auto_trade_sys/backend/market_overview.py

"""
市场行情概览 - 用于全局配置页展示
拉取 Binance 公开接口（无需 API Key），与策略过滤逻辑对应的数据。
"""
import json
import logging
import ssl
import urllib.request
from typing import Any, Dict, Optional

logger = logging.getLogger(__name__)

BINANCE_FUTURES_BASE = "https://fapi.binance.com"
BINANCE_FUTURES_DATA = "https://fapi.binance.com/futures/data"
REQUEST_TIMEOUT = 10


def _http_get(url: str, params: Optional[dict] = None) -> Optional[Any]:
    """发起 GET 请求，返回 JSON 或 None。"""
    if params:
        qs = "&".join(f"{k}={v}" for k, v in params.items())
        url = f"{url}?{qs}"
    try:
        req = urllib.request.Request(url, headers={"Accept": "application/json"})
        ctx = ssl.create_default_context()
        with urllib.request.urlopen(req, timeout=REQUEST_TIMEOUT, context=ctx) as resp:
            return json.loads(resp.read().decode("utf-8"))
    except Exception as e:
        logger.debug("market_overview HTTP GET 失败 %s: %s", url[:80], e)
        return None


def _fetch_klines(symbol: str, interval: str, limit: int) -> Optional[list]:
    """获取 K 线数据。"""
    data = _http_get(
        f"{BINANCE_FUTURES_BASE}/fapi/v1/klines",
        {"symbol": symbol, "interval": interval, "limit": limit},
    )
    return data if isinstance(data, list) else None


def _compute_change_from_klines(klines: list, periods: int) -> Optional[float]:
    """根据 K 线计算最近 N 根的总涨跌幅（比例，如 -0.0167 表示 -1.67%）。"""
    if not klines or len(klines) < periods + 1:
        return None
    first_close = float(klines[0][4])
    last_close = float(klines[-1][4])
    return (last_close - first_close) / first_close if first_close else None


def fetch_symbol_change_period(symbol: str, interval: str, periods: int) -> Optional[float]:
    """获取指定交易对在指定周期内的涨跌幅（比例）。"""
    klines = _fetch_klines(symbol, interval, periods + 1)
    return _compute_change_from_klines(klines, periods) if klines else None


def fetch_ticker_24h(symbol: str) -> Optional[Dict]:
    """获取 24h ticker。"""
    data = _http_get(f"{BINANCE_FUTURES_BASE}/fapi/v1/ticker/24hr", {"symbol": symbol})
    return data if isinstance(data, dict) else None


def fetch_premium_index(symbol: str) -> Optional[Dict]:
    """获取资金费率等。"""
    data = _http_get(f"{BINANCE_FUTURES_BASE}/fapi/v1/premiumIndex", {"symbol": symbol})
    return data if isinstance(data, dict) else None


def fetch_long_short_ratio(symbol: str = "BTCUSDT", period: str = "1d", limit: int = 1) -> Optional[float]:
    """获取大户多空比。"""
    data = _http_get(
        f"{BINANCE_FUTURES_DATA}/topLongShortPositionRatio",
        {"symbol": symbol, "period": period, "limit": limit},
    )
    if not isinstance(data, list) or len(data) == 0:
        return None
    try:
        return float(data[-1].get("longShortRatio", 1))
    except (TypeError, ValueError):
        return None


def get_market_overview() -> Dict[str, Any]:
    """
    获取市场行情概览，与策略过滤逻辑对应的数据。
    供全局配置页展示，帮助用户确认当前策略方案是否匹配市场。
    """
    result = {
        "btc_24h_change_pct": None,
        "eth_24h_change_pct": None,
        "btc_15m_change_pct": None,
        "btc_1h_change_pct": None,
        "eth_15m_change_pct": None,
        "eth_1h_change_pct": None,
        "btc_funding_rate": None,
        "eth_funding_rate": None,
        "btc_long_short_ratio": None,
        "btc_trend_4h": None,
        "market_regime": None,
        "beta_filter_triggered": None,
    }

    # 24h 涨跌幅
    btc_ticker = fetch_ticker_24h("BTCUSDT")
    if btc_ticker is not None:
        try:
            result["btc_24h_change_pct"] = round(float(btc_ticker.get("priceChangePercent", 0)), 2)
        except (TypeError, ValueError):
            pass
    eth_ticker = fetch_ticker_24h("ETHUSDT")
    if eth_ticker is not None:
        try:
            result["eth_24h_change_pct"] = round(float(eth_ticker.get("priceChangePercent", 0)), 2)
        except (TypeError, ValueError):
            pass

    # 15m / 1h 涨跌幅（大盘共振过滤用）
    btc_15m = fetch_symbol_change_period("BTCUSDT", "15m", 5)
    btc_1h = fetch_symbol_change_period("BTCUSDT", "1h", 3)
    eth_15m = fetch_symbol_change_period("ETHUSDT", "15m", 5)
    eth_1h = fetch_symbol_change_period("ETHUSDT", "1h", 3)
    if btc_15m is not None:
        result["btc_15m_change_pct"] = round(btc_15m * 100, 2)
    if btc_1h is not None:
        result["btc_1h_change_pct"] = round(btc_1h * 100, 2)
    if eth_15m is not None:
        result["eth_15m_change_pct"] = round(eth_15m * 100, 2)
    if eth_1h is not None:
        result["eth_1h_change_pct"] = round(eth_1h * 100, 2)

    # 资金费率
    btc_prem = fetch_premium_index("BTCUSDT")
    if btc_prem is not None:
        try:
            result["btc_funding_rate"] = round(float(btc_prem.get("lastFundingRate", 0)), 6)
        except (TypeError, ValueError):
            pass
    eth_prem = fetch_premium_index("ETHUSDT")
    if eth_prem is not None:
        try:
            result["eth_funding_rate"] = round(float(eth_prem.get("lastFundingRate", 0)), 6)
        except (TypeError, ValueError):
            pass

    # 大户多空比
    lsr = fetch_long_short_ratio("BTCUSDT", "1d", 1)
    if lsr is not None:
        result["btc_long_short_ratio"] = round(lsr, 4)

    # 4H 趋势
    klines_4h = _fetch_klines("BTCUSDT", "4h", 60)
    if klines_4h and len(klines_4h) >= 21:
        try:
            from trading_system.market_regime_detector import compute_trend_4h_from_klines
            result["btc_trend_4h"] = compute_trend_4h_from_klines(klines_4h)
        except Exception:
            result["btc_trend_4h"] = _simple_trend_4h(klines_4h)

    # 市场状态（bull/bear/normal）
    try:
        from trading_system.market_regime_detector import detect_market_regime
        regime, details = detect_market_regime()
        result["market_regime"] = regime
        result["market_regime_details"] = details
    except Exception as e:
        logger.debug("market_overview 获取市场状态失败: %s", e)

    return result


def _simple_trend_4h(klines: list) -> str:
    """简化 4H 趋势：价格 vs 最近一根 K 线前 20 根均价。"""
    if len(klines) < 21:
        return "neutral"
    closes = [float(k[4]) for k in klines]
    price = closes[-1]
    avg20 = sum(closes[-21:-1]) / 20
    if price > avg20 * 1.002:
        return "up"
    if price < avg20 * 0.998:
        return "down"
    return "neutral"