Интегрирован wesp в сайт

WESP_REL/app/lab/nutrient_schema.py

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+"""Канонические поля zootech-показателей компонента (parity tab INGREDIENT_NUTRIENT_EDIT_ROWS)."""
+
+from __future__ import annotations
+
+from typing import Any
+
+# column_name -> ключи в API/calc (первый — канон для UI)
+NUTRIENT_FIELD_SPECS: tuple[tuple[str, tuple[str, ...]], ...] = (
+    ("crude_protein", ("Сыр. Протеин",)),
+    ("usp", ("уСП",)),
+    ("rnb", ("RNB", "БРА", "    БРА ")),
+    ("nel_cattle", ("ЧЭЛ- КРС", "    ЧЭЛ- КРС", "ЧЭЛ - КРС Форм")),
+    ("oe_cattle", ("ОЭ-КРС", "    ОЭ-КРС", "OЭ КРС форм")),
+    ("ndf", ("Сырая клетчатка", "Сырая клетч")),
+    ("structural_fiber", ("Структур. клетчатка", "Структур клетч")),
+    ("crude_fat", ("Сырой жир",)),
+)
+
+
+def _normalize_key(value: str) -> str:
+    return " ".join((value or "").split()).strip().lower()
+
+
+def _parse_num(value: Any) -> float | None:
+    if value is None or value == "":
+        return None
+    try:
+        n = float(value)
+    except (TypeError, ValueError):
+        return None
+    return None if n != n else n
+
+
+def dry_matter_g_per_kg(dry_matter_pct: float | None) -> float | None:
+    """СВ г/кг из канонического component.dry_matter (%): 88.7% → 887 г/кг."""
+    dm = _parse_num(dry_matter_pct)
+    if dm is None:
+        return None
+    if 0 < dm <= 100:
+        return dm * 10.0
+    if dm > 100:
+        return dm
+    return None
+
+
+def resolve_sv_g_per_kg(
+    nutrients: dict[str, Any] | None,
+    dry_matter_pct: float | None,
+) -> float | None:
+    """Deprecated alias: СВ только из component.dry_matter (%). nutrients игнорируется."""
+    return dry_matter_g_per_kg(dry_matter_pct)
+
+
+def read_from_mapping(data: dict[str, Any] | None, keys: tuple[str, ...]) -> float | None:
+    if not data:
+        return None
+    for search in keys:
+        target = _normalize_key(search)
+        for k, v in data.items():
+            if _normalize_key(str(k)) != target:
+                continue
+            n = _parse_num(v)
+            if n is not None:
+                return n
+    return None
+
+
+def api_dict_to_column_values(data: dict[str, Any] | None) -> dict[str, float | None]:
+    payload = data or {}
+    out: dict[str, float | None] = {}
+    for col, keys in NUTRIENT_FIELD_SPECS:
+        out[col] = read_from_mapping(payload, keys)
+    return out
+
+
+def derived_to_column_values(data: dict[str, Any] | None) -> dict[str, float | None]:
+    return api_dict_to_column_values(data)
+
+
+def column_values_to_mapping(values: dict[str, float | None]) -> dict[str, float]:
+    out: dict[str, float] = {}
+    for col, keys in NUTRIENT_FIELD_SPECS:
+        val = values.get(col)
+        n = _parse_num(val)
+        if n is not None:
+            out[keys[0]] = n
+    return out
+
+
+def mapping_to_calc_dict(data: dict[str, Any] | None) -> dict[str, float]:
+    if not data:
+        return {}
+    from app.lab.indicators import RATION_ALL_INDICATORS
+
+    result: dict[str, float] = {}
+    for _col, keys in NUTRIENT_FIELD_SPECS:
+        val = read_from_mapping(data, keys)
+        if val is None:
+            continue
+        for key in keys:
+            result[key] = val
+    seen: set[str] = set()
+    for defn in RATION_ALL_INDICATORS:
+        for key in defn.get("nutrient_keys") or []:
+            if key in seen:
+                continue
+            seen.add(key)
+            val = read_from_mapping(data, (key,))
+            if val is not None:
+                result[key] = val
+    return result
+
+
+def row_to_calc_dict(row: Any | None) -> dict[str, float]:
+    if row is None:
+        return {}
+    result: dict[str, float] = {}
+    for col, keys in NUTRIENT_FIELD_SPECS:
+        val = getattr(row, col, None)
+        if val is None:
+            continue
+        n = _parse_num(val)
+        if n is None:
+            continue
+        for key in keys:
+            result[key] = n
+    return result
+
+
+def row_to_api_dict(row: Any | None) -> dict[str, float]:
+    """API nutrients — канонические ключи tab."""
+    if row is None:
+        return {}
+    out: dict[str, float] = {}
+    for col, keys in NUTRIENT_FIELD_SPECS:
+        val = getattr(row, col, None)
+        n = _parse_num(val)
+        if n is not None:
+            out[keys[0]] = n
+    return out
+
+
+def row_is_empty(row: Any | None) -> bool:
+    if row is None:
+        return True
+    for col, _keys in NUTRIENT_FIELD_SPECS:
+        if _parse_num(getattr(row, col, None)) is not None:
+            return False
+    return True
+
+
+def legacy_json_to_column_values(raw: str | None) -> dict[str, float | None]:
+    if not raw or not str(raw).strip() or str(raw).strip() == "{}":
+        return {col: None for col, _ in NUTRIENT_FIELD_SPECS}
+    import json
+
+    try:
+        data = json.loads(raw)
+    except (json.JSONDecodeError, TypeError):
+        data = {}
+    if not isinstance(data, dict):
+        data = {}
+    return api_dict_to_column_values(data)