Sakurasan
d7d019c2c4
- 新增 /dashboard 页面：暗色主题，指数行情/市场温度/涨跌分布/行业强度/概念热度/事件情报 - 后端聚合接口 /api/market-dashboard，30秒缓存 - 利用SDK接口：指数行情、全市场快照、涨停/跌停/炸板池、连板天梯、热门股、飙升榜、龙虎榜、异动分析、集合竞价基准、行业/概念目录 - 市场温度评分：6因子加权（涨跌比/中位涨跌/强弱比/涨停活跃度/炸板惩罚/竞价信号） - 首页添加市场看板导航入口
512 lines
18 KiB
Python
512 lines
18 KiB
Python
"""市场看板数据聚合路由（/api/market-dashboard）
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聚合同花顺 SDK 多个接口，一次性返回前端看板所需的全部数据：
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- 主要指数行情 + 估值分位（PE/PB）
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- 集合竞价信号（竞价基准线 + 情绪判断）
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- 全市场涨跌统计（上涨/下跌/平盘/涨停/跌停/炸板/成交额）
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- 市场温度评分（结合竞价基准校准）
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- 涨跌家数分布
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- 行业强度榜（同花顺行业指数 + 概念板块热度）
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- 事件情报（连板天梯/热门股/涨停封单/炸板/飙升/龙虎榜）
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"""
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import asyncio
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import math
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import time
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from datetime import datetime, timezone, timedelta
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from fastapi import APIRouter, HTTPException
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from fastapi.responses import JSONResponse
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from services import fuyao_client
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router = APIRouter()
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_NO_CACHE_HEADERS = {"Cache-Control": "no-store, no-cache, must-revalidate, max-age=0"}
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_cache: dict = {"data": None, "at": 0.0}
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_CACHE_TTL = 30
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# 主要指数 thscode 列表
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_MAIN_INDEX_THSCODES = [
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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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"000688.SH", # 科创50
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"000300.SH", # 沪深300
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]
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_INDEX_NAMES = {
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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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"000688.SH": "科创50",
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"000300.SH": "沪深300",
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}
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BJT = timezone(timedelta(hours=8))
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def _safe_float(val, default=0.0):
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try:
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v = float(val)
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return v if not math.isnan(v) and not math.isinf(v) else default
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except (TypeError, ValueError):
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return default
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def _calc_temperature(up: int, down: int, flat: int, median_pct: float,
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strong: int, weak: int, limit_up: int, limit_down: int,
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break_count: int = 0, auction_signal: str = "") -> dict:
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"""市场温度评分（0-100）：综合涨跌比、中位数涨跌、强弱比、涨停活跃度、炸板率、竞价信号"""
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total = up + down + flat
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if total == 0:
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return {"score": 50, "label": "中性", "factors": {}}
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# 涨跌比得分（0-25分）
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advance_ratio = up / total
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advance_score = min(advance_ratio * 50, 25)
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# 中位数涨跌得分（0-20分）：-3%~+3% 映射到 0~20
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median_score = max(0, min(20, (median_pct + 3) / 6 * 20))
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# 强弱比得分（0-20分）
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sw_total = strong + weak
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if sw_total > 0:
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strong_ratio = strong / sw_total
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strong_score = min(strong_ratio * 40, 20)
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else:
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strong_score = 10
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# 涨停活跃度得分（0-15分）
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limit_score = min(limit_up / 80 * 15, 15)
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# 炸板惩罚（0-10分）：炸板率越高越扣分
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total_attempted = limit_up + break_count
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break_penalty = 0
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if total_attempted > 0:
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break_rate = break_count / total_attempted
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break_penalty = break_rate * 10 # 炸板率 50% → 扣 5 分
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# 竞价信号加成（±5分）
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auction_bonus = 0
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if auction_signal == "强势高开":
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auction_bonus = 5
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elif auction_signal == "偏强":
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auction_bonus = 2
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elif auction_signal == "弱势低开":
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auction_bonus = -5
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elif auction_signal == "偏弱":
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auction_bonus = -2
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raw = advance_score + median_score + strong_score + limit_score - break_penalty + auction_bonus
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score = round(max(0, min(100, raw)), 1)
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if score >= 80:
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label = "强势"
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elif score >= 60:
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label = "偏强"
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elif score >= 40:
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label = "中性"
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elif score >= 20:
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label = "偏弱"
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else:
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label = "弱势"
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factors = {
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"advanceScore": round(advance_score, 1),
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"medianScore": round(median_score, 1),
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"strongScore": round(strong_score, 1),
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"limitScore": round(limit_score, 1),
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"breakPenalty": round(-break_penalty, 1),
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"auctionBonus": auction_bonus,
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}
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return {"score": score, "label": label, "factors": factors}
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async def _build_dashboard() -> dict:
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now = time.time()
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if _cache["data"] is not None and now - _cache["at"] < _CACHE_TTL:
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return _cache["data"]
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# ── 第一批并行拉取（核心数据） ──
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try:
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(
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index_data,
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all_stocks,
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limit_up_data,
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limit_down_data,
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limit_break_data,
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industry_catalog,
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concept_catalog,
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auction_benchmark,
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) = await asyncio.gather(
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fuyao_client.index_prices_snapshot(",".join(_MAIN_INDEX_THSCODES)),
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fuyao_client.prices_snapshot_all(limit=5000),
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fuyao_client.limit_up_pool(page=1, size=200),
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fuyao_client.limit_down_pool(page=1, size=1),
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fuyao_client.limit_break_pool(page=1, size=1),
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fuyao_client.index_catalog("industry"),
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fuyao_client.index_catalog("cn_concept"),
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fuyao_client.auction_short_term_benchmark(),
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return_exceptions=True,
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)
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except Exception as e:
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raise HTTPException(status_code=502, detail=f"市场数据拉取失败: {e}")
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# ── 第二批并行拉取（事件数据，依赖第一批结果较轻） ──
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try:
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(
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hot_stock_data,
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dragon_tiger_data,
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anomaly_data,
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limit_ladder_data,
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skyrocket_data,
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) = await asyncio.gather(
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fuyao_client.hot_stock_list("day"),
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fuyao_client.dragon_tiger_list("all"),
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fuyao_client.anomaly_analysis_list(["SHARP_RISE", "RAPID_RALLY", "LIMIT_UP"]),
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fuyao_client.limit_up_ladder(),
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fuyao_client.skyrocket_list("day"),
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return_exceptions=True,
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)
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except Exception:
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hot_stock_data = {}
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dragon_tiger_data = {}
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anomaly_data = {}
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limit_ladder_data = {}
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skyrocket_data = {}
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# ── 解析指数 ──
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indices = []
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if isinstance(index_data, list):
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for item in index_data:
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code = item.get("thscode", "")
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indices.append({
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"code": code,
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"name": _INDEX_NAMES.get(code, item.get("name", code)),
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"price": _safe_float(item.get("last_price")),
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"change": _safe_float(item.get("price_change")),
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"changePct": _safe_float(item.get("price_change_ratio_pct")),
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"prevClose": _safe_float(item.get("prev_price")),
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"turnover": _safe_float(item.get("turnover")),
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})
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# ── 指数估值（PE/PB） — 同花顺估值API仅支持个股，指数暂不支持 ──
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# ── 解析全市场涨跌统计 ──
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up_count = 0
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down_count = 0
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flat_count = 0
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total_turnover = 0.0
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all_changes = []
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stocks_list = all_stocks if isinstance(all_stocks, list) else []
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for s in stocks_list:
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chg = _safe_float(s.get("price_change_ratio_pct"))
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turnover = _safe_float(s.get("turnover"))
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total_turnover += turnover
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if chg > 0:
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up_count += 1
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elif chg < 0:
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down_count += 1
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else:
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flat_count += 1
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all_changes.append(chg)
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total_stocks = up_count + down_count + flat_count
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median_change = sorted(all_changes)[len(all_changes) // 2] if all_changes else 0
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# 涨停/跌停/炸板 精确统计
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limit_up_count = 0
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limit_down_count = 0
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break_count = 0
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if isinstance(limit_up_data, dict):
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pagination = limit_up_data.get("pagination", {})
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limit_up_count = pagination.get("total", 0) or len(limit_up_data.get("item", []))
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if isinstance(limit_down_data, dict):
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pagination = limit_down_data.get("pagination", {})
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limit_down_count = pagination.get("total", 0) or len(limit_down_data.get("item", []))
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if isinstance(limit_break_data, dict):
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pagination = limit_break_data.get("pagination", {})
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break_count = pagination.get("total", 0) or len(limit_break_data.get("item", []))
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# 强势/弱势（涨幅 > 2% 为强，< -2% 为弱）
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strong_count = sum(1 for c in all_changes if c > 2)
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weak_count = sum(1 for c in all_changes if c < -2)
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# 市场宽度
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market_breadth = round(up_count / total_stocks * 100, 1) if total_stocks > 0 else 50
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# ── 集合竞价信号 ──
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auction_signal = ""
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auction_detail = {}
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if isinstance(auction_benchmark, dict) and not isinstance(auction_benchmark, Exception):
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# 短线风向标：根据竞价基准判断多空
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benchmark_score = _safe_float(auction_benchmark.get("score", 0))
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benchmark_label = auction_benchmark.get("label", "")
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auction_detail = {
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"score": benchmark_score,
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"label": benchmark_label,
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"date": auction_benchmark.get("date", ""),
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"benchmark": auction_benchmark.get("benchmark", {}),
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}
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if benchmark_score >= 60:
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auction_signal = "强势高开"
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elif benchmark_score >= 45:
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auction_signal = "偏强"
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elif benchmark_score <= 30:
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auction_signal = "弱势低开"
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elif benchmark_score <= 45:
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auction_signal = "偏弱"
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else:
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auction_signal = "中性"
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# ── 市场温度（结合竞价信号校准） ──
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temperature = _calc_temperature(
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up_count, down_count, flat_count, median_change,
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strong_count, weak_count, limit_up_count, limit_down_count,
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break_count, auction_signal,
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)
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market_stats = {
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"upCount": up_count,
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"downCount": down_count,
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"flatCount": flat_count,
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"total": total_stocks,
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"marketBreadth": market_breadth,
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"medianChange": round(median_change, 2),
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"strongCount": strong_count,
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"weakCount": weak_count,
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"limitUp": limit_up_count,
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"limitDown": limit_down_count,
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"limitBreak": break_count,
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"breakRate": round(break_count / (limit_up_count + break_count) * 100, 1) if (limit_up_count + break_count) > 0 else 0,
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"totalTurnover": round(total_turnover, 2),
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"temperature": temperature,
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"auction": auction_detail,
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"auctionSignal": auction_signal,
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}
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# ── 行业强度榜（使用行业指数真实涨幅） ──
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sector_strength = []
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industries = industry_catalog if isinstance(industry_catalog, list) else []
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industry_codes = [ind.get("thscode", "") for ind in industries[:31] if ind.get("thscode")]
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if industry_codes:
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try:
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industry_snapshots = []
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batch_size = 50
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for i in range(0, len(industry_codes), batch_size):
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batch = industry_codes[i:i + batch_size]
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snap = await fuyao_client.index_prices_snapshot(",".join(batch))
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if isinstance(snap, list):
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industry_snapshots.extend(snap)
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await asyncio.sleep(0.05)
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for snap_item in industry_snapshots:
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code = snap_item.get("thscode", "")
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name = ""
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for ind in industries:
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if ind.get("thscode") == code:
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name = ind.get("name", code)
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break
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gain_pct = _safe_float(snap_item.get("price_change_ratio_pct"))
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last = _safe_float(snap_item.get("last_price"))
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sector_strength.append({
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"code": code,
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"name": name or code,
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"price": last,
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"change": _safe_float(snap_item.get("price_change")),
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"changePct": gain_pct,
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})
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sector_strength.sort(key=lambda x: x["changePct"], reverse=True)
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for sec in sector_strength[:31]:
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gp = sec["changePct"]
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strength = round(max(0, min(100, 50 + gp * 12)), 1)
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sec["strength"] = strength
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sec["breadthPct"] = round(max(0, min(100, 50 + gp * 18)), 1)
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sec["strongCount"] = max(0, int(gp * 5))
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except Exception:
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sector_strength = []
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# ── 概念板块热度 Top10 ──
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concept_strength = []
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concepts = concept_catalog if isinstance(concept_catalog, list) else []
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concept_codes = [c.get("thscode", "") for c in concepts[:20] if c.get("thscode")]
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if concept_codes:
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try:
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concept_snapshots = []
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for i in range(0, len(concept_codes), 50):
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batch = concept_codes[i:i + 50]
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snap = await fuyao_client.index_prices_snapshot(",".join(batch))
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if isinstance(snap, list):
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concept_snapshots.extend(snap)
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await asyncio.sleep(0.05)
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for snap_item in concept_snapshots:
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code = snap_item.get("thscode", "")
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name = ""
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for c in concepts:
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if c.get("thscode") == code:
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name = c.get("name", code)
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break
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concept_strength.append({
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"code": code,
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"name": name or code,
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"changePct": _safe_float(snap_item.get("price_change_ratio_pct")),
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})
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concept_strength.sort(key=lambda x: x["changePct"], reverse=True)
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except Exception:
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concept_strength = []
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# ── 事件情报 ──
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events = []
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# 1) 连板天梯
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if isinstance(limit_ladder_data, dict):
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ladder_items = limit_ladder_data.get("item", [])
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if ladder_items:
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today_boards = ladder_items[0].get("boards", {})
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for board_key in ("seven_over", "six_board", "five_board", "four_board", "three_board", "two_board"):
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board_list = today_boards.get(board_key, [])
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for item in board_list[:2]:
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board_num = item.get("board_num", 0)
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events.append({
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"type": "ladder",
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"label": f"{board_num}连板" if board_num > 1 else "首板",
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"name": item.get("name", ""),
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"code": item.get("thscode", ""),
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"detail": "",
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})
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# 2) 热门股 Top5
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if isinstance(hot_stock_data, dict):
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hot_items = hot_stock_data.get("item", [])
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for item in hot_items[:5]:
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rank = item.get("rank", "")
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heat = item.get("heat", "")
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trend = item.get("rank_trend", "")
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trend_icon = "↑" if trend == "up" else ("↓" if trend == "down" else "→")
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events.append({
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"type": "hot",
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"label": f"热门 #{rank}" if rank else "热门",
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"name": item.get("name", ""),
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"code": item.get("thscode", ""),
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"detail": f"热度 {heat} {trend_icon}",
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})
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# 3) 飙升榜 Top3
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if isinstance(skyrocket_data, dict):
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sky_items = skyrocket_data.get("item", [])
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for item in sky_items[:3]:
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heat = item.get("heat", "")
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trend = item.get("rank_trend", "")
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trend_icon = "↑" if trend == "up" else ("↓" if trend == "down" else "→")
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events.append({
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"type": "skyrocket",
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"label": "飙升",
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"name": item.get("name", ""),
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"code": item.get("thscode", ""),
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"detail": f"飙升指数 {heat} {trend_icon}",
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})
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# 4) 涨停池封单 Top3
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if isinstance(limit_up_data, dict):
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lu_items = limit_up_data.get("item", [])
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for item in lu_items[:3]:
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seal = _safe_float(item.get("seal_money", 0))
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reason = item.get("limit_up_reason", "")
|
||
continue_text = item.get("continue_day_text", "")
|
||
events.append({
|
||
"type": "limit_up",
|
||
"label": continue_text or "涨停",
|
||
"name": item.get("name", ""),
|
||
"code": item.get("thscode", ""),
|
||
"detail": f"封单 {seal / 10000:.0f}万 {reason}" if reason else f"封单 {seal / 10000:.0f}万",
|
||
})
|
||
|
||
# 5) 炸板池 Top3
|
||
if isinstance(limit_break_data, dict):
|
||
break_items = limit_break_data.get("item", [])
|
||
for item in break_items[:3]:
|
||
events.append({
|
||
"type": "limit_break",
|
||
"label": "炸板",
|
||
"name": item.get("name", ""),
|
||
"code": item.get("thscode", ""),
|
||
"detail": f"开板 {_safe_float(item.get('open_times', 0))}次",
|
||
})
|
||
|
||
# 6) 龙虎榜
|
||
if isinstance(dragon_tiger_data, dict):
|
||
dt_items = dragon_tiger_data.get("item", [])
|
||
for item in dt_items[:3]:
|
||
reason = item.get("reason", item.get("上榜原因", ""))
|
||
events.append({
|
||
"type": "dragon_tiger",
|
||
"label": "龙虎榜",
|
||
"name": item.get("name", ""),
|
||
"code": item.get("thscode", ""),
|
||
"detail": reason[:40] if reason else "",
|
||
})
|
||
|
||
# 7) 异动分析
|
||
if isinstance(anomaly_data, dict):
|
||
anomaly_items = anomaly_data.get("item", [])
|
||
for item in anomaly_items[:3]:
|
||
tag = item.get("tagName", item.get("tag_code", ""))
|
||
events.append({
|
||
"type": "anomaly",
|
||
"label": "异动",
|
||
"name": item.get("name", ""),
|
||
"code": item.get("thscode", ""),
|
||
"detail": tag,
|
||
})
|
||
|
||
# 8) 盘面统计摘要（固定在最后）
|
||
events.append({
|
||
"type": "summary",
|
||
"label": "盘面",
|
||
"name": f"上涨 {up_count} / 下跌 {down_count} / 平盘 {flat_count}",
|
||
"code": "",
|
||
"detail": f"涨停 {limit_up_count} 跌停 {limit_down_count} 炸板 {break_count}",
|
||
})
|
||
|
||
# ── 组装结果 ──
|
||
result = {
|
||
"indices": indices,
|
||
"marketStats": market_stats,
|
||
"sectorStrength": sector_strength[:31],
|
||
"conceptStrength": concept_strength[:10],
|
||
"events": events,
|
||
"updateTime": datetime.now(BJT).strftime("%Y-%m-%d %H:%M:%S"),
|
||
}
|
||
|
||
_cache["data"] = result
|
||
_cache["at"] = now
|
||
return result
|
||
|
||
|
||
@router.get("/market-dashboard", summary="市场看板数据聚合")
|
||
async def get_market_dashboard():
|
||
try:
|
||
data = await _build_dashboard()
|
||
return JSONResponse({"data": data}, headers=_NO_CACHE_HEADERS)
|
||
except HTTPException:
|
||
raise
|
||
except Exception as e:
|
||
raise HTTPException(status_code=500, detail=f"市场看板数据获取失败: {e}")
|