"""大盘行情总览(主页展示)——两层结构。 - live 层:腾讯免费实时行情(qt.gtimg.cn,一次 GET 拿 A股/美股指数现价/涨跌幅)+ 东财 push2(日韩指数,腾讯 s_ 前缀不覆盖,实测 s_jp*/s_kr* 均无符号), 进程内缓存 30s(成功)/ 15s 负缓存(失败,防止接口抖动持续拖慢请求)。 - EOD 层:tushare 收盘数据 —— A 股指数 pro.index_daily、全球指数 pro.index_global (45 日 spark 走势)+ 两市统计/成交额历史 pro.daily_info。收盘数据一天一变, 进程内新鲜期 4h + Redis 兜底 24h,过期走 SWR(先返旧值,后台刷新,永不阻塞用户)。 - merge:实时价覆盖 close/change/pct_chg(realtime=True),拿不到实时值的指数回退 收盘口径;今日为交易日且 EOD 尚未含今日时,用腾讯全市口径成交额追加盘中 bar。 口径说明(daily_info 板块行,实测 2026-09): - 沪市 SH_MARKET = 主板A + 科创板(SH_STAR) + B股,不含基金(SH_FUND); 旧口径 SH_A 漏科创板(日均 ~2500 亿),是成交额偏小的根因。 - 深市 SZ_MARKET = 主板 + 创业板,全部为股票。 - 任何单个来源失败只是跳过(errors 里注明),全部失败才抛 MarketOverviewError。 """ from __future__ import annotations import asyncio import time from datetime import date, datetime, timedelta import httpx import pandas as pd from .. import cache from ..config import settings from .sync_utils import d8_iso, f_clean # (tushare代码, 名称, 地区, 腾讯符号) —— 展示顺序即列表顺序 # 首页聚焦中美 + 日韩(其余国际指数在 /indexes 国际指数页);标普500 腾讯符号是 s_usINX(不是 s_usSPX) MARKET_INDEXES: list[tuple[str, str, str, str]] = [ ("000001.SH", "上证指数", "cn", "s_sh000001"), ("399001.SZ", "深证成指", "cn", "s_sz399001"), ("399006.SZ", "创业板指", "cn", "s_sz399006"), ("000688.SH", "科创50", "cn", "s_sh000688"), ("DJI", "道琼斯", "us", "s_usDJI"), ("IXIC", "纳斯达克", "us", "s_usIXIC"), ("SPX", "标普500", "us", "s_usINX"), ("N225", "日经225", "apac", ""), # 日韩实时走东财(_APAC_SECIDS),腾讯符号留空 ("KS11", "韩国KOSPI", "apac", ""), ] # 深证综指:不展示,仅取其 f[7](深市全市成交额,万元) _TENCENT_SZ_TOTAL = "s_sz399106" _TENCENT_MAP = {ts_code: sym for ts_code, _, _, sym in MARKET_INDEXES if sym} _TENCENT_URL = "http://qt.gtimg.cn/q=" + ",".join([*_TENCENT_MAP.values(), _TENCENT_SZ_TOTAL]) # 日韩指数实时源:东财 push2 ulist 一次 GET(主站 + 延迟镜像双 host)。腾讯 s_ 前缀不 # 覆盖日韩(实测均返回 pv_none_match);新浪 int_kospi 为空且 int_* 行情明显滞后 # (实测 DJI 差价 ~6000 点),故不用。 _APAC_SECIDS = {"N225": "100.N225", "KS11": "100.KS11"} _EM_HEADERS = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 " "(KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36"} # 同 etf_provider _EM_HOSTS = ["https://push2.eastmoney.com", "https://push2delay.eastmoney.com"] _EM_PATH = ("/api/qt/ulist.np/get?fltt=2&invt=2&fields=f2,f3,f4,f12,f14&secids=" + ",".join(_APAC_SECIDS.values())) # 指数 code -> live 行情键(em: 前缀与腾讯符号隔离),merge 时查表 _LIVE_SYM_MAP: dict[str, str] = {**_TENCENT_MAP, **{c: f"em:{c}" for c in _APAC_SECIDS}} _SPARK_DAYS = 45 # 迷你走势取最近 45 个交易日收盘 _HISTORY_DAYS = 150 # 日历日窗口(约 100 个交易日,够取 spark) _CALL_INTERVAL = 0.12 # 顺序调用间隔(秒),对 tushare 控频 _EOD_KEY = "market_overview:eod:v4" # v4:新增日韩指数(N225/KS11),与 v3 隔离 _AMOUNT_HIST_CAL_DAYS = 190 # 成交额历史的日历日窗口(≈128 交易日) _AMOUNT_HIST_BARS = 120 # 输出的柱数(取尾部) _LIVE_FAIL_TTL = 15.0 # 腾讯 live 层失败负缓存(秒) _EM_FAIL_TTL = 90.0 # 东财日韩失败负缓存(秒):长于 live 缓存 30s, # 持续故障时最多每 90s 才有一次超时等待,其余刷新直接跳过 class MarketOverviewError(RuntimeError): """所有指数都拉不到(token/网络故障)——接口层转 503。""" def _get_pro(): if not settings.tushare_token: raise MarketOverviewError("未配置 TUSHARE_TOKEN,无法获取大盘行情(backend/.env)") # 走统一入口:15000 积分档 token 只认 quicksync 镜像(直连 api.tushare.pro 会 40101) from .tushare_provider import get_pro return get_pro() # ======================= live 层:腾讯实时行情 ======================= _live: dict = {"at": 0.0, "quotes": None} # 进程内缓存(monotonic 时钟) _live_error: str | None = None # 最近一次腾讯实时拉取失败的原因(成功后清空) _live_em_error: str | None = None # 最近一次东财日韩实时拉取失败的原因(成功后清空) _em_state: dict = {"at": 0.0, "ok": None, "host": 0} # 东财日韩负缓存 + 最近成功 host 索引 async def _fetch_live_http() -> dict[str, dict]: """一次 GET 拿全部符号。响应 GBK,行如 v_s_sh000001="1~上证指数~000001~3930.12~-11.97~-0.30~537286161~93825519~~"; 字段序:f[1]名称 / f[3]现价 / f[4]涨跌 / f[5]涨跌% / f[7]成交额。 单位陷阱:仅 s_sh000001 与 s_sz399106 的 f[7] 是「万元、全市口径」,可算两市成交额; 港股行的 f[7] 是手数、美股行非人民币金额,s_sz399001(深证成指)是成分股口径——都不能用。 """ async with httpx.AsyncClient(timeout=settings.tencent_quote_timeout) as client: resp = await client.get(_TENCENT_URL) resp.raise_for_status() text = resp.content.decode("gbk", errors="replace") # 响应头 charset 不可靠,显式解码 quotes: dict[str, dict] = {} for line in text.splitlines(): if "=" not in line: continue head, _, body = line.partition("=") sym = head.strip().removeprefix("v_") fields = body.strip().strip(';"').split("~") if not sym or len(fields) < 8: continue def _num(i: int) -> float | None: try: return float(fields[i]) except (TypeError, ValueError): return None quotes[sym] = { "name": fields[1], "price": _num(3), "change": _num(4), "pct": _num(5), "amount_wan": _num(7), } if not quotes: raise RuntimeError("腾讯行情响应为空或无法解析") return quotes def _parse_em_ulist(payload: dict) -> dict[str, dict]: """ulist JSON -> {em:code: {name, price, change, pct, amount_wan}}。fltt=2 下 f2/f3/f4 直接是浮点;未开盘等场景字段是 "-",解析为 None。""" diff = (payload.get("data") or {}).get("diff") or [] quotes: dict[str, dict] = {} for row in diff: code = str(row.get("f12") or "") if code not in _APAC_SECIDS: continue def _num(v) -> float | None: try: return float(v) except (TypeError, ValueError): return None quotes[f"em:{code}"] = { "name": row.get("f14"), "price": _num(row.get("f2")), "change": _num(row.get("f4")), "pct": _num(row.get("f3")), "amount_wan": None, # 日韩成交额口径不同且未使用,不取 } if not quotes: raise RuntimeError("东财日韩行情响应为空或无法解析") return quotes async def _fetch_live_apac_http() -> dict[str, dict]: """日韩指数实时(东财 ulist 一次 GET,主站/延迟镜像按序重试,粘住最近成功的 host)。 坑(同 etf_provider 实测):push2 主站短连发几次会直接断连,push2delay 镜像稳; 本机 v2rayN 系统代理(127.0.0.1:10808)对 push2 的 https CONNECT 隧道断连(curl -x 同样失败,腾讯 http:// 却正常)——必须带浏览器 UA 且 trust_env=False 直连。""" start = _em_state.get("host", 0) last_err: Exception | None = None for i in range(len(_EM_HOSTS)): url = _EM_HOSTS[(start + i) % len(_EM_HOSTS)] + _EM_PATH try: async with httpx.AsyncClient( timeout=settings.tencent_quote_timeout, headers=_EM_HEADERS, trust_env=False, ) as client: resp = await client.get(url) resp.raise_for_status() payload = resp.json() quotes = _parse_em_ulist(payload) _em_state["host"] = (start + i) % len(_EM_HOSTS) # 粘住成功 host return quotes except Exception as e: # noqa: BLE001 —— 换镜像整重来 last_err = e raise RuntimeError(f"东财日韩行情双镜像均失败: {str(last_err)[:60]}") async def _fetch_live() -> dict[str, dict] | None: """实时行情(进程内缓存);腾讯与东财各自独立降级,全失败返回 None,上层降级 EOD。 东财有独立负缓存(_EM_FAIL_TTL):持续故障时后续刷新直接跳过,不吃超时等待。""" global _live_error, _live_em_error now = time.monotonic() age = now - _live["at"] if _live["quotes"] is not None and age < settings.market_live_ttl: return _live["quotes"] if _live["quotes"] is None and _live["at"] > 0 and age < _LIVE_FAIL_TTL: return None # 负缓存:刚失败过,短时间内不再打行情接口 quotes: dict[str, dict] = {} try: quotes.update(await _fetch_live_http()) _live_error = None except Exception as e: # noqa: BLE001 —— 实时层是锦上添花,失败不拖垮整包 _live_error = f"实时行情: {str(e)[:60]}" if _em_state["ok"] is False and now - _em_state["at"] < _EM_FAIL_TTL: pass # 东财刚失败过:负缓存期内跳过(_live_em_error 保留上次原因) else: try: quotes.update(await _fetch_live_apac_http()) _live_em_error = None _em_state.update(at=now, ok=True) except Exception as e: # noqa: BLE001 _live_em_error = f"日韩实时行情: {str(e)[:60]}" _em_state.update(at=now, ok=False) if not quotes: _live.update(at=now, quotes=None) return None _live.update(at=now, quotes=quotes) return quotes # ======================= EOD 层:tushare 收盘数据 ======================= def _fetch_index_sync(pro, ts_code: str) -> pd.DataFrame: start = (datetime.now() - timedelta(days=_HISTORY_DAYS)).strftime("%Y%m%d") if "." in ts_code: # A 股指数(000001.SH 形式) return pro.index_daily(ts_code=ts_code, start_date=start) return pro.index_global(ts_code=ts_code, start_date=start) def _quote_from_df(df: pd.DataFrame) -> dict | None: """DataFrame -> {close, change, pct_chg, trade_date, spark, spark_dates}(旧 -> 新)。""" if df is None or df.empty: return None df = df.sort_values("trade_date") tail = df.tail(_SPARK_DAYS) last = df.iloc[-1] return { "close": f_clean(last["close"]), "change": f_clean(last.get("change")), "pct_chg": f_clean(last.get("pct_chg")), "trade_date": d8_iso(last["trade_date"]), "spark": [round(float(c), 4) for c in tail["close"]], "spark_dates": [str(d) for d in tail["trade_date"]], } def _fetch_stats_sync(pro) -> dict | None: """两市市值/成交统计:沪 SH_MARKET(主板A+科创+B,不含基金)+ 深 SZ_MARKET(全部股票)。 口径与本地 candles 全市场 sum(amount) 吻合(candles 另含北交所,约 +70 亿)。 """ start = (datetime.now() - timedelta(days=14)).strftime("%Y%m%d") sh = pro.daily_info(exchange="SH", start_date=start) sz = pro.daily_info(exchange="SZ", start_date=start) if sh is None or sh.empty or sz is None or sz.empty: return None def _board(df: pd.DataFrame, code: str): sub = df[df["ts_code"] == code].sort_values("trade_date") # 接口不保证有序 return sub.iloc[-1] if not sub.empty else None sh_m, sz_m = _board(sh, "SH_MARKET"), _board(sz, "SZ_MARKET") if sh_m is None or sz_m is None: return None # 两边各自取最新,日期不一致时以较旧一天为准凑齐口径(罕见,通常同日) d = min(d8_iso(sh_m["trade_date"]), d8_iso(sz_m["trade_date"])) def _sum(col: str) -> float | None: a, b = f_clean(sh_m.get(col)), f_clean(sz_m.get(col)) return None if a is None or b is None else round(a + b, 2) return { "trade_date": d, "total_mv": _sum("total_mv"), "float_mv": _sum("float_mv"), "amount": _sum("amount"), "turnover": f_clean(sh_m.get("tr")), # 换手率仅沪市有,展示口径注明沪市 } def _fetch_amount_history_sync(pro) -> list[dict]: """两市成交额历史:daily_info 范围查询一次拉多日(SH 6 个月实测 0.09s), 沪 SH_MARKET + 深 SZ_MARKET 按日对齐相加(接口原生亿元),升序取尾部 120 根。""" start = (datetime.now() - timedelta(days=_AMOUNT_HIST_CAL_DAYS)).strftime("%Y%m%d") sh = pro.daily_info(exchange="SH", start_date=start) sz = pro.daily_info(exchange="SZ", start_date=start) if sh is None or sh.empty or sz is None or sz.empty: return [] sh_m = sh[sh["ts_code"] == "SH_MARKET"].set_index("trade_date")["amount"] sz_m = sz[sz["ts_code"] == "SZ_MARKET"].set_index("trade_date")["amount"] common = sh_m.index.intersection(sz_m.index) # 内连接:两市都有数据的交易日 if len(common) == 0: return [] total = (sh_m[common] + sz_m[common]).sort_index() return [{"date": d8_iso(d), "amount": round(float(v), 2)} for d, v in total.tail(_AMOUNT_HIST_BARS).items()] # ---- EOD 的 SWR(stale-while-revalidate):新鲜期内直返;过期先返旧值后台刷新 ---- _eod_state: dict = {"payload": None} # 进程内新鲜/陈旧兜底(payload 自带 fetched_ts 墙钟) _eod_refreshing = False # 后台刷新防重入标志 _eod_refresh_error: str | None = None # 最近一次后台刷新失败的原因 _bg_tasks: set[asyncio.Task] = set() # 持引用防 GC async def _refresh_eod() -> dict: """拉全量 EOD(9 指数 + 统计 + 成交额历史,顺序控频),写进程内 state + Redis。""" pro = await asyncio.to_thread(_get_pro) indexes: list[dict] = [] errors: list[str] = [] for ts_code, name, region, _sym in MARKET_INDEXES: try: df = await asyncio.to_thread(_fetch_index_sync, pro, ts_code) q = _quote_from_df(df) if q is None: raise MarketOverviewError("无数据") indexes.append({"code": ts_code, "name": name, "region": region, **q}) except Exception as e: # noqa: BLE001 —— 单个指数失败不拖垮整包 errors.append(f"{name}: {str(e)[:60]}") await asyncio.sleep(_CALL_INTERVAL) if not indexes: raise MarketOverviewError("大盘行情全部拉取失败: " + "; ".join(errors)[:200]) stats: dict | None = None try: await asyncio.sleep(_CALL_INTERVAL) stats = await asyncio.to_thread(_fetch_stats_sync, pro) except Exception as e: # noqa: BLE001 —— 统计缺失时指数照常展示 errors.append(f"两市统计: {str(e)[:60]}") amount_history: list[dict] = [] try: await asyncio.sleep(_CALL_INTERVAL) amount_history = await asyncio.to_thread(_fetch_amount_history_sync, pro) except Exception as e: # noqa: BLE001 —— 历史图缺数据时其余照常 errors.append(f"成交额历史: {str(e)[:60]}") payload = { "fetched_at": datetime.now().isoformat(), "fetched_ts": time.time(), # 墙钟(epoch float):跨进程(Redis)判新鲜度用 "indexes": indexes, "stats": stats, "amount_history": amount_history, "errors": errors, } _eod_state["payload"] = payload await cache.cache_set(_EOD_KEY, payload, ttl=settings.market_eod_redis_ttl) return payload async def _refresh_eod_wrapped() -> None: """后台刷新的主体:失败静默保留旧值并记录原因(下次请求并入 errors 便于排查)。""" global _eod_refresh_error, _eod_refreshing try: await _refresh_eod() _eod_refresh_error = None except Exception as e: # noqa: BLE001 _eod_refresh_error = f"EOD后台刷新: {str(e)[:60]}" finally: _eod_refreshing = False def _spawn_eod_refresh() -> None: global _eod_refreshing if _eod_refreshing: return _eod_refreshing = True task = asyncio.create_task(_refresh_eod_wrapped()) _bg_tasks.add(task) task.add_done_callback(_bg_tasks.discard) async def _get_eod() -> dict: """读 EOD:内存新鲜直返(0 RTT)→ Redis 回填 → 有旧值先返 + SWR 后台刷新 → 真冷启动同步拉。""" p = _eod_state["payload"] if p is not None and time.time() - p["fetched_ts"] < settings.market_eod_fresh_ttl: return p if p is None: cached = await cache.cache_get(_EOD_KEY) if cached: p = cached _eod_state["payload"] = p if p is not None: _spawn_eod_refresh() # 陈旧但可用:立即返回,后台拉新 return p return await _refresh_eod() # 首次访问:同步等(~3.5s,与旧行为一致) # ======================= merge:实时叠加收盘 ======================= async def fetch_overview(is_trading_day: bool | None = None) -> dict: """聚合 live + EOD。实时价覆盖 close/change/pct_chg(realtime=True),今日实时成交额 (腾讯全市口径)在 EOD 尚未含今日时追加为盘中 bar。响应不再整包缓存:两层各有 进程内缓存,合并是 O(10) 操作,热路径 0 外部 RTT。""" eod = await _get_eod() live = await _fetch_live() today_iso = date.today().isoformat() indexes: list[dict] = [] for it in eod["indexes"]: out = dict(it) sym = _LIVE_SYM_MAP.get(it["code"]) q = live.get(sym) if (live and sym) else None if q and q.get("price") is not None: # spark 永远来自 EOD(末点是上一收盘点,与实时价并存是已知的装饰性差异,不改历史序列) out.update(close=q["price"], change=q["change"], pct_chg=q["pct"], trade_date=today_iso, realtime=True) else: out["realtime"] = False indexes.append(out) stats = dict(eod["stats"]) if eod.get("stats") else None history = list(eod.get("amount_history") or []) # 今日实时两市成交额:沪深全市口径(万元->亿)。EOD 已含今日、非交易日、金额缺失时不追加。 if live and stats and stats.get("trade_date") != today_iso: if is_trading_day is None: is_trading_day = datetime.now().weekday() < 5 # 日历判定不可用时的降级启发式 if is_trading_day: sh_amt = (live.get("s_sh000001") or {}).get("amount_wan") sz_amt = (live.get(_TENCENT_SZ_TOTAL) or {}).get("amount_wan") if sh_amt is not None and sz_amt is not None: amt = round((sh_amt + sz_amt) / 10000, 2) stats["amount_today"] = amt history.append({"date": today_iso, "amount": amt, "intraday": True}) errors = list(eod.get("errors") or []) if _eod_refresh_error: errors.append(_eod_refresh_error) if _live_error: errors.append(_live_error) if _live_em_error: errors.append(_live_em_error) return { "updated_at": datetime.now().isoformat(), "indexes": indexes, "stats": stats, "amount_history": history, "errors": errors, }