feat(HEL-402): 接通网站首批只读 datahub 并建立双路对比

默认全部读取/影子开关关闭，网站继续走旧 Tushare 链路；开启单项时只替换该类原料并在失败时回旧，问天保持旧路径。

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: multica-agent <github@multica.ai>

backend/data/datahub/compare.py

@@ -0,0 +1,134 @@
+from __future__ import annotations
+
+from typing import Any
+
+from backend.data.datahub.native import SCALE_FIELDS, row_key, to_canonical_row, yyyymmdd
+
+NUMERIC_TOLERANCE = 1e-4
+
+
+def compare_rows(
+    dataset: str,
+    legacy_rows: list[dict[str, Any]],
+    hub_rows: list[dict[str, Any]] | None,
+    hub_meta: dict[str, Any] | None = None,
+    hub_error: str | None = None,
+) -> dict[str, Any]:
+    hub = hub_rows or []
+    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}
+    missing_hub = sorted(key for key in legacy_map if key not in hub_map)
+    missing_legacy = sorted(key for key in hub_map if key not in legacy_map)
+    value_diffs: list[dict[str, Any]] = []
+    unit_conversion: list[dict[str, Any]] = []
+    matched = 0
+    for key, legacy in legacy_map.items():
+        hub_row = hub_map.get(key)
+        if hub_row is None:
+            continue
+        field_report = _compare_fields(dataset, legacy, hub_row)
+        if field_report["unit_conversion"]:
+            unit_conversion.append({"key": list(key), "fields": field_report["unit_conversion"]})
+        if field_report["value_diff"]:
+            value_diffs.append({"key": list(key), "fields": field_report["value_diff"]})
+        if not field_report["unit_conversion"] and not field_report["value_diff"]:
+            matched += 1
+    stale_seconds = int((hub_meta or {}).get("staleness_seconds") or 0)
+    time_skew = bool((hub_meta or {}).get("stale")) or stale_seconds > 0
+    return {
+        "dataset": dataset,
+        "legacy_rows": len(legacy_rows),
+        "hub_rows": len(hub),
+        "matched": matched,
+        "missing_hub": [list(item) for item in missing_hub[:20]],
+        "missing_legacy": [list(item) for item in missing_legacy[:20]],
+        "missing_hub_count": len(missing_hub),
+        "missing_legacy_count": len(missing_legacy),
+        "value_diff_count": len(value_diffs),
+        "unit_conversion_count": len(unit_conversion),
+        "value_diffs": value_diffs[:20],
+        "unit_conversion": unit_conversion[:20],
+        "time_skew": time_skew,
+        "staleness_seconds": stale_seconds,
+        "published_at": (hub_meta or {}).get("published_at"),
+        "trade_date": yyyymmdd((hub_meta or {}).get("trade_date")),
+        "hub_error": hub_error,
+        "equal": (
+            not hub_error
+            and not missing_hub
+            and not missing_legacy
+            and not value_diffs
+            and not unit_conversion
+            and not time_skew
+        ),
+    }
+
+
+def _align_hub_row(row: dict[str, Any]) -> dict[str, Any]:
+    aligned = dict(row)
+    if "volume" in aligned and "vol" not in aligned:
+        aligned["vol"] = aligned.get("volume")
+    return aligned
+
+
+def _compare_fields(dataset: str, legacy: dict[str, Any], hub: dict[str, Any]) -> dict[str, list[dict[str, Any]]]:
+    canonical_legacy = to_canonical_row(dataset, legacy)
+    hub_canonical = _hub_canonical(dataset, hub)
+    native_hub = _align_hub_row(hub)
+    value_diff: list[dict[str, Any]] = []
+    unit_conversion: list[dict[str, Any]] = []
+    keys = (set(canonical_legacy) | set(hub_canonical)) - {"batch_id", "updated_at", "volume"}
+    scales = SCALE_FIELDS.get(dataset) or {}
+    for field in sorted(keys):
+        left = canonical_legacy.get(field)
+        right = hub_canonical.get(field)
+        if _same(left, right):
+            continue
+        native_left = legacy.get(field)
+        hub_raw = native_hub.get(field)
+        if field in scales and _near(_optional(native_left), _optional(hub_raw)):
+            unit_conversion.append(
+                {"field": field, "legacy": native_left, "hub": hub_raw, "reason": "unit_conversion"}
+            )
+            continue
+        value_diff.append({"field": field, "legacy": left, "hub": right, "reason": "value_diff"})
+    return {"value_diff": value_diff, "unit_conversion": unit_conversion}
+
+
+def _hub_canonical(dataset: str, row: dict[str, Any]) -> dict[str, Any]:
+    """Hub API rows are already canonical; only align field names."""
+    aligned = dict(row)
+    if "volume" in aligned and "vol" not in aligned:
+        aligned["vol"] = aligned.get("volume")
+    if dataset == "calendar":
+        is_open = aligned.get("is_open")
+        aligned["is_open"] = 1 if is_open in (True, 1, "1", "Y", "y") else 0
+        aligned["cal_date"] = yyyymmdd(aligned.get("cal_date"))
+        aligned["pretrade_date"] = yyyymmdd(aligned.get("pretrade_date")) or None
+        aligned["exchange"] = str(aligned.get("exchange") or "SSE")
+    return aligned
+
+
+def _same(left: Any, right: Any) -> bool:
+    if left in (None, "") and right in (None, ""):
+        return True
+    if isinstance(left, (int, float)) or isinstance(right, (int, float)):
+        return _near(_optional(left), _optional(right))
+    return str(left or "") == str(right or "")
+
+
+def _near(left: float | None, right: float | None) -> bool:
+    if left is None and right is None:
+        return True
+    if left is None or right is None:
+        return False
+    return abs(left - right) <= max(NUMERIC_TOLERANCE, abs(left) * 1e-9, abs(right) * 1e-9)
+
+
+def _optional(value: Any) -> float | None:
+    if value in (None, ""):
+        return None
+    try:
+        return float(value)
+    except (TypeError, ValueError):
+        return None