site/apps/api/app/modules/zootech/lab/calc/engine.py

from __future__ import annotations

from datetime import datetime, timezone
from typing import Any

from app.modules.zootech.lab.calc.compound import calculate_compound_feed
from app.modules.zootech.lab.calc.derived import apply_content_derived
from app.modules.zootech.lab.calc.nutrients import daily_intake_total, get_nutrient_value, norm_diff, weighted_average
from app.modules.zootech.lab.constants import RATION_TOTAL_KEYS
from app.modules.zootech.lab.indicators import RATION_ALL_INDICATORS


def _active_lines(lines: list[dict[str, Any]]) -> list[dict[str, Any]]:
    return [
        l
        for l in lines
        if l.get("in_ration") and (l.get("daily_kg") or 0) > 0
    ]


def _sum_kg(lines: list[dict[str, Any]]) -> float:
    return sum(float(l.get("daily_kg") or 0) for l in lines)


def _sum_cost(lines: list[dict[str, Any]]) -> float | None:
    total = 0.0
    any_cost = False
    for line in lines:
        kg = line.get("daily_kg")
        price = line.get("price_per_kg")
        if kg is None or price is None:
            continue
        total += float(kg) * float(price)
        any_cost = True
    return total if any_cost else None


def _sum_ration_percent(lines: list[dict[str, Any]], total_kg: float) -> float | None:
    if total_kg <= 0:
        return None
    return sum((float(l.get("daily_kg") or 0) / total_kg) * 100 for l in lines)


def _compute_totals(
    ration_type: str,
    active: list[dict[str, Any]],
    total_kg: float,
) -> list[dict[str, Any]]:
    defs = RATION_TOTAL_KEYS.get(ration_type, RATION_TOTAL_KEYS["BEEF"])
    ration_kg = _sum_kg(active)
    values = {
        "total_kg": total_kg if total_kg > 0 else None,
        "ration_kg": ration_kg if ration_kg > 0 else None,
        "ration_pct_sum": _sum_ration_percent(active, total_kg),
        "cost_total": _sum_cost(active),
    }
    return [{"key": d["key"], "label": d["label"], "value": values.get(d["key"])} for d in defs]


def _indicator_content(
    defn: dict[str, Any],
    active: list[dict[str, Any]],
    total_kg: float,
    *,
    heads_per_trip: int,
) -> float | None:
    key = defn.get("key")
    if defn.get("aggregation") == "weighted_avg":
        return weighted_average(
            active,
            total_kg,
            defn["nutrient_keys"],
            indicator_key=key,
        )
    return daily_intake_total(
        active,
        defn["nutrient_keys"],
        heads_per_trip=heads_per_trip,
        indicator_key=key,
    )


def _compute_indicators(
    active: list[dict[str, Any]],
    total_kg: float,
    norms: dict[str, dict[str, float | None]],
    *,
    heads_per_trip: int = 1,
    profile_mass_kg: float | None = None,
) -> list[dict[str, Any]]:
    content_by_key: dict[str, float | None] = {}
    for defn in RATION_ALL_INDICATORS:
        if defn.get("derived"):
            continue
        content_by_key[defn["key"]] = _indicator_content(
            defn, active, total_kg, heads_per_trip=heads_per_trip
        )

    for defn in RATION_ALL_INDICATORS:
        if not defn.get("derived"):
            continue
        content_by_key[defn["key"]] = apply_content_derived(
            content_by_key,
            defn,
            total_kg=total_kg,
            heads_per_trip=heads_per_trip,
            profile_mass_kg=profile_mass_kg,
        )

    rows = []
    for defn in RATION_ALL_INDICATORS:
        key = defn["key"]
        content = content_by_key.get(key)
        bounds = norms.get(key, {})
        min_v = bounds.get("min")
        max_v = bounds.get("max")
        diff = norm_diff(content, min_v, max_v)
        if content is None and min_v is None and max_v is None:
            continue
        rows.append(
            {
                "key": key,
                "label": defn["label"],
                "unit": defn["unit"],
                "min": min_v,
                "max": max_v,
                "content": content,
                "diff": diff,
            }
        )
    return rows


def _missing_nutrient_warnings(active: list[dict[str, Any]]) -> list[str]:
    warnings: list[str] = []
    for line in active:
        nutrients = line.get("nutrients") or {}
        cp = get_nutrient_value(
            line.get("dry_matter"),
            nutrients,
            ["Сыр. Протеин"],
            indicator_key="crude_protein",
        )
        if cp is not None:
            continue
        name = line.get("ingredient_name") or line.get("component_id") or "?"
        warnings.append(f"nutrients_missing:{name}")
    return warnings


def calculate_ration(
    ration_type: str,
    lines: list[dict[str, Any]],
    norms: dict[str, dict[str, float | None]] | None = None,
    *,
    heads_per_trip: int = 1,
    profile_mass_kg: float | None = None,
) -> dict[str, Any]:
    norms = norms or {}
    errors: list[str] = []
    active = _active_lines(lines)
    total_kg = _sum_kg(active)
    heads = max(int(heads_per_trip or 1), 1)
    if not active:
        errors.append("Нет строк сырья «в рационе» с дозировкой кг/день")
    warnings = _missing_nutrient_warnings(active)
    compound = calculate_compound_feed(
        lines, norms, profile_mass_kg=profile_mass_kg, heads_per_trip=heads
    )
    return {
        "calculated_at": datetime.now(timezone.utc).isoformat(),
        "engine": "native",
        "totals": _compute_totals(ration_type, active, total_kg),
        "indicators": _compute_indicators(
            active,
            total_kg,
            norms,
            heads_per_trip=heads,
            profile_mass_kg=profile_mass_kg,
        ),
        "compound": compound,
        "errors": errors,
        "warnings": warnings,
    }