fix: stage missing code review fixes (7 files)

Files were edited but not staged in earlier commits:
- adaptive_rhythm_manager.py: mt→mt5, pytz→timezone, get_volatility_level, shutdown()
- check_market_regime.py: ADX_THRESHOLD, Wilder EWM, try/finally, UTC timestamp, sys import
- check_system_status.py: remove duplicate cursor.execute
- drawdown_protection.py: float(inf), persist pause state, DB save_setting, Markdown fix
- performance_analysis.py: KeyError export fix, profit factor, drawdown positive, SQL filter
- performance_analysis_simple.py: fromisoformat, numeric bin sort, profit factor
- trading_dashboard.py: st.rerun(), session_state auto-refresh, pathlib DB path, errors=coerce

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

trading_dashboard.py

@@ -10,6 +10,7 @@ import pandas as pd
 from datetime import datetime, timedelta
 import plotly.express as px
 import plotly.graph_objects as go
+from pathlib import Path
 
 # ==========================================
 # PAGE CONFIG
@@ -25,9 +26,14 @@ st.set_page_config(
 # DATABASE CONNECTION
 # ==========================================
 
+DB_PATH = Path(__file__).parent / "trading_bot.db"
+
 @st.cache_resource
 def get_connection():
-    return sqlite3.connect("trading_bot.db", check_same_thread=False)
+    if not DB_PATH.exists():
+        st.error(f"Database not found: {DB_PATH}")
+        st.stop()
+    return sqlite3.connect(str(DB_PATH), check_same_thread=False)
 
 conn = get_connection()
 
@@ -43,10 +49,10 @@ col1, col2, col3 = st.columns([1, 1, 2])
 with col1:
     if st.button("🔄 Refresh Data"):
         st.cache_data.clear()
-        st.experimental_rerun()
+        st.rerun()
 
 with col2:
-    auto_refresh = st.checkbox("Auto-refresh (30s)")
+    auto_refresh = st.toggle("Auto-refresh (30s)")
 
 with col3:
     trade_filter = st.selectbox(
@@ -56,10 +62,14 @@ with col3:
     )
 
 if auto_refresh:
-    st.markdown("*Auto-refreshing every 30 seconds...*")
-    import time
-    time.sleep(30)
-    st.experimental_rerun()
+    if "last_refresh" not in st.session_state:
+        st.session_state.last_refresh = datetime.now()
+    elapsed = (datetime.now() - st.session_state.last_refresh).total_seconds()
+    if elapsed >= 30:
+        st.session_state.last_refresh = datetime.now()
+        st.rerun()
+    else:
+        st.markdown(f"*Auto-refresh in {30 - int(elapsed)}s...*")
 
 # ==========================================
 # LOAD DATA
@@ -69,38 +79,27 @@ if auto_refresh:
 def load_all_trades():
     query = """
     SELECT
-        ticket,
-        position_id,
-        symbol,
-        strategy_name,
-        type,
-        volume,
-        entry_price,
-        sl_price,
-        tp_price,
-        entry_time,
-        exit_time,
-        session,
-        regime,
-        quality,
-        confidence,
-        timeframe_alignment,
-        risk_amount,
-        risk_pct,
-        net_profit,
-        profit_pct,
-        rr_ratio,
-        status,
-        exit_reason
+        ticket, position_id, symbol, strategy_name, type, volume,
+        entry_price, sl_price, tp_price, entry_time, exit_time,
+        session, regime, quality, confidence, timeframe_alignment,
+        risk_amount, risk_pct, net_profit, profit_pct, rr_ratio,
+        status, exit_reason
     FROM trades
     ORDER BY entry_time DESC
     """
-    return pd.read_sql_query(query, conn)
+    try:
+        return pd.read_sql_query(query, conn)
+    except Exception as e:
+        st.error(f"Error loading trades: {e}")
+        return pd.DataFrame()
 
 @st.cache_data(ttl=30)
 def load_bot_status():
-    query = "SELECT * FROM bot_status ORDER BY timestamp DESC LIMIT 1"
-    return pd.read_sql_query(query, conn)
+    try:
+        return pd.read_sql_query("SELECT * FROM bot_status ORDER BY timestamp DESC LIMIT 1", conn)
+    except Exception as e:
+        st.error(f"Error loading bot status: {e}")
+        return pd.DataFrame()
 
 # Load data
 df_trades_raw = load_all_trades()
@@ -219,7 +218,7 @@ st.subheader("⏰ Trades by Hour (UTC)")
 
 if not df_trades.empty:
     # Extract hour from entry_time (handle both ISO8601 and standard format)
-    df_trades['hour_utc'] = pd.to_datetime(df_trades['entry_time'], format='mixed').dt.hour
+    df_trades['hour_utc'] = pd.to_datetime(df_trades['entry_time'], errors='coerce').dt.hour
 
     # Count trades by hour
     hourly_dist = df_trades.groupby('hour_utc').size().reset_index(name='count')
@@ -338,7 +337,7 @@ st.subheader("💰 Cumulative Profit Over Time")
 
 if closed_trades > 0:
     profit_timeline = df_trades[df_trades['status'] == 'closed'].copy()
-    profit_timeline['exit_time'] = pd.to_datetime(profit_timeline['exit_time'], format='mixed')
+    profit_timeline['exit_time'] = pd.to_datetime(profit_timeline['exit_time'], errors='coerce')
     profit_timeline = profit_timeline.sort_values('exit_time')
     profit_timeline['cumulative_profit'] = profit_timeline['net_profit'].cumsum()