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Author SHA1 Message Date
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
16841e9ae3 fix(HEL-459): 影子比较按请求字段投影,盘后整批原子发布
比较侧只对网站本次请求字段计业务差异,忽略数据中枢额外列;
盘后 A/B/重发改为先整批暂存与交叉校验,再单事务切换公开版本。

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: multica-agent <github@multica.ai>
2026-09-05 08:39:31 +08:00
11 changed files with 1051 additions and 118 deletions
+4 -2
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@@ -122,10 +122,12 @@ class DatahubBridge:
legacy_rows = legacy_query(api_name, params, fields) legacy_rows = legacy_query(api_name, params, fields)
except Exception as exc: except Exception as exc:
if flags.read and hub_rows is not None and hub_error is None: if flags.read and hub_rows is not None and hub_error is None:
self._emit_shadow(compare_rows(dataset, [], hub_canonical, hub_meta, self._error_text(exc))) self._emit_shadow(
compare_rows(dataset, [], hub_canonical, hub_meta, self._error_text(exc), fields)
)
return project_fields(hub_rows, fields) return project_fields(hub_rows, fields)
raise raise
self._emit_shadow(compare_rows(dataset, legacy_rows, hub_canonical, hub_meta, hub_error)) self._emit_shadow(compare_rows(dataset, legacy_rows, hub_canonical, hub_meta, hub_error, fields))
if flags.read and hub_rows is not None and hub_error is None: if flags.read and hub_rows is not None and hub_error is None:
return project_fields(hub_rows, fields) return project_fields(hub_rows, fields)
return legacy_rows return legacy_rows
+29 -2
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@@ -5,6 +5,7 @@ from typing import Any
from backend.data.datahub.native import SCALE_FIELDS, row_key, to_canonical_row, yyyymmdd from backend.data.datahub.native import SCALE_FIELDS, row_key, to_canonical_row, yyyymmdd
NUMERIC_TOLERANCE = 1e-4 NUMERIC_TOLERANCE = 1e-4
CANONICAL_ALIASES = {"volume": "vol"}
def compare_rows( def compare_rows(
@@ -13,8 +14,10 @@ def compare_rows(
hub_rows: list[dict[str, Any]] | None, hub_rows: list[dict[str, Any]] | None,
hub_meta: dict[str, Any] | None = None, hub_meta: dict[str, Any] | None = None,
hub_error: str | None = None, hub_error: str | None = None,
fields: str = "",
) -> dict[str, Any]: ) -> dict[str, Any]:
hub = hub_rows or [] hub = hub_rows or []
requested = _requested_fields(fields)
legacy_map = {row_key(dataset, row): row for row in legacy_rows} legacy_map = {row_key(dataset, row): row for row in legacy_rows}
hub_map = {row_key(dataset, _align_hub_row(row)): row for row in hub} hub_map = {row_key(dataset, _align_hub_row(row)): row for row in hub}
missing_hub = sorted(key for key in legacy_map if key not in hub_map) missing_hub = sorted(key for key in legacy_map if key not in hub_map)
@@ -26,7 +29,7 @@ def compare_rows(
hub_row = hub_map.get(key) hub_row = hub_map.get(key)
if hub_row is None: if hub_row is None:
continue continue
field_report = _compare_fields(dataset, legacy, hub_row) field_report = _compare_fields(dataset, legacy, hub_row, requested)
if field_report["unit_conversion"]: if field_report["unit_conversion"]:
unit_conversion.append({"key": list(key), "fields": field_report["unit_conversion"]}) unit_conversion.append({"key": list(key), "fields": field_report["unit_conversion"]})
if field_report["value_diff"]: if field_report["value_diff"]:
@@ -53,6 +56,7 @@ def compare_rows(
"published_at": (hub_meta or {}).get("published_at"), "published_at": (hub_meta or {}).get("published_at"),
"trade_date": yyyymmdd((hub_meta or {}).get("trade_date")), "trade_date": yyyymmdd((hub_meta or {}).get("trade_date")),
"hub_error": hub_error, "hub_error": hub_error,
"fields_compared": sorted(requested) if requested is not None else None,
"equal": ( "equal": (
not hub_error not hub_error
and not missing_hub and not missing_hub
@@ -71,13 +75,36 @@ def _align_hub_row(row: dict[str, Any]) -> dict[str, Any]:
return aligned return aligned
def _compare_fields(dataset: str, legacy: dict[str, Any], hub: dict[str, Any]) -> dict[str, list[dict[str, Any]]]: def _requested_fields(fields: str) -> list[str] | None:
"""Fields the website actually asked for; None means "no projection"."""
keys = [item.strip() for item in str(fields or "").split(",") if item.strip()]
if not keys:
return None
seen: list[str] = []
for key in keys:
canonical = CANONICAL_ALIASES.get(key, key)
if canonical not in seen:
seen.append(canonical)
return seen
def _compare_fields(
dataset: str,
legacy: dict[str, Any],
hub: dict[str, Any],
requested: list[str] | None = None,
) -> dict[str, list[dict[str, Any]]]:
canonical_legacy = to_canonical_row(dataset, legacy) canonical_legacy = to_canonical_row(dataset, legacy)
hub_canonical = _hub_canonical(dataset, hub) hub_canonical = _hub_canonical(dataset, hub)
native_hub = _align_hub_row(hub) native_hub = _align_hub_row(hub)
value_diff: list[dict[str, Any]] = [] value_diff: list[dict[str, Any]] = []
unit_conversion: list[dict[str, Any]] = [] unit_conversion: list[dict[str, Any]] = []
keys = (set(canonical_legacy) | set(hub_canonical)) - {"batch_id", "updated_at", "volume"} keys = (set(canonical_legacy) | set(hub_canonical)) - {"batch_id", "updated_at", "volume"}
if requested is not None:
# Compare only what the website asked for. Extra hub columns are
# transport detail, not business differences; a requested field still
# alarms when it is missing or holds a different value.
keys = set(requested) - {"batch_id", "updated_at", "volume"}
scales = SCALE_FIELDS.get(dataset) or {} scales = SCALE_FIELDS.get(dataset) or {}
for field in sorted(keys): for field in sorted(keys):
left = canonical_legacy.get(field) left = canonical_legacy.get(field)
+81
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@@ -201,6 +201,87 @@ class DatahubBridgeTests(unittest.TestCase):
skew = compare_rows("daily", [LEGACY_DAILY], [HUB_DAILY], {"stale": False, "staleness_seconds": 12}) skew = compare_rows("daily", [LEGACY_DAILY], [HUB_DAILY], {"stale": False, "staleness_seconds": 12})
self.assertTrue(skew["time_skew"]) self.assertTrue(skew["time_skew"])
def test_shadow_extra_hub_columns_are_not_false_diffs_when_projected(self) -> None:
hub_full = {**HUB_DAILY, "adj_factor": 1.1}
legacy_close_only = {k: LEGACY_DAILY[k] for k in ("ts_code", "trade_date", "close")}
report = compare_rows(
"daily", [legacy_close_only], [hub_full],
{"stale": False, "staleness_seconds": 0},
fields="ts_code,trade_date,close",
)
self.assertTrue(report["equal"])
self.assertEqual(report["value_diff_count"], 0)
self.assertEqual(report["fields_compared"], ["close", "trade_date", "ts_code"])
# without projection the same pair shows the historic false diff
unprojected = compare_rows("daily", [legacy_close_only], [hub_full])
self.assertFalse(unprojected["equal"])
legacy_stocks = {"ts_code": "600000.SH", "name": "浦发银行"}
hub_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",
}
stocks = compare_rows("stocks", [legacy_stocks], [hub_stocks], {}, fields="ts_code,name")
self.assertTrue(stocks["equal"])
legacy_cal = {"cal_date": "20240902", "is_open": 1}
hub_cal = {
"cal_date": "20240902", "is_open": True,
"pretrade_date": "20240830", "prev_open": "20240830",
}
calendar = compare_rows(
"calendar", [legacy_cal], [hub_cal], {}, fields="cal_date,is_open"
)
self.assertTrue(calendar["equal"])
def test_shadow_projection_still_alarms_on_requested_field_problems(self) -> None:
hub_missing_field = {k: v for k, v in HUB_DAILY.items() if k != "close"}
legacy_close_only = {k: LEGACY_DAILY[k] for k in ("ts_code", "trade_date", "close")}
lost = compare_rows(
"daily", [legacy_close_only], [hub_missing_field], fields="ts_code,trade_date,close"
)
self.assertFalse(lost["equal"])
self.assertEqual(lost["value_diff_count"], 1)
changed = compare_rows(
"daily", [legacy_close_only], [{**HUB_DAILY, "close": 99.0}],
fields="ts_code,trade_date,close",
)
self.assertFalse(changed["equal"])
self.assertEqual(changed["value_diff_count"], 1)
self.assertEqual(changed["value_diffs"][0]["fields"][0]["field"], "close")
gone = compare_rows("daily", [LEGACY_DAILY], [], fields="ts_code,trade_date,close")
self.assertEqual(gone["missing_hub_count"], 1)
self.assertFalse(gone["equal"])
unit = compare_rows(
"daily", [LEGACY_DAILY], [{**HUB_DAILY, "amount": 2000.0, "volume": 1000.0}],
fields="ts_code,trade_date,vol,amount",
)
self.assertGreater(unit["unit_conversion_count"], 0)
self.assertFalse(unit["equal"])
def test_bridge_shadow_report_uses_website_request_fields(self) -> None:
hub_full = {**HUB_DAILY, "adj_factor": 1.1}
legacy_close_only = {k: LEGACY_DAILY[k] for k in ("ts_code", "trade_date", "close", "vol", "amount")}
reports: list[dict[str, Any]] = []
client = FakeClient(
response=DatahubResponse(
data=[hub_full],
meta={"tier": "official", "trade_date": "20240902", "stale": False, "staleness_seconds": 0},
)
)
wrapped = DatahubAwareTushareClient(
FakeLegacy([legacy_close_only]),
DatahubBridge(flags(daily=(False, True)), client, shadow_sink=reports.append),
)
rows = wrapped.query("daily", {"trade_date": "20240902"}, "ts_code,trade_date,close,vol,amount")
self.assertEqual(rows[0]["close"], 10.20)
self.assertEqual(rows[0]["vol"], 1000.0)
self.assertTrue(reports[0]["equal"])
self.assertEqual(reports[0]["matched"], 1)
def test_native_roundtrip_matches_known_scales(self) -> None: def test_native_roundtrip_matches_known_scales(self) -> None:
native = to_native_row("daily", HUB_DAILY) native = to_native_row("daily", HUB_DAILY)
self.assertEqual(native["vol"], 1000.0) self.assertEqual(native["vol"], 1000.0)
+14 -2
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@@ -83,6 +83,16 @@ python -m datahub history-backfill
`hub-quality.config.json``field_gates` 按数据集配置关键字段:非空率下限(支持按字段覆盖,如 `dv_ttm` 合法高空值)、非有限值比例上限、以及相对上一已发布批次的非空率塌陷保护。字段大面积为空的批次会被拒绝发布、保留上一份正常正式数据,失败原因逐字段写入 `batches.error` / `quality_json`。被拒后数据集仍视为缺失,盘后自动重试(HEL-435 机制)会继续尝试直到成功或截止。配置对任意数据集生效,不写死单日或单字段。 `hub-quality.config.json``field_gates` 按数据集配置关键字段:非空率下限(支持按字段覆盖,如 `dv_ttm` 合法高空值)、非有限值比例上限、以及相对上一已发布批次的非空率塌陷保护。字段大面积为空的批次会被拒绝发布、保留上一份正常正式数据,失败原因逐字段写入 `batches.error` / `quality_json`。被拒后数据集仍视为缺失,盘后自动重试(HEL-435 机制)会继续尝试直到成功或截止。配置对任意数据集生效,不写死单日或单字段。
## 整批原子发布(release group
盘后发布/重发(eod_a、eod_retry、`eod-refresh`、跨数据集重发)不再逐数据集各自切换,而是走整批原子可见机制:
- 一致性边界:日 K、估值、资金流、竞价同属 A 组整批;指数日 K 为 B 组;当日股票主档快照随 A 组一同切换(主档 `stock_master` 的 UPSERT 与快照发布同一事务,不会出现主档先行/滞后)。
- 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: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 ## 股票主档每日刷新与发布
交易日 20:00 与 23:10`stocks_refresh_times` 可配)自动刷新股票主档并发布版本化快照(`eod_stocks` + `publications.dataset='stocks'`),覆盖当日新上市、证券简称变化和上市首日 N/C 前缀摘除;无变化则跳过,重复执行幂等。`/v1/stocks` 从最新已发布快照提供数据并带 `batch_id` / `published_at``/v1/datasets/status` 同步展示 stocks 状态。 交易日 20:00 与 23:10`stocks_refresh_times` 可配)自动刷新股票主档并发布版本化快照(`eod_stocks` + `publications.dataset='stocks'`),覆盖当日新上市、证券简称变化和上市首日 N/C 前缀摘除;无变化则跳过,重复执行幂等。`/v1/stocks` 从最新已发布快照提供数据并带 `batch_id` / `published_at``/v1/datasets/status` 同步展示 stocks 状态。
@@ -105,11 +115,13 @@ python -m datahub moneyflow-backfill # --trading-days 60 --end-date --for
```bash ```bash
cd xiaobai-datahub 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 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。
## 备份 ## 备份
+1 -1
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@@ -269,7 +269,7 @@ function renderRelease(data) {
async function dangerous(kind, dataset) { async function dangerous(kind, dataset) {
const date = ($("rel-date") && $("rel-date").value) || ""; const date = ($("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; if (!ds) return;
const password = prompt("二次确认:输入管理密码"); const password = prompt("二次确认:输入管理密码");
if (!password) return; if (!password) return;
@@ -22,6 +22,18 @@
"20:00", "20:00",
"23:10" "23:10"
], ],
"cross_gates": [
{
"left": "daily",
"right": "valuation",
"min_key_overlap": 0.98
},
{
"left": "daily",
"right": "moneyflow",
"min_key_overlap": 0.98
}
],
"field_gates": { "field_gates": {
"valuation": { "valuation": {
"fields": [ "fields": [
+16 -2
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@@ -6,7 +6,7 @@ from typing import Any
from datahub.adapters import RESERVED from datahub.adapters import RESERVED
from datahub.auth import AuthService from datahub.auth import AuthService
from datahub.db import HubDB 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.scheduler import Scheduler
from datahub.serving import ApiError from datahub.serving import ApiError
from datahub.timeutil import isoformat, now_shanghai, session_phase, yyyymmdd from datahub.timeutil import isoformat, now_shanghai, session_phase, yyyymmdd
@@ -143,8 +143,22 @@ class AdminAPI:
self._dangerous(password, confirm, f"{dataset}:{day}") self._dangerous(password, confirm, f"{dataset}:{day}")
if dataset == "reference": if dataset == "reference":
result = self.pipeline.ingest_reference(day) 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: 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})) self.pipeline.audit(actor, "backfill", f"{dataset}:{day}", json.dumps({"ok": True}))
return result return result
+15 -14
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@@ -7,7 +7,7 @@ import json
import sys import sys
from datahub.hub import build_hub 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.settings import load_settings
from datahub.timeutil import yyyymmdd 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("--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("--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") 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("--trade-date", default=None, help="交易日 YYYYMMDD,默认今天")
refresh.add_argument( refresh.add_argument(
"--force", action="store_true", "--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( refresh.add_argument(
"--dataset", default=None, "--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 = 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") 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": if args.command == "eod-refresh":
day = yyyymmdd(args.trade_date) if args.trade_date else yyyymmdd() day = yyyymmdd(args.trade_date) if args.trade_date else yyyymmdd()
if args.force: if args.force:
datasets = tuple(sorted({args.dataset} & OFFICIAL_DATASETS)) if args.dataset else () allowed = set(OFFICIAL_DATASETS) | {STOCKS_DATASET}
if args.dataset and not datasets: if not args.dataset:
parser.error(f"unknown dataset: {args.dataset}")
if not datasets:
parser.error("--force requires --dataset (e.g. --dataset valuation)") parser.error("--force requires --dataset (e.g. --dataset valuation)")
result = {} if args.dataset not in allowed:
for dataset in datasets: parser.error(f"unknown dataset: {args.dataset}")
result[dataset] = hub.pipeline.run_dataset(dataset, day) 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: else:
result = hub.pipeline.run_eod_missing(day) result = hub.pipeline.run_eod_missing(day)
boundary = None
hub.pipeline.audit("cli", "eod-refresh", f"eod:{day}", json.dumps( 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)}}, **{name: item.get("state") for name, item in result.items() if isinstance(item, dict)}},
ensure_ascii=False, ensure_ascii=False,
)) ))
if args.force: 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) json.dump(payload, sys.stdout, ensure_ascii=False, indent=2, default=str)
sys.stdout.write("\n") sys.stdout.write("\n")
return 0 return 0 if not failures else 1
missing = hub.pipeline.missing_official_datasets(day) missing = hub.pipeline.missing_official_datasets(day)
payload = {"trade_date": day, "datasets": result, "missing_after": missing} payload = {"trade_date": day, "datasets": result, "missing_after": missing}
json.dump(payload, sys.stdout, ensure_ascii=False, indent=2, default=str) json.dump(payload, sys.stdout, ensure_ascii=False, indent=2, default=str)
+448 -81
View File
@@ -133,6 +133,95 @@ def _staging_row_count(connection: Any, dataset: str, batch_id: str) -> int:
return int(row["n"] if row is not None else 0) return int(row["n"] if row is not None else 0)
def _staging_count_or_raise(connection: Any, dataset: str, trade_date: str, batch_id: str) -> int:
rows_out = _staging_row_count(connection, dataset, batch_id)
if rows_out <= 0:
report = {
"rows": 0,
"errors": [EMPTY_BATCH_ERROR],
"warnings": [],
"hard_fail": True,
"soft_fail": False,
"batch_id": batch_id,
"dataset": dataset,
"trade_date": trade_date,
}
LOGGER.warning(
"skip official publish for empty batch",
extra={
"hub": {
"dataset": dataset,
"trade_date": trade_date,
"batch_id": batch_id,
"rows_out": rows_out,
"reason": "upstream_empty",
}
},
)
raise QualityError("empty batch cannot be officially published", report)
return rows_out
def _upsert_publication(
connection: Any,
dataset: str,
trade_date: str,
batch_id: str,
state: str,
published_at: str,
) -> None:
current = connection.execute(
"SELECT active_batch FROM publications WHERE dataset = ? AND trade_date = ?",
(dataset, trade_date),
).fetchone()
prev = str(current["active_batch"]) if current else None
connection.execute(
"""
INSERT INTO publications(dataset, trade_date, active_batch, prev_batch, state, published_at)
VALUES (?, ?, ?, ?, ?, ?)
ON CONFLICT(dataset, trade_date) DO UPDATE SET
prev_batch=excluded.prev_batch,
active_batch=excluded.active_batch,
state=excluded.state,
published_at=excluded.published_at
""",
(dataset, trade_date, batch_id, prev, state, published_at),
)
def _record_publication_history(
connection: Any,
dataset: str,
trade_date: str,
batch_id: str,
published_at: str,
quality: dict[str, Any],
) -> None:
max_gen = connection.execute(
"SELECT COALESCE(MAX(generation), 0) AS g FROM publication_history WHERE dataset = ? AND trade_date = ?",
(dataset, trade_date),
).fetchone()
generation = int(max_gen["g"]) + 1
connection.execute(
"INSERT OR REPLACE INTO publication_history(dataset, trade_date, batch_id, published_at, generation) VALUES (?,?,?,?,?)",
(dataset, trade_date, batch_id, published_at, generation),
)
keep = int(quality.get("publication_generations") or 3)
stale = connection.execute(
"""
SELECT batch_id FROM publication_history
WHERE dataset = ? AND trade_date = ?
ORDER BY generation DESC
""",
(dataset, trade_date),
).fetchall()
for row in stale[keep:]:
connection.execute(
"DELETE FROM publication_history WHERE dataset = ? AND trade_date = ? AND batch_id = ?",
(dataset, trade_date, row["batch_id"]),
)
class QualityError(RuntimeError): class QualityError(RuntimeError):
def __init__(self, message: str, report: dict[str, Any]) -> None: def __init__(self, message: str, report: dict[str, Any]) -> None:
super().__init__(message) super().__init__(message)
@@ -259,11 +348,20 @@ class Pipeline:
is published; ``force`` re-publishes unconditionally. New listings, is published; ``force`` re-publishes unconditionally. New listings,
renames (incl. N/C prefix removal) and status changes all flow into renames (incl. N/C prefix removal) and status changes all flow into
the snapshot, which carries batch_id/published_at metadata. 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()) day = yyyymmdd(trade_date or self.clock())
try:
rows = self._fetch_dataset(STOCKS_DATASET, day) rows = self._fetch_dataset(STOCKS_DATASET, day)
with self.db.write() as connection: except Exception as exc:
self._upsert_stock_master(connection, rows, isoformat(self.clock())) self.audit(
"pipeline", "stocks-refresh", f"{STOCKS_DATASET}:{day}",
json.dumps({"state": "failed", "error": str(exc)}, ensure_ascii=False),
)
raise
if not force: if not force:
active, snapshot = self.published_stock_snapshot(day) active, snapshot = self.published_stock_snapshot(day)
if active is not None: if active is not None:
@@ -280,7 +378,14 @@ class Pipeline:
"batch_id": active, "batch_id": active,
"rows": len(snapshot), "rows": len(snapshot),
} }
try:
result = self.run_dataset(STOCKS_DATASET, day, prepared_rows=rows) 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( self.audit(
"pipeline", "stocks-refresh", f"{STOCKS_DATASET}:{day}", "pipeline", "stocks-refresh", f"{STOCKS_DATASET}:{day}",
json.dumps({"batch_id": result["batch_id"], "rows": result["rows"]}, ensure_ascii=False), json.dumps({"batch_id": result["batch_id"], "rows": result["rows"]}, ensure_ascii=False),
@@ -548,43 +653,358 @@ class Pipeline:
return [dataset for dataset in sorted(OFFICIAL_DATASETS) if dataset not in published] return [dataset for dataset in sorted(OFFICIAL_DATASETS) if dataset not in published]
def run_eod_missing(self, trade_date: str) -> dict[str, Any]: 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 A-group (daily/valuation/moneyflow/auction + stocks) and B-group
repeats never overwrite the current official batch. Per-dataset (index_daily) are separate boundaries. Within a group, either the
failures are collected instead of aborting the remaining datasets. 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_eod_datasets(tuple(sorted(OFFICIAL_DATASETS)), trade_date) results: dict[str, Any] = {}
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) -> dict[str, Any]: def run_eod_batch_a(self, trade_date: str, force: bool = False) -> dict[str, Any]:
return self._run_eod_datasets(EOD_A_DATASETS, trade_date) return self.run_release_group(EOD_A_DATASETS, trade_date, include_stocks=True, force=force)
def run_eod_batch_b(self, trade_date: str) -> dict[str, Any]: def run_eod_batch_b(self, trade_date: str, force: bool = False) -> dict[str, Any]:
return self._run_eod_datasets(EOD_B_DATASETS, trade_date) return self.run_release_group(EOD_B_DATASETS, trade_date, force=force)
def _run_eod_datasets(self, datasets: tuple[str, ...], trade_date: str) -> dict[str, Any]: 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.
"""
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)
raise ValueError(f"dataset is not part of an EOD release boundary: {dataset}")
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) day = yyyymmdd(trade_date)
results: dict[str, Any] = {} 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: for dataset in datasets:
if self.active_batch(dataset, day) is not None:
results[dataset] = { results[dataset] = {
"dataset": dataset, "dataset": dataset,
"trade_date": day, "trade_date": day,
"state": "skipped", "state": "skipped",
"reason": "already_published", "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:
results[dataset] = {
"dataset": dataset,
"trade_date": day,
"state": "aborted",
"reason": f"release group aborted: {failure}",
}
continue continue
try: try:
results[dataset] = self.run_dataset(dataset, day) staged[dataset] = self._stage_and_validate(dataset, day)
except Exception as exc: except Exception as exc:
failure = f"{dataset}: {exc}"
results[dataset] = { results[dataset] = {
"dataset": dataset, "dataset": dataset,
"trade_date": day, "trade_date": day,
"state": "failed", "state": "failed",
"error": str(exc), "error": str(exc),
} }
# 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, force=rebuild_official)
except Exception as exc:
failure = f"{STOCKS_DATASET}: {exc}"
results[STOCKS_DATASET] = {
"dataset": STOCKS_DATASET,
"trade_date": day,
"state": "failed",
"error": str(exc),
}
else:
if stocks_plan is not None:
staged[STOCKS_DATASET] = stocks_plan
if failure is None and staged:
cross_errors = self._cross_gate_errors(staged)
if cross_errors:
failure = "; ".join(cross_errors)
if failure is not None:
for dataset, item in staged.items():
self._abandon_batch(item["batch_id"], f"release group not switched: {failure}")
results[dataset] = {
"dataset": dataset,
"trade_date": day,
"state": "failed",
"error": f"release group not switched: {failure}",
"batch_id": item["batch_id"],
}
LOGGER.warning(
"release group blocked, previous official version keeps serving",
extra={
"hub": {
"trade_date": day,
"datasets": sorted(staged),
"reason": failure,
"event": "release_group_blocked",
}
},
)
self.audit(
"pipeline", "release-group", f"eod:{day}",
json.dumps({"state": "failed", "reason": failure}, ensure_ascii=False),
)
return results return results
if staged:
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"], 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] = {
"dataset": dataset,
"trade_date": day,
"state": item["state"],
"batch_id": item["batch_id"],
"rows": item["rows"],
}
self.audit(
"pipeline", "release-group", f"eod:{day}",
json.dumps(
{"state": "ok", "switched": sorted(staged), "force": bool(force)},
ensure_ascii=False,
),
)
return results
def _stage_and_validate(self, dataset: str, trade_date: str, attempts: int | None = None) -> dict[str, Any]:
"""Fetch → stage → quality-gate one member without publishing it."""
day = yyyymmdd(trade_date)
batch_id = self.next_batch_id(dataset, day)
max_attempts = attempts or self.settings.max_publish_attempts
rows: list[dict[str, Any]] = []
self._set_batch(batch_id, dataset, day, "scheduled", 0)
try:
self._set_batch(batch_id, dataset, day, "fetching", 1)
rows = retry_call(
lambda: self._fetch_dataset(dataset, day),
attempts=max_attempts,
base_delay=0.05,
sleeper=lambda _d: time.sleep(_d),
)
self._stage(dataset, batch_id, rows)
self._set_batch(batch_id, dataset, day, "staged", 1, rows_in=len(rows), rows_out=len(rows))
self._set_batch(batch_id, dataset, day, "validating", 1, rows_in=len(rows), rows_out=len(rows))
report = self.validate(dataset, batch_id, day, rows)
if report["hard_fail"]:
self._reject_batch(batch_id, dataset, day, rows, report)
raise QualityError("integrity gate failed", report)
except RetryError as exc:
self._set_batch(batch_id, dataset, day, "failed", max_attempts, error=str(exc), finished=True)
raise
except QualityError as exc:
current = self.db.fetchone("SELECT state FROM batches WHERE batch_id = ?", (batch_id,))
if current and current["state"] not in {"staged", "failed"}:
self._reject_batch(batch_id, dataset, day, rows, exc.report)
raise
except Exception as exc:
self._set_batch(batch_id, dataset, day, "failed", 1, error=str(exc), finished=True)
raise
self._set_batch(
batch_id, dataset, day, "ready", 1, rows_in=len(rows), rows_out=len(rows), quality=report
)
return {
"dataset": dataset,
"trade_date": day,
"batch_id": batch_id,
"rows": len(rows),
"quality": report,
"state": "degraded" if report["soft_fail"] else "published",
}
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) 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 and not force:
upstream = sorted(
tuple(str(row.get(field)) for field in STOCK_SNAPSHOT_FIELDS) for row in rows
)
published = sorted(tuple(str(row.get(field)) for field in STOCK_SNAPSHOT_FIELDS) for row in snapshot)
if upstream == published:
return None
batch_id = self.next_batch_id(STOCKS_DATASET, day)
self._set_batch(batch_id, STOCKS_DATASET, day, "scheduled", 0)
self._set_batch(batch_id, STOCKS_DATASET, day, "fetching", 1)
self._stage(STOCKS_DATASET, batch_id, rows)
self._set_batch(batch_id, STOCKS_DATASET, day, "staged", 1, rows_in=len(rows), rows_out=len(rows))
self._set_batch(batch_id, STOCKS_DATASET, day, "validating", 1, rows_in=len(rows), rows_out=len(rows))
report = self.validate(STOCKS_DATASET, batch_id, day, rows)
if report["hard_fail"]:
self._reject_batch(batch_id, STOCKS_DATASET, day, rows, report)
raise QualityError("integrity gate failed", report)
self._set_batch(
batch_id, STOCKS_DATASET, day, "ready", 1, rows_in=len(rows), rows_out=len(rows), quality=report
)
return {
"dataset": STOCKS_DATASET,
"trade_date": day,
"batch_id": batch_id,
"rows": len(rows),
"row_values": rows,
"quality": report,
"state": "degraded" if report["soft_fail"] else "published",
}
def _cross_gate_errors(self, staged: dict[str, dict[str, Any]]) -> list[str]:
"""Cross-dataset consistency checks on staged batches (交叉校验)."""
errors: list[str] = []
gates = self.settings.quality.get("cross_gates") or []
for gate in gates if isinstance(gates, list) else []:
if not isinstance(gate, dict):
continue
left = str(gate.get("left") or "")
right = str(gate.get("right") or "")
if not left or not right or left not in staged or right not in staged:
continue
floor = float(gate.get("min_key_overlap") or 0.98)
left_keys = self._staging_keys(left, staged[left]["batch_id"])
right_keys = self._staging_keys(right, staged[right]["batch_id"])
denom = max(len(left_keys), len(right_keys))
overlap = (len(left_keys & right_keys) / denom) if denom else 1.0
if overlap < floor:
errors.append(
f"cross gate: {left} vs {right} key overlap {overlap:.4f} < {floor}"
)
return errors
def _staging_keys(self, dataset: str, batch_id: str) -> set[str]:
table = DATASET_TABLES[dataset][1]
rows = self.db.fetchall(
f"SELECT DISTINCT ts_code FROM {table} WHERE batch_id = ?",
(batch_id,),
)
return {str(row["ts_code"]) for row in rows}
def _switch_release_group(self, trade_date: str, members: dict[str, dict[str, Any]]) -> None:
"""Single transaction: copy every member and flip every publication."""
day = yyyymmdd(trade_date)
published_at = isoformat(self.clock())
with self.db.write() as connection:
for dataset, item in members.items():
_staging_count_or_raise(connection, dataset, day, item["batch_id"])
for dataset, item in members.items():
connection.execute(EOD_COPY[dataset], (item["batch_id"],))
if dataset == STOCKS_DATASET:
self._upsert_stock_master(connection, item["row_values"], published_at)
if self.before_commit:
self.before_commit()
for dataset, item in members.items():
_upsert_publication(connection, dataset, day, item["batch_id"], item["state"], published_at)
_record_publication_history(
connection, dataset, day, item["batch_id"], published_at, self.settings.quality
)
connection.execute(
"UPDATE batches SET state='published', finished_at=? WHERE batch_id=?",
(published_at, item["batch_id"]),
)
def _abandon_batch(self, batch_id: str, reason: str) -> None:
row = self.db.fetchone("SELECT dataset, trade_date FROM batches WHERE batch_id = ?", (batch_id,))
if not row:
return
self._set_batch(
batch_id, str(row["dataset"]), str(row["trade_date"]), "failed", 1,
error=reason, finished=True,
)
@staticmethod @staticmethod
def eod_failures(results: dict[str, Any]) -> list[str]: def eod_failures(results: dict[str, Any]) -> list[str]:
return [ return [
@@ -735,77 +1155,24 @@ class Pipeline:
return batch_id, stats return batch_id, stats
def publish(self, dataset: str, trade_date: str, batch_id: str, state: str = "published") -> None: def publish(self, dataset: str, trade_date: str, batch_id: str, state: str = "published") -> None:
copy_sql = EOD_COPY[dataset]
published_at = isoformat(self.clock()) published_at = isoformat(self.clock())
with self.db.write() as connection: with self.db.write() as connection:
rows_out = _staging_row_count(connection, dataset, batch_id) _staging_count_or_raise(connection, dataset, trade_date, batch_id)
if rows_out <= 0: connection.execute(EOD_COPY[dataset], (batch_id,))
report = { if dataset == STOCKS_DATASET:
"rows": 0, staging = DATASET_TABLES[STOCKS_DATASET][1]
"errors": [EMPTY_BATCH_ERROR], stock_rows = [
"warnings": [], dict(row)
"hard_fail": True, for row in connection.execute(
"soft_fail": False, f"SELECT * FROM {staging} WHERE batch_id = ?",
"batch_id": batch_id, (batch_id,),
"dataset": dataset, ).fetchall()
"trade_date": trade_date, ]
} self._upsert_stock_master(connection, stock_rows, published_at)
LOGGER.warning(
"skip official publish for empty batch",
extra={
"hub": {
"dataset": dataset,
"trade_date": trade_date,
"batch_id": batch_id,
"rows_out": rows_out,
"reason": "upstream_empty",
}
},
)
raise QualityError("empty batch cannot be officially published", report)
current = connection.execute(
"SELECT active_batch FROM publications WHERE dataset = ? AND trade_date = ?",
(dataset, trade_date),
).fetchone()
prev = str(current["active_batch"]) if current else None
connection.execute(copy_sql, (batch_id,))
if self.before_commit: if self.before_commit:
self.before_commit() self.before_commit()
connection.execute( _upsert_publication(connection, dataset, trade_date, batch_id, state, published_at)
""" _record_publication_history(connection, dataset, trade_date, batch_id, published_at, self.settings.quality)
INSERT INTO publications(dataset, trade_date, active_batch, prev_batch, state, published_at)
VALUES (?, ?, ?, ?, ?, ?)
ON CONFLICT(dataset, trade_date) DO UPDATE SET
prev_batch=excluded.prev_batch,
active_batch=excluded.active_batch,
state=excluded.state,
published_at=excluded.published_at
""",
(dataset, trade_date, batch_id, prev, state, published_at),
)
max_gen = connection.execute(
"SELECT COALESCE(MAX(generation), 0) AS g FROM publication_history WHERE dataset = ? AND trade_date = ?",
(dataset, trade_date),
).fetchone()
generation = int(max_gen["g"]) + 1
connection.execute(
"INSERT OR REPLACE INTO publication_history(dataset, trade_date, batch_id, published_at, generation) VALUES (?,?,?,?,?)",
(dataset, trade_date, batch_id, published_at, generation),
)
keep = int(self.settings.quality.get("publication_generations") or 3)
stale = connection.execute(
"""
SELECT batch_id FROM publication_history
WHERE dataset = ? AND trade_date = ?
ORDER BY generation DESC
""",
(dataset, trade_date),
).fetchall()
for row in stale[keep:]:
connection.execute(
"DELETE FROM publication_history WHERE dataset = ? AND trade_date = ? AND batch_id = ?",
(dataset, trade_date, row["batch_id"]),
)
def rollback(self, dataset: str, trade_date: str, actor: str = "admin") -> dict[str, Any]: def rollback(self, dataset: str, trade_date: str, actor: str = "admin") -> dict[str, Any]:
trade_date = yyyymmdd(trade_date) trade_date = yyyymmdd(trade_date)
@@ -0,0 +1,408 @@
from __future__ import annotations
import unittest
from pathlib import Path
import tempfile
from datahub.adapters.tushare import TushareAdapter
from datahub.crypto import SecretVault
from datahub.db import HubDB
from datahub.pipeline import Pipeline
from datahub.settings import Settings
from datahub.serving import V1API
from tests.fixtures import TRADE_DATE, fake_transport
GROUP_A = ("daily", "valuation", "moneyflow", "auction")
class GroupTransport:
"""fake_transport with per-API degradation switches for release-group tests."""
def __init__(self) -> None:
self.empty: set[str] = set()
self.keep_rows: dict[str, int] = {}
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 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)
if keep is not None:
return rows[:keep]
return rows
def make_pipe(transport: GroupTransport, quality_extra: dict | None = None):
tmp = tempfile.TemporaryDirectory()
db = HubDB(Path(tmp.name) / "hub.db")
adapter = TushareAdapter("test-token", transport=transport)
quality = {
"daily_row_ratio": 0.98,
"null_rate_max": 0.01,
"max_publish_attempts": 2,
"publication_generations": 3,
}
if quality_extra:
quality.update(quality_extra)
settings = Settings(
encryption_key=SecretVault.generate_key(),
api_token="t" * 32,
admin_password="admin-pass",
tushare_token="test-token",
db_path=db.path,
quality=quality,
scheduler_enabled=False,
)
pipe = Pipeline(db, adapter, settings)
pipe._tmp = tmp
return pipe, db
def publications_map(db: HubDB, day: str) -> dict[str, str]:
rows = db.fetchall("SELECT dataset, active_batch FROM publications WHERE trade_date = ?", (day,))
return {str(row["dataset"]): str(row["active_batch"]) for row in rows}
class ReleaseGroupSwitchTests(unittest.TestCase):
def setUp(self) -> None:
self.transport = GroupTransport()
self.pipe, self.db = make_pipe(self.transport)
self.pipe.ingest_reference(TRADE_DATE)
def test_whole_group_switches_in_one_publish_instant(self) -> None:
results = self.pipe.run_eod_batch_a(TRADE_DATE)
self.assertEqual(set(results), {*GROUP_A, "stocks"})
self.assertEqual({item["state"] for item in results.values()}, {"published"})
pubs = self.db.fetchall("SELECT * FROM publications WHERE trade_date = ?", (TRADE_DATE,))
self.assertEqual(len(pubs), 5)
self.assertEqual(len({row["published_at"] for row in pubs}), 1)
# official rows copied and serving resolves the new batches
api = V1API(self.db, self.pipe, self.pipe.settings)
payload = api.handle("/v1/bars/daily", {"date": [TRADE_DATE], "code": ["600000.SH"]})
self.assertEqual(payload["meta"]["batch_id"], results["daily"]["batch_id"])
stocks = api.handle("/v1/stocks", {})
self.assertEqual(stocks["meta"]["batch_id"], results["stocks"]["batch_id"])
def test_any_member_failure_blocks_entire_group(self) -> None:
self.transport.empty = {"daily_basic"} # valuation upstream returns nothing
results = self.pipe.run_eod_batch_a(TRADE_DATE)
self.assertEqual(results["valuation"]["state"], "failed")
self.assertEqual(results["moneyflow"]["state"], "aborted")
self.assertEqual(results["auction"]["state"], "aborted")
self.assertEqual(results["daily"]["state"], "failed") # staged fine, then abandoned
# nothing became visible, and the reason is recorded
self.assertEqual(publications_map(self.db, TRADE_DATE), {})
abandoned = self.db.fetchall(
"SELECT * FROM batches WHERE trade_date = ? AND state = 'failed'",
(TRADE_DATE,),
)
self.assertTrue(any("release group not switched" in str(row["error"] or "") for row in abandoned))
audit = self.db.fetchone(
"SELECT * FROM audit_log WHERE action = 'release-group' ORDER BY id DESC"
)
self.assertIn("valuation", str(audit["detail"]))
# still missing → evening retries keep trying
self.assertIn("daily", self.pipe.missing_official_datasets(TRADE_DATE))
def test_failure_keeps_previous_complete_version_serving(self) -> None:
first = self.pipe.run_dataset("daily", TRADE_DATE)
self.transport.empty = {"daily_basic"}
results = self.pipe.run_eod_missing(TRADE_DATE)
# 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 daily batch is untouched and keeps serving
self.assertEqual(self.pipe.active_batch("daily", TRADE_DATE), 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] = []
def watcher() -> None:
with self.db.connect() as connection:
rows = connection.execute(
"SELECT dataset, active_batch FROM publications WHERE trade_date = ?",
(TRADE_DATE,),
).fetchall()
snapshots.append({str(row["dataset"]): row["active_batch"] for row in rows})
self.pipe.before_commit = watcher
self.pipe.run_eod_batch_a(TRADE_DATE)
# inside the switch transaction the group was still invisible
self.assertEqual(snapshots[0], {})
after = publications_map(self.db, TRADE_DATE)
self.assertEqual(set(after), {*GROUP_A, "stocks"})
def test_switch_crash_rolls_back_whole_group(self) -> None:
def explode() -> None:
raise RuntimeError("killed mid-switch")
self.pipe.before_commit = explode
with self.assertRaises(RuntimeError):
self.pipe.run_eod_batch_a(TRADE_DATE)
self.assertEqual(publications_map(self.db, TRADE_DATE), {})
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)
self.pipe.run_eod_batch_b(TRADE_DATE)
batches_before = {
str(row["batch_id"])
for row in self.db.fetchall("SELECT batch_id FROM batches WHERE trade_date = ?", (TRADE_DATE,))
}
calls_before = len(self.transport.calls)
again = self.pipe.run_eod_missing(TRADE_DATE)
self.assertEqual({item["state"] for item in again.values()}, {"skipped"})
self.assertEqual({item["reason"] for item in again.values()}, {"already_published"})
batches_after = {
str(row["batch_id"])
for row in self.db.fetchall("SELECT batch_id FROM batches WHERE trade_date = ?", (TRADE_DATE,))
}
self.assertEqual(batches_after, batches_before)
self.assertEqual(len(self.transport.calls), calls_before)
self.assertEqual(self.pipe.missing_official_datasets(TRADE_DATE), [])
def test_cross_gate_failure_blocks_switch(self) -> None:
transport = GroupTransport()
pipe, db = make_pipe(
transport,
quality_extra={"cross_gates": [
{"left": "daily", "right": "moneyflow", "min_key_overlap": 1.0},
]},
)
pipe.ingest_reference(TRADE_DATE)
transport.keep_rows["moneyflow"] = 1 # moneyflow covers only half the market
results = pipe.run_eod_batch_a(TRADE_DATE)
self.assertEqual(results["moneyflow"]["state"], "failed")
self.assertIn("cross gate", str(results["moneyflow"]["error"]))
self.assertEqual(publications_map(db, TRADE_DATE), {})
def test_stocks_master_and_snapshot_switch_together_or_not_at_all(self) -> None:
original = [
{"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"},
]
renamed = [dict(original[0]), {**original[1], "name": "金钛股份"}]
self.transport.stocks = renamed
self.pipe.run_eod_batch_a(TRADE_DATE)
master = self.db.fetchone("SELECT name FROM stock_master WHERE ts_code = '920071.BJ'")
self.assertEqual(master["name"], "金钛股份")
stocks_pub = self.db.fetchone(
"SELECT active_batch FROM publications WHERE dataset = 'stocks' AND trade_date = ?",
(TRADE_DATE,),
)
self.assertIsNotNone(stocks_pub)
# failure path: rename staged but the group is blocked → master stays untouched
transport = GroupTransport()
transport.stocks = original
pipe, db = make_pipe(
transport,
quality_extra={"cross_gates": [
{"left": "daily", "right": "moneyflow", "min_key_overlap": 1.0},
]},
)
pipe.ingest_reference(TRADE_DATE) # master seeded with "N金钛"
transport.stocks = renamed
transport.keep_rows["moneyflow"] = 1
results = pipe.run_eod_batch_a(TRADE_DATE)
self.assertEqual(results["stocks"]["state"], "failed")
master = db.fetchone("SELECT name FROM stock_master WHERE ts_code = '920071.BJ'")
self.assertEqual(master["name"], "N金钛") # rename not applied
stocks_pub = db.fetchone(
"SELECT active_batch FROM publications WHERE dataset = 'stocks' AND trade_date = ?",
(TRADE_DATE,),
)
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()
+20 -11
View File
@@ -228,25 +228,34 @@ class GateRetryInterplayTests(unittest.TestCase):
class ForceRepublishTests(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() transport = ValuationTransport()
pipe, db = make_pipe(transport) pipe, db = make_pipe(transport)
pipe.ingest_reference(TRADE_DATE) 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" transport.mode = "vr_all_null"
with self.assertRaises(QualityError): blocked = pipe.force_republish_boundary("valuation", TRADE_DATE)
pipe.run_dataset("valuation", TRADE_DATE) # gate holds: bad re-publish refused 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" transport.mode = "ok"
second = pipe.run_dataset("valuation", TRADE_DATE) # CLI --force path second = pipe.force_republish_boundary("valuation", TRADE_DATE)
self.assertNotEqual(first["batch_id"], second["batch_id"]) self.assertEqual(second["valuation"]["state"], "published")
pub = db.fetchone( self.assertNotEqual(second["valuation"]["batch_id"], first_val)
"SELECT * FROM publications WHERE dataset='valuation' AND trade_date=?", 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,), (TRADE_DATE,),
) )
self.assertEqual(pub["active_batch"], second["batch_id"]) by_ds = {str(row["dataset"]): row for row in pubs}
self.assertEqual(pub["prev_batch"], first["batch_id"]) 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") 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__": if __name__ == "__main__":