refactor: establish standalone application boundary

This commit is contained in:
leefer
2026-08-03 21:42:25 +08:00
parent cc5fb8d73e
commit e1e76cd51e
324 changed files with 63090 additions and 44743 deletions
+412
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from __future__ import annotations
import copy
from typing import Any
from backend.bootstrap.config import validate_text
from backend.data.providers.tushare_client import _sector_coverage_issue
from backend.features.heaven.engine import _market_line_scores, _score_to_line
class HeavenManualMixin:
@staticmethod
def _heaven_manual_schema(market_mode: str) -> dict[str, dict[str, Any]]:
intraday = market_mode == "intraday"
fields = {
"stock_amount_percentile": {"line": 1, "label": "成交额全市场分位", "unit": "%", "min": 0, "max": 100},
"stock_turnover_rate": {"line": 1, "label": "个股换手率", "unit": "%", "min": 0, "max": 100},
"stock_turnover_relative": {"line": 1, "label": "相对市场换手", "unit": "", "min": 0, "max": 20},
"stock_volume_activity_ratio": {"line": 1, "label": "同进度量能", "unit": "", "min": 0, "max": 20},
"stock_seal_amount_million": {"line": 1, "label": "封单金额", "unit": "万元", "min": 0, "max": 100000000},
"stock_open_times": {"line": 1, "label": "开板次数", "unit": "", "min": 0, "max": 100, "integer": True},
"stock_change": {"line": 2, "label": "个股涨跌幅", "unit": "%", "min": -100, "max": 100},
"stock_streak": {"line": 2, "label": "连板高度", "unit": "", "min": 0, "max": 100, "integer": True},
"stock_status": {"line": 2, "label": "个股状态", "type": "select", "options": ["普通", "涨停", "炸板", "跌停"]},
"sector_name": {"line": [3, 4], "label": "申万二级行业", "type": "text", "max_length": 50},
"sector_up_count": {"line": 3, "label": "行业上涨家数", "unit": "", "min": 0, "max": 10000, "integer": True},
"sector_down_count": {"line": 3, "label": "行业下跌家数", "unit": "", "min": 0, "max": 10000, "integer": True},
"sector_coverage": {"line": 3, "label": "成分行情覆盖率", "unit": "%", "min": 0, "max": 100},
"sector_relative_turnover": {"line": 3, "label": "行业相对市场换手", "unit": "", "min": 0, "max": 20},
"sector_member_equal_change": {"line": 3, "label": "成分等权涨跌幅", "unit": "%", "min": -100, "max": 100},
"sector_change": {"line": 4, "label": "申万官方涨跌幅", "unit": "%", "min": -100, "max": 100},
"sector_leading_pct": {"line": [3, 4], "label": "行业领涨股涨跌幅", "unit": "%", "min": -100, "max": 100},
"market_sentiment_score": {"line": 5, "label": "市场情绪温度", "unit": "", "min": 0, "max": 100},
"market_seal_rate": {"line": 5, "label": "封板率", "unit": "%", "min": 0, "max": 100},
"market_amount_billion": {"line": 5, "label": "两市成交额", "unit": "亿元", "min": 0, "max": 10000000},
"market_recent_average_amount_billion": {"line": 5, "label": "近期平均成交额", "unit": "亿元", "min": 0, "max": 10000000},
"market_up_count": {"line": 5, "label": "上涨家数", "unit": "", "min": 0, "max": 10000, "integer": True},
"market_down_count": {"line": 5, "label": "下跌家数", "unit": "", "min": 0, "max": 10000, "integer": True},
"market_limit_up_count": {"line": 5, "label": "涨停家数", "unit": "", "min": 0, "max": 10000, "integer": True},
"market_limit_down_count": {"line": 5, "label": "跌停家数", "unit": "", "min": 0, "max": 10000, "integer": True},
"index_sh_change": {"line": 6, "label": "上证指数涨跌幅", "unit": "%", "min": -20, "max": 20},
"index_sz_change": {"line": 6, "label": "深证成指涨跌幅", "unit": "%", "min": -20, "max": 20},
"index_cy_change": {"line": 6, "label": "创业板指涨跌幅", "unit": "%", "min": -20, "max": 20},
"note": {"line": [], "label": "补录说明", "type": "text", "max_length": 200},
}
if intraday:
for key in ("stock_seal_amount_million", "stock_open_times"):
fields.pop(key)
else:
for key in ("stock_turnover_relative", "stock_volume_activity_ratio", "sector_relative_turnover"):
fields.pop(key)
return fields
@classmethod
def _validate_heaven_manual_data(
cls, raw: Any, market_mode: str
) -> dict[str, Any]:
if raw in (None, ""):
return {}
if not isinstance(raw, dict):
raise ValueError("六爻补录数据格式不正确。")
schema = cls._heaven_manual_schema(market_mode)
unknown = set(raw) - set(schema)
if unknown:
raise ValueError(f"六爻补录包含未知字段:{next(iter(sorted(unknown)))}")
values: dict[str, Any] = {}
for key, value in raw.items():
if value is None or (isinstance(value, str) and not value.strip()):
continue
spec = schema[key]
if spec.get("type") == "text":
values[key] = validate_text(value, spec["label"], int(spec["max_length"]))
continue
if spec.get("type") == "select":
text = str(value).strip()
if text not in spec["options"]:
raise ValueError(f"{spec['label']}不在允许范围内。")
values[key] = text
continue
try:
number = float(value)
except (TypeError, ValueError) as exc:
raise ValueError(f"{spec['label']}必须是数字。") from exc
if number < float(spec["min"]) or number > float(spec["max"]):
raise ValueError(
f"{spec['label']}应在 {spec['min']}{spec['max']} 之间。"
)
values[key] = int(number) if spec.get("integer") else number
return values
@staticmethod
def _apply_heaven_manual_data(
dashboard: dict[str, Any],
index_context: dict[str, Any],
sector: dict[str, Any] | None,
stock: dict[str, Any] | None,
manual_data: dict[str, Any],
market_mode: str,
trade_date: str,
stock_code: str,
) -> tuple[dict[str, Any], dict[str, Any], dict[str, Any], dict[str, Any]]:
dashboard = copy.deepcopy(dashboard)
index_context = copy.deepcopy(index_context or {})
sector = copy.deepcopy(sector or {})
stock = copy.deepcopy(stock or {})
overview = dashboard.setdefault("overview", {})
stock_map = {
"stock_amount_percentile": "amount_percentile",
"stock_turnover_rate": "turnover_rate",
"stock_turnover_relative": "turnover_relative",
"stock_volume_activity_ratio": "volume_activity_ratio",
"stock_seal_amount_million": "seal_amount_million",
"stock_open_times": "open_times",
"stock_change": "change",
"stock_streak": "streak",
"stock_status": "status",
}
sector_map = {
"sector_name": "name",
"sector_up_count": "up_count",
"sector_down_count": "down_count",
"sector_coverage": "coverage",
"sector_relative_turnover": "relative_turnover",
"sector_member_equal_change": "member_equal_change",
"sector_change": "change",
"sector_leading_pct": "leading_pct",
}
overview_map = {
"market_sentiment_score": "sentiment_score",
"market_seal_rate": "seal_rate",
"market_amount_billion": "amount_billion",
"market_recent_average_amount_billion": "recent_average_amount_billion",
"market_up_count": "up_count",
"market_down_count": "down_count",
"market_limit_up_count": "limit_up_count",
"market_limit_down_count": "limit_down_count",
}
for manual_key, target in stock_map.items():
if manual_key in manual_data:
stock[target] = manual_data[manual_key]
for manual_key, target in sector_map.items():
if manual_key in manual_data:
sector[target] = manual_data[manual_key]
for manual_key, target in overview_map.items():
if manual_key in manual_data:
overview[target] = manual_data[manual_key]
if any(key.startswith("stock_") for key in manual_data):
stock.setdefault("code", stock_code)
stock.setdefault("name", stock_code or "--")
stock["_quantitative_mode"] = "intraday" if market_mode == "intraday" else "historical"
if market_mode == "intraday" and "stock_volume_activity_ratio" in manual_data:
stock["activity_source"] = "user_supplied"
if any(key.startswith("sector_") for key in manual_data):
sector["_quantitative_mode"] = "intraday" if market_mode == "intraday" else "historical"
sector.setdefault("taxonomy", "sw_l2")
index_keys = (
("index_sh_change", "000001.SH", "上证指数"),
("index_sz_change", "399001.SZ", "深证成指"),
("index_cy_change", "399006.SZ", "创业板指"),
)
rows = {str(row.get("ts_code") or row.get("code") or ""): dict(row) for row in index_context.get("indices") or []}
for manual_key, code, name in index_keys:
if manual_key not in manual_data:
continue
row = rows.get(code, {"ts_code": code, "name": name})
row.update({"pct_chg": manual_data[manual_key], "trade_date": trade_date})
rows[code] = row
ordered_rows = [rows.get(code) for _, code, _ in index_keys]
if all(ordered_rows):
index_context["indices"] = ordered_rows
changes = [float(row.get("pct_chg") or 0) for row in ordered_rows]
aggregate = dict(index_context.get("aggregate") or {})
aggregate["average_pct_chg"] = sum(changes) / 3
index_context["aggregate"] = aggregate
return dashboard, index_context, sector, stock
@classmethod
def _heaven_line_checks(
cls,
trade_date: str,
dashboard: dict[str, Any],
recent_history: list[dict[str, Any]],
index_context: dict[str, Any],
sector: dict[str, Any],
stock: dict[str, Any],
market_mode: str,
manual_data: dict[str, Any],
) -> list[dict[str, Any]]:
intraday = market_mode == "intraday"
closed = market_mode == "closed"
schema = cls._heaven_manual_schema(market_mode)
required = {
1: (["stock_amount_percentile", "stock_turnover_relative", "stock_volume_activity_ratio"] if intraday else ["stock_amount_percentile", "stock_turnover_rate", "stock_seal_amount_million", "stock_open_times"]),
2: ["stock_change", "stock_streak", "stock_status"],
3: (["sector_name", "sector_up_count", "sector_down_count", "sector_coverage", "sector_relative_turnover"] if intraday else ["sector_name", "sector_up_count", "sector_down_count", "sector_coverage", "sector_member_equal_change", "sector_leading_pct"]),
4: ["sector_name", "sector_change", "sector_leading_pct"],
5: ["market_sentiment_score", "market_seal_rate", "market_amount_billion", "market_recent_average_amount_billion", "market_up_count", "market_down_count", "market_limit_up_count", "market_limit_down_count"],
6: ["index_sh_change", "index_sz_change", "index_cy_change"],
}
names = {
1: ("初爻", "个股内核", "成交活跃、换手与量能"),
2: ("二爻", "个股外显", "涨跌、连板与状态"),
3: ("三爻", "行业内核", "行业宽度与成交活跃"),
4: ("四爻", "行业外显", "行业涨跌与领涨表现"),
5: ("五爻", "市场内核", "情绪、封板、成交与市场宽度"),
6: ("上爻", "指数外显", "三大指数当日涨跌"),
}
index_date = str(index_context.get("trade_date") or "").replace("-", "")
index_rows = list(index_context.get("indices") or [])
index_dates = {str(row.get("trade_date") or "").replace("-", "") for row in index_rows}
index_issues = []
if len(index_rows) < 3:
index_issues.append(f"三大指数仅取得 {len(index_rows)}/3 条行情")
elif index_date != trade_date or index_dates != {trade_date}:
actual_dates = "".join(sorted(value for value in index_dates if value)) or "未知"
index_issues.append(f"指数实际日期为 {actual_dates},目标交易日为 {trade_date}")
elif not index_context.get("precise"):
index_issues.append("三大指数行情未通过完整性校验")
elif intraday and not index_context.get("realtime"):
index_issues.append("盘中缺少可核验的实时指数行情")
elif not intraday and (index_context.get("realtime") or str(index_context.get("source") or "") != "tushare"):
index_issues.append("收盘或历史行情不是官方指数日线")
sector_date = str(sector.get("trade_date") or "").replace("-", "")
sector_coverage = float(sector.get("coverage") or 0)
sector_explained_count = int(
sector.get("explained_count")
if sector.get("explained_count") is not None
else sector.get("quote_count") or 0
)
sector_explained_coverage = float(
sector.get("explained_coverage")
if sector.get("explained_coverage") is not None
else sector_coverage
)
sector_coverage_issue = _sector_coverage_issue(
int(sector.get("member_count") or 0),
int(sector.get("quote_count") or 0),
sector_explained_coverage,
sector_explained_count,
)
sector_common = []
if not sector:
sector_common.append("未取得申万二级行业归属")
elif sector.get("taxonomy") != "sw_l2":
sector_common.append("行业分类不是申万二级")
elif sector_date != trade_date:
sector_common.append("行业行情日期与目标交易日不一致")
elif intraday and not sector.get("realtime"):
sector_common.append("盘中行业行情不是申万实时行情")
elif market_mode == "historical" and sector.get("realtime"):
sector_common.append("历史行业行情不能使用实时快照")
elif closed and sector.get("realtime") and not sector.get("finalized"):
sector_common.append("收盘行业实时行情尚未形成15:00最终快照")
sector_inner = list(sector_common)
sector_outer = list(sector_common)
if not sector.get("inner_precise", sector.get("precise")):
sector_inner.append(str(sector.get("inner_error") or sector.get("error") or "行业内核数据未通过校验"))
if not sector.get("outer_precise", sector.get("precise")):
sector_outer.append(str(sector.get("outer_error") or sector.get("error") or "行业外显数据未通过校验"))
if sector and sector_coverage_issue and sector_coverage_issue not in sector_inner:
sector_inner.append(sector_coverage_issue)
if sector.get("realtime") and not sector.get("relative_turnover"):
sector_inner.append("缺少行业相对全市场换手活跃度")
stock_date = str(stock.get("trade_date") or "").replace("-", "")
stock_common = []
if not stock.get("code"):
stock_common.append("尚未载入有效个股")
elif stock_date != trade_date:
stock_common.append(f"个股实际日期为 {stock_date or '未知'},目标交易日为 {trade_date}")
elif not stock.get("precise"):
stock_common.append("个股行情未通过完整性校验")
elif intraday and not stock.get("realtime"):
stock_common.append("盘中个股行情不是实时行情")
elif not intraday and (stock.get("realtime") or str(stock.get("data_source") or "") != "tushare"):
stock_common.append("收盘或历史个股行情不是官方日线")
stock_inner = list(stock_common)
if intraday and stock.get("turnover_source") in {None, "", "unavailable"}:
stock_inner.append("缺少可核验的实时换手率")
if intraday and stock.get("activity_source") in {None, "", "unavailable"}:
stock_inner.append("缺少同时间进度量能基准")
overview = dashboard.get("overview") or {}
market_key_map = {
"market_sentiment_score": "sentiment_score", "market_seal_rate": "seal_rate",
"market_amount_billion": "amount_billion", "market_recent_average_amount_billion": "recent_average_amount_billion",
"market_up_count": "up_count", "market_down_count": "down_count",
"market_limit_up_count": "limit_up_count", "market_limit_down_count": "limit_down_count",
}
market_issues = []
for manual_key, source_key in market_key_map.items():
if source_key == "recent_average_amount_billion":
history_values = [item.get("amount_billion") for item in recent_history[:-1] if item.get("amount_billion") is not None]
if source_key not in overview and not history_values:
market_issues.append(f"缺少{schema[manual_key]['label']}")
elif source_key not in overview or overview.get(source_key) is None:
market_issues.append(f"缺少{schema[manual_key]['label']}")
automatic_issues = {
1: stock_inner, 2: stock_common, 3: sector_inner,
4: sector_outer, 5: market_issues, 6: index_issues,
}
limits = list(dashboard.get("limits") or [])
scores = _market_line_scores(dashboard, recent_history, index_context, sector, stock, limits)
value_map: dict[str, Any] = {
"stock_amount_percentile": stock.get("amount_percentile"),
"stock_turnover_rate": stock.get("turnover_rate"),
"stock_turnover_relative": stock.get("turnover_relative"),
"stock_volume_activity_ratio": stock.get("volume_activity_ratio"),
"stock_seal_amount_million": stock.get("seal_amount_million"),
"stock_open_times": stock.get("open_times"),
"stock_change": stock.get("change"), "stock_streak": stock.get("streak"),
"stock_status": stock.get("status"), "sector_name": sector.get("name"),
"sector_up_count": sector.get("up_count"), "sector_down_count": sector.get("down_count"),
"sector_coverage": sector.get("coverage"), "sector_relative_turnover": sector.get("relative_turnover"),
"sector_member_equal_change": sector.get("member_equal_change"),
"sector_change": sector.get("change"), "sector_leading_pct": sector.get("leading_pct"),
"market_sentiment_score": overview.get("sentiment_score"), "market_seal_rate": overview.get("seal_rate"),
"market_amount_billion": overview.get("amount_billion"),
"market_recent_average_amount_billion": overview.get("recent_average_amount_billion"),
"market_up_count": overview.get("up_count"), "market_down_count": overview.get("down_count"),
"market_limit_up_count": overview.get("limit_up_count"), "market_limit_down_count": overview.get("limit_down_count"),
}
history_values = [float(item.get("amount_billion")) for item in recent_history[:-1] if item.get("amount_billion") is not None]
if value_map["market_recent_average_amount_billion"] is None and history_values:
value_map["market_recent_average_amount_billion"] = sum(history_values) / len(history_values)
if value_map["stock_amount_percentile"] is None and not intraday:
amount = float(stock.get("amount_billion") or 0)
amounts = [float(item.get("amount_billion") or 0) for item in limits if item.get("amount_billion") is not None]
value_map["stock_amount_percentile"] = (
sum(item <= amount for item in amounts) / len(amounts) * 100 if amounts else None
)
row_by_code = {str(row.get("ts_code") or row.get("code") or ""): row for row in index_context.get("indices") or []}
value_map.update({
"index_sh_change": (row_by_code.get("000001.SH") or {}).get("pct_chg"),
"index_sz_change": (row_by_code.get("399001.SZ") or {}).get("pct_chg"),
"index_cy_change": (row_by_code.get("399006.SZ") or {}).get("pct_chg"),
})
def missing_value(key: str) -> bool:
value = value_map.get(key)
return value is None or (isinstance(value, str) and not value.strip())
invalid_fields = {
line_number: {key for key in keys if missing_value(key)}
for line_number, keys in required.items()
}
if stock_common:
invalid_fields[1].update(required[1])
invalid_fields[2].update(required[2])
else:
if intraday and stock.get("turnover_source") in {None, "", "unavailable"}:
invalid_fields[1].add("stock_turnover_relative")
if intraday and stock.get("activity_source") in {None, "", "unavailable"}:
invalid_fields[1].add("stock_volume_activity_ratio")
if sector_common:
invalid_fields[3].update(required[3])
invalid_fields[4].update(required[4])
else:
if not sector.get("inner_precise", sector.get("precise")) or sector_coverage_issue:
invalid_fields[3].update(key for key in required[3] if key != "sector_name")
if sector.get("realtime") and not sector.get("relative_turnover"):
invalid_fields[3].add("sector_relative_turnover")
# The official SW index supplies only the sector's external change. A valid
# membership name and member-stock leader remain usable when that quote fails.
if not sector.get("outer_precise", sector.get("precise")):
invalid_fields[4].add("sector_change")
if index_issues:
invalid_fields[6].update(required[6])
checks = []
for line_number in range(1, 7):
manual_keys = [key for key in required[line_number] if key in manual_data]
unresolved_fields = [
key for key in required[line_number]
if key in invalid_fields[line_number] and key not in manual_data
]
hard_missing_identity = line_number in {1, 2} and not stock.get("code")
passed = not hard_missing_identity and not unresolved_fields
status = "manual" if passed and manual_keys else "passed" if passed else "failed"
reasons = [] if passed else [
*( ["请先输入并载入股票代码或名称"] if hard_missing_identity else automatic_issues[line_number] ),
*( ["需补充:" + "".join(schema[key]["label"] for key in unresolved_fields)] if unresolved_fields else [] ),
]
score = float(scores[line_number - 1]["score"])
position, layer, formula = names[line_number]
checks.append({
"line": line_number, "position": position, "layer": layer, "formula": formula,
"status": status, "passed": passed, "reasons": reasons,
"score": round(score, 3) if passed else None,
"line_value": _score_to_line(score) if passed else None,
"evidence": scores[line_number - 1]["evidence"] if passed else [],
"fields": [
{
"key": key, "label": schema[key]["label"], "unit": schema[key].get("unit", ""),
"type": schema[key].get("type", "number"), "options": schema[key].get("options", []),
"value": value_map.get(key), "manual": key in manual_data,
"required": True, "min": schema[key].get("min"), "max": schema[key].get("max"),
"integer": bool(schema[key].get("integer")),
}
for key in required[line_number]
],
})
return checks
@@ -0,0 +1,338 @@
from __future__ import annotations
import re
from datetime import datetime, timedelta
from typing import Any
from backend.bootstrap.config import (
normalize_date,
tushare_code,
validate_stock_code,
validate_text,
)
from backend.data.providers.tushare_client import TushareError
class HeavenMarketContextMixin:
def _resolve_heaven_stock_code(self, query: str) -> str:
raw = validate_text(query, "股票代码或名称", 30, required=True)
code_match = re.fullmatch(r"(\d{6})(?:\.(?:SH|SZ|BJ))?", raw.upper())
if code_match:
return validate_stock_code(code_match.group(1))
candidates = self.database.search_stock_master(raw)
exact = [item for item in candidates if str(item.get("name") or "").casefold() == raw.casefold()]
if not exact and self.configured:
try:
rows = self._tushare_client().query(
"stock_basic",
{"name": raw, "list_status": "L"},
"ts_code,symbol,name,industry,market,list_date",
)
except TushareError:
rows = []
if rows:
self.database.upsert_stock_master(rows)
candidates = self.database.search_stock_master(raw)
exact = [
item
for item in candidates
if str(item.get("name") or "").casefold() == raw.casefold()
]
matches = exact or candidates
if len(matches) == 1:
return validate_stock_code(str(matches[0].get("code") or ""))
if len(matches) > 1:
choices = "".join(
f"{item.get('name') or '--'}{item.get('code') or '--'}"
for item in matches[:5]
)
raise ValueError(f"匹配到多只股票:{choices}。请输入六位股票代码。")
raise ValueError(f"未找到股票“{raw}”,请检查名称或输入六位股票代码。")
def _heaven_stock_context(
self,
stock_code: str,
trade_date: str,
dashboard: dict[str, Any],
market_mode: str,
) -> dict[str, Any]:
"""Return the only stock contract accepted by heaven trend."""
pool_row = next(
(
dict(row) for key in ("limits", "broken", "down_limits")
for row in dashboard.get(key) or []
if str(row.get("code") or "") == stock_code
),
{},
)
if market_mode == "intraday":
if self.configured:
try:
quote = self._tushare_client().realtime_stock_quote(
tushare_code(stock_code),
trade_date,
)
return {
**quote,
"status": pool_row.get("status") or "普通",
"seal_amount_million": pool_row.get("seal_amount_million") or 0,
"open_times": pool_row.get("open_times") or 0,
"streak": pool_row.get("streak") or 0,
"precise": True,
}
except TushareError:
pass
if pool_row:
return {
**pool_row,
"data_source": "dashboard_rt" if dashboard.get("meta", {}).get("realtime") else "dashboard",
"trade_date": trade_date,
"realtime": bool(dashboard.get("meta", {}).get("realtime")),
"precise": False,
}
return {
"code": stock_code,
"name": "--",
"sector": "其他",
"trade_date": trade_date,
"realtime": False,
"precise": False,
}
detail = self.get_stock_detail(stock_code, trade_date, force=True)
detail_meta = detail.get("meta") or {}
stock = detail.get("stock") or {}
resolved_date = normalize_date(str(detail_meta.get("trade_date") or trade_date))
source = str(detail_meta.get("source") or "")
return {
"code": stock_code,
"name": stock.get("name") or pool_row.get("name") or "--",
"sector": stock.get("industry") or pool_row.get("sector") or "其他",
"status": pool_row.get("status") or "普通",
"change": stock.get("change") or 0,
"turnover_rate": stock.get("turnover_rate") or 0,
"amount_billion": stock.get("amount_billion") or 0,
"seal_amount_million": pool_row.get("seal_amount_million") or 0,
"open_times": pool_row.get("open_times") or 0,
"streak": pool_row.get("streak") or 0,
"data_source": source,
"trade_date": resolved_date,
"realtime": False,
"precise": source == "tushare" and resolved_date == trade_date,
}
def _heaven_index_context(
self,
trade_date: str,
dashboard: dict[str, Any],
market_mode: str = "historical",
) -> dict[str, Any]:
cached = self.database.get_data_snapshot("heaven_indices", trade_date)
cached_valid = False
if cached:
cached_rows = list(cached.get("indices") or [])
cached_dates = {
str(row.get("trade_date") or "").replace("-", "")
for row in cached_rows
}
cached_valid = (
len(cached_rows) == 3
and cached_dates == {trade_date}
and bool(cached.get("precise"))
and not cached.get("realtime")
and str(cached.get("source") or "") == "tushare"
and int(cached.get("schema_version") or 0) >= 3
)
if market_mode != "intraday" and cached_valid:
return cached
if not self.configured:
error = "Tushare Token 未配置"
else:
try:
client = self._tushare_client()
if market_mode == "intraday":
payload = self._aggregate_index_context(trade_date)
payload["schema_version"] = 3
return payload
payload = client.market_indices(trade_date)
payload["schema_version"] = 3
if market_mode == "closed":
payload["finalized"] = True
self.database.save_data_snapshot(
"heaven_indices",
trade_date,
str(payload.get("source") or "tushare"),
payload,
)
return payload
except Exception as exc:
error = str(exc)
overview = dashboard.get("overview") or {}
up_count = float(overview.get("up_count") or 0)
down_count = float(overview.get("down_count") or 0)
breadth = (up_count - down_count) / max(up_count + down_count, 1)
return {
"source": "market_breadth_proxy",
"trade_date": trade_date,
"realtime": False,
"precise": False,
"schema_version": 3,
"notice": f"指数数据不可用,当前以市场宽度代理:{error}",
"indices": [],
"aggregate": {
"average_pct_chg": round(breadth * 2.5, 3),
"average_return_5d": 0,
"average_return_20d": 0,
},
}
def _aggregate_index_context(
self,
trade_date: str,
tushare_error: str = "",
) -> dict[str, Any]:
quotes = self.realtime_aggregator.tencent_indices()
epochs = [int(item.get("quote_time_epoch") or 0) for item in quotes]
quote_dates = {
datetime.fromtimestamp(epoch).astimezone().strftime("%Y%m%d")
for epoch in epochs if epoch
}
if len(quotes) != 3 or quote_dates != {trade_date}:
raise ValueError("腾讯三大指数日期与目标交易日不一致")
now = datetime.now().astimezone()
max_skew = 120 if now.hour >= 15 else 15
if max(epochs) - min(epochs) > max_skew:
raise ValueError(f"腾讯三大指数时间差超过{max_skew}")
code_map = {
"000001": "000001.SH",
"399001": "399001.SZ",
"399006": "399006.SZ",
}
client = self._tushare_client()
indices = []
start_date = (
datetime.strptime(trade_date, "%Y%m%d") - timedelta(days=20)
).strftime("%Y%m%d")
for quote in quotes:
ts_code = code_map[str(quote.get("code") or "")]
history = client.query(
"index_daily",
{"ts_code": ts_code, "start_date": start_date, "end_date": trade_date},
"ts_code,trade_date,close,pct_chg",
)
history.sort(key=lambda item: str(item.get("trade_date") or ""))
completed_closes = [
float(item.get("close") or 0)
for item in history
if str(item.get("trade_date") or "") < trade_date
and float(item.get("close") or 0) > 0
]
close_5d = (
completed_closes[-5]
if len(completed_closes) >= 5
else completed_closes[0] if completed_closes else 0
)
close = float(quote.get("price") or 0)
indices.append(
{
"ts_code": ts_code,
"name": quote.get("name") or ts_code,
"trade_date": trade_date,
"close": close,
"pct_chg": round(float(quote.get("change") or 0), 3),
"return_5d": round((close / close_5d - 1) * 100, 3) if close_5d else 0,
"return_20d": 0,
"amount_billion": float(quote.get("amount_billion") or 0),
"quote_time": quote.get("quote_time") or "",
}
)
return {
"trade_date": trade_date,
"source": "+".join(
sorted({str(item.get("source") or "web_quote") for item in quotes})
+ ["tushare_index_daily"]
),
"realtime": True,
"precise": True,
"indices": indices,
"aggregate": {
"average_pct_chg": round(
sum(item["pct_chg"] for item in indices) / len(indices), 3
),
"average_return_5d": round(
sum(item["return_5d"] for item in indices) / len(indices), 3
),
"average_return_20d": 0,
},
"quote_time_skew_seconds": max(epochs) - min(epochs),
"notice": (
"指数实时行情来自腾讯行情,5日趋势来自Tushare历史指数。"
+ (f" Tushare实时指数未使用:{tushare_error}" if tushare_error else "")
),
}
def _heaven_sector_context(
self,
identifier: str,
trade_date: str,
market_mode: str = "historical",
) -> dict[str, Any] | None:
"""Return the Shenwan L2 sector context for heaven trend.
观势行业层只使用申万二级行业。外显盘中使用 rt_sw_k、历史使用
sw_daily;内核独立使用目标日期成分股行情聚合。收盘过渡期在
sw_daily 入库前接受同日15:00后的 rt_sw_k 收盘快照。
"""
cache_key = f"{trade_date}:{identifier.strip().lower()}"
cached = self.database.get_data_snapshot("heaven_sector", cache_key)
cached_date = str((cached or {}).get("trade_date") or "").replace("-", "")
cached_valid = bool(
cached
and cached_date == trade_date
and cached.get("taxonomy") == "sw_l2"
and cached.get("inner_precise", cached.get("precise"))
and cached.get("outer_precise", cached.get("precise"))
and not cached.get("realtime")
and int(cached.get("schema_version") or 0) >= 6
)
if market_mode != "intraday" and cached_valid:
return cached
if not self.configured:
return None
try:
payload = self._tushare_client().sw_sector_snapshot(
tushare_code(identifier),
trade_date,
realtime_expected=market_mode == "intraday",
allow_realtime_close=market_mode == "closed",
)
except TushareError as exc:
if cached_valid:
return cached
return {
"name": "",
"code": "",
"taxonomy": "sw_l2",
"source": "tushare",
"trade_date": trade_date,
"realtime": market_mode == "intraday",
"precise": False,
"inner_precise": False,
"outer_precise": False,
"coverage": 0,
"member_count": 0,
"quote_count": 0,
"error": f"申万二级行业数据获取失败:{exc}",
}
if not payload.get("realtime") and payload.get("precise"):
self.database.save_data_snapshot(
"heaven_sector",
cache_key,
str(payload.get("source") or "tushare"),
payload,
)
return payload
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from __future__ import annotations
import json
import secrets
from datetime import date
from typing import Any
from backend.bootstrap.config import normalize_date
from backend.features.heaven.agent import HeavenAgentError, interpret_heaven
from backend.features.heaven.engine import (
build_five_phase_field,
hexagram_from_lines,
)
from backend.features.market import MarketServiceMixin
class HeavenReadingMixin:
def heaven_personal(self, payload: dict[str, Any]) -> dict[str, Any]:
trade_date = normalize_date(str(payload.get("trade_date") or date.today().isoformat()))
field = build_five_phase_field(
trade_date,
self.database.list_sector_phase_overrides(),
)
personal = self.account_personal_field(trade_date, field, public=True)
if not personal:
raise ValueError("请先在账号设置中保存个人命理资料。")
return personal
def heaven_hexagram(self, raw_lines: Any) -> dict[str, Any]:
if not isinstance(raw_lines, list):
raise ValueError("六爻起卦结果格式不正确。")
try:
lines = [int(value) for value in raw_lines]
except (TypeError, ValueError) as exc:
raise ValueError("六爻必须由六、七、八、九组成。") from exc
return hexagram_from_lines(lines)
def heaven_readings(
self, mode: str, context_date: str = "", limit: int = 100
) -> dict[str, Any]:
mode = str(mode or "").strip()
if mode not in {"trend", "fortune", "heart"}:
raise ValueError("解读记录类型不正确。")
normalized_date = normalize_date(context_date) if context_date else ""
return {
"mode": mode,
"items": self.database.list_heaven_readings(
self.current_user_id, mode, normalized_date, limit
),
}
@staticmethod
def _heaven_reading_identity(
mode: str, context_date: str, context: dict[str, Any]
) -> tuple[str, str]:
display_date = MarketServiceMixin._display_compact_date(context_date)
if mode == "trend":
stock = (context.get("selected_focus") or {}).get("stock") or {}
code = str(stock.get("code") or "").strip()
name = str(stock.get("name") or "").strip()
hexagram = context.get("hexagram") or {}
transformed = hexagram.get("transformed") or {}
subject = " ".join(item for item in (code, name) if item) or "观势"
detail = f"{display_date} · {hexagram.get('name') or '--'}{transformed.get('name') or '--'}"
return subject, detail
if mode == "fortune":
field = context.get("five_phase_field") or {}
pillars = field.get("pillars") or {}
dominant = (field.get("balance") or [{}])[0]
subject = f"{display_date} 观气"
detail = (
f"{pillars.get('year') or '--'}年 · {pillars.get('month') or '--'}月 · "
f"{pillars.get('day') or '--'}日 · {dominant.get('element') or '--'}气偏显"
)
return subject, detail
hexagram = context.get("hexagram") or {}
transformed = hexagram.get("transformed") or {}
return (
f"{display_date} 观心",
f"{hexagram.get('name') or '--'}{transformed.get('name') or '--'}",
)
def heaven_interpret(self, payload: dict[str, Any]) -> dict[str, Any]:
mode = str(payload.get("mode") or "").strip()
if mode not in {"trend", "fortune", "heart"}:
raise ValueError("问天解读模式不正确。")
trade_date = normalize_date(str(payload.get("trade_date") or date.today().isoformat()))
if mode == "fortune":
existing = self.database.latest_heaven_reading(
self.current_user_id, "fortune", trade_date
)
if self._legacy_truncated_heaven_reading(existing):
self.database.delete_heaven_reading(
self.current_user_id, int(existing["id"])
)
existing = None
if existing:
return {
"answer": existing["answer"],
"mode": mode,
"compiler": "stored",
"notice": "",
"reading": existing,
"reused": True,
}
if mode in {"trend", "fortune"}:
setup = self.heaven_setup(
trade_date,
str(payload.get("sector") or ""),
str(payload.get("stock_code") or ""),
payload.get("manual_data"),
)
if mode == "trend":
chart = setup["chart"]
if not chart.get("available"):
issues = "".join((chart.get("quality") or {}).get("issues") or [])
raise ValueError(f"观势数据未通过六爻校验,暂不解势:{issues}")
hexagram_context = json.loads(json.dumps(chart["hexagram"], ensure_ascii=False))
for line in hexagram_context.get("lines", []):
line.pop("evidence", None)
line.pop("score", None)
line.pop("talent", None)
line.pop("layer", None)
line.pop("role", None)
if not line.get("moving"):
line.pop("text", None)
line.pop("image", None)
line.pop("line_name", None)
context = {
"data_trade_date": setup["trade_date"],
"selected_focus": {
"sector": chart.get("sector") or "",
"stock": chart.get("stock") or {},
},
"hexagram": hexagram_context,
"movement": chart.get("movement") or {},
}
else:
personal_profile = self.account_personal_field(
setup["calendar_date"],
setup["field"],
public=False,
)
fortune_field = json.loads(json.dumps(setup["field"], ensure_ascii=False))
catalog = fortune_field.pop("sector_catalog", [])
dominant_elements = {
item.get("element") for item in fortune_field.get("balance", [])[:2]
}
fortune_field["industry_affinity"] = [
{
"element": group.get("element"),
"examples": [
item.get("name")
for item in group.get("industries", [])[:8]
if item.get("name")
],
}
for group in catalog
if group.get("element") in dominant_elements
]
context = {
"calendar_date": setup["calendar_date"],
"five_phase_field": fortune_field,
"personal_profile": personal_profile,
}
context_date = setup["calendar_date"]
if mode == "trend":
context_date = setup["trade_date"]
else:
context = {
"hexagram": self.heaven_hexagram(payload.get("lines")),
"ritual": "用户已完成30秒静心、六次三枚铜钱起卦,并在心中察看第一念。问题未输入。",
}
context_date = trade_date
result, compiler = self._call_heaven_agent(mode, context)
subject, subject_detail = self._heaven_reading_identity(
mode, context_date, context
)
dedupe_key = (
f"fortune:{context_date}"
if mode == "fortune"
else f"{mode}:{context_date}:{secrets.token_urlsafe(12)}"
)
reading = self.database.save_heaven_reading(
self.current_user_id,
mode,
context_date,
subject,
subject_detail,
str(result.get("answer") or ""),
context,
dedupe_key,
)
return {
**result,
"mode": mode,
"compiler": compiler,
"notice": "智能解读已自动切换可用服务。" if compiler == "fallback" else "",
"reading": reading,
"reused": False,
}
@staticmethod
def _legacy_truncated_heaven_reading(reading: dict[str, Any] | None) -> bool:
return bool(reading and str(reading.get("answer") or "").rstrip().endswith("……"))
def _call_heaven_agent(self, mode: str, context: dict[str, Any]) -> tuple[dict[str, Any], str]:
result = self.llm_gateway.call(
f"heaven_{mode}",
f"heaven-{mode}-v1",
lambda profile: interpret_heaven(
mode,
context,
profile.api_key,
profile.base_url,
profile.model,
),
(HeavenAgentError,),
)
return result.value, result.role
+79
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from __future__ import annotations
import json
import re
from datetime import date
from http import HTTPStatus
from urllib.parse import parse_qs, unquote
from backend.bootstrap.config import validate_text
class HeavenRoutesMixin:
def _handle_heaven_get(self, parsed) -> bool:
if parsed.path == "/api/heaven/readings":
query = parse_qs(parsed.query)
try:
self.send_json(
self.application_service.heaven_readings(
query.get("mode", [""])[0],
query.get("context_date", [""])[0],
int(query.get("limit", ["100"])[0]),
)
)
except (TypeError, ValueError) as exc:
self.send_json({"error": str(exc)}, HTTPStatus.BAD_REQUEST)
return True
if parsed.path == "/api/heaven/setup":
query = parse_qs(parsed.query)
trade_date = query.get("trade_date", [date.today().isoformat()])[0]
sector_name = query.get("sector", [""])[0]
stock_code = query.get("stock_code", [""])[0]
manual_data = None
manual_text = query.get("manual_data", [""])[0]
if manual_text:
try:
manual_data = json.loads(manual_text)
except json.JSONDecodeError:
self.send_json({"error": "六爻补录数据格式不正确。"}, HTTPStatus.BAD_REQUEST)
return True
try:
self.send_json(
self.application_service.heaven_setup(
trade_date,
sector_name,
stock_code,
manual_data,
)
)
except ValueError as exc:
self.send_json({"error": str(exc)}, HTTPStatus.BAD_REQUEST)
return True
return False
def _handle_heaven_delete(self, parsed) -> bool:
heaven_reading_match = re.fullmatch(r"/api/heaven/readings/(\d+)", parsed.path)
if heaven_reading_match:
deleted = self.application_service.database.delete_heaven_reading(
self.application_service.current_user_id, int(heaven_reading_match.group(1))
)
self.send_json({"ok": True, "deleted": deleted})
return True
sector_phase_match = re.fullmatch(r"/api/heaven/sector-phases/(.+)", parsed.path)
if sector_phase_match:
name = unquote(sector_phase_match.group(1)).strip()
deleted = self.application_service.database.delete_sector_phase_override(name)
self.send_json({"ok": True, "deleted": deleted})
return True
return False
def save_sector_phase_override(self) -> None:
try:
body = self.read_json_body()
name = validate_text(body.get("name"), "行业或题材名称", 50, required=True)
element = str(body.get("element") or "").strip()
if element not in {"", "", "", "", ""}:
raise ValueError("五行归类必须是木、火、土、金或水。")
self.application_service.database.save_sector_phase_override(name, element)
self.send_json({"ok": True})
except (ValueError, json.JSONDecodeError) as exc:
self.send_json({"error": str(exc)}, HTTPStatus.BAD_REQUEST)
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from __future__ import annotations
from datetime import datetime
from typing import Any
from backend.bootstrap.config import normalize_date
from backend.data.providers.tushare_client import _sector_coverage_issue
from backend.features.heaven.engine import build_five_phase_field, build_market_hexagram
class HeavenTrendMixin:
def heaven_setup(
self,
trade_date: str,
sector_name: str = "",
stock_code: str = "",
manual_data: dict[str, Any] | None = None,
) -> dict[str, Any]:
normalized_date = normalize_date(trade_date)
dashboard = self.get_dashboard(normalized_date)
data_date = normalize_date(str(dashboard.get("meta", {}).get("trade_date") or normalized_date))
recent_history = self.database.snapshot_summaries(data_date, 10)
market_mode = self._heaven_market_mode(data_date, dashboard)
manual_data = self._validate_heaven_manual_data(manual_data, market_mode)
index_context = self._heaven_index_context(data_date, dashboard, market_mode)
external_stock = None
normalized_stock_code = ""
if stock_code.strip():
normalized_stock_code = self._resolve_heaven_stock_code(stock_code)
external_stock = self._heaven_stock_context(
normalized_stock_code,
data_date,
dashboard,
market_mode,
)
external_sector = None
if normalized_stock_code and self.configured:
external_sector = self._heaven_sector_context(
normalized_stock_code,
data_date,
market_mode,
)
if external_sector and external_stock:
external_stock["sector"] = external_sector.get("name") or external_stock.get("sector")
dashboard, index_context, external_sector, external_stock = self._apply_heaven_manual_data(
dashboard,
index_context,
external_sector,
external_stock,
manual_data,
market_mode,
data_date,
normalized_stock_code,
)
if external_sector and external_stock:
external_stock["sector"] = external_sector.get("name") or external_stock.get("sector")
sector_input = str((external_sector or {}).get("name") or sector_name.strip())
if not normalized_stock_code:
data_checks = []
chart = {
"available": False,
"selection_required": True,
"data_trade_date": data_date,
"sector": "",
"sector_code": "",
"sector_taxonomy": "",
"stock": {"code": "", "name": "", "status": ""},
"quality": {
"status": "awaiting_selection",
"issues": [],
"principle": "",
"sources": [],
},
"index_context": index_context,
}
else:
data_checks = self._heaven_line_checks(
data_date,
dashboard,
recent_history,
index_context,
external_sector or {},
external_stock or {},
market_mode,
manual_data,
)
quality_issues = [
f"{check['position']}·{check['layer']}{''.join(check['reasons'])}"
for check in data_checks
if not check["passed"]
]
if quality_issues:
chart = {
"available": False,
"selection_required": False,
"data_trade_date": data_date,
"sector": str((external_sector or {}).get("name") or sector_input or "--"),
"sector_code": str((external_sector or {}).get("code") or ""),
"sector_taxonomy": str((external_sector or {}).get("taxonomy") or ""),
"stock": {
"code": normalized_stock_code,
"name": str((external_stock or {}).get("name") or "--"),
"status": str((external_stock or {}).get("status") or ""),
},
"quality": {
"status": "blocked",
"issues": quality_issues,
"principle": "六爻任一层缺少同日、同口径的有效数据,本系统不成卦。",
"sources": self._heaven_trend_sources(
data_date, index_context, external_sector, external_stock
),
},
"index_context": index_context,
}
else:
chart = build_market_hexagram(
dashboard,
recent_history,
index_context,
sector_input,
normalized_stock_code,
external_stock,
external_sector,
)
chart["available"] = True
chart["selection_required"] = False
manual_active = any(check["status"] == "manual" for check in data_checks)
chart["quality"] = {
"status": "manual" if manual_active else "verified",
"issues": [],
"principle": (
"自动行情与用户补充数据均已通过同一套量化公式校验。"
if manual_active
else "指数、板块、个股均已通过同日同口径校验。"
),
"sources": [
*self._heaven_trend_sources(
data_date, index_context, external_sector, external_stock
),
*([{
"lines": "补录爻位",
"layer": "用户补充",
"realtime": market_mode == "intraday",
"detail": str(manual_data.get("note") or "量化数据经原公式重新计算"),
}] if manual_active else []),
],
}
chart["data_checks"] = data_checks
chart["manual_data"] = manual_data
sector_phase_overrides = self.database.list_sector_phase_overrides()
field = build_five_phase_field(
normalized_date,
sector_phase_overrides,
)
personal_profile = self.account_personal_field(
normalized_date,
field,
public=True,
)
daily_fortune_reading = self.database.latest_heaven_reading(
self.current_user_id, "fortune", normalized_date
)
if self._legacy_truncated_heaven_reading(daily_fortune_reading):
daily_fortune_reading = None
return {
"trade_date": data_date,
"calendar_date": normalized_date,
"market_mode": market_mode,
"chart": chart,
"field": field,
"personal_profile": personal_profile,
"daily_fortune_reading": daily_fortune_reading,
"sector_phase_overrides": [
{"name": name, "element": element}
for name, element in sector_phase_overrides.items()
],
"llm": {
"configured": self.llm_configured,
"model": self.llm_primary_model if self.llm_configured else "",
"fallback_configured": self.llm_fallback_configured,
"fallback_model": self.llm_fallback_model if self.llm_fallback_configured else "",
},
}
@staticmethod
def _heaven_market_mode(
trade_date: str,
dashboard: dict[str, Any],
now: datetime | None = None,
) -> str:
"""区分盘中、今日收盘和历史,避免把 rt_k 数据来源误当成交易状态。"""
now = now or datetime.now().astimezone()
if trade_date != now.strftime("%Y%m%d"):
return "historical"
meta = dashboard.get("meta") or {}
status = str(meta.get("market_status") or "").lower()
local_time = now.time().replace(tzinfo=None)
if status == "closed" or local_time > datetime.strptime("15:05", "%H:%M").time():
return "closed"
if status in {"trading", "auction", "pre_open"} or (
bool(meta.get("realtime"))
and local_time >= datetime.strptime("09:15", "%H:%M").time()
):
return "intraday"
return "historical"
@staticmethod
def _heaven_trend_sources(
trade_date: str,
index_context: dict[str, Any],
sector: dict[str, Any] | None,
stock: dict[str, Any] | None,
) -> list[dict[str, Any]]:
sector = sector or {}
stock = stock or {}
return [
{
"lines": "五爻、上爻",
"layer": "指数",
"source": index_context.get("source") or "unavailable",
"trade_date": index_context.get("trade_date") or "",
"realtime": bool(index_context.get("realtime")),
"detail": f"三大指数 {len(index_context.get('indices') or [])}/3",
},
{
"lines": "三爻、四爻",
"layer": "行业",
"source": sector.get("source") or "unavailable",
"trade_date": sector.get("trade_date") or "",
"realtime": bool(sector.get("realtime")),
"detail": (
f"申万二级 {sector.get('name') or '--'} {sector.get('code') or '--'} "
f"成分覆盖 {int(sector.get('quote_count') or 0)}/{int(sector.get('member_count') or 0)}"
),
},
{
"lines": "初爻、二爻",
"layer": "个股",
"source": stock.get("data_source") or "unavailable",
"trade_date": stock.get("trade_date") or trade_date,
"realtime": bool(stock.get("realtime")),
"detail": (
f"{stock.get('name') or '--'};换手基准 "
f"{stock.get('capital_trade_date') or '--'}"
),
},
]
@staticmethod
def _heaven_trend_quality_issues(
trade_date: str,
dashboard: dict[str, Any],
index_context: dict[str, Any],
sector: dict[str, Any] | None,
stock: dict[str, Any] | None,
market_mode: str = "historical",
) -> list[str]:
issues: list[str] = []
intraday = market_mode == "intraday"
closed = market_mode == "closed"
if intraday:
meta = dashboard.get("meta") or {}
market_status = str(meta.get("market_status") or "")
now = datetime.now().astimezone()
try:
updated_at = datetime.fromisoformat(str(meta.get("updated_at") or ""))
if updated_at.tzinfo is None:
updated_at = updated_at.replace(tzinfo=now.tzinfo)
snapshot_age = (now - updated_at.astimezone(now.tzinfo)).total_seconds()
except ValueError:
snapshot_age = float("inf")
if market_status in {"trading", "auction", "pre_open"} and snapshot_age > 120:
issues.append("主行情快照超过2分钟,请点击顶部刷新")
# 收盘后不再用 dashboard.market_status 作为阻断条件。盘后同步可能将
# rt_k 快照替换成同日盘后日线而不带该字段;六爻数据本身的日期、
# 完整性和来源校验已足以判断是否可以成卦。
index_date = str(index_context.get("trade_date") or "").replace("-", "")
index_rows = list(index_context.get("indices") or [])
index_row_dates = {
str(row.get("trade_date") or "").replace("-", "") for row in index_rows
}
if not index_context.get("precise") or len(index_rows) < 3:
issues.append("指数层缺少三大指数的有效行情")
elif index_date != trade_date or index_row_dates != {trade_date}:
issues.append("指数行情与目标交易日不一致")
elif intraday and not index_context.get("realtime"):
issues.append("盘中指数层缺少可核验的实时行情")
elif not intraday and (
index_context.get("realtime")
or str(index_context.get("source") or "") != "tushare"
):
issues.append("历史/收盘指数层必须使用 Tushare 官方指数日线")
sector = sector or {}
sector_date = str(sector.get("trade_date") or "").replace("-", "")
sector_coverage = float(sector.get("coverage") or 0)
sector_explained_count = int(
sector.get("explained_count")
if sector.get("explained_count") is not None
else sector.get("quote_count") or 0
)
sector_explained_coverage = float(
sector.get("explained_coverage")
if sector.get("explained_coverage") is not None
else sector_coverage
)
sector_coverage_issue = _sector_coverage_issue(
int(sector.get("member_count") or 0),
int(sector.get("quote_count") or 0),
sector_explained_coverage,
sector_explained_count,
)
if not sector:
issues.append("行业层缺少申万二级行业归属")
elif sector.get("taxonomy") != "sw_l2":
issues.append("行业层必须使用申万二级行业分类")
elif sector_date != trade_date:
issues.append("行业行情与目标交易日不一致")
elif intraday and not sector.get("realtime"):
issues.append("盘中行业层缺少申万实时行情")
elif market_mode == "historical" and sector.get("realtime"):
issues.append("历史行业层不能使用实时快照")
elif closed and sector.get("realtime") and not sector.get("finalized"):
issues.append("收盘行业层缺少15:00最终快照")
if not sector.get("inner_precise", sector.get("precise")):
issues.append("行业内核缺少可核验的成分行情")
if not sector.get("outer_precise", sector.get("precise")):
issues.append("行业外显缺少申万官方行情")
if sector and sector_coverage_issue:
issues.append(sector_coverage_issue)
if sector.get("realtime") and not sector.get("relative_turnover"):
issues.append("行业内核缺少相对全市场换手活跃度")
stock = stock or {}
stock_date = str(stock.get("trade_date") or "").replace("-", "")
if not stock or not stock.get("code"):
issues.append("个股层尚未载入有效标的")
elif not stock.get("precise"):
issues.append("个股层缺少可核验的行情数据")
elif stock_date != trade_date:
issues.append("个股行情与目标交易日不一致")
elif intraday and not stock.get("realtime"):
issues.append("盘中个股层不是 rt_k 实时行情")
elif not intraday and (
stock.get("realtime")
or str(stock.get("data_source") or "") != "tushare"
):
issues.append("历史/收盘个股层必须使用 Tushare 官方日线")
if intraday and stock and not stock.get("turnover_source"):
issues.append("个股内核缺少可核验的实时换手率")
elif intraday and stock.get("turnover_source") == "unavailable":
issues.append("个股内核缺少流通股本,无法计算实时换手率")
if intraday and stock.get("activity_source") == "unavailable":
issues.append("个股内核缺少近5日量能基准")
elif intraday and not stock.get("activity_source"):
issues.append("个股内核缺少同时间进度量能")
return issues