wip COB data source - not ready
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Dobromir Popov
@ -86,6 +86,15 @@ class StandardizedDataProvider(DataProvider):
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enabled=True,
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websocket_url="wss://stream.binance.com:9443/ws/",
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symbols_mapping={symbol: symbol.replace('/', '').lower() for symbol in self.symbols}
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),
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# CoinAPI REST for supplemental depth snapshots (merged with WS streams)
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'coinapi': ExchangeConfig(
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exchange_type=ExchangeType.COINAPI,
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weight=0.6,
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enabled=True,
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rest_api_url="https://rest.coinapi.io/v1/",
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symbols_mapping={symbol: symbol.replace('/', '_').replace('USDT', 'USD') for symbol in self.symbols},
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rate_limits={"min_interval_ms": 500}
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)
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}
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@ -229,69 +238,24 @@ class StandardizedDataProvider(DataProvider):
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COBData: COB data with price buckets and moving averages
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"""
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try:
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if not self.cob_provider:
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# Use real-time COB snapshot from parent and convert to COBData
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cob_obj = self._get_latest_cob_data_object(symbol)
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if cob_obj is None:
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return None
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# Get current price
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current_price = self.current_prices.get(symbol.replace('/', '').upper(), 0.0)
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if current_price <= 0:
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return None
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# Determine bucket size based on symbol
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bucket_size = 1.0 if 'ETH' in symbol else 10.0 # $1 for ETH, $10 for BTC
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# Calculate price range (±20 buckets)
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price_range = 20 * bucket_size
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min_price = current_price - price_range
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max_price = current_price + price_range
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# Create price buckets
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price_buckets = {}
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bid_ask_imbalance = {}
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volume_weighted_prices = {}
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# Generate mock COB data for now (will be replaced with real COB provider data)
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for i in range(-20, 21):
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price = current_price + (i * bucket_size)
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if price > 0:
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# Mock data - replace with real COB provider data
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bid_volume = max(0, 1000 - abs(i) * 50) # More volume near current price
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ask_volume = max(0, 1000 - abs(i) * 50)
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total_volume = bid_volume + ask_volume
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imbalance = (bid_volume - ask_volume) / max(total_volume, 1)
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price_buckets[price] = {
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'bid_volume': bid_volume,
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'ask_volume': ask_volume,
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'total_volume': total_volume,
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'imbalance': imbalance
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}
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bid_ask_imbalance[price] = imbalance
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volume_weighted_prices[price] = price # Simplified VWAP
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# Calculate moving averages of imbalance for ±5 buckets
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ma_data = self._calculate_cob_moving_averages(symbol, bid_ask_imbalance, timestamp)
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cob_data = COBData(
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symbol=symbol,
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timestamp=timestamp,
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current_price=current_price,
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bucket_size=bucket_size,
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price_buckets=price_buckets,
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bid_ask_imbalance=bid_ask_imbalance,
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volume_weighted_prices=volume_weighted_prices,
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order_flow_metrics={},
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ma_1s_imbalance=ma_data.get('1s', {}),
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ma_5s_imbalance=ma_data.get('5s', {}),
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ma_15s_imbalance=ma_data.get('15s', {}),
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ma_60s_imbalance=ma_data.get('60s', {})
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)
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# Cache the COB data
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self.cob_data_cache[symbol] = cob_data
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return cob_data
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ma_data = self._calculate_cob_moving_averages(symbol, cob_obj.bid_ask_imbalance, timestamp)
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# Update MA fields
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cob_obj.ma_1s_imbalance = ma_data.get('1s', {})
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cob_obj.ma_5s_imbalance = ma_data.get('5s', {})
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cob_obj.ma_15s_imbalance = ma_data.get('15s', {})
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cob_obj.ma_60s_imbalance = ma_data.get('60s', {})
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# Cache and return
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self.cob_data_cache[symbol] = cob_obj
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return cob_obj
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except Exception as e:
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logger.error(f"Error getting COB data for {symbol}: {e}")
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return None
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@ -379,16 +343,40 @@ class StandardizedDataProvider(DataProvider):
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def _get_pivot_points(self, symbol: str) -> List[PivotPoint]:
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"""Get pivot points for a symbol"""
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try:
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pivot_points = []
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# Get pivot points from Williams Market Structure if available
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if symbol in self.williams_structure:
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williams = self.williams_structure[symbol]
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# This would need to be implemented based on the actual Williams structure
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# For now, return empty list
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pass
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return pivot_points
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results: List[PivotPoint] = []
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# Prefer DataProvider's Williams calculation (1s OHLCV based)
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try:
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levels = self.calculate_williams_pivot_points(symbol)
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except Exception:
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levels = {}
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# Flatten levels into standardized PivotPoint list
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if levels:
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for level_idx, trend_level in levels.items():
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# Expect trend_level to have an iterable of pivot points
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pivots = getattr(trend_level, 'pivots', None)
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if not pivots:
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# Some implementations may expose as list directly
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pivots = getattr(trend_level, 'points', [])
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for p in pivots or []:
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# Map fields defensively
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ts = getattr(p, 'timestamp', None)
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price = float(getattr(p, 'price', 0.0) or 0.0)
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ptype = getattr(p, 'pivot_type', getattr(p, 'type', 'low'))
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ptype = 'high' if str(ptype).lower() == 'high' else 'low'
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lvl = int(getattr(p, 'level', level_idx) or level_idx)
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if ts and price > 0:
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results.append(PivotPoint(
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symbol=symbol,
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timestamp=ts,
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price=price,
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type=ptype,
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level=lvl,
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confidence=1.0
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))
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return results
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except Exception as e:
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logger.error(f"Error getting pivot points for {symbol}: {e}")
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