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COB working

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This commit is contained in:
Dobromir Popov
2025-06-30 02:39:37 +03:00
parent 4c53871014
commit 296e1be422
3 changed files with 232 additions and 134 deletions
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8
web/clean_dashboard.py
View File

@ -1809,13 +1809,7 @@ class CleanTradingDashboard:
def __init__(self, data): def __init__(self, data):
self.consolidated_bids = data.get('bids', []) self.consolidated_bids = data.get('bids', [])
self.consolidated_asks = data.get('asks', []) self.consolidated_asks = data.get('asks', [])
stats = data.get('stats', {}) self.stats = data.get('stats', {})
self.spread_bps = stats.get('spread_bps', 0)
self.volume_weighted_mid = stats.get('mid_price', 0)
self.liquidity_imbalance = stats.get('imbalance', 0)
self.total_bid_liquidity = stats.get('total_bid_liquidity', 0)
self.total_ask_liquidity = stats.get('total_ask_liquidity', 0)
self.exchanges_active = stats.get('exchanges_active', [])
return COBSnapshot(cob_data) return COBSnapshot(cob_data)
else: else:

262
web/component_manager.py
View File

@ -4,8 +4,10 @@ Manages the formatting and creation of dashboard components
""" """
from dash import html, dcc from dash import html, dcc
import dash_bootstrap_components as dbc
from datetime import datetime from datetime import datetime
import logging import logging
import numpy as np
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -245,139 +247,108 @@ class DashboardComponentManager:
logger.error(f"Error formatting system status: {e}") logger.error(f"Error formatting system status: {e}")
return [html.P(f"Error: {str(e)}", className="text-danger small")] return [html.P(f"Error: {str(e)}", className="text-danger small")]
def _format_cnn_pivot_prediction(self, model_info):
"""Format CNN pivot prediction for display"""
try:
pivot_prediction = model_info.get('pivot_prediction')
if not pivot_prediction:
return html.Div()
pivot_type = pivot_prediction.get('pivot_type', 'UNKNOWN')
predicted_price = pivot_prediction.get('predicted_price', 0)
confidence = pivot_prediction.get('confidence', 0)
time_horizon = pivot_prediction.get('time_horizon_minutes', 0)
# Color coding for pivot types
if 'RESISTANCE' in pivot_type:
pivot_color = "text-danger"
pivot_icon = "fas fa-arrow-up"
elif 'SUPPORT' in pivot_type:
pivot_color = "text-success"
pivot_icon = "fas fa-arrow-down"
else:
pivot_color = "text-warning"
pivot_icon = "fas fa-arrows-alt-h"
return html.Div([
html.Div([
html.I(className=f"{pivot_icon} me-1 {pivot_color}"),
html.Span("Next Pivot: ", className="text-muted small"),
html.Span(f"${predicted_price:.2f}", className=f"small fw-bold {pivot_color}")
], className="mb-1"),
html.Div([
html.Span(f"{pivot_type.replace('_', ' ')}", className=f"small {pivot_color}"),
html.Span(f" ({confidence:.0%}) in ~{time_horizon}m", className="text-muted small")
])
], className="mt-1 p-1", style={"backgroundColor": "rgba(255,255,255,0.02)", "borderRadius": "3px"})
except Exception as e:
logger.debug(f"Error formatting CNN pivot prediction: {e}")
return html.Div()
def format_cob_data(self, cob_snapshot, symbol): def format_cob_data(self, cob_snapshot, symbol):
"""Format COB data for display""" """Format COB data into a ladder display with volume bars"""
try: try:
if not cob_snapshot: if not cob_snapshot or not hasattr(cob_snapshot, 'stats'):
return [html.P("No COB data", className="text-muted small")] return html.Div([
html.H6(f"{symbol} COB", className="mb-2"),
html.P("No COB data available", className="text-muted small")
])
# Real COB data display stats = cob_snapshot.stats if hasattr(cob_snapshot, 'stats') else {}
cob_info = [] mid_price = stats.get('mid_price', 0)
spread_bps = stats.get('spread_bps', 0)
total_bid_liquidity = stats.get('total_bid_liquidity', 0)
total_ask_liquidity = stats.get('total_ask_liquidity', 0)
imbalance = stats.get('imbalance', 0)
bids = getattr(cob_snapshot, 'consolidated_bids', [])
asks = getattr(cob_snapshot, 'consolidated_asks', [])
if mid_price == 0 or not bids or not asks:
return html.Div([
html.H6(f"{symbol} COB", className="mb-2"),
html.P("Awaiting valid order book data...", className="text-muted small")
])
# Header with summary stats
imbalance_text = f"Bid Heavy ({imbalance:.3f})" if imbalance > 0 else f"Ask Heavy ({imbalance:.3f})"
imbalance_color = "text-success" if imbalance > 0 else "text-danger"
# Symbol header header = html.Div([
cob_info.append(html.Div([ html.H6(f"{symbol} - COB Ladder", className="mb-1"),
html.Strong(f"{symbol}", className="text-info"), html.Div([
html.Span(" - COB Snapshot", className="small text-muted") html.Span(f"Mid: ${mid_price:,.2f}", className="me-3"),
], className="mb-2")) html.Span(f"Spread: {spread_bps:.1f} bps", className="me-3"),
html.Span(f"Imbalance: ", className="small"),
# Check if we have a real COB snapshot object html.Span(imbalance_text, className=f"fw-bold {imbalance_color}")
if hasattr(cob_snapshot, 'volume_weighted_mid'): ], className="small text-muted")
# Real COB snapshot data ], className="mb-2")
mid_price = getattr(cob_snapshot, 'volume_weighted_mid', 0)
spread_bps = getattr(cob_snapshot, 'spread_bps', 0) # --- Ladder Creation ---
bid_liquidity = getattr(cob_snapshot, 'total_bid_liquidity', 0) bucket_size = 10 # $10 price buckets
ask_liquidity = getattr(cob_snapshot, 'total_ask_liquidity', 0) num_levels = 5 # 5 levels above and below
imbalance = getattr(cob_snapshot, 'liquidity_imbalance', 0)
bid_levels = len(getattr(cob_snapshot, 'consolidated_bids', [])) # Aggregate bids and asks into buckets
ask_levels = len(getattr(cob_snapshot, 'consolidated_asks', [])) def aggregate_buckets(orders, mid_price, bucket_size):
buckets = {}
# Price and spread for order in orders:
cob_info.append(html.Div([ price = order.get('price', 0)
html.Div([ size = order.get('size', 0)
html.I(className="fas fa-dollar-sign text-success me-2"), if price > 0:
html.Span(f"Mid: ${mid_price:.2f}", className="small fw-bold") bucket_key = round(price / bucket_size) * bucket_size
], className="mb-1"), if bucket_key not in buckets:
html.Div([ buckets[bucket_key] = 0
html.I(className="fas fa-arrows-alt-h text-warning me-2"), buckets[bucket_key] += size * price # Volume in quote currency (USD)
html.Span(f"Spread: {spread_bps:.1f} bps", className="small") return buckets
], className="mb-1")
bid_buckets = aggregate_buckets(bids, mid_price, bucket_size)
ask_buckets = aggregate_buckets(asks, mid_price, bucket_size)
all_volumes = list(bid_buckets.values()) + list(ask_buckets.values())
max_volume = max(all_volumes) if all_volumes else 1
# Determine ladder price levels
center_bucket = round(mid_price / bucket_size) * bucket_size
ask_levels = [center_bucket + i * bucket_size for i in range(1, num_levels + 1)]
bid_levels = [center_bucket - i * bucket_size for i in range(num_levels)]
# Create ladder rows
ask_rows = []
for price in sorted(ask_levels, reverse=True):
volume = ask_buckets.get(price, 0)
progress = (volume / max_volume) * 100
ask_rows.append(html.Tr([
html.Td(f"${price:,.2f}", className="text-danger price-level"),
html.Td(f"${volume:,.0f}", className="volume-level"),
html.Td(dbc.Progress(value=progress, color="danger", className="vh-25"), className="progress-cell")
])) ]))
# Liquidity info bid_rows = []
total_liquidity = bid_liquidity + ask_liquidity for price in sorted(bid_levels, reverse=True):
bid_pct = (bid_liquidity / total_liquidity * 100) if total_liquidity > 0 else 0 volume = bid_buckets.get(price, 0)
ask_pct = (ask_liquidity / total_liquidity * 100) if total_liquidity > 0 else 0 progress = (volume / max_volume) * 100
bid_rows.append(html.Tr([
cob_info.append(html.Div([ html.Td(f"${price:,.2f}", className="text-success price-level"),
html.Div([ html.Td(f"${volume:,.0f}", className="volume-level"),
html.I(className="fas fa-layer-group text-info me-2"), html.Td(dbc.Progress(value=progress, color="success", className="vh-25"), className="progress-cell")
html.Span(f"Liquidity: ${total_liquidity:,.0f}", className="small")
], className="mb-1"),
html.Div([
html.Span(f"Bids: {bid_pct:.0f}% ", className="small text-success"),
html.Span(f"Asks: {ask_pct:.0f}%", className="small text-danger")
], className="mb-1")
]))
# Order book depth
cob_info.append(html.Div([
html.Div([
html.I(className="fas fa-list text-secondary me-2"),
html.Span(f"Levels: {bid_levels} bids, {ask_levels} asks", className="small")
], className="mb-1")
]))
# Imbalance indicator
imbalance_color = "text-success" if imbalance > 0.1 else "text-danger" if imbalance < -0.1 else "text-muted"
imbalance_text = "Bid Heavy" if imbalance > 0.1 else "Ask Heavy" if imbalance < -0.1 else "Balanced"
cob_info.append(html.Div([
html.I(className="fas fa-balance-scale me-2"),
html.Span(f"Imbalance: ", className="small text-muted"),
html.Span(f"{imbalance_text} ({imbalance:.3f})", className=f"small {imbalance_color}")
], className="mb-1"))
else:
# Fallback display for other data formats
cob_info.append(html.Div([
html.Div([
html.I(className="fas fa-chart-bar text-success me-2"),
html.Span("Order Book: Active", className="small")
], className="mb-1"),
html.Div([
html.I(className="fas fa-coins text-warning me-2"),
html.Span("Liquidity: Good", className="small")
], className="mb-1"),
html.Div([
html.I(className="fas fa-balance-scale text-info me-2"),
html.Span("Imbalance: Neutral", className="small")
])
])) ]))
return cob_info # Mid-price separator
mid_row = html.Tr([
html.Td(f"${mid_price:,.2f}", colSpan=3, className="text-center fw-bold text-white bg-secondary")
])
ladder_table = html.Table([
html.Thead(html.Tr([html.Th("Price (USD)"), html.Th("Volume (USD)"), html.Th("Total")])),
html.Tbody(ask_rows + [mid_row] + bid_rows)
], className="table table-sm table-dark cob-ladder-table")
return html.Div([header, ladder_table])
except Exception as e: except Exception as e:
logger.error(f"Error formatting COB data: {e}") logger.error(f"Error formatting COB data ladder: {e}")
return [html.P(f"Error: {str(e)}", className="text-danger small")] return html.P(f"Error: {str(e)}", className="text-danger small")
def format_cob_data_with_buckets(self, cob_snapshot, symbol, price_buckets, memory_stats, bucket_size=1.0): def format_cob_data_with_buckets(self, cob_snapshot, symbol, price_buckets, memory_stats, bucket_size=1.0):
"""Format COB data with price buckets for high-frequency display""" """Format COB data with price buckets for high-frequency display"""
@ -692,4 +663,43 @@ class DashboardComponentManager:
except Exception as e: except Exception as e:
logger.error(f"Error formatting training metrics: {e}") logger.error(f"Error formatting training metrics: {e}")
return [html.P(f"Error: {str(e)}", className="text-danger small")] return [html.P(f"Error: {str(e)}", className="text-danger small")]
def _format_cnn_pivot_prediction(self, model_info):
"""Format CNN pivot prediction for display"""
try:
pivot_prediction = model_info.get('pivot_prediction')
if not pivot_prediction:
return html.Div()
pivot_type = pivot_prediction.get('pivot_type', 'UNKNOWN')
predicted_price = pivot_prediction.get('predicted_price', 0)
confidence = pivot_prediction.get('confidence', 0)
time_horizon = pivot_prediction.get('time_horizon_minutes', 0)
# Color coding for pivot types
if 'RESISTANCE' in pivot_type:
pivot_color = "text-danger"
pivot_icon = "fas fa-arrow-up"
elif 'SUPPORT' in pivot_type:
pivot_color = "text-success"
pivot_icon = "fas fa-arrow-down"
else:
pivot_color = "text-warning"
pivot_icon = "fas fa-arrows-alt-h"
return html.Div([
html.Div([
html.I(className=f"{pivot_icon} me-1 {pivot_color}"),
html.Span("Next Pivot: ", className="text-muted small"),
html.Span(f"${predicted_price:.2f}", className=f"small fw-bold {pivot_color}")
], className="mb-1"),
html.Div([
html.Span(f"{pivot_type.replace('_', ' ')}", className=f"small {pivot_color}"),
html.Span(f" ({confidence:.0%}) in ~{time_horizon}m", className="text-muted small")
])
], className="mt-1 p-1", style={"backgroundColor": "rgba(255,255,255,0.02)", "borderRadius": "3px"})
except Exception as e:
logger.debug(f"Error formatting CNN pivot prediction: {e}")
return html.Div()

96
web/layout_manager.py
View File

@ -51,7 +51,7 @@ class DashboardLayoutManager:
return html.Div([ return html.Div([
self._create_metrics_and_signals_row(), self._create_metrics_and_signals_row(),
self._create_charts_row(), self._create_charts_row(),
self._create_analytics_and_performance_row() self._create_cob_and_trades_row()
]) ])
def _create_metrics_and_signals_row(self): def _create_metrics_and_signals_row(self):
@ -199,6 +199,100 @@ class DashboardLayoutManager:
], className="card") ], className="card")
]) ])
def _create_cob_and_trades_row(self):
"""Creates the row for COB ladders, closed trades, and model status."""
return html.Div(
[
# Left side: COB Ladders (60% width)
html.Div(
[
html.Div(
[
# ETH/USDT COB
html.Div(
[
html.Div(
id="eth-cob-content",
className="card-body p-2",
)
],
className="card",
style={"flex": "1"},
),
# BTC/USDT COB
html.Div(
[
html.Div(
id="btc-cob-content",
className="card-body p-2",
)
],
className="card",
style={"flex": "1", "marginLeft": "1rem"},
),
],
className="d-flex",
)
],
style={"width": "60%"},
),
# Right side: Trades and Model Status (40% width)
html.Div(
[
# Closed Trades
html.Div(
[
html.Div(
[
html.H6(
[
html.I(className="fas fa-history me-2"),
"Closed Trades",
],
className="card-title mb-2",
),
html.Div(
id="closed-trades-table",
style={"height": "250px", "overflowY": "auto"},
),
],
className="card-body p-2",
)
],
className="card mb-3",
),
# Model Status
html.Div(
[
html.Div(
[
html.H6(
[
html.I(className="fas fa-brain me-2"),
"Models & Training Progress",
],
className="card-title mb-2",
),
html.Div(
id="training-metrics",
style={
"height": "250px",
"overflowY": "auto",
},
),
],
className="card-body p-2",
)
],
className="card",
),
],
style={"width": "38%", "marginLeft": "2%"},
),
],
className="d-flex mb-3",
)
def _create_analytics_and_performance_row(self): def _create_analytics_and_performance_row(self):
"""Create the combined analytics and performance row with COB data, trades, and training progress""" """Create the combined analytics and performance row with COB data, trades, and training progress"""
return html.Div([ return html.Div([