bsp_monitor: 支持全部20个币对 + 数据源切换至data_provider + Python 3.9兼容

- fetcher.py: 数据源从CCXT改为data_provider HTTP API，新增get_symbols()自动获取所有币对
- main.py: 重构为多币对架构，每个币对独立SymbolState（pivot_monitor/BSP去重/首轮抑制）
- engine.py: format_bsp_detail()支持动态币对名
- ChanPivotMonitor/Classifier: 修复Python 3.9类型注解兼容（X|None → Optional[X]）
- 首轮初始化时不推送中枢和BSP，避免启动时20条消息轰炸

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

bsp_monitor/fetcher.py

@@ -2,23 +2,42 @@
 fetcher.py - 从 data_provider HTTP API 拉取 K 线数据。
 """
 
+from typing import List, Optional
+
 import requests
 import pandas as pd
 import logging
 
 logger = logging.getLogger(__name__)
 
-SYMBOL = "BTC/USDT:USDT"
 TIMEFRAME = "1m"
 PROVIDER_URL = "http://103.179.242.166"
 FETCH_LIMIT = 1000
 
+_symbols_cache: Optional[List[str]] = None
 
-def fetch_ohlcv() -> pd.DataFrame:
-    """从 data_provider API 拉取最近 FETCH_LIMIT 根 1m K 线。"""
+
+def get_symbols() -> list[str]:
+    """从 data_provider /health 获取所有可用币对（缓存）。"""
+    global _symbols_cache
+    if _symbols_cache is not None:
+        return _symbols_cache
+    try:
+        resp = requests.get(f"{PROVIDER_URL}/health", timeout=10)
+        resp.raise_for_status()
+        _symbols_cache = resp.json().get("symbols", [])
+        logger.info(f"获取到 {len(_symbols_cache)} 个币对")
+    except Exception as e:
+        logger.error(f"获取币对列表失败: {e}")
+        _symbols_cache = ["BTC/USDT:USDT"]
+    return _symbols_cache
+
+
+def fetch_ohlcv(symbol: str) -> pd.DataFrame:
+    """从 data_provider API 拉取某个币对最近 FETCH_LIMIT 根 1m K 线。"""
     url = f"{PROVIDER_URL}/api/candles"
     params = {
-        "symbol": SYMBOL,
+        "symbol": symbol,
         "tf": TIMEFRAME,
         "limit": FETCH_LIMIT,
     }
@@ -27,7 +46,7 @@ def fetch_ohlcv() -> pd.DataFrame:
     data = resp.json()
 
     if not data:
-        logger.warning("API 返回空数据")
+        logger.warning(f"{symbol}: API 返回空数据")
         return pd.DataFrame()
 
     df = pd.DataFrame(data)
@@ -35,5 +54,4 @@ def fetch_ohlcv() -> pd.DataFrame:
     df["date"] = df["timestamp"]
 
     df = df.drop_duplicates(subset="timestamp").sort_values("timestamp").reset_index(drop=True)
-    logger.info(f"拉取 {len(df)} 根 {TIMEFRAME} K 线 from {PROVIDER_URL}")
     return df