wip COB data source - not ready
This commit is contained in:
Dobromir Popov
@ -1300,7 +1300,7 @@ class CleanTradingDashboard:
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"""Update COB data displays with real order book ladders and cumulative stats"""
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try:
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# COB data is critical for trading - keep at 2s interval
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import time
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eth_snapshot = self._get_cob_snapshot('ETH/USDT')
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btc_snapshot = self._get_cob_snapshot('BTC/USDT')
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@ -1352,8 +1352,47 @@ class CleanTradingDashboard:
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if isinstance(btc_snapshot, list):
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btc_snapshot = None
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eth_components = self.component_manager.format_cob_data(eth_snapshot, 'ETH/USDT', eth_imbalance_stats, cob_mode)
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btc_components = self.component_manager.format_cob_data(btc_snapshot, 'BTC/USDT', btc_imbalance_stats, cob_mode)
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# Compute and display COB update rate and include recent aggregated views
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def _calc_update_rate(symbol):
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if not hasattr(self, 'cob_last_update'):
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return "n/a"
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last_ts = self.cob_last_update.get(symbol)
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if not last_ts:
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return "n/a"
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age = time.time() - last_ts
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if age <= 0:
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return "n/a"
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hz = 1.0 / age if age > 0 else 0
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return f"{hz:.1f} Hz"
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# Fetch aggregated 1s COB and recent ~0.2s ticks
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def _recent_ticks(symbol):
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if hasattr(self.data_provider, 'get_cob_raw_ticks'):
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ticks = self.data_provider.get_cob_raw_ticks(symbol, count=25)
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return ticks[-5:] if ticks else []
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return []
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eth_rate = _calc_update_rate('ETH/USDT')
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btc_rate = _calc_update_rate('BTC/USDT')
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eth_agg_1s = self.data_provider.get_cob_1s_aggregated('ETH/USDT') if hasattr(self.data_provider, 'get_cob_1s_aggregated') else []
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btc_agg_1s = self.data_provider.get_cob_1s_aggregated('BTC/USDT') if hasattr(self.data_provider, 'get_cob_1s_aggregated') else []
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eth_recent = _recent_ticks('ETH/USDT')
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btc_recent = _recent_ticks('BTC/USDT')
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eth_components = self.component_manager.format_cob_data(
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eth_snapshot,
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'ETH/USDT',
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eth_imbalance_stats,
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cob_mode,
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update_info={'update_rate': eth_rate, 'aggregated_1s': eth_agg_1s[-5:], 'recent_ticks': eth_recent}
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)
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btc_components = self.component_manager.format_cob_data(
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btc_snapshot,
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'BTC/USDT',
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btc_imbalance_stats,
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cob_mode,
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update_info={'update_rate': btc_rate, 'aggregated_1s': btc_agg_1s[-5:], 'recent_ticks': btc_recent}
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)
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return eth_components, btc_components
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@ -3427,23 +3466,28 @@ class CleanTradingDashboard:
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def _get_cob_mode(self) -> str:
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"""Get current COB data collection mode"""
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try:
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# Check if data provider has WebSocket COB integration
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if self.data_provider and hasattr(self.data_provider, 'cob_websocket'):
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# Check WebSocket status
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if hasattr(self.data_provider.cob_websocket, 'status'):
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eth_status = self.data_provider.cob_websocket.status.get('ETH/USDT')
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if eth_status and eth_status.connected:
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return "WS" # WebSocket mode
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# Check if we have recent WebSocket data
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if hasattr(self.data_provider, 'cob_raw_ticks'):
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eth_ticks = self.data_provider.cob_raw_ticks.get('ETH/USDT', [])
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if eth_ticks:
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import time
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latest_tick = eth_ticks[-1]
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tick_time = latest_tick.get('timestamp', 0)
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if isinstance(tick_time, (int, float)) and (time.time() - tick_time) < 10:
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return "WS" # Recent WebSocket data
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# Determine WS mode using provider's enhanced websocket or raw tick recency
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if self.data_provider:
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# Preferred: enhanced websocket status summary
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if hasattr(self.data_provider, 'get_cob_websocket_status'):
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try:
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status = self.data_provider.get_cob_websocket_status()
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overall = status.get('overall_status') or status.get('status')
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if overall in ("active", "ok", "ready"):
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return "WS"
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except Exception:
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pass
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# Fallback: raw ticks recency
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if hasattr(self.data_provider, 'get_cob_raw_ticks'):
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try:
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ticks = self.data_provider.get_cob_raw_ticks('ETH/USDT', count=1)
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if ticks:
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import time
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t = ticks[-1].get('timestamp', 0)
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if isinstance(t, (int, float)) and (time.time() - t) < 5:
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return "WS"
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except Exception:
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pass
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# Check if we have any COB data (REST fallback)
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if hasattr(self, 'latest_cob_data') and 'ETH/USDT' in self.latest_cob_data:
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@ -7193,9 +7237,8 @@ class CleanTradingDashboard:
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if hasattr(self.data_provider, 'get_base_data_input'):
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return self.data_provider.get_base_data_input(symbol)
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# Fallback: create BaseDataInput from available data
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from core.data_models import BaseDataInput, OHLCVBar, COBData
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import random
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# Fallback: create BaseDataInput from available data (no synthetic data)
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from core.data_models import BaseDataInput
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# Get OHLCV data for different timeframes - ensure we have enough data
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ohlcv_1s = self._get_ohlcv_bars(symbol, '1s', 300)
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@ -7206,53 +7249,11 @@ class CleanTradingDashboard:
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# Get BTC reference data
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btc_ohlcv_1s = self._get_ohlcv_bars('BTC/USDT', '1s', 300)
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# Ensure we have minimum required data (pad if necessary)
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def pad_ohlcv_data(bars, target_count=300):
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if len(bars) < target_count:
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# Pad with realistic variation instead of identical bars
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if len(bars) > 0:
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last_bar = bars[-1]
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# Add small random variation to prevent identical data
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for i in range(target_count - len(bars)):
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# Create slight variations of the last bar
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variation = random.uniform(-0.001, 0.001) # 0.1% variation
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new_bar = OHLCVBar(
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symbol=last_bar.symbol,
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timestamp=last_bar.timestamp + timedelta(seconds=i),
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open=last_bar.open * (1 + variation),
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high=last_bar.high * (1 + variation),
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low=last_bar.low * (1 + variation),
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close=last_bar.close * (1 + variation),
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volume=last_bar.volume * (1 + random.uniform(-0.1, 0.1)),
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timeframe=last_bar.timeframe
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)
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bars.append(new_bar)
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else:
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# Create realistic dummy bars with variation
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base_price = 3500.0
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for i in range(target_count):
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# Add realistic price movement
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price_change = random.uniform(-0.02, 0.02) # 2% max change
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current_price = base_price * (1 + price_change)
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dummy_bar = OHLCVBar(
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symbol=symbol,
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timestamp=datetime.now() - timedelta(seconds=target_count-i),
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open=current_price * random.uniform(0.998, 1.002),
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high=current_price * random.uniform(1.000, 1.005),
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low=current_price * random.uniform(0.995, 1.000),
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close=current_price,
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volume=random.uniform(500.0, 2000.0),
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timeframe="1s"
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)
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bars.append(dummy_bar)
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return bars[:target_count] # Ensure exactly target_count
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# Pad all data to required length
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ohlcv_1s = pad_ohlcv_data(ohlcv_1s, 300)
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ohlcv_1m = pad_ohlcv_data(ohlcv_1m, 300)
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ohlcv_1h = pad_ohlcv_data(ohlcv_1h, 300)
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ohlcv_1d = pad_ohlcv_data(ohlcv_1d, 300)
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btc_ohlcv_1s = pad_ohlcv_data(btc_ohlcv_1s, 300)
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# Strictly require sufficient real data; otherwise return None
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datasets = [ohlcv_1s, ohlcv_1m, ohlcv_1h, ohlcv_1d, btc_ohlcv_1s]
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if any(len(ds) < 100 for ds in datasets):
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logger.warning(f"Insufficient real OHLCV data for {symbol}; skipping BaseDataInput fallback")
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return None
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logger.debug(f"OHLCV data lengths: 1s={len(ohlcv_1s)}, 1m={len(ohlcv_1m)}, 1h={len(ohlcv_1h)}, 1d={len(ohlcv_1d)}, BTC={len(btc_ohlcv_1s)}")
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@ -296,14 +296,17 @@ class DashboardComponentManager:
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logger.error(f"Error formatting system status: {e}")
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return [html.P(f"Error: {str(e)}", className="text-danger small")]
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def format_cob_data(self, cob_snapshot, symbol, cumulative_imbalance_stats=None, cob_mode="Unknown"):
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"""Format COB data into a split view with summary, imbalance stats, and a compact ladder."""
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def format_cob_data(self, cob_snapshot, symbol, cumulative_imbalance_stats=None, cob_mode="Unknown", update_info: dict = None):
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"""Format COB data into a split view with summary, imbalance stats, and a compact ladder.
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update_info can include keys: 'update_rate', 'aggregated_1s', 'recent_ticks'.
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"""
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try:
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if not cob_snapshot:
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return html.Div([
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html.H6(f"{symbol} COB", className="mb-2"),
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html.P("No COB data available", className="text-muted small"),
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html.P(f"Mode: {cob_mode}", className="text-muted small")
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html.P(f"Mode: {cob_mode}", className="text-muted small"),
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html.P(f"Update: {(update_info or {}).get('update_rate', 'n/a')}", className="text-muted small")
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])
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# Defensive: If cob_snapshot is a list, log and return error
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@ -312,7 +315,8 @@ class DashboardComponentManager:
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return html.Div([
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html.H6(f"{symbol} COB", className="mb-2"),
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html.P("Invalid COB data format (list)", className="text-danger small"),
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html.P(f"Mode: {cob_mode}", className="text-muted small")
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html.P(f"Mode: {cob_mode}", className="text-muted small"),
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html.P(f"Update: {(update_info or {}).get('update_rate', 'n/a')}", className="text-muted small")
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])
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# Debug: Log the type and structure of cob_snapshot
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@ -347,7 +351,9 @@ class DashboardComponentManager:
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if mid_price == 0 or not bids or not asks:
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return html.Div([
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html.H6(f"{symbol} COB", className="mb-2"),
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html.P("Awaiting valid order book data...", className="text-muted small")
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html.P("Awaiting valid order book data...", className="text-muted small"),
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html.P(f"Mode: {cob_mode}", className="text-muted small"),
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html.P(f"Update: {(update_info or {}).get('update_rate', 'n/a')}", className="text-muted small")
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])
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# Create stats dict for compatibility with existing code
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@ -362,15 +368,38 @@ class DashboardComponentManager:
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}
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# --- Left Panel: Overview and Stats ---
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# Prepend update info to overview
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overview_panel = self._create_cob_overview_panel(symbol, stats, cumulative_imbalance_stats, cob_mode)
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if update_info and update_info.get('update_rate'):
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# Wrap with a small header line for update rate
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overview_panel = html.Div([
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html.Div(html.Small(f"Update: {update_info['update_rate']}", className="text-muted"), className="mb-1"),
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overview_panel
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])
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# --- Right Panel: Compact Ladder ---
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ladder_panel = self._create_cob_ladder_panel(bids, asks, mid_price, symbol)
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# Append small extras line from aggregated_1s and recent_ticks
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extras = []
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if update_info:
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agg = (update_info.get('aggregated_1s') or [])
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if agg and isinstance(agg[-1], dict):
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last = agg[-1]
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avg_spread = last.get('spread', {}).get('average_bps', 0)
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avg_imb = last.get('imbalance', {}).get('average', 0)
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tick_count = last.get('tick_count', 0)
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extras.append(html.Small(f"1s agg: {tick_count} ticks, spread {avg_spread:.1f} bps, imb {avg_imb:.2f}", className="text-muted"))
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recent = (update_info.get('recent_ticks') or [])
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if recent:
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extras.append(html.Small(f"Recent ticks: {len(recent)}", className="text-muted ms-2"))
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extras_div = html.Div(extras, className="mb-1") if extras else None
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return dbc.Row([
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dbc.Col(overview_panel, width=5, className="pe-1"),
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dbc.Col(ladder_panel, width=7, className="ps-1")
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], className="g-0") # g-0 removes gutters
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children = [dbc.Col(overview_panel, width=5, className="pe-1")]
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right_children = [ladder_panel]
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if extras_div:
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right_children.insert(0, extras_div)
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children.append(dbc.Col(html.Div(right_children), width=7, className="ps-1"))
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return dbc.Row(children, className="g-0") # g-0 removes gutters
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except Exception as e:
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logger.error(f"Error formatting split COB data: {e}")
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