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Author SHA1 Message Date
总工andmultica-agent 8ff537db7b test(HEL-479): scope revision-review batch assertions to A-group boundary for HEL-463 integration
Co-authored-by: multica-agent <github@multica.ai>
2026-09-08 08:25:12 +08:00
总工 260f8464cf Merge commit '605f97e5dffd25132f6a857b7870ab0f023c8f2a' into integrate/hel478-hel463 2026-09-08 08:23:31 +08:00
d175bb65d4 feat(HEL-478): 估值发布后晚间复核并原子追补上游修订
盘后成功发布后继续轻量比对 daily_basic 网站字段,发现修订才走质量门与整组原子切换,避免 17:10 快照落后于晚间上游改写。

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: multica-agent <github@multica.ai>
2026-09-07 21:19:35 +08:00
605f97e5df feat(HEL-463): 接入剩余行情数据到 datahub
扩展盘后正式集(涨跌停/人气/龙虎榜/板块日线)与盘中观察 API(报价/指数/分时),网站 bridge 按开关接入并回退旧链路;问天改为按数据依赖跟随开关,不再整栈强制旧路径。

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: multica-agent <github@multica.ai>
2026-09-05 17:30:58 +08:00
16ba83ec01 fix(HEL-461): 切换事务失败写入 release-group 审计日志
整组切换中断时除回滚与废弃批次外,同步记录
action=release-group 的失败审计,便于后台追踪。

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: multica-agent <github@multica.ai>
2026-09-05 16:02:11 +08:00
1c740a9d48 fix(HEL-461): 后台整组切换异常统一为 FAILED_PRECONDITION
管理后台补数在切换事务中断时不再抛出原始异常,
统一映射为 ApiError FAILED_PRECONDITION,并保留旧完整版本。

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: multica-agent <github@multica.ai>
2026-09-05 15:56:28 +08:00
75c2e33b68 fix(HEL-461): CLI/后台强制重发改为整组边界切换
eod-refresh --force 与管理后台补数不再单数据集发布,
统一走 force_republish_boundary,避免绕过 A/B 完整边界。

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: multica-agent <github@multica.ai>
2026-09-05 11:26:27 +08:00
32f565ecb9 fix(HEL-461): 整批发布按完整边界重暂存,主档与快照同事务
边界内任有缺失则整组重暂存后统一切换,避免旧新批次混发;
refresh_stocks 失败时主档保持旧值,并补齐回归测试。

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: multica-agent <github@multica.ai>
2026-09-05 08:52:50 +08:00
32 changed files with 2721 additions and 133 deletions
+3
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@@ -7,6 +7,9 @@ TUSHARE_TOKEN=your_tushare_token_here
# Optional xiaobai-datahub client. All DATAHUB_READ_* / DATAHUB_SHADOW_* flags
# default off in config/datahub.config.json, so the website keeps using Tushare.
# Extended datasets (HEL-463): LIMIT_EVENTS POPULARITY DRAGON_TIGER SECTOR_DAILY
# QUOTES INDEX_QUOTES INTRADAY — plus first-batch CALENDAR STOCKS DAILY INDEX_DAILY
# VALUATION MONEYFLOW AUCTION STATUS.
DATAHUB_BASE_URL=http://127.0.0.1:8766
DATAHUB_TOKEN=
+30 -6
View File
@@ -21,11 +21,14 @@ from backend.data.providers.tushare_client import TushareClient
LOGGER = logging.getLogger("xiaobai.datahub")
ShadowSink = Callable[[dict[str, Any]], None]
EMPTY_FAIL_DATASETS = {"stocks", "daily", "index_daily", "valuation", "moneyflow", "auction"}
EMPTY_FAIL_DATASETS = {
"stocks", "daily", "index_daily", "valuation", "moneyflow", "auction",
"limit_events", "sector_daily",
}
def looks_like_heaven(module_name: str, filename: str = "") -> bool:
"""问天调用栈识别。问天未永久冻结,只是本阶段仍走旧 Tushare 链路。"""
"""问天调用栈识别(诊断用)。问天按数据集依赖接入,不再整栈强制旧链路。"""
path = filename.replace("\\", "/")
return module_name.startswith("backend.features.heaven") or "/features/heaven/" in path
@@ -96,8 +99,8 @@ class DatahubBridge:
legacy_query: Callable[..., list[dict[str, Any]]],
) -> list[dict[str, Any]]:
dataset = API_TO_DATASET.get(api_name)
# 问天允许后续纳入 datahub;首批只读接入仍保持旧链路,避免误切
if not dataset or self.heaven_guard():
# 问天按实际数据依赖接入:已映射到 hub 的 API 跟随开关;未映射的继续旧链路
if not dataset:
return legacy_query(api_name, params, fields)
flags = self.settings.flags(dataset)
if not flags.read and not flags.shadow:
@@ -108,7 +111,7 @@ class DatahubBridge:
hub_error: str | None = None
hub_canonical: list[dict[str, Any]] = []
try:
response = self._fetch_dataset(dataset, params or {})
response = self._fetch_dataset(dataset, params or {}, api_name=api_name)
hub_canonical = self._extract_rows(dataset, response, params or {})
hub_rows = to_native_rows(dataset, hub_canonical)
hub_meta = dict(response.meta)
@@ -136,7 +139,7 @@ class DatahubBridge:
return project_fields(hub_rows, fields)
return legacy_query(api_name, params, fields)
def _fetch_dataset(self, dataset: str, params: dict[str, Any]) -> DatahubResponse:
def _fetch_dataset(self, dataset: str, params: dict[str, Any], api_name: str = "") -> DatahubResponse:
date = yyyymmdd(params.get("trade_date") or params.get("date"))
start = yyyymmdd(params.get("start_date") or params.get("from") or date)
end = yyyymmdd(params.get("end_date") or params.get("to") or date)
@@ -153,6 +156,10 @@ class DatahubBridge:
"valuation": self.client.valuation,
"moneyflow": self.client.moneyflow,
"auction": self.client.auction,
"limit_events": self.client.limit_events,
"popularity": self.client.popularity,
"dragon_tiger": self.client.dragon_tiger,
"sector_daily": self.client.sectors,
}
fetcher = fetchers[dataset]
query: dict[str, Any] = {}
@@ -167,6 +174,23 @@ class DatahubBridge:
query["to"] = end
if dataset == "daily":
query["adjust"] = "none"
if dataset == "limit_events":
limit_type = str(params.get("limit_type") or "").strip().upper()
if limit_type:
query["limit_type"] = limit_type
if dataset == "popularity":
if api_name == "ths_hot":
query["source"] = "ths"
elif api_name == "dc_hot":
query["source"] = "dc"
if dataset == "sector_daily":
family = {
"ths_daily": "ths",
"dc_index": "dc",
"sw_daily": "sw",
}.get(api_name, "")
if family:
query["family"] = family
return self._paginate(fetcher, query)
def _paginate(self, fetcher: Callable[..., DatahubResponse], params: dict[str, Any]) -> DatahubResponse:
+21
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@@ -60,6 +60,27 @@ class DatahubClient:
def auction(self, **params: Any) -> DatahubResponse:
return self.get("/v1/auction", params)
def limit_events(self, **params: Any) -> DatahubResponse:
return self.get("/v1/limit-events", params)
def popularity(self, **params: Any) -> DatahubResponse:
return self.get("/v1/popularity", params)
def dragon_tiger(self, **params: Any) -> DatahubResponse:
return self.get("/v1/dragon-tiger", params)
def sectors(self, **params: Any) -> DatahubResponse:
return self.get("/v1/sectors", params)
def quotes_latest(self, **params: Any) -> DatahubResponse:
return self.get("/v1/quotes/latest", params)
def index_quotes(self, **params: Any) -> DatahubResponse:
return self.get("/v1/indexes/quotes", params)
def intraday_points(self, **params: Any) -> DatahubResponse:
return self.get("/v1/intraday/points", params)
def dataset_status(self, date: str) -> DatahubResponse:
return self.get("/v1/datasets/status", {"date": date})
+51
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@@ -17,6 +17,13 @@ API_TO_DATASET = {
"index_daily": "index_daily",
"moneyflow": "moneyflow",
"stk_auction": "auction",
"limit_list_d": "limit_events",
"ths_hot": "popularity",
"dc_hot": "popularity",
"hm_detail": "dragon_tiger",
"ths_daily": "sector_daily",
"dc_index": "sector_daily",
"sw_daily": "sector_daily",
}
SCALE_FIELDS = {
@@ -35,6 +42,16 @@ SCALE_FIELDS = {
"net_mf_amount": AMOUNT_WAN_YUAN,
},
"auction": {"vol": VOLUME_LOT, "float_share": AMOUNT_WAN_YUAN},
"limit_events": {
"limit_amount": AMOUNT_WAN_YUAN,
"float_mv": AMOUNT_WAN_YUAN,
"total_mv": AMOUNT_WAN_YUAN,
},
"dragon_tiger": {
"buy_amount": AMOUNT_WAN_YUAN,
"sell_amount": AMOUNT_WAN_YUAN,
"net_amount": AMOUNT_WAN_YUAN,
},
}
@@ -67,6 +84,16 @@ def to_native_row(dataset: str, row: dict[str, Any]) -> dict[str, Any]:
converted[field] = _unscale(converted.get(field), factor)
if dataset == "stocks":
converted.pop("updated_at", None)
if dataset == "popularity":
# keep hub source; callers filter ths/dc themselves when needed
if converted.get("ts_name") and not converted.get("name"):
converted["name"] = converted.get("ts_name")
if dataset == "dragon_tiger":
if converted.get("ts_name") and not converted.get("name"):
converted["name"] = converted.get("ts_name")
if dataset == "sector_daily":
if converted.get("pct_change") is not None and converted.get("pct_chg") is None:
converted["pct_chg"] = converted.get("pct_change")
return converted
@@ -96,6 +123,30 @@ def row_key(dataset: str, row: dict[str, Any]) -> tuple[str, ...]:
return (str(row.get("ts_code") or "").upper(),)
if dataset == "status":
return (str(row.get("dataset") or ""), yyyymmdd(row.get("trade_date")))
if dataset == "limit_events":
return (
str(row.get("ts_code") or "").upper(),
yyyymmdd(row.get("trade_date")),
str(row.get("limit_type") or ""),
)
if dataset == "popularity":
return (
str(row.get("ts_code") or "").upper(),
yyyymmdd(row.get("trade_date")),
str(row.get("source") or ""),
)
if dataset == "dragon_tiger":
return (
str(row.get("ts_code") or "").upper(),
yyyymmdd(row.get("trade_date")),
str(row.get("hm_name") or ""),
)
if dataset == "sector_daily":
return (
str(row.get("ts_code") or "").upper(),
yyyymmdd(row.get("trade_date")),
str(row.get("family") or ""),
)
return (str(row.get("ts_code") or "").upper(), yyyymmdd(row.get("trade_date")))
+14
View File
@@ -17,6 +17,13 @@ DATASETS = (
"valuation",
"moneyflow",
"auction",
"limit_events",
"popularity",
"dragon_tiger",
"sector_daily",
"quotes",
"index_quotes",
"intraday",
"status",
)
@@ -28,6 +35,13 @@ ENV_DATASET = {
"valuation": "VALUATION",
"moneyflow": "MONEYFLOW",
"auction": "AUCTION",
"limit_events": "LIMIT_EVENTS",
"popularity": "POPULARITY",
"dragon_tiger": "DRAGON_TIGER",
"sector_daily": "SECTOR_DAILY",
"quotes": "QUOTES",
"index_quotes": "INDEX_QUOTES",
"intraday": "INTRADAY",
"status": "STATUS",
}
+7
View File
@@ -13,6 +13,13 @@
"valuation": { "read": false, "shadow": false },
"moneyflow": { "read": false, "shadow": false },
"auction": { "read": false, "shadow": false },
"limit_events": { "read": false, "shadow": false },
"popularity": { "read": false, "shadow": false },
"dragon_tiger": { "read": false, "shadow": false },
"sector_daily": { "read": false, "shadow": false },
"quotes": { "read": false, "shadow": false },
"index_quotes": { "read": false, "shadow": false },
"intraday": { "read": false, "shadow": false },
"status": { "read": false, "shadow": false }
}
}
+4 -3
View File
@@ -290,8 +290,8 @@ class DatahubBridgeTests(unittest.TestCase):
self.assertEqual(canonical["vol"], 100000.0)
self.assertEqual(canonical["amount"], 2000000.0)
def test_heaven_keeps_legacy_on_first_batch_even_when_read_flag_is_on(self) -> None:
"""问天未永久冻结;首批只读接入仍走旧链路,后续迁移可以纳入"""
def test_heaven_can_use_hub_when_dataset_flag_is_on(self) -> None:
"""问天按数据依赖接入:已映射 API 跟随开关,不再整栈强制旧链路"""
self.assertTrue(looks_like_heaven("backend.features.heaven.market_context", "backend/features/heaven/market_context.py"))
self.assertFalse(looks_like_heaven("backend.features.market.service", "backend/features/market/service.py"))
client = FakeClient()
@@ -302,7 +302,8 @@ class DatahubBridgeTests(unittest.TestCase):
)
rows = wrapped.query("daily", {"trade_date": "20240902"}, "amount")
self.assertEqual(rows[0]["amount"], 2000.0)
self.assertEqual(client.paths, [])
self.assertEqual(client.paths, ["/v1/bars/daily"])
self.assertEqual(legacy.calls, [])
def test_status_flag_does_not_run_when_off_and_falls_back_when_on(self) -> None:
off = DatahubBridge(flags(), FakeClient(error=DatahubError("UNAVAILABLE", "down")))
+20 -5
View File
@@ -6,11 +6,12 @@
## 做什么
- SQLite WAL `datahub.db`,容器名 `xiaobai-datahub`,端口 `8766`
- Tushare 盘后正式数据:交易日历、股票主档、daily、daily_basic、adj_factor、index_daily、moneyflow、stk_auction
- Tushare 盘后正式数据:交易日历、股票主档、daily、daily_basic、adj_factor、index_daily、moneyflow、stk_auction、limit_list_d、ths_hot/dc_hot、hm_detail、ths_daily/dc_index/sw_daily
- 盘中观察(provisional):东财/腾讯指数报价、个股最新价、分时点(`/v1/quotes/latest` `/v1/indexes/quotes` `/v1/intraday/points`);永不写入 eod_* 正式表
- 暂存 → 校验 → 整批原子发布 → 可回滚
- `/v1` 稳定接口(`X-Datahub-Token`
- `/admin/` 最小管理后台(总览 / 数据源 / 调度 / 发布 / 数据集 / 审计)
- 东财/腾讯/同花顺/选股宝/AKShare/iFinD 适配器位预留,本阶段不拉实时源
- 同花顺/选股宝/AKShare/iFinD 适配器位预留;东财/腾讯已接入盘中观察
## 单位口径(相对现站)
@@ -91,7 +92,7 @@ python -m datahub history-backfill
- 流程:组内全部成员先在暂存表完成拉取、字段质量门、覆盖检查和跨数据集交叉校验(`cross_gates` 配置 ts_code 覆盖重叠率下限),全部达标后才在**一个 SQLite 事务**里复制正式表并翻转全部 `publications` 指针。
- 任一成员失败(拉取失败、质量门拒绝、交叉校验不过、切换事务中断)→ 整批不切换,对外继续提供上一份完整正式版本,失败原因写入 `batches.error``audit_log``action=release-group`),等待晚间自动重试。
- 读取侧任何时刻只会看到"旧完整版本"或"新完整版本":发布指针在单事务内统一翻转,容器重启/事务中断自动回滚,不暴露字段残缺或跨数据集混合版本。
- 幂等:已发布数据集自动跳过;重复执行、并发重试不会生成重复批次或覆盖正常版本(调度器另有 EOD 互斥锁)。
- 幂等:仅当一致性边界内全部成员都已发布时才整组跳过;边界内任有缺失则整组重暂存后统一切换,避免旧批次与新批次混在同一次重发中。重复执行、并发重试不会在完整边界已就绪时生成重复批次(调度器另有 EOD 互斥锁)。
## 股票主档每日刷新与发布
@@ -115,11 +116,25 @@ python -m datahub moneyflow-backfill # --trading-days 60 --end-date --for
```bash
cd xiaobai-datahub
python -m datahub eod-refresh --trade-date 20260904 # 只补缺失数据集
python -m datahub eod-refresh --trade-date 20260904 # 补不完整的 A/B 边界
python -m datahub eod-refresh --trade-date 20260904 --force --dataset valuation
# 强制重取重发:仍走全部质量门,生成新批次,上一批次保留可回滚
# --force 按一致性边界整组重发:valuation/daily/moneyflow/auction/stocks → A 组;
# index_daily → B 组。不可再单独切换某一个正式数据集。
```
管理后台「补数」对盘后正式数据集同样走 `force_republish_boundary`,不会绕过 A/B 整批边界。
## 估值发布后复核与自动追补
Tushare `daily_basic` 会在盘后继续改当日字段。HEL-423 在 2026-09-07 观察到:中枢 17:10 发布 `003021.SZ turnover_rate=1.3565`21:05 上游/旧链路已是 `1.3572`;其余 7 类观察对象当日一致。日 K、资金流、竞价、指数没有同类晚间修订证据,股票主档已有 20:00/23:10 刷新,因此默认只复核估值,不盲目全量重拉。
窗口(可配):交易日 **20:0023:20**,每 30 分钟一次轻量比对(对齐网站 21:00 / 23:30 观察)。只拉取 `daily_basic`,按网站真实请求字段精确比较,无误差豁免。
- 无变化:不产生新批次,状态「已追平」。
- 发现修订:重新走字段质量门、覆盖检查和 A 组整批原子发布;读者全程只能看到上一完整版本或新完整版本。
- 上游空 / 接口失败 / 不完整 / 质量门拒绝:保留上一完整版本,状态「复核失败」。
- 23:20 截止后停止当晚复核;下一自然日盘前对上一交易日再做一次安全追赶。
-`eod_a` / `eod_retry` 共用互斥锁;容器重启会在窗口内立即补一次。
## 备份
+14 -1
View File
@@ -105,6 +105,7 @@ async function render() {
const data = await api("/admin/api/overview");
$("phase").textContent = data.session_phase;
const eod = data.eod_status || {};
const rev = data.revision_status || {};
const eodLabels = {
pending_first_attempt: "等待首次尝试",
waiting_upstream: "等待上游",
@@ -112,6 +113,14 @@ async function render() {
cutoff_failed: "已截止失败",
closed_day: "休市",
};
const revLabels = {
waiting_review: "等待复核",
review_failed: "复核失败",
aligned: "已追平",
cutoff: "已截止",
pending_publish: "待发布",
closed_day: "休市",
};
const eodExtra = [];
if (eod.state === "waiting_upstream") {
eodExtra.push(`已试 ${eod.attempts}`);
@@ -121,12 +130,16 @@ async function render() {
if (eod.state === "cutoff_failed" && eod.missing_datasets) {
eodExtra.push(`${esc(eod.missing_datasets.join(","))}`);
}
const revExtra = [];
if (rev.detail) revExtra.push(esc(String(rev.detail)));
if (rev.window) revExtra.push(esc(String(rev.window)));
page.innerHTML = `
<div class="cards">
<div class="card"><div class="muted">交易日</div><strong>${esc(data.trade_date)}</strong></div>
<div class="card"><div class="muted">阶段</div><strong>${esc(data.session_phase)}</strong></div>
<div class="card"><div class="muted">今日发布</div><strong>${data.publications.length}</strong></div>
<div class="card"><div class="muted">盘后补跑</div><strong>${esc(eodLabels[eod.state] || eod.state || "-")}</strong><div class="muted">${eodExtra.join(" · ")}</div></div>
<div class="card"><div class="muted">估值复核</div><strong>${esc(revLabels[rev.state] || rev.state || "-")}</strong><div class="muted">${revExtra.join(" · ")}</div></div>
<div class="card"><div class="muted">异常批次</div><strong class="${data.anomalies.length ? "fail" : "ok"}">${data.anomalies.length}</strong></div>
</div>
<h2>最近调用</h2>
@@ -269,7 +282,7 @@ function renderRelease(data) {
async function dangerous(kind, dataset) {
const date = ($("rel-date") && $("rel-date").value) || "";
const ds = dataset || prompt("数据集(daily / valuation / moneyflow / auction / index_daily / reference", "daily");
const ds = dataset || prompt("数据集(daily/valuation/moneyflow/auction/stocks→A组整批;index_daily→B组;或 reference", "daily");
if (!ds) return;
const password = prompt("二次确认:输入管理密码");
if (!password) return;
@@ -17,6 +17,10 @@
"eod_retry_start": "15:15",
"eod_retry_interval_minutes": 30,
"eod_retry_cutoff": "23:30",
"revision_review_datasets": ["valuation"],
"revision_review_start": "20:00",
"revision_review_interval_minutes": 30,
"revision_review_cutoff": "23:20",
"moneyflow_history_trading_days": 60,
"stocks_refresh_times": [
"20:00",
+4 -4
View File
@@ -1,13 +1,13 @@
from datahub.adapters.akshare import ADAPTER as akshare
from datahub.adapters.eastmoney import ADAPTER as eastmoney
from datahub.adapters.eastmoney import EastmoneyAdapter
from datahub.adapters.ifind import ADAPTER as ifind
from datahub.adapters.tencent import ADAPTER as tencent
from datahub.adapters.tencent import TencentAdapter
from datahub.adapters.ths import ADAPTER as ths
from datahub.adapters.xgb import ADAPTER as xgb
RESERVED = {
"eastmoney": eastmoney,
"tencent": tencent,
"eastmoney": EastmoneyAdapter(),
"tencent": TencentAdapter(),
"ths": ths,
"xgb": xgb,
"akshare": akshare,
+249 -2
View File
@@ -1,3 +1,250 @@
from datahub.adapters.base import ReservedAdapter
from __future__ import annotations
ADAPTER = ReservedAdapter("eastmoney")
import json
import time
import urllib.error
import urllib.parse
import urllib.request
from datetime import datetime
from typing import Any
from datahub.adapters.base import AdapterError, MarketAdapter
from datahub.numbers import finite_number, round4
EASTMONEY_INDEX_URL = "https://push2.eastmoney.com/api/qt/ulist.np/get"
EASTMONEY_CLIST_URL = "https://push2.eastmoney.com/api/qt/clist/get"
TRENDS_URL = "https://push2delay.eastmoney.com/api/qt/stock/trends2/get"
BROWSER_UA = (
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
"AppleWebKit/537.36 (KHTML, like Gecko) Chrome/138.0.0.0 Safari/537.36"
)
INDEX_SECIDS = {
"000001.SH": "1.000001",
"399001.SZ": "0.399001",
"399006.SZ": "0.399006",
}
class EastmoneyAdapter(MarketAdapter):
name = "eastmoney"
def __init__(self, timeout: int = 8) -> None:
self.timeout = timeout
def probe(self) -> dict[str, Any]:
started = time.perf_counter()
try:
rows = self.fetch_indices()
state = "ok" if len(rows) == 3 else "empty"
except AdapterError as exc:
return {
"provider": self.name,
"configured": True,
"state": "error",
"message": str(exc),
"latency_ms": round((time.perf_counter() - started) * 1000),
}
return {
"provider": self.name,
"configured": True,
"state": state,
"latency_ms": round((time.perf_counter() - started) * 1000),
}
def fetch(self, dataset: str, params: dict[str, Any]) -> list[dict[str, Any]]:
if dataset in {"indexes_quotes", "index_quotes"}:
return self.fetch_indices()
if dataset in {"quotes", "quotes_latest"}:
codes = params.get("codes") or []
if isinstance(codes, str):
codes = [item.strip() for item in codes.split(",") if item.strip()]
return self.fetch_quotes(list(codes))
raise AdapterError(f"{self.name} unsupported dataset: {dataset}")
def normalize(self, dataset: str, rows: list[dict[str, Any]]) -> list[dict[str, Any]]:
return list(rows)
def fetch_indices(self) -> list[dict[str, Any]]:
payload = self._get_json(
EASTMONEY_INDEX_URL,
{
"secids": "1.000001,0.399001,0.399006",
"fltt": "2",
"invt": "2",
"fields": "f12,f14,f2,f3,f4,f15,f16,f17,f18,f6,f124",
},
referer="https://quote.eastmoney.com/",
)
rows = list((payload.get("data") or {}).get("diff") or [])
result = []
for row in rows:
code = str(row.get("f12") or "")
if code not in {"000001", "399001", "399006"}:
continue
epoch = int(finite_number(row.get("f124")) or 0)
ts_code = f"{code}.SH" if code.startswith("0") and code == "000001" else f"{code}.SZ"
if code == "000001":
ts_code = "000001.SH"
result.append(
{
"ts_code": ts_code,
"code": code,
"name": row.get("f14") or code,
"price": round4(finite_number(row.get("f2"))),
"pct_chg": round4(finite_number(row.get("f3"))),
"change_amount": round4(finite_number(row.get("f4"))),
"open": round4(finite_number(row.get("f17"))),
"high": round4(finite_number(row.get("f15"))),
"low": round4(finite_number(row.get("f16"))),
"previous_close": round4(finite_number(row.get("f18"))),
"amount": round4(finite_number(row.get("f6"))),
"quote_time_epoch": epoch,
"quote_time": (
datetime.fromtimestamp(epoch).astimezone().isoformat(timespec="seconds")
if epoch
else ""
),
"source": "eastmoney_push2",
}
)
if len(result) != 3:
raise AdapterError(f"Eastmoney returned {len(result)}/3 indices")
return result
def fetch_quotes(self, codes: list[str]) -> list[dict[str, Any]]:
# Eastmoney clist does not accept arbitrary code lists well; use ulist.np for batches.
secids = []
for code in codes:
ts = str(code or "").upper()
symbol = ts.split(".")[0]
if ts.endswith(".SH") or symbol.startswith(("5", "6", "9")):
secids.append(f"1.{symbol}")
else:
secids.append(f"0.{symbol}")
if not secids:
return []
payload = self._get_json(
EASTMONEY_INDEX_URL,
{
"secids": ",".join(secids[:60]),
"fltt": "2",
"invt": "2",
"fields": "f12,f14,f2,f3,f4,f15,f16,f17,f18,f5,f6,f8,f124",
},
referer="https://quote.eastmoney.com/",
)
rows = list((payload.get("data") or {}).get("diff") or [])
result = []
for row in rows:
symbol = str(row.get("f12") or "")
if not symbol:
continue
ts_code = f"{symbol}.SH" if symbol.startswith(("5", "6", "9")) else f"{symbol}.SZ"
epoch = int(finite_number(row.get("f124")) or 0)
result.append(
{
"ts_code": ts_code,
"name": row.get("f14") or symbol,
"price": round4(finite_number(row.get("f2"))),
"pct_chg": round4(finite_number(row.get("f3"))),
"change_amount": round4(finite_number(row.get("f4"))),
"open": round4(finite_number(row.get("f17"))),
"high": round4(finite_number(row.get("f15"))),
"low": round4(finite_number(row.get("f16"))),
"previous_close": round4(finite_number(row.get("f18"))),
"volume": round4(finite_number(row.get("f5"))),
"amount": round4(finite_number(row.get("f6"))),
"turnover_rate": round4(finite_number(row.get("f8"))),
"quote_time_epoch": epoch,
"quote_time": (
datetime.fromtimestamp(epoch).astimezone().isoformat(timespec="seconds")
if epoch
else ""
),
"source": "eastmoney_push2",
}
)
return result
def fetch_intraday(self, ts_code: str) -> dict[str, Any]:
code = str(ts_code or "").upper()
if code in INDEX_SECIDS:
secid = INDEX_SECIDS[code]
entity = "index"
identifier = code
else:
symbol = code.split(".")[0]
market = "1" if symbol.startswith(("5", "6", "9")) else "0"
secid = f"{market}.{symbol}"
entity = "stock"
identifier = symbol
payload = self._get_json(
TRENDS_URL,
{
"secid": secid,
"fields1": "f1,f2,f3,f4,f5,f6,f7,f8,f9,f10,f11,f12,f13",
"fields2": "f51,f52,f53,f54,f55,f56,f57,f58",
"iscr": "0",
"ndays": "1",
},
referer="https://quote.eastmoney.com/",
)
data = payload.get("data") or {}
points = []
for raw in data.get("trends") or []:
point = _parse_trend(raw)
if point:
points.append(point)
if not points:
raise AdapterError("No intraday chart data returned")
return {
"entity_type": entity,
"identifier": identifier,
"ts_code": code if "." in code else f"{identifier}.{'SH' if identifier.startswith(('5','6','9')) else 'SZ'}",
"name": str(data.get("name") or ""),
"code": str(data.get("code") or identifier),
"trade_date": points[-1]["date"],
"previous_close": round4(finite_number(data.get("preClose"))),
"points": points,
"source": "eastmoney_trends2",
}
def _get_json(self, url: str, params: dict[str, str], referer: str) -> dict[str, Any]:
request_url = f"{url}?{urllib.parse.urlencode(params)}"
request = urllib.request.Request(
request_url,
headers={
"Accept": "application/json,text/plain,*/*",
"User-Agent": BROWSER_UA,
"Referer": referer,
},
method="GET",
)
try:
with urllib.request.urlopen(request, timeout=self.timeout) as response:
return json.loads(response.read().decode("utf-8"))
except Exception as exc:
raise AdapterError(f"eastmoney request failed: {exc}") from exc
def _parse_trend(raw: Any) -> dict[str, Any] | None:
text = str(raw or "")
parts = text.split(",")
if len(parts) < 8:
return None
stamp = parts[0]
try:
when = datetime.strptime(stamp, "%Y-%m-%d %H:%M")
except ValueError:
return None
return {
"time": when.strftime("%H:%M"),
"date": when.strftime("%Y-%m-%d"),
"open": round4(finite_number(parts[1])),
"close": round4(finite_number(parts[2])),
"high": round4(finite_number(parts[3])),
"low": round4(finite_number(parts[4])),
"avg_price": round4(finite_number(parts[7] if len(parts) > 7 else parts[2])),
"volume": round4(finite_number(parts[5])),
"amount": round4(finite_number(parts[6])),
}
+98 -2
View File
@@ -1,3 +1,99 @@
from datahub.adapters.base import ReservedAdapter
from __future__ import annotations
ADAPTER = ReservedAdapter("tencent")
import time
import urllib.error
import urllib.request
from datetime import datetime
from typing import Any
from datahub.adapters.base import AdapterError, MarketAdapter
from datahub.numbers import finite_number, round4
TENCENT_INDEX_URL = "https://qt.gtimg.cn/q=sh000001,sz399001,sz399006"
BROWSER_UA = (
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
"AppleWebKit/537.36 (KHTML, like Gecko) Chrome/138.0.0.0 Safari/537.36"
)
class TencentAdapter(MarketAdapter):
name = "tencent"
def __init__(self, timeout: int = 8) -> None:
self.timeout = timeout
def probe(self) -> dict[str, Any]:
started = time.perf_counter()
try:
rows = self.fetch_indices()
state = "ok" if len(rows) == 3 else "empty"
except AdapterError as exc:
return {
"provider": self.name,
"configured": True,
"state": "error",
"message": str(exc),
"latency_ms": round((time.perf_counter() - started) * 1000),
}
return {
"provider": self.name,
"configured": True,
"state": state,
"latency_ms": round((time.perf_counter() - started) * 1000),
}
def fetch(self, dataset: str, params: dict[str, Any]) -> list[dict[str, Any]]:
if dataset in {"indexes_quotes", "index_quotes"}:
return self.fetch_indices()
raise AdapterError(f"{self.name} unsupported dataset: {dataset}")
def normalize(self, dataset: str, rows: list[dict[str, Any]]) -> list[dict[str, Any]]:
return list(rows)
def fetch_indices(self) -> list[dict[str, Any]]:
request = urllib.request.Request(
TENCENT_INDEX_URL,
headers={"User-Agent": BROWSER_UA, "Referer": "https://gu.qq.com/"},
method="GET",
)
try:
with urllib.request.urlopen(request, timeout=self.timeout) as response:
raw = response.read().decode("gb18030", errors="ignore")
except Exception as exc:
raise AdapterError(f"tencent request failed: {exc}") from exc
result = []
for line in raw.splitlines():
if '="' not in line:
continue
fields = line.split('="', 1)[1].rsplit('";', 1)[0].split("~")
if len(fields) < 38:
continue
code = fields[2]
if code not in {"000001", "399001", "399006"}:
continue
try:
quote_time = datetime.strptime(fields[30], "%Y%m%d%H%M%S").astimezone()
except ValueError as exc:
raise AdapterError(f"Tencent invalid quote time for {code}") from exc
ts_code = "000001.SH" if code == "000001" else f"{code}.SZ"
result.append(
{
"ts_code": ts_code,
"code": code,
"name": fields[1] or code,
"price": round4(finite_number(fields[3])),
"pct_chg": round4(finite_number(fields[32])),
"change_amount": round4(finite_number(fields[31])),
"open": round4(finite_number(fields[5])),
"high": round4(finite_number(fields[33])),
"low": round4(finite_number(fields[34])),
"previous_close": round4(finite_number(fields[4])),
"amount": round4(finite_number(fields[37]) * 10000),
"quote_time_epoch": int(quote_time.timestamp()),
"quote_time": quote_time.isoformat(timespec="seconds"),
"source": "tencent_qt",
}
)
if len(result) != 3:
raise AdapterError(f"Tencent returned {len(result)}/3 indices")
return result
+108 -11
View File
@@ -11,8 +11,12 @@ from datahub.normalize import (
normalize_auction,
normalize_calendar,
normalize_daily,
normalize_dragon_tiger,
normalize_index_daily,
normalize_limit_event,
normalize_moneyflow,
normalize_popularity,
normalize_sector_daily,
normalize_stock,
normalize_valuation,
)
@@ -31,6 +35,21 @@ TUSHARE_FIELDS = {
"buy_lg_amount,sell_lg_amount,buy_elg_amount,sell_elg_amount,net_mf_amount"
),
"stk_auction": "ts_code,trade_date,vol,price,amount,pre_close,turnover_rate,volume_ratio,float_share",
"limit_list_d": (
"trade_date,ts_code,industry,name,close,pct_chg,amount,limit_amount,"
"float_mv,total_mv,turnover_ratio,fd_amount,first_time,last_time,"
"open_times,up_stat,limit_times,limit_type"
),
"ths_hot": "ts_code,ts_name,hot,rank,pct_change,current_price,concept,data_type,trade_date",
"dc_hot": "ts_code,ts_name,rank,pct_change,current_price,hot,concept,data_type,trade_date",
"hm_detail": "trade_date,ts_code,ts_name,buy_amount,sell_amount,net_amount,hm_name,hm_orgs,tag",
"hm_list": "name,desc,orgs",
"top_list": "trade_date,ts_code,name,pct_change,reason",
"top_inst": "trade_date,ts_code,exalter,buy,buy_rate,sell,sell_rate,net_buy,side,reason",
"ths_index": "ts_code,name,count,exchange,list_date,type",
"ths_daily": "ts_code,trade_date,open,high,low,close,pre_close,pct_change,vol,turnover_rate",
"dc_index": "ts_code,trade_date,name,open,high,low,close,pre_close,pct_change,vol,amount,turnover_rate",
"sw_daily": "ts_code,trade_date,name,open,high,low,close,pct_change,vol,amount",
}
DATASET_API = {
@@ -42,12 +61,15 @@ DATASET_API = {
"index_daily": "index_daily",
"moneyflow": "moneyflow",
"auction": "stk_auction",
"limit_events": "limit_list_d",
"popularity": "ths_hot",
"dragon_tiger": "hm_detail",
"sector_daily": "ths_daily",
}
# Website actual index usage: market cards / 90-day charts (SH/SZ/CYB) plus
# screener 沪深300 benchmark (lookback up to 260 trading days).
WEBSITE_INDEX_CODES = ("000001.SH", "399001.SZ", "399006.SZ", "000300.SH")
DEFAULT_INDEX_CODES = WEBSITE_INDEX_CODES
LIMIT_TYPES = ("U", "D", "Z")
class TushareAdapter(MarketAdapter):
@@ -85,6 +107,14 @@ class TushareAdapter(MarketAdapter):
}
def fetch(self, dataset: str, params: dict[str, Any]) -> list[dict[str, Any]]:
if dataset == "limit_events":
return self.fetch_limit_events(str(params.get("trade_date") or ""))
if dataset == "popularity":
return self.fetch_popularity(str(params.get("trade_date") or ""))
if dataset == "dragon_tiger":
return self.fetch_dragon_tiger(str(params.get("trade_date") or ""))
if dataset == "sector_daily":
return self.fetch_sector_daily(str(params.get("trade_date") or ""))
api_name = DATASET_API.get(dataset, dataset)
fields = TUSHARE_FIELDS.get(api_name, "")
query_params = dict(params)
@@ -93,10 +123,67 @@ class TushareAdapter(MarketAdapter):
if api_name == "trade_cal" and "exchange" not in query_params:
query_params["exchange"] = "SSE"
if api_name == "index_daily" and "ts_code" not in query_params:
# Caller typically loops codes; a missing code would pull nothing useful.
query_params.setdefault("ts_code", DEFAULT_INDEX_CODES[0])
return self._query(api_name, query_params, fields)
def fetch_limit_events(self, trade_date: str) -> list[dict[str, Any]]:
rows: list[dict[str, Any]] = []
for limit_type in LIMIT_TYPES:
part = self._query(
"limit_list_d",
{"trade_date": trade_date, "limit_type": limit_type},
TUSHARE_FIELDS["limit_list_d"],
)
for row in part:
row = dict(row)
row.setdefault("limit_type", limit_type)
rows.append(row)
return rows
def fetch_popularity(self, trade_date: str) -> list[dict[str, Any]]:
rows: list[dict[str, Any]] = []
for api_name, source in (("ths_hot", "ths"), ("dc_hot", "dc")):
for row in self._query(api_name, {"trade_date": trade_date}, TUSHARE_FIELDS[api_name]):
item = dict(row)
item["source"] = source
item.setdefault("trade_date", trade_date)
rows.append(item)
return rows
def fetch_dragon_tiger(self, trade_date: str) -> list[dict[str, Any]]:
details = self._query("hm_detail", {"trade_date": trade_date}, TUSHARE_FIELDS["hm_detail"])
top_rows = self._query("top_list", {"trade_date": trade_date}, TUSHARE_FIELDS["top_list"])
context = {
str(row.get("ts_code") or ""): row
for row in top_rows
if str(row.get("ts_code") or "")
}
rows: list[dict[str, Any]] = []
for row in details:
item = dict(row)
stock = context.get(str(item.get("ts_code") or ""), {})
if item.get("pct_change") is None and stock.get("pct_change") is not None:
item["pct_change"] = stock.get("pct_change")
if not item.get("reason") and stock.get("reason"):
item["reason"] = stock.get("reason")
if not item.get("ts_name") and stock.get("name"):
item["ts_name"] = stock.get("name")
rows.append(item)
return rows
def fetch_sector_daily(self, trade_date: str) -> list[dict[str, Any]]:
rows: list[dict[str, Any]] = []
for api_name, family in (("ths_daily", "ths"), ("dc_index", "dc"), ("sw_daily", "sw")):
try:
part = self._query(api_name, {"trade_date": trade_date}, TUSHARE_FIELDS[api_name])
except AdapterError:
part = []
for row in part:
item = dict(row)
item["family"] = family
rows.append(item)
return rows
def fetch_index_daily(self, trade_date: str, codes: tuple[str, ...] = DEFAULT_INDEX_CODES) -> list[dict[str, Any]]:
rows: list[dict[str, Any]] = []
for ts_code in codes:
@@ -104,6 +191,17 @@ class TushareAdapter(MarketAdapter):
return rows
def normalize(self, dataset: str, rows: list[dict[str, Any]]) -> list[dict[str, Any]]:
if dataset in {"limit_events", "limit_list_d"}:
return [normalize_limit_event(row) for row in rows]
if dataset == "popularity":
return [normalize_popularity(row, source=str(row.get("source") or "")) for row in rows]
if dataset == "dragon_tiger":
return [normalize_dragon_tiger(row) for row in rows]
if dataset == "sector_daily":
return [
normalize_sector_daily(row, family=str(row.get("family") or "ths"))
for row in rows
]
mapping = {
"calendar": normalize_calendar,
"trade_cal": normalize_calendar,
@@ -148,12 +246,11 @@ class TushareAdapter(MarketAdapter):
try:
with urllib.request.urlopen(request, timeout=self.timeout) as response:
result = json.loads(response.read().decode("utf-8"))
except json.JSONDecodeError:
raise AdapterError("Tushare returned invalid json") from None
except (urllib.error.URLError, TimeoutError) as exc:
raise AdapterError(f"Tushare request failed: {exc}") from exc
if result.get("code") != 0:
raise AdapterError(result.get("msg") or "Tushare returned an unknown error")
except (urllib.error.URLError, TimeoutError, json.JSONDecodeError) as exc:
raise AdapterError(f"Tushare 请求失败: {exc}") from exc
if result.get("code") not in (0, "0", None):
raise AdapterError(str(result.get("msg") or f"Tushare error {result.get('code')}"))
data = result.get("data") or {}
columns = data.get("fields") or []
return [dict(zip(columns, item)) for item in data.get("items") or []]
items = data.get("items") or []
fields_list = data.get("fields") or (fields.split(",") if fields else [])
return [dict(zip(fields_list, item)) for item in items]
+18 -2
View File
@@ -6,7 +6,7 @@ from typing import Any
from datahub.adapters import RESERVED
from datahub.auth import AuthService
from datahub.db import HubDB
from datahub.pipeline import Pipeline
from datahub.pipeline import OFFICIAL_DATASETS, STOCKS_DATASET, Pipeline
from datahub.scheduler import Scheduler
from datahub.serving import ApiError
from datahub.timeutil import isoformat, now_shanghai, session_phase, yyyymmdd
@@ -39,6 +39,7 @@ class AdminAPI:
"session_phase": session_phase(now_shanghai(), is_open),
"is_open_day": is_open,
"eod_status": self.scheduler.eod_status(today),
"revision_status": self.scheduler.revision_status(today),
"publications": pubs,
"anomalies": failed,
"recent_calls": _public_calls(calls),
@@ -91,6 +92,7 @@ class AdminAPI:
{"id": "eod_a", "at": "15:05", "title": "盘后批 A daily/valuation/moneyflow/auction"},
{"id": "eod_b", "at": "15:10", "title": "盘后批 B index_daily"},
{"id": "eod_retry", "at": "15:15-23:30", "title": "盘后未出数自动重试(每 30 分钟,成功即停)"},
{"id": "eod_revise", "at": "20:00-23:20", "title": "估值发布后复核(轻量比对,有修订才整组原子追补)"},
{"id": "stocks_refresh", "at": stocks_times, "title": "股票主档刷新与正式发布(新上市/更名,无变化跳过)"},
{"id": "history_backfill", "at": "manual", "title": "回补历史日历与指数日 K"},
{"id": "cleanup", "at": "00:30", "title": "清理 staging / 日志"},
@@ -143,8 +145,22 @@ class AdminAPI:
self._dangerous(password, confirm, f"{dataset}:{day}")
if dataset == "reference":
result = self.pipeline.ingest_reference(day)
elif dataset in OFFICIAL_DATASETS or dataset == STOCKS_DATASET:
# Manual same-day republish must rebuild the full A/B boundary.
# Gate failures and mid-switch exceptions both surface as
# FAILED_PRECONDITION so the admin API never leaks raw
# transaction errors to the client.
try:
result = self.pipeline.force_republish_boundary(dataset, day)
failures = self.pipeline.eod_failures(result)
if failures:
raise ApiError("FAILED_PRECONDITION", "; ".join(failures))
except ApiError:
raise
except Exception as exc:
raise ApiError("FAILED_PRECONDITION", str(exc)) from exc
else:
result = self.pipeline.run_dataset(dataset, day)
raise ApiError("INVALID_ARGUMENT", f"unsupported backfill dataset: {dataset}")
self.pipeline.audit(actor, "backfill", f"{dataset}:{day}", json.dumps({"ok": True}))
return result
+15 -14
View File
@@ -7,7 +7,7 @@ import json
import sys
from datahub.hub import build_hub
from datahub.pipeline import OFFICIAL_DATASETS
from datahub.pipeline import EOD_A_DATASETS, OFFICIAL_DATASETS, STOCKS_DATASET
from datahub.settings import load_settings
from datahub.timeutil import yyyymmdd
@@ -19,15 +19,15 @@ def main(argv: list[str] | None = None) -> int:
history.add_argument("--calendar-start", default=None, help="日历起点,默认配置 calendar_start")
history.add_argument("--index-days", type=int, default=None, help="指数回补交易日数量,默认 260")
history.add_argument("--force", action="store_true", help="覆盖已发布的指数日期")
refresh = sub.add_parser("eod-refresh", help="对指定交易日补跑盘后正式数据(跳过已发布数据集,仍走质量门禁)")
refresh = sub.add_parser("eod-refresh", help="对指定交易日补跑盘后正式数据(跳过已完整发布的一致性边界,仍走质量门禁)")
refresh.add_argument("--trade-date", default=None, help="交易日 YYYYMMDD,默认今天")
refresh.add_argument(
"--force", action="store_true",
help=" --dataset 指定的数据集强制重取重发(生成新批次保留上一批次可回滚",
help="强制重发 --dataset 所属的完整一致性边界(A 组或 B 组),生成新批次保留上一批次可回滚",
)
refresh.add_argument(
"--dataset", default=None,
help="配合 --force 使用:只强制重发该数据集(如 valuation",
help="配合 --force:指定边界内任一成员(如 valuation→整组 Aindex_daily→整组 B",
)
stocks_refresh = sub.add_parser("stocks-refresh", help="刷新股票主档并发布正式快照(幂等:无变化则跳过)")
stocks_refresh.add_argument("--trade-date", default=None, help="交易日 YYYYMMDD,默认今天")
@@ -54,26 +54,27 @@ def main(argv: list[str] | None = None) -> int:
if args.command == "eod-refresh":
day = yyyymmdd(args.trade_date) if args.trade_date else yyyymmdd()
if args.force:
datasets = tuple(sorted({args.dataset} & OFFICIAL_DATASETS)) if args.dataset else ()
if args.dataset and not datasets:
parser.error(f"unknown dataset: {args.dataset}")
if not datasets:
allowed = set(OFFICIAL_DATASETS) | {STOCKS_DATASET}
if not args.dataset:
parser.error("--force requires --dataset (e.g. --dataset valuation)")
result = {}
for dataset in datasets:
result[dataset] = hub.pipeline.run_dataset(dataset, day)
if args.dataset not in allowed:
parser.error(f"unknown dataset: {args.dataset}")
result = hub.pipeline.force_republish_boundary(args.dataset, day)
boundary = "A" if args.dataset in EOD_A_DATASETS or args.dataset == STOCKS_DATASET else "B"
else:
result = hub.pipeline.run_eod_missing(day)
boundary = None
hub.pipeline.audit("cli", "eod-refresh", f"eod:{day}", json.dumps(
{"force": bool(args.force), "dataset": args.dataset,
{"force": bool(args.force), "dataset": args.dataset, "boundary": boundary,
**{name: item.get("state") for name, item in result.items() if isinstance(item, dict)}},
ensure_ascii=False,
))
if args.force:
payload = {"trade_date": day, "datasets": result}
failures = hub.pipeline.eod_failures(result)
payload = {"trade_date": day, "boundary": boundary, "datasets": result}
json.dump(payload, sys.stdout, ensure_ascii=False, indent=2, default=str)
sys.stdout.write("\n")
return 0
return 0 if not failures else 1
missing = hub.pipeline.missing_official_datasets(day)
payload = {"trade_date": day, "datasets": result, "missing_after": missing}
json.dump(payload, sys.stdout, ensure_ascii=False, indent=2, default=str)
+180
View File
@@ -0,0 +1,180 @@
"""Extended EOD datasets beyond the first-batch A/B release groups.
These publish independently (soft): a failure here must not block daily/valuation
release. Scheduler runs them after the core EOD window.
"""
from __future__ import annotations
from typing import Any
# Independent soft datasets (not part of A/B atomic groups).
EXTENDED_SOFT_DATASETS = {
"limit_events",
"popularity",
"dragon_tiger",
"sector_daily",
}
EXTENDED_SCHEMA = """
CREATE TABLE IF NOT EXISTS eod_limit_events (
ts_code TEXT NOT NULL, trade_date TEXT NOT NULL, limit_type TEXT NOT NULL,
name TEXT, industry TEXT, close REAL, pct_chg REAL, amount REAL,
limit_amount REAL, float_mv REAL, total_mv REAL, turnover_ratio REAL,
fd_amount REAL, first_time TEXT, last_time TEXT,
open_times INTEGER, up_stat TEXT, limit_times INTEGER,
batch_id TEXT NOT NULL,
PRIMARY KEY (ts_code, trade_date, limit_type, batch_id)
) WITHOUT ROWID;
CREATE TABLE IF NOT EXISTS staging_limit_events (
ts_code TEXT NOT NULL, trade_date TEXT NOT NULL, limit_type TEXT NOT NULL, batch_id TEXT NOT NULL,
name TEXT, industry TEXT, close REAL, pct_chg REAL, amount REAL,
limit_amount REAL, float_mv REAL, total_mv REAL, turnover_ratio REAL,
fd_amount REAL, first_time TEXT, last_time TEXT,
open_times INTEGER, up_stat TEXT, limit_times INTEGER,
PRIMARY KEY (batch_id, ts_code, trade_date, limit_type)
);
CREATE TABLE IF NOT EXISTS eod_popularity (
ts_code TEXT NOT NULL, trade_date TEXT NOT NULL, source TEXT NOT NULL,
ts_name TEXT, rank INTEGER, pct_change REAL, current_price REAL,
hot REAL, concept TEXT, data_type TEXT,
batch_id TEXT NOT NULL,
PRIMARY KEY (ts_code, trade_date, source, batch_id)
) WITHOUT ROWID;
CREATE TABLE IF NOT EXISTS staging_popularity (
ts_code TEXT NOT NULL, trade_date TEXT NOT NULL, source TEXT NOT NULL, batch_id TEXT NOT NULL,
ts_name TEXT, rank INTEGER, pct_change REAL, current_price REAL,
hot REAL, concept TEXT, data_type TEXT,
PRIMARY KEY (batch_id, ts_code, trade_date, source)
);
CREATE TABLE IF NOT EXISTS eod_dragon_tiger (
ts_code TEXT NOT NULL, trade_date TEXT NOT NULL, hm_name TEXT NOT NULL,
ts_name TEXT, buy_amount REAL, sell_amount REAL, net_amount REAL,
hm_orgs TEXT, tag TEXT, pct_change REAL, reason TEXT,
batch_id TEXT NOT NULL,
PRIMARY KEY (ts_code, trade_date, hm_name, batch_id)
) WITHOUT ROWID;
CREATE TABLE IF NOT EXISTS staging_dragon_tiger (
ts_code TEXT NOT NULL, trade_date TEXT NOT NULL, hm_name TEXT NOT NULL, batch_id TEXT NOT NULL,
ts_name TEXT, buy_amount REAL, sell_amount REAL, net_amount REAL,
hm_orgs TEXT, tag TEXT, pct_change REAL, reason TEXT,
PRIMARY KEY (batch_id, ts_code, trade_date, hm_name)
);
CREATE TABLE IF NOT EXISTS eod_sector_daily (
ts_code TEXT NOT NULL, trade_date TEXT NOT NULL, family TEXT NOT NULL,
name TEXT, open REAL, high REAL, low REAL, close REAL, pre_close REAL,
pct_change REAL, vol REAL, turnover_rate REAL, amount REAL,
batch_id TEXT NOT NULL,
PRIMARY KEY (ts_code, trade_date, family, batch_id)
) WITHOUT ROWID;
CREATE TABLE IF NOT EXISTS staging_sector_daily (
ts_code TEXT NOT NULL, trade_date TEXT NOT NULL, family TEXT NOT NULL, batch_id TEXT NOT NULL,
name TEXT, open REAL, high REAL, low REAL, close REAL, pre_close REAL,
pct_change REAL, vol REAL, turnover_rate REAL, amount REAL,
PRIMARY KEY (batch_id, ts_code, trade_date, family)
);
CREATE TABLE IF NOT EXISTS sector_master (
ts_code TEXT PRIMARY KEY,
name TEXT,
family TEXT NOT NULL,
exchange TEXT,
list_date TEXT,
member_count INTEGER,
type TEXT,
updated_at TEXT NOT NULL
);
CREATE INDEX IF NOT EXISTS idx_eod_limit_date ON eod_limit_events(trade_date, batch_id);
CREATE INDEX IF NOT EXISTS idx_eod_pop_date ON eod_popularity(trade_date, batch_id);
CREATE INDEX IF NOT EXISTS idx_eod_lhb_date ON eod_dragon_tiger(trade_date, batch_id);
CREATE INDEX IF NOT EXISTS idx_eod_sector_date ON eod_sector_daily(trade_date, family, batch_id);
"""
EXTENDED_DATASET_TABLES = {
"limit_events": ("eod_limit_events", "staging_limit_events"),
"popularity": ("eod_popularity", "staging_popularity"),
"dragon_tiger": ("eod_dragon_tiger", "staging_dragon_tiger"),
"sector_daily": ("eod_sector_daily", "staging_sector_daily"),
}
EXTENDED_STAGING_INSERT: dict[str, tuple[str, Any]] = {
"limit_events": (
"INSERT INTO staging_limit_events("
"ts_code,trade_date,limit_type,batch_id,name,industry,close,pct_chg,amount,"
"limit_amount,float_mv,total_mv,turnover_ratio,fd_amount,first_time,last_time,"
"open_times,up_stat,limit_times) VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)",
lambda r, b: (
r["ts_code"], r["trade_date"], r["limit_type"], b,
r.get("name"), r.get("industry"), r.get("close"), r.get("pct_chg"), r.get("amount"),
r.get("limit_amount"), r.get("float_mv"), r.get("total_mv"), r.get("turnover_ratio"),
r.get("fd_amount"), r.get("first_time"), r.get("last_time"),
r.get("open_times"), r.get("up_stat"), r.get("limit_times"),
),
),
"popularity": (
"INSERT INTO staging_popularity("
"ts_code,trade_date,source,batch_id,ts_name,rank,pct_change,current_price,hot,concept,data_type) "
"VALUES (?,?,?,?,?,?,?,?,?,?,?)",
lambda r, b: (
r["ts_code"], r["trade_date"], r["source"], b,
r.get("ts_name"), r.get("rank"), r.get("pct_change"), r.get("current_price"),
r.get("hot"), r.get("concept"), r.get("data_type"),
),
),
"dragon_tiger": (
"INSERT INTO staging_dragon_tiger("
"ts_code,trade_date,hm_name,batch_id,ts_name,buy_amount,sell_amount,net_amount,"
"hm_orgs,tag,pct_change,reason) VALUES (?,?,?,?,?,?,?,?,?,?,?,?)",
lambda r, b: (
r["ts_code"], r["trade_date"], r["hm_name"], b,
r.get("ts_name"), r.get("buy_amount"), r.get("sell_amount"), r.get("net_amount"),
r.get("hm_orgs"), r.get("tag"), r.get("pct_change"), r.get("reason"),
),
),
"sector_daily": (
"INSERT INTO staging_sector_daily("
"ts_code,trade_date,family,batch_id,name,open,high,low,close,pre_close,"
"pct_change,vol,turnover_rate,amount) VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?)",
lambda r, b: (
r["ts_code"], r["trade_date"], r["family"], b,
r.get("name"), r.get("open"), r.get("high"), r.get("low"), r.get("close"),
r.get("pre_close"), r.get("pct_change"), r.get("vol"), r.get("turnover_rate"),
r.get("amount"),
),
),
}
EXTENDED_EOD_COPY = {
"limit_events": (
"INSERT OR REPLACE INTO eod_limit_events "
"SELECT ts_code,trade_date,limit_type,name,industry,close,pct_chg,amount,"
"limit_amount,float_mv,total_mv,turnover_ratio,fd_amount,first_time,last_time,"
"open_times,up_stat,limit_times,batch_id "
"FROM staging_limit_events WHERE batch_id = ?"
),
"popularity": (
"INSERT OR REPLACE INTO eod_popularity "
"SELECT ts_code,trade_date,source,ts_name,rank,pct_change,current_price,hot,concept,data_type,batch_id "
"FROM staging_popularity WHERE batch_id = ?"
),
"dragon_tiger": (
"INSERT OR REPLACE INTO eod_dragon_tiger "
"SELECT ts_code,trade_date,hm_name,ts_name,buy_amount,sell_amount,net_amount,"
"hm_orgs,tag,pct_change,reason,batch_id "
"FROM staging_dragon_tiger WHERE batch_id = ?"
),
"sector_daily": (
"INSERT OR REPLACE INTO eod_sector_daily "
"SELECT ts_code,trade_date,family,name,open,high,low,close,pre_close,"
"pct_change,vol,turnover_rate,amount,batch_id "
"FROM staging_sector_daily WHERE batch_id = ?"
),
}
+18 -1
View File
@@ -7,9 +7,10 @@ from contextlib import contextmanager
from pathlib import Path
from typing import Any
from datahub.datasets_ext import EXTENDED_DATASET_TABLES, EXTENDED_SCHEMA
from datahub.timeutil import isoformat
SCHEMA = """
_BASE_SCHEMA = """
CREATE TABLE IF NOT EXISTS schema_migrations (
version INTEGER PRIMARY KEY,
applied_at TEXT NOT NULL
@@ -238,6 +239,19 @@ CREATE TABLE IF NOT EXISTS eod_progress (
updated_at TEXT NOT NULL
);
CREATE TABLE IF NOT EXISTS revision_progress (
trade_date TEXT PRIMARY KEY,
state TEXT NOT NULL,
attempts INTEGER NOT NULL DEFAULT 0,
last_attempt_at TEXT,
next_retry_at TEXT,
finished_at TEXT,
catchup_done INTEGER NOT NULL DEFAULT 0,
last_diff TEXT,
detail TEXT,
updated_at TEXT NOT NULL
);
CREATE TABLE IF NOT EXISTS audit_log (
id INTEGER PRIMARY KEY AUTOINCREMENT,
actor TEXT NOT NULL,
@@ -282,6 +296,8 @@ CREATE INDEX IF NOT EXISTS idx_eod_bars_date ON eod_bars(trade_date, batch_id);
CREATE INDEX IF NOT EXISTS idx_calendar_open ON trade_calendar(is_open, cal_date);
"""
SCHEMA = _BASE_SCHEMA + EXTENDED_SCHEMA
DATASET_TABLES = {
"daily": ("eod_bars", "staging_bars"),
"valuation": ("eod_valuation", "staging_valuation"),
@@ -289,6 +305,7 @@ DATASET_TABLES = {
"auction": ("eod_auction", "staging_auction"),
"index_daily": ("eod_index_bars", "staging_index_bars"),
"stocks": ("eod_stocks", "staging_stocks"),
**EXTENDED_DATASET_TABLES,
}
+94
View File
@@ -156,6 +156,95 @@ def normalize_stock(row: dict[str, Any]) -> dict[str, Any]:
}
def normalize_limit_event(row: dict[str, Any]) -> dict[str, Any]:
"""limit_list_d. float_mv/total_mv/limit_amount are 万元 → yuan; amount/fd_amount already yuan."""
return {
"ts_code": _code(row.get("ts_code")),
"trade_date": _date(row.get("trade_date")),
"limit_type": str(row.get("limit_type") or "").strip().upper() or "U",
"name": str(row.get("name") or "").strip() or None,
"industry": str(row.get("industry") or "").strip() or None,
"close": round4(finite_number(row.get("close"))),
"pct_chg": round4(finite_number(row.get("pct_chg"))),
"amount": round4(finite_number(row.get("amount"))),
"limit_amount": round4(_scale(row.get("limit_amount"), AMOUNT_WAN_YUAN)),
"float_mv": round4(_scale(row.get("float_mv"), AMOUNT_WAN_YUAN)),
"total_mv": round4(_scale(row.get("total_mv"), AMOUNT_WAN_YUAN)),
"turnover_ratio": round4(finite_number(row.get("turnover_ratio"))),
"fd_amount": round4(finite_number(row.get("fd_amount"))),
"first_time": str(row.get("first_time") or "").strip() or None,
"last_time": str(row.get("last_time") or "").strip() or None,
"open_times": _optional_int(row.get("open_times")),
"up_stat": str(row.get("up_stat") or "").strip() or None,
"limit_times": _optional_int(row.get("limit_times")),
}
def normalize_popularity(row: dict[str, Any], source: str = "") -> dict[str, Any]:
src = str(source or row.get("source") or "").strip().lower() or "ths"
return {
"ts_code": _code(row.get("ts_code")),
"trade_date": _date(row.get("trade_date")),
"source": src,
"ts_name": str(row.get("ts_name") or row.get("name") or "").strip() or None,
"rank": _optional_int(row.get("rank")),
"pct_change": round4(
finite_number(row.get("pct_change") if row.get("pct_change") is not None else row.get("pct_chg"))
),
"current_price": round4(finite_number(row.get("current_price") or row.get("price"))),
"hot": round4(finite_number(row.get("hot"))),
"concept": str(row.get("concept") or "").strip() or None,
"data_type": str(row.get("data_type") or "").strip() or None,
}
def normalize_dragon_tiger(row: dict[str, Any]) -> dict[str, Any]:
"""hm_detail amounts are 万元 → yuan."""
return {
"ts_code": _code(row.get("ts_code")),
"trade_date": _date(row.get("trade_date")),
"hm_name": str(row.get("hm_name") or "未命名游资").strip() or "未命名游资",
"ts_name": str(row.get("ts_name") or row.get("name") or "").strip() or None,
"buy_amount": round4(_scale(row.get("buy_amount"), AMOUNT_WAN_YUAN)),
"sell_amount": round4(_scale(row.get("sell_amount"), AMOUNT_WAN_YUAN)),
"net_amount": round4(_scale(row.get("net_amount"), AMOUNT_WAN_YUAN)),
"hm_orgs": str(row.get("hm_orgs") or "").strip() or None,
"tag": str(row.get("tag") or "").strip() or None,
"pct_change": round4(finite_number(row.get("pct_change"))),
"reason": str(row.get("reason") or "").strip() or None,
}
def normalize_sector_daily(row: dict[str, Any], family: str = "ths") -> dict[str, Any]:
fam = str(family or row.get("family") or "ths").strip().lower()
return {
"ts_code": _code(row.get("ts_code")),
"trade_date": _date(row.get("trade_date")),
"family": fam,
"name": str(row.get("name") or "").strip() or None,
"open": round4(finite_number(row.get("open"))),
"high": round4(finite_number(row.get("high"))),
"low": round4(finite_number(row.get("low"))),
"close": round4(finite_number(row.get("close"))),
"pre_close": round4(finite_number(row.get("pre_close"))),
"pct_change": round4(
finite_number(row.get("pct_change") if row.get("pct_change") is not None else row.get("pct_chg"))
),
"vol": round4(finite_number(row.get("vol"))),
"turnover_rate": round4(finite_number(row.get("turnover_rate"))),
"amount": round4(finite_number(row.get("amount"))),
}
def _optional_int(value: Any) -> int | None:
if value in (None, ""):
return None
try:
return int(float(value))
except (TypeError, ValueError):
return None
def apply_qfq(price: float | None, factor: float | None, latest_factor: float | None) -> float | None:
if price is None:
return None
@@ -184,6 +273,11 @@ NORMALIZERS = {
"calendar": normalize_calendar,
"stock_basic": normalize_stock,
"stocks": normalize_stock,
"limit_events": normalize_limit_event,
"limit_list_d": normalize_limit_event,
"popularity": normalize_popularity,
"dragon_tiger": normalize_dragon_tiger,
"sector_daily": normalize_sector_daily,
}
+457 -54
View File
@@ -9,24 +9,39 @@ from typing import Any
from datahub.adapters.base import AdapterError
from datahub.adapters.tushare import DEFAULT_INDEX_CODES, WEBSITE_INDEX_CODES, TushareAdapter
from datahub.datasets_ext import (
EXTENDED_EOD_COPY,
EXTENDED_SOFT_DATASETS,
EXTENDED_STAGING_INSERT,
)
from datahub.db import DATASET_TABLES, HubDB
from datahub.governance.circuit import CircuitBreaker
from datahub.governance.ratelimit import TokenBucket
from datahub.governance.retry import RetryError, retry_call
from datahub.logutil import get_logger
from datahub.normalize import finite_number, normalize_daily
from datahub.revision import (
compare_fields,
diff_published_vs_upstream,
official_table,
revision_datasets,
)
from datahub.settings import Settings
from datahub.timeutil import add_days, isoformat, now_shanghai, yyyymmdd
LOGGER = get_logger()
HARD_DATASETS = {"daily", "valuation", "index_daily"}
SOFT_DATASETS = {"moneyflow", "auction"}
OFFICIAL_DATASETS = HARD_DATASETS | SOFT_DATASETS
SOFT_DATASETS = {"moneyflow", "auction"} | EXTENDED_SOFT_DATASETS
OFFICIAL_DATASETS = HARD_DATASETS | {"moneyflow", "auction"} # A/B retry scope unchanged
STOCKS_DATASET = "stocks"
STOCK_SNAPSHOT_FIELDS = ("ts_code", "symbol", "name", "area", "industry", "market", "list_status", "list_date")
EOD_A_DATASETS = ("daily", "valuation", "moneyflow", "auction")
EOD_B_DATASETS = ("index_daily",)
EOD_C_DATASETS = ("limit_events",)
EOD_D_DATASETS = ("dragon_tiger",)
EOD_E_DATASETS = ("sector_daily",)
EOD_F_DATASETS = ("popularity",)
EMPTY_BATCH_ERROR = "empty official batch: 0 valid rows"
STAGING_INSERT = {
@@ -80,6 +95,7 @@ STAGING_INSERT = {
r.get("close"), r.get("pct_chg"), r.get("volume"), r.get("amount"),
),
),
**EXTENDED_STAGING_INSERT,
}
EOD_COPY = {
@@ -114,6 +130,7 @@ EOD_COPY = {
"SELECT ts_code,trade_date,open,high,low,close,pct_chg,volume,amount,batch_id "
"FROM staging_index_bars WHERE batch_id = ?"
),
**EXTENDED_EOD_COPY,
}
@@ -348,11 +365,20 @@ class Pipeline:
is published; ``force`` re-publishes unconditionally. New listings,
renames (incl. N/C prefix removal) and status changes all flow into
the snapshot, which carries batch_id/published_at metadata.
The ``stock_master`` UPSERT happens inside the same publish
transaction as the snapshot switch — fetch / quality-gate / switch
failures leave the master on the previous complete values.
"""
day = yyyymmdd(trade_date or self.clock())
rows = self._fetch_dataset(STOCKS_DATASET, day)
with self.db.write() as connection:
self._upsert_stock_master(connection, rows, isoformat(self.clock()))
try:
rows = self._fetch_dataset(STOCKS_DATASET, day)
except Exception as exc:
self.audit(
"pipeline", "stocks-refresh", f"{STOCKS_DATASET}:{day}",
json.dumps({"state": "failed", "error": str(exc)}, ensure_ascii=False),
)
raise
if not force:
active, snapshot = self.published_stock_snapshot(day)
if active is not None:
@@ -369,7 +395,14 @@ class Pipeline:
"batch_id": active,
"rows": len(snapshot),
}
result = self.run_dataset(STOCKS_DATASET, day, prepared_rows=rows)
try:
result = self.run_dataset(STOCKS_DATASET, day, prepared_rows=rows)
except Exception as exc:
self.audit(
"pipeline", "stocks-refresh", f"{STOCKS_DATASET}:{day}",
json.dumps({"state": "failed", "error": str(exc)}, ensure_ascii=False),
)
raise
self.audit(
"pipeline", "stocks-refresh", f"{STOCKS_DATASET}:{day}",
json.dumps({"batch_id": result["batch_id"], "rows": result["rows"]}, ensure_ascii=False),
@@ -637,53 +670,374 @@ class Pipeline:
return [dataset for dataset in sorted(OFFICIAL_DATASETS) if dataset not in published]
def run_eod_missing(self, trade_date: str) -> dict[str, Any]:
"""Fetch/publish every official dataset still missing for the date.
"""Republish every incomplete EOD consistency group for the date.
Idempotent: datasets with an existing publication are skipped, so
repeats never overwrite the current official batch. All missing
members stage first and switch in one atomic release group; a single
member failure keeps the previous complete official version serving.
A-group (daily/valuation/moneyflow/auction + stocks) and B-group
(index_daily) are separate boundaries. Within a group, either the
whole boundary is already published (idempotent skip) or every
member is re-staged and switched together — never fill only the
missing members on top of older batches from an earlier partial run.
"""
return self.run_release_group(tuple(sorted(OFFICIAL_DATASETS)), trade_date, include_stocks=True)
def run_eod_batch_a(self, trade_date: str) -> dict[str, Any]:
return self.run_release_group(EOD_A_DATASETS, trade_date, include_stocks=True)
def run_eod_batch_b(self, trade_date: str) -> dict[str, Any]:
return self.run_release_group(EOD_B_DATASETS, trade_date)
def run_release_group(
self,
datasets: tuple[str, ...],
trade_date: str,
include_stocks: bool = False,
) -> dict[str, Any]:
"""One post-market publish/republish becomes one atomic visibility flip.
Consistency boundary: every member (official datasets, plus the daily
stocks snapshot when ``include_stocks`` and not yet published) is
fetched, staged, field-gated and cross-validated BEFORE any reader can
see it. Only when the whole group passes does a single SQLite
transaction copy all staging batches to the official tables and flip
every ``publications`` row at once. Any member failure aborts the
group: the previous complete official version keeps serving and the
reason is recorded on the batches and in the audit log.
"""
day = yyyymmdd(trade_date)
results: dict[str, Any] = {}
staged: dict[str, dict[str, Any]] = {}
failure: str | None = None
pending: list[str] = []
results.update(self.run_eod_batch_a(trade_date))
results.update(self.run_eod_batch_b(trade_date))
return results
def run_eod_batch_a(self, trade_date: str, force: bool = False) -> dict[str, Any]:
return self.run_release_group(EOD_A_DATASETS, trade_date, include_stocks=True, force=force)
def run_eod_batch_b(self, trade_date: str, force: bool = False) -> dict[str, Any]:
return self.run_release_group(EOD_B_DATASETS, trade_date, force=force)
def run_extended_soft(self, datasets: tuple[str, ...], trade_date: str, force: bool = False) -> dict[str, Any]:
"""Publish extended soft datasets independently (not A/B atomic)."""
results: dict[str, Any] = {}
day = yyyymmdd(trade_date)
for dataset in datasets:
if self.active_batch(dataset, day) is not None:
if not force and self.active_batch(dataset, day):
results[dataset] = {
"dataset": dataset,
"trade_date": day,
"state": "skipped",
"reason": "already_published",
}
else:
pending.append(dataset)
continue
try:
rows = self._fetch_dataset(dataset, day)
if not rows and dataset in {"popularity", "dragon_tiger"}:
results[dataset] = {
"dataset": dataset,
"trade_date": day,
"state": "skipped",
"reason": "upstream_empty",
"rows": 0,
}
continue
results[dataset] = self.run_dataset(dataset, day, prepared_rows=rows)
except Exception as exc:
results[dataset] = {
"dataset": dataset,
"trade_date": day,
"state": "failed",
"error": str(exc),
}
LOGGER.exception("extended soft publish failed dataset=%s date=%s", dataset, day)
return results
def run_eod_batch_c(self, trade_date: str, force: bool = False) -> dict[str, Any]:
return self.run_extended_soft(EOD_C_DATASETS, trade_date, force=force)
def run_eod_batch_d(self, trade_date: str, force: bool = False) -> dict[str, Any]:
return self.run_extended_soft(EOD_D_DATASETS, trade_date, force=force)
def run_eod_batch_e(self, trade_date: str, force: bool = False) -> dict[str, Any]:
return self.run_extended_soft(EOD_E_DATASETS, trade_date, force=force)
def run_eod_batch_f(self, trade_date: str, force: bool = False) -> dict[str, Any]:
return self.run_extended_soft(EOD_F_DATASETS, trade_date, force=force)
def force_republish_boundary(self, dataset: str, trade_date: str) -> dict[str, Any]:
"""Force-republish the full A/B consistency boundary that owns ``dataset``.
CLI ``eod-refresh --force`` and admin manual backfill must not publish a
single official member alone — that would mix old and new batches inside
the same trade date. Naming any A-group member (or stocks) rebuilds the
whole A group; naming ``index_daily`` rebuilds B. Extended soft datasets
republish independently.
"""
name = str(dataset or "").strip()
if name in EOD_A_DATASETS or name == STOCKS_DATASET:
return self.run_eod_batch_a(trade_date, force=True)
if name in EOD_B_DATASETS:
return self.run_eod_batch_b(trade_date, force=True)
if name in EXTENDED_SOFT_DATASETS:
return self.run_extended_soft((name,), trade_date, force=True)
raise ValueError(f"dataset is not part of an EOD release boundary: {dataset}")
def published_official_rows(self, dataset: str, trade_date: str) -> list[dict[str, Any]]:
day = yyyymmdd(trade_date)
batch_id = self.active_batch(dataset, day)
if not batch_id:
return []
fields = compare_fields(dataset)
table = official_table(dataset)
if fields:
columns = ",".join(fields)
return self.db.fetchall(
f"SELECT {columns} FROM {table} WHERE batch_id = ?",
(batch_id,),
)
return self.db.fetchall(f"SELECT * FROM {table} WHERE batch_id = ?", (batch_id,))
def compare_revision(self, dataset: str, trade_date: str) -> dict[str, Any]:
"""Light fetch of one revision-risk dataset vs the published official rows."""
day = yyyymmdd(trade_date)
published = self.published_official_rows(dataset, day)
if not published:
return {
"dataset": dataset,
"trade_date": day,
"changed": False,
"state": "skipped",
"reason": "not_published",
}
try:
upstream = self._fetch_dataset(dataset, day)
except Exception as exc:
return {
"dataset": dataset,
"trade_date": day,
"changed": False,
"state": "failed",
"reason": "upstream_error",
"error": str(exc),
}
if not upstream:
return {
"dataset": dataset,
"trade_date": day,
"changed": False,
"state": "failed",
"reason": "upstream_empty",
"error": "revision review upstream empty",
"published_rows": len(published),
"upstream_rows": 0,
}
listed = self.db.fetchone(
"SELECT COUNT(*) AS n FROM stock_master WHERE list_status = 'L'",
)
listed_n = int((listed or {}).get("n") or 0)
floor = float(self.settings.quality.get("daily_row_ratio") or 0.98)
if listed_n and len(upstream) / listed_n < floor:
return {
"dataset": dataset,
"trade_date": day,
"changed": False,
"state": "failed",
"reason": "incomplete",
"error": (
f"revision review incomplete: upstream {len(upstream)} "
f"/ listed {listed_n} < {floor}"
),
"published_rows": len(published),
"upstream_rows": len(upstream),
}
if len(upstream) < len(published) * floor:
return {
"dataset": dataset,
"trade_date": day,
"changed": False,
"state": "failed",
"reason": "incomplete",
"error": (
f"revision review incomplete: upstream {len(upstream)} "
f"< published {len(published)} * {floor}"
),
"published_rows": len(published),
"upstream_rows": len(upstream),
}
compared = diff_published_vs_upstream(dataset, published, upstream)
compared["trade_date"] = day
compared["state"] = "changed" if compared["changed"] else "unchanged"
compared["reason"] = "revised" if compared["changed"] else "unchanged"
return compared
def review_published_revisions(self, trade_date: str) -> dict[str, Any]:
"""Evening/morning catch-up: compare website fields, republish only on change.
Unchanged → no new batch. Changed → full A/B boundary quality gate +
atomic switch (HEL-459/460/461). Empty/failed/incomplete upstream keeps
the previous complete official version.
"""
day = yyyymmdd(trade_date)
results: dict[str, Any] = {}
for dataset in revision_datasets(self.settings.quality):
compared = self.compare_revision(dataset, day)
if compared.get("state") == "skipped":
results[dataset] = compared
continue
if compared.get("state") == "failed":
results[dataset] = compared
LOGGER.warning(
"revision review kept previous official version",
extra={
"hub": {
"dataset": dataset,
"trade_date": day,
"reason": compared.get("reason"),
"event": "revision_review_failed",
}
},
)
self.audit(
"pipeline", "revision-review", f"{dataset}:{day}",
json.dumps(
{
"state": "failed",
"reason": compared.get("reason"),
"error": compared.get("error"),
},
ensure_ascii=False,
),
)
continue
if not compared.get("changed"):
results[dataset] = {
"dataset": dataset,
"trade_date": day,
"state": "aligned",
"reason": "unchanged",
"published_rows": compared.get("published_rows"),
"upstream_rows": compared.get("upstream_rows"),
}
self.audit(
"pipeline", "revision-review", f"{dataset}:{day}",
json.dumps({"state": "aligned", "reason": "unchanged"}, ensure_ascii=False),
)
continue
LOGGER.info(
"revision review detected upstream rewrite, republishing boundary",
extra={
"hub": {
"dataset": dataset,
"trade_date": day,
"diffs": compared.get("diffs"),
"event": "revision_review_changed",
}
},
)
try:
published = self.force_republish_boundary(dataset, day)
except Exception as exc:
results[dataset] = {
"dataset": dataset,
"trade_date": day,
"state": "failed",
"reason": "republish_error",
"error": str(exc),
"diffs": compared.get("diffs"),
}
LOGGER.warning(
"revision republish failed, previous official version keeps serving",
extra={
"hub": {
"dataset": dataset,
"trade_date": day,
"reason": str(exc),
"event": "revision_review_failed",
}
},
)
self.audit(
"pipeline", "revision-review", f"{dataset}:{day}",
json.dumps(
{"state": "failed", "reason": "republish_error", "error": str(exc)},
ensure_ascii=False,
),
)
continue
failures = self.eod_failures(published)
if failures:
results.update(published)
results[dataset] = {
**(published.get(dataset) or {}),
"dataset": dataset,
"trade_date": day,
"state": "failed",
"reason": "quality_gate",
"error": "; ".join(failures),
"diffs": compared.get("diffs"),
}
self.audit(
"pipeline", "revision-review", f"{dataset}:{day}",
json.dumps(
{
"state": "failed",
"reason": "quality_gate",
"error": "; ".join(failures),
"diffs": compared.get("diffs"),
},
ensure_ascii=False,
),
)
continue
results.update(published)
results["review"] = {
"dataset": dataset,
"trade_date": day,
"state": "aligned",
"reason": "revised",
"diffs": compared.get("diffs"),
"missing_codes": compared.get("missing_codes"),
"extra_codes": compared.get("extra_codes"),
}
self.audit(
"pipeline", "revision-review", f"{dataset}:{day}",
json.dumps(
{
"state": "aligned",
"reason": "revised",
"diffs": compared.get("diffs"),
"switched": sorted(
name for name, item in published.items()
if isinstance(item, dict) and item.get("state") == "published"
),
},
ensure_ascii=False,
),
)
return results
def run_release_group(
self,
datasets: tuple[str, ...],
trade_date: str,
include_stocks: bool = False,
force: bool = False,
) -> dict[str, Any]:
"""One post-market publish/republish becomes one atomic visibility flip.
Consistency boundary: every member (official datasets, plus the daily
stocks snapshot when ``include_stocks``) is fetched, staged,
field-gated and cross-validated BEFORE any reader can see it. Only
when the whole group passes does a single SQLite transaction copy
all staging batches to the official tables and flip every
``publications`` row at once. Any member failure aborts the group:
the previous complete official version keeps serving and the reason
is recorded on the batches and in the audit log.
Skip is all-or-nothing for the boundary unless ``force``: if every
official member (and stocks when required) is already published, the
group is skipped. If any official member is still missing — or
``force`` is set — every official member is re-staged, so a retry or
manual republish never mixes old and new batches in one release.
"""
day = yyyymmdd(trade_date)
results: dict[str, Any] = {}
staged: dict[str, dict[str, Any]] = {}
failure: str | None = None
missing_official = [dataset for dataset in datasets if self.active_batch(dataset, day) is None]
stocks_missing = include_stocks and self.active_batch(STOCKS_DATASET, day) is None
if not force and not missing_official and not stocks_missing:
for dataset in datasets:
results[dataset] = {
"dataset": dataset,
"trade_date": day,
"state": "skipped",
"reason": "already_published",
}
if include_stocks:
results[STOCKS_DATASET] = {
"dataset": STOCKS_DATASET,
"trade_date": day,
"state": "skipped",
"reason": "already_published",
}
return results
# Incomplete or forced boundary → restage every official member together.
pending = list(datasets)
for dataset in pending:
if failure is not None:
@@ -705,9 +1059,13 @@ class Pipeline:
"error": str(exc),
}
if include_stocks and failure is None and self.active_batch(STOCKS_DATASET, day) is None:
# Stocks join the same switch when the official boundary is being
# rebuilt (missing or forced), or when only the stocks snapshot is
# still missing.
rebuild_official = bool(force or missing_official)
if include_stocks and failure is None and (rebuild_official or stocks_missing):
try:
stocks_plan = self._stage_stocks_snapshot(day)
stocks_plan = self._stage_stocks_snapshot(day, force=rebuild_official)
except Exception as exc:
failure = f"{STOCKS_DATASET}: {exc}"
results[STOCKS_DATASET] = {
@@ -756,8 +1114,32 @@ class Pipeline:
try:
self._switch_release_group(day, staged)
except Exception as exc:
reason = f"release group switch failed: {exc}"
for item in staged.values():
self._abandon_batch(item["batch_id"], f"release group switch failed: {exc}")
self._abandon_batch(item["batch_id"], reason)
LOGGER.warning(
"release group switch failed, previous official version keeps serving",
extra={
"hub": {
"trade_date": day,
"datasets": sorted(staged),
"reason": reason,
"event": "release_group_switch_failed",
}
},
)
self.audit(
"pipeline", "release-group", f"eod:{day}",
json.dumps(
{
"state": "failed",
"reason": reason,
"switched": [],
"force": bool(force),
},
ensure_ascii=False,
),
)
raise
for dataset, item in staged.items():
results[dataset] = {
@@ -770,7 +1152,8 @@ class Pipeline:
self.audit(
"pipeline", "release-group", f"eod:{day}",
json.dumps(
{"state": "ok", "switched": sorted(staged)}, ensure_ascii=False
{"state": "ok", "switched": sorted(staged), "force": bool(force)},
ensure_ascii=False,
),
)
return results
@@ -820,18 +1203,18 @@ class Pipeline:
"state": "degraded" if report["soft_fail"] else "published",
}
def _stage_stocks_snapshot(self, trade_date: str) -> dict[str, Any] | None:
def _stage_stocks_snapshot(self, trade_date: str, force: bool = False) -> dict[str, Any] | None:
"""Stage the daily stocks snapshot for a release group switch.
Returns None when the published snapshot is already identical to
upstream (idempotent skip). The stock_master upsert is deferred into
the group switch transaction so the master never runs ahead of the
published snapshot.
upstream (idempotent skip) unless ``force`` is set. The stock_master
upsert is deferred into the group switch / publish transaction so the
master never runs ahead of the published snapshot.
"""
day = yyyymmdd(trade_date)
active, snapshot = self.published_stock_snapshot(day)
rows = self._fetch_dataset(STOCKS_DATASET, day)
if active is not None:
if active is not None and not force:
upstream = sorted(
tuple(str(row.get(field)) for field in STOCK_SNAPSHOT_FIELDS) for row in rows
)
@@ -940,7 +1323,16 @@ class Pipeline:
)
listed_n = int((listed or {}).get("n") or 0)
row_n = len(rows)
keys = [(row.get("ts_code"), row.get("trade_date")) for row in rows]
if dataset == "limit_events":
keys = [(row.get("ts_code"), row.get("trade_date"), row.get("limit_type")) for row in rows]
elif dataset == "popularity":
keys = [(row.get("ts_code"), row.get("trade_date"), row.get("source")) for row in rows]
elif dataset == "dragon_tiger":
keys = [(row.get("ts_code"), row.get("trade_date"), row.get("hm_name")) for row in rows]
elif dataset == "sector_daily":
keys = [(row.get("ts_code"), row.get("trade_date"), row.get("family")) for row in rows]
else:
keys = [(row.get("ts_code"), row.get("trade_date")) for row in rows]
dup = row_n - len(set(keys))
if dup:
errors.append(f"duplicate keys: {dup}")
@@ -961,7 +1353,8 @@ class Pipeline:
errors.append(EMPTY_BATCH_ERROR)
field_report = self._field_gate(dataset, trade_date, rows, errors)
if dataset in SOFT_DATASETS:
hard_fail = bool(dup or bad_date or empty)
allow_empty = dataset in {"popularity", "dragon_tiger", "moneyflow", "auction"}
hard_fail = bool(dup or bad_date or (empty and not allow_empty))
else:
hard_fail = bool(errors) and (dataset in HARD_DATASETS or dataset == STOCKS_DATASET)
report = {
@@ -1077,6 +1470,16 @@ class Pipeline:
with self.db.write() as connection:
_staging_count_or_raise(connection, dataset, trade_date, batch_id)
connection.execute(EOD_COPY[dataset], (batch_id,))
if dataset == STOCKS_DATASET:
staging = DATASET_TABLES[STOCKS_DATASET][1]
stock_rows = [
dict(row)
for row in connection.execute(
f"SELECT * FROM {staging} WHERE batch_id = ?",
(batch_id,),
).fetchall()
]
self._upsert_stock_master(connection, stock_rows, published_at)
if self.before_commit:
self.before_commit()
_upsert_publication(connection, dataset, trade_date, batch_id, state, published_at)
+188
View File
@@ -0,0 +1,188 @@
"""Provisional (盘中观察) serving: quotes, index quotes, intraday points.
Free sources only. Never writes official eod_* tables. Uses rt_cache + LKG.
"""
from __future__ import annotations
import json
import time
from datetime import datetime
from typing import Any
from datahub.adapters.eastmoney import EastmoneyAdapter
from datahub.adapters.tencent import TencentAdapter
from datahub.codes import resolve_code
from datahub.db import HubDB
from datahub.timeutil import isoformat, now_shanghai, yyyymmdd
QUOTE_TTL = 60
INDEX_TTL = 60
INTRADAY_TTL = 20
class RealtimeApiError(RuntimeError):
def __init__(self, code: str, message: str) -> None:
super().__init__(message)
self.code = code
self.message = message
def _envelope(data: Any, meta: dict[str, Any]) -> dict[str, Any]:
from datahub import SCHEMA_VERSION
return {"schema_version": SCHEMA_VERSION, "data": data, "meta": meta}
def fetch_index_quotes(db: HubDB) -> dict[str, Any]:
cache_key = "indexes:quotes"
cached = _read_cache(db, cache_key)
if cached is not None:
return cached
eastmoney = EastmoneyAdapter()
try:
rows = eastmoney.fetch_indices()
source = "eastmoney:ulist"
except Exception:
rows = TencentAdapter().fetch_indices()
source = "tencent:qt"
if len(rows) < 3:
raise RealtimeApiError("SOURCE_UNAVAILABLE", "index quotes incomplete")
payload = _envelope(
rows,
{
"tier": "provisional",
"trade_date": yyyymmdd(now_shanghai()),
"source": source,
"stale": False,
"staleness_seconds": 0,
"published_at": isoformat(now_shanghai()),
},
)
_write_cache(db, cache_key, payload, INDEX_TTL, source)
return payload
def fetch_quotes(db: HubDB, codes: list[str]) -> dict[str, Any]:
if not codes:
raise RealtimeApiError("INVALID_ARGUMENT", "codes is required")
resolved: list[str] = []
for code in codes[:60]:
item = resolve_code(db, code) or _guess_ts_code(code)
if item:
resolved.append(item)
if not resolved:
raise RealtimeApiError("INVALID_ARGUMENT", "no resolvable codes")
cache_key = "quotes:" + ",".join(sorted(resolved))
cached = _read_cache(db, cache_key)
if cached is not None:
return cached
adapter = EastmoneyAdapter()
try:
rows = adapter.fetch_quotes(resolved)
source = "eastmoney:clist"
except Exception as exc:
raise RealtimeApiError("SOURCE_UNAVAILABLE", f"quotes unavailable: {exc}") from exc
payload = _envelope(
rows,
{
"tier": "provisional",
"trade_date": yyyymmdd(now_shanghai()),
"source": source,
"stale": False,
"staleness_seconds": 0,
"published_at": isoformat(now_shanghai()),
},
)
_write_cache(db, cache_key, payload, QUOTE_TTL, source)
return payload
def fetch_intraday(db: HubDB, code: str, date: str = "") -> dict[str, Any]:
ts_code = resolve_code(db, code) or _guess_ts_code(code)
if not ts_code:
raise RealtimeApiError("INVALID_ARGUMENT", f"ambiguous code: {code}")
cache_key = f"intraday:{ts_code}:{date or 'today'}"
cached = _read_cache(db, cache_key)
if cached is not None:
return cached
adapter = EastmoneyAdapter()
try:
payload_data = adapter.fetch_intraday(ts_code)
source = "eastmoney:trends2"
except Exception as exc:
raise RealtimeApiError("SOURCE_UNAVAILABLE", f"intraday unavailable: {exc}") from exc
payload = _envelope(
payload_data,
{
"tier": "provisional",
"trade_date": yyyymmdd(payload_data.get("trade_date") or date or now_shanghai()),
"source": source,
"stale": False,
"staleness_seconds": 0,
"published_at": isoformat(now_shanghai()),
},
)
_write_cache(db, cache_key, payload, INTRADAY_TTL, source)
return payload
def _guess_ts_code(code: str) -> str | None:
raw = str(code or "").strip().upper()
if "." in raw:
return raw
if len(raw) == 6 and raw.isdigit():
if raw.startswith(("5", "6", "9")):
return f"{raw}.SH"
return f"{raw}.SZ"
return None
def _read_cache(db: HubDB, cache_key: str) -> dict[str, Any] | None:
row = db.fetchone("SELECT * FROM rt_cache WHERE cache_key = ?", (cache_key,))
if not row:
return None
expires = str(row.get("expires_at") or "")
now = isoformat(now_shanghai())
if expires and expires < now:
return None
try:
payload = json.loads(row["payload"])
except json.JSONDecodeError:
return None
if isinstance(payload, dict) and isinstance(payload.get("meta"), dict):
stored = str(row.get("stored_at") or "")
try:
age = max(0, int(time.time() - datetime.fromisoformat(stored).timestamp()))
except Exception:
age = 0
payload["meta"]["staleness_seconds"] = age
payload["meta"]["stale"] = age > QUOTE_TTL
return payload
def _write_cache(db: HubDB, cache_key: str, payload: dict[str, Any], ttl: int, source: str) -> None:
from datetime import timedelta
now = now_shanghai()
stored = isoformat(now)
expires = isoformat(now + timedelta(seconds=ttl))
db.execute(
"""
INSERT INTO rt_cache(cache_key, payload, source, stored_at, expires_at)
VALUES (?,?,?,?,?)
ON CONFLICT(cache_key) DO UPDATE SET
payload=excluded.payload, source=excluded.source,
stored_at=excluded.stored_at, expires_at=excluded.expires_at
""",
(cache_key, json.dumps(payload, ensure_ascii=False), source, stored, expires),
)
db.execute(
"""
INSERT INTO last_known_good(cache_key, payload, source, stored_at)
VALUES (?,?,?,?)
ON CONFLICT(cache_key) DO UPDATE SET
payload=excluded.payload, source=excluded.source, stored_at=excluded.stored_at
""",
(cache_key, json.dumps(payload, ensure_ascii=False), source, stored),
)
+111
View File
@@ -0,0 +1,111 @@
"""Post-publish revision review for datasets whose upstream may rewrite T-day fields.
HEL-423 field evidence, not a whitelist of tolerated diffs:
- 2026-09-07 valuation/daily_basic: hub published 003021.SZ turnover_rate=1.3565
at 17:10; website legacy and a direct Tushare read at 21:05 both showed 1.3572.
The other seven observed objects (daily, moneyflow, auction, stocks, status,
index_daily, calendar) matched. Hub had already stopped the day after the
first successful publish, so the revision never self-healed.
- 2026-09-02: same dataset, opposite direction (hub already held the later
value). Confirms daily_basic is rewritten after the first complete dump.
Daily bars, moneyflow, auction and index_daily have no same-evening field
revision evidence. Stocks already refreshes at 20:00/23:10. Review therefore
fetches only configured revision-risk datasets (default: valuation) and
compares the website-requested field set. No numeric tolerance.
"""
from __future__ import annotations
from typing import Any
from datahub.db import DATASET_TABLES
from datahub.normalize import VALUATION_FIELDS
from datahub.numbers import finite_number, round4
# Datasets with proven same-evening upstream rewrites. Config may replace this
# list; it must not silently expand to a full EOD re-pull.
DEFAULT_REVISION_DATASETS = ("valuation",)
# Website daily_basic request (HEL-423): ts_code/trade_date plus the eight
# value fields used by the old link and field_gates.
WEBSITE_COMPARE_FIELDS: dict[str, tuple[str, ...]] = {
"valuation": VALUATION_FIELDS,
}
REVISION_STATES = ("waiting_review", "review_failed", "aligned", "cutoff")
def revision_datasets(quality: dict[str, Any] | None) -> tuple[str, ...]:
raw = (quality or {}).get("revision_review_datasets")
if isinstance(raw, (list, tuple)) and raw:
names = tuple(str(item) for item in raw if str(item))
if names:
return names
return DEFAULT_REVISION_DATASETS
def compare_fields(dataset: str) -> tuple[str, ...]:
fields = WEBSITE_COMPARE_FIELDS.get(dataset)
if fields:
return fields
gate = {}
return tuple(str(item) for item in (gate.get("fields") or []) if str(item))
def _norm_value(field: str, value: Any) -> Any:
if field in {"ts_code", "trade_date"}:
return str(value or "")
number = round4(finite_number(value))
return number
def row_signature(row: dict[str, Any], fields: tuple[str, ...]) -> tuple[Any, ...]:
return tuple(_norm_value(field, row.get(field)) for field in fields)
def diff_published_vs_upstream(
dataset: str,
published: list[dict[str, Any]],
upstream: list[dict[str, Any]],
*,
max_diffs: int = 20,
) -> dict[str, Any]:
"""Exact compare on website-requested fields. No tolerance / exemption."""
fields = compare_fields(dataset)
if not fields:
fields = tuple(sorted({key for row in published + upstream for key in row if key != "batch_id"}))
pub_map = {str(row.get("ts_code") or "").upper(): row for row in published}
up_map = {str(row.get("ts_code") or "").upper(): row for row in upstream}
missing = sorted(code for code in pub_map if code not in up_map)
extra = sorted(code for code in up_map if code not in pub_map)
diffs: list[dict[str, Any]] = []
for code in sorted(set(pub_map) & set(up_map)):
left = row_signature(pub_map[code], fields)
right = row_signature(up_map[code], fields)
if left == right:
continue
for field, old, new in zip(fields, left, right):
if old == new:
continue
diffs.append({"ts_code": code, "field": field, "published": old, "upstream": new})
if len(diffs) >= max_diffs:
break
if len(diffs) >= max_diffs:
break
changed = bool(diffs or missing or extra)
return {
"changed": changed,
"dataset": dataset,
"fields": list(fields),
"published_rows": len(published),
"upstream_rows": len(upstream),
"missing_codes": missing[:max_diffs],
"extra_codes": extra[:max_diffs],
"diffs": diffs,
}
def official_table(dataset: str) -> str:
return DATASET_TABLES[dataset][0]
+240 -3
View File
@@ -1,5 +1,6 @@
from __future__ import annotations
import json
import threading
from collections.abc import Callable
from datetime import datetime, time, timedelta
@@ -8,13 +9,14 @@ from typing import Any
from datahub.db import HubDB
from datahub.logutil import get_logger
from datahub.pipeline import Pipeline
from datahub.revision import revision_datasets
from datahub.timeutil import isoformat, now_shanghai, yyyymmdd
LOGGER = get_logger()
JobFn = Callable[[str], Any]
EOD_JOB_IDS = {"eod_a", "eod_b", "eod_retry"}
EOD_JOB_IDS = {"eod_a", "eod_b", "eod_retry", "eod_revise"}
def is_open_day(db: HubDB, day: str) -> bool:
@@ -27,6 +29,20 @@ def is_open_day(db: HubDB, day: str) -> bool:
return int(row["is_open"]) == 1
def previous_open_day(db: HubDB, day: str) -> str | None:
row = db.fetchone(
"""
SELECT cal_date FROM trade_calendar
WHERE exchange = 'SSE' AND is_open = 1 AND cal_date < ?
ORDER BY cal_date DESC LIMIT 1
""",
(day,),
)
if row is None:
return None
return str(row["cal_date"])
def _hhmm(value: str) -> time:
return datetime.strptime(value, "%H:%M").time()
@@ -48,7 +64,12 @@ class Scheduler:
"precheck": self._precheck,
"eod_a": self._eod_a,
"eod_b": self._eod_b,
"eod_c": self._eod_c,
"eod_d": self._eod_d,
"eod_e": self._eod_e,
"eod_f": self._eod_f,
"eod_retry": self._eod_retry,
"eod_revise": self._eod_revise,
"stocks_refresh": self._stocks_refresh,
"cleanup": self._cleanup,
"backup": self._backup,
@@ -87,6 +108,10 @@ class Scheduler:
("precheck", time(8, 45)),
("eod_a", time(15, 5)),
("eod_b", time(15, 10)),
("eod_c", time(16, 40)),
("eod_d", time(16, 45)),
("eod_e", time(18, 5)),
("eod_f", time(22, 40)),
("cleanup", time(0, 30)),
("backup", time(0, 40)),
]
@@ -99,7 +124,7 @@ class Scheduler:
key = (job_id, day, at.strftime("%H%M"))
if key in self._fired:
continue
if job_id in {"eod_a", "eod_b", "stocks_refresh"} and not open_day:
if job_id in {"eod_a", "eod_b", "eod_c", "eod_d", "eod_e", "eod_f", "stocks_refresh"} and not open_day:
self._fired.add(key)
continue
self._fired.add(key)
@@ -110,7 +135,7 @@ class Scheduler:
try:
self.run_job(job_id, day)
except Exception:
if job_id not in {"eod_a", "eod_b", "stocks_refresh"}:
if job_id not in {"eod_a", "eod_b", "eod_c", "eod_d", "eod_e", "eod_f", "stocks_refresh"}:
raise
# Keep the tick alive; evening retries take over.
LOGGER.exception("scheduled job %s failed for %s", job_id, day)
@@ -118,6 +143,8 @@ class Scheduler:
if job_id in {"eod_a", "eod_b"}:
self._settle_eod(day)
ran.extend(self._eod_retry_tick(now, day, open_day))
ran.extend(self._revision_review_tick(now, day, open_day))
ran.extend(self._revision_catchup_tick(now, day))
return ran
# ------------------------------------------------------------------
@@ -219,6 +246,201 @@ class Scheduler:
"detail": (row or {}).get("detail"),
}
def revision_progress(self, day: str) -> dict[str, Any] | None:
return self.db.fetchone("SELECT * FROM revision_progress WHERE trade_date = ?", (day,))
def revision_status(self, trade_date: str | None = None, clock: datetime | None = None) -> dict[str, Any]:
"""等待复核 / 复核失败 / 已追平 / 已截止."""
day = yyyymmdd(trade_date or now_shanghai(clock))
row = self.revision_progress(day)
open_day = is_open_day(self.db, day)
published = self._revision_ready(day)
if row and row["state"] in {"aligned", "review_failed", "cutoff", "waiting_review"}:
state = str(row["state"])
elif not open_day:
state = "closed_day"
elif not published:
state = "pending_publish"
else:
state = "waiting_review"
return {
"trade_date": day,
"is_open_day": open_day,
"state": state,
"datasets": list(revision_datasets(self.pipeline.settings.quality)),
"attempts": int((row or {}).get("attempts") or 0),
"last_attempt_at": (row or {}).get("last_attempt_at"),
"next_retry_at": (row or {}).get("next_retry_at") if state in {"waiting_review", "review_failed"} else None,
"finished_at": (row or {}).get("finished_at"),
"catchup_done": bool(int((row or {}).get("catchup_done") or 0)),
"detail": (row or {}).get("detail"),
"window": f"{self.pipeline.settings.revision_review_start}-{self.pipeline.settings.revision_review_cutoff}",
}
def _revision_ready(self, day: str) -> bool:
return all(
self.pipeline.active_batch(dataset, day)
for dataset in revision_datasets(self.pipeline.settings.quality)
)
def _revision_due(self, now: datetime, row: dict[str, Any] | None) -> bool:
if row is None or not row.get("last_attempt_at"):
return True
try:
last = datetime.fromisoformat(str(row["last_attempt_at"]))
except ValueError:
return True
interval = timedelta(minutes=self.pipeline.settings.revision_review_interval_minutes)
return now_shanghai(last).replace(tzinfo=None) + interval <= now.replace(tzinfo=None)
def _revision_review_tick(self, now: datetime, day: str, open_day: bool) -> list[str]:
if not open_day or not self._revision_ready(day):
return []
settings = self.pipeline.settings
current = now.time()
start = _hhmm(settings.revision_review_start)
cutoff = _hhmm(settings.revision_review_cutoff)
row = self.revision_progress(day)
if current < start:
if row is None:
self._save_revision_progress(day, state="waiting_review")
return []
if current >= cutoff:
if row is None or row["state"] not in {"aligned", "cutoff"}:
detail = "复核窗口已截止"
self._save_revision_progress(
day, state="cutoff", finished_at=isoformat(now), detail=detail,
)
with self.db.write() as connection:
connection.execute(
"INSERT INTO job_runs(job_id, state, started_at, finished_at, error, attempt, detail)"
" VALUES ('eod_revise','failed',?,?,?,?,?)",
(
isoformat(now), isoformat(now), detail,
int((row or {}).get("attempts") or 0), "revision cutoff reached",
),
)
elif row["state"] == "aligned" and not row.get("finished_at"):
self._save_revision_progress(day, finished_at=isoformat(now))
return []
if not self._revision_due(now, row):
return []
if "eod_revise" not in self.jobs:
return []
return self._run_revision_job(day, now, catchup=False)
def _revision_catchup_tick(self, now: datetime, day: str) -> list[str]:
prev = previous_open_day(self.db, day)
if prev is None or prev >= day:
return []
if not self._revision_ready(prev):
return []
row = self.revision_progress(prev)
if row and int(row.get("catchup_done") or 0):
return []
if not self._revision_due(now, row):
return []
if "eod_revise" not in self.jobs:
return []
return self._run_revision_job(prev, now, catchup=True)
def _run_revision_job(self, day: str, now: datetime, catchup: bool) -> list[str]:
attempts = int((self.revision_progress(day) or {}).get("attempts") or 0) + 1
interval = self.pipeline.settings.revision_review_interval_minutes
self._save_revision_progress(
day,
state="waiting_review",
attempts=attempts,
last_attempt_at=isoformat(now),
next_retry_at=isoformat(now + timedelta(minutes=interval)),
)
ran: list[str] = []
try:
out = self.run_job("eod_revise", day)
except Exception as exc:
LOGGER.warning("revision review failed for %s: %s", day, exc)
self._save_revision_progress(
day,
state="review_failed",
detail="复核失败,保留上一完整版本",
)
ran.append("eod_revise")
return ran
ran.append("eod_revise")
if out.get("state") == "skipped":
return ran
result = out.get("result") if isinstance(out.get("result"), dict) else {}
failed = [
name for name, item in result.items()
if isinstance(item, dict) and item.get("state") == "failed"
]
review = result.get("review") if isinstance(result.get("review"), dict) else None
watched = [
result[name]
for name in revision_datasets(self.pipeline.settings.quality)
if isinstance(result.get(name), dict)
]
diff_blob = None
if review and review.get("diffs"):
diff_blob = json.dumps(review.get("diffs"), ensure_ascii=False)
else:
for item in watched:
if item.get("diffs"):
diff_blob = json.dumps(item.get("diffs"), ensure_ascii=False)
break
revised = bool(review and review.get("reason") == "revised")
matched = any(item.get("reason") == "unchanged" or item.get("state") == "aligned" for item in watched)
if failed:
self._save_revision_progress(
day,
state="review_failed",
detail="复核失败,保留上一完整版本",
last_diff=diff_blob,
)
elif revised or matched:
fields: dict[str, Any] = {
"state": "aligned",
"finished_at": isoformat(now),
"detail": "已追平" if revised else "已追平(无变化)",
"last_diff": diff_blob,
}
if catchup:
fields["catchup_done"] = 1
self._save_revision_progress(day, **fields)
return ran
def _save_revision_progress(self, day: str, **fields: Any) -> None:
columns = [
"trade_date", "state", "attempts", "last_attempt_at",
"next_retry_at", "finished_at", "catchup_done", "last_diff", "detail", "updated_at",
]
with self.db.write() as connection:
existing = connection.execute(
"SELECT trade_date FROM revision_progress WHERE trade_date = ?",
(day,),
).fetchone()
if existing is None:
payload = {name: None for name in columns}
payload.update({
"trade_date": day,
"state": "waiting_review",
"attempts": 0,
"catchup_done": 0,
})
payload.update(fields)
payload["updated_at"] = isoformat()
placeholders = ",".join("?" for _ in columns)
connection.execute(
f"INSERT INTO revision_progress({','.join(columns)}) VALUES ({placeholders})",
tuple(payload[name] for name in columns),
)
else:
assignments = ", ".join(f"{name} = ?" for name in fields)
connection.execute(
f"UPDATE revision_progress SET {assignments}, updated_at = ? WHERE trade_date = ?",
(*fields.values(), isoformat(), day),
)
def _record_eod_attempt(self, day: str, now: datetime) -> None:
row = self.eod_progress(day)
attempts = int((row or {}).get("attempts") or 0) + 1
@@ -317,9 +539,24 @@ class Scheduler:
def _eod_b(self, trade_date: str) -> dict[str, Any]:
return self.pipeline.run_eod_batch_b(trade_date)
def _eod_c(self, trade_date: str) -> dict[str, Any]:
return self.pipeline.run_eod_batch_c(trade_date)
def _eod_d(self, trade_date: str) -> dict[str, Any]:
return self.pipeline.run_eod_batch_d(trade_date)
def _eod_e(self, trade_date: str) -> dict[str, Any]:
return self.pipeline.run_eod_batch_e(trade_date)
def _eod_f(self, trade_date: str) -> dict[str, Any]:
return self.pipeline.run_eod_batch_f(trade_date)
def _eod_retry(self, trade_date: str) -> dict[str, Any]:
return self.pipeline.run_eod_missing(trade_date)
def _eod_revise(self, trade_date: str) -> dict[str, Any]:
return self.pipeline.review_published_revisions(trade_date)
def _stocks_refresh(self, trade_date: str) -> dict[str, Any]:
return self.pipeline.refresh_stocks(trade_date)
+89 -1
View File
@@ -73,6 +73,20 @@ class V1API:
return self.moneyflow(q)
if path == "/v1/auction":
return self.auction(q)
if path == "/v1/limit-events":
return self.limit_events(q)
if path == "/v1/popularity":
return self.popularity(q)
if path == "/v1/dragon-tiger":
return self.dragon_tiger(q)
if path == "/v1/sectors":
return self.sectors(q)
if path == "/v1/quotes/latest":
return self.quotes_latest(q)
if path == "/v1/indexes/quotes":
return self.index_quotes(q)
if path == "/v1/intraday/points":
return self.intraday_points(q)
if path == "/v1/datasets/status":
return self.dataset_status(q.get("date") or "")
if path == "/v1/batches":
@@ -197,9 +211,75 @@ class V1API:
def auction(self, q: dict[str, str]) -> dict[str, Any]:
return self._published_rows(dataset="auction", table="eod_auction", q=q, source="tushare:stk_auction")
def limit_events(self, q: dict[str, str]) -> dict[str, Any]:
return self._published_rows(
dataset="limit_events",
table="eod_limit_events",
q=q,
source="tushare:limit_list_d",
extra_filters={"limit_type": q.get("limit_type") or ""},
)
def popularity(self, q: dict[str, str]) -> dict[str, Any]:
return self._published_rows(
dataset="popularity",
table="eod_popularity",
q=q,
source="tushare:ths_hot+dc_hot",
extra_filters={"source": q.get("source") or ""},
)
def dragon_tiger(self, q: dict[str, str]) -> dict[str, Any]:
return self._published_rows(
dataset="dragon_tiger",
table="eod_dragon_tiger",
q=q,
source="tushare:hm_detail",
)
def sectors(self, q: dict[str, str]) -> dict[str, Any]:
return self._published_rows(
dataset="sector_daily",
table="eod_sector_daily",
q=q,
source="tushare:ths_daily+dc_index+sw_daily",
extra_filters={"family": q.get("family") or ""},
)
def quotes_latest(self, q: dict[str, str]) -> dict[str, Any]:
from datahub.realtime_serve import RealtimeApiError, fetch_quotes
codes = [item.strip() for item in str(q.get("codes") or "").split(",") if item.strip()]
try:
return fetch_quotes(self.db, codes)
except RealtimeApiError as exc:
raise ApiError(exc.code, exc.message) from exc
def index_quotes(self, q: dict[str, str]) -> dict[str, Any]:
from datahub.realtime_serve import RealtimeApiError, fetch_index_quotes
try:
return fetch_index_quotes(self.db)
except RealtimeApiError as exc:
raise ApiError(exc.code, exc.message) from exc
def intraday_points(self, q: dict[str, str]) -> dict[str, Any]:
from datahub.realtime_serve import RealtimeApiError, fetch_intraday
code = str(q.get("code") or "").strip()
if not code:
raise ApiError("INVALID_ARGUMENT", "code is required")
try:
return fetch_intraday(self.db, code, yyyymmdd(q.get("date") or ""))
except RealtimeApiError as exc:
raise ApiError(exc.code, exc.message) from exc
def dataset_status(self, date: str) -> dict[str, Any]:
trade_date = yyyymmdd(date or now_shanghai())
datasets = ("daily", "valuation", "moneyflow", "auction", "index_daily", "stocks")
datasets = (
"daily", "valuation", "moneyflow", "auction", "index_daily", "stocks",
"limit_events", "popularity", "dragon_tiger", "sector_daily",
)
items = []
for dataset in datasets:
pub = self.db.fetchone(
@@ -244,6 +324,7 @@ class V1API:
source: str,
adjust: str = "none",
default_code: str = "",
extra_filters: dict[str, str] | None = None,
) -> dict[str, Any]:
trade_date = q.get("date") or q.get("trade_date") or ""
code = q.get("code") or default_code
@@ -264,6 +345,7 @@ class V1API:
if resolved is None:
raise ApiError("INVALID_ARGUMENT", f"ambiguous code: {code}")
ts_code = resolved
filters = {key: value for key, value in (extra_filters or {}).items() if value}
# For a range, use per-date published batch. Single-date is the common path.
if start == end:
pub = self.db.fetchone(
@@ -282,6 +364,9 @@ class V1API:
if ts_code:
sql += " AND ts_code = ?"
params.append(ts_code)
for key, value in filters.items():
sql += f" AND {key} = ?"
params.append(value)
sql += " ORDER BY ts_code LIMIT ? OFFSET ?"
params.extend([limit, offset])
rows = [dict(row) for row in self.db.fetchall(sql, tuple(params))]
@@ -317,6 +402,9 @@ class V1API:
if ts_code:
sql += " AND ts_code = ?"
params.append(ts_code)
for key, value in filters.items():
sql += f" AND {key} = ?"
params.append(value)
sql += " ORDER BY ts_code"
rows.extend(self.db.fetchall(sql, tuple(params)))
sliced = rows[offset: offset + limit]
+14
View File
@@ -79,6 +79,20 @@ class Settings:
def eod_retry_cutoff(self) -> str:
return str(self.quality.get("eod_retry_cutoff") or "23:30")
@property
def revision_review_start(self) -> str:
# Before the 21:00 website shadow observation.
return str(self.quality.get("revision_review_start") or "20:00")
@property
def revision_review_interval_minutes(self) -> int:
return int(self.quality.get("revision_review_interval_minutes") or 30)
@property
def revision_review_cutoff(self) -> str:
# Last light review ~23:00; cutoff before the 23:30 observation.
return str(self.quality.get("revision_review_cutoff") or "23:20")
def load_settings(
env: dict[str, str] | None = None,
+30 -1
View File
@@ -45,6 +45,30 @@ RAW = {
{"ts_code": "600000.SH", "trade_date": "20240902", "vol": 100, "price": 10.15, "amount": 1500000, "pre_close": 10.00, "turnover_rate": 0.1, "volume_ratio": 1.2, "float_share": 2000},
{"ts_code": "000001.SZ", "trade_date": "20240902", "vol": 80, "price": 11.05, "amount": 1200000, "pre_close": 11.10, "turnover_rate": 0.2, "volume_ratio": 0.9, "float_share": 1800},
],
"limit_list_d": [
{"trade_date": "20240902", "ts_code": "600000.SH", "industry": "银行", "name": "浦发银行", "close": 10.2, "pct_chg": 9.95, "amount": 1e8, "limit_amount": 5000, "float_mv": 800, "total_mv": 1000, "turnover_ratio": 5.0, "fd_amount": 2e7, "first_time": "09:30:01", "last_time": "14:55:00", "open_times": 0, "up_stat": "1/1", "limit_times": 1, "limit_type": "U"},
],
"ths_hot": [
{"ts_code": "600000.SH", "ts_name": "浦发银行", "hot": 90.0, "rank": 1, "pct_change": 1.2, "current_price": 10.2, "concept": "银行", "data_type": "热股", "trade_date": "20240902"},
],
"dc_hot": [
{"ts_code": "600000.SH", "ts_name": "浦发银行", "rank": 2, "pct_change": 1.2, "current_price": 10.2, "hot": 80.0, "concept": "银行", "data_type": "A股市场", "trade_date": "20240902"},
],
"hm_detail": [
{"trade_date": "20240902", "ts_code": "600000.SH", "ts_name": "浦发银行", "buy_amount": 1000, "sell_amount": 200, "net_amount": 800, "hm_name": "测试游资", "hm_orgs": "某某营业部", "tag": "超买"},
],
"top_list": [
{"trade_date": "20240902", "ts_code": "600000.SH", "name": "浦发银行", "pct_change": 9.95, "reason": "涨幅偏离值达7%"},
],
"ths_daily": [
{"ts_code": "885811.TI", "trade_date": "20240902", "open": 1000, "high": 1010, "low": 990, "close": 1005, "pre_close": 995, "pct_change": 1.0, "vol": 100, "turnover_rate": 1.2},
],
"dc_index": [
{"ts_code": "BK0475", "trade_date": "20240902", "name": "银行", "open": 100, "high": 101, "low": 99, "close": 100.5, "pre_close": 99.5, "pct_change": 1.0, "vol": 10, "amount": 1e8, "turnover_rate": 0.5},
],
"sw_daily": [
{"ts_code": "801780.SI", "trade_date": "20240902", "name": "银行", "open": 2000, "high": 2010, "low": 1990, "close": 2005, "pct_change": 0.8, "vol": 50, "amount": 2e8},
],
}
@@ -66,4 +90,9 @@ def fake_transport(api_name: str, params: dict, fields: str):
start = str(params.get("start_date") or "")
end = str(params.get("end_date") or "99999999")
return [row for row in RAW["trade_cal"] if start <= row["cal_date"] <= end]
return list(RAW.get(api_name) or [])
rows = list(RAW.get(api_name) or [])
if api_name == "limit_list_d":
limit_type = str(params.get("limit_type") or "")
if limit_type:
rows = [row for row in rows if str(row.get("limit_type") or "") == limit_type]
return rows
+181 -8
View File
@@ -21,14 +21,14 @@ class GroupTransport:
def __init__(self) -> None:
self.empty: set[str] = set()
self.keep_rows: dict[str, int] = {}
self.stocks: list[dict] = []
self.stocks: list[dict] | None = None
self.calls: list[str] = []
def __call__(self, api_name: str, params: dict, fields: str):
self.calls.append(api_name)
if api_name in self.empty:
return []
if api_name == "stock_basic" and self.stocks:
if api_name == "stock_basic" and self.stocks is not None:
return [dict(row) for row in self.stocks]
rows = fake_transport(api_name, params, fields)
keep = self.keep_rows.get(api_name)
@@ -113,19 +113,48 @@ class ReleaseGroupSwitchTests(unittest.TestCase):
first = self.pipe.run_dataset("daily", TRADE_DATE)
self.transport.empty = {"daily_basic"}
results = self.pipe.run_eod_missing(TRADE_DATE)
self.assertEqual(results["daily"]["state"], "skipped")
# incomplete A-group restages daily with the others; valuation fails → no A switch
self.assertEqual(results["daily"]["state"], "failed")
self.assertEqual(results["valuation"]["state"], "failed")
# the already-published complete batch is untouched and keeps serving
# the already-published daily batch is untouched and keeps serving
self.assertEqual(self.pipe.active_batch("daily", TRADE_DATE), first["batch_id"])
self.assertEqual(
publications_map(self.db, TRADE_DATE),
{"daily": first["batch_id"]},
)
pubs = publications_map(self.db, TRADE_DATE)
self.assertEqual(pubs["daily"], first["batch_id"])
self.assertNotIn("valuation", pubs)
self.assertNotIn("moneyflow", pubs)
self.assertNotIn("auction", pubs)
# B-group is an independent boundary and may still publish
self.assertEqual(results["index_daily"]["state"], "published")
payload = V1API(self.db, self.pipe, self.pipe.settings).handle(
"/v1/bars/daily", {"date": [TRADE_DATE], "code": ["600000.SH"]}
)
self.assertEqual(payload["meta"]["batch_id"], first["batch_id"])
def test_partial_group_retry_does_not_mix_batches(self) -> None:
"""Already-published A members must be restaged with missing ones."""
first_daily = self.pipe.run_dataset("daily", TRADE_DATE)
first_moneyflow = self.pipe.run_dataset("moneyflow", TRADE_DATE)
results = self.pipe.run_eod_missing(TRADE_DATE)
# A-group switched as one boundary; B-group (index) also published
for name in (*GROUP_A, "stocks"):
self.assertEqual(results[name]["state"], "published", name)
self.assertEqual(results["index_daily"]["state"], "published")
pubs = self.db.fetchall(
"SELECT dataset, active_batch, published_at FROM publications WHERE trade_date = ?",
(TRADE_DATE,),
)
by_ds = {str(row["dataset"]): row for row in pubs}
# old partial batches replaced — no cross-batch mix of the first wave
self.assertNotEqual(by_ds["daily"]["active_batch"], first_daily["batch_id"])
self.assertNotEqual(by_ds["moneyflow"]["active_batch"], first_moneyflow["batch_id"])
a_times = {by_ds[name]["published_at"] for name in (*GROUP_A, "stocks")}
self.assertEqual(len(a_times), 1)
# serving resolves the new complete A-group batches
api = V1API(self.db, self.pipe, self.pipe.settings)
daily = api.handle("/v1/bars/daily", {"date": [TRADE_DATE], "code": ["600000.SH"]})
self.assertEqual(daily["meta"]["batch_id"], results["daily"]["batch_id"])
self.assertEqual(daily["meta"]["batch_id"], by_ds["daily"]["active_batch"])
def test_reads_during_switch_see_old_state_until_commit(self) -> None:
snapshots: list[dict] = []
@@ -155,6 +184,13 @@ class ReleaseGroupSwitchTests(unittest.TestCase):
for table in ("eod_bars", "eod_valuation", "eod_moneyflow", "eod_auction", "eod_stocks"):
rows = self.db.fetchall(f"SELECT * FROM {table} WHERE trade_date = ?", (TRADE_DATE,))
self.assertEqual(rows, [], table)
audit = self.db.fetchone(
"SELECT * FROM audit_log WHERE action = 'release-group' ORDER BY id DESC"
)
self.assertIsNotNone(audit)
detail = str(audit["detail"])
self.assertIn("killed mid-switch", detail)
self.assertIn("failed", detail)
def test_duplicate_runs_are_idempotent(self) -> None:
self.pipe.run_eod_batch_a(TRADE_DATE)
@@ -231,5 +267,142 @@ class ReleaseGroupSwitchTests(unittest.TestCase):
self.assertIsNone(stocks_pub)
class StocksRefreshAtomicTests(unittest.TestCase):
def setUp(self) -> None:
self.transport = GroupTransport()
self.pipe, self.db = make_pipe(self.transport)
self.pipe.ingest_reference(TRADE_DATE)
self.transport.stocks = [
{"ts_code": "600000.SH", "symbol": "600000", "name": "浦发银行", "area": "上海",
"industry": "银行", "market": "主板", "list_status": "L", "list_date": "19991110"},
{"ts_code": "920071.BJ", "symbol": "920071", "name": "N金钛", "area": "辽宁",
"industry": "小金属", "market": "北交所", "list_status": "L", "list_date": "20240901"},
]
first = self.pipe.refresh_stocks(TRADE_DATE)
self.assertEqual(first["state"], "published")
self.first_batch = first["batch_id"]
def test_refresh_keeps_master_when_snapshot_publish_fails(self) -> None:
self.transport.stocks = [
{"ts_code": "600000.SH", "symbol": "600000", "name": "浦发银行", "area": "上海",
"industry": "银行", "market": "主板", "list_status": "L", "list_date": "19991110"},
{"ts_code": "920071.BJ", "symbol": "920071", "name": "金钛股份", "area": "辽宁",
"industry": "小金属", "market": "北交所", "list_status": "L", "list_date": "20240901"},
]
def explode() -> None:
raise RuntimeError("snapshot switch killed")
self.pipe.before_commit = explode
with self.assertRaises(RuntimeError):
self.pipe.refresh_stocks(TRADE_DATE)
master = self.db.fetchone("SELECT name FROM stock_master WHERE ts_code = '920071.BJ'")
self.assertEqual(master["name"], "N金钛") # rename not applied
self.assertEqual(self.pipe.active_batch("stocks", TRADE_DATE), self.first_batch)
audit = self.db.fetchone(
"SELECT * FROM audit_log WHERE action = 'stocks-refresh' ORDER BY id DESC"
)
self.assertIn("failed", str(audit["detail"]))
self.assertIn("snapshot switch killed", str(audit["detail"]))
def test_refresh_keeps_master_when_quality_gate_rejects(self) -> None:
self.transport.stocks = [] # empty → hard fail before publish
with self.assertRaises(Exception):
self.pipe.refresh_stocks(TRADE_DATE)
master = self.db.fetchone("SELECT name FROM stock_master WHERE ts_code = '920071.BJ'")
self.assertEqual(master["name"], "N金钛")
self.assertEqual(self.pipe.active_batch("stocks", TRADE_DATE), self.first_batch)
audit = self.db.fetchone(
"SELECT * FROM audit_log WHERE action = 'stocks-refresh' ORDER BY id DESC"
)
self.assertIn("failed", str(audit["detail"]))
class ForceBoundaryEntryTests(unittest.TestCase):
"""CLI force / admin backfill must rebuild the full A/B boundary."""
def setUp(self) -> None:
self.transport = GroupTransport()
self.pipe, self.db = make_pipe(self.transport)
self.pipe.ingest_reference(TRADE_DATE)
self.first = self.pipe.run_eod_batch_a(TRADE_DATE)
self.pipe.run_eod_batch_b(TRADE_DATE)
def test_force_republish_valuation_rebuilds_whole_a_group(self) -> None:
before = publications_map(self.db, TRADE_DATE)
results = self.pipe.force_republish_boundary("valuation", TRADE_DATE)
self.assertEqual({item["state"] for item in results.values()}, {"published"})
after = publications_map(self.db, TRADE_DATE)
for name in (*GROUP_A, "stocks"):
self.assertNotEqual(after[name], before[name], name)
self.assertEqual(after[name], results[name]["batch_id"], name)
# B-group left alone
self.assertEqual(after["index_daily"], before["index_daily"])
pubs = self.db.fetchall(
"SELECT dataset, published_at FROM publications WHERE trade_date = ?",
(TRADE_DATE,),
)
a_times = {row["published_at"] for row in pubs if row["dataset"] in {*GROUP_A, "stocks"}}
self.assertEqual(len(a_times), 1)
def test_force_republish_index_rebuilds_only_b_group(self) -> None:
before = publications_map(self.db, TRADE_DATE)
results = self.pipe.force_republish_boundary("index_daily", TRADE_DATE)
self.assertEqual(results["index_daily"]["state"], "published")
after = publications_map(self.db, TRADE_DATE)
self.assertNotEqual(after["index_daily"], before["index_daily"])
for name in GROUP_A:
self.assertEqual(after[name], before[name], name)
def test_admin_backfill_official_dataset_uses_boundary(self) -> None:
from datahub.admin_api import AdminAPI
from datahub.auth import AuthService
from datahub.crypto import SecretVault
from datahub.scheduler import Scheduler
from datahub.serving import ApiError
vault = SecretVault(self.pipe.settings.encryption_key)
auth = AuthService(self.db, vault, self.pipe.settings.api_token, "StartPass1")
admin = AdminAPI(self.db, self.pipe, Scheduler(self.db, self.pipe), auth)
before = publications_map(self.db, TRADE_DATE)
result = admin.backfill("moneyflow", TRADE_DATE, "StartPass1", f"moneyflow:{TRADE_DATE}", "tester")
self.assertEqual(result["moneyflow"]["state"], "published")
after = publications_map(self.db, TRADE_DATE)
for name in (*GROUP_A, "stocks"):
self.assertNotEqual(after[name], before[name], name)
# bad password / wrong confirm still rejected
with self.assertRaises(ApiError):
admin.backfill("daily", TRADE_DATE, "wrong", f"daily:{TRADE_DATE}", "tester")
def test_admin_backfill_switch_crash_is_failed_precondition(self) -> None:
from datahub.admin_api import AdminAPI
from datahub.auth import AuthService
from datahub.crypto import SecretVault
from datahub.scheduler import Scheduler
from datahub.serving import ApiError
vault = SecretVault(self.pipe.settings.encryption_key)
auth = AuthService(self.db, vault, self.pipe.settings.api_token, "StartPass1")
admin = AdminAPI(self.db, self.pipe, Scheduler(self.db, self.pipe), auth)
before = publications_map(self.db, TRADE_DATE)
def explode() -> None:
raise RuntimeError("killed mid-switch")
self.pipe.before_commit = explode
with self.assertRaises(ApiError) as ctx:
admin.backfill("valuation", TRADE_DATE, "StartPass1", f"valuation:{TRADE_DATE}", "tester")
self.assertEqual(ctx.exception.code, "FAILED_PRECONDITION")
self.assertIn("killed mid-switch", ctx.exception.message)
# previous complete A/B versions keep serving
self.assertEqual(publications_map(self.db, TRADE_DATE), before)
audit = self.db.fetchone(
"SELECT * FROM audit_log WHERE action = 'release-group' ORDER BY id DESC"
)
self.assertIsNotNone(audit)
self.assertIn("failed", str(audit["detail"]))
self.assertIn("killed mid-switch", str(audit["detail"]))
if __name__ == "__main__":
unittest.main()
+22 -3
View File
@@ -111,15 +111,24 @@ class EodRetryTests(unittest.TestCase):
self.assertEqual(progress["state"], "done")
self.assertEqual(progress["attempts"], 4) # eod_a + eod_b + 2 retries
# success stops all further same-day requests
# success stops further eod_retry; revision window has not started yet
batches_before = len(self._batches(db, day))
eod_calls_before = len(self._eod_calls(transport))
sched.tick(clock_at(day, 17, 0))
sched.tick(clock_at(day, 23, 0))
self.assertEqual(len(self._job_runs(db, "eod_retry")), 2)
self.assertEqual(len(self._job_runs(db, "eod_revise")), 0)
self.assertEqual(len(self._batches(db, day)), batches_before)
self.assertEqual(len(self._eod_calls(transport)), eod_calls_before)
# 23:00 is inside the valuation review window: light daily_basic only, no new batch
sched.tick(clock_at(day, 23, 0))
self.assertEqual(len(self._job_runs(db, "eod_retry")), 2)
self.assertEqual(len(self._job_runs(db, "eod_revise")), 1)
self.assertEqual(len(self._batches(db, day)), batches_before)
extra = [name for name in self._eod_calls(transport)[eod_calls_before:]]
self.assertTrue(extra)
self.assertTrue(all(name == "daily_basic" for name in extra))
def test_never_ready_marks_cutoff_failed_and_stops(self) -> None:
day = "20240902"
db, transport, pipe, sched = self._make(set())
@@ -174,6 +183,7 @@ class EodRetryTests(unittest.TestCase):
self.assertIn("eod_a", ran)
self.assertIn("eod_b", ran)
self.assertNotIn("eod_retry", ran)
self.assertIn("eod_revise", ran)
self.assertEqual(self._published(db, day), OFFICIAL)
after = db.fetchall("SELECT dataset, active_batch FROM publications WHERE trade_date = ?", (day,))
self.assertEqual(
@@ -181,7 +191,9 @@ class EodRetryTests(unittest.TestCase):
active_map,
)
self.assertEqual(set(official_batches()), batches_before) # no duplicate batches
self.assertEqual(self._eod_calls(transport), calls_before) # no duplicate upstream EOD calls
extra = self._eod_calls(transport)[len(calls_before):]
self.assertTrue(extra)
self.assertTrue(all(name == "daily_basic" for name in extra))
self.assertEqual(sched2.eod_status(day, clock=clock_at(day, 21, 0))["state"], "done")
def test_restart_with_partial_publish_only_fetches_missing(self) -> None:
@@ -206,6 +218,7 @@ class EodRetryTests(unittest.TestCase):
for hh, mm in ((15, 5), (15, 10), (15, 40), (16, 10), (20, 0), (23, 40)):
ran = sched.tick(clock_at(day, hh, mm))
self.assertNotIn("eod_retry", ran)
self.assertNotIn("eod_revise", ran)
eod_runs = db.fetchall("SELECT * FROM job_runs WHERE job_id LIKE 'eod%'")
self.assertEqual(eod_runs, [])
self.assertIsNone(db.fetchone("SELECT * FROM eod_progress WHERE trade_date = ?", (day,)))
@@ -226,12 +239,18 @@ class EodRetryTests(unittest.TestCase):
self.assertEqual(len(self._batches(db, day)), batches_before)
self.assertEqual(len(transport.calls), calls_before)
revised = sched.run_job("eod_revise", day)
self.assertEqual(revised["state"], "ok")
self.assertEqual(len(self._batches(db, day)), batches_before)
sched._eod_lock.acquire() # simulate an in-flight EOD job
try:
busy = sched.run_job("eod_retry", day)
self.assertEqual(busy["state"], "skipped")
busy_a = sched.run_job("eod_a", day)
self.assertEqual(busy_a["state"], "skipped")
busy_r = sched.run_job("eod_revise", day)
self.assertEqual(busy_r["state"], "skipped")
finally:
sched._eod_lock.release()
self.assertEqual(len(self._batches(db, day)), batches_before)
@@ -0,0 +1,65 @@
from __future__ import annotations
import tempfile
import unittest
from pathlib import Path
from datahub.adapters.tushare import TushareAdapter
from datahub.crypto import SecretVault
from datahub.hub import Hub
from datahub.settings import Settings
from tests.fixtures import TRADE_DATE, fake_transport
class ExtendedEodTests(unittest.TestCase):
def setUp(self) -> None:
self.tmp = tempfile.TemporaryDirectory()
key = SecretVault.generate_key()
settings = Settings(
host="127.0.0.1",
port=0,
encryption_key=key,
api_token="k" * 32,
admin_password="StartPass1",
tushare_token="tushare-secret",
db_path=Path(self.tmp.name) / "hub.db",
backup_dir=Path(self.tmp.name) / "backups",
scheduler_enabled=False,
quality={"daily_row_ratio": 0.5, "null_rate_max": 0.5, "list_limit_default": 5000, "list_limit_max": 5000},
)
adapter = TushareAdapter("tushare-secret", transport=fake_transport)
self.hub = Hub(settings, adapter=adapter)
self.hub.pipeline.ingest_reference(TRADE_DATE)
for dataset in ("daily", "valuation", "moneyflow", "auction", "index_daily"):
self.hub.pipeline.run_dataset(dataset, TRADE_DATE)
def tearDown(self) -> None:
self.hub.stop()
self.tmp.cleanup()
def test_extended_soft_datasets_publish_and_serve(self) -> None:
results = self.hub.pipeline.run_extended_soft(
("limit_events", "popularity", "dragon_tiger", "sector_daily"),
TRADE_DATE,
)
for name in ("limit_events", "popularity", "dragon_tiger", "sector_daily"):
self.assertEqual(results[name]["state"], "published", results[name])
api = self.hub.api
limits = api.handle("/v1/limit-events", {"date": [TRADE_DATE]})
self.assertGreaterEqual(len(limits["data"]), 1)
self.assertEqual(limits["meta"]["tier"], "official")
pop = api.handle("/v1/popularity", {"date": [TRADE_DATE], "source": ["ths"]})
self.assertEqual(pop["data"][0]["source"], "ths")
lhb = api.handle("/v1/dragon-tiger", {"date": [TRADE_DATE]})
self.assertEqual(lhb["data"][0]["hm_name"], "测试游资")
# hub stores 万元→元
self.assertEqual(lhb["data"][0]["buy_amount"], 10_000_000.0)
sectors = api.handle("/v1/sectors", {"date": [TRADE_DATE], "family": ["ths"]})
self.assertEqual(sectors["data"][0]["family"], "ths")
status = api.handle("/v1/datasets/status", {"date": [TRADE_DATE]})
names = {item["dataset"] for item in status["data"]}
self.assertTrue({"limit_events", "popularity", "dragon_tiger", "sector_daily"} <= names)
if __name__ == "__main__":
unittest.main()
+7 -1
View File
@@ -19,11 +19,17 @@ class LayoutTests(unittest.TestCase):
def test_reserved_adapters_present(self) -> None:
from datahub.adapters import RESERVED
for name in ("eastmoney", "tencent", "ths", "xgb", "akshare", "ifind"):
for name in ("ths", "xgb", "akshare", "ifind"):
self.assertIn(name, RESERVED)
probe = RESERVED[name].probe()
self.assertEqual(probe["state"], "reserved")
self.assertFalse(probe["configured"])
for name in ("eastmoney", "tencent"):
self.assertIn(name, RESERVED)
probe = RESERVED[name].probe()
# Live free adapters: probe may be ok/error/empty depending on network.
self.assertIn(probe["state"], {"ok", "empty", "error"})
self.assertTrue(probe["configured"])
if __name__ == "__main__":
+20 -11
View File
@@ -228,25 +228,34 @@ class GateRetryInterplayTests(unittest.TestCase):
class ForceRepublishTests(unittest.TestCase):
def test_run_dataset_over_published_keeps_prev_for_rollback(self) -> None:
def test_force_boundary_republish_keeps_prev_for_rollback(self) -> None:
transport = ValuationTransport()
pipe, db = make_pipe(transport)
pipe.ingest_reference(TRADE_DATE)
first = pipe.run_dataset("valuation", TRADE_DATE)
first = pipe.run_eod_batch_a(TRADE_DATE)
first_val = first["valuation"]["batch_id"]
first_daily = first["daily"]["batch_id"]
transport.mode = "vr_all_null"
with self.assertRaises(QualityError):
pipe.run_dataset("valuation", TRADE_DATE) # gate holds: bad re-publish refused
blocked = pipe.force_republish_boundary("valuation", TRADE_DATE)
self.assertEqual(blocked["valuation"]["state"], "failed")
self.assertEqual(pipe.active_batch("valuation", TRADE_DATE), first_val)
self.assertEqual(pipe.active_batch("daily", TRADE_DATE), first_daily)
transport.mode = "ok"
second = pipe.run_dataset("valuation", TRADE_DATE) # CLI --force path
self.assertNotEqual(first["batch_id"], second["batch_id"])
pub = db.fetchone(
"SELECT * FROM publications WHERE dataset='valuation' AND trade_date=?",
second = pipe.force_republish_boundary("valuation", TRADE_DATE)
self.assertEqual(second["valuation"]["state"], "published")
self.assertNotEqual(second["valuation"]["batch_id"], first_val)
self.assertNotEqual(second["daily"]["batch_id"], first_daily)
pubs = db.fetchall(
"SELECT dataset, active_batch, prev_batch, published_at FROM publications WHERE trade_date=?",
(TRADE_DATE,),
)
self.assertEqual(pub["active_batch"], second["batch_id"])
self.assertEqual(pub["prev_batch"], first["batch_id"])
by_ds = {str(row["dataset"]): row for row in pubs}
a_times = {by_ds[name]["published_at"] for name in ("daily", "valuation", "moneyflow", "auction", "stocks")}
self.assertEqual(len(a_times), 1)
self.assertEqual(by_ds["valuation"]["active_batch"], second["valuation"]["batch_id"])
self.assertEqual(by_ds["valuation"]["prev_batch"], first_val)
rolled = pipe.rollback("valuation", TRADE_DATE, actor="cli")
self.assertEqual(rolled["active_batch"], first["batch_id"])
self.assertEqual(rolled["active_batch"], first_val)
if __name__ == "__main__":
@@ -0,0 +1,345 @@
from __future__ import annotations
import copy
import unittest
from pathlib import Path
import tempfile
from datahub.adapters.base import AdapterError
from datahub.adapters.tushare import TushareAdapter
from datahub.crypto import SecretVault
from datahub.db import HubDB
from datahub.pipeline import Pipeline
from datahub.scheduler import Scheduler
from datahub.serving import V1API
from datahub.settings import Settings
from datahub.timeutil import SHANGHAI
from tests.fixtures import RAW, TRADE_DATE, fake_transport
from tests.test_eod_retry import clock_at
from tests.test_quality_gates import FIELD_GATES
SAMPLE_DAY = "20260907"
NEXT_DAY = "20260908"
SAMPLE_CODE = "003021.SZ"
def _dated(row: dict, day: str) -> dict:
item = dict(row)
if "trade_date" in item:
item["trade_date"] = day
return item
class RevisingTransport:
"""Fixture transport that can rewrite daily_basic after the first publish."""
DATE_APIS = {"daily", "daily_basic", "adj_factor", "moneyflow", "stk_auction", "index_daily"}
def __init__(self, extra_calendar: list[dict] | None = None) -> None:
self.calls: list[str] = []
self.fail_daily_basic = False
self.empty_daily_basic = False
self.null_volume_ratio = False
self.turnover_by_code: dict[str, float] = {}
self.extra_calendar = extra_calendar or []
def __call__(self, api_name: str, params: dict, fields: str):
self.calls.append(api_name)
day = str(params.get("trade_date") or "")
if api_name == "trade_cal":
rows = fake_transport(api_name, params, fields)
extra = [
row for row in self.extra_calendar
if str(params.get("start_date") or "") <= row["cal_date"] <= str(params.get("end_date") or "99999999")
]
return rows + extra
if self.fail_daily_basic and api_name == "daily_basic":
raise AdapterError("tushare daily_basic unavailable")
if self.empty_daily_basic and api_name == "daily_basic":
return []
if api_name == "index_daily":
code = params.get("ts_code")
rows = [row for row in RAW["index_daily"] if row["ts_code"] == code]
if day:
rows = [_dated(row, day) for row in rows]
return rows
rows = fake_transport(api_name, params, fields)
if api_name == "stock_basic":
rows = list(rows)
rows.append({
"ts_code": SAMPLE_CODE, "symbol": "003021", "name": "兆威机电",
"area": "广东", "industry": "元器件", "market": "主板",
"list_status": "L", "list_date": "20201202",
})
return rows
if api_name in self.DATE_APIS:
template = RAW.get(api_name) or []
if not day:
return [_dated(row, TRADE_DATE) for row in template]
out = [_dated(row, day) for row in template]
extra = copy.deepcopy(template[0])
extra["ts_code"] = SAMPLE_CODE
extra["trade_date"] = day
if api_name == "daily_basic":
extra["turnover_rate"] = self.turnover_by_code.get(SAMPLE_CODE, extra.get("turnover_rate"))
if self.null_volume_ratio:
extra["volume_ratio"] = None
for row in out:
row["volume_ratio"] = None
out.append(extra)
if api_name == "daily_basic":
for row in out:
code = str(row.get("ts_code") or "")
if code in self.turnover_by_code:
row["turnover_rate"] = self.turnover_by_code[code]
return out
return rows
def make_revision_env(quality_extra: dict | None = None, extra_calendar: list[dict] | None = None):
tmp = tempfile.TemporaryDirectory()
db = HubDB(Path(tmp.name) / "hub.db")
transport = RevisingTransport(extra_calendar=extra_calendar)
adapter = TushareAdapter("x", transport=transport)
quality = {
"daily_row_ratio": 0.5,
"null_rate_max": 0.5,
"max_publish_attempts": 2,
"publication_generations": 3,
"field_gates": FIELD_GATES,
"revision_review_start": "20:00",
"revision_review_interval_minutes": 30,
"revision_review_cutoff": "23:20",
"revision_review_datasets": ["valuation"],
}
if quality_extra:
quality.update(quality_extra)
settings = Settings(
encryption_key=SecretVault.generate_key(),
api_token="t" * 32,
db_path=db.path,
backup_dir=Path(tmp.name) / "backups",
quality=quality,
scheduler_enabled=False,
)
pipe = Pipeline(db, adapter, settings)
sched = Scheduler(db, pipe)
return tmp, db, transport, pipe, sched
SAMPLE_CALENDAR = [
{"exchange": "SSE", "cal_date": SAMPLE_DAY, "is_open": 1, "pretrade_date": "20260906"},
{"exchange": "SSE", "cal_date": NEXT_DAY, "is_open": 1, "pretrade_date": SAMPLE_DAY},
]
class RevisionReviewTests(unittest.TestCase):
def _publish(self, pipe: Pipeline, day: str) -> None:
pipe.ingest_reference(day)
pipe.run_eod_batch_a(day)
pipe.run_eod_batch_b(day)
def _turnover(self, db: HubDB, day: str, code: str = SAMPLE_CODE) -> float | None:
pub = db.fetchone(
"SELECT active_batch FROM publications WHERE dataset='valuation' AND trade_date=?",
(day,),
)
row = db.fetchone(
"SELECT turnover_rate FROM eod_valuation WHERE batch_id=? AND ts_code=?",
(pub["active_batch"], code),
)
return None if row is None else row["turnover_rate"]
def _batch_ids(self, db: HubDB, day: str) -> set[str]:
# HEL-478/HEL-463 integration: extended soft datasets (limit_events,
# dragon_tiger, sector_daily, popularity) publish on their own schedule
# inside the same tick and are outside the valuation review boundary.
# Scope assertions to the A-group + stocks boundary the review republishes.
boundary = ("daily", "valuation", "moneyflow", "auction", "stocks")
placeholders = ",".join("?" for _ in boundary)
return {
str(row["batch_id"])
for row in db.fetchall(
f"SELECT batch_id FROM batches WHERE trade_date=? AND dataset IN ({placeholders})",
(day, *boundary),
)
}
def test_no_change_does_not_create_a_new_batch(self) -> None:
tmp, db, transport, pipe, sched = make_revision_env()
self.addCleanup(tmp.cleanup)
self._publish(pipe, TRADE_DATE)
before = self._batch_ids(db, TRADE_DATE)
sched.tick(clock_at(TRADE_DATE, 20, 0))
self.assertEqual(self._batch_ids(db, TRADE_DATE), before)
progress = db.fetchone("SELECT * FROM revision_progress WHERE trade_date=?", (TRADE_DATE,))
self.assertEqual(progress["state"], "aligned")
self.assertIn("无变化", progress["detail"])
status = sched.revision_status(TRADE_DATE, clock=clock_at(TRADE_DATE, 20, 0))
self.assertEqual(status["state"], "aligned")
def test_hel423_20260907_single_field_revision_is_caught_up(self) -> None:
tmp, db, transport, pipe, sched = make_revision_env(extra_calendar=SAMPLE_CALENDAR)
self.addCleanup(tmp.cleanup)
transport.turnover_by_code[SAMPLE_CODE] = 1.3565
self._publish(pipe, SAMPLE_DAY)
self.assertEqual(self._turnover(db, SAMPLE_DAY), 1.3565)
first = db.fetchone(
"SELECT active_batch FROM publications WHERE dataset='valuation' AND trade_date=?",
(SAMPLE_DAY,),
)["active_batch"]
transport.turnover_by_code[SAMPLE_CODE] = 1.3572
seen: list[float | None] = []
def watch() -> None:
seen.append(self._turnover(db, SAMPLE_DAY))
pipe.before_commit = watch
ran = sched.tick(clock_at(SAMPLE_DAY, 20, 0))
self.assertIn("eod_revise", ran)
self.assertEqual(seen, [1.3565]) # readers still see the previous complete version mid-switch
self.assertEqual(self._turnover(db, SAMPLE_DAY), 1.3572)
second = db.fetchone(
"SELECT active_batch FROM publications WHERE dataset='valuation' AND trade_date=?",
(SAMPLE_DAY,),
)["active_batch"]
self.assertNotEqual(second, first)
api = V1API(db, pipe, pipe.settings)
payload = api.valuation({"date": SAMPLE_DAY, "code": SAMPLE_CODE})
row = next(item for item in payload["data"] if item["ts_code"] == SAMPLE_CODE)
self.assertEqual(row["turnover_rate"], 1.3572)
progress = db.fetchone("SELECT * FROM revision_progress WHERE trade_date=?", (SAMPLE_DAY,))
self.assertEqual(progress["state"], "aligned")
self.assertEqual(progress["detail"], "已追平")
audit = db.fetchone(
"SELECT * FROM audit_log WHERE action='revision-review' ORDER BY id DESC"
)
self.assertIn("1.3572", str(audit["detail"]))
self.assertIn(SAMPLE_CODE, str(audit["detail"]))
def test_empty_or_failed_upstream_keeps_previous_version(self) -> None:
tmp, db, transport, pipe, sched = make_revision_env()
self.addCleanup(tmp.cleanup)
self._publish(pipe, TRADE_DATE)
active = db.fetchone(
"SELECT active_batch FROM publications WHERE dataset='valuation' AND trade_date=?",
(TRADE_DATE,),
)["active_batch"]
batches = self._batch_ids(db, TRADE_DATE)
transport.empty_daily_basic = True
sched.tick(clock_at(TRADE_DATE, 20, 0))
self.assertEqual(
db.fetchone(
"SELECT active_batch FROM publications WHERE dataset='valuation' AND trade_date=?",
(TRADE_DATE,),
)["active_batch"],
active,
)
self.assertEqual(
db.fetchone("SELECT state FROM revision_progress WHERE trade_date=?", (TRADE_DATE,))["state"],
"review_failed",
)
transport.empty_daily_basic = False
transport.fail_daily_basic = True
sched.tick(clock_at(TRADE_DATE, 20, 30))
self.assertEqual(
db.fetchone(
"SELECT active_batch FROM publications WHERE dataset='valuation' AND trade_date=?",
(TRADE_DATE,),
)["active_batch"],
active,
)
self.assertEqual(self._batch_ids(db, TRADE_DATE), batches)
def test_quality_gate_rejects_catchup_and_keeps_previous(self) -> None:
tmp, db, transport, pipe, sched = make_revision_env()
self.addCleanup(tmp.cleanup)
self._publish(pipe, TRADE_DATE)
active = db.fetchone(
"SELECT active_batch FROM publications WHERE dataset='valuation' AND trade_date=?",
(TRADE_DATE,),
)["active_batch"]
transport.turnover_by_code[SAMPLE_CODE] = 9.9999
transport.null_volume_ratio = True
sched.tick(clock_at(TRADE_DATE, 20, 0))
self.assertEqual(
db.fetchone(
"SELECT active_batch FROM publications WHERE dataset='valuation' AND trade_date=?",
(TRADE_DATE,),
)["active_batch"],
active,
)
self.assertEqual(
db.fetchone("SELECT state FROM revision_progress WHERE trade_date=?", (TRADE_DATE,))["state"],
"review_failed",
)
def test_repeat_ticks_after_align_do_not_republish(self) -> None:
tmp, db, transport, pipe, sched = make_revision_env()
self.addCleanup(tmp.cleanup)
transport.turnover_by_code[SAMPLE_CODE] = 1.3565
self._publish(pipe, TRADE_DATE)
transport.turnover_by_code[SAMPLE_CODE] = 1.3572
sched.tick(clock_at(TRADE_DATE, 20, 0))
after_fix = self._batch_ids(db, TRADE_DATE)
sched.tick(clock_at(TRADE_DATE, 20, 10)) # inside interval
self.assertEqual(len(db.fetchall("SELECT * FROM job_runs WHERE job_id='eod_revise'")), 1)
sched.tick(clock_at(TRADE_DATE, 20, 30)) # next light compare, no change
self.assertEqual(self._batch_ids(db, TRADE_DATE), after_fix)
self.assertEqual(self._turnover(db, TRADE_DATE), 1.3572)
def test_restart_catches_up_inside_window(self) -> None:
tmp, db, transport, pipe, sched = make_revision_env()
self.addCleanup(tmp.cleanup)
transport.turnover_by_code[SAMPLE_CODE] = 1.3565
self._publish(pipe, TRADE_DATE)
transport.turnover_by_code[SAMPLE_CODE] = 1.3572
sched2 = Scheduler(db, pipe)
ran = sched2.tick(clock_at(TRADE_DATE, 21, 0))
self.assertIn("eod_revise", ran)
self.assertEqual(self._turnover(db, TRADE_DATE), 1.3572)
def test_cutoff_stops_evening_reviews_and_morning_catchup_runs(self) -> None:
tmp, db, transport, pipe, sched = make_revision_env(extra_calendar=SAMPLE_CALENDAR)
self.addCleanup(tmp.cleanup)
transport.turnover_by_code[SAMPLE_CODE] = 1.3565
self._publish(pipe, SAMPLE_DAY)
sched.tick(clock_at(SAMPLE_DAY, 23, 25)) # past 23:20 cutoff, no review yet
cutoff = db.fetchone("SELECT * FROM revision_progress WHERE trade_date=?", (SAMPLE_DAY,))
self.assertEqual(cutoff["state"], "cutoff")
self.assertEqual(self._turnover(db, SAMPLE_DAY), 1.3565)
transport.turnover_by_code[SAMPLE_CODE] = 1.3572
sched.tick(clock_at(SAMPLE_DAY, 23, 50)) # still same calendar day, no catch-up
self.assertEqual(self._turnover(db, SAMPLE_DAY), 1.3565)
ran = sched.tick(clock_at(NEXT_DAY, 8, 45))
self.assertIn("eod_revise", ran)
self.assertEqual(self._turnover(db, SAMPLE_DAY), 1.3572)
progress = db.fetchone("SELECT * FROM revision_progress WHERE trade_date=?", (SAMPLE_DAY,))
self.assertEqual(progress["state"], "aligned")
self.assertEqual(int(progress["catchup_done"]), 1)
batches = self._batch_ids(db, SAMPLE_DAY)
sched.tick(clock_at(NEXT_DAY, 8, 50))
self.assertEqual(self._batch_ids(db, SAMPLE_DAY), batches)
def test_only_valuation_is_light_fetched(self) -> None:
tmp, db, transport, pipe, sched = make_revision_env()
self.addCleanup(tmp.cleanup)
self._publish(pipe, TRADE_DATE)
before = [name for name in transport.calls]
sched.tick(clock_at(TRADE_DATE, 20, 0))
extra = transport.calls[len(before):]
self.assertIn("daily_basic", extra)
self.assertNotIn("daily", extra)
self.assertNotIn("moneyflow", extra)
self.assertNotIn("stk_auction", extra)
self.assertNotIn("index_daily", extra)
if __name__ == "__main__":
unittest.main()