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

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+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,
+    }