f4feea6b87
在 `ticker_24h_stream.py` 和 `book_ticker_stream.py` 中引入新的内存管理机制，限制进程内缓存的最大条数为 500，避免内存无限增长。更新 Redis 写入逻辑，确保在有 Redis 时优先写入 Redis，而不在进程内存中常驻数据。通过定期从 Redis 拉取数据并合并，提升了系统的内存使用效率与稳定性，同时优化了日志记录以减少高负载时的输出频率。此改动进一步增强了系统性能与资源管理能力。
205 lines
8.1 KiB
Python
205 lines
8.1 KiB
Python
"""
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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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支持多进程共用：Leader 写 Redis，所有进程可通过 refresh_ticker_24h_from_redis_loop 从 Redis 更新本地缓存。
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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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try:
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from .market_ws_leader import KEY_TICKER_24H
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except ImportError:
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KEY_TICKER_24H = "market:ticker_24h"
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# 全市场 24h ticker 缓存：symbol -> { symbol, price, volume, changePercent, ts }
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# 有 Redis 时由 refresh 循环从 Redis 回填，不在此无限累积
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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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_TICKER_24H_CACHE_MAX_KEYS = 500 # 进程内存最多保留 500 个，避免无限增长
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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。Leader 时可选写 Redis 供多进程读。"""
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def __init__(self, testnet: bool = False, redis_cache: Any = None):
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self.testnet = testnet
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self._redis_cache = redis_cache
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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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err_msg = getattr(e, "message", str(e)) or repr(e)
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err_type = type(e).__name__
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logger.warning(
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"Ticker24hStream: WS 异常 %s: %s，10s 后重连",
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err_type, err_msg,
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exc_info=logger.isEnabledFor(logging.DEBUG),
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)
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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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if isinstance(data, list):
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arr = data
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elif isinstance(data, dict):
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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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new_items = {}
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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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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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new_items[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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if not new_items:
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return
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# 有 Redis 时只写 Redis，不写进程内存（由 refresh 循环从 Redis 回填，避免双重占用）
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if self._redis_cache:
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try:
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asyncio.get_event_loop().create_task(
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self._merge_and_write_ticker_24h_to_redis(new_items)
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)
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except Exception as e:
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logger.debug("Ticker24hStream: 写入 Redis 调度失败 %s", e)
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return
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# 无 Redis 时才写进程内存
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for s, v in new_items.items():
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_ticker_24h_cache[s] = v
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_ticker_24h_updated_at = time.monotonic()
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if len(_ticker_24h_cache) > _TICKER_24H_CACHE_MAX_KEYS:
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keys = list(_ticker_24h_cache.keys())
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for k in keys[_TICKER_24H_CACHE_MAX_KEYS:]:
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del _ticker_24h_cache[k]
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logger.debug(f"Ticker24hStream: 已更新 {len(new_items)} 条，缓存共 {len(_ticker_24h_cache)} 个交易对")
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async def _merge_and_write_ticker_24h_to_redis(self, new_items: Dict[str, Dict[str, Any]]) -> None:
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"""从 Redis 读出、合并新数据、写回，不占用进程内存常驻"""
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try:
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if not self._redis_cache:
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return
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existing = await self._redis_cache.get(KEY_TICKER_24H)
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merged = dict(existing) if isinstance(existing, dict) else {}
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merged.update(new_items)
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await self._redis_cache.set(KEY_TICKER_24H, merged, ttl=120)
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except Exception as e:
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logger.debug("Ticker24hStream: 写入 Redis 失败 %s", e)
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async def refresh_ticker_24h_from_redis_loop(redis_cache: Any, interval_sec: float = 2.0) -> None:
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"""定期从 Redis 拉取 24h ticker 到本地缓存（Leader 与非 Leader 都跑，避免进程内常驻全量）。"""
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global _ticker_24h_cache, _ticker_24h_updated_at
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if redis_cache is None:
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return
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while True:
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try:
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await asyncio.sleep(interval_sec)
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data = await redis_cache.get(KEY_TICKER_24H)
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if data and isinstance(data, dict):
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_ticker_24h_cache.update(data)
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if len(_ticker_24h_cache) > _TICKER_24H_CACHE_MAX_KEYS:
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keys = list(_ticker_24h_cache.keys())
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for k in keys[_TICKER_24H_CACHE_MAX_KEYS:]:
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del _ticker_24h_cache[k]
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_ticker_24h_updated_at = time.monotonic()
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logger.debug("Ticker24h: 从 Redis 刷新 %s 个交易对", len(_ticker_24h_cache))
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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.debug("Ticker24h: 从 Redis 刷新失败 %s", e)
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