105 lines
3.1 KiB
Python
105 lines
3.1 KiB
Python
"""市场概览 API"""
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from fastapi import APIRouter
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from app.data.tushare_client import tushare_client
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from app.data import tencent_client
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from app.engine.recommender import get_latest_recommendations
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from app.config import is_trading_hours, is_market_session
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router = APIRouter(prefix="/api/market", tags=["market"])
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@router.get("/temperature")
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async def get_temperature():
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"""获取市场温度（只读缓存，不触发扫描）"""
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result = await get_latest_recommendations()
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mt = result.get("market_temp")
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if mt:
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return {
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"trade_date": mt.trade_date,
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"temperature": mt.temperature,
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"up_count": mt.up_count,
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"down_count": mt.down_count,
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"limit_up_count": mt.limit_up_count,
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"limit_down_count": mt.limit_down_count,
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"max_streak": mt.max_streak,
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"broken_rate": mt.broken_rate,
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"index_above_ma20": getattr(mt, "index_above_ma20", False),
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"is_trading": is_trading_hours(),
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}
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return {
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"trade_date": "",
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"temperature": 0,
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"up_count": 0,
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"down_count": 0,
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"limit_up_count": 0,
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"limit_down_count": 0,
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"max_streak": 0,
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"broken_rate": 0,
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"index_above_ma20": False,
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"is_trading": is_trading_hours(),
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}
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@router.get("/overview")
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async def get_overview():
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"""市场概况：上证、深证、创业板指数
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盘中用腾讯实时行情，盘后用 Tushare 日线（有缓存）。
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"""
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if is_market_session():
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return await _overview_realtime()
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return _overview_daily()
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async def _overview_realtime():
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"""盘中：腾讯实时指数行情"""
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index_data = await tencent_client.get_index_realtime()
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result = []
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name_map = {
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"000001.SH": "上证指数",
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"399001.SZ": "深证成指",
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"399006.SZ": "创业板指",
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}
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for code in ["000001.SH", "399001.SZ", "399006.SZ"]:
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data = index_data.get(code)
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if not data:
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continue
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result.append({
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"name": name_map.get(code, data.get("name", code)),
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"code": code,
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"close": round(data["price"], 2),
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"pct_chg": round(data["pct_chg"], 2),
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"volume": round(data["volume"], 2),
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"realtime": True,
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})
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return result
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def _overview_daily():
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"""盘后：Tushare 日线数据"""
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indices = {
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"上证指数": "000001.SH",
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"深证成指": "399001.SZ",
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"创业板指": "399006.SZ",
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}
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result = []
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for name, code in indices.items():
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df = tushare_client.get_index_daily(code, days=5)
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if df.empty:
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continue
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df = df.sort_values("trade_date")
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latest = df.iloc[-1]
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prev = df.iloc[-2] if len(df) > 1 else latest
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pct = (latest["close"] - prev["close"]) / prev["close"] * 100
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result.append({
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"name": name,
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"code": code,
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"close": round(float(latest["close"]), 2),
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"pct_chg": round(pct, 2),
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"volume": round(float(latest["vol"]), 2),
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"realtime": False,
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})
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return result
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