site/apps/api/app/modules/zootech/lab/nutrient_schema.py

"""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.modules.zootech.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)