feat(ticker_stream): 引入24小时行情WebSocket流以优化数据获取
在交易系统中新增24小时行情WebSocket流的支持，优先从缓存中读取行情数据，减少对REST API的依赖。更新市场扫描器以使用WebSocket缓存，确保在缓存过期时回退到REST请求。同时，添加了相应的异常处理逻辑以增强系统的稳定性。
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薇薇安
parent
5154b4933e
commit
c6126a42c9
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@ -236,6 +236,7 @@ async def main():
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# 初始化组件
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client = None
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user_data_stream = None
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ticker_24h_stream = None
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try:
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# 1. 初始化币安客户端
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logger.info("初始化币安客户端...")
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@ -324,6 +325,19 @@ async def main():
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logger.warning("⚠ User Data Stream 未启动，将仅依赖 REST 同步订单与持仓")
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user_data_stream = None
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# 3.1 启动 24h ticker WS 流（扫描时优先用缓存，避免批量 REST 与超时）
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try:
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from .ticker_24h_stream import Ticker24hStream
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use_testnet = getattr(config, "USE_TESTNET", False)
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ticker_24h_stream = Ticker24hStream(testnet=use_testnet)
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if await ticker_24h_stream.start():
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logger.info("✓ 24h ticker WS 已启动（扫描将优先使用 WS 缓存）")
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else:
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ticker_24h_stream = None
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except Exception as e:
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logger.debug(f"启动 24h ticker WS 失败（将使用 REST）: {e}")
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ticker_24h_stream = None
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# 4. 初始化各个模块
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logger.info("初始化交易模块...")
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scanner = MarketScanner(client)
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@ -411,6 +425,12 @@ async def main():
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logger.info("User Data Stream 已停止")
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except Exception as e:
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logger.debug(f"停止 User Data Stream 时异常: {e}")
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try:
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if ticker_24h_stream is not None:
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await ticker_24h_stream.stop()
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logger.info("Ticker24h Stream 已停止")
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except Exception as e:
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logger.debug(f"停止 Ticker24h Stream 时异常: {e}")
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if client:
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await client.disconnect()
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logger.info("程序已退出")
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@ -90,14 +90,27 @@ class MarketScanner:
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if excluded_count > 0:
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logger.info(f"排除主流币 {excluded_count} 个，剩余 {len(symbols)} 个交易对（专注于山寨币）")
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# 先批量获取所有交易对的24小时行情数据（减少API请求）
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logger.info(f"批量获取 {len(symbols)} 个交易对的24小时行情数据...")
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all_tickers = await self.client.get_all_tickers_24h()
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# 优先从 24h ticker WebSocket 缓存读取，避免批量 REST 请求与超时；无/过期再走 REST
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all_tickers = None
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try:
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try:
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from .ticker_24h_stream import get_tickers_24h_cache, is_ticker_24h_cache_fresh
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except ImportError:
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from ticker_24h_stream import get_tickers_24h_cache, is_ticker_24h_cache_fresh
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if is_ticker_24h_cache_fresh(max_age_sec=120.0):
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all_tickers = get_tickers_24h_cache()
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if all_tickers:
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logger.info(f"使用 24h ticker WS 缓存（{len(all_tickers)} 个交易对），跳过 REST 批量请求")
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except Exception as e:
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logger.debug(f"读取 24h ticker WS 缓存失败: {e}")
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if not all_tickers:
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logger.info(f"批量获取 {len(symbols)} 个交易对的24小时行情数据...")
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all_tickers = await self.client.get_all_tickers_24h()
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# 过滤最小涨跌幅和成交量，减少需要详细分析的交易对数量
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pre_filtered_symbols = []
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for symbol in symbols:
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ticker = all_tickers.get(symbol)
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ticker = all_tickers.get(symbol) if all_tickers else None
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if ticker:
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change_percent = abs(ticker.get('changePercent', 0))
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volume = ticker.get('volume', 0)
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138
trading_system/ticker_24h_stream.py
Normal file
138
trading_system/ticker_24h_stream.py
Normal file
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@ -0,0 +1,138 @@
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"""
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24 小时行情 WebSocket 流：订阅 !ticker@arr，维护全市场 ticker 缓存。
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供 market_scanner 优先使用，避免批量 REST get_all_tickers_24h，减少请求与超时。
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文档：仅发生变化的交易对会出现在推送数组中，约 1 秒一次。
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"""
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import asyncio
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import json
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import logging
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import time
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from typing import Dict, Optional, Any
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logger = logging.getLogger(__name__)
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# 全市场 24h ticker 缓存：symbol -> { symbol, price, volume, changePercent, ts }
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_ticker_24h_cache: Dict[str, Dict[str, Any]] = {}
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_ticker_24h_updated_at: float = 0.0
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def get_tickers_24h_cache() -> Dict[str, Dict[str, Any]]:
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"""返回当前 24h ticker 缓存（与 get_all_tickers_24h 结构兼容）。"""
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return dict(_ticker_24h_cache)
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def get_tickers_24h_cache_updated_at() -> float:
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"""返回缓存最后更新时间（monotonic）。未更新过为 0。"""
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return _ticker_24h_updated_at
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def is_ticker_24h_cache_fresh(max_age_sec: float = 120.0) -> bool:
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"""缓存是否在 max_age_sec 秒内更新过且非空。"""
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if not _ticker_24h_cache:
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return False
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return (time.monotonic() - _ticker_24h_updated_at) <= max_age_sec
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class Ticker24hStream:
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"""订阅合约 !ticker@arr，持续更新 _ticker_24h_cache。无需 listenKey，公开行情。"""
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def __init__(self, testnet: bool = False):
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self.testnet = testnet
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self._ws = None
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self._task: Optional[asyncio.Task] = None
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self._running = False
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def _ws_url(self) -> str:
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if self.testnet:
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return "wss://stream.binancefuture.com/ws/!ticker@arr"
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return "wss://fstream.binance.com/ws/!ticker@arr"
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async def start(self) -> bool:
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if self._running:
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return True
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self._running = True
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self._task = asyncio.create_task(self._run_ws())
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logger.info("Ticker24hStream: 已启动（!ticker@arr），扫描将优先使用 WS 缓存")
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return True
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async def stop(self):
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self._running = False
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if self._task:
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self._task.cancel()
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try:
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await self._task
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except asyncio.CancelledError:
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pass
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self._task = None
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if self._ws:
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try:
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await self._ws.close()
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except Exception:
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pass
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self._ws = None
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logger.info("Ticker24hStream: 已停止")
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async def _run_ws(self):
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import aiohttp
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while self._running:
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url = self._ws_url()
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try:
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async with aiohttp.ClientSession() as session:
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async with session.ws_connect(
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url, heartbeat=50, timeout=aiohttp.ClientTimeout(total=15)
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) as ws:
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self._ws = ws
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logger.info("Ticker24hStream: WS 已连接")
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async for msg in ws:
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if not self._running:
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break
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if msg.type == aiohttp.WSMsgType.TEXT:
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self._handle_message(msg.data)
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elif msg.type in (aiohttp.WSMsgType.ERROR, aiohttp.WSMsgType.CLOSED, aiohttp.WSMsgType.CLOSE):
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break
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except asyncio.CancelledError:
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break
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except Exception as e:
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logger.warning(f"Ticker24hStream: WS 异常 {e}，10s 后重连")
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await asyncio.sleep(10)
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self._ws = None
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if not self._running:
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break
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def _handle_message(self, raw: str):
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global _ticker_24h_cache, _ticker_24h_updated_at
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try:
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data = json.loads(raw)
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except Exception:
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return
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# 可能是单条对象（stream 名）或数组；文档说是数组
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if isinstance(data, list):
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arr = data
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elif isinstance(data, dict):
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# 组合流格式 { "stream": "!ticker@arr", "data": [ ... ] }
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arr = data.get("data") if isinstance(data.get("data"), list) else [data]
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else:
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return
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now_ms = int(time.time() * 1000)
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for t in arr:
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if not isinstance(t, dict):
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continue
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s = (t.get("s") or t.get("symbol") or "").strip()
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if not s or not s.endswith("USDT"):
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continue
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try:
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price = float(t.get("c") or t.get("lastPrice") or 0)
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change_pct = float(t.get("P") or t.get("priceChangePercent") or 0)
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# 成交量：优先 quoteVolume（USDT），文档可能为 q 或 quoteVolume
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vol = float(t.get("quoteVolume") or t.get("q") or t.get("v") or 0)
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except (TypeError, ValueError):
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continue
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_ticker_24h_cache[s] = {
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"symbol": s,
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"price": price,
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"volume": vol,
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"changePercent": change_pct,
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"ts": now_ms,
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}
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_ticker_24h_updated_at = time.monotonic()
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logger.debug(f"Ticker24hStream: 已更新 {len(arr)} 条，缓存共 {len(_ticker_24h_cache)} 个交易对")
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