:
+            strategy = CategoricalStrategy(
+                lookback=lookback,
+                range_threshold=threshold,
+                atr_multiplier=atr_mult
+            )
+            trades = run_backtest(candles_5m, strategy, 10000)
+            if len(trades) < 50:
+                continue
+            total_pnl = sum(t.pnl for t in trades)
+            win_rate = len([t for t in trades if t.pnl > 0]) / len(trades) * 100
+            if total_pnl > best_pnl:
+                best_pnl = total_pnl
+                best_params = (lookback, threshold, atr_mult)
+                print(f"New best: LB={lookback}, TH={threshold}, ATR={atr_mult} -> PnL={total_pnl:.2f}, WR={win_rate:.1f}%, Trades={len(trades)}")
+
+print(f"\nBest: lookback={best_params[0]}, threshold={best_params[1]}, atr_mult={best_params[2]}, PnL={best_pnl:.2f}")

backend/strategies/ict_strategy.py

@@ -3,7 +3,7 @@ from indicators.market_structure import find_swing_points, detect_structure
 from indicators.liquidity import find_liquidity_levels
 from indicators.fvg import find_fvgs
 from indicators.order_blocks import find_order_blocks
-from indicators.sessions import in_session, in_day_filter, get_asian_range
+from indicators.sessions import in_session, in_day_filter, get_asian_range, get_sessions_for_tz
 from collections import defaultdict
 
 
@@ -33,6 +33,7 @@ class ICTStrategy:
             use_partial_tp=False,
             partial_tp_rr=1.0,
             partial_tp_percent=50.0,
+            timezone="est",
     ):
         self.lookback = lookback
         self.atr_mult = atr_mult
@@ -58,6 +59,7 @@ class ICTStrategy:
         self.use_partial_tp = use_partial_tp
         self.partial_tp_rr = partial_tp_rr
         self.partial_tp_percent = partial_tp_percent
+        self.sessions_map = get_sessions_for_tz(timezone)
 
         self.swings = []
         self.structure = []
@@ -88,7 +90,7 @@ class ICTStrategy:
         for c in candles:
             daily[c.time_open.date()].append(c)
         for date, day_candles in daily.items():
-            ar = get_asian_range(day_candles)
+            ar = get_asian_range(day_candles, sessions_map=self.sessions_map)
             if ar:
                 self.asian_ranges[date] = ar
 
@@ -204,7 +206,7 @@ class ICTStrategy:
 
         candle = candles[index]
 
-        if not in_session(candle.time_open, self.session):
+        if not in_session(candle.time_open, self.session, sessions_map=self.sessions_map):
             self.recent_sweep = None
             return None
 

frontend/src/App.jsx

@@ -8,7 +8,7 @@ import {
 import { BacktestingTab } from './components/BacktestingTab';
 import { OptimizerTab } from './components/OptimizerTab';
 import { TradeHistory } from './components/TradeHistory';
-import { motion } from 'motion/react';
+import { motion as Motion } from 'motion/react';
 
 import { EquityCurve } from './components/EquityCurve';
 import { MetricCard } from './components/MetricCard';
@@ -115,6 +115,7 @@ export default function App() {
   const candleSeriesRef = useRef(null);
   const equitySeriesRef = useRef(null);
   const markersRef = useRef(null);
+  const abortControllerRef = useRef(null);
 
   const [mounted, setMounted] = useState(false);
   const [activeTab, setActiveTab] = useState('dashboard');
@@ -194,30 +195,41 @@ export default function App() {
   const loadData = useCallback(async () => {
     const shouldLoadDashboardData = ['dashboard', 'forex-stats', 'trade-history'].includes(activeTab);
     if (!shouldLoadDashboardData) {
+      if (abortControllerRef.current) {
+        abortControllerRef.current.abort();
+      }
       setLoading(false);
       return;
     }
 
+    if (abortControllerRef.current) {
+      abortControllerRef.current.abort();
+    }
+    const controller = new AbortController();
+    abortControllerRef.current = controller;
+
     setLoading(true);
     try {
       const shouldLoadBacktest = showBacktest || activeTab === 'forex-stats';
       const shouldFetchBacktest = shouldLoadBacktest && !hasSharedBacktest;
       const datasetQuery = `dataset=${encodeURIComponent(selectedDataset)}`;
       const fetches = [
-        fetch(`http://localhost:8000/api/candles?timeframe=${timeframe}&${datasetQuery}`),
+        fetch(`http://localhost:8000/api/candles?timeframe=${timeframe}&${datasetQuery}`, { signal: controller.signal }),
-        fetch(`http://localhost:8000/api/indicators?timeframe=${timeframe}&${datasetQuery}`),
+        fetch(`http://localhost:8000/api/indicators?timeframe=${timeframe}&${datasetQuery}`, { signal: controller.signal }),
       ];
       if (shouldFetchBacktest) {
-        fetches.push(fetch(`http://localhost:8000/api/backtest?timeframe=${timeframe}&rr=${riskReward}&lookback=${stratParams.lookback}&ob_age=${stratParams.obAge}&atr_mult=${stratParams.atrMult}&sweep=${stratParams.sweep}&sweep_lookback=${stratParams.sweepLookback}&session=${stratParams.session}&${datasetQuery}`));
+        fetches.push(fetch(`http://localhost:8000/api/backtest?timeframe=${timeframe}&rr=${riskReward}&lookback=${stratParams.lookback}&ob_age=${stratParams.obAge}&atr_mult=${stratParams.atrMult}&sweep=${stratParams.sweep}&sweep_lookback=${stratParams.sweepLookback}&session=${stratParams.session}&${datasetQuery}`, { signal: controller.signal }));
       }
 
       const responses = await Promise.all(fetches);
+      if (controller.signal.aborted) return;
       const candleData = await responses[0].json();
       const indicatorData = await responses[1].json();
       const backtestPayload = shouldFetchBacktest
         ? await responses[2].json()
         : (shouldLoadBacktest ? backtestData : null);
 
+      if (controller.signal.aborted) return;
       const candles = candleData.candles.map((candle) => ({
         time: Math.floor(new Date(candle.time).getTime() / 1000),
         open: candle.open,
@@ -331,10 +343,13 @@ export default function App() {
         setBacktestData(backtestPayload);
       }
     } catch (error) {
+      if (error?.name === 'AbortError') return;
       console.error('Failed to load data:', error);
     } finally {
+      if (!controller.signal.aborted) {
         setLoading(false);
       }
+    }
   }, [activeTab, backtestData, hasSharedBacktest, indicators, riskReward, selectedDataset, showBacktest, timeframe]);
 
   useEffect(() => {
@@ -419,8 +434,18 @@ export default function App() {
   const backtestStats = backtestData?.stats ?? null;
   const equityCurve = useMemo(() => buildEquityCurve(backtestTrades), [backtestTrades]);
   const monthlyReturns = useMemo(() => buildMonthlyReturns(backtestTrades), [backtestTrades]);
-  const maxDrawdown = useMemo(() => calculateMaxDrawdown(equityCurve), [equityCurve]);
+  const maxDrawdown = useMemo(() => {
-  const sharpeRatio = useMemo(() => calculateSharpeRatio(backtestTrades), [backtestTrades]);
+    if (backtestStats?.max_drawdown_pct != null) {
+      return -Math.abs(backtestStats.max_drawdown_pct);
+    }
+    return calculateMaxDrawdown(equityCurve);
+  }, [backtestStats, equityCurve]);
+  const sharpeRatio = useMemo(() => {
+    if (backtestStats?.sharpe_ratio != null) {
+      return backtestStats.sharpe_ratio;
+    }
+    return calculateSharpeRatio(backtestTrades);
+  }, [backtestStats, backtestTrades]);
   const largestWin = useMemo(() => backtestTrades.reduce((best, t) => Math.max(best, t.pnl), 0), [backtestTrades]);
   const largestLoss = useMemo(() => backtestTrades.reduce((worst, t) => Math.min(worst, t.pnl), 0), [backtestTrades]);
   const grossProfit = backtestStats ? backtestStats.winners * backtestStats.avg_win : 0;
@@ -466,7 +491,7 @@ export default function App() {
       <div className="max-w-[1440px] mx-auto px-6 py-8">
 
         {/* Header */}
-        <motion.header
+        <Motion.header
           className="flex justify-between items-center gap-4 mb-8 flex-wrap"
           variants={itemVariants}
           initial="hidden"
@@ -495,7 +520,7 @@ export default function App() {
               <div className="w-2 h-2 bg-[#10b981] animate-pulse" />
             )}
           </div>
-        </motion.header>
+        </Motion.header>
 
         {/* Tabs */}
         <div className="flex gap-2 mb-8 border-b border-[#262626] pb-4">
@@ -521,7 +546,7 @@ export default function App() {
         </div>
 
         {/* Dashboard Tab */}
-        <motion.div
+        <Motion.div
           className="space-y-6"
           variants={containerVariants}
           initial="hidden"
@@ -529,7 +554,7 @@ export default function App() {
           style={{ display: activeTab === 'dashboard' ? 'block' : 'none' }}
         >
           {/* Toolbar */}
-          <motion.div variants={itemVariants} className="p-5 border border-[#262626] bg-[#0a0a0a]">
+          <Motion.div variants={itemVariants} className="p-5 border border-[#262626] bg-[#0a0a0a]">
             <div className="flex flex-wrap gap-6 items-center">
               <div className="flex items-center gap-3">
                 <span className="text-[11px] text-[#737373] font-mono uppercase tracking-widest">Timeframe</span>
@@ -606,31 +631,31 @@ export default function App() {
                 </div>
               </div>
             </div>
-          </motion.div>
+          </Motion.div>
 
           {/* Candlestick Chart */}
-          <motion.section variants={itemVariants} className="border border-[#262626] bg-[#0a0a0a] p-6">
+          <Motion.section variants={itemVariants} className="border border-[#262626] bg-[#0a0a0a] p-6">
             <div className="mb-4">
               <p className="text-[11px] text-[#737373] font-mono uppercase tracking-widest mb-1">Market Chart</p>
               <h2 className="text-[20px] font-semibold tracking-tight">Candles with structure and trade markers</h2>
             </div>
             <div ref={chartContainerRef} className="h-[480px] border border-[#1a1a1a] overflow-hidden" />
-          </motion.section>
+          </Motion.section>
 
           {/* Equity Line (lightweight-charts) */}
           {showBacktest && (
-            <motion.section variants={itemVariants} className="border border-[#262626] bg-[#0a0a0a] p-6">
+            <Motion.section variants={itemVariants} className="border border-[#262626] bg-[#0a0a0a] p-6">
               <div className="mb-4">
                 <p className="text-[11px] text-[#737373] font-mono uppercase tracking-widest mb-1">Equity Curve</p>
                 <h2 className="text-[20px] font-semibold tracking-tight">Strategy balance progression</h2>
               </div>
               <div ref={equityChartRef} className="h-[180px] border border-[#1a1a1a] overflow-hidden" />
-            </motion.section>
+            </Motion.section>
           )}
-        </motion.div>
+        </Motion.div>
 
         {/* Stats Tab */}
-        <motion.div
+        <Motion.div
           className="space-y-6"
           variants={containerVariants}
           initial="hidden"
@@ -638,7 +663,7 @@ export default function App() {
           style={{ display: activeTab === 'forex-stats' ? 'block' : 'none' }}
         >
           {/* Hero */}
-          <motion.section variants={itemVariants} className="grid grid-cols-1 lg:grid-cols-[1.7fr_0.9fr] gap-6 p-8 border border-[#262626] bg-[#0a0a0a]">
+          <Motion.section variants={itemVariants} className="grid grid-cols-1 lg:grid-cols-[1.7fr_0.9fr] gap-6 p-8 border border-[#262626] bg-[#0a0a0a]">
             <div className="flex flex-col gap-4">
               <div className="flex gap-3 flex-wrap text-[13px] font-mono">
               </div>
@@ -656,10 +681,10 @@ export default function App() {
               </select>
               <p className="text-[11px] text-[#525252] font-mono">Switch CSVs here to refresh all metrics and charts.</p>
             </div>
-          </motion.section>
+          </Motion.section>
           
           {/* Metrics Grid */}
-          <motion.section variants={itemVariants} className="grid grid-cols-2 md:grid-cols-3 lg:grid-cols-6 gap-4">
+          <Motion.section variants={itemVariants} className="grid grid-cols-2 md:grid-cols-3 lg:grid-cols-6 gap-4">
             {overviewMetrics.map((metric) => (
               <MetricCard
                 key={metric.label}
@@ -671,15 +696,15 @@ export default function App() {
                 neutral={metric.neutral}
               />
             ))}
-          </motion.section>
+          </Motion.section>
 
           {/* Equity Curve (recharts) */}
-          <motion.section variants={itemVariants}>
+          <Motion.section variants={itemVariants}>
             <EquityCurve data={equityCurve} startingBalance={STARTING_BALANCE} />
-          </motion.section>
+          </Motion.section>
 
           {/* Distribution + Breakdown */}
-          <motion.div variants={itemVariants} className="grid grid-cols-1 lg:grid-cols-2 gap-6">
+          <Motion.div variants={itemVariants} className="grid grid-cols-1 lg:grid-cols-2 gap-6">
             <TradeDistribution
               wins={backtestStats?.winners ?? 0}
               losses={backtestStats?.losers ?? 0}
@@ -695,25 +720,25 @@ export default function App() {
               maxDrawdown={maxDrawdown}
               sharpeRatio={sharpeRatio}
             />
-          </motion.div>
+          </Motion.div>
-        </motion.div>
+        </Motion.div>
 
         {/* Trade History Tab */}
-        <motion.div
+        <Motion.div
           className="space-y-6"
           variants={containerVariants}
           initial="hidden"
           animate={mounted ? 'visible' : 'hidden'}
           style={{ display: activeTab === 'trade-history' ? 'block' : 'none' }}
         >
-          <motion.section variants={itemVariants}>
+          <Motion.section variants={itemVariants}>
             <TradeHistory trades={backtestTrades} />
-          </motion.section>
+          </Motion.section>
-        </motion.div>
+        </Motion.div>
 
         {/* Backtesting Tab */}
         {activeTab === 'backtesting' && (
-            <motion.div
+            <Motion.div
                 variants={containerVariants}
                 initial="hidden"
                 animate={mounted ? 'visible' : 'hidden'}
@@ -724,11 +749,11 @@ export default function App() {
                   onDatasetChange={setSelectedDataset}
                   onBacktestComplete={handleBacktestComplete}
               />
-            </motion.div>
+            </Motion.div>
         )}
 
         {activeTab === 'optimizer' && (
-          <motion.div
+          <Motion.div
             variants={containerVariants}
             initial="hidden"
             animate={mounted ? 'visible' : 'hidden'}
@@ -738,7 +763,7 @@ export default function App() {
               selectedDataset={selectedDataset}
               onDatasetChange={setSelectedDataset}
             />
-          </motion.div>
+          </Motion.div>
         )}
       </div>
     </div>

frontend/src/components/BacktestingTab.jsx

@@ -1,5 +1,5 @@
 import { useCallback, useEffect, useRef, useState } from 'react';
-import { motion } from 'motion/react';
+import { motion as Motion } from 'motion/react';
 import {
   CandlestickSeries,
   LineSeries,
@@ -618,7 +618,7 @@ export function BacktestingTab({ datasets = [], selectedDataset, onDatasetChange
 
   return (
       <div className="space-y-6">
-        <motion.div variants={itemVariants} className="border border-[#262626] bg-[#0a0a0a] p-6">
+        <Motion.div variants={itemVariants} className="border border-[#262626] bg-[#0a0a0a] p-6">
           {/* Header row */}
           <div className="flex items-center justify-between mb-6 flex-wrap gap-4">
             <div>
@@ -817,29 +817,29 @@ export function BacktestingTab({ datasets = [], selectedDataset, onDatasetChange
             <ToggleInput label="Use Break-Even" value={useBreakEven} onChange={setUseBreakEven} />
             <ToggleInput label="Use Partial TP" value={usePartialTp} onChange={setUsePartialTp} />
           </div>
-        </motion.div>
+        </Motion.div>
 
         {/* Chart */}
-        <motion.div variants={itemVariants} className="border border-[#262626] bg-[#0a0a0a] p-6">
+        <Motion.div variants={itemVariants} className="border border-[#262626] bg-[#0a0a0a] p-6">
           <div className="mb-4">
             <p className="text-[11px] text-[#525252] font-mono uppercase tracking-widest mb-1">Backtest Chart</p>
             <h2 className="text-[20px] font-semibold tracking-tight">Trade entries and exits</h2>
           </div>
           <div ref={chartContainerRef} className="h-[420px] border border-[#1a1a1a] overflow-hidden" />
-        </motion.div>
+        </Motion.div>
 
         {/* Equity */}
-        <motion.div variants={itemVariants} className="border border-[#262626] bg-[#0a0a0a] p-6">
+        <Motion.div variants={itemVariants} className="border border-[#262626] bg-[#0a0a0a] p-6">
           <div className="mb-4">
             <p className="text-[11px] text-[#525252] font-mono uppercase tracking-widest mb-1">Equity Curve</p>
             <h2 className="text-[20px] font-semibold tracking-tight">Balance progression</h2>
           </div>
           <div ref={equityChartRef} className="h-[160px] border border-[#1a1a1a] overflow-hidden" />
-        </motion.div>
+        </Motion.div>
 
         {/* Results */}
         {stats && (
-            <motion.div variants={itemVariants} className="border border-[#262626] bg-[#0a0a0a] p-6">
+            <Motion.div variants={itemVariants} className="border border-[#262626] bg-[#0a0a0a] p-6">
               <div className="mb-6">
                 <p className="text-[11px] text-[#525252] font-mono uppercase tracking-widest mb-1">Results</p>
                 <h2 className="text-[20px] font-semibold tracking-tight">Backtest Summary</h2>
@@ -992,8 +992,10 @@ export function BacktestingTab({ datasets = [], selectedDataset, onDatasetChange
                   <p className={`text-[24px] font-semibold ${partialTpRealized >= 0 ? 'text-[#10b981]' : 'text-[#ef4444]'}`}>${formatMoney(partialTpRealized)}</p>
                 </div>
               </div>
-            </motion.div>
+            </Motion.div>
         )}
       </div>
   );
 }
+
+

frontend/src/components/MetricCard.jsx

@@ -1,48 +1,24 @@
-import { motion, useInView } from 'motion/react';
+import { motion as Motion } from 'motion/react';
-import { useEffect, useRef, useState } from 'react';
+import { useMemo } from 'react';
 
 export function MetricCard({ label, value, change, isPositive, isPrimary = false, neutral = false }) {
-  const ref = useRef(null);
+  const displayValue = useMemo(() => {
-  const isInView = useInView(ref, { once: true, amount: 0.3 });
-  const [displayValue, setDisplayValue] = useState('0');
-
-  useEffect(() => {
-    if (!isInView) return;
-
     const numericValue = parseFloat(value.replace(/[^0-9.-]/g, ''));
-    if (isNaN(numericValue)) {
+    if (isNaN(numericValue)) return value;
-      setDisplayValue(value);
-      return;
-    }
-
-    const duration = 1200;
-    const startTime = Date.now();
-
-    const animate = () => {
-      const progress = Math.min((Date.now() - startTime) / duration, 1);
-      const eased = 1 - Math.pow(1 - progress, 3);
-      const current = numericValue * eased;
-
     if (value.includes('$')) {
-        setDisplayValue(`$${current.toLocaleString('en-US', { minimumFractionDigits: 2, maximumFractionDigits: 2 })}`);
+      return `$${numericValue.toLocaleString('en-US', { minimumFractionDigits: 2, maximumFractionDigits: 2 })}`;
-      } else if (value.includes('%')) {
-        setDisplayValue(`${current.toFixed(1)}%`);
-      } else {
-        setDisplayValue(current % 1 === 0 ? Math.round(current).toString() : current.toFixed(2));
     }
-
+    if (value.includes('%')) {
-      if (progress < 1) requestAnimationFrame(animate);
+      return `${numericValue.toFixed(1)}%`;
-    };
+    }
-
+    return numericValue % 1 === 0 ? Math.round(numericValue).toString() : numericValue.toFixed(2);
-    animate();
+  }, [value]);
-  }, [isInView, value]);
 
   const color = neutral ? 'text-[#fafafa]' : isPositive ? 'text-[#10b981]' : 'text-[#ef4444]';
   const changeLabel = typeof change === 'number' ? `${change >= 0 ? '+' : ''}${change.toFixed(1)}%` : change;
 
   return (
-    <motion.div
+    <Motion.div
-      ref={ref}
       className={isPrimary ? 'col-span-2 md:col-span-1' : ''}
       whileHover={{ scale: 1.02 }}
       transition={{ duration: 0.2 }}
@@ -76,6 +52,6 @@ export function MetricCard({ label, value, change, isPositive, isPrimary = false
           )}
         </div>
       </div>
-    </motion.div>
+    </Motion.div>
   );
 }

frontend/src/components/TradeDistribution.jsx

@@ -21,7 +21,7 @@ function CustomTooltip({ active, payload, total }) {
   return null;
 }
 
-export function TradeDistribution({ wins = 0, losses = 0, avgWin = 0, avgLoss = 0, largestWin = 0, largestLoss = 0 }) {
+export function TradeDistribution({ wins = 0, losses = 0, avgWin = 0, avgLoss = 0 }) {
   const total = wins + losses;
   const data = [
     { name: 'Wins', value: wins },

frontend/src/components/TradeHistory.jsx

@@ -1,5 +1,5 @@
 import { useState, useMemo } from 'react';
-import { motion } from 'motion/react';
+import { motion as Motion } from 'motion/react';
 
 function formatCurrency(value) {
     const abs = Math.abs(value);
@@ -104,7 +104,6 @@ export function TradeHistory({ trades = [] }) {
                         pageSlice.map((trade, index) => {
                             const globalIndex = (safeCurrentPage - 1) * ROWS_PER_PAGE + index;
                             const isWin = trade.pnl > 0;
-                            const enterDate = new Date(trade.enter_time);
                             const exitDate = new Date(trade.exit_time);
                             const dateStr = exitDate.toLocaleDateString('en-CA');
                             const timeStr = exitDate.toLocaleTimeString('en-GB', { hour: '2-digit', minute: '2-digit', second: '2-digit' });
@@ -112,7 +111,7 @@ export function TradeHistory({ trades = [] }) {
                             const direction = trade.direction === 'long' ? 'BUY' : 'SELL';
 
                             return (
-                                <motion.tr
+                                <Motion.tr
                                     key={`${trade.enter_time}-${index}`}
                                     className="border-b border-[#1a1a1a] hover:bg-[#111111] transition-colors"
                                     initial={{ opacity: 0 }}
@@ -142,7 +141,7 @@ export function TradeHistory({ trades = [] }) {
                         Closed
                       </span>
                                     </td>
-                                </motion.tr>
+                                </Motion.tr>
                             );
                         })
                     )}