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"""Роутер методик суточных норм: WESP / Москва / Петербург."""
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from __future__ import annotations
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from dataclasses import dataclass, field
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from typing import Any, Literal
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from app.lab.calc.gfe_norms import apply_dynamic_norms
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from app.lab.calc.racion.moscow import MoscowDairyParams, resolve_moscow_dairy_norms
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from app.lab.calc.racion.piter import PiterDairyParams, PiterPrepError, resolve_piter_dairy_norms
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from app.lab.indicators import RATION_ALL_INDICATORS
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NormsMethod = Literal["wesp", "racion_moscow", "racion_piter"]
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VALID_NORMS_METHODS: frozenset[str] = frozenset({"wesp", "racion_moscow", "racion_piter"})
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@dataclass
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class NormsParams:
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milk_fat_pct: float | None = None
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lactation_no: int | None = None
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lactation_stage: int | None = None
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body_condition: int | None = None
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housing_system: int | None = None
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konc_oe_sv: float | None = None
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@classmethod
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def from_dict(cls, raw: dict[str, Any] | None) -> NormsParams:
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if not raw:
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return cls()
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return cls(
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milk_fat_pct=_flt(raw.get("milkFatPct", raw.get("milk_fat_pct"))),
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lactation_no=_int(raw.get("lactationNo", raw.get("lactation_no"))),
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lactation_stage=_int(raw.get("lactationStage", raw.get("lactation_stage"))),
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body_condition=_int(raw.get("bodyCondition", raw.get("body_condition"))),
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housing_system=_int(raw.get("housingSystem", raw.get("housing_system"))),
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konc_oe_sv=_flt(raw.get("koncOeSv", raw.get("konc_oe_sv"))),
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)
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def _flt(v: Any) -> float | None:
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if v is None or v == "":
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return None
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try:
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return float(v)
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except (TypeError, ValueError):
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return None
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def _int(v: Any) -> int | None:
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if v is None or v == "":
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return None
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try:
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return int(v)
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except (TypeError, ValueError):
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return None
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def normalize_norms_method(method: str | None) -> NormsMethod:
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m = (method or "wesp").strip().lower()
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if m not in VALID_NORMS_METHODS:
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return "wesp"
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return m # type: ignore[return-value]
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@dataclass
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class NormsResolveRequest:
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method: NormsMethod = "wesp"
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stored: dict[str, dict[str, float | None]] = field(default_factory=dict)
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mass_kg: float | None = None
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milk_yield_kg: float | None = None
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ration_type: str | None = None
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force_dynamic: bool = False
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params: NormsParams = field(default_factory=NormsParams)
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def merge_hybrid_norms(
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racion_resolved: dict[str, dict[str, float | None]],
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stored: dict[str, dict[str, float | None]],
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*,
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dynamic_meta: dict[str, Any] | None = None,
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) -> tuple[dict[str, dict[str, float | None]], dict[str, Any]]:
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"""
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RACION + derived имеют приоритет по min.
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stored дополняет ключи без RACION-min; max всегда из stored, если задан.
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"""
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out: dict[str, dict[str, float | None]] = {}
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coverage: dict[str, list[str]] = {
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"racion": [],
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"derived": [],
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"fallback": [],
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"missing": [],
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}
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dynamic = dynamic_meta or {}
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all_keys = {d["key"] for d in RATION_ALL_INDICATORS}
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all_keys.update(racion_resolved.keys())
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all_keys.update(stored.keys())
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for key in sorted(all_keys):
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rac = racion_resolved.get(key) or {}
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st = stored.get(key) or {}
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rac_min = rac.get("min")
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st_min = st.get("min")
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st_max = st.get("max")
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source: str | None = None
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min_v: float | None = None
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if rac_min is not None:
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min_v = rac_min
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src = (dynamic.get(key) or {}).get("source")
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source = "derived" if src == "derived" else "racion"
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elif st_min is not None:
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min_v = st_min
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source = "fallback"
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max_v = st_max if st_max is not None else rac.get("max")
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if min_v is not None or max_v is not None:
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out[key] = {"min": min_v, "max": max_v}
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if source == "racion":
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coverage["racion"].append(key)
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elif source == "derived":
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coverage["derived"].append(key)
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elif source == "fallback":
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coverage["fallback"].append(key)
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elif key in {d["key"] for d in RATION_ALL_INDICATORS}:
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coverage["missing"].append(key)
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coverage["withMin"] = len([k for k, b in out.items() if b.get("min") is not None])
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coverage["total"] = len(RATION_ALL_INDICATORS)
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return out, coverage
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def _require_dairy_params(req: NormsResolveRequest) -> tuple[float, float]:
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if req.mass_kg is None or req.mass_kg <= 0:
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raise ValueError("Для методики Москва/Петербург укажите живую массу, кг")
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if req.milk_yield_kg is None or req.milk_yield_kg <= 0:
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raise ValueError("Для методики Москва/Петербург укажите суточный удой, кг")
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return float(req.mass_kg), float(req.milk_yield_kg)
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def _moscow_params(req: NormsResolveRequest) -> MoscowDairyParams:
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mass, milk = _require_dairy_params(req)
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p = req.params
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return MoscowDairyParams(
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mass_kg=mass,
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milk_yield_kg=milk,
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milk_fat_pct=p.milk_fat_pct if p.milk_fat_pct is not None else 4.0,
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lactation_no=p.lactation_no if p.lactation_no is not None else 2,
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body_condition=p.body_condition if p.body_condition is not None else 1,
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housing_system=p.housing_system if p.housing_system is not None else 1,
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)
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def _piter_params(req: NormsResolveRequest) -> PiterDairyParams:
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mass, milk = _require_dairy_params(req)
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p = req.params
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konc = p.konc_oe_sv
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if konc is None or konc <= 0:
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raise ValueError("Для методики Петербург укажите концентрацию ОЭ/СВ, МДж/кг СВ")
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return PiterDairyParams(
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mass_kg=mass,
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milk_yield_kg=milk,
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milk_fat_pct=p.milk_fat_pct if p.milk_fat_pct is not None else 4.0,
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lactation_no=p.lactation_no if p.lactation_no is not None else 2,
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body_condition=p.body_condition if p.body_condition is not None else 1,
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housing_system=p.housing_system if p.housing_system is not None else 1,
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konc_oe_sv=float(konc),
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)
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def resolve_norms(req: NormsResolveRequest) -> tuple[dict[str, dict[str, float | None]], dict[str, Any]]:
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method = normalize_norms_method(req.method)
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if method == "wesp":
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resolved, dynamic = apply_dynamic_norms(
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req.stored,
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mass_kg=req.mass_kg,
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milk_yield_kg=req.milk_yield_kg,
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ration_type=req.ration_type,
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force_dynamic=req.force_dynamic,
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)
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return resolved, {"normsMethod": "wesp", "dynamicNorms": dynamic}
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try:
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if method == "racion_moscow":
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racion, pack = resolve_moscow_dairy_norms(_moscow_params(req))
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else:
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racion, pack = resolve_piter_dairy_norms(_piter_params(req))
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except PiterPrepError as exc:
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raise ValueError(str(exc)) from exc
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resolved, coverage = merge_hybrid_norms(racion, req.stored, dynamic_meta=pack.get("dynamic"))
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return resolved, {"normsMethod": method, "coverage": coverage, **pack}
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