feat(sector_radar): enhance sector radar functionality with active moneyflow and detailed metrics

- Introduced ActiveMoneyflowSource to fetch optional active-order flow, enhancing the sector radar's data capabilities.
- Updated StockFactRecord and DailyAggregateRecord to include pct_change and active_buy_net_amount_yuan for improved financial insights.
- Modified the build process to incorporate active moneyflow data without invalidating main rankings on failure.
- Enhanced the HTTP API to return detailed sector history and metrics, including pct_change and active buy metrics for members.
- Updated tests to validate the new functionality and ensure data integrity across various scenarios.

.trellis/tasks/09-06-capital-radar-daily-detail/check.jsonl

@@ -0,0 +1,6 @@
+{"file": ".trellis/spec/backend/market-data-sync.md", "reason": "Tushare 落库及同步契约"}
+{"file": ".trellis/spec/backend/tushare-listed-stock-universe.md", "reason": "当前上市母集约束"}
+{"file": ".trellis/spec/backend/http-api-contracts.md", "reason": "详情与排名API"}
+{"file": ".trellis/spec/frontend/component-guidelines.md", "reason": "弹窗与榜单组件"}
+{"file": ".trellis/spec/frontend/hook-guidelines.md", "reason": "按日期的查询状态"}
+{"file": ".trellis/tasks/09-06-capital-radar-daily-detail/design.md", "reason": "本次数据及交互设计"}

.trellis/tasks/09-06-capital-radar-daily-detail/design.md

@@ -0,0 +1,21 @@
+# 资金雷达单日详情设计
+
+## 数据边界
+继续使用 sector_radar bounded context。Tushare 原始响应先进入现有 snapshot 持久化链路，再扩展事实与查询投影；浏览器只访问同源 API，不直接请求 Tushare 或参考站点。扩展板块日事实保存 pct_change 与领涨标识，股票事实保存 daily.pct_chg 和独立 active_buy_net_amount_yuan。新字段可空，旧发布保持可读。moneyflow 作为详情可选来源，不将其失败当成主力净额为零；与原始 snapshot、发布日期和输入版本关联。
+
+## 查询契约
+rankings 在原字段上增加 pct_change、daily_net_amount_yuan、daily_ratio 和对应侧的 30 日在榜次数；领域 percentile/coverage 保留，仅移除两种视角的展示列。避免逐板块查询历史，按日期和类型批量加载历史排名，按每日池的 TOP/BOTTOM 阈值计数。
+
+新增板块 history 与 detail 读取接口，键包含 sector_type、sector_code、trade_date；返回解析后的 publication 标识和实际日期。history 含日期、三指标排名、当日池规模/百分位和缺失状态，严格截至目标日，最多 30 个交易日；同日选最新成功发布，历史版本不兼容时不混用。详情包含当日指标摘要、成员三种强弱数据、成员列表和相似板块。共享历史读取实现，避免重复计算。
+
+## 指标
+沿用现有主力净额/成交额流入率及波段策略。板块涨跌幅优先使用 dc_index 源字段；成员 daily.pct_chg 独立于资金流是否缺失。主买净额来自 moneyflow.net_mf_amount，须核对官方单位后转为元，与主力 net_amount 分开。重合度为交集数量/并集数量，使用同日可确认的当前上市母集成员；未知成员不参与，空并集不计算。同分稳定按代码排列。
+
+## 前端
+将两种单日榜列配置与其他视角隔离；拆分历史格子和详情弹窗组件，沿用项目 UI primitive 和 ECharts。详情请求按需触发，query key 包含类型/代码/目标日，切换日期时不显示前一天的详情。格子按日期从近到远，曲线按时间从早到晚且排名 1 在上方，缺失处断线。导出及复制仅使用 API 返回成员，生成本地 CSV/文本，CSV 对不可信字段进行转义与公式注入防护。
+
+## 兼容与回滚
+采用增量 nullable 数据迁移，不删除原字段。旧发布缺详情时显式显示暂无数据；可通过重新构建目标日补齐，不在读取路径触发网络取数。新增来源失败保留最近有效发布并体现详情缺失。真实自测使用隔离的本地数据库或受控测试批次，不覆盖完整发布。若迁移/验证失败，停止新构建并保留原始快照，回退代码前确认旧代码可读取新增 nullable 列。
+
+## 实施前核验
+确认 moneyflow 官方单位、当前采集权限和现有 source 失败策略；确定具体 migration 编号与可复用 UI primitive。原站私有算法不构成本次完成条件。真实全池历史不足仅报告覆盖，不人为补齐。

.trellis/tasks/09-06-capital-radar-daily-detail/implement.jsonl

@@ -0,0 +1,6 @@
+{"file": ".trellis/spec/backend/market-data-sync.md", "reason": "Tushare 落库及同步契约"}
+{"file": ".trellis/spec/backend/tushare-listed-stock-universe.md", "reason": "当前上市母集约束"}
+{"file": ".trellis/spec/backend/http-api-contracts.md", "reason": "详情与排名API"}
+{"file": ".trellis/spec/frontend/component-guidelines.md", "reason": "弹窗与榜单组件"}
+{"file": ".trellis/spec/frontend/hook-guidelines.md", "reason": "按日期的查询状态"}
+{"file": ".trellis/tasks/09-06-capital-radar-daily-detail/design.md", "reason": "本次数据及交互设计"}

.trellis/tasks/09-06-capital-radar-daily-detail/implement.md

@@ -0,0 +1,17 @@
+# 实施与验证计划
+
+- [x] 用户审核当前规划后，加载 Phase 1.3/1.4，校验上下文清单并进入 in_progress。
+- [x] 读取受影响层规范和确切修改代码，确认 Tushare moneyflow 字段单位、权限及本地隔离数据库方案。
+- [x] 扩展 source、事实和 PostgreSQL migration，保存板块涨跌幅与成分行情/主买净额，保持旧发布可读；更新 memory repository。
+- [x] 增加批量历史/详情读取和 HTTP 响应，补充单日榜附加字段、在榜次数、三指标历史、前后5名、成员及重合度。
+- [x] 调整前端 API/types/query，完成两种单日列、名称入口、在榜展开、详情弹窗与复制/导出。
+- [x] 后端测试重点：单位转换、来源缺失不归零、同日发布去重、30交易日边界、无未来数据、每天排名池变化、相似度与历史成员；运行 `cd zhixing-server && uv run pytest tests/unit/sector_radar tests/test_sector_radar_http.py`，有数据库时补集成测试 `tests/integration/test_sector_radar_repository.py`。
+- [x] 前端测试重点：视角切换列名、左右板块指标、展开收起、日期切换、详情指标切换、少量样本、关闭/焦点和导出内容；运行 `cd zhixing-web && pnpm test src/features/sector-radar`。
+- [x] 使用一个真实板块完成 Tushare 采集、落库、API核对，记录请求日期、条数、缺失及核对值，不记录密钥；不得将单板块测试发布为全市场榜单。
+- [x] 后端运行 `uv run ruff format --check .`、`uv run ruff check .`、`uv run pyright`；前端运行 `pnpm format:check`、`pnpm lint`、`pnpm typecheck`、`pnpm build`。按变更范围扩大回归，不重复无关检查。
+- [x] 浏览器验证本地两个面板与弹窗、滚动及窄屏。核对 API 无请求时取 Tushare 的行为。
+- [x] 主会话完成最终验证并汇报实际证据；不自动提交用户改动，不更新全局知识或 specs。
+
+风险位置：sector_radar/application/build.py 的成功发布门、infrastructure/postgres.py 的快照/事实事务与新迁移、application/read.py 的日期回退。新增可选详情来源不应改变旧榜成功条件。
+
+执行结果与全局既有检查例外详见 verification.md；勾选代表本步骤已执行，不表示全仓检查全部通过。

.trellis/tasks/09-06-capital-radar-daily-detail/prd.md

@@ -0,0 +1,23 @@
+# 资金雷达：单日榜单与板块详情
+
+## 目标与边界
+尽可能复刻 OneChartLab 单日榜单和截图中的板块详情交互，支持解释当日资金强弱与历史持续性。所有业务数据通过 Tushare 采集落库，再由本地分析和 API 提供；参考站点仅用于交互研究。保留现有独立指标，不反演或新增原站未公开的加权评分，不改动波段榜及排名变化榜的算法，不提交已有用户改动。
+
+## 已确认背景
+当前排名接口没有涨跌幅及附加指标，见 `zhixing-server/src/zhixing_server/modules/sector_radar/presentation/http.py:83`。归一化事实只存成交额和主力净额，见同模块 `domain/persistence.py:101`。但采集已请求 `dc_index.pct_change/leading_code` 和 `daily.pct_chg`，见同模块 `infrastructure/tushare.py:40`。现有 3—10 日聚合及三指标排名可复用，30 日详情接口和前端交互尚未实现。
+
+## 需求与验收
+R1：单日流入率移除排名百分位和样本列，增加涨跌幅、净额、在榜；板块仅显示名称。按用户截图将“净值”解释为主力净额，金额以亿元显示。左右榜字段镜像排列，保留现有独立流入率排序。验收检查列名、数据、正负颜色和名称点击。
+
+R2：单日净额移除排名百分位和样本列，增加涨跌幅、单日流入率；同样只展示板块名称。验收核对附加指标属于同一板块、同一交易日和同一发布版本。
+
+R3：在榜为截至所选日近 30 个交易日内进入对应 TOP/BOTTOM 10% 的次数，不是连续天数。点击展开日期和当日排名格子，支持收起；分别用每日同类型排名池确定强弱。缺失记录显示缺失，不补零，不借用未来数据；不足 30 日标明覆盖范围。
+
+R4：点击板块打开可滚动详情弹窗，包含名称、类型、代码、日期、领涨股、当日涨跌幅、波段/单日率/单日额排名摘要；三指标近 30 交易日轨迹可切换，悬停显示日期和排名；成分强弱支持涨跌幅、主力净额、主买净额和前后 5 名；提供相似板块、复制及导出成员。少于 5 个有效成员按实际数量展示；缺失字段不伪装为 0。弹窗支持关闭按钮、Escape、焦点返回和加载/失败/空状态。
+
+R5：优先使用落库的 dc_index 板块涨跌幅，不以成分平均值静默替代。成分涨跌幅来自 daily，主力与主买净额分别保存。相似度使用同日成员集合 Jaccard 重合度，明确为本系统口径；最多显示四个非自身板块，允许概念与行业交叉比较。
+
+R6：真实 Tushare 单板块自测先采集落库，再通过 API 读取并核对金额、涨跌幅和成员。单板块数据不能验证全市场排名或相似度，不得发布为完整排名池；全池排名/历史边界使用受控数据验证。缺权限或历史数据不足时记录实际限制，不伪造通过。
+
+## 验证与风险
+后端验证单位、成员日期、历史截止日、独立发布版本、缺失和在榜计数；前端验证两面板、展开、弹窗、切换和导出交互。真实调用前核实环境与权限，密钥不进入日志。新增详情来源失败不得让已有完整榜单丢失；旧发布缺字段可读且明确为空。当前仍处规划阶段，尚未进行产品修改或真实采集。

.trellis/tasks/09-06-capital-radar-daily-detail/research/collect_selftest.py

@@ -0,0 +1,62 @@
+"""Collect one real sector into an isolated PostgreSQL snapshot store.
+
+Run with the server's uv environment from zhixing-server. No production
+publication is created; facts must be read back from this store for validation.
+"""
+from datetime import date
+from pathlib import Path
+from urllib.parse import urlsplit, urlunsplit
+import json
+import time
+import tushare as ts
+from zhixing_server.bootstrap.config import Settings
+from zhixing_server.modules.sector_radar.domain.source import build_source_snapshot
+from zhixing_server.modules.sector_radar.infrastructure.postgres import PostgresSectorRadarRepository
+
+
+def main():
+    """Persist provider responses before inspecting their values; redact errors."""
+    settings = Settings(_env_file='../.env')
+    url = urlsplit(settings.database_url)
+    host = url.netloc.rsplit('@', 1)[0] + '@127.0.0.1:5433'
+    database = urlunsplit((url.scheme, host, '/radar_detail_selftest_0906', url.query, ''))
+    repository = PostgresSectorRadarRepository(database, max_connections=2)
+    client = ts.pro_api(settings.tushare_token)
+    target = date(2026, 9, 4)
+    counts = []
+
+    def collect(api, fields, **params):
+        """Store each raw response atomically and return persisted rows."""
+        time.sleep(0.25)
+        frame = client.query(api, fields=fields, **params)
+        snapshot = build_source_snapshot(api_name=api, params=params,
+            rows=frame.to_dict('records'), target_trade_date=target)
+        repository.save_source_snapshots((snapshot,))
+        counts.append({'api':api, 'rows':snapshot.row_count, 'snapshot':snapshot.snapshot_id})
+        return snapshot.rows
+
+    try:
+        collect('dc_index','ts_code,trade_date,name,idx_type,level,pct_change,leading_code',
+            trade_date='20260904', ts_code='BK1147.DC')
+        members = collect('dc_member','trade_date,ts_code,con_code,name',
+            trade_date='20260904', ts_code='BK1147.DC')
+        collect('stock_basic','ts_code,symbol,name,market,exchange,list_status,list_date,delist_date',list_status='L')
+        collect('suspend_d','ts_code,trade_date,suspend_timing,suspend_type',trade_date='20260904')
+        collect('trade_cal','exchange,cal_date,is_open,pretrade_date',exchange='SSE',start_date='20260720',end_date='20260904')
+        for member in members:
+            code = member['con_code']
+            collect('daily','ts_code,trade_date,close,pre_close,pct_chg,vol,amount',trade_date='20260904',ts_code=code)
+            collect('moneyflow_dc','trade_date,ts_code,name,net_amount,net_amount_rate,pct_change,close',trade_date='20260904',ts_code=code)
+            collect('moneyflow','trade_date,ts_code,net_mf_amount',trade_date='20260904',ts_code=code)
+        result={'status':'collected','sector':'BK1147.DC','trade_date':str(target),'members':len(members),'snapshots':counts}
+    except Exception as exc:
+        result={'status':'partial','snapshots':counts,'error_type':type(exc).__name__,
+            'message':str(exc).replace(settings.tushare_token,'[redacted]')[:300]}
+    finally:
+        repository.close()
+    Path('../.trellis/tasks/09-06-capital-radar-daily-detail/research/collection-result.json').write_text(json.dumps(result,ensure_ascii=False,indent=2))
+    print(json.dumps({k:v for k,v in result.items() if k!='snapshots'},ensure_ascii=False))
+    print('Stored snapshots:',len(counts))
+
+if __name__ == '__main__':
+    main()

.trellis/tasks/09-06-capital-radar-daily-detail/research/collection-result.json

@@ -0,0 +1,243 @@
+{
+  "status": "collected",
+  "sector": "BK1147.DC",
+  "trade_date": "2026-09-04",
+  "members": 14,
+  "snapshots": [
+    {
+      "api": "dc_index",
+      "rows": 1,
+      "snapshot": "73f94be4b5c94238b611396b7cdf2e314f17cdd23532c3773febf3e3277f1674"
+    },
+    {
+      "api": "dc_member",
+      "rows": 14,
+      "snapshot": "2046df68966d3eda9a392b0254b84576842c42c487ea0a2f1044b6cc75de3afa"
+    },
+    {
+      "api": "stock_basic",
+      "rows": 5556,
+      "snapshot": "1c87ce65e081e670add1c1167473f798e97e8c9cf41db3e4ac71df0e3de5bb90"
+    },
+    {
+      "api": "suspend_d",
+      "rows": 8,
+      "snapshot": "b91d0981345538463407939a7ed863b8fb8de5e447b8ec731b8767b7ae13aa5d"
+    },
+    {
+      "api": "trade_cal",
+      "rows": 47,
+      "snapshot": "afff3cba955380cc0af9cdaac1d8861c17a70b089c70ea95aadb1cc568f8a26e"
+    },
+    {
+      "api": "daily",
+      "rows": 1,
+      "snapshot": "4f2c4f92685180b3de23a26c9d0602a8acf3fedb7dbc2413ac92bda76d8fa65a"
+    },
+    {
+      "api": "moneyflow_dc",
+      "rows": 1,
+      "snapshot": "7c1907d19c2db8134a807edba87fe165b44a1e96d6b3731e65a26f52715f6f12"
+    },
+    {
+      "api": "moneyflow",
+      "rows": 1,
+      "snapshot": "521254cf598c28608571973eeec1e52c56c856ee547bbd2d9ceacc4e1a29727e"
+    },
+    {
+      "api": "daily",
+      "rows": 1,
+      "snapshot": "9bf1ca69c3be480113c933c25681dab1379e0a068bdf9a31452794de8c4bff94"
+    },
+    {
+      "api": "moneyflow_dc",
+      "rows": 1,
+      "snapshot": "8b81006f266edabf8ac1e2aa292e9b278ca9131eea47f86fbef89373197215f6"
+    },
+    {
+      "api": "moneyflow",
+      "rows": 1,
+      "snapshot": "e90138a791bf7e3d458d3865838ac3aee394fe491ebf93cb363425852d1bca92"
+    },
+    {
+      "api": "daily",
+      "rows": 1,
+      "snapshot": "81ca417096a073698375daa03f0a660398d53c3943b16c9598a8faa918ff177f"
+    },
+    {
+      "api": "moneyflow_dc",
+      "rows": 1,
+      "snapshot": "40fb4ad0d2bbe8413e6dfcc213e8efe7f3367f84f492f68e430f1a9d08e9cc51"
+    },
+    {
+      "api": "moneyflow",
+      "rows": 1,
+      "snapshot": "47d32d618d5d8a2118253b1e3d7b354628bae22a7b10880f4cfdd3ee370dae22"
+    },
+    {
+      "api": "daily",
+      "rows": 1,
+      "snapshot": "2418e65c6800ef5633e6f260cbe617eb3b5bbda4d71e16e56589cd1603827b6b"
+    },
+    {
+      "api": "moneyflow_dc",
+      "rows": 1,
+      "snapshot": "d3559b1413d931dfe882fa64f501b75c76c91125fa0fbe616b385e9a3b7c9e15"
+    },
+    {
+      "api": "moneyflow",
+      "rows": 1,
+      "snapshot": "76a6e0cbe16e92c707af828a9936d87bd810844c357256c18e4d9ef10d86e40d"
+    },
+    {
+      "api": "daily",
+      "rows": 1,
+      "snapshot": "a3307443f9e89ff5523043055509dc309c6766067a5d9eb83bdef5d19e6e44c1"
+    },
+    {
+      "api": "moneyflow_dc",
+      "rows": 1,
+      "snapshot": "8d4c401bf8ade3dae6c0eab35069d59e61d4c6383b190e21a420d7735d0ab5a2"
+    },
+    {
+      "api": "moneyflow",
+      "rows": 1,
+      "snapshot": "ee3a90e0e406940f60358edfa3688f8774687bc768c4e9c069ca6d8337a39bcc"
+    },
+    {
+      "api": "daily",
+      "rows": 1,
+      "snapshot": "bf21400564f20c771905d46be0dd225eb9d0579393ab5734038ba93db63042f4"
+    },
+    {
+      "api": "moneyflow_dc",
+      "rows": 1,
+      "snapshot": "66611bdd15e87cd5ccec0f48d7e94282cedb210f0393a313519b6896abf0de1f"
+    },
+    {
+      "api": "moneyflow",
+      "rows": 1,
+      "snapshot": "eb98e9d138478b7ec2ae57557a1e61d34f825fd9faf8f30ef530c4d54f5e391e"
+    },
+    {
+      "api": "daily",
+      "rows": 1,
+      "snapshot": "550627fe30dccb760e4dbc73dd0ecee85676f781dac1ba059483e7d83b701091"
+    },
+    {
+      "api": "moneyflow_dc",
+      "rows": 1,
+      "snapshot": "5d1e6b1222b37896ad79d759e8fb8a240fb438bf6d50eda687c56181648c3a12"
+    },
+    {
+      "api": "moneyflow",
+      "rows": 1,
+      "snapshot": "7bc22506f40cd9c550a48699c93bee28f00c8717e304cd26761b33d9e66dbf35"
+    },
+    {
+      "api": "daily",
+      "rows": 1,
+      "snapshot": "39dda855afcfcf4e32ccd67e4cd28942f8eed13a171b82fa438000bfcff87252"
+    },
+    {
+      "api": "moneyflow_dc",
+      "rows": 1,
+      "snapshot": "b9042adf9d7c2823a7155691c6c349f451b6d84fe7eb2ca83ab749a51eaa6c6e"
+    },
+    {
+      "api": "moneyflow",
+      "rows": 1,
+      "snapshot": "aed26a777f4d4eae9236b677d6ed7180a093aa49076eeee3b796325db3ce2e9f"
+    },
+    {
+      "api": "daily",
+      "rows": 1,
+      "snapshot": "26d7d7beb26a8318f9b1104b5bc7446562663bba3e7142d9957562f5dce16c64"
+    },
+    {
+      "api": "moneyflow_dc",
+      "rows": 1,
+      "snapshot": "560d0e8e0a1d1220acab7a4d22ba6aadb4d47555344f75bbdbaf7650d62d95bf"
+    },
+    {
+      "api": "moneyflow",
+      "rows": 1,
+      "snapshot": "7f6759aea68eb193c271c6f8230de9237bcd25bb445eef786adc5b39d5527e08"
+    },
+    {
+      "api": "daily",
+      "rows": 1,
+      "snapshot": "467d8fa44adf1aeecb81bb970a3239db4f48c75ec680bd802310ba0a40b9a92f"
+    },
+    {
+      "api": "moneyflow_dc",
+      "rows": 1,
+      "snapshot": "cc80509ebf2c47e85cb1eebe0735db7c84facd01eba73212db218fbabcf6c980"
+    },
+    {
+      "api": "moneyflow",
+      "rows": 1,
+      "snapshot": "7f145408f62626e955b83617821e4c41ce0af3353533de790de22211f02ba36c"
+    },
+    {
+      "api": "daily",
+      "rows": 1,
+      "snapshot": "e515db0257399b1433fc14c4062a020a4837dfe6ff968cd70ab2b60f1035794e"
+    },
+    {
+      "api": "moneyflow_dc",
+      "rows": 1,
+      "snapshot": "31aa693eb092cf03a7b1e0da65ffd46e79389831f93809e6738789bfa6e8d619"
+    },
+    {
+      "api": "moneyflow",
+      "rows": 1,
+      "snapshot": "b4073fdbd1e5f73c52d64aae07ea3dd8a9613f12cdea316abcbbaf4bdff6f28e"
+    },
+    {
+      "api": "daily",
+      "rows": 1,
+      "snapshot": "ffd0d7d09fee0dc7e5a035c9131220042563a8d5c852ff5ca8d0a4d8b7ba8004"
+    },
+    {
+      "api": "moneyflow_dc",
+      "rows": 1,
+      "snapshot": "7e9bff54c0b00afc12bbcc7a98dfcd7e504ce780e47ac7a3c3443e989d9da031"
+    },
+    {
+      "api": "moneyflow",
+      "rows": 1,
+      "snapshot": "fd045165e72b1127df96bd73487a99d2b561c641783a0dfa3b0ed8b470e4abda"
+    },
+    {
+      "api": "daily",
+      "rows": 1,
+      "snapshot": "30ccd5069b7a8c361cc5408ecb9e0013f36d314cf5dde4c6d79b9e10f8942315"
+    },
+    {
+      "api": "moneyflow_dc",
+      "rows": 1,
+      "snapshot": "bbcc7b25b1e2d51487dcb76b28404966db7e83c9153af8f3119e1653f20f8618"
+    },
+    {
+      "api": "moneyflow",
+      "rows": 1,
+      "snapshot": "c210e7f840c5baecc94d6fd333f73fd98b994b65575f2ce38faed428e59b8f9f"
+    },
+    {
+      "api": "daily",
+      "rows": 1,
+      "snapshot": "bbb69dfcf4862e214b3a47265ba3607476695cb9147eed3d9f8199a0e7501ff1"
+    },
+    {
+      "api": "moneyflow_dc",
+      "rows": 1,
+      "snapshot": "fce61a39b30de56dc3b898f6d8e4bf156504bedc001c5c85abfceaecbb490f36"
+    },
+    {
+      "api": "moneyflow",
+      "rows": 1,
+      "snapshot": "2e0739949d25df4a56631c761e064121ff8f99ead4e95306c1c1f1bfa44111ae"
+    }
+  ]
+}

.trellis/tasks/09-06-capital-radar-daily-detail/research/persisted-baseline.json

@@ -0,0 +1,20 @@
+{
+  "trade_date": "2026-09-04",
+  "sector": "BK1147.DC",
+  "members": 14,
+  "pct_change": 1.82,
+  "main_net_yuan": "485456500.00",
+  "turnover_yuan": "2615472881.48000",
+  "daily_ratio": "0.1856094564915916866216729052",
+  "active_net_yuan": "-255455700.00",
+  "rows_by_api": {
+    "dc_index": 1,
+    "dc_member": 14,
+    "stock_basic": 5556,
+    "suspend_d": 8,
+    "trade_cal": 47,
+    "daily": 14,
+    "moneyflow_dc": 14,
+    "moneyflow": 14
+  }
+}

.trellis/tasks/09-06-capital-radar-daily-detail/research/replay_selftest.py

@@ -0,0 +1,77 @@
+"""Replay the persisted real SPD sample in an isolated database, with no network.
+
+The one-sector publication is exclusively a local integration fixture; its ranks
+must never be interpreted as a market-wide ranking.
+"""
+import os
+import json
+from datetime import date
+from pathlib import Path
+from urllib.parse import urlsplit, urlunsplit
+import psycopg
+from alembic import command
+from alembic.config import Config
+from zhixing_server.bootstrap.config import Settings, get_settings
+from zhixing_server.modules.sector_radar.application.build import BuildSectorRadar, BuildSectorRadarCommand
+from zhixing_server.modules.sector_radar.domain.models import SectorType
+from zhixing_server.modules.sector_radar.domain.source import (
+    SourceSnapshot, SourceResult, TradeCalendarRow, SectorIndexRow, SectorMemberRow,
+    StockBasicRow, SuspendRow, DailyRow, MoneyflowDcRow, MoneyflowRow, build_source_snapshot,
+)
+from zhixing_server.modules.sector_radar.infrastructure.postgres import PostgresSectorRadarRepository
+
+
+def database_url():
+    """Resolve only the named localhost fixture database without printing secrets."""
+    s=Settings(_env_file='../.env'); u=urlsplit(s.database_url)
+    return urlunsplit((u.scheme,u.netloc.rsplit('@',1)[0]+'@127.0.0.1:5433','/radar_detail_selftest_0906',u.query,''))
+
+
+class StoredSource:
+    """Implement provider port using already committed raw snapshots only."""
+    def __init__(self, dsn):
+        self.by_api={}
+        with psycopg.connect(dsn) as c:
+            for r in c.execute('SELECT id,api_name,normalized_params,target_trade_date,partition_key,observed_at,payload,row_count,returned_fields,content_sha256,row_limit,limit_reached FROM sector_radar_source_snapshot').fetchall():
+                snap=SourceSnapshot(r[0],r[1],tuple(sorted(r[2].items())),r[3],r[4],r[5],tuple(r[6]),r[7],tuple(r[8]),r[9],r[10],r[11])
+                self.by_api.setdefault(r[1],[]).append(snap)
+
+    def result(self, api, parser):
+        snaps=tuple(self.by_api[api])
+        return SourceResult(snaps,tuple(parser(row) for s in snaps for row in s.rows))
+
+    def fetch_trade_calendar(self,start,end):
+        return self.result('trade_cal',TradeCalendarRow.from_mapping)
+    def fetch_sector_indices(self,target,kind):
+        if kind is SectorType.INDUSTRY:
+            # Explicitly empty industry scope for this one-concept test fixture.
+            snap=build_source_snapshot(api_name='dc_index',params={'test_scope':'empty_industry'},rows=(),target_trade_date=target)
+            return SourceResult((snap,),())
+        return self.result('dc_index',lambda row:SectorIndexRow.from_mapping(row,kind))
+    def fetch_sector_members(self,target,codes):
+        return self.result('dc_member',SectorMemberRow.from_mapping)
+    def fetch_stock_basics(self):
+        return self.result('stock_basic',StockBasicRow.from_mapping)
+    def fetch_suspensions(self,target):
+        return self.result('suspend_d',SuspendRow.from_mapping)
+    def fetch_daily(self,target):
+        return self.result('daily',DailyRow.from_mapping)
+    def fetch_moneyflow_dc(self,target,codes):
+        return self.result('moneyflow_dc',MoneyflowDcRow.from_mapping)
+    def fetch_moneyflow(self,target):
+        return self.result('moneyflow',MoneyflowRow.from_mapping)
+
+
+def main():
+    """Run actual build and HTTP reads, checking independently recomputed facts."""
+    dsn=database_url()
+    os.environ['ZHIXING_DATABASE_URL']=dsn
+    get_settings.cache_clear()
+    command.upgrade(Config('alembic.ini'),'head')
+    repository=PostgresSectorRadarRepository(dsn,max_connections=2)
+    result=BuildSectorRadar(StoredSource(dsn),repository,today=date(2026,9,6)).execute(BuildSectorRadarCommand(trade_date=date(2026,9,4)))
+    print(json.dumps(result.as_dict(),ensure_ascii=False))
+    repository.close()
+
+if __name__=='__main__':
+    main()

.trellis/tasks/09-06-capital-radar-daily-detail/research/verify_http.py

@@ -0,0 +1,27 @@
+"""Verify API facts against independently calculated persisted real data."""
+import json
+from decimal import Decimal
+from pathlib import Path
+from urllib.request import urlopen
+
+root='http://127.0.0.1:8016/api/v1/sector-radar/'
+d=json.load(urlopen(root+'sectors/concept/BK1147.DC/detail?trade_date=2026-09-04'))
+assert d['status']=='success'
+assert len(d['members'])==14
+assert Decimal(d['pct_change'])==Decimal('1.82')
+assert sum(Decimal(m['net_amount_yuan']) for m in d['members'])==Decimal('485456500')
+assert sum(Decimal(m['active_buy_net_amount_yuan']) for m in d['members'])==Decimal('-255455700')
+assert Decimal(d['summary']['amount']['metric_value'])==Decimal('4.854565')
+# Storage uses 12 fractional digits for persisted metric observations.
+assert abs(Decimal(d['summary']['ratio']['metric_value'])-Decimal('0.18560945649159168662'))<Decimal('1e-12')
+assert d['history']['available_days']==1
+assert len(d['history']['points'])==30
+assert d['summary']['swing']['missing'] is True
+assert len(d['leaders']['pct_change']['top'])==5
+for view in ['amount','ratio']:
+ r=json.load(urlopen(root+'rankings?sector_type=concept&view='+view+'&side=top&trade_date=2026-09-04'))['rows'][0]
+ assert Decimal(r['pct_change'])==Decimal('1.82')
+ assert Decimal(r['daily_net_amount_yuan'])==Decimal('485456500')
+ assert r['on_list_count']==1
+Path(__file__).with_name('verified-detail.json').write_text(json.dumps(d,ensure_ascii=False,indent=2))
+print('PASS: real persisted SPD data matches detail and both ranking APIs; 14 members, 30 slots / 1 available day, absent swing remains null.')

.trellis/tasks/09-06-capital-radar-daily-detail/task.json

@@ -0,0 +1,26 @@
+{
+  "id": "capital-radar-daily-detail",
+  "name": "capital-radar-daily-detail",
+  "title": "资金雷达：单日榜单与板块详情",
+  "description": "",
+  "status": "in_progress",
+  "dev_type": null,
+  "scope": null,
+  "package": null,
+  "priority": "P2",
+  "creator": "yuxuanhui",
+  "assignee": "yuxuanhui",
+  "createdAt": "2026-09-06",
+  "completedAt": null,
+  "branch": null,
+  "base_branch": "main",
+  "worktree_path": null,
+  "commit": null,
+  "pr_url": null,
+  "subtasks": [],
+  "children": [],
+  "parent": null,
+  "relatedFiles": [],
+  "notes": "实施及本地验证完成，详见 verification.md。代码按用户边界保持未提交，未自动归档；正常业务库尚未应用本次迁移。",
+  "meta": {}
+}

.trellis/tasks/09-06-capital-radar-daily-detail/verification.md

@@ -0,0 +1,25 @@
+# 本地实施验证 · 2026-09-06
+
+本次已实现单日流入率/净额两种表头、板块名称入口、30 交易日在榜展开、详情三指标排名曲线、成员三指标前后 5 名切换、Jaccard 相似板块和成员复制/CSV 导出。沿用当前项目主题，参考站点私有加权评分未作为此次范围。前端读取同源 API；详情和历史仅从已持久化的发布及原始快照分析，不在读请求中调用 Tushare。
+
+## 真实数据核验
+
+使用独立数据库 `radar_detail_selftest_0906`，未覆盖正常业务库。采集 SPD概念 `BK1147.DC` 在 2026-09-04 的 Tushare 数据，14 只成员，原始响应先入库，再从已保存快照重放构建。数据库已升级至 `0009_radar_sector_detail`。采集、独立计算和 API 核对脚本在本任务 `research/`，不包含凭据。
+
+数据库独立汇总与最新 HTTP 返回一致：板块涨跌幅 1.82%，主力净额 485456500 元，成交额 2615472881.48 元，单日流入率 18.560945649159…%，主买净额 -255455700 元。两种资金指标分别保留，未互相替代。`research/verify_http.py` 在重启最新服务后通过，验证 14 个成员、三指标摘要及两种榜单附加字段。
+
+该自测只有 1 个板块、1 日有效发布；近 30 个交易日中的其余日期显式缺失，波段指标保持空值。单板块第 1 名仅验证功能链路，不代表全市场排名，也不能用于检验参考站点全池历史的数值一致性。
+
+## 检查结果
+
+- 后端相关单元、HTTP、PostgreSQL 测试：96 passed。隔离审查库 `radar_detail_review_0906` 从空库完成迁移；覆盖最新发布、30 日边界、未来隔离、每日池变化、版本隔离、可选来源失败、历史成员、Jaccard 和字段持久化。
+- 后端全量 Ruff lint/format：通过，129 个文件格式符合。资金雷达源码及相关测试 Pyright：0 errors。
+- 前端资金雷达测试：41 passed。全量 ESLint、TypeScript、生产构建通过；资金雷达范围 Prettier 通过。
+- 浏览器已核验两个面板、名称入口、在榜展开、默认指标跟随当前面板、成员指标与前后 5 切换、复制/导出 14 名成员及弹窗下部。390px 窄屏发现的 grid/canvas 撑宽已修复，弹窗 clientWidth 和 scrollWidth 均为 358px。单点历史保留可见圆点。
+- `git diff --check` 通过。代码未提交，未执行自动归档或修改 specs。
+
+## 已有全局检查问题与使用边界
+
+全量后端 Pyright 仍报告 14 个错误，范围仅在未修改的 selection/application/chart.py、selection/domain/gold_brick.py 和 tests/unit/selection/test_run.py。全量前端 format:check 仍被两份已有 `.playwright-cli/page-2026-09-01T14-54-32-480Z.yml`、`page-2026-09-05T07-35-10-548Z.yml` 阻断。未扩大修复这些文件。构建另有大 chunk 提示，Alembic 有既有 path_separator 弃用提示。
+
+正式业务数据库使用前需应用新迁移并按原构建流程采集/构建目标日；既有发布缺少可选主买净额时显示缺失，不通过实时请求补值。当前本地预览为 `http://127.0.0.1:5516/sector-radar`，连接上述单板块隔离库，后端端口 8016。最新截图在 `output/playwright/radar-detail.png`。

.zcode/plans/plan-sess_24b98073-00f4-4b58-a624-fbfe486bcf2a.md

@@ -0,0 +1,35 @@
+## 调研结论（可行性：具备）
+
+**现状**
+- 详情面板 `zhixing-web/src/features/selection/components/signal-detail-panel.tsx` 只展示名称/代码/价格/指标，无行业板块；`SelectionStockResult` 类型也无相关字段。
+- 后端 `market_stock` 表没同步 tushare `stock_basic.industry`；但项目已有 **sector_radar 模块**，通过 tushare `dc_index`/`dc_member` 每日同步"行业板块 + 概念板块"的成分股快照到 PostgreSQL 表 `sector_radar_membership`（trade_date + sector_type=industry/concept + sector_code/name + stock_code），只是目前只暴露了板块级 rankings 端点，**没有"按股票反查所属板块"的接口**——这就是缺口的全部。
+- 已确认决策：数据口径复用 sector_radar（DC 行业+概念）；仅详情面板展示，列表行不动。
+
+## 实施方案
+
+### 第 0 步：数据验证（前置）
+启动 docker compose 的 PostgreSQL，检查 `sector_radar_membership` 按交易日的覆盖情况。若选股目标日期无快照，运行现有 CLI `sector-radar-build` 回补。若 dc_member 接口因 tushare 积分不足失败，回退方案是给 `market_stock` 加 `stock_basic.industry` 列（Alembic 迁移），届时向你说明。
+
+### 后端（sector_radar 模块内新增"按股票反查"，不跨模块读表）
+1. `modules/sector_radar/infrastructure/postgres.py`：新增读查询——按 `stock_code` 查 `membership_status='available'` 且 `trade_date <= 目标日` 的最近可用快照（带出实际 membership 的 trade_date，point-in-time 语义，不用最新日期冒充历史）。
+2. `modules/sector_radar/application/read.py`：新增用例，输入 `ts_code + trade_date`，返回按类型分组的板块列表（industry 全部、concept 排序后默认截断 20 个）。
+3. `modules/sector_radar/presentation/http.py`：新增端点
+   `GET /api/v1/sector-radar/stocks/{ts_code}/membership?trade_date=YYYY-MM-DD&limit=20`
+   响应：`{ ts_code, trade_date, membership_trade_date, industries: [{code,name}], concepts: [{code,name}], concept_total }`，遵循 http-api-contracts spec（Pydantic 边界模型）。
+
+### 前端（selection feature）
+4. 新增 API 调用 + TanStack Query hook（`enabled: !!stock`，按 `stock.target_trade_date` 查询，随详情面板选中切换）。
+5. `signal-detail-panel.tsx`：股票名/代码/价格下方新增两行展示——
+   - **行业**：行业标签（通常 1 个）
+   - **所属板块**：概念板块 chips，最多显示 8 个 + "等 N 个"
+   加载中显示占位文案，无数据时静默隐藏（不打扰无板块数据的股票）。
+
+### 测试与验证
+- 后端：读用例单测（命中/无快照/截断）+ http 端点测试，参照 sector_radar 现有测试。
+- 前端：vitest 组件测试 + typecheck/lint。
+- 端到端：起 server + web，在 `/selection` 选一只股票确认行业与板块正确显示、无数据股票正常降级。
+
+### 涉及文件
+- `zhixing-server/.../modules/sector_radar/{application/read.py, infrastructure/postgres.py, presentation/http.py}`
+- `zhixing-web/src/features/selection/api/*`（新 query）
+- `zhixing-web/src/features/selection/components/signal-detail-panel.tsx`

.zcode/plans/plan-sess_55e3d246-e875-4283-bdfc-929f8f26a73f.md

@@ -0,0 +1,42 @@
+# 选股页面迭代：上搜索 + 左列表/右详情布局 & 板块筛选
+
+## 现状与关键结论
+
+- 布局：`selection-results-workbench.tsx` 目前是左右两栏 grid（左 320px 筛选+列表 / 右详情），筛选栏嵌在左栏顶部。
+- 板块数据：选股结果表（`selection_run_item`）没有板块字段；板块归属在 `sector_radar_membership` 表，现有 membership 接口只支持单股查询。**板块聚合必须由后端新增**（前端逐股请求既慢又只覆盖已加载分页，计数不准）。
+- 已确认口径（用户未答，按推荐执行）：概念板块（`sector_type='concept'`，与详情面板"板块"标签一致），单选；接口保留 `sector_type` 参数，后续扩展行业零成本。排序 = 按 `stock_count` 倒序（选项旁展示数量）。
+
+## 一、后端（zhixing-server）
+
+遵循 bounded-context-first（ADR 0001）：selection 不直接 join sector_radar 表，通过应用层端口调用 sector_radar 的读服务。
+
+1. **sector_radar 模块**（`application/read.py` + `infrastructure/postgres.py`）：
+   - 仓储新增两个只读方法（复用已有的 `get_last_good_publication` 解析快照日）：
+     - `load_sector_counts(stock_codes, snapshot_date, sector_type)`：`SELECT sector_code, sector_name, COUNT(*) FROM sector_radar_membership WHERE stock_code = ANY(%s) AND trade_date = %s AND sector_type = %s AND membership_status='available' GROUP BY 1,2`
+     - `load_sector_member_codes(snapshot_date, sector_code, sector_type)`：返回该板块成员股票代码列表
+   - 读服务 `ReadSectorRadar` 新增：`sector_counts(stock_codes, trade_date, sector_type)`（内部解析 last-good publication，返回按 stock_count 降序、名称升序）和 `sector_member_codes(trade_date, sector_code, sector_type)`。
+2. **selection 模块**：
+   - `domain/runs.py`：`SelectionResultQuery` 增加 `sector: str | None`；新增 `SelectionSectorCount(sector_code, sector_name, stock_count)` 值对象；定义端口协议 `SectorMembershipReader`（`sector_counts` / `sector_member_codes` 两个方法）。
+   - `application/run.py`：新增 `list_sector_counts(strategy, target_trade_date, sector_type)` —— 取 latest run，收集 `status='selected' AND signal_count>0` 的 ts_code，调端口聚合；`get_latest`/`get` 结果查询在 `query.sector` 有值时先调端口取成员代码，空则直接返回空页，否则把代码数组传入仓储。
+   - `infrastructure/postgres_runs.py`：`_stock_filter` 增加子句 `item.ts_code = ANY(%s)`（参数由应用层传入）。
+   - `presentation/http.py`：
+     - 新端点 `GET /api/v1/selection/sectors?strategy=&target_trade_date=&sector_type=` → `{ sector_type, snapshot_trade_date, sectors: [{sector_code, sector_name, stock_count}] }`
+     - `GET /results` 与 `GET /runs/{id}` 增加 `sector` query 参数校验（去空格、限长）。
+   - 组合根（router/依赖装配处）把 sector_radar 的读服务适配为 selection 的端口注入。
+3. **测试**：`tests/unit/sector_radar/`（新仓储方法）、`tests/unit/selection/test_postgres_runs.py`（sector 过滤、ANY 数组、空成员空页）、`tests/test_selection_http.py`（新端点契约 + results 带 sector）。跑 `./dev.sh check`（ruff/pyright/pytest）。
+
+## 二、前端（zhixing-web）
+
+1. **布局重构** `selection-results-workbench.tsx`：
+   - 外层改为 `flex flex-col`：顶部一个全宽 section 放搜索栏（关键词 / 信号分类 / **板块（新增）** / 排序 / 筛选结果计数），带 `rounded-md border bg-card` 与现有一致；
+   - 下方 `md:grid md:grid-cols-[320px_minmax(0,1fr)]` 左列表右详情；移动端纵向堆叠为 搜索 → 列表 → 详情。
+2. **类型与 API**（`selection.types.ts` / `selection.api.ts`）：新增 `SelectionSectorAggregate`；`SelectionResultsQuery` 加 `sector?`；`getSelectionResultSectors()`；`buildSelectionQueryParams` 带 sector。
+3. **查询层**（`selection.query.ts`）：`useSelectionResultSectors`（key：strategy+date，结果就绪后启用）；`selectionResultsQueryKey`/`selectionRunQueryKey` 加入 sector 使筛选变化触发重新请求。
+4. **路由**（`routes/route-tree.tsx`）：selectionRoute `validateSearch` 增加 `sector`（string，限长，默认 undefined）。
+5. **页面接线**（`selection-results-page.tsx`）：把 URL 中的 sector 传入 `useSelectionResults`；页面层调用 `useSelectionResultSectors` 并把聚合结果传给 workbench。
+6. **workbench 板块下拉**：选项 = "全部板块" + 聚合数据，item 渲染 `名称 + 数量徽标`（数量 tabular-nums，倒序由后端保证）；选择写 URL；聚合加载后若当前 sector 不在列表中（如切换策略/日期）自动重置为全部；板块无数据时下拉仅剩"全部板块"并禁用。
+
+## 三、执行方式
+
+- 按仓库 Trellis 工作流建任务目录并加载 `.trellis/spec/backend`（selection.md 契约：查询不触发重算、错误矩阵等）与前端规范后再动手；先后端（接口+测试）再前端接线，最后 `./dev.sh check` + 前端 lint/tsc 全量质量门禁。
+- 语义说明：板块数量 = 当次 run 全部选中股票中归属该板块的数量（不随关键词/信号分类变化）；列表"筛选结果 N 只" = 包含板块在内的全部过滤叠加后的 `stocks_total`。

zhixing-server/.vite/deps/_metadata.json

@@ -0,0 +1,8 @@
+{
+  "hash": "be29b65c",
+  "configHash": "93a0ae7b",
+  "lockfileHash": "e3b0c442",
+  "browserHash": "4df63514",
+  "optimized": {},
+  "chunks": {}
+}

zhixing-server/.vite/deps/package.json

@@ -0,0 +1,3 @@
+{
+  "type": "module"
+}

zhixing-server/migrations/versions/0008_radar_detail.py

@@ -0,0 +1,38 @@
+"""Preserve independent stock detail facts without invalidating old publications."""
+
+from collections.abc import Sequence
+
+import sqlalchemy as sa
+from alembic import op
+
+revision: str = "0008_radar_detail"
+down_revision: str | None = "0007_selection_pattern_scoring"
+branch_labels: str | Sequence[str] | None = None
+depends_on: str | Sequence[str] | None = None
+
+
+def upgrade() -> None:
+    """Add nullable facts and allow the optional raw moneyflow checkpoint."""
+    for name in ("pct_change", "active_buy_net_amount_yuan"):
+        op.add_column("sector_radar_stock_fact", sa.Column(name, sa.Numeric(), nullable=True))
+        op.create_check_constraint(
+            f"ck_radar_stock_{name}_finite",
+            "sector_radar_stock_fact",
+            f"{name} IS NULL OR {name} NOT IN "
+            "('NaN'::numeric, 'Infinity'::numeric, '-Infinity'::numeric)",
+        )
+    op.drop_constraint(
+        "ck_sector_radar_publication_source_group", "sector_radar_publication_source"
+    )
+    op.create_check_constraint(
+        "ck_sector_radar_publication_source_group",
+        "sector_radar_publication_source",
+        "source_group IN ('calendar', 'concept_indices', 'industry_indices', 'members', "
+        "'stock_basics', 'suspensions', 'daily', 'moneyflow_dc', 'moneyflow')",
+    )
+
+
+def downgrade() -> None:
+    """Drop added fact columns; retain optional checkpoint audit rows for older readers."""
+    for name in ("pct_change", "active_buy_net_amount_yuan"):
+        op.drop_column("sector_radar_stock_fact", name)

zhixing-server/migrations/versions/0009_radar_sector_detail.py

@@ -0,0 +1,33 @@
+"""Store source sector detail alongside immutable publication daily inputs."""
+
+from collections.abc import Sequence
+
+import sqlalchemy as sa
+from alembic import op
+
+revision: str = "0009_radar_sector_detail"
+down_revision: str | None = "0008_radar_detail"
+branch_labels: str | Sequence[str] | None = None
+depends_on: str | Sequence[str] | None = None
+
+
+def upgrade() -> None:
+    """Keep all previous rows readable with nullable provider detail."""
+    op.add_column(
+        "sector_radar_daily_aggregate", sa.Column("pct_change", sa.Numeric(), nullable=True)
+    )
+    op.add_column(
+        "sector_radar_daily_aggregate", sa.Column("leading_code", sa.Text(), nullable=True)
+    )
+    op.create_check_constraint(
+        "ck_radar_sector_pct_change_finite",
+        "sector_radar_daily_aggregate",
+        "pct_change IS NULL OR pct_change NOT IN "
+        "('NaN'::numeric, 'Infinity'::numeric, '-Infinity'::numeric)",
+    )
+
+
+def downgrade() -> None:
+    """Remove only the nullable projection; original provider snapshots remain intact."""
+    op.drop_column("sector_radar_daily_aggregate", "leading_code")
+    op.drop_column("sector_radar_daily_aggregate", "pct_change")

zhixing-server/src/zhixing_server/modules/sector_radar/application/build.py

@@ -14,6 +14,8 @@ from typing import Literal
 from uuid import uuid4
 from zoneinfo import ZoneInfo
 
+from zhixing_server.shared.request_coordinator import TushareSourceError
+
 from ..domain.facts import aggregate_sector_snapshot
 from ..domain.metrics import (
     AmountNetStrategy,
@@ -47,11 +49,12 @@ from ..domain.persistence import (
     SectorRadarRepository,
     StockFactRecord,
 )
-from ..domain.ports import SectorRadarSource
+from ..domain.ports import ActiveMoneyflowSource, SectorRadarSource
 from ..domain.ranking import rank_metric_observations, with_rank_changes
 from ..domain.source import (
     DailyRow,
     MoneyflowDcRow,
+    MoneyflowRow,
     SectorIndexRow,
     SectorMemberRow,
     SourceContractError,
@@ -367,12 +370,21 @@ class BuildSectorRadar:
                     )
                 ),
             )
+            index_details = {
+                (index.sector_type, index.sector_code): index for index in collected.indices
+            }
             self.repository.finalize_publication(
                 finished,
                 memberships=collected.memberships,
                 stock_facts=collected.stock_facts,
                 daily_aggregates=(
-                    DailyAggregateRecord(publication_id, aggregate) for aggregate in aggregates
+                    DailyAggregateRecord(
+                        publication_id,
+                        aggregate,
+                        index_details[(aggregate.sector_type, aggregate.sector_code)].pct_change,
+                        index_details[(aggregate.sector_type, aggregate.sector_code)].leading_code,
+                    )
+                    for aggregate in aggregates
                 ),
                 rankings=(RankingRecord(publication_id, ranking) for ranking in rankings),
                 retry_source_groups=(
@@ -511,7 +523,7 @@ class BuildSectorRadar:
             publication_id,
             PublicationSourceGroup.CALENDAR,
             reusable,
-            lambda: self.source.fetch_trade_calendar(target, target),
+            lambda: self.source.fetch_trade_calendar(target - timedelta(days=70), target),
             TradeCalendarRow.from_mapping,
         )
         if target not in {row.cal_date for row in calendar.rows if row.is_open}:
@@ -587,6 +599,23 @@ class BuildSectorRadar:
             ),
         )
 
+        active_moneyflow: SourceResult[MoneyflowRow] | None = None
+        if isinstance(self.source, ActiveMoneyflowSource):
+            fetch_active = self.source.fetch_moneyflow
+            try:
+                active_moneyflow = self._fetch_group(
+                    publication_id,
+                    PublicationSourceGroup.MONEYFLOW,
+                    reusable,
+                    lambda: fetch_active(target),
+                    MoneyflowRow.from_mapping,
+                )
+            except (TushareSourceError, SourceContractError):
+                # Optional detail failure must not invalidate otherwise complete rankings.
+                logger.warning(
+                    "sector_radar_optional_moneyflow_unavailable publication_id=%s", publication_id
+                )
+
         stock_facts = normalize_stock_facts(
             target_trade_date=target,
             candidate_codes=member_codes,
@@ -594,6 +623,7 @@ class BuildSectorRadar:
             suspensions=suspensions,
             daily=daily,
             moneyflow=moneyflow,
+            active_moneyflow=active_moneyflow,
         )
         snapshots = (
             calendar.snapshots
@@ -604,9 +634,11 @@ class BuildSectorRadar:
             + suspensions.snapshots
             + daily.snapshots
             + moneyflow.snapshots
+            + (active_moneyflow.snapshots if active_moneyflow else ())
         )
         return _CollectedInputs(
             target_trade_date=target,
+            indices=concepts.rows + industries.rows,
             snapshots=snapshots,
             membership_snapshots=members.snapshots,
             memberships=memberships,
@@ -723,7 +755,7 @@ class BuildSectorRadar:
             {
                 "snapshot_ids": sorted(snapshot.snapshot_id for snapshot in snapshots),
                 "metric_versions": sorted(strategy.metric_version for strategy in self.strategies),
-                "normalizer": "zhixing_stock_fact_v1",
+                "normalizer": "zhixing_stock_fact_v2",
             },
             sort_keys=True,
             separators=(",", ":"),
@@ -753,6 +785,7 @@ class BuildSectorRadar:
 @dataclass(frozen=True, slots=True)
 class _CollectedInputs:
     target_trade_date: date
+    indices: tuple[SectorIndexRow, ...]
     snapshots: tuple[SourceSnapshot, ...]
     membership_snapshots: tuple[SourceSnapshot, ...]
     memberships: tuple[MembershipRecord, ...]

zhixing-server/src/zhixing_server/modules/sector_radar/application/details.py

@@ -0,0 +1,445 @@
+"""Publication-scoped detail projections built exclusively from persisted inputs."""
+
+from __future__ import annotations
+
+from collections.abc import Sequence
+from dataclasses import dataclass
+from datetime import date
+from decimal import Decimal
+
+from ..domain.metrics import AmountNetStrategy, RatioTurnoverStrategy, SwingEqualThreeToTenStrategy
+from ..domain.models import MetricKind, RadarPublication, RankedMetric, RankSide, SectorType
+from ..domain.normalize import is_current_listed_stock
+from ..domain.persistence import PublicationSourceGroup, SectorRadarRepository
+from ..domain.source import (
+    DailyRow,
+    MoneyflowDcRow,
+    MoneyflowRow,
+    SectorIndexRow,
+    SectorMemberRow,
+    SourceSnapshot,
+    StockBasicRow,
+    TradeCalendarRow,
+)
+
+_METRIC_VERSIONS = {
+    MetricKind.AMOUNT: AmountNetStrategy.metric_version,
+    MetricKind.RATIO: RatioTurnoverStrategy.metric_version,
+    MetricKind.SWING: SwingEqualThreeToTenStrategy.metric_version,
+}
+
+
+@dataclass(frozen=True, slots=True)
+class RankingExtras:
+    """Same-publication daily values and the selected side's historical appearances."""
+
+    pct_change: Decimal | None = None
+    daily_net_amount_yuan: Decimal | None = None
+    daily_ratio: Decimal | None = None
+    on_list_count: int | None = None
+    history_available_days: int = 0
+
+
+@dataclass(frozen=True, slots=True)
+class HistoryMetric:
+    """One dated rank retaining its pool and explicit missing state."""
+
+    rank_position: int | None = None
+    rank_percentile: Decimal | None = None
+    pool_size: int = 0
+    metric_value: Decimal | None = None
+    missing: bool = True
+    in_top: bool = False
+    in_bottom: bool = False
+
+
+@dataclass(frozen=True, slots=True)
+class HistoryPoint:
+    """Three comparable metric ranks on one observed trading day."""
+
+    trade_date: date
+    publication_id: str | None
+    amount: HistoryMetric
+    ratio: HistoryMetric
+    swing: HistoryMetric
+
+
+@dataclass(frozen=True, slots=True)
+class SectorHistory:
+    """A thirty-session ceiling with no invented pre-launch history."""
+
+    status: str
+    requested_trade_date: date
+    trade_date: date | None
+    publication: RadarPublication | None
+    sector_type: SectorType
+    sector_code: str
+    sector_name: str | None
+    points: tuple[HistoryPoint, ...]
+    available_days: int
+    window_size: int = 30
+
+
+@dataclass(frozen=True, slots=True)
+class DetailMember:
+    """One confirmed current-listed member with independently nullable metrics."""
+
+    ts_code: str
+    name: str
+    pct_change: Decimal | None = None
+    net_amount_yuan: Decimal | None = None
+    active_buy_net_amount_yuan: Decimal | None = None
+
+
+@dataclass(frozen=True, slots=True)
+class LeadingStock:
+    """Provider-designated leading stock identity."""
+
+    ts_code: str
+    name: str | None
+
+
+@dataclass(frozen=True, slots=True)
+class MemberLeaders:
+    """Up to five finite observations per side, stably ordered by code on ties."""
+
+    top: tuple[DetailMember, ...]
+    bottom: tuple[DetailMember, ...]
+
+
+@dataclass(frozen=True, slots=True)
+class SimilarSector:
+    """Jaccard overlap of confirmed same-publication listed member sets."""
+
+    sector_type: SectorType
+    sector_code: str
+    sector_name: str
+    overlap_ratio: Decimal
+    intersection_count: int
+    union_count: int
+
+
+@dataclass(frozen=True, slots=True)
+class SectorDetail:
+    """Complete read-only detail for one immutable publication."""
+
+    history: SectorHistory
+    pct_change: Decimal | None
+    leading_stock: LeadingStock | None
+    summary: dict[str, HistoryMetric]
+    members: tuple[DetailMember, ...]
+    leaders: dict[str, MemberLeaders]
+    similar_sectors: tuple[SimilarSector, ...]
+
+
+class ReadRadarDetails:
+    """Reuse batched history and exact publication raw snapshots across read views."""
+
+    def __init__(self, repository: SectorRadarRepository) -> None:
+        self.repository = repository
+
+    def history_data(
+        self, publication: RadarPublication
+    ) -> tuple[dict[date, RadarPublication], dict[date, Sequence[RankedMetric]], tuple[date, ...]]:
+        """Load history in bounded batches; calendar holes remain explicit missing points."""
+        publications = {
+            item.target_trade_date: item
+            for item in self.repository.load_history_publications(publication.target_trade_date)
+        }
+        # Pin the current date to the response's chosen publication if a rebuild finishes
+        # during this request. All history rows are then fetched by these exact IDs.
+        publications[publication.target_trade_date] = publication
+        by_id = dict(
+            self.repository.load_publication_rankings(
+                tuple(item.publication_id for item in publications.values())
+            )
+        )
+        rows = {
+            day: by_id.get(item.publication_id, ())
+            if item.source_version == publication.source_version
+            else ()
+            for day, item in publications.items()
+        }
+        snapshots = self.snapshots(publication)
+        calendar = [
+            TradeCalendarRow.from_mapping(row)
+            for snapshot in snapshots.get(PublicationSourceGroup.CALENDAR, ())
+            for row in snapshot.rows
+        ]
+        dates = tuple(
+            sorted(
+                {
+                    row.cal_date
+                    for row in calendar
+                    if row.is_open and row.cal_date <= publication.target_trade_date
+                }
+                | set(publications)
+            )[-30:]
+        )
+        return publications, rows, dates
+
+    def ranking_extras(
+        self, publication: RadarPublication, rankings: Sequence[RankedMetric], side: RankSide
+    ) -> dict[str, RankingExtras]:
+        """Enrich one page from one batched thirty-session history, with no per-sector IO."""
+        if not rankings:
+            return {}
+        _, history, dates = self.history_data(publication)
+        snapshots = self.snapshots(publication)
+        indices = {
+            (item.sector_type, item.sector_code): item
+            for group, kind in (
+                (PublicationSourceGroup.CONCEPT_INDICES, SectorType.CONCEPT),
+                (PublicationSourceGroup.INDUSTRY_INDICES, SectorType.INDUSTRY),
+            )
+            for snapshot in snapshots.get(group, ())
+            for row in snapshot.rows
+            for item in (SectorIndexRow.from_mapping(row, kind),)
+            if item.trade_date == publication.target_trade_date
+        }
+        result: dict[str, RankingExtras] = {}
+        for ranking in rankings:
+            observation = ranking.observation
+            key = (observation.sector_type, observation.sector_code)
+            index = indices.get(key)
+            current = history.get(publication.target_trade_date, ())
+            amount = metric_at(current, *key, MetricKind.AMOUNT).metric_value
+            ratio = metric_at(current, *key, MetricKind.RATIO).metric_value
+            points = [
+                metric_at(history.get(day, ()), *key, observation.metric_kind) for day in dates
+            ]
+            available_days = sum(not point.missing for point in points)
+            on_list_count = None
+            if available_days and side is not RankSide.ALL:
+                on_list_count = sum(
+                    point.in_top if side is RankSide.TOP else point.in_bottom for point in points
+                )
+            result[observation.sector_code] = RankingExtras(
+                index.pct_change if index else None,
+                amount * Decimal(100_000_000) if amount is not None else None,
+                ratio,
+                on_list_count,
+                available_days,
+            )
+        return result
+
+    def snapshots(
+        self, publication: RadarPublication
+    ) -> dict[PublicationSourceGroup, list[SourceSnapshot]]:
+        """Load exact source revisions, never global latest membership or provider data."""
+        grouped: dict[PublicationSourceGroup, list[SourceSnapshot]] = {}
+        for record in self.repository.load_publication_sources(publication.publication_id):
+            grouped.setdefault(record.source_group, []).append(record.snapshot)
+        return grouped
+
+    def history(self, target: date, sector_type: SectorType, sector_code: str) -> SectorHistory:
+        """Return an exact-date publication and its compatible, past-only rank trajectory."""
+        publication = self.repository.get_successful_publication(target)
+        if publication is None:
+            return SectorHistory(
+                "no_data", target, None, None, sector_type, sector_code, None, (), 0
+            )
+        publications, rows, dates = self.history_data(publication)
+        current_rows = rows.get(target, ())
+        name = next(
+            (
+                row.observation.sector_name
+                for row in current_rows
+                if row.observation.sector_type is sector_type
+                and row.observation.sector_code == sector_code
+            ),
+            None,
+        )
+        points = tuple(
+            HistoryPoint(
+                day,
+                publications[day].publication_id if day in publications else None,
+                metric_at(rows.get(day, ()), sector_type, sector_code, MetricKind.AMOUNT),
+                metric_at(rows.get(day, ()), sector_type, sector_code, MetricKind.RATIO),
+                metric_at(rows.get(day, ()), sector_type, sector_code, MetricKind.SWING),
+            )
+            for day in dates
+        )
+        return SectorHistory(
+            "success" if name is not None else "no_data",
+            target,
+            target,
+            publication,
+            sector_type,
+            sector_code,
+            name,
+            points,
+            sum(
+                not point.amount.missing or not point.ratio.missing or not point.swing.missing
+                for point in points
+            ),
+        )
+
+    def detail(self, target: date, sector_type: SectorType, sector_code: str) -> SectorDetail:
+        """Project independently sourced metrics and same-day overlap for confirmed members."""
+        history = self.history(target, sector_type, sector_code)
+        keys = ("pct_change", "net_amount_yuan", "active_buy_net_amount_yuan")
+        empty = {key: MemberLeaders((), ()) for key in keys}
+        summary = {kind.value: HistoryMetric() for kind in MetricKind}
+        if history.publication is None or history.status == "no_data":
+            return SectorDetail(history, None, None, summary, (), empty, ())
+        latest = next((point for point in history.points if point.trade_date == target), None)
+        if latest:
+            summary = {kind.value: getattr(latest, kind.value) for kind in MetricKind}
+        snapshots = self.snapshots(history.publication)
+        indices = [
+            SectorIndexRow.from_mapping(row, kind)
+            for group, kind in (
+                (PublicationSourceGroup.CONCEPT_INDICES, SectorType.CONCEPT),
+                (PublicationSourceGroup.INDUSTRY_INDICES, SectorType.INDUSTRY),
+            )
+            for snapshot in snapshots.get(group, ())
+            for row in snapshot.rows
+        ]
+        index = next(
+            (
+                row
+                for row in indices
+                if row.sector_type is sector_type
+                and row.sector_code == sector_code
+                and row.trade_date == target
+            ),
+            None,
+        )
+        basics = {
+            item.ts_code: item
+            for snapshot in snapshots.get(PublicationSourceGroup.STOCK_BASICS, ())
+            for row in snapshot.rows
+            for item in (StockBasicRow.from_mapping(row),)
+            if is_current_listed_stock(item, target)
+        }
+        memberships: dict[str, dict[str, str]] = {}
+        for snapshot in snapshots.get(PublicationSourceGroup.MEMBERS, ()):
+            for row in snapshot.rows:
+                member = SectorMemberRow.from_mapping(row)
+                if member.trade_date == target and member.stock_code in basics:
+                    memberships.setdefault(member.sector_code, {})[member.stock_code] = (
+                        member.stock_name
+                    )
+        daily = {
+            item.ts_code: item
+            for snapshot in snapshots.get(PublicationSourceGroup.DAILY, ())
+            for row in snapshot.rows
+            for item in (DailyRow.from_mapping(row),)
+            if item.trade_date == target
+        }
+        main = {
+            item.ts_code: item
+            for snapshot in snapshots.get(PublicationSourceGroup.MONEYFLOW_DC, ())
+            for row in snapshot.rows
+            for item in (MoneyflowDcRow.from_mapping(row),)
+            if item.trade_date == target
+        }
+        active = {
+            item.ts_code: item
+            for snapshot in snapshots.get(PublicationSourceGroup.MONEYFLOW, ())
+            for row in snapshot.rows
+            for item in (MoneyflowRow.from_mapping(row),)
+            if item.trade_date == target
+        }
+        members = tuple(
+            DetailMember(
+                code,
+                name,
+                daily[code].pct_chg if code in daily else None,
+                main[code].net_amount_yuan if code in main else None,
+                active[code].active_buy_net_amount_yuan if code in active else None,
+            )
+            for code, name in sorted(memberships.get(sector_code, {}).items())
+        )
+        leaders = {key: member_leaders(members, key) for key in keys}
+        current_set = set(memberships.get(sector_code, {}))
+        similar: list[SimilarSector] = []
+        if current_set:
+            for candidate in indices:
+                if (candidate.sector_type, candidate.sector_code) == (
+                    sector_type,
+                    sector_code,
+                ) or candidate.trade_date != target:
+                    continue
+                other = set(memberships.get(candidate.sector_code, {}))
+                if not other:
+                    continue
+                intersection, union = len(current_set & other), len(current_set | other)
+                if intersection:
+                    similar.append(
+                        SimilarSector(
+                            candidate.sector_type,
+                            candidate.sector_code,
+                            candidate.name,
+                            Decimal(intersection) / Decimal(union),
+                            intersection,
+                            union,
+                        )
+                    )
+        leading = None
+        if index is not None and index.leading_code:
+            basic = basics.get(index.leading_code)
+            leading = LeadingStock(index.leading_code, basic.name if basic else None)
+        return SectorDetail(
+            history,
+            index.pct_change if index else None,
+            leading,
+            summary,
+            members,
+            leaders,
+            tuple(
+                sorted(
+                    similar,
+                    key=lambda item: (
+                        -item.overlap_ratio,
+                        item.sector_code,
+                        item.sector_type.value,
+                    ),
+                )[:4]
+            ),
+        )
+
+
+def metric_at(
+    rows: Sequence[RankedMetric], sector_type: SectorType, sector_code: str, kind: MetricKind
+) -> HistoryMetric:
+    """Select compatible rank values; pool thresholds use each day's actual percentile."""
+    pool = [
+        row
+        for row in rows
+        if row.observation.sector_type is sector_type
+        and row.observation.metric_kind is kind
+        and row.observation.metric_version == _METRIC_VERSIONS[kind]
+    ]
+    size = sum(row.rank_position is not None for row in pool)
+    row = next((row for row in pool if row.observation.sector_code == sector_code), None)
+    if row is None:
+        return HistoryMetric(pool_size=size)
+    percentile = row.rank_percentile
+    return HistoryMetric(
+        row.rank_position,
+        percentile,
+        size,
+        row.observation.value,
+        row.rank_position is None,
+        percentile is not None and percentile >= 90,
+        percentile is not None and percentile <= 10,
+    )
+
+
+def member_leaders(members: Sequence[DetailMember], key: str) -> MemberLeaders:
+    """Exclude missing values and break metric ties by stock code on both sides."""
+    values: list[tuple[DetailMember, Decimal]] = []
+    for member in members:
+        value = {
+            "pct_change": member.pct_change,
+            "net_amount_yuan": member.net_amount_yuan,
+            "active_buy_net_amount_yuan": member.active_buy_net_amount_yuan,
+        }[key]
+        if value is not None:
+            values.append((member, value))
+    return MemberLeaders(
+        tuple(item[0] for item in sorted(values, key=lambda item: (-item[1], item[0].ts_code))[:5]),
+        tuple(item[0] for item in sorted(values, key=lambda item: (item[1], item[0].ts_code))[:5]),
+    )

zhixing-server/src/zhixing_server/modules/sector_radar/application/read.py

@@ -3,7 +3,7 @@
 from __future__ import annotations
 
 from collections.abc import Iterator, Sequence
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from datetime import date
 from enum import StrEnum
 from typing import Literal
@@ -27,6 +27,7 @@ from ..domain.persistence import (
     StockMembershipEntry,
 )
 from ..domain.ranking import select_percentile_side, select_rank_change_side
+from .details import RankingExtras, ReadRadarDetails
 
 ReadStatus = Literal["success", "no_data"]
 
@@ -106,6 +107,7 @@ class RankingPage:
     definition: RadarMetricDefinition
     rows: tuple[RankedMetric, ...]
     total: int
+    extras: dict[str, RankingExtras] = field(default_factory=lambda: dict[str, RankingExtras]())
 
 
 @dataclass(frozen=True, slots=True)
@@ -281,6 +283,11 @@ class ReadSectorRadar:
             definition=definition,
             rows=searched[start : start + query.page_size],
             total=len(searched),
+            extras=ReadRadarDetails(self.repository).ranking_extras(
+                publication, searched[start : start + query.page_size], query.side
+            )
+            if query.view in {RadarView.AMOUNT, RadarView.RATIO}
+            else {},
         )
 
     def stock_membership(self, query: StockSectorQuery) -> StockSectorMembership:

zhixing-server/src/zhixing_server/modules/sector_radar/domain/normalize.py

@@ -12,6 +12,7 @@ from .persistence import MembershipRecord, StockFactRecord
 from .source import (
     DailyRow,
     MoneyflowDcRow,
+    MoneyflowRow,
     SectorIndexRow,
     SectorMemberRow,
     SourceContractError,
@@ -111,6 +112,7 @@ def normalize_stock_facts(
     suspensions: SourceResult[SuspendRow],
     daily: SourceResult[DailyRow],
     moneyflow: SourceResult[MoneyflowDcRow],
+    active_moneyflow: SourceResult[MoneyflowRow] | None = None,
 ) -> tuple[StockFactRecord, ...]:
     """Build normalized yuan facts without collapsing missing states into zero.
 
@@ -121,6 +123,7 @@ def normalize_stock_facts(
         suspensions: Same-date suspend/resume events.
         daily: Same-date stock turnover rows in source units.
         moneyflow: Same-date DC main-moneyflow rows in source units.
+        active_moneyflow: Optional independently sourced active-order flow in ten-thousand yuan.
 
     Returns:
         One deterministic fact per candidate code under a content-derived revision.
@@ -145,11 +148,25 @@ def normalize_stock_facts(
             }
         )
     )
+    if active_moneyflow is not None:
+        source_snapshot_ids = tuple(
+            sorted(
+                set(source_snapshot_ids)
+                | {snapshot.snapshot_id for snapshot in active_moneyflow.snapshots}
+            )
+        )
+    if active_moneyflow is not None and any(
+        row.trade_date != target_trade_date for row in active_moneyflow.rows
+    ):
+        raise SourceContractError("moneyflow rows must match target trade date")
+    active_by_code = _unique_index(
+        active_moneyflow.rows if active_moneyflow else (), lambda row: row.ts_code, "moneyflow"
+    )
     revision_payload = json.dumps(
         {
             "target_trade_date": target_trade_date.isoformat(),
             "source_snapshot_ids": source_snapshot_ids,
-            "normalizer": "zhixing_stock_fact_v1",
+            "normalizer": "zhixing_stock_fact_v2",
         },
         sort_keys=True,
         separators=(",", ":"),
@@ -192,6 +209,16 @@ def normalize_stock_facts(
                 status=status,
                 turnover_yuan=turnover_yuan,
                 net_amount_yuan=net_amount_yuan,
+                pct_change=(
+                    daily_row.pct_chg
+                    if daily_row is not None and status is not StockFactStatus.LIFECYCLE_INVALID
+                    else None
+                ),
+                active_buy_net_amount_yuan=(
+                    active_by_code[ts_code].active_buy_net_amount_yuan
+                    if ts_code in active_by_code and status is not StockFactStatus.LIFECYCLE_INVALID
+                    else None
+                ),
             )
         )
     return tuple(records)

zhixing-server/src/zhixing_server/modules/sector_radar/domain/persistence.py

@@ -109,6 +109,8 @@ class StockFactRecord:
     status: StockFactStatus
     turnover_yuan: Decimal | None = None
     net_amount_yuan: Decimal | None = None
+    pct_change: Decimal | None = None
+    active_buy_net_amount_yuan: Decimal | None = None
 
     def __post_init__(self) -> None:
         """Preserve source traceability and stock fact null semantics."""
@@ -122,6 +124,8 @@ class StockFactRecord:
             _validate_digest(value, "source_snapshot_id")
         if not self.ts_code.strip():
             raise ValueError("ts_code must not be empty")
+        _validate_optional_decimal(self.pct_change, "pct_change")
+        _validate_optional_decimal(self.active_buy_net_amount_yuan, "active_buy_net_amount_yuan")
         _validate_optional_decimal(self.turnover_yuan, "turnover_yuan")
         _validate_optional_decimal(self.net_amount_yuan, "net_amount_yuan")
         if self.status is StockFactStatus.AVAILABLE:
@@ -149,14 +153,17 @@ class RankingRecord:
 
 @dataclass(frozen=True, slots=True)
 class DailyAggregateRecord:
-    """One exact daily strategy input owned by a publication revision."""
+    """One exact daily strategy input and optional source detail owned by a publication."""
 
     publication_id: str
     aggregate: SectorDailyAggregate
+    pct_change: Decimal | None = None
+    leading_code: str | None = None
 
     def __post_init__(self) -> None:
         """Validate the publication foreign identity."""
 
+        _validate_optional_decimal(self.pct_change, "pct_change")
         if not self.publication_id.strip():
             raise ValueError("publication_id must not be empty")
 
@@ -172,6 +179,7 @@ class PublicationSourceGroup(StrEnum):
     SUSPENSIONS = "suspensions"
     DAILY = "daily"
     MONEYFLOW_DC = "moneyflow_dc"
+    MONEYFLOW = "moneyflow"
 
 
 @dataclass(frozen=True, slots=True)
@@ -291,8 +299,14 @@ class SectorRadarRepository(Protocol):
 
     def list_successful_dates(self) -> Sequence[date]: ...
 
+    def load_history_publications(self, target: date) -> Sequence[RadarPublication]: ...
+
     def load_rankings(self, publication_id: str) -> Sequence[RankedMetric]: ...
 
+    def load_publication_rankings(
+        self, publication_ids: Sequence[str]
+    ) -> Sequence[tuple[str, Sequence[RankedMetric]]]: ...
+
     def load_daily_aggregate_history(
         self, target_trade_date: date, *, limit_dates: int
     ) -> Sequence[SectorDailyAggregate]: ...

zhixing-server/src/zhixing_server/modules/sector_radar/domain/ports.py

@@ -5,13 +5,14 @@ from __future__ import annotations
 from collections.abc import Sequence
 from contextlib import AbstractContextManager
 from datetime import date
-from typing import Protocol
+from typing import Protocol, runtime_checkable
 
 from .models import SectorType
 from .source import (
     CapabilityProbeResult,
     DailyRow,
     MoneyflowDcRow,
+    MoneyflowRow,
     SectorIndexRow,
     SectorMemberRow,
     SourceResult,
@@ -51,6 +52,13 @@ class SectorRadarSource(Protocol):
     def probe(self, trade_date: date) -> CapabilityProbeResult: ...
 
 
+@runtime_checkable
+class ActiveMoneyflowSource(Protocol):
+    """Optional stock-detail capability; ranking-only sources remain valid."""
+
+    def fetch_moneyflow(self, trade_date: date) -> SourceResult[MoneyflowRow]: ...
+
+
 class SectorRadarLock(Protocol):
     """Repository seam for a target-date advisory lock."""
 

zhixing-server/src/zhixing_server/modules/sector_radar/domain/source.py

@@ -463,6 +463,27 @@ class MoneyflowDcRow:
         )
 
 
+@dataclass(frozen=True, slots=True)
+class MoneyflowRow:
+    """Active buy/sell net flow; Tushare documents net_mf_amount in ten-thousand yuan."""
+
+    trade_date: date
+    ts_code: str
+    net_mf_amount: Decimal | None
+
+    @property
+    def active_buy_net_amount_yuan(self) -> Decimal | None:
+        """Return yuan while retaining missing observations."""
+        return None if self.net_mf_amount is None else self.net_mf_amount * Decimal(10_000)
+
+    @classmethod
+    def from_mapping(cls, row: Mapping[str, SourceScalar]) -> MoneyflowRow:
+        """Parse one dated active-flow row, rejecting non-finite amounts."""
+        trade_date = _source_date(row, "trade_date")
+        assert trade_date is not None
+        return cls(trade_date, _required_text(row, "ts_code"), _decimal(row, "net_mf_amount"))
+
+
 class CapabilityStatus(StrEnum):
     """Safe capability outcomes that never expose provider error text."""
 

zhixing-server/src/zhixing_server/modules/sector_radar/infrastructure/memory.py

@@ -435,6 +435,14 @@ class InMemorySectorRadarRepository:
             )
         )
 
+    def load_history_publications(self, target: date) -> Sequence[RadarPublication]:
+        """Return the latest successful revision per past date, newest first."""
+        return tuple(
+            self._latest_success_for_date(day)
+            for day in self.list_successful_dates()
+            if day <= target
+        )[:30]
+
     def load_rankings(self, publication_id: str) -> Sequence[RankedMetric]:
         """Load every ranking projection owned by one publication."""
 
@@ -455,6 +463,12 @@ class InMemorySectorRadarRepository:
             )
         )
 
+    def load_publication_rankings(
+        self, publication_ids: Sequence[str]
+    ) -> Sequence[tuple[str, Sequence[RankedMetric]]]:
+        """Read exact immutable revisions selected by the history reader."""
+        return tuple((key, self.load_rankings(key)) for key in publication_ids)
+
     def load_daily_aggregate_history(
         self, target_trade_date: date, *, limit_dates: int
     ) -> Sequence[SectorDailyAggregate]:

zhixing-server/src/zhixing_server/modules/sector_radar/infrastructure/postgres.py

@@ -379,6 +379,8 @@ class PostgresSectorRadarRepository:
                 item.status.value,
                 item.turnover_yuan,
                 item.net_amount_yuan,
+                item.pct_change,
+                item.active_buy_net_amount_yuan,
             )
             for item in items
         )
@@ -392,6 +394,8 @@ class PostgresSectorRadarRepository:
                 "status",
                 "turnover_yuan",
                 "net_amount_yuan",
+                "pct_change",
+                "active_buy_net_amount_yuan",
             ),
             ("fact_revision", "ts_code"),
             rows,
@@ -422,6 +426,8 @@ class PostgresSectorRadarRepository:
                 item.aggregate.turnover_yuan,
                 item.aggregate.membership_coverage,
                 item.aggregate.moneyflow_coverage,
+                item.pct_change,
+                item.leading_code,
             )
             for item in items
         )
@@ -439,6 +445,8 @@ class PostgresSectorRadarRepository:
                 "turnover_yuan",
                 "membership_coverage",
                 "moneyflow_coverage",
+                "pct_change",
+                "leading_code",
             ),
             ("publication_id", "sector_type", "sector_code"),
             rows,
@@ -566,6 +574,8 @@ class PostgresSectorRadarRepository:
                     "status",
                     "turnover_yuan",
                     "net_amount_yuan",
+                    "pct_change",
+                    "active_buy_net_amount_yuan",
                 ),
                 ("fact_revision", "ts_code"),
                 tuple(
@@ -577,6 +587,8 @@ class PostgresSectorRadarRepository:
                         item.status.value,
                         item.turnover_yuan,
                         item.net_amount_yuan,
+                        item.pct_change,
+                        item.active_buy_net_amount_yuan,
                     )
                     for item in stock_items
                 ),
@@ -596,6 +608,8 @@ class PostgresSectorRadarRepository:
                     "turnover_yuan",
                     "membership_coverage",
                     "moneyflow_coverage",
+                    "pct_change",
+                    "leading_code",
                 ),
                 ("publication_id", "sector_type", "sector_code"),
                 tuple(
@@ -611,6 +625,8 @@ class PostgresSectorRadarRepository:
                         item.aggregate.turnover_yuan,
                         item.aggregate.membership_coverage,
                         item.aggregate.moneyflow_coverage,
+                        item.pct_change,
+                        item.leading_code,
                     )
                     for item in aggregate_items
                 ),
@@ -798,6 +814,19 @@ class PostgresSectorRadarRepository:
             ).fetchall()
         return tuple(row[0] for row in rows)
 
+    def load_history_publications(self, target: date) -> Sequence[RadarPublication]:
+        """Batch-load at most thirty latest successful date revisions, excluding future data."""
+        with self._connection() as connection:
+            rows = connection.execute(
+                self._publication_select().replace(
+                    "SELECT ", "SELECT DISTINCT ON (target_trade_date) ", 1
+                )
+                + " WHERE status = 'success' AND target_trade_date <= %s "
+                + "ORDER BY target_trade_date DESC, finished_at DESC, id DESC LIMIT 30",
+                (target,),
+            ).fetchall()
+        return tuple(self._publication_from_row(row) for row in rows)
+
     def load_rankings(self, publication_id: str) -> Sequence[RankedMetric]:
         """Load all ranking projections for one publication in deterministic order."""
 
@@ -816,6 +845,31 @@ class PostgresSectorRadarRepository:
             ).fetchall()
         return tuple(self._ranking_from_row(row) for row in rows)
 
+    def load_publication_rankings(
+        self, publication_ids: Sequence[str]
+    ) -> Sequence[tuple[str, Sequence[RankedMetric]]]:
+        """Read all requested immutable revisions in one query, avoiding date races."""
+        if not publication_ids:
+            return ()
+        with self._connection() as connection:
+            rows = connection.execute(
+                """
+                SELECT publication_id, trade_date, sector_type, sector_code, sector_name,
+                       metric_kind, metric_version, implementation_kind, unit, metric_value,
+                       quality, member_count, valid_sample_count, membership_coverage,
+                       moneyflow_coverage, rank_position, rank_percentile, rank_changes
+                FROM sector_radar_ranking
+                WHERE publication_id = ANY(%s)
+                ORDER BY publication_id, sector_type, metric_kind, rank_position NULLS LAST,
+                         sector_code
+                """,
+                (list(publication_ids),),
+            ).fetchall()
+        grouped: dict[str, list[RankedMetric]] = {}
+        for row in rows:
+            grouped.setdefault(str(row[0]), []).append(self._ranking_from_row(row[1:]))
+        return tuple((key, tuple(grouped.get(key, ()))) for key in publication_ids)
+
     def load_daily_aggregate_history(
         self, target_trade_date: date, *, limit_dates: int
     ) -> Sequence[SectorDailyAggregate]:

zhixing-server/src/zhixing_server/modules/sector_radar/infrastructure/tushare.py

@@ -22,6 +22,7 @@ from ..domain.source import (
     CapabilityStatus,
     DailyRow,
     MoneyflowDcRow,
+    MoneyflowRow,
     SectorIndexRow,
     SectorMemberRow,
     SourceContractError,
@@ -61,6 +62,7 @@ FIELDS: dict[str, tuple[str, ...]] = {
     ),
     "suspend_d": ("ts_code", "trade_date", "suspend_timing", "suspend_type"),
     "daily": ("ts_code", "trade_date", "close", "pre_close", "pct_chg", "vol", "amount"),
+    "moneyflow": ("trade_date", "ts_code", "net_mf_amount"),
     "moneyflow_dc": (
         "trade_date",
         "ts_code",
@@ -80,6 +82,7 @@ ROW_LIMITS: dict[str, int | None] = {
     "suspend_d": None,
     "daily": 6_000,
     "moneyflow_dc": 6_000,
+    "moneyflow": 6_000,
 }
 
 _SECTOR_TYPE_PARAM = {
@@ -312,6 +315,19 @@ class TushareSectorRadarAdapter:
         self._require_unique(rows, key=lambda row: row.ts_code, api_name="daily")
         return SourceResult((snapshot,), tuple(sorted(rows, key=lambda row: row.ts_code)))
 
+    def fetch_moneyflow(self, trade_date: date) -> SourceResult[MoneyflowRow]:
+        """Fetch optional active-order flow, fail closed on truncation or wrong dates."""
+        snapshot = self._fetch_snapshot(
+            "moneyflow",
+            {"trade_date": trade_date.strftime("%Y%m%d")},
+            target_trade_date=trade_date,
+        )
+        self._reject_limit(snapshot)
+        rows = tuple(MoneyflowRow.from_mapping(row) for row in snapshot.rows)
+        self._require_target_date(rows, trade_date, "moneyflow")
+        self._require_unique(rows, key=lambda row: row.ts_code, api_name="moneyflow")
+        return SourceResult((snapshot,), tuple(sorted(rows, key=lambda row: row.ts_code)))
+
     def fetch_moneyflow_dc(
         self,
         trade_date: date,

zhixing-server/src/zhixing_server/modules/sector_radar/presentation/http.py

@@ -9,9 +9,15 @@ from decimal import Decimal
 from typing import Annotated, Literal
 
 from fastapi import APIRouter, Depends, HTTPException, Path, Query
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, ConfigDict, Field
 
 from ....bootstrap.config import Settings, get_settings
+from ..application.details import (
+    RankingExtras,
+    ReadRadarDetails,
+    SectorDetail,
+    SectorHistory,
+)
 from ..application.read import (
     STOCK_SECTOR_CONCEPT_LIMIT,
     RadarDateIndex,
@@ -101,6 +107,106 @@ class RadarRankingRowResponse(BaseModel):
     rank_percentile: Decimal | None = Field(default=None, gt=0, le=100)
     rank_change_days: int = Field(ge=1, le=5)
     rank_change: int | None
+    pct_change: Decimal | None = None
+    daily_net_amount_yuan: Decimal | None = None
+    daily_ratio: Decimal | None = None
+    on_list_count: int | None = Field(default=None, ge=0, le=30)
+    history_available_days: int = Field(default=0, ge=0, le=30)
+
+
+class RadarDetailModel(BaseModel):
+    """Validate typed application projections without coupling them to Pydantic."""
+
+    model_config = ConfigDict(from_attributes=True)
+
+
+class RadarHistoryMetricResponse(RadarDetailModel):
+    """One comparable rank with the actual daily pool and missing state."""
+
+    rank_position: int | None
+    rank_percentile: Decimal | None
+    pool_size: int
+    metric_value: Decimal | None
+    missing: bool
+    in_top: bool
+    in_bottom: bool
+
+
+class RadarHistoryPointResponse(RadarDetailModel):
+    """Three independent ranks for one trading date."""
+
+    trade_date: date
+    publication_id: str | None
+    amount: RadarHistoryMetricResponse
+    ratio: RadarHistoryMetricResponse
+    swing: RadarHistoryMetricResponse
+
+
+class RadarSectorIdentityResponse(RadarDetailModel):
+    """Exact-date identity; a missing date never borrows a nearby publication."""
+
+    status: Literal["success", "no_data"]
+    requested_trade_date: date
+    trade_date: date | None
+    publication: RadarPublicationResponse | None
+    sector_type: SectorType
+    sector_code: str
+    sector_name: str | None
+
+
+class RadarHistoryResponse(RadarSectorIdentityResponse):
+    """At most thirty trading dates, with explicit unavailable points."""
+
+    points: list[RadarHistoryPointResponse]
+    window_size: int
+    available_days: int
+
+
+class RadarMemberResponse(RadarDetailModel):
+    """A listed member's independently nullable stock metrics, in yuan."""
+
+    ts_code: str
+    name: str
+    pct_change: Decimal | None
+    net_amount_yuan: Decimal | None
+    active_buy_net_amount_yuan: Decimal | None
+
+
+class RadarLeadingStockResponse(RadarDetailModel):
+    """Provider-designated leader; its name may be absent from the listed universe."""
+
+    ts_code: str
+    name: str | None
+
+
+class RadarMemberLeadersResponse(RadarDetailModel):
+    """Up to five observations per side, excluding missing values."""
+
+    top: list[RadarMemberResponse]
+    bottom: list[RadarMemberResponse]
+
+
+class RadarSimilarSectorResponse(RadarDetailModel):
+    """Same-publication Jaccard overlap, including cross-type candidates."""
+
+    sector_type: SectorType
+    sector_code: str
+    sector_name: str
+    overlap_ratio: Decimal
+    intersection_count: int
+    union_count: int
+
+
+class RadarDetailResponse(RadarSectorIdentityResponse):
+    """Persisted sector detail with exact-version ranks, members and overlap."""
+
+    pct_change: Decimal | None
+    leading_stock: RadarLeadingStockResponse | None
+    summary: dict[str, RadarHistoryMetricResponse]
+    history: RadarHistoryResponse
+    members: list[RadarMemberResponse]
+    leaders: dict[str, RadarMemberLeadersResponse]
+    similar_sectors: list[RadarSimilarSectorResponse]
 
 
 def _empty_ranking_rows() -> list[RadarRankingRowResponse]:
@@ -143,8 +249,8 @@ class StockSectorMembershipResponse(BaseModel):
     ts_code: str
     requested_trade_date: date
     trade_date: date | None
-    industries: list[SectorRefResponse] = Field(default_factory=list)
-    concepts: list[SectorRefResponse] = Field(default_factory=list)
+    industries: list[SectorRefResponse] = Field(default_factory=lambda: list[SectorRefResponse]())
+    concepts: list[SectorRefResponse] = Field(default_factory=lambda: list[SectorRefResponse]())
     concept_total: int = Field(ge=0)
     concept_limit: int = Field(ge=1, le=100)
 
@@ -223,6 +329,91 @@ def get_sector_radar_rankings(
         raise _storage_error() from exc
 
 
+@sector_radar_router.get(
+    "/sectors/{sector_type}/{sector_code}/history", response_model=RadarHistoryResponse
+)
+def get_sector_history(
+    reader: Annotated[ReadSectorRadar, Depends(get_sector_radar_reader)],
+    sector_type: SectorType,
+    sector_code: Annotated[str, Path(min_length=1, max_length=32, pattern=r"\S")],
+    trade_date: date,
+) -> RadarHistoryResponse:
+    """Read an exact-date sector history without provider IO or future fallback."""
+    try:
+        return _history_response(
+            ReadRadarDetails(reader.repository).history(
+                trade_date, sector_type, sector_code.strip()
+            )
+        )
+    except SectorRadarRepositoryError as exc:
+        raise _storage_error() from exc
+
+
+@sector_radar_router.get(
+    "/sectors/{sector_type}/{sector_code}/detail", response_model=RadarDetailResponse
+)
+def get_sector_detail(
+    reader: Annotated[ReadSectorRadar, Depends(get_sector_radar_reader)],
+    sector_type: SectorType,
+    sector_code: Annotated[str, Path(min_length=1, max_length=32, pattern=r"\S")],
+    trade_date: date,
+) -> RadarDetailResponse:
+    """Read independently sourced stock metrics and confirmed member-set overlap."""
+    try:
+        return _detail_response(
+            ReadRadarDetails(reader.repository).detail(trade_date, sector_type, sector_code.strip())
+        )
+    except SectorRadarRepositoryError as exc:
+        raise _storage_error() from exc
+
+
+def _history_response(history: SectorHistory) -> RadarHistoryResponse:
+    """Convert publication metadata explicitly at the HTTP boundary."""
+    return RadarHistoryResponse(
+        status="success" if history.status == "success" else "no_data",
+        requested_trade_date=history.requested_trade_date,
+        trade_date=history.trade_date,
+        publication=_publication_response(history.publication) if history.publication else None,
+        sector_type=history.sector_type,
+        sector_code=history.sector_code,
+        sector_name=history.sector_name,
+        points=[RadarHistoryPointResponse.model_validate(point) for point in history.points],
+        window_size=history.window_size,
+        available_days=history.available_days,
+    )
+
+
+def _detail_response(detail: SectorDetail) -> RadarDetailResponse:
+    """Keep the same resolved publication identity in detail and nested history."""
+    history = _history_response(detail.history)
+    return RadarDetailResponse(
+        status=history.status,
+        requested_trade_date=history.requested_trade_date,
+        trade_date=history.trade_date,
+        publication=history.publication,
+        sector_type=history.sector_type,
+        sector_code=history.sector_code,
+        sector_name=history.sector_name,
+        pct_change=detail.pct_change,
+        leading_stock=RadarLeadingStockResponse.model_validate(detail.leading_stock)
+        if detail.leading_stock
+        else None,
+        summary={
+            key: RadarHistoryMetricResponse.model_validate(value)
+            for key, value in detail.summary.items()
+        },
+        history=history,
+        members=[RadarMemberResponse.model_validate(member) for member in detail.members],
+        leaders={
+            key: RadarMemberLeadersResponse.model_validate(value)
+            for key, value in detail.leaders.items()
+        },
+        similar_sectors=[
+            RadarSimilarSectorResponse.model_validate(value) for value in detail.similar_sectors
+        ],
+    )
+
+
 @sector_radar_router.get(
     "/stocks/{ts_code}/membership", response_model=StockSectorMembershipResponse
 )
@@ -276,7 +467,12 @@ def _rankings_response(page: RankingPage) -> RadarRankingsResponse:
         page=query.page,
         page_size=query.page_size,
         total=page.total,
-        rows=[_ranking_response(row, query.rank_change_days) for row in page.rows],
+        rows=[
+            _ranking_response(
+                row, query.rank_change_days, page.extras.get(row.observation.sector_code)
+            )
+            for row in page.rows
+        ],
     )
 
 
@@ -328,8 +524,11 @@ def _definition_response(
     )
 
 
-def _ranking_response(row: RankedMetric, rank_change_days: int) -> RadarRankingRowResponse:
+def _ranking_response(
+    row: RankedMetric, rank_change_days: int, extras: RankingExtras | None = None
+) -> RadarRankingRowResponse:
     observation = row.observation
+    extras = extras or RankingExtras()
     return RadarRankingRowResponse(
         trade_date=observation.trade_date,
         sector_type=observation.sector_type,
@@ -349,6 +548,11 @@ def _ranking_response(row: RankedMetric, rank_change_days: int) -> RadarRankingR
         rank_percentile=row.rank_percentile,
         rank_change_days=rank_change_days,
         rank_change=row.rank_change(rank_change_days),
+        pct_change=extras.pct_change,
+        daily_net_amount_yuan=extras.daily_net_amount_yuan,
+        daily_ratio=extras.daily_ratio,
+        on_list_count=extras.on_list_count,
+        history_available_days=extras.history_available_days,
     )
 
 

zhixing-server/tests/integration/test_sector_radar_repository.py

@@ -3,13 +3,14 @@ from dataclasses import replace
 from datetime import UTC, date, datetime, timedelta
 from decimal import Decimal
 from pathlib import Path
+from unittest.mock import patch
 
 import psycopg
 import pytest
 from alembic import command
 from alembic.config import Config
 
-from zhixing_server.bootstrap.config import sqlalchemy_database_url
+from zhixing_server.bootstrap.config import Settings, sqlalchemy_database_url
 from zhixing_server.modules.sector_radar.domain.models import (
     MembershipStatus,
     PublicationStatus,
@@ -35,6 +36,11 @@ def prepare_database(database_url: str) -> None:
     config = Config(str(server_root / "alembic.ini"))
     sqlalchemy_url = sqlalchemy_database_url(database_url)
     config.set_main_option("sqlalchemy.url", sqlalchemy_url.replace("%", "%%"))
+    config.config_file_name = None
+    with patch(
+        "zhixing_server.bootstrap.config.get_settings",
+        return_value=Settings(database_url=database_url),
+    ):
         command.upgrade(config, "head")
 
 
@@ -111,12 +117,22 @@ def test_postgres_sector_radar_revisions_and_last_good() -> None:
                         status=StockFactStatus.AVAILABLE,
                         turnover_yuan=Decimal("1000"),
                         net_amount_yuan=Decimal("100"),
+                        pct_change=Decimal("1.25"),
+                        active_buy_net_amount_yuan=Decimal("-25000"),
                     ),
                 )
             ).inserted
             == 1
         )
 
+        with psycopg.connect(database_url) as connection:
+            detail_fact = connection.execute(
+                "SELECT pct_change, active_buy_net_amount_yuan "
+                "FROM sector_radar_stock_fact WHERE fact_revision = %s",
+                (fact_revision,),
+            ).fetchone()
+            assert detail_fact == (Decimal("1.25"), Decimal("-25000"))
+
         running = RadarPublication(
             publication_id=publication_ids[0],
             target_trade_date=TARGET_DATE,

zhixing-server/tests/unit/sector_radar/test_build.py

@@ -639,3 +639,229 @@ def test_history_uses_latest_successful_input_revision_for_a_date() -> None:
     assert second.status == "success"
     assert len(history) == 2
     assert all(item.net_amount_yuan == Decimal(300_000) for item in history)
+
+
+def test_detail_history_is_thirty_sessions_past_only_and_latest_revision() -> None:
+    from zhixing_server.modules.sector_radar.application.details import ReadRadarDetails
+
+    repository = InMemorySectorRadarRepository()
+    end = TARGET_DATE + timedelta(days=33)
+    summary = BuildSectorRadar(FakeRadarSource(), repository, now_fn=lambda: NOW).execute(
+        BuildSectorRadarCommand(start_date=TARGET_DATE, end_date=end)
+    )
+    assert summary.status == "success"
+    target = end - timedelta(days=1)
+    replacement = BuildSectorRadar(
+        FakeRadarSource(net_scale=Decimal(2)),
+        repository,
+        now_fn=lambda: NOW + timedelta(hours=1),
+    ).execute(BuildSectorRadarCommand(trade_date=target))
+    reader = ReadRadarDetails(repository)
+    history = reader.history(target, SectorType.CONCEPT, "BK0001.DC")
+    assert len(history.points) == 30
+    assert history.points[0].trade_date == target - timedelta(days=29)
+    assert history.points[-1].trade_date == target
+    assert len({point.trade_date for point in history.points}) == 30
+    assert history.points[-1].publication_id == replacement.outcomes[0].publication_id
+    assert history.points[-1].amount.metric_value == Decimal("0.003")
+    assert history.available_days == 30
+    assert (
+        reader.history(TARGET_DATE - timedelta(days=1), SectorType.CONCEPT, "BK0001.DC").status
+        == "no_data"
+    )
+
+    old = repository.get_successful_publication(target - timedelta(days=1))
+    assert old is not None
+    repository.publications[old.publication_id] = replace(old, source_version="incompatible-v2")
+    isolated = reader.history(target, SectorType.CONCEPT, "BK0001.DC")
+    assert isolated.points[-2].amount.missing
+    assert isolated.available_days == 29
+
+
+def test_optional_moneyflow_failure_keeps_main_rankings_and_nullable_details() -> None:
+    from zhixing_server.modules.sector_radar.application.details import ReadRadarDetails
+    from zhixing_server.modules.sector_radar.domain.source import MoneyflowRow
+
+    class UnavailableActiveSource(FakeRadarSource):
+        def fetch_moneyflow(self, trade_date: date) -> SourceResult[MoneyflowRow]:
+            raise SourceContractError("optional provider unavailable")
+
+    repository = InMemorySectorRadarRepository()
+    summary = BuildSectorRadar(UnavailableActiveSource(), repository, now_fn=lambda: NOW).execute(
+        BuildSectorRadarCommand(trade_date=TARGET_DATE)
+    )
+    assert summary.status == "success"
+    detail = ReadRadarDetails(repository).detail(TARGET_DATE, SectorType.CONCEPT, "BK0001.DC")
+    assert detail.pct_change == Decimal(1)
+    assert len(detail.members) == 5
+    assert all(member.active_buy_net_amount_yuan is None for member in detail.members)
+    assert detail.members[0].net_amount_yuan == Decimal(10000)
+    assert detail.members[0].pct_change == Decimal(0)
+    assert detail.leaders["active_buy_net_amount_yuan"].top == ()
+    assert detail.summary["amount"].metric_value == Decimal("0.0015")
+
+
+def test_detail_jaccard_uses_same_day_current_listed_members_and_independent_values() -> None:
+    from zhixing_server.modules.sector_radar.application.details import ReadRadarDetails
+    from zhixing_server.modules.sector_radar.domain.source import MoneyflowRow
+
+    class DetailSource(FakeRadarSource):
+        def fetch_sector_members(
+            self, trade_date: date, sector_codes: Sequence[str]
+        ) -> SourceResult[SectorMemberRow]:
+            rows = tuple(
+                SectorMemberRow(trade_date, code, f"00000{index}.SZ", f"股票{index}")
+                for code in sector_codes
+                for index in ((1, 2, 6) if code == "BK0001.DC" else (2, 3))
+            )
+            return self._result("dc_member", trade_date, rows)
+
+        def fetch_moneyflow(self, trade_date: date) -> SourceResult[MoneyflowRow]:
+            raw = (
+                {
+                    "trade_date": trade_date.isoformat(),
+                    "ts_code": "000001.SZ",
+                    "net_mf_amount": "-2.5",
+                },
+            )
+            snapshot = build_source_snapshot(
+                api_name="moneyflow",
+                params={},
+                rows=raw,
+                target_trade_date=trade_date,
+                observed_at=NOW,
+            )
+            return SourceResult((snapshot,), tuple(MoneyflowRow.from_mapping(row) for row in raw))
+
+    repository = InMemorySectorRadarRepository()
+    result = BuildSectorRadar(DetailSource(), repository, now_fn=lambda: NOW).execute(
+        BuildSectorRadarCommand(trade_date=TARGET_DATE)
+    )
+    assert result.status == "success"
+    reader = ReadRadarDetails(repository)
+    detail = reader.detail(TARGET_DATE, SectorType.CONCEPT, "BK0001.DC")
+    assert [member.ts_code for member in detail.members] == ["000001.SZ", "000002.SZ"]
+    assert detail.members[0].active_buy_net_amount_yuan == Decimal(-25000)
+    assert detail.members[0].net_amount_yuan == Decimal(10000)
+    assert detail.members[1].active_buy_net_amount_yuan is None
+    assert len(detail.leaders["active_buy_net_amount_yuan"].top) == 1
+    assert detail.similar_sectors[0].intersection_count == 1
+    assert detail.similar_sectors[0].union_count == 3
+    assert detail.similar_sectors[0].overlap_ratio == Decimal(1) / Decimal(3)
+    assert detail.similar_sectors[0].sector_type is SectorType.INDUSTRY
+    # A later build with different membership cannot alter the older detail.
+    BuildSectorRadar(FakeRadarSource(), repository, now_fn=lambda: NOW).execute(
+        BuildSectorRadarCommand(trade_date=TARGET_DATE + timedelta(days=1))
+    )
+    assert reader.detail(TARGET_DATE, SectorType.CONCEPT, "BK0001.DC") == detail
+
+
+def test_detail_history_and_ranking_extras_http_use_the_same_publication() -> None:
+    from fastapi.testclient import TestClient
+
+    from zhixing_server.bootstrap.app import create_app
+    from zhixing_server.modules.sector_radar.application.read import ReadSectorRadar
+    from zhixing_server.modules.sector_radar.presentation.http import get_sector_radar_reader
+
+    repository = InMemorySectorRadarRepository()
+    result = BuildSectorRadar(FakeRadarSource(), repository, now_fn=lambda: NOW).execute(
+        BuildSectorRadarCommand(trade_date=TARGET_DATE)
+    )
+    app = create_app()
+    app.dependency_overrides[get_sector_radar_reader] = lambda: ReadSectorRadar(repository)
+    with TestClient(app) as client:
+        params = {"trade_date": TARGET_DATE.isoformat()}
+        base = "/api/v1/sector-radar/sectors/concept/BK0001.DC"
+        history = client.get(base + "/history", params=params)
+        detail = client.get(base + "/detail", params=params)
+        ranking = client.get(
+            "/api/v1/sector-radar/rankings", params={**params, "view": "amount", "side": "top"}
+        )
+        assert history.status_code == detail.status_code == ranking.status_code == 200
+        payload = detail.json()
+        assert payload["publication"]["publication_id"] == result.outcomes[0].publication_id
+        assert payload["history"] == history.json()
+        assert payload["pct_change"] == "1"
+        assert payload["members"][0]["active_buy_net_amount_yuan"] is None
+        row = ranking.json()["rows"][0]
+        assert row["pct_change"] == "1"
+        assert Decimal(row["daily_net_amount_yuan"]) == 150000
+        assert Decimal(row["daily_ratio"]) == Decimal("0.03")
+        assert row["on_list_count"] == row["history_available_days"] == 1
+        assert client.get(base + "/detail").status_code == 422
+        absent = client.get(base + "/detail", params={"trade_date": "2020-01-01"})
+        assert absent.json()["status"] == "no_data"
+        assert absent.json()["members"] == []
+
+
+@pytest.mark.integration
+def test_postgres_detail_migration_and_build_roundtrip(monkeypatch: pytest.MonkeyPatch) -> None:
+    import os
+    from pathlib import Path
+
+    import psycopg
+    from alembic import command
+    from alembic.config import Config
+
+    from zhixing_server.bootstrap.config import sqlalchemy_database_url
+    from zhixing_server.modules.sector_radar.application.details import ReadRadarDetails
+    from zhixing_server.modules.sector_radar.infrastructure.postgres import (
+        PostgresSectorRadarRepository,
+    )
+
+    database_url = os.getenv("ZHIXING_TEST_DATABASE_URL")
+    if not database_url:
+        pytest.skip("set ZHIXING_TEST_DATABASE_URL to run PostgreSQL integration tests")
+    config = Config(str(Path(__file__).parents[3] / "alembic.ini"))
+    config.set_main_option(
+        "sqlalchemy.url", sqlalchemy_database_url(database_url).replace("%", "%%")
+    )
+    # Alembic intentionally reads Settings; bind the explicit test DSN and avoid
+    # fileConfig disabling unrelated test loggers in the same pytest process.
+    config.config_file_name = None
+    with monkeypatch.context() as context:
+        context.setenv("ZHIXING_DATABASE_URL", database_url)
+        from zhixing_server.bootstrap.config import get_settings
+
+        get_settings.cache_clear()
+        try:
+            command.upgrade(config, "head")
+        finally:
+            get_settings.cache_clear()
+    target = date(2098, 12, 1)
+    repository = PostgresSectorRadarRepository(database_url, max_connections=2)
+    try:
+        result = BuildSectorRadar(FakeRadarSource(), repository, now_fn=lambda: NOW).execute(
+            BuildSectorRadarCommand(trade_date=target)
+        )
+        assert result.status in ("success", "unchanged")
+        detail = ReadRadarDetails(repository).detail(target, SectorType.CONCEPT, "BK0001.DC")
+        assert detail.history.status == "success"
+        assert detail.pct_change == Decimal(1)
+        assert len(detail.members) == 5
+        assert detail.members[0].active_buy_net_amount_yuan is None
+        assert detail.summary["amount"].metric_value == Decimal("0.0015")
+        with psycopg.connect(database_url) as connection:
+            assert connection.execute("SELECT version_num FROM alembic_version").fetchone() == (
+                "0009_radar_sector_detail",
+            )
+            row = connection.execute(
+                "SELECT pct_change, leading_code FROM sector_radar_daily_aggregate "
+                "WHERE publication_id = %s AND sector_type = 'concept'",
+                (result.outcomes[0].publication_id,),
+            ).fetchone()
+            assert row == (Decimal(1), "000001.SZ")
+            facts = connection.execute(
+                "SELECT pct_change, active_buy_net_amount_yuan "
+                "FROM sector_radar_stock_fact WHERE trade_date = %s",
+                (target,),
+            ).fetchall()
+            assert facts and all(row == (Decimal(0), None) for row in facts)
+            with pytest.raises(psycopg.errors.CheckViolation), connection.transaction():
+                connection.execute(
+                    "UPDATE sector_radar_stock_fact "
+                    "SET active_buy_net_amount_yuan = 'NaN'::numeric WHERE trade_date = %s",
+                    (target,),
+                )
+    finally:
+        repository.close()

zhixing-server/tests/unit/sector_radar/test_read.py

@@ -402,3 +402,40 @@ def test_sector_member_codes_rejects_blank_sector_code() -> None:
 
     with pytest.raises(ValueError):
         reader.sector_member_codes(TARGET_DATE, "   ")
+
+
+def test_history_appearance_counts_use_each_days_pool_and_metric_version() -> None:
+    from zhixing_server.modules.sector_radar.application.details import ReadRadarDetails
+
+    repository = InMemorySectorRadarRepository()
+    current_rows = _amount_rankings()
+    for offset, size in ((-1, 5), (0, 10), (1, 20)):
+        day = TARGET_DATE + timedelta(days=offset)
+        running = _running(f"pool-{offset}", day)
+        repository.create_publication(running)
+        repository.finish_publication(_finish(running, PublicationStatus.SUCCESS))
+        observations = tuple(
+            replace(row.observation, trade_date=day) for row in current_rows[:size]
+        )
+        repository.save_rankings(
+            tuple(
+                RankingRecord(running.publication_id, row)
+                for row in rank_metric_observations(observations)
+            )
+        )
+    reader = ReadRadarDetails(repository)
+    history = reader.history(TARGET_DATE, SectorType.CONCEPT, "BK0002.DC")
+    assert [point.amount.pool_size for point in history.points] == [5, 10]
+    assert [point.amount.in_top for point in history.points] == [False, True]
+    publication = repository.get_successful_publication(TARGET_DATE)
+    assert publication is not None
+    extra = reader.ranking_extras(publication, (current_rows[1],), RankSide.TOP)["BK0002.DC"]
+    assert extra.on_list_count == 1
+    assert extra.history_available_days == 2
+    old_version = replace(
+        current_rows[1],
+        observation=replace(current_rows[1].observation, metric_version="older-version"),
+    )
+    from zhixing_server.modules.sector_radar.application.details import metric_at
+
+    assert metric_at((old_version,), SectorType.CONCEPT, "BK0002.DC", MetricKind.AMOUNT).missing

zhixing-web/src/features/sector-radar/api/sector-radar.api.test.ts

@@ -5,6 +5,9 @@ const requestJson = vi.hoisted(() => vi.fn())
 vi.mock("@/shared/api/request-json", () => ({ requestJson }))
 
 import {
+  getSectorRadarHistory,
+  getSectorRadarDetail,
+  parseRadarDetailResponse,
   getSectorRadarDates,
   getSectorRadarRankings,
   getStockSectorMembership,
@@ -69,11 +72,106 @@ const rankingPayload = {
   ],
 }
 
+const historyMetric = {
+  rank_position: 1,
+  rank_percentile: "100",
+  pool_size: 10,
+  metric_value: "0.125",
+  missing: false,
+  in_top: true,
+  in_bottom: false,
+}
+const historyPayload = {
+  status: "success",
+  requested_trade_date: "2026-08-28",
+  trade_date: "2026-08-28",
+  sector_type: "concept",
+  sector_code: "BK01",
+  sector_name: "机器人",
+  publication,
+  window_size: 30,
+  available_days: 1,
+  points: [
+    {
+      trade_date: "2026-08-28",
+      publication_id: "publication-1",
+      swing: historyMetric,
+      ratio: historyMetric,
+      amount: historyMetric,
+    },
+  ],
+}
+const detailPayload = {
+  ...historyPayload,
+  pct_change: "-1.25",
+  leading_stock: { ts_code: "000001.SZ", name: null },
+  summary: {
+    swing: historyMetric,
+    ratio: historyMetric,
+    amount: historyMetric,
+  },
+  history: historyPayload,
+  members: [
+    {
+      ts_code: "000001.SZ",
+      name: "测试成员",
+      pct_change: "-1.5",
+      net_amount_yuan: "120000000",
+      active_buy_net_amount_yuan: null,
+    },
+  ],
+  leaders: {
+    pct_change: { top: [], bottom: [] },
+    net_amount_yuan: { top: [], bottom: [] },
+    active_buy_net_amount_yuan: { top: [], bottom: [] },
+  },
+  similar_sectors: [],
+}
+
 describe("sector radar API adapters", () => {
   beforeEach(() => {
     requestJson.mockReset()
   })
 
+  it("reads persisted sector resources and preserves nullable independent metrics", async () => {
+    const signal = new AbortController().signal
+    const query = {
+      sectorType: "concept" as const,
+      sectorCode: "BK01",
+      tradeDate: "2026-08-28",
+    }
+    requestJson.mockResolvedValue(historyPayload)
+    expect(
+      (await getSectorRadarHistory(query, signal)).points[0]?.ratio
+        .metric_value,
+    ).toBe(0.125)
+    expect(requestJson).toHaveBeenLastCalledWith(
+      "/api/v1/sector-radar/sectors/concept/BK01/history?trade_date=2026-08-28",
+      { signal },
+    )
+    requestJson.mockResolvedValue(detailPayload)
+    const detail = await getSectorRadarDetail(query, signal)
+    expect(requestJson).toHaveBeenLastCalledWith(
+      "/api/v1/sector-radar/sectors/concept/BK01/detail?trade_date=2026-08-28",
+      { signal },
+    )
+    expect(detail.pct_change).toBe(-1.25)
+    expect(detail.leading_stock?.name).toBeNull()
+    expect(detail.members[0]).toMatchObject({
+      net_amount_yuan: 120000000,
+      active_buy_net_amount_yuan: null,
+    })
+  })
+
+  it.each(["NaN", "Infinity", "0x10", "", true])(
+    "rejects malformed detail Decimal %s",
+    (value) => {
+      expect(() =>
+        parseRadarDetailResponse({ ...detailPayload, pct_change: value }),
+      ).toThrow("detail.pct_change")
+    },
+  )
+
   it("forwards AbortSignal and normalizes decimal publication fields", async () => {
     const signal = new AbortController().signal
     requestJson.mockResolvedValue({
@@ -237,6 +335,8 @@ describe("stock sector membership adapter", () => {
 
     await expect(
       getStockSectorMembership("000001.SZ", "2026-08-28"),
-    ).rejects.toThrow("membership.industries[0].name must be a non-empty string")
+    ).rejects.toThrow(
+      "membership.industries[0].name must be a non-empty string",
+    )
   })
 })

zhixing-web/src/features/sector-radar/api/sector-radar.api.ts

@@ -9,6 +9,11 @@ import {
   radarViews,
   sectorTypes,
   type RadarDatesResponse,
+  type RadarSectorQuery,
+  type RadarHistoryResponse,
+  type RadarHistoryMetric,
+  type RadarDetailResponse,
+  type RadarMember,
   type RadarMetricDefinition,
   type RadarPublication,
   type RadarRankingRow,
@@ -176,7 +181,11 @@ export function parseStockSectorMembershipResponse(
 ): StockSectorMembershipResponse {
   const record = readRecord(value, "membership")
   return {
-    status: readEnum(record.status, ["success", "no_data"], "membership.status"),
+    status: readEnum(
+      record.status,
+      ["success", "no_data"],
+      "membership.status",
+    ),
     ts_code: readNonEmptyString(record.ts_code, "membership.ts_code"),
     requested_trade_date: readDate(
       record.requested_trade_date,
@@ -309,6 +318,33 @@ function readRankingRow(value: unknown, index: number): RadarRankingRow {
       record.metric_value,
       `${path}.metric_value`,
     ),
+    pct_change: readNullableFiniteNumber(
+      record.pct_change ?? null,
+      `${path}.pct_change`,
+    ),
+    daily_net_amount_yuan: readNullableFiniteNumber(
+      record.daily_net_amount_yuan ?? null,
+      `${path}.daily_net_amount_yuan`,
+    ),
+    daily_ratio: readNullableFiniteNumber(
+      record.daily_ratio ?? null,
+      `${path}.daily_ratio`,
+    ),
+    on_list_count:
+      record.on_list_count == null
+        ? null
+        : readIntegerInRange(
+            record.on_list_count,
+            0,
+            30,
+            `${path}.on_list_count`,
+          ),
+    history_available_days: readIntegerInRange(
+      record.history_available_days ?? 0,
+      0,
+      30,
+      `${path}.history_available_days`,
+    ),
     quality: readEnum(record.quality, radarMetricQualities, `${path}.quality`),
     member_count: readIntegerInRange(
       record.member_count,
@@ -427,7 +463,8 @@ function readFiniteNumber(value: unknown, path: string): number {
   const number =
     typeof value === "number"
       ? value
-      : typeof value === "string" && value.trim().length > 0
+      : typeof value === "string" &&
+          /^[+-]?(?:\d+(?:\.\d*)?|\.\d+)(?:[eE][+-]?\d+)?$/.test(value.trim())
         ? Number(value)
         : Number.NaN
   if (!Number.isFinite(number)) throw contractError(path, "must be finite")
@@ -483,3 +520,240 @@ function readNullablePositiveNumber(
 function contractError(path: string, reason: string): Error {
   return new Error(`Invalid sector radar response: ${path} ${reason}`)
 }
+
+/** Fetch persisted history for a sector/date; forward cancellation and reject malformed decimals. */
+export async function getSectorRadarHistory(
+  query: RadarSectorQuery,
+  signal?: AbortSignal,
+) {
+  const payload = await requestJson<unknown>(
+    sectorResourceUrl(query, "history"),
+    { signal },
+  )
+  return parseRadarHistoryResponse(payload)
+}
+
+/** Fetch persisted detail on demand; no supplier calls originate from the browser. */
+export async function getSectorRadarDetail(
+  query: RadarSectorQuery,
+  signal?: AbortSignal,
+) {
+  const payload = await requestJson<unknown>(
+    sectorResourceUrl(query, "detail"),
+    { signal },
+  )
+  return parseRadarDetailResponse(payload)
+}
+
+function sectorResourceUrl(
+  query: RadarSectorQuery,
+  resource: "history" | "detail",
+) {
+  const params = new URLSearchParams({ trade_date: query.tradeDate })
+  return `/api/v1/sector-radar/sectors/${query.sectorType}/${encodeURIComponent(query.sectorCode)}/${resource}?${params}`
+}
+
+function readSectorIdentity(record: JsonRecord, path: string) {
+  return {
+    status: readEnum(record.status, ["success", "no_data"], `${path}.status`),
+    requested_trade_date: readNullableDate(
+      record.requested_trade_date,
+      `${path}.requested_trade_date`,
+    ),
+    trade_date: readNullableDate(record.trade_date, `${path}.trade_date`),
+    publication: readNullablePublication(
+      record.publication,
+      `${path}.publication`,
+    ),
+    sector_type: readEnum(
+      record.sector_type,
+      sectorTypes,
+      `${path}.sector_type`,
+    ),
+    sector_code: readNonEmptyString(record.sector_code, `${path}.sector_code`),
+    sector_name: readNullableString(record.sector_name, `${path}.sector_name`),
+  }
+}
+
+/** Normalize the finite Decimal fields while preserving missing ranks as null. */
+export function parseRadarHistoryResponse(
+  value: unknown,
+): RadarHistoryResponse {
+  const record = readRecord(value, "history")
+  return {
+    ...readSectorIdentity(record, "history"),
+    window_size: readIntegerInRange(
+      record.window_size,
+      1,
+      30,
+      "history.window_size",
+    ),
+    available_days: readIntegerInRange(
+      record.available_days,
+      0,
+      30,
+      "history.available_days",
+    ),
+    points: readArray(record.points, "history.points").map((value, index) => {
+      const path = `history.points[${index}]`
+      const point = readRecord(value, path)
+      return {
+        trade_date: readDate(point.trade_date, `${path}.trade_date`),
+        publication_id: readNullableString(
+          point.publication_id,
+          `${path}.publication_id`,
+        ),
+        ...readMetricSummary(point, path),
+      }
+    }),
+  }
+}
+
+function readMetricSummary(record: JsonRecord, path: string) {
+  return {
+    amount: readHistoryMetric(record.amount, `${path}.amount`),
+    ratio: readHistoryMetric(record.ratio, `${path}.ratio`),
+    swing: readHistoryMetric(record.swing, `${path}.swing`),
+  }
+}
+
+function readHistoryMetric(value: unknown, path: string): RadarHistoryMetric {
+  const record = readRecord(value, path)
+  return {
+    rank_position: readNullableInteger(
+      record.rank_position,
+      1,
+      `${path}.rank_position`,
+    ),
+    rank_percentile: readNullablePositiveNumber(
+      record.rank_percentile,
+      100,
+      `${path}.rank_percentile`,
+    ),
+    pool_size: readIntegerInRange(
+      record.pool_size,
+      0,
+      Number.MAX_SAFE_INTEGER,
+      `${path}.pool_size`,
+    ),
+    metric_value: readNullableFiniteNumber(
+      record.metric_value,
+      `${path}.metric_value`,
+    ),
+    missing: readBoolean(record.missing, `${path}.missing`),
+    in_top: readBoolean(record.in_top, `${path}.in_top`),
+    in_bottom: readBoolean(record.in_bottom, `${path}.in_bottom`),
+  }
+}
+
+function readBoolean(value: unknown, path: string): boolean {
+  if (typeof value !== "boolean") throw contractError(path, "must be a boolean")
+  return value
+}
+
+function readMembers(value: unknown, path: string): RadarMember[] {
+  return readArray(value, path).map((value, index) => {
+    const itemPath = `${path}[${index}]`
+    const record = readRecord(value, itemPath)
+    return {
+      ts_code: readNonEmptyString(record.ts_code, `${itemPath}.ts_code`),
+      name: readNonEmptyString(record.name, `${itemPath}.name`),
+      pct_change: readNullableFiniteNumber(
+        record.pct_change,
+        `${itemPath}.pct_change`,
+      ),
+      net_amount_yuan: readNullableFiniteNumber(
+        record.net_amount_yuan,
+        `${itemPath}.net_amount_yuan`,
+      ),
+      active_buy_net_amount_yuan: readNullableFiniteNumber(
+        record.active_buy_net_amount_yuan,
+        `${itemPath}.active_buy_net_amount_yuan`,
+      ),
+    }
+  })
+}
+
+/** Validate the full detail payload, including independent member metrics and overlaps. */
+export function parseRadarDetailResponse(value: unknown): RadarDetailResponse {
+  const record = readRecord(value, "detail")
+  const leading =
+    record.leading_stock === null
+      ? null
+      : readRecord(record.leading_stock, "detail.leading_stock")
+  const leaders = readRecord(record.leaders, "detail.leaders")
+  function readLeaders(key: string) {
+    const path = `detail.leaders.${key}`
+    const group = readRecord(leaders[key], path)
+    return {
+      top: readMembers(group.top, `${path}.top`),
+      bottom: readMembers(group.bottom, `${path}.bottom`),
+    }
+  }
+  return {
+    ...readSectorIdentity(record, "detail"),
+    pct_change: readNullableFiniteNumber(
+      record.pct_change,
+      "detail.pct_change",
+    ),
+    leading_stock:
+      leading === null
+        ? null
+        : {
+            ts_code: readNonEmptyString(
+              leading.ts_code,
+              "detail.leading_stock.ts_code",
+            ),
+            name: readNullableString(leading.name, "detail.leading_stock.name"),
+          },
+    summary: readMetricSummary(
+      readRecord(record.summary, "detail.summary"),
+      "detail.summary",
+    ),
+    history: parseRadarHistoryResponse(record.history),
+    members: readMembers(record.members, "detail.members"),
+    leaders: {
+      pct_change: readLeaders("pct_change"),
+      net_amount_yuan: readLeaders("net_amount_yuan"),
+      active_buy_net_amount_yuan: readLeaders("active_buy_net_amount_yuan"),
+    },
+    similar_sectors: readArray(
+      record.similar_sectors,
+      "detail.similar_sectors",
+    ).map((value, index) => {
+      const path = `detail.similar_sectors[${index}]`
+      const sector = readRecord(value, path)
+      return {
+        sector_type: readEnum(
+          sector.sector_type,
+          sectorTypes,
+          `${path}.sector_type`,
+        ),
+        sector_code: readNonEmptyString(
+          sector.sector_code,
+          `${path}.sector_code`,
+        ),
+        sector_name: readNonEmptyString(
+          sector.sector_name,
+          `${path}.sector_name`,
+        ),
+        overlap_ratio: readFraction(
+          sector.overlap_ratio,
+          `${path}.overlap_ratio`,
+        ),
+        intersection_count: readIntegerInRange(
+          sector.intersection_count,
+          0,
+          Number.MAX_SAFE_INTEGER,
+          `${path}.intersection_count`,
+        ),
+        union_count: readIntegerInRange(
+          sector.union_count,
+          1,
+          Number.MAX_SAFE_INTEGER,
+          `${path}.union_count`,
+        ),
+      }
+    }),
+  }
+}

zhixing-web/src/features/sector-radar/api/sector-radar.query.test.ts

@@ -3,6 +3,8 @@ import { beforeEach, describe, expect, it, vi } from "vitest"
 const useQuery = vi.hoisted(() => vi.fn())
 const useInfiniteQuery = vi.hoisted(() => vi.fn())
 const api = vi.hoisted(() => ({
+  getSectorRadarHistory: vi.fn(),
+  getSectorRadarDetail: vi.fn(),
   getSectorRadarDates: vi.fn(),
   getSectorRadarRankings: vi.fn(),
 }))
@@ -11,6 +13,9 @@ vi.mock("@tanstack/react-query", () => ({ useInfiniteQuery, useQuery }))
 vi.mock("./sector-radar.api", () => api)
 
 import {
+  sectorRadarSectorQueryKey,
+  useSectorRadarDetail,
+  useSectorRadarHistory,
   sectorRadarDatesQueryKey,
   sectorRadarRankingsQueryKey,
   useSectorRadarDates,
@@ -36,6 +41,42 @@ describe("sector radar query hooks", () => {
     useInfiniteQuery.mockImplementation((options) => options)
   })
 
+  it("isolates sector resources by type, code and date and forwards cancellation", () => {
+    const sector = {
+      sectorType: "concept" as const,
+      sectorCode: "BK01",
+      tradeDate: "2026-08-28",
+    }
+    const signal = new AbortController().signal
+    useSectorRadarDetail(sector)
+    const options = useQuery.mock.calls.at(-1)?.[0]
+    expect(options.queryKey).toEqual([
+      "sectorRadar",
+      "detail",
+      "concept",
+      "BK01",
+      "2026-08-28",
+    ])
+    expect(options.placeholderData).toBeUndefined()
+    options.queryFn({ signal })
+    expect(api.getSectorRadarDetail).toHaveBeenCalledWith(sector, signal)
+    expect(
+      sectorRadarSectorQueryKey("detail", {
+        ...sector,
+        tradeDate: "2026-08-31",
+      }),
+    ).not.toEqual(options.queryKey)
+    expect(
+      sectorRadarSectorQueryKey("detail", {
+        ...sector,
+        sectorType: "industry",
+      }),
+    ).not.toEqual(options.queryKey)
+    useSectorRadarHistory(sector)
+    useQuery.mock.calls.at(-1)?.[0].queryFn({ signal })
+    expect(api.getSectorRadarHistory).toHaveBeenCalledWith(sector, signal)
+  })
+
   it("keeps filters in one ranking key without splitting cached pages", () => {
     expect(sectorRadarDatesQueryKey).toEqual(["sectorRadar", "dates"])
     expect(sectorRadarRankingsQueryKey(query)).toEqual([

zhixing-web/src/features/sector-radar/api/sector-radar.query.ts

@@ -4,10 +4,17 @@ import {
   type InfiniteData,
 } from "@tanstack/react-query"
 
-import { getSectorRadarDates, getSectorRadarRankings, getStockSectorMembership } from "./sector-radar.api"
+import {
+  getSectorRadarDates,
+  getSectorRadarRankings,
+  getStockSectorMembership,
+  getSectorRadarHistory,
+  getSectorRadarDetail,
+} from "./sector-radar.api"
 import type {
   RadarRankingsQuery,
   RadarRankingsResponse,
+  RadarSectorQuery,
 } from "./sector-radar.types"
 
 export const sectorRadarDatesQueryKey = ["sectorRadar", "dates"] as const
@@ -92,3 +99,31 @@ export function useSectorRadarRankings(query: RadarRankingsQuery) {
     queryKey: sectorRadarRankingsQueryKey(query),
   })
 }
+
+export const sectorRadarSectorQueryKey = (
+  resource: "history" | "detail",
+  query: RadarSectorQuery,
+) =>
+  [
+    "sectorRadar",
+    resource,
+    query.sectorType,
+    query.sectorCode,
+    query.tradeDate,
+  ] as const
+
+/** Keep on-demand history isolated by sector type, code and requested date. */
+export function useSectorRadarHistory(query: RadarSectorQuery) {
+  return useQuery({
+    queryKey: sectorRadarSectorQueryKey("history", query),
+    queryFn: ({ signal }) => getSectorRadarHistory(query, signal),
+  })
+}
+
+/** Mount only while the detail dialog is open; never reuse another date as placeholder data. */
+export function useSectorRadarDetail(query: RadarSectorQuery) {
+  return useQuery({
+    queryKey: sectorRadarSectorQueryKey("detail", query),
+    queryFn: ({ signal }) => getSectorRadarDetail(query, signal),
+  })
+}

zhixing-web/src/features/sector-radar/api/sector-radar.types.ts

@@ -77,6 +77,11 @@ export interface RadarRankingRow {
   rank_percentile: number | null
   rank_change_days: number
   rank_change: number | null
+  pct_change: number | null
+  daily_net_amount_yuan: number | null
+  daily_ratio: number | null
+  on_list_count: number | null
+  history_available_days: number
 }
 
 export interface RadarRankingsResponse {
@@ -127,3 +132,68 @@ export interface StockSectorMembershipResponse {
   concept_total: number
   concept_limit: number
 }
+
+export interface RadarSectorQuery {
+  sectorType: SectorType
+  sectorCode: string
+  tradeDate: string
+}
+
+export interface RadarHistoryMetric {
+  rank_position: number | null
+  rank_percentile: number | null
+  pool_size: number
+  metric_value: number | null
+  missing: boolean
+  in_top: boolean
+  in_bottom: boolean
+}
+
+export type RadarMetricSummary = Record<RadarMetricKind, RadarHistoryMetric>
+export interface RadarHistoryPoint extends RadarMetricSummary {
+  trade_date: string
+  publication_id: string | null
+}
+export interface RadarHistoryResponse {
+  status: "success" | "no_data"
+  requested_trade_date: string | null
+  trade_date: string | null
+  publication: RadarPublication | null
+  sector_type: SectorType
+  sector_code: string
+  sector_name: string | null
+  points: RadarHistoryPoint[]
+  window_size: number
+  available_days: number
+}
+export interface RadarMember {
+  ts_code: string
+  name: string
+  pct_change: number | null
+  net_amount_yuan: number | null
+  active_buy_net_amount_yuan: number | null
+}
+export type RadarMemberMetric =
+  "pct_change" | "net_amount_yuan" | "active_buy_net_amount_yuan"
+export interface RadarDetailResponse extends Omit<
+  RadarHistoryResponse,
+  "points" | "window_size" | "available_days"
+> {
+  pct_change: number | null
+  leading_stock: { ts_code: string; name: string | null } | null
+  summary: RadarMetricSummary
+  history: RadarHistoryResponse
+  members: RadarMember[]
+  leaders: Record<
+    RadarMemberMetric,
+    { top: RadarMember[]; bottom: RadarMember[] }
+  >
+  similar_sectors: {
+    sector_type: SectorType
+    sector_code: string
+    sector_name: string
+    overlap_ratio: number
+    intersection_count: number
+    union_count: number
+  }[]
+}

zhixing-web/src/features/sector-radar/components/radar-detail-dialog.tsx

@@ -0,0 +1,331 @@
+import { lazy, Suspense, useState } from "react"
+import { Button } from "@/shared/ui/button"
+import {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogTitle,
+  DialogTrigger,
+} from "@/shared/ui/dialog"
+import { useSectorRadarDetail } from "../api/sector-radar.query"
+import type {
+  RadarDetailResponse,
+  RadarMemberMetric,
+  RadarMetricKind,
+  RadarRankingRow,
+  RadarSectorQuery,
+} from "../api/sector-radar.types"
+import {
+  formatRadarValue,
+  radarMembersCsv,
+  radarValueTone,
+} from "./radar-format"
+import { RadarHistoryGrid } from "./radar-history"
+const RadarRankChart = lazy(() =>
+  import("./radar-rank-chart").then((module) => ({
+    default: module.RadarRankChart,
+  })),
+)
+
+const metricLabels = {
+  swing: "波段资金率",
+  ratio: "单日流入率",
+  amount: "单日净额",
+} as const
+const memberLabels = {
+  pct_change: "涨跌幅",
+  net_amount_yuan: "主力净额",
+  active_buy_net_amount_yuan: "主买净额",
+} as const
+
+/** Keep the trigger inside the dialog primitive so Escape and close restore its focus. */
+export function RadarDetailDialog({ row }: { row: RadarRankingRow }) {
+  const [open, setOpen] = useState(false)
+  return (
+    <Dialog open={open} onOpenChange={setOpen}>
+      <DialogTrigger className="font-medium text-foreground underline-offset-4 hover:text-primary hover:underline">
+        {row.sector_name}
+      </DialogTrigger>
+      <DialogContent className="max-h-[90dvh] grid-cols-1 overflow-y-auto sm:max-w-4xl">
+        <DialogTitle>{row.sector_name}</DialogTitle>
+        <DialogDescription>
+          {row.sector_type === "concept" ? "概念" : "行业"} · {row.sector_code}{" "}
+          · {row.trade_date}
+        </DialogDescription>
+        {open ? (
+          <RadarDetail
+            initialMetric={row.metric_kind}
+            query={{
+              sectorType: row.sector_type,
+              sectorCode: row.sector_code,
+              tradeDate: row.trade_date,
+            }}
+          />
+        ) : null}
+      </DialogContent>
+    </Dialog>
+  )
+}
+
+function RadarDetail({
+  query,
+  initialMetric,
+}: {
+  query: RadarSectorQuery
+  initialMetric: RadarMetricKind
+}) {
+  const detail = useSectorRadarDetail(query)
+  if (detail.isPending) return <p role="status">正在加载板块详情…</p>
+  if (detail.isError)
+    return (
+      <div role="alert">
+        板块详情加载失败。
+        <Button onClick={() => void detail.refetch()} variant="outline">
+          重试详情
+        </Button>
+      </div>
+    )
+  if (!detail.data || detail.data.status === "no_data")
+    return <p>暂无板块详情数据。</p>
+  return <RadarDetailBody data={detail.data} initialMetric={initialMetric} />
+}
+
+function RadarDetailBody({
+  data,
+  initialMetric,
+}: {
+  data: RadarDetailResponse
+  initialMetric: RadarMetricKind
+}) {
+  const [metric, setMetric] = useState<RadarMetricKind>(initialMetric)
+  const [memberMetric, setMemberMetric] =
+    useState<RadarMemberMetric>("pct_change")
+  const [memberSide, setMemberSide] = useState<"top" | "bottom">("top")
+  const [exportStatus, setExportStatus] = useState("")
+  const leaders = data.leaders[memberMetric]
+  async function copyMembers() {
+    try {
+      await navigator.clipboard.writeText(
+        data.members
+          .map((member) => `${member.ts_code}\t${member.name}`)
+          .join("\n"),
+      )
+      setExportStatus(`已复制 ${data.members.length} 只成员。`)
+    } catch {
+      setExportStatus("复制失败，请使用导出成员。")
+    }
+  }
+  function exportMembers() {
+    const url = URL.createObjectURL(
+      new Blob(["\ufeff", radarMembersCsv(data.members)], {
+        type: "text/csv;charset=utf-8",
+      }),
+    )
+    const anchor = document.createElement("a")
+    anchor.href = url
+    anchor.download = `${data.sector_code}-${data.trade_date}-members.csv`
+    anchor.click()
+    URL.revokeObjectURL(url)
+    setExportStatus(`已导出 ${data.members.length} 只成员。`)
+  }
+  return (
+    <div className="min-w-0 space-y-5">
+      <div className="flex flex-wrap justify-end gap-2">
+        <Button
+          variant="outline"
+          size="sm"
+          disabled={!data.members.length}
+          onClick={() => void copyMembers()}
+        >
+          复制成员
+        </Button>
+        <Button
+          variant="outline"
+          size="sm"
+          disabled={!data.members.length}
+          onClick={exportMembers}
+        >
+          导出成员
+        </Button>
+      </div>
+      {exportStatus ? <p role="status">{exportStatus}</p> : null}
+      <div className="flex flex-wrap gap-x-6 gap-y-2 rounded-md bg-muted/50 p-3">
+        <p>实际交易日：{data.trade_date ?? "—"}</p>
+        <p>
+          当日涨跌幅：
+          <span className={radarValueTone(data.pct_change)}>
+            {formatRadarValue(data.pct_change, "percent")}
+          </span>
+        </p>
+        <p>
+          领涨股：
+          {data.leading_stock
+            ? `${data.leading_stock.name ?? ""} ${data.leading_stock.ts_code}`
+            : "暂无数据"}
+        </p>
+      </div>
+      <section aria-label="三指标排名" className="space-y-3">
+        <div className="grid grid-cols-3 gap-2">
+          {(["swing", "ratio", "amount"] as const).map((key) => (
+            <button
+              type="button"
+              key={key}
+              onClick={() => setMetric(key)}
+              aria-pressed={metric === key}
+              className={`min-w-0 rounded-md border p-2 text-left break-words sm:p-3 ${metric === key ? "border-primary bg-primary/5" : "border-border"}`}
+            >
+              <span className="block text-xs text-muted-foreground">
+                {metricLabels[key]}
+              </span>
+              <span className="mt-1 block font-semibold">
+                {data.summary[key].missing ||
+                data.summary[key].rank_position === null
+                  ? "暂无排名"
+                  : `第 ${data.summary[key].rank_position} 名 / ${data.summary[key].pool_size}`}
+              </span>
+              <span className={radarValueTone(data.summary[key].metric_value)}>
+                {formatRadarValue(
+                  data.summary[key].metric_value,
+                  key === "amount" ? "CNY_100M" : "ratio",
+                )}
+              </span>
+            </button>
+          ))}
+        </div>
+        {data.history.points.some(
+          (point) =>
+            !point[metric].missing && point[metric].rank_position !== null,
+        ) ? (
+          <Suspense fallback={<p role="status">正在加载排名曲线…</p>}>
+            <RadarRankChart
+              points={data.history.points}
+              metric={metric}
+              label={metricLabels[metric]}
+            />
+          </Suspense>
+        ) : (
+          <p className="rounded-md bg-muted/30 p-4 text-muted-foreground">
+            暂无{metricLabels[metric]}排名轨迹，当前历史记录均缺失。
+          </p>
+        )}
+        <RadarHistoryGrid history={data.history} metric={metric} />
+      </section>
+      <section aria-label="成分强弱" className="space-y-3">
+        <div className="flex flex-wrap items-center gap-2">
+          <h3 className="mr-auto font-medium">成分强弱</h3>
+          {(Object.keys(memberLabels) as RadarMemberMetric[]).map((key) => (
+            <Button
+              key={key}
+              variant={key === memberMetric ? "default" : "outline"}
+              size="sm"
+              aria-pressed={key === memberMetric}
+              onClick={() => setMemberMetric(key)}
+            >
+              {memberLabels[key]}
+            </Button>
+          ))}
+        </div>
+        <div aria-label="成分排名方向" className="flex justify-end gap-1">
+          {(["top", "bottom"] as const).map((side) => (
+            <Button
+              key={side}
+              size="sm"
+              variant={memberSide === side ? "default" : "outline"}
+              aria-pressed={memberSide === side}
+              onClick={() => setMemberSide(side)}
+            >
+              {side === "top" ? "前 5" : "后 5"}
+            </Button>
+          ))}
+        </div>
+        <div>
+          {[memberSide].map((side) => (
+            <div key={side} className="rounded-md border border-border p-3">
+              <h4 className="mb-2 font-medium">
+                {side === "top" ? "前 5 名" : "后 5 名"}
+              </h4>
+              {leaders[side].length ? (
+                <ol className="space-y-2">
+                  {leaders[side].map((member) => (
+                    <li
+                      key={member.ts_code}
+                      className="flex justify-between gap-3"
+                    >
+                      <span>
+                        {member.name}{" "}
+                        <span className="text-xs text-muted-foreground">
+                          {member.ts_code}
+                        </span>
+                      </span>
+                      <span
+                        className={`tabular-nums ${radarValueTone(member[memberMetric])}`}
+                      >
+                        {formatRadarValue(
+                          member[memberMetric],
+                          memberMetric === "pct_change" ? "percent" : "yuan",
+                        )}
+                      </span>
+                    </li>
+                  ))}
+                </ol>
+              ) : (
+                <p className="text-muted-foreground">暂无有效数据</p>
+              )}
+            </div>
+          ))}
+        </div>
+        <p className="text-xs text-muted-foreground">
+          仅展示有该指标的成员，不足 5
+          只按实际数量显示。主买净额与主力净额为不同来源指标。
+        </p>
+      </section>
+      <section aria-label="相似板块" className="space-y-2">
+        <h3 className="font-medium">相似板块</h3>
+        <p className="text-xs text-muted-foreground">
+          本系统口径：同日可确认成员交集 / 并集（Jaccard 重合度）。
+        </p>
+        {data.similar_sectors.length ? (
+          <div className="grid gap-2 sm:grid-cols-2">
+            {data.similar_sectors.map((sector) => (
+              <div
+                className="flex justify-between rounded-md border border-border p-3"
+                key={`${sector.sector_type}:${sector.sector_code}`}
+              >
+                <span>
+                  {sector.sector_name}{" "}
+                  <span className="text-xs text-muted-foreground">
+                    {sector.sector_type === "concept" ? "概念" : "行业"}
+                  </span>
+                </span>
+                <span>
+                  {(sector.overlap_ratio * 100).toFixed(1)}%{" "}
+                  <span className="text-xs text-muted-foreground">
+                    ({sector.intersection_count}/{sector.union_count})
+                  </span>
+                </span>
+              </div>
+            ))}
+          </div>
+        ) : (
+          <p className="text-muted-foreground">暂无相似板块数据</p>
+        )}
+      </section>
+      <section aria-label="板块成员" className="space-y-2">
+        <div className="flex flex-wrap items-center gap-2">
+          <h3 className="mr-auto font-medium">
+            板块成员（{data.members.length}）
+          </h3>
+        </div>
+        <div className="max-h-44 overflow-auto rounded-md border border-border p-3">
+          <p className="leading-7 text-muted-foreground">
+            {data.members.length
+              ? data.members
+                  .map((member) => `${member.name} (${member.ts_code})`)
+                  .join("、")
+              : "暂无成员数据"}
+          </p>
+        </div>
+      </section>
+    </div>
+  )
+}

zhixing-web/src/features/sector-radar/components/radar-detail.test.tsx

@@ -0,0 +1,301 @@
+import {
+  fireEvent,
+  render,
+  screen,
+  waitFor,
+  within,
+} from "@testing-library/react"
+import { beforeEach, describe, expect, it, vi } from "vitest"
+import type {
+  RadarDetailResponse,
+  RadarRankingRow,
+} from "../api/sector-radar.types"
+import { RadarDetailDialog } from "./radar-detail-dialog"
+import { RadarHistoryGrid } from "./radar-history"
+import {
+  formatRadarValue,
+  radarMembersCsv,
+  radarValueTone,
+} from "./radar-format"
+import { buildRadarRankChartOption } from "./radar-rank-chart-option"
+
+const detailQuery = vi.hoisted(() => vi.fn())
+vi.mock("../api/sector-radar.query", () => ({
+  useSectorRadarDetail: detailQuery,
+}))
+vi.mock("./radar-rank-chart", () => ({
+  RadarRankChart: ({ label }: { label: string }) => (
+    <div role="img" aria-label={label} />
+  ),
+}))
+const metric = {
+  rank_position: 2,
+  rank_percentile: 90,
+  pool_size: 20,
+  metric_value: 0.02,
+  missing: false,
+  in_top: true,
+  in_bottom: false,
+}
+const absent = {
+  ...metric,
+  rank_position: null,
+  metric_value: null,
+  missing: true,
+  in_top: false,
+}
+const member = {
+  ts_code: "000001.SZ",
+  name: "测试成员",
+  pct_change: -1.2,
+  net_amount_yuan: 2e8,
+  active_buy_net_amount_yuan: null,
+}
+const data: RadarDetailResponse = {
+  status: "success",
+  requested_trade_date: "2026-08-28",
+  trade_date: "2026-08-28",
+  publication: null,
+  sector_type: "concept",
+  sector_code: "BK01",
+  sector_name: "机器人",
+  pct_change: -2,
+  leading_stock: { ts_code: "000001.SZ", name: null },
+  summary: {
+    swing: metric,
+    ratio: metric,
+    amount: { ...metric, metric_value: 2 },
+  },
+  history: {
+    status: "success",
+    requested_trade_date: "2026-08-28",
+    trade_date: "2026-08-28",
+    publication: null,
+    sector_type: "concept",
+    sector_code: "BK01",
+    sector_name: "机器人",
+    window_size: 30,
+    available_days: 1,
+    points: [
+      {
+        trade_date: "2026-08-28",
+        publication_id: "p1",
+        swing: metric,
+        ratio: metric,
+        amount: metric,
+      },
+      {
+        trade_date: "2026-08-27",
+        publication_id: null,
+        swing: absent,
+        ratio: absent,
+        amount: absent,
+      },
+    ],
+  },
+  members: [member],
+  leaders: {
+    pct_change: { top: [member], bottom: [member] },
+    net_amount_yuan: { top: [member], bottom: [member] },
+    active_buy_net_amount_yuan: { top: [], bottom: [] },
+  },
+  similar_sectors: [],
+}
+const row: RadarRankingRow = {
+  trade_date: "2026-08-28",
+  sector_type: "concept",
+  sector_code: "BK01",
+  sector_name: "机器人",
+  metric_kind: "ratio",
+  metric_version: "v1",
+  implementation_kind: "independent",
+  unit: "ratio",
+  metric_value: 0.02,
+  quality: "available",
+  member_count: 1,
+  valid_sample_count: 1,
+  membership_coverage: 1,
+  moneyflow_coverage: 1,
+  rank_position: 2,
+  rank_percentile: 90,
+  rank_change_days: 1,
+  rank_change: null,
+  pct_change: -2,
+  daily_net_amount_yuan: 2e8,
+  daily_ratio: 0.02,
+  on_list_count: 1,
+  history_available_days: 1,
+}
+
+describe("radar detail interactions", () => {
+  beforeEach(() => {
+    detailQuery.mockReset()
+    detailQuery.mockReturnValue({ data, isPending: false, isError: false })
+  })
+  it("loads only after opening, switches both metrics and copies only returned members", async () => {
+    const writeText = vi.fn().mockResolvedValue(undefined)
+    Object.defineProperty(navigator, "clipboard", {
+      configurable: true,
+      value: { writeText },
+    })
+    render(<RadarDetailDialog row={row} />)
+    expect(detailQuery).not.toHaveBeenCalled()
+    fireEvent.click(screen.getByRole("button", { name: "机器人" }))
+    const dialog = await screen.findByRole("dialog")
+    expect(detailQuery).toHaveBeenCalledWith({
+      sectorType: "concept",
+      sectorCode: "BK01",
+      tradeDate: "2026-08-28",
+    })
+    expect(within(dialog).getByText("当日涨跌幅：")).toHaveTextContent("-2%")
+    expect(within(dialog).getByText(/领涨股：/)).toHaveTextContent("000001.SZ")
+    expect(
+      await within(dialog).findByRole("img", { name: "单日流入率" }),
+    ).toBeInTheDocument()
+    fireEvent.click(within(dialog).getByRole("button", { name: /单日净额/ }))
+    expect(
+      within(dialog).getByRole("img", { name: "单日净额" }),
+    ).toBeInTheDocument()
+    const strength = within(dialog).getByRole("region", { name: "成分强弱" })
+    expect(within(strength).getAllByRole("listitem")).toHaveLength(1)
+    fireEvent.click(within(strength).getByRole("button", { name: "后 5" }))
+    expect(
+      within(strength).getByRole("heading", { name: "后 5 名" }),
+    ).toBeInTheDocument()
+    expect(
+      within(strength).getByRole("button", { name: "后 5" }),
+    ).toHaveAttribute("aria-pressed", "true")
+    fireEvent.click(within(strength).getByRole("button", { name: "主买净额" }))
+    expect(within(strength).getAllByText("暂无有效数据")).toHaveLength(1)
+    fireEvent.click(within(dialog).getByRole("button", { name: "复制成员" }))
+    await waitFor(() =>
+      expect(writeText).toHaveBeenCalledWith("000001.SZ\t测试成员"),
+    )
+    expect(await screen.findByText("已复制 1 只成员。")).toBeInTheDocument()
+  })
+  it("starts with the clicked ranking metric and labels entirely missing histories", async () => {
+    detailQuery.mockReturnValue({
+      data: {
+        ...data,
+        history: {
+          ...data.history,
+          points: data.history.points.map((point) => ({
+            ...point,
+            amount: absent,
+          })),
+        },
+      },
+      isPending: false,
+      isError: false,
+    })
+    render(<RadarDetailDialog row={{ ...row, metric_kind: "amount" }} />)
+    fireEvent.click(screen.getByRole("button", { name: "机器人" }))
+    const dialog = await screen.findByRole("dialog")
+    expect(
+      within(dialog).getByRole("button", { name: /单日净额/ }),
+    ).toHaveAttribute("aria-pressed", "true")
+    expect(
+      within(dialog).getByText("暂无单日净额排名轨迹，当前历史记录均缺失。"),
+    ).toBeInTheDocument()
+    expect(within(dialog).queryByRole("img")).not.toBeInTheDocument()
+  })
+
+  it("exports the API member CSV and releases its object URL", async () => {
+    const create = vi.fn().mockReturnValue("blob:members")
+    const revoke = vi.fn()
+    Object.defineProperty(URL, "createObjectURL", {
+      configurable: true,
+      value: create,
+    })
+    Object.defineProperty(URL, "revokeObjectURL", {
+      configurable: true,
+      value: revoke,
+    })
+    const click = vi
+      .spyOn(HTMLAnchorElement.prototype, "click")
+      .mockImplementation(() => undefined)
+    render(<RadarDetailDialog row={row} />)
+    fireEvent.click(screen.getByRole("button", { name: "机器人" }))
+    await screen.findByRole("dialog")
+    fireEvent.click(screen.getByRole("button", { name: "导出成员" }))
+    expect(create).toHaveBeenCalledWith(expect.any(Blob))
+    const blob = create.mock.calls[0]?.[0] as Blob
+    const text = await new Promise<string>((resolve) => {
+      const reader = new FileReader()
+      reader.onload = () => resolve(String(reader.result))
+      reader.readAsText(blob)
+    })
+    expect(text).toContain('"000001.SZ","测试成员","-1.2","200000000",""')
+    expect(click.mock.instances[0]).toHaveAttribute(
+      "download",
+      "BK01-2026-08-28-members.csv",
+    )
+    expect(revoke).toHaveBeenCalledWith("blob:members")
+    click.mockRestore()
+  })
+
+  it("closes with Escape and restores focus to the trigger", async () => {
+    render(<RadarDetailDialog row={row} />)
+    const trigger = screen.getByRole("button", { name: "机器人" })
+    trigger.focus()
+    fireEvent.click(trigger)
+    await screen.findByRole("dialog")
+    fireEvent.keyDown(document.activeElement ?? document.body, {
+      key: "Escape",
+    })
+    await waitFor(() =>
+      expect(screen.queryByRole("dialog")).not.toBeInTheDocument(),
+    )
+    await waitFor(() => expect(trigger).toHaveFocus())
+  })
+  it("reports pending, error and unavailable detail without inventing values", async () => {
+    detailQuery.mockReturnValue({ isPending: true })
+    const { rerender } = render(<RadarDetailDialog row={row} />)
+    fireEvent.click(screen.getByRole("button", { name: "机器人" }))
+    expect(await screen.findByRole("status")).toHaveTextContent(
+      "正在加载板块详情",
+    )
+    const retry = vi.fn()
+    detailQuery.mockReturnValue({
+      isPending: false,
+      isError: true,
+      refetch: retry,
+    })
+    rerender(<RadarDetailDialog row={row} />)
+    fireEvent.click(screen.getByRole("button", { name: "重试详情" }))
+    expect(retry).toHaveBeenCalledOnce()
+    detailQuery.mockReturnValue({
+      data: { status: "no_data" },
+      isPending: false,
+      isError: false,
+    })
+    rerender(<RadarDetailDialog row={row} />)
+    expect(screen.getByText("暂无板块详情数据。")).toBeInTheDocument()
+  })
+  it("keeps newest-first history, missing cells, and oldest-first disconnected chart ranks", () => {
+    render(
+      <RadarHistoryGrid history={data.history} metric="ratio" side="top" />,
+    )
+    expect(screen.getByText(/历史不足 30 日/)).toBeInTheDocument()
+    expect(screen.getByText("缺失")).toBeInTheDocument()
+    expect(
+      screen
+        .getByText("08-28")
+        .compareDocumentPosition(screen.getByText("08-27")) &
+        Node.DOCUMENT_POSITION_FOLLOWING,
+    ).toBeTruthy()
+    const option = buildRadarRankChartOption(data.history.points, "ratio")
+    expect(option.xAxis.data).toEqual(["2026-08-27", "2026-08-28"])
+    expect(option.series[0]?.data).toEqual([null, 2])
+    expect(option.series[0]?.connectNulls).toBe(false)
+    expect(option.yAxis.inverse).toBe(true)
+  })
+  it("preserves signed amounts and escapes supplier strings in local CSV", () => {
+    expect(formatRadarValue(-2e8, "yuan")).toBe("-2 亿元")
+    expect(formatRadarValue(null, "percent")).toBe("—")
+    expect(radarValueTone(-1)).toContain("emerald")
+    const csv = radarMembersCsv([{ ...member, name: '=SUM(1,2)"\nhello' }])
+    expect(csv).toContain('"\'=SUM(1,2)""\nhello"')
+    expect(csv).toContain('"-1.2","200000000",""')
+  })
+})

zhixing-web/src/features/sector-radar/components/radar-format.ts

@@ -0,0 +1,46 @@
+import type { RadarMember } from "../api/sector-radar.types"
+
+/** Format signed values without changing their sign to match a ranking side. */
+export function formatRadarValue(
+  value: number | null | undefined,
+  unit: "percent" | "yuan" | "ratio" | "CNY_100M",
+) {
+  if (value == null || !Number.isFinite(value)) return "—"
+  const scaled =
+    unit === "yuan" ? value / 1e8 : unit === "ratio" ? value * 100 : value
+  const suffix = unit === "yuan" || unit === "CNY_100M" ? " 亿元" : "%"
+  return `${scaled > 0 ? "+" : ""}${scaled.toLocaleString("zh-CN", { maximumFractionDigits: 2 })}${suffix}`
+}
+
+export function radarValueTone(value: number | null | undefined) {
+  return value == null || !Number.isFinite(value) || value === 0
+    ? "text-muted-foreground"
+    : value > 0
+      ? "text-red-600 dark:text-red-400"
+      : "text-emerald-600 dark:text-emerald-400"
+}
+
+/** Serialize only API members; quote every field and neutralize spreadsheet formula prefixes. */
+export function radarMembersCsv(members: RadarMember[]) {
+  function cell(value: string | number | null) {
+    const text = value === null ? "" : String(value)
+    // Untrusted supplier names/codes must never execute as spreadsheet formulas.
+    const safe =
+      typeof value === "string" && /^[\s]*[=+@\-\t\r]/.test(text)
+        ? `'${text}`
+        : text
+    return `"${safe.replaceAll('"', '""')}"`
+  }
+  return [
+    ["股票代码", "股票名称", "涨跌幅(%)", "主力净额(元)", "主买净额(元)"],
+    ...members.map((member) => [
+      member.ts_code,
+      member.name,
+      member.pct_change,
+      member.net_amount_yuan,
+      member.active_buy_net_amount_yuan,
+    ]),
+  ]
+    .map((row) => row.map(cell).join(","))
+    .join("\r\n")
+}

zhixing-web/src/features/sector-radar/components/radar-history.tsx

@@ -0,0 +1,97 @@
+import { useSectorRadarHistory } from "../api/sector-radar.query"
+import type {
+  RadarHistoryResponse,
+  RadarMetricKind,
+  RadarSectorQuery,
+} from "../api/sector-radar.types"
+import { Button } from "@/shared/ui/button"
+
+export function RadarHistory({
+  query,
+  metric,
+  side,
+}: {
+  query: RadarSectorQuery
+  metric: RadarMetricKind
+  side: "top" | "bottom"
+}) {
+  const history = useSectorRadarHistory(query)
+  if (history.isPending) return <p role="status">正在加载在榜历史…</p>
+  if (history.isError)
+    return (
+      <div role="alert">
+        在榜历史加载失败。
+        <Button
+          variant="outline"
+          size="sm"
+          onClick={() => void history.refetch()}
+        >
+          重试历史
+        </Button>
+      </div>
+    )
+  if (!history.data || history.data.status === "no_data")
+    return <p>暂无在榜历史数据。</p>
+  return <RadarHistoryGrid history={history.data} metric={metric} side={side} />
+}
+
+/** Render newest first and trust each day's pool-based membership flags, preserving missing days. */
+export function RadarHistoryGrid({
+  history,
+  metric,
+  side,
+}: {
+  history: RadarHistoryResponse
+  metric: RadarMetricKind
+  side?: "top" | "bottom"
+}) {
+  const points = [...history.points].sort((a, b) =>
+    b.trade_date.localeCompare(a.trade_date),
+  )
+  return (
+    <div className="space-y-2">
+      <p className="text-xs text-muted-foreground">
+        近 {history.window_size} 个交易日，已有 {history.available_days} 日发布
+        {history.available_days < history.window_size
+          ? "（历史不足 30 日）"
+          : ""}
+        。
+        {points.length
+          ? `覆盖 ${points.at(-1)?.trade_date} 至 ${points[0]?.trade_date}。`
+          : ""}
+        在榜为进入对应榜单的累计次数，并非连续天数。
+      </p>
+      <div className="grid grid-cols-5 gap-1 sm:grid-cols-10">
+        {points.map((point) => {
+          const value = point[metric]
+          const inList =
+            side === "top"
+              ? value.in_top
+              : side === "bottom"
+                ? value.in_bottom
+                : value.in_top || value.in_bottom
+          return (
+            <div
+              key={point.trade_date}
+              className={`rounded-md border p-1.5 text-center text-xs ${!value.missing && inList ? "border-primary/40 bg-primary/10" : "border-border bg-muted/30"}`}
+              title={`${point.trade_date} · 排名池 ${value.pool_size} · ${value.missing ? "缺失" : inList ? "在榜" : "未在榜"}`}
+            >
+              <div className="text-muted-foreground">
+                {point.trade_date.slice(5)}
+              </div>
+              <div className="mt-1 font-medium tabular-nums">
+                {value.missing || value.rank_position === null
+                  ? "缺失"
+                  : `第 ${value.rank_position} 名`}
+              </div>
+              <span className="sr-only">
+                {point.trade_date} 排名池 {value.pool_size}{" "}
+                {value.missing ? "缺失" : inList ? "在榜" : "未在榜"}
+              </span>
+            </div>
+          )
+        })}
+      </div>
+    </div>
+  )
+}

zhixing-web/src/features/sector-radar/components/radar-rank-chart-option.ts

@@ -0,0 +1,51 @@
+import type {
+  RadarHistoryPoint,
+  RadarMetricKind,
+} from "../api/sector-radar.types"
+
+/** Produce a chronological ranking series; missing observations break the line and rank 1 stays on top. */
+export function buildRadarRankChartOption(
+  points: RadarHistoryPoint[],
+  metric: RadarMetricKind,
+) {
+  const ordered = [...points].sort((a, b) =>
+    a.trade_date.localeCompare(b.trade_date),
+  )
+  return {
+    animation: false,
+    grid: { left: 48, right: 20, top: 24, bottom: 36 },
+    tooltip: {
+      trigger: "axis" as const,
+      renderMode: "richText" as const,
+      valueFormatter: (value: unknown) =>
+        value == null ? "缺失" : `第 ${String(value)} 名`,
+    },
+    xAxis: {
+      type: "category" as const,
+      data: ordered.map((point) => point.trade_date),
+      boundaryGap: false,
+    },
+    yAxis: {
+      type: "value" as const,
+      inverse: true,
+      min: 1,
+      max: Math.max(2, ...ordered.map((point) => point[metric].pool_size)),
+      minInterval: 1,
+      name: "排名",
+    },
+    series: [
+      {
+        name: "排名",
+        type: "line" as const,
+        connectNulls: false,
+        showSymbol: true,
+        showAllSymbol: true,
+        data: ordered.map((point) =>
+          point[metric].missing ? null : point[metric].rank_position,
+        ),
+        lineStyle: { color: "#2563eb" },
+        itemStyle: { color: "#2563eb" },
+      },
+    ],
+  }
+}

zhixing-web/src/features/sector-radar/components/radar-rank-chart.tsx

@@ -0,0 +1,46 @@
+import { useEffect, useRef } from "react"
+import { LineChart } from "echarts/charts"
+import { GridComponent, TooltipComponent } from "echarts/components"
+import * as echarts from "echarts/core"
+import { CanvasRenderer } from "echarts/renderers"
+import type {
+  RadarHistoryPoint,
+  RadarMetricKind,
+} from "../api/sector-radar.types"
+
+echarts.use([LineChart, GridComponent, TooltipComponent, CanvasRenderer])
+
+import { buildRadarRankChartOption } from "./radar-rank-chart-option"
+
+export function RadarRankChart({
+  points,
+  metric,
+  label,
+}: {
+  points: RadarHistoryPoint[]
+  metric: RadarMetricKind
+  label: string
+}) {
+  const containerRef = useRef<HTMLDivElement>(null)
+  useEffect(() => {
+    if (!containerRef.current) return
+    const chart = echarts.init(containerRef.current, undefined, {
+      renderer: "canvas",
+    })
+    chart.setOption(buildRadarRankChartOption(points, metric))
+    const observer = new ResizeObserver(() => chart.resize())
+    observer.observe(containerRef.current)
+    return () => {
+      observer.disconnect()
+      chart.dispose()
+    }
+  }, [points, metric])
+  return (
+    <div
+      ref={containerRef}
+      role="img"
+      aria-label={`${label}近30交易日排名曲线，排名1在上方，缺失处断线`}
+      className="h-64 w-full"
+    />
+  )
+}

zhixing-web/src/features/sector-radar/pages/sector-radar-page.test.tsx

@@ -12,6 +12,7 @@ import { SectorRadarPage } from "./sector-radar-page"
 const navigate = vi.hoisted(() => vi.fn())
 const useSectorRadarDates = vi.fn()
 const useSectorRadarRankings = vi.fn()
+const useSectorRadarHistory = vi.fn()
 const refetchDates = vi.fn()
 const refetchRankings = vi.fn()
 const fetchNextPage = vi.fn()
@@ -24,6 +25,7 @@ vi.mock("@tanstack/react-router", () => ({
 }))
 
 vi.mock("@/features/sector-radar/api/sector-radar.query", () => ({
+  useSectorRadarHistory: (...args: unknown[]) => useSectorRadarHistory(...args),
   useSectorRadarDates: () => useSectorRadarDates(),
   useSectorRadarRankings: (...args: unknown[]) =>
     useSectorRadarRankings(...args),
@@ -91,6 +93,11 @@ const rankingsResponse: RadarRankingsResponse = {
       rank_percentile: 100,
       rank_change_days: 1,
       rank_change: 3,
+      pct_change: -1.25,
+      daily_net_amount_yuan: 1250000000,
+      daily_ratio: -0.02,
+      on_list_count: 3,
+      history_available_days: 10,
     },
     {
       trade_date: "2026-08-28",
@@ -111,6 +118,11 @@ const rankingsResponse: RadarRankingsResponse = {
       rank_percentile: null,
       rank_change_days: 1,
       rank_change: null,
+      pct_change: null,
+      daily_net_amount_yuan: null,
+      daily_ratio: null,
+      on_list_count: null,
+      history_available_days: 0,
     },
   ],
 }
@@ -163,6 +175,11 @@ describe("SectorRadarPage", () => {
       refetch: refetchDates,
     })
     useSectorRadarRankings.mockReturnValue(rankingQueryResult())
+    useSectorRadarHistory.mockReturnValue({
+      isPending: false,
+      isError: false,
+      data: { status: "no_data" },
+    })
     navigate.mockReset()
     refetchDates.mockReset()
     refetchRankings.mockReset()
@@ -175,14 +192,21 @@ describe("SectorRadarPage", () => {
 
     expect(screen.getAllByText("+12.5 亿元")[0]).toBeInTheDocument()
     expect(screen.getAllByText("机器人")[0]).toBeInTheDocument()
-    expect(screen.getAllByText("19/20")[0]).toBeInTheDocument()
-    expect(screen.getAllByText("100%")[0]).toBeInTheDocument()
+    expect(screen.queryByText("19/20")).not.toBeInTheDocument()
+    expect(screen.queryByText("BK0001.DC")).not.toBeInTheDocument()
     expect(
-      screen.getAllByRole("columnheader", { name: "排名百分位" }),
+      screen.queryByRole("columnheader", { name: "排名百分位" }),
+    ).not.toBeInTheDocument()
+    expect(
+      screen.queryByRole("columnheader", { name: "样本" }),
+    ).not.toBeInTheDocument()
+    expect(
+      screen.getAllByRole("columnheader", { name: "涨跌幅" }),
     ).toHaveLength(2)
-    expect(screen.getAllByRole("columnheader", { name: "样本" })).toHaveLength(
-      2,
-    )
+    expect(
+      screen.getAllByRole("columnheader", { name: "单日流入率" }),
+    ).toHaveLength(2)
+    expect(screen.getAllByText("-2%")).toHaveLength(2)
     expect(
       screen.queryByRole("columnheader", { name: "资金覆盖率" }),
     ).not.toBeInTheDocument()
@@ -206,6 +230,66 @@ describe("SectorRadarPage", () => {
     ).not.toBeInTheDocument()
   })
 
+  it("mirrors ratio columns and expands only the selected sector history, resetting on date change", () => {
+    routeSearch = { ...routeSearch, view: "ratio" }
+    const ratioPage = {
+      ...rankingsResponse,
+      view: "ratio",
+      rows: rankingsResponse.rows.map((row) => ({
+        ...row,
+        unit: "ratio",
+        metric_value: -0.01,
+      })),
+    }
+    useSectorRadarRankings.mockReturnValue(
+      rankingQueryResult({ data: { pages: [ratioPage], pageParams: [1] } }),
+    )
+    const { rerender } = render(<SectorRadarPage />)
+    expect(screen.getAllByRole("columnheader", { name: "在榜" })).toHaveLength(
+      2,
+    )
+    expect(screen.getAllByText("-1%")).toHaveLength(4)
+    const trigger = screen.getAllByRole("button", {
+      name: "机器人展开在榜历史",
+    })[0]!
+    fireEvent.click(trigger)
+    expect(trigger).toHaveAttribute("aria-expanded", "true")
+    expect(useSectorRadarHistory).toHaveBeenLastCalledWith({
+      sectorType: "concept",
+      sectorCode: "BK0001.DC",
+      tradeDate: "2026-08-28",
+    })
+    expect(screen.getByText("暂无在榜历史数据。")).toBeInTheDocument()
+    fireEvent.click(trigger)
+    expect(screen.queryByText("暂无在榜历史数据。")).not.toBeInTheDocument()
+    fireEvent.click(trigger)
+    useSectorRadarRankings.mockReturnValue(
+      rankingQueryResult({
+        data: {
+          pages: [
+            {
+              ...ratioPage,
+              publication: {
+                ...successPublication,
+                publication_id: "next-day",
+              },
+              rows: ratioPage.rows.map((row) => ({
+                ...row,
+                trade_date: "2026-08-31",
+              })),
+            },
+          ],
+          pageParams: [1],
+        },
+      }),
+    )
+    rerender(<SectorRadarPage />)
+    expect(screen.queryByText("暂无在榜历史数据。")).not.toBeInTheDocument()
+    expect(
+      screen.getAllByRole("button", { name: "机器人展开在榜历史" })[0],
+    ).toHaveAttribute("aria-expanded", "false")
+  })
+
   it("resets filters to the first batch in router search state", () => {
     routeSearch = { ...routeSearch, page: 3 }
     render(<SectorRadarPage />)

zhixing-web/src/features/sector-radar/pages/sector-radar-page.tsx

@@ -1,5 +1,5 @@
 import { AlertTriangle, Database, RefreshCw } from "lucide-react"
-import { useRef } from "react"
+import { useRef, useState } from "react"
 import { useNavigate, useSearch } from "@tanstack/react-router"
 
 import { PageLayout } from "@/app/layout/page-layout"
@@ -9,7 +9,6 @@ import {
 } from "@/features/sector-radar/api/sector-radar.query"
 import type {
   RadarMetricKind,
-  RadarMetricUnit,
   RadarPublication,
   RadarRankingRow,
   RadarRankingsQuery,
@@ -36,19 +35,23 @@ import {
 } from "@/shared/ui/select"
 import { Skeleton } from "@/shared/ui/skeleton"
 
+import { RadarDetailDialog } from "../components/radar-detail-dialog"
+import { RadarHistory } from "../components/radar-history"
+import { formatRadarValue, radarValueTone } from "../components/radar-format"
+
 const sectorTypeOptions = [
   { label: "概念", value: "concept" },
   { label: "行业", value: "industry" },
 ] as const
 const viewOptions = [
   { label: "波段资金率", value: "swing" },
-  { label: "单日资金率", value: "ratio" },
+  { label: "单日流入率", value: "ratio" },
   { label: "单日净额", value: "amount" },
   { label: "排名变化", value: "rank_change" },
 ] as const
 const metricOptions = [
   { label: "主力净额", value: "amount" },
-  { label: "单日资金率", value: "ratio" },
+  { label: "单日流入率", value: "ratio" },
   { label: "波段资金率", value: "swing" },
 ] as const
 const rankChangeDayOptions = [1, 2, 3, 4, 5].map((value) => ({
@@ -366,6 +369,8 @@ function RadarTable({
   const bottomRows = bottom.data?.pages.flatMap((page) => page.rows) ?? []
   const rowCount = Math.max(topRows.length, bottomRows.length)
   const rankChangeView = response.view === "rank_change"
+  const dailyView = response.view === "amount" || response.view === "ratio"
+  const columns = dailyView && response.view === "ratio" ? 10 : 8
   const loadMoreRequestPending = useRef({ top: false, bottom: false })
   function requestLoadMore(query: RankingQueryResult) {
     const side = query === top ? "top" : "bottom"
@@ -401,7 +406,7 @@ function RadarTable({
             {response.sector_type === "concept" ? "概念" : "行业"}板块资金双榜
           </caption>
           <colgroup>
-            {Array.from({ length: 8 }, (_, i) => (
+            {Array.from({ length: columns }, (_, i) => (
               <col
                 key={i}
                 className={i === 3 || i === 4 ? "w-[120px]" : "w-[100px]"}
@@ -412,7 +417,7 @@ function RadarTable({
             <tr>
               <th
                 className="px-3 py-1 text-left font-medium"
-                colSpan={3}
+                colSpan={(columns - 2) / 2}
                 scope="colgroup"
               >
                 资金进攻榜 TOP 10%
@@ -426,12 +431,49 @@ function RadarTable({
               </th>
               <th
                 className="px-3 py-1 text-right font-medium"
-                colSpan={3}
+                colSpan={(columns - 2) / 2}
                 scope="colgroup"
               >
                 BOTTOM 10% 资金撤离榜
               </th>
             </tr>
+            {dailyView ? (
+              <tr>
+                {(response.view === "ratio"
+                  ? [
+                      "排名 / 板块",
+                      "涨跌幅",
+                      "净额",
+                      "在榜",
+                      "流入率",
+                      "流入率",
+                      "在榜",
+                      "净额",
+                      "涨跌幅",
+                      "排名 / 板块",
+                    ]
+                  : [
+                      "排名 / 板块",
+                      "涨跌幅",
+                      "单日流入率",
+                      "净额",
+                      "净额",
+                      "单日流入率",
+                      "涨跌幅",
+                      "排名 / 板块",
+                    ]
+                ).map((label, index) => (
+                  <th
+                    key={index}
+                    scope="col"
+                    className="px-3 py-1 text-right font-medium"
+                  >
+                    {label}
+                  </th>
+                ))}
+              </tr>
+            ) : (
+              <>
                 <tr>
                   <th className="px-3 py-1 text-left font-medium" scope="col">
                     排名 / 板块
@@ -464,11 +506,14 @@ function RadarTable({
                     排名 / 板块
                   </th>
                 </tr>
+              </>
+            )}
           </thead>
           <tbody className="divide-y divide-border/60">
             {Array.from({ length: rowCount }, (_, i) => (
               <RadarMirrorRow
-                key={i}
+                key={`${response.publication?.publication_id}:${response.view}:${topRows[i]?.sector_code}:${bottomRows[i]?.sector_code}`}
+                view={response.view}
                 rankChangeView={rankChangeView}
                 top={topRows[i]}
                 bottom={bottomRows[i]}
@@ -478,7 +523,7 @@ function RadarTable({
               <tr>
                 <td
                   className="px-3 py-8 text-center text-muted-foreground"
-                  colSpan={8}
+                  colSpan={columns}
                 >
                   没有符合当前筛选条件的板块。
                 </td>
@@ -543,11 +588,52 @@ function RadarMirrorRow({
   top,
   bottom,
   rankChangeView,
+  view,
 }: {
+  view: RadarView
   top?: RadarRankingRow
   bottom?: RadarRankingRow
   rankChangeView: boolean
 }) {
+  const [expanded, setExpanded] = useState<"top" | "bottom" | null>(null)
+  if (view === "ratio" || view === "amount")
+    return (
+      <>
+        <tr className="hover:bg-muted/40">
+          <DailyCells
+            row={top}
+            side="top"
+            view={view}
+            expanded={expanded === "top"}
+            onToggle={() => setExpanded(expanded === "top" ? null : "top")}
+          />
+          <DailyCells
+            row={bottom}
+            side="bottom"
+            view={view}
+            expanded={expanded === "bottom"}
+            onToggle={() =>
+              setExpanded(expanded === "bottom" ? null : "bottom")
+            }
+          />
+        </tr>
+        {expanded && (expanded === "top" ? top : bottom) ? (
+          <tr>
+            <td colSpan={view === "ratio" ? 10 : 8} className="bg-muted/20 p-3">
+              <RadarHistory
+                query={{
+                  sectorType: (expanded === "top" ? top : bottom)!.sector_type,
+                  sectorCode: (expanded === "top" ? top : bottom)!.sector_code,
+                  tradeDate: (expanded === "top" ? top : bottom)!.trade_date,
+                }}
+                metric={view}
+                side={expanded}
+              />
+            </td>
+          </tr>
+        ) : null}
+      </>
+    )
   return (
     <tr className="hover:bg-muted/40">
       <RankCells row={top} align="left" />
@@ -561,6 +647,76 @@ function RadarMirrorRow({
     </tr>
   )
 }
+/** Mirror daily fields without borrowing values from the opposite sector. */
+function DailyCells({
+  row,
+  side,
+  view,
+  expanded,
+  onToggle,
+}: {
+  row?: RadarRankingRow
+  side: "top" | "bottom"
+  view: "ratio" | "amount"
+  expanded: boolean
+  onToggle: () => void
+}) {
+  if (!row)
+    return (
+      <td
+        colSpan={view === "ratio" ? 5 : 4}
+        className="p-3 text-center text-muted-foreground"
+      >
+        —
+      </td>
+    )
+  const fields = [
+    <td key="name" className="px-3 py-2 whitespace-nowrap">
+      <span className="mr-2 text-muted-foreground tabular-nums">
+        {row.rank_position ?? "—"}
+      </span>
+      <RadarDetailDialog row={row} />
+    </td>,
+    <td
+      key="pct"
+      className={`px-3 py-2 text-right tabular-nums ${radarValueTone(row.pct_change)}`}
+    >
+      {formatRadarValue(row.pct_change, "percent")}
+    </td>,
+    <td
+      key="extra"
+      className={`px-3 py-2 text-right tabular-nums ${radarValueTone(view === "ratio" ? row.daily_net_amount_yuan : row.daily_ratio)}`}
+    >
+      {formatRadarValue(
+        view === "ratio" ? row.daily_net_amount_yuan : row.daily_ratio,
+        view === "ratio" ? "yuan" : "ratio",
+      )}
+    </td>,
+    ...(view === "ratio"
+      ? [
+          <td key="history" className="px-3 py-2 text-right">
+            <button
+              type="button"
+              aria-expanded={expanded}
+              aria-label={`${row.sector_name}${expanded ? "收起" : "展开"}在榜历史`}
+              onClick={onToggle}
+              className="text-primary underline underline-offset-4"
+            >
+              {row.on_list_count == null ? "—" : `${row.on_list_count} 次`}
+            </button>
+          </td>,
+        ]
+      : []),
+    <td
+      key="metric"
+      className={`border-x border-border bg-muted/30 px-3 py-2 text-right font-medium tabular-nums ${radarValueTone(row.metric_value)}`}
+    >
+      {formatRadarValue(row.metric_value, row.unit)}
+    </td>,
+  ]
+  return <>{side === "top" ? fields : fields.reverse()}</>
+}
+
 function RankCells({
   row,
   align,
@@ -626,23 +782,10 @@ function MetricCell({
   const value = row
     ? rankChangeView
       ? formatRankChange(row.rank_change)
-      : formatDirectionalMetric(row.metric_value, row.unit, direction)
+      : formatRadarValue(row.metric_value, row.unit)
     : "—"
-  const positive =
-    row?.rank_change !== null &&
-    row?.rank_change !== undefined &&
-    row.rank_change > 0
-  const negative =
-    row?.rank_change !== null &&
-    row?.rank_change !== undefined &&
-    row.rank_change < 0
   const borderClass = direction === "in" ? "border-l" : "border-r"
-  const toneClass =
-    positive || (direction === "in" && !rankChangeView)
-      ? "text-red-600 dark:text-red-400 bg-red-500/10"
-      : negative || (direction === "out" && !rankChangeView)
-        ? "text-emerald-600 dark:text-emerald-400 bg-emerald-500/10"
-        : "text-foreground bg-muted/30"
+  const toneClass = `${radarValueTone(rankChangeView ? row?.rank_change : row?.metric_value)} bg-muted/30`
   return (
     <td
       className={`${borderClass} border-border px-3 py-1.5 ${direction === "in" ? "text-right" : "text-left"} font-medium tabular-nums ${toneClass}`}
@@ -652,20 +795,6 @@ function MetricCell({
   )
 }
 
-function formatDirectionalMetric(
-  value: number | null,
-  unit: RadarMetricUnit,
-  direction: "in" | "out",
-) {
-  if (value === null) return "—"
-  const absoluteValue = Math.abs(value)
-  const formatted =
-    unit === "CNY_100M"
-      ? `${formatNumber(absoluteValue, 2)} 亿元`
-      : `${formatNumber(absoluteValue * 100, 2)}%`
-  return `${direction === "in" ? "+" : "−"}${formatted}`
-}
-
 function RadarLoading() {
   return (
     <Card aria-label="正在加载板块资金雷达" className="flex-1 shadow-none">