chore: safety snapshot 2026-03-05 — HCM infrastructure before 2y klines experiment
Captures critical infrastructure surrounding the nautilus_dolphin core package: - dolphin_vbt_real.py: VBT vectorized backtest engine (6008 lines) - dolphin_paper_trade_adaptive_cb_v2.py: champion runner (champion_5x_f20) - _update_vbt_cache.py / update_VBT_parquet_cache.bat: cache builder - external_factors/: ExF system (all 85 indicator fetchers + NPZ cache) - mc_forewarning_qlabs_fork/: QLabs-enhanced MC-Forewarner research fork - DATA_LOCATIONS.md: source-of-truth path registry - .gitignore: excludes vbt_cache*, backfilled_data, .venv, models, etc. Note: nautilus_dolphin/ has own git repo (inner) — safety snapshot committed there separately. Champion state: WR=49.3%, ROI=+44.89%, PF=1.123, DD=14.95%, Sharpe=2.50 (55d, full-stack, abs_max_lev=6.0). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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external_factors/ob_stream_service.py
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228
external_factors/ob_stream_service.py
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import asyncio
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import aiohttp
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import json
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import time
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import logging
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import numpy as np
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from typing import Dict, List, Optional
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from collections import defaultdict
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# Setup basic logging
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logging.basicConfig(level=logging.INFO, format='%(asctime)s [%(levelname)s] %(name)s: %(message)s')
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logger = logging.getLogger("OBStreamService")
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try:
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import websockets
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except ImportError:
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logger.warning("websockets package not found. Run pip install websockets aiohttp")
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class OBStreamService:
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"""
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Real-Time Order Book Streamer for Binance Futures.
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Connects via WebSockets to maintain a perfectly synchronized local L2 Book,
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and slices the book into 5% notional depth buckets dynamically for the
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SmartPlacer and OBFeatureEngine layers.
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"""
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def __init__(self, assets: List[str], max_depth_pct: int = 5):
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self.assets = [a.upper() for a in assets]
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self.streams = [f"{a.lower()}@depth@100ms" for a in self.assets]
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self.max_depth_pct = max_depth_pct
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# In-memory Order Book caches (Price -> Quantity)
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self.bids: Dict[str, Dict[float, float]] = {a: {} for a in self.assets}
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self.asks: Dict[str, Dict[float, float]] = {a: {} for a in self.assets}
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# Synchronization mechanisms
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self.last_update_id: Dict[str, int] = {a: 0 for a in self.assets}
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self.buffer: Dict[str, List[dict]] = {a: [] for a in self.assets}
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self.initialized: Dict[str, bool] = {a: False for a in self.assets}
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# Optional: Lock for thread-safe reads if requested asynchronously
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self.locks: Dict[str, asyncio.Lock] = {a: asyncio.Lock() for a in self.assets}
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async def fetch_snapshot(self, asset: str):
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"""Fetch REST snapshot of the Order Book to initialize local state."""
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url = f"https://fapi.binance.com/fapi/v1/depth?symbol={asset}&limit=1000"
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try:
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async with aiohttp.ClientSession() as session:
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async with session.get(url) as resp:
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data = await resp.json()
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if 'lastUpdateId' not in data:
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logger.error(f"Failed to fetch snapshot for {asset}: {data}")
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return
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last_id = data['lastUpdateId']
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async with self.locks[asset]:
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self.bids[asset] = {float(p): float(q) for p, q in data['bids']}
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self.asks[asset] = {float(p): float(q) for p, q in data['asks']}
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self.last_update_id[asset] = last_id
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# Apply any buffered updates
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buffered = self.buffer[asset]
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for event in buffered:
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if event['u'] <= last_id:
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continue # Ignore old events
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self._apply_event(asset, event)
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self.buffer[asset].clear()
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self.initialized[asset] = True
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logger.info(f"Synchronized L2 book for {asset} (UpdateId: {last_id})")
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except Exception as e:
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logger.error(f"Error initializing snapshot for {asset}: {e}")
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def _apply_event(self, asset: str, event: dict):
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"""Apply a streaming diff event to the local book."""
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bids = self.bids[asset]
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asks = self.asks[asset]
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# Process Bids
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for p_str, q_str in event['b']:
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p, q = float(p_str), float(q_str)
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if q == 0.0:
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bids.pop(p, None)
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else:
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bids[p] = q
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# Process Asks
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for p_str, q_str in event['a']:
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p, q = float(p_str), float(q_str)
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if q == 0.0:
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asks.pop(p, None)
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else:
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asks[p] = q
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self.last_update_id[asset] = event['u']
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async def stream(self):
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"""Main loop: connect to WebSocket streams and maintain books."""
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import websockets
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# 1. Fire off REST snapshot initialization concurrently
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for a in self.assets:
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asyncio.create_task(self.fetch_snapshot(a))
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# 2. Start WebSocket listening instantly to buffer diffs
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stream_url = "wss://fstream.binance.com/stream?streams=" + "/".join(self.streams)
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logger.info(f"Connecting to Binance Stream: {stream_url}")
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while True:
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try:
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async with websockets.connect(stream_url, ping_interval=20, ping_timeout=20) as ws:
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logger.info("WebSocket connected. Streaming depth diffs...")
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while True:
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msg = await ws.recv()
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data = json.loads(msg)
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if 'data' in data:
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ev = data['data']
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asset = ev['s'].upper()
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async with self.locks[asset]:
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if not self.initialized[asset]:
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self.buffer[asset].append(ev)
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else:
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self._apply_event(asset, ev)
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except websockets.exceptions.ConnectionClosed as e:
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logger.warning(f"WebSocket closed ({e}). Reconnecting in 3s...")
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# Require re-init on disconnect to prevent drifted states
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for a in self.assets:
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self.initialized[a] = False
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asyncio.create_task(self.fetch_snapshot(a))
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await asyncio.sleep(3)
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except Exception as e:
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logger.error(f"Stream error: {e}")
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await asyncio.sleep(3)
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async def get_depth_buckets(self, asset: str) -> Optional[dict]:
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"""
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Extract the Notional Depth vectors matching OBSnapshot.
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Creates 5 elements summing USD depth between 0-1%, 1-2%, ..., 4-5% from mid.
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"""
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async with self.locks[asset]:
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if not self.initialized[asset]:
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return None
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# Extract and sort bids (descending) & asks (ascending)
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bids = sorted(self.bids[asset].items(), key=lambda x: -x[0])
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asks = sorted(self.asks[asset].items(), key=lambda x: x[0])
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if not bids or not asks:
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return None
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best_bid = bids[0][0]
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best_ask = asks[0][0]
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mid = (best_bid + best_ask) / 2.0
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bid_not = np.zeros(self.max_depth_pct, dtype=np.float64)
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ask_not = np.zeros(self.max_depth_pct, dtype=np.float64)
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bid_dep = np.zeros(self.max_depth_pct, dtype=np.float64)
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ask_dep = np.zeros(self.max_depth_pct, dtype=np.float64)
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# Bin bids into percentages
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for p, q in bids:
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dist_pct = (mid - p) / mid * 100
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idx = int(dist_pct)
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if idx < self.max_depth_pct:
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bid_not[idx] += p * q
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bid_dep[idx] += q
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else: # Since sorted, if we exceed max distance, we can safely break
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break
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# Bin asks into percentages
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for p, q in asks:
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dist_pct = (p - mid) / mid * 100
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idx = int(dist_pct)
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if idx < self.max_depth_pct:
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ask_not[idx] += p * q
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ask_dep[idx] += q
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else:
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break
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return {
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"timestamp": time.time(),
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"asset": asset,
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"bid_notional": bid_not,
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"ask_notional": ask_not,
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"bid_depth": bid_dep,
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"ask_depth": ask_dep,
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"best_bid": best_bid,
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"best_ask": best_ask,
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"spread_bps": (best_ask - best_bid) / mid * 10_000
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}
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# -----------------------------------------------------------------------------
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# Standalone run/test hook
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# -----------------------------------------------------------------------------
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async def demo():
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assets_to_track = ["BTCUSDT", "ETHUSDT", "SOLUSDT"]
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service = OBStreamService(assets=assets_to_track)
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# Run the streaming listener in the background
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asyncio.create_task(service.stream())
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await asyncio.sleep(4) # Let it initialize
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for _ in range(3):
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print("\n--- Current Real-Time OB Snapshots ---")
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for asset in assets_to_track:
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snap = await service.get_depth_buckets(asset)
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if snap:
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imb = (snap['bid_notional'][0] - snap['ask_notional'][0]) / (snap['bid_notional'][0] + snap['ask_notional'][0] + 1e-9)
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b1 = snap['bid_notional'][0]
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a1 = snap['ask_notional'][0]
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print(f"{asset:10s} | Spread: {snap['spread_bps']:.2f} bps | 1% Bid: ${b1:,.0f} | 1% Ask: ${a1:,.0f} | 1% Imb: {imb:+.3f}")
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else:
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print(f"{asset:10s} | Waiting for init...")
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await asyncio.sleep(2)
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if __name__ == "__main__":
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try:
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asyncio.run(demo())
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except KeyboardInterrupt:
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print("OB Streamer shut down manually.")
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