fix chart and trade actions
This commit is contained in:
Dobromir Popov
136
web/dashboard.py
136
web/dashboard.py
@ -1209,11 +1209,11 @@ class TradingDashboard:
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if time.time() - cache_time < 3: # Use cached chart if < 3s old for faster updates
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price_chart = getattr(self, '_cached_price_chart', None)
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else:
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price_chart = self._create_price_chart_optimized_v2(symbol)
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price_chart = self._create_price_chart(symbol)
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self._cached_price_chart = price_chart
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self._cached_chart_data_time = time.time()
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else:
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price_chart = self._create_price_chart_optimized_v2(symbol)
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price_chart = self._create_price_chart(symbol)
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self._cached_price_chart = price_chart
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self._cached_chart_data_time = time.time()
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except Exception as e:
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@ -1343,13 +1343,29 @@ class TradingDashboard:
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"""Clear trade history and reset session stats"""
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if n_clicks and n_clicks > 0:
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try:
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# Clear both closed trades and session stats (they're the same now)
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# Store current position status before clearing
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has_position = bool(self.current_position)
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position_info = ""
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if has_position:
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side = self.current_position.get('side', 'UNKNOWN')
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price = self.current_position.get('price', 0)
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size = self.current_position.get('size', 0)
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position_info = f" (Current {side} position preserved: {size:.6f} @ ${price:.2f})"
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# Clear trade history and session stats
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self.clear_closed_trades_history()
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logger.info("DASHBOARD: Trade history and session stats cleared by user")
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return [html.P("Trade history cleared", className="text-success text-center")]
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logger.info(f"DASHBOARD: Trade history cleared by user{position_info}")
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# Provide detailed feedback to user
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feedback_message = "✅ Trade history and session stats cleared"
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if has_position:
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feedback_message += f" • Current {self.current_position.get('side', 'UNKNOWN')} position preserved"
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return [html.P(feedback_message, className="text-success text-center")]
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except Exception as e:
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logger.error(f"Error clearing trade history: {e}")
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return [html.P(f"Error clearing history: {str(e)}", className="text-danger text-center")]
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return [html.P(f"❌ Error clearing history: {str(e)}", className="text-danger text-center")]
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return dash.no_update
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# Leverage slider callback
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@ -1426,7 +1442,7 @@ class TradingDashboard:
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'price': current_price,
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'size': 0.001, # Small test size (max 1 lot)
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'confidence': 1.0, # Manual trades have 100% confidence
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'timestamp': datetime.now(),
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'timestamp': self._now_local(), # Use local timezone for consistency with manual decisions
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'source': 'MANUAL_BUY',
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'mexc_executed': False, # Mark as manual/test trade
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'usd_size': current_price * 0.001
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@ -1464,7 +1480,7 @@ class TradingDashboard:
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'price': current_price,
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'size': 0.001, # Small test size (max 1 lot)
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'confidence': 1.0, # Manual trades have 100% confidence
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'timestamp': datetime.now(),
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'timestamp': self._now_local(), # Use local timezone for consistency with manual decisions
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'source': 'MANUAL_SELL',
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'mexc_executed': False, # Mark as manual/test trade
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'usd_size': current_price * 0.001
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@ -1643,15 +1659,17 @@ class TradingDashboard:
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logger.debug(f"[CHART] Added Williams pivot points using {actual_timeframe} data")
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except Exception as e:
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logger.debug(f"Error adding Williams pivot points to chart: {e}")
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# Continue without pivot points if there's an error
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# Add moving averages if we have enough data
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# Add moving averages if we have enough data - FIXED pandas warnings
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if len(df) >= 20:
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# 20-period SMA
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df['sma_20'] = df['close'].rolling(window=20).mean()
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# 20-period SMA - use .copy() to avoid SettingWithCopyWarning
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df_with_sma = df.copy()
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df_with_sma.loc[:, 'sma_20'] = df_with_sma['close'].rolling(window=20).mean()
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fig.add_trace(
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go.Scatter(
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x=df.index,
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y=df['sma_20'],
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x=df_with_sma.index,
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y=df_with_sma['sma_20'],
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name='SMA 20',
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line=dict(color='#ff1493', width=1),
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opacity=0.8,
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@ -1661,12 +1679,14 @@ class TradingDashboard:
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)
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if len(df) >= 50:
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# 50-period SMA
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df['sma_50'] = df['close'].rolling(window=50).mean()
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# 50-period SMA - use .copy() to avoid SettingWithCopyWarning
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if 'df_with_sma' not in locals():
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df_with_sma = df.copy()
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df_with_sma.loc[:, 'sma_50'] = df_with_sma['close'].rolling(window=50).mean()
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fig.add_trace(
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go.Scatter(
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x=df.index,
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y=df['sma_50'],
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x=df_with_sma.index,
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y=df_with_sma['sma_50'],
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name='SMA 50',
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line=dict(color='#ffa500', width=1),
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opacity=0.8,
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@ -1705,9 +1725,13 @@ class TradingDashboard:
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# Convert decision timestamp to match chart timezone if needed
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if isinstance(decision_time, datetime):
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if decision_time.tzinfo is not None:
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decision_time_utc = decision_time.astimezone(timezone.utc).replace(tzinfo=None)
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# Decision has timezone info, convert to local timezone first, then UTC for comparison
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decision_time_local = decision_time.astimezone(self.timezone)
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decision_time_utc = decision_time_local.astimezone(timezone.utc).replace(tzinfo=None)
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else:
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decision_time_utc = decision_time
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# Decision is naive datetime, assume it's already in local timezone
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decision_time_local = self.timezone.localize(decision_time)
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decision_time_utc = decision_time_local.astimezone(timezone.utc).replace(tzinfo=None)
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else:
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continue
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@ -1844,14 +1868,23 @@ class TradingDashboard:
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if not entry_time or not exit_time:
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continue
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# Convert times to UTC for comparison
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# Convert times to UTC for comparison - FIXED timezone handling
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try:
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if isinstance(entry_time, datetime):
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entry_time_utc = entry_time.astimezone(timezone.utc).replace(tzinfo=None) if entry_time.tzinfo else entry_time
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# If naive datetime, assume it's in local timezone
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if entry_time.tzinfo is None:
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entry_time_utc = self.timezone.localize(entry_time).astimezone(timezone.utc).replace(tzinfo=None)
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else:
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entry_time_utc = entry_time.astimezone(timezone.utc).replace(tzinfo=None)
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else:
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continue
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if isinstance(exit_time, datetime):
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exit_time_utc = exit_time.astimezone(timezone.utc).replace(tzinfo=None) if exit_time.tzinfo else exit_time
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# If naive datetime, assume it's in local timezone
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if exit_time.tzinfo is None:
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exit_time_utc = self.timezone.localize(exit_time).astimezone(timezone.utc).replace(tzinfo=None)
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else:
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exit_time_utc = exit_time.astimezone(timezone.utc).replace(tzinfo=None)
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else:
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continue
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@ -1861,6 +1894,9 @@ class TradingDashboard:
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if (chart_start_utc <= entry_time_pd <= chart_end_utc) or (chart_start_utc <= exit_time_pd <= chart_end_utc):
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chart_trades.append(trade)
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except Exception as e:
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logger.debug(f"Error processing trade timestamps: {e}")
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continue
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# Minimal logging - only show count
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if len(chart_trades) > 0:
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@ -2415,7 +2451,7 @@ class TradingDashboard:
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'symbol': symbol,
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'price': current_price,
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'confidence': confidence,
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'timestamp': datetime.now(timezone.utc), # Use UTC to match candle data
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'timestamp': self._now_local(), # Use local timezone for consistency with manual decisions
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'size': 0.1, # Will be adjusted by confidence in processing
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'reason': f'Scalping BUY: momentum={momentum:.6f}, trend={trend_strength:.6f}, conf={confidence:.3f}'
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}
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@ -2434,7 +2470,7 @@ class TradingDashboard:
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'symbol': symbol,
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'price': current_price,
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'confidence': confidence,
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'timestamp': datetime.now(timezone.utc), # Use UTC to match candle data
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'timestamp': self._now_local(), # Use local timezone for consistency with manual decisions
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'size': 0.1, # Will be adjusted by confidence in processing
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'reason': f'Scalping SELL: momentum={momentum:.6f}, trend={trend_strength:.6f}, conf={confidence:.3f}'
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}
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@ -2451,7 +2487,7 @@ class TradingDashboard:
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if not decision:
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return
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current_time = datetime.now(timezone.utc) # Use UTC for consistency
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current_time = self._now_local() # Use local timezone for consistency
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# Get fee structure from config (fallback to hardcoded values)
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try:
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@ -2998,14 +3034,22 @@ class TradingDashboard:
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import json
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from datetime import datetime
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# Convert datetime objects to strings for JSON serialization
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# Convert datetime objects to strings for JSON serialization with timezone info
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trades_for_json = []
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for trade in self.closed_trades:
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trade_copy = trade.copy()
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if isinstance(trade_copy.get('entry_time'), datetime):
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trade_copy['entry_time'] = trade_copy['entry_time'].isoformat()
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# Ensure timezone is set before saving
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dt = trade_copy['entry_time']
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if dt.tzinfo is None:
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dt = self.timezone.localize(dt)
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trade_copy['entry_time'] = dt.isoformat()
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if isinstance(trade_copy.get('exit_time'), datetime):
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trade_copy['exit_time'] = trade_copy['exit_time'].isoformat()
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# Ensure timezone is set before saving
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dt = trade_copy['exit_time']
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if dt.tzinfo is None:
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dt = self.timezone.localize(dt)
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trade_copy['exit_time'] = dt.isoformat()
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if isinstance(trade_copy.get('duration'), timedelta):
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trade_copy['duration'] = str(trade_copy['duration'])
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trades_for_json.append(trade_copy)
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@ -3031,12 +3075,20 @@ class TradingDashboard:
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trades_data = json.load(f)
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logger.info(f"LOAD_TRADES: Raw data loaded: {len(trades_data)} trades")
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# Convert string dates back to datetime objects
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# Convert string dates back to datetime objects with proper timezone handling
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for trade in trades_data:
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if isinstance(trade.get('entry_time'), str):
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trade['entry_time'] = datetime.fromisoformat(trade['entry_time'])
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dt = datetime.fromisoformat(trade['entry_time'])
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# If loaded datetime is naive, assume it's in local timezone (Sofia)
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if dt.tzinfo is None:
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dt = self.timezone.localize(dt)
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trade['entry_time'] = dt
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if isinstance(trade.get('exit_time'), str):
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trade['exit_time'] = datetime.fromisoformat(trade['exit_time'])
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dt = datetime.fromisoformat(trade['exit_time'])
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# If loaded datetime is naive, assume it's in local timezone (Sofia)
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if dt.tzinfo is None:
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dt = self.timezone.localize(dt)
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trade['exit_time'] = dt
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if isinstance(trade.get('duration'), str):
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# Parse duration string back to timedelta
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duration_parts = trade['duration'].split(':')
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@ -3054,16 +3106,30 @@ class TradingDashboard:
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self.closed_trades = []
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def clear_closed_trades_history(self):
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"""Clear closed trades history and remove file"""
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"""Clear closed trades history and reset session stats (but keep current positions)"""
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try:
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# Clear closed trades history only
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self.closed_trades = []
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# Reset session statistics (but NOT current position)
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self.total_realized_pnl = 0.0
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self.total_fees = 0.0
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self.session_pnl = 0.0
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# Clear recent decisions related to closed trades but keep current position decisions
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# Keep only the last few decisions that might be related to current open position
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if self.recent_decisions:
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# Keep last 5 decisions in case they're related to current position
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self.recent_decisions = self.recent_decisions[-5:] if len(self.recent_decisions) > 5 else self.recent_decisions
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# Remove file if it exists
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from pathlib import Path
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if Path('closed_trades_history.json').exists():
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Path('closed_trades_history.json').unlink()
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logger.info("Cleared closed trades history")
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# Log what was preserved
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position_status = "PRESERVED" if self.current_position else "NONE"
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logger.info(f"Cleared closed trades history - Current position: {position_status}")
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except Exception as e:
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logger.error(f"Error clearing closed trades history: {e}")
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@ -6318,8 +6384,8 @@ class TradingDashboard:
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logger.error(f"Optimized chart error: {e}")
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return self._create_empty_chart(f"{symbol} Chart", f"Chart Error: {str(e)}")
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def _create_price_chart_optimized(self, symbol, current_price):
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"""Optimized chart creation with minimal data fetching"""
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def _get_williams_pivot_points_for_chart(self, df: pd.DataFrame, chart_df: pd.DataFrame = None) -> List[Dict]:
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"""Get Williams pivot points for chart display"""
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try:
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# Use minimal data for chart
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df = self.data_provider.get_historical_data(symbol, '1m', limit=20, refresh=False)
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