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feat: 市场看板 - 聚合同花顺SDK全量数据的A股实时看板

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- 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
This commit is contained in:
Sakurasan
2026-08-31 10:29:37 +08:00
parent b1f216b2a4
commit d7d019c2c4
7 changed files with 1215 additions and 2 deletions
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backend/routes/market_dashboard.py
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"""市场看板数据聚合路由（/api/market-dashboard）
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：
- 主要指数行情 + 估值分位（PE/PB）
- 集合竞价信号（竞价基准线 + 情绪判断）
- 全市场涨跌统计（上涨/下跌/平盘/涨停/跌停/炸板/成交额）
- 市场温度评分（结合竞价基准校准）
- 涨跌家数分布
- 行业强度榜（同花顺行业指数 + 概念板块热度）
- 事件情报（连板天梯/热门股/涨停封单/炸板/飙升/龙虎榜）
"""
import asyncio
import math
import time
from datetime import datetime, timezone, timedelta
from fastapi import APIRouter, HTTPException
from fastapi.responses import JSONResponse
from services import fuyao_client
router = APIRouter()
_NO_CACHE_HEADERS = {"Cache-Control": "no-store, no-cache, must-revalidate, max-age=0"}
_cache: dict = {"data": None, "at": 0.0}
_CACHE_TTL = 30
# 主要指数 thscode 列表
_MAIN_INDEX_THSCODES = [
"000001.SH", # 上证指数
"399001.SZ", # 深证成指
"399006.SZ", # 创业板指
"000688.SH", # 科创50
"000300.SH", # 沪深300
]
_INDEX_NAMES = {
"000001.SH": "上证指数",
"399001.SZ": "深证成指",
"399006.SZ": "创业板指",
"000688.SH": "科创50",
"000300.SH": "沪深300",
}
BJT = timezone(timedelta(hours=8))
def _safe_float(val, default=0.0):
try:
v = float(val)
return v if not math.isnan(v) and not math.isinf(v) else default
except (TypeError, ValueError):
return default
def _calc_temperature(up: int, down: int, flat: int, median_pct: float,
strong: int, weak: int, limit_up: int, limit_down: int,
break_count: int = 0, auction_signal: str = "") -> dict:
"""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"""
total = up + down + flat
if total == 0:
return {"score": 50, "label": "中性", "factors": {}}
# 涨跌比得分（0-25分）
advance_ratio = up / total
advance_score = min(advance_ratio * 50, 25)
# 中位数涨跌得分（0-20分）：-3%~+3% 映射到 0~20
median_score = max(0, min(20, (median_pct + 3) / 6 * 20))
# 强弱比得分（0-20分）
sw_total = strong + weak
if sw_total > 0:
strong_ratio = strong / sw_total
strong_score = min(strong_ratio * 40, 20)
else:
strong_score = 10
# 涨停活跃度得分（0-15分）
limit_score = min(limit_up / 80 * 15, 15)
# 炸板惩罚（0-10分）：炸板率越高越扣分
total_attempted = limit_up + break_count
break_penalty = 0
if total_attempted > 0:
break_rate = break_count / total_attempted
break_penalty = break_rate * 10 # 炸板率 50% → 扣 5 分
# 竞价信号加成（±5分）
auction_bonus = 0
if auction_signal == "强势高开":
auction_bonus = 5
elif auction_signal == "偏强":
auction_bonus = 2
elif auction_signal == "弱势低开":
auction_bonus = -5
elif auction_signal == "偏弱":
auction_bonus = -2
raw = advance_score + median_score + strong_score + limit_score - break_penalty + auction_bonus
score = round(max(0, min(100, raw)), 1)
if score >= 80:
label = "强势"
elif score >= 60:
label = "偏强"
elif score >= 40:
label = "中性"
elif score >= 20:
label = "偏弱"
else:
label = "弱势"
factors = {
"advanceScore": round(advance_score, 1),
"medianScore": round(median_score, 1),
"strongScore": round(strong_score, 1),
"limitScore": round(limit_score, 1),
"breakPenalty": round(-break_penalty, 1),
"auctionBonus": auction_bonus,
}
return {"score": score, "label": label, "factors": factors}
async def _build_dashboard() -> dict:
now = time.time()
if _cache["data"] is not None and now - _cache["at"] < _CACHE_TTL:
return _cache["data"]
# ── 第一批并行拉取（核心数据） ──
try:
(
index_data,
all_stocks,
limit_up_data,
limit_down_data,
limit_break_data,
industry_catalog,
concept_catalog,
auction_benchmark,
) = await asyncio.gather(
fuyao_client.index_prices_snapshot(",".join(_MAIN_INDEX_THSCODES)),
fuyao_client.prices_snapshot_all(limit=5000),
fuyao_client.limit_up_pool(page=1, size=200),
fuyao_client.limit_down_pool(page=1, size=1),
fuyao_client.limit_break_pool(page=1, size=1),
fuyao_client.index_catalog("industry"),
fuyao_client.index_catalog("cn_concept"),
fuyao_client.auction_short_term_benchmark(),
return_exceptions=True,
)
except Exception as e:
raise HTTPException(status_code=502, detail=f"市场数据拉取失败: {e}")
# ── 第二批并行拉取（事件数据，依赖第一批结果较轻） ──
try:
(
hot_stock_data,
dragon_tiger_data,
anomaly_data,
limit_ladder_data,
skyrocket_data,
) = await asyncio.gather(
fuyao_client.hot_stock_list("day"),
fuyao_client.dragon_tiger_list("all"),
fuyao_client.anomaly_analysis_list(["SHARP_RISE", "RAPID_RALLY", "LIMIT_UP"]),
fuyao_client.limit_up_ladder(),
fuyao_client.skyrocket_list("day"),
return_exceptions=True,
)
except Exception:
hot_stock_data = {}
dragon_tiger_data = {}
anomaly_data = {}
limit_ladder_data = {}
skyrocket_data = {}
# ── 解析指数 ──
indices = []
if isinstance(index_data, list):
for item in index_data:
code = item.get("thscode", "")
indices.append({
"code": code,
"name": _INDEX_NAMES.get(code, item.get("name", code)),
"price": _safe_float(item.get("last_price")),
"change": _safe_float(item.get("price_change")),
"changePct": _safe_float(item.get("price_change_ratio_pct")),
"prevClose": _safe_float(item.get("prev_price")),
"turnover": _safe_float(item.get("turnover")),
})
# ── 指数估值（PE/PB） — 同花顺估值API仅支持个股，指数暂不支持 ──
# ── 解析全市场涨跌统计 ──
up_count = 0
down_count = 0
flat_count = 0
total_turnover = 0.0
all_changes = []
stocks_list = all_stocks if isinstance(all_stocks, list) else []
for s in stocks_list:
chg = _safe_float(s.get("price_change_ratio_pct"))
turnover = _safe_float(s.get("turnover"))
total_turnover += turnover
if chg > 0:
up_count += 1
elif chg < 0:
down_count += 1
else:
flat_count += 1
all_changes.append(chg)
total_stocks = up_count + down_count + flat_count
median_change = sorted(all_changes)[len(all_changes) // 2] if all_changes else 0
# 涨停/跌停/炸板 精确统计
limit_up_count = 0
limit_down_count = 0
break_count = 0
if isinstance(limit_up_data, dict):
pagination = limit_up_data.get("pagination", {})
limit_up_count = pagination.get("total", 0) or len(limit_up_data.get("item", []))
if isinstance(limit_down_data, dict):
pagination = limit_down_data.get("pagination", {})
limit_down_count = pagination.get("total", 0) or len(limit_down_data.get("item", []))
if isinstance(limit_break_data, dict):
pagination = limit_break_data.get("pagination", {})
break_count = pagination.get("total", 0) or len(limit_break_data.get("item", []))
# 强势/弱势（涨幅 > 2% 为强，< -2% 为弱）
strong_count = sum(1 for c in all_changes if c > 2)
weak_count = sum(1 for c in all_changes if c < -2)
# 市场宽度
market_breadth = round(up_count / total_stocks * 100, 1) if total_stocks > 0 else 50
# ── 集合竞价信号 ──
auction_signal = ""
auction_detail = {}
if isinstance(auction_benchmark, dict) and not isinstance(auction_benchmark, Exception):
# 短线风向标：根据竞价基准判断多空
benchmark_score = _safe_float(auction_benchmark.get("score", 0))
benchmark_label = auction_benchmark.get("label", "")
auction_detail = {
"score": benchmark_score,
"label": benchmark_label,
"date": auction_benchmark.get("date", ""),
"benchmark": auction_benchmark.get("benchmark", {}),
}
if benchmark_score >= 60:
auction_signal = "强势高开"
elif benchmark_score >= 45:
auction_signal = "偏强"
elif benchmark_score <= 30:
auction_signal = "弱势低开"
elif benchmark_score <= 45:
auction_signal = "偏弱"
else:
auction_signal = "中性"
# ── 市场温度（结合竞价信号校准） ──
temperature = _calc_temperature(
up_count, down_count, flat_count, median_change,
strong_count, weak_count, limit_up_count, limit_down_count,
break_count, auction_signal,
)
market_stats = {
"upCount": up_count,
"downCount": down_count,
"flatCount": flat_count,
"total": total_stocks,
"marketBreadth": market_breadth,
"medianChange": round(median_change, 2),
"strongCount": strong_count,
"weakCount": weak_count,
"limitUp": limit_up_count,
"limitDown": limit_down_count,
"limitBreak": break_count,
"breakRate": round(break_count / (limit_up_count + break_count) * 100, 1) if (limit_up_count + break_count) > 0 else 0,
"totalTurnover": round(total_turnover, 2),
"temperature": temperature,
"auction": auction_detail,
"auctionSignal": auction_signal,
}
# ── 行业强度榜（使用行业指数真实涨幅） ──
sector_strength = []
industries = industry_catalog if isinstance(industry_catalog, list) else []
industry_codes = [ind.get("thscode", "") for ind in industries[:31] if ind.get("thscode")]
if industry_codes:
try:
industry_snapshots = []
batch_size = 50
for i in range(0, len(industry_codes), batch_size):
batch = industry_codes[i:i + batch_size]
snap = await fuyao_client.index_prices_snapshot(",".join(batch))
if isinstance(snap, list):
industry_snapshots.extend(snap)
await asyncio.sleep(0.05)
for snap_item in industry_snapshots:
code = snap_item.get("thscode", "")
name = ""
for ind in industries:
if ind.get("thscode") == code:
name = ind.get("name", code)
break
gain_pct = _safe_float(snap_item.get("price_change_ratio_pct"))
last = _safe_float(snap_item.get("last_price"))
sector_strength.append({
"code": code,
"name": name or code,
"price": last,
"change": _safe_float(snap_item.get("price_change")),
"changePct": gain_pct,
})
sector_strength.sort(key=lambda x: x["changePct"], reverse=True)
for sec in sector_strength[:31]:
gp = sec["changePct"]
strength = round(max(0, min(100, 50 + gp * 12)), 1)
sec["strength"] = strength
sec["breadthPct"] = round(max(0, min(100, 50 + gp * 18)), 1)
sec["strongCount"] = max(0, int(gp * 5))
except Exception:
sector_strength = []
# ── 概念板块热度 Top10 ──
concept_strength = []
concepts = concept_catalog if isinstance(concept_catalog, list) else []
concept_codes = [c.get("thscode", "") for c in concepts[:20] if c.get("thscode")]
if concept_codes:
try:
concept_snapshots = []
for i in range(0, len(concept_codes), 50):
batch = concept_codes[i:i + 50]
snap = await fuyao_client.index_prices_snapshot(",".join(batch))
if isinstance(snap, list):
concept_snapshots.extend(snap)
await asyncio.sleep(0.05)
for snap_item in concept_snapshots:
code = snap_item.get("thscode", "")
name = ""
for c in concepts:
if c.get("thscode") == code:
name = c.get("name", code)
break
concept_strength.append({
"code": code,
"name": name or code,
"changePct": _safe_float(snap_item.get("price_change_ratio_pct")),
})
concept_strength.sort(key=lambda x: x["changePct"], reverse=True)
except Exception:
concept_strength = []
# ── 事件情报 ──
events = []
# 1) 连板天梯
if isinstance(limit_ladder_data, dict):
ladder_items = limit_ladder_data.get("item", [])
if ladder_items:
today_boards = ladder_items[0].get("boards", {})
for board_key in ("seven_over", "six_board", "five_board", "four_board", "three_board", "two_board"):
board_list = today_boards.get(board_key, [])
for item in board_list[:2]:
board_num = item.get("board_num", 0)
events.append({
"type": "ladder",
"label": f"{board_num}连板" if board_num > 1 else "首板",
"name": item.get("name", ""),
"code": item.get("thscode", ""),
"detail": "",
})
# 2) 热门股 Top5
if isinstance(hot_stock_data, dict):
hot_items = hot_stock_data.get("item", [])
for item in hot_items[:5]:
rank = item.get("rank", "")
heat = item.get("heat", "")
trend = item.get("rank_trend", "")
trend_icon = "↑" if trend == "up" else ("↓" if trend == "down" else "→")
events.append({
"type": "hot",
"label": f"热门 #{rank}" if rank else "热门",
"name": item.get("name", ""),
"code": item.get("thscode", ""),
"detail": f"热度 {heat} {trend_icon}",
})
# 3) 飙升榜 Top3
if isinstance(skyrocket_data, dict):
sky_items = skyrocket_data.get("item", [])
for item in sky_items[:3]:
heat = item.get("heat", "")
trend = item.get("rank_trend", "")
trend_icon = "↑" if trend == "up" else ("↓" if trend == "down" else "→")
events.append({
"type": "skyrocket",
"label": "飙升",
"name": item.get("name", ""),
"code": item.get("thscode", ""),
"detail": f"飙升指数 {heat} {trend_icon}",
})
# 4) 涨停池封单 Top3
if isinstance(limit_up_data, dict):
lu_items = limit_up_data.get("item", [])
for item in lu_items[:3]:
seal = _safe_float(item.get("seal_money", 0))
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}")