Интегрирован wesp в сайт

WESP_REL/app/lab/loaders/ration_loader.py

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+from __future__ import annotations
+
+from app.lab.calc.nutrients import norm_diff
+from app.lab.indicators import label_to_indicator_key
+from app.lab.dto.ration import RationLineSnapshot, RationSnapshot
+from app.lab.models import LabAnimalProfile, LabRationLine, LabRecipeRation
+from app.lab.services.component_nutrients import nutrients_calc_dict
+from app.lab.services.profile_norms import resolve_norms_for_profile
+from app.lab.services.ration_calc_store import (
+    load_compound_results,
+    load_params,
+    load_ration_results,
+)
+from app.models import Component, Recipe
+
+
+def _refresh_indicator_norms(
+    indicators: list[dict],
+    norms: dict[str, dict[str, float | None]],
+) -> list[dict]:
+    """min/max/diff в сохранённом расчёте — по текущему профилю норм."""
+    if not indicators or not norms:
+        return indicators
+    out: list[dict] = []
+    for row in indicators:
+        item = dict(row)
+        key = item.get("key") or label_to_indicator_key(str(item.get("label") or ""))
+        if key and key in norms:
+            bounds = norms[key]
+            min_v = bounds.get("min")
+            max_v = bounds.get("max")
+            item["min"] = min_v
+            item["max"] = max_v
+            item["diff"] = norm_diff(item.get("content"), min_v, max_v)
+        out.append(item)
+    return out
+
+
+def load_ration(recipe_id: str) -> RationSnapshot:
+    recipe = Recipe.query.filter_by(id=recipe_id, is_deleted=False).first()
+    if recipe is None:
+        raise LookupError("Рецепт не найден")
+    header = LabRecipeRation.query.filter_by(recipe_id=recipe_id, is_deleted=False).first()
+    ration_type = recipe.ration_type or "BEEF"
+    norms: dict = {}
+    params: dict = {}
+    ration_results: dict = {}
+    compound_results: dict = {}
+    calculated_at = None
+    animal_profile_id = None
+    norms_profile_key = None
+    if header:
+        animal_profile_id = header.animal_profile_id
+        params = load_params(recipe_id, header)
+        ration_results = load_ration_results(recipe_id, header)
+        compound_results = load_compound_results(recipe_id)
+        calculated_at = header.calculated_at.isoformat() if header.calculated_at else None
+        if header.animal_profile_id:
+            profile = LabAnimalProfile.query.filter_by(
+                id=header.animal_profile_id, is_deleted=False
+            ).first()
+            if profile:
+                norms_profile_key = profile.profile_key
+                norms = resolve_norms_for_profile(profile)
+    if ration_results.get("indicators") and norms:
+        ration_results = {
+            **ration_results,
+            "indicators": _refresh_indicator_norms(ration_results["indicators"], norms),
+        }
+    lines_q = (
+        LabRationLine.query.filter_by(recipe_id=recipe_id, is_deleted=False)
+        .order_by(LabRationLine.row_index)
+        .all()
+    )
+    line_snaps = []
+    for line in lines_q:
+        comp = Component.query.get(line.component_id) if line.component_id else None
+        nutrients = nutrients_calc_dict(line.component_id) if line.component_id else {}
+        dry_matter_pct = comp.dry_matter if comp else None
+        line_snaps.append(
+            RationLineSnapshot(
+                id=line.id,
+                component_id=line.component_id,
+                ingredient_name=line.ingredient_name or (comp.name if comp else None),
+                row_index=line.row_index,
+                daily_kg=line.daily_kg,
+                in_ration=bool(line.in_ration),
+                in_compound=bool(line.in_compound),
+                dry_matter=dry_matter_pct,
+                price_per_kg=comp.price if comp else None,
+                nutrients=nutrients,
+            )
+        )
+    return RationSnapshot(
+        recipe_id=recipe_id,
+        recipe_name=recipe.name,
+        ration_type=ration_type,
+        heads_per_trip=int(recipe.heads_per_trip or 1),
+        animal_profile_id=animal_profile_id,
+        params=params,
+        lines=tuple(line_snaps),
+        norms=norms,
+        ration_results=ration_results,
+        compound_results=compound_results,
+        calculated_at=calculated_at,
+        exists=header is not None,
+        norms_profile_key=norms_profile_key,
+        legacy_norms_remapped=False,
+    )
+
+
+def ration_to_calc_lines(snapshot: RationSnapshot) -> list[dict]:
+    return [
+        {
+            "daily_kg": line.daily_kg,
+            "in_ration": line.in_ration,
+            "in_compound": line.in_compound,
+            "ingredient_name": line.ingredient_name,
+            "price_per_kg": line.price_per_kg,
+            "dry_matter": line.dry_matter,
+            "nutrients": line.nutrients,
+            "component_id": line.component_id,
+        }
+        for line in snapshot.lines
+    ]