ChanPivotMonitor: 实时中枢特征跟踪 + Telegram推送
- ChanPivotClassifier: 提取 calc_duration/contraction/shift 为 @staticmethod，新增 compute_features() - ChanPivotMonitor: 实时追踪当前中枢，bi_count 增长时重新计算 shift/contraction/duration - bsp_monitor/fetcher: 改用 data_provider HTTP API 替代直连 CCXT - bsp_monitor/notify: 新增 send_telegram_message() 通用推送 - bsp_monitor/main: 集成 ChanPivotMonitor，有新笔或 BSP 时推送到 Telegram Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
jackyu66git
co-authored by
Claude Opus 4.7
Claude Opus 4.7
parent
5ad761fad4
commit
b1cbdca707
+20
-26
@@ -1,45 +1,39 @@
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"""
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fetcher.py - CCXT REST 拉取 Binance 永续合约 1m K 线，从固定起点累积。
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fetcher.py - 从 data_provider HTTP API 拉取 K 线数据。
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"""
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import ccxt
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import requests
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import pandas as pd
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import logging
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from datetime import datetime, timezone
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logger = logging.getLogger(__name__)
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SYMBOL = "BTC/USDT:USDT"
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TIMEFRAME = "1m"
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# 每次拉取最近 LIMIT 根 K 线（Binance 上限 1500，足够缠论管线用 ~25h 数据）
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_FETCH_LIMIT = 1000
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_exchange = None
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def _get_exchange():
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global _exchange
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if _exchange is None:
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_exchange = ccxt.binance({
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"enableRateLimit": True,
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"options": {"defaultType": "future"},
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})
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_exchange.load_markets()
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logger.info("ccxt binance 已初始化")
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return _exchange
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PROVIDER_URL = "http://103.179.242.166"
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FETCH_LIMIT = 1000
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def fetch_ohlcv() -> pd.DataFrame:
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"""拉取最近 _FETCH_LIMIT 根 1m K 线。
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"""从 data_provider API 拉取最近 FETCH_LIMIT 根 1m K 线。"""
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url = f"{PROVIDER_URL}/api/candles"
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params = {
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"symbol": SYMBOL,
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"tf": TIMEFRAME,
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"limit": FETCH_LIMIT,
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}
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resp = requests.get(url, params=params, timeout=30)
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resp.raise_for_status()
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data = resp.json()
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管线每次重跑最新的 K 线窗口。
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用 limit 而非 since 避免 API 500 根限制截断新数据。
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"""
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exchange = _get_exchange()
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raw = exchange.fetch_ohlcv(SYMBOL, TIMEFRAME, limit=_FETCH_LIMIT)
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if not data:
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logger.warning("API 返回空数据")
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return pd.DataFrame()
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df = pd.DataFrame(raw, columns=["timestamp", "open", "high", "low", "close", "volume"])
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df = pd.DataFrame(data)
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df["timestamp"] = pd.to_datetime(df["timestamp"], unit="ms", utc=True)
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df["date"] = df["timestamp"]
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df = df.drop_duplicates(subset="timestamp").sort_values("timestamp").reset_index(drop=True)
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logger.info(f"拉取 {len(df)} 根 {TIMEFRAME} K 线 from {PROVIDER_URL}")
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return df
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+57
-1
@@ -19,7 +19,12 @@ sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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from fetcher import fetch_ohlcv
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from engine import ChanEngine
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from notify import send_bsp_alert, BOT_TOKEN, CHAT_ID
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from notify import send_bsp_alert, send_telegram_message, BOT_TOKEN, CHAT_ID
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_PARENT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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if _PARENT not in sys.path:
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sys.path.insert(0, _PARENT)
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from ChanPivotMonitor import ChanPivotMonitor
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logging.basicConfig(
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level=logging.INFO,
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@@ -38,6 +43,7 @@ class BSPMonitor:
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self._first_run = True
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self._last_df_ts = None
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self._known_bsp_keys: set = set() # 已见过的 BSP 键（含已推送和历史的）
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self.pivot_monitor = ChanPivotMonitor(window_size=10)
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async def tick(self):
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"""单次 tick。"""
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@@ -68,6 +74,56 @@ class BSPMonitor:
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logger.error(f"缠论计算失败: {e}", exc_info=True)
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return
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# 2.5 更新中枢特征监控 + 推送
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pivot_state = self.pivot_monitor.update(engine.bi_zs_list)
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if pivot_state:
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logger.info(
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f"中枢特征更新: bi_count={pivot_state['bi_count']} "
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f"is_sure={pivot_state['is_sure']} "
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f"contraction={pivot_state['contraction']:.4f} "
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f"shift_norm={pivot_state['shift_norm']:+.4f} "
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f"duration_norm={pivot_state['duration_norm']:.4f}"
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)
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# Telegram 推送
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if pivot_state["is_sure"]:
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phase = "✅ 已确认"
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elif pivot_state["bi_count"] > 3:
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phase = "🔄 延伸中"
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else:
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phase = "🆕 刚形成"
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zs_dir = pivot_state["zs_dir"]
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dir_label = "⬆️ 向上" if "UP" in zs_dir else "⬇️ 向下"
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# 白话解释
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c = pivot_state["contraction"]
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if c < 0.85:
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contraction_note = "收敛（振幅缩小，可能快出方向）"
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elif c > 1.15:
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contraction_note = "扩张（振幅放大，波动加剧）"
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else:
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contraction_note = "稳定"
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s = pivot_state["shift_norm"]
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if s > 0.3:
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shift_note = "重心上移（偏多）"
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elif s < -0.3:
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shift_note = "重心下移（偏空）"
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else:
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shift_note = "重心居中"
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msg = (
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f"🏠 <b>中枢更新</b> — BTC/USDT 1m\n"
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f"\n"
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f"📐 笔数: <b>{pivot_state['bi_count']}</b> {dir_label} {phase}\n"
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f"📏 收敛率: <b>{pivot_state['contraction']:.4f}</b> → {contraction_note}\n"
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f"⚖️ 重心漂移: <b>{pivot_state['shift_norm']:+.4f}</b> → {shift_note}\n"
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f"⏱️ 持续: {pivot_state['duration_raw']}K "
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f"(norm: {pivot_state['duration_norm']:.2f})\n"
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f"📦 区间: {pivot_state['zd']:.2f} – {pivot_state['zg']:.2f} "
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f"(gg/dd: {pivot_state['gg']:.2f}/{pivot_state['dd']:.2f})"
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)
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send_telegram_message(msg)
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# 3. 检测新 BSP（用 stable key 去重）
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current_bsps = engine.bsp_list
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current_keys = {_bsp_stable_key(b) for b in current_bsps}
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@@ -54,6 +54,39 @@ def _save_pushed():
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_load_pushed()
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def send_telegram_message(text: str) -> bool:
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"""发送 Telegram 消息（不去重，每次调用都发）。
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Args:
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text: HTML 格式的消息文本
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Returns:
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True 如果发送成功
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"""
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if not BOT_TOKEN or not CHAT_ID:
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logger.warning("Telegram 未配置，跳过推送")
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return False
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url = f"https://api.telegram.org/bot{BOT_TOKEN}/sendMessage"
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try:
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resp = requests.post(
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url,
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json={
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"chat_id": CHAT_ID,
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"text": text,
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"parse_mode": "HTML",
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"disable_web_page_preview": True,
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},
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timeout=10,
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)
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resp.raise_for_status()
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logger.info(f"Telegram 推送成功")
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return True
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except Exception as e:
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logger.error(f"Telegram 推送失败: {e}")
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return False
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def send_bsp_alert(text: str, bsp_key: str = "") -> bool:
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"""通过 Telegram Bot API 推送买卖点消息（自动去重）。
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