mitai-jinkendo/backend/data_layer/nutrition_items.py

"""Nutrition diary items, three macro sums, import policy, attribute resolve."""
from __future__ import annotations

import uuid
from datetime import date, datetime
from typing import Any

from data_layer.food_mapping import (
    get_food_mapping_with_cursor,
    normalize_food_name,
    parse_quantity_g,
)

MACRO_ATTR_KEYS = {
    "kcal": "ENERCC",
    "protein_g": "PROT625",
    "fat_g": "FAT",
    "carbs_g": "CHO",
}

POLICIES = frozenset({"prompt", "overwrite_catalog", "overwrite_fddb", "keep_existing"})


def _f(v: Any) -> float:
    if v is None or v == "":
        return 0.0
    try:
        return float(v)
    except (TypeError, ValueError):
        return 0.0


def _round_macros(d: dict[str, float]) -> dict[str, float]:
    return {
        "kcal": round(_f(d.get("kcal")), 1),
        "protein_g": round(_f(d.get("protein_g")), 1),
        "fat_g": round(_f(d.get("fat_g")), 1),
        "carbs_g": round(_f(d.get("carbs_g")), 1),
    }


def macros_differ(a: dict[str, float], b: dict[str, float]) -> bool:
    aa, bb = _round_macros(a), _round_macros(b)
    return any(aa[k] != bb[k] for k in aa)


def get_import_policy(cur, profile_id: str) -> str:
    cur.execute(
        "SELECT nutrition_import_conflict_policy FROM profiles WHERE id = %s",
        (profile_id,),
    )
    row = cur.fetchone()
    if not row:
        return "prompt"
    pol = row.get("nutrition_import_conflict_policy") or "prompt"
    return pol if pol in POLICIES else "prompt"


def catalog_macros_for_item(cur, food_id: str | None, quantity_g: float | None) -> dict[str, float] | None:
    if not food_id or quantity_g is None or quantity_g <= 0:
        return None
    cur.execute(
        """
        SELECT a.attr_key, v.value_num, v.is_trace
        FROM food_attribute_values v
        JOIN food_attributes a ON a.id = v.attribute_id
        WHERE v.food_id = %s AND a.attr_key = ANY(%s) AND a.data_type = 'num_per_100g'
        """,
        (food_id, list(MACRO_ATTR_KEYS.values())),
    )
    by_key = {r["attr_key"]: r for r in cur.fetchall()}
    if not by_key:
        return None
    out = {}
    factor = float(quantity_g) / 100.0
    missing = False
    for field, key in MACRO_ATTR_KEYS.items():
        row = by_key.get(key)
        if not row or row.get("is_trace") or row.get("value_num") is None:
            missing = True
            break
        out[field] = float(row["value_num"]) * factor
    return None if missing else out


def compute_day_macro_sums(cur, profile_id: str, day: date | str) -> dict[str, Any]:
    cur.execute(
        """
        SELECT kcal, protein_g, fat_g, carbs_g, macro_origin, has_items
        FROM nutrition_log WHERE profile_id = %s AND date = %s
        """,
        (profile_id, day),
    )
    existing = cur.fetchone()
    existing_macros = (
        _round_macros(existing)
        if existing
        else None
    )
    cur.execute(
        """
        SELECT food_id, quantity_g, fddb_kcal, fddb_protein_g, fddb_fat_g, fddb_carbs_g, value_origin
        FROM nutrition_items
        WHERE profile_id = %s AND date = %s
        """,
        (profile_id, day),
    )
    items = cur.fetchall()
    fddb = {"kcal": 0.0, "protein_g": 0.0, "fat_g": 0.0, "carbs_g": 0.0}
    catalog = {"kcal": 0.0, "protein_g": 0.0, "fat_g": 0.0, "carbs_g": 0.0}
    mapped = unmapped = 0
    used_bls = used_fddb = False
    for it in items:
        fddb["kcal"] += _f(it.get("fddb_kcal"))
        fddb["protein_g"] += _f(it.get("fddb_protein_g"))
        fddb["fat_g"] += _f(it.get("fddb_fat_g"))
        fddb["carbs_g"] += _f(it.get("fddb_carbs_g"))
        cat = catalog_macros_for_item(cur, it.get("food_id"), it.get("quantity_g"))
        if cat:
            mapped += 1
            used_bls = True
            for k in catalog:
                catalog[k] += cat[k]
        else:
            unmapped += 1
            used_fddb = True
            catalog["kcal"] += _f(it.get("fddb_kcal"))
            catalog["protein_g"] += _f(it.get("fddb_protein_g"))
            catalog["fat_g"] += _f(it.get("fddb_fat_g"))
            catalog["carbs_g"] += _f(it.get("fddb_carbs_g"))
    origin = "mixed"
    if used_bls and not used_fddb:
        origin = "bls"
    elif used_fddb and not used_bls:
        origin = "fddb"
    if not items:
        origin = "manual"
    return {
        "existing": existing_macros,
        "fddb": _round_macros(fddb) if items else None,
        "catalog": _round_macros(catalog) if items else None,
        "mapped_item_count": mapped,
        "unmapped_item_count": unmapped,
        "has_items": bool(items),
        "catalog_origin": origin,
        "has_log": existing is not None,
        "macro_origin": existing["macro_origin"] if existing else None,
    }


def apply_nutrition_day_macros(
    cur,
    profile_id: str,
    day: date | str,
    macros: dict[str, float],
    *,
    macro_origin: str,
    source: str = "csv",
    confirm: bool = False,
) -> str:
    m = _round_macros(macros)
    cur.execute("SELECT id FROM nutrition_log WHERE profile_id = %s AND date = %s", (profile_id, day))
    row = cur.fetchone()
    counts = compute_day_macro_sums(cur, profile_id, day)
    extra = (
        counts["mapped_item_count"],
        counts["unmapped_item_count"],
        counts["has_items"],
    )
    confirmed = datetime.utcnow() if confirm else None
    if row:
        cur.execute(
            """
            UPDATE nutrition_log
            SET kcal=%s, protein_g=%s, fat_g=%s, carbs_g=%s, source=%s,
                macro_origin=%s, mapped_item_count=%s, unmapped_item_count=%s,
                has_items=%s, last_import_at=NOW(), macros_confirmed_at=COALESCE(%s, macros_confirmed_at)
            WHERE profile_id=%s AND date=%s
            """,
            (
                m["kcal"], m["protein_g"], m["fat_g"], m["carbs_g"], source,
                macro_origin, extra[0], extra[1], extra[2], confirmed, profile_id, day,
            ),
        )
        return "updated"
    eid = str(uuid.uuid4())
    cur.execute(
        """
        INSERT INTO nutrition_log (
            id, profile_id, date, kcal, protein_g, fat_g, carbs_g, source,
            macro_origin, mapped_item_count, unmapped_item_count, has_items,
            last_import_at, macros_confirmed_at, created
        ) VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,NOW(),%s,CURRENT_TIMESTAMP)
        """,
        (
            eid, profile_id, day, m["kcal"], m["protein_g"], m["fat_g"], m["carbs_g"], source,
            macro_origin, extra[0], extra[1], extra[2], confirmed,
        ),
    )
    return "created"


def rebuild_daily_nutrients(cur, profile_id: str, day: date | str) -> None:
    cur.execute(
        "DELETE FROM nutrition_daily_nutrients WHERE profile_id = %s AND date = %s",
        (profile_id, day),
    )
    cur.execute(
        """
        SELECT i.food_id, i.quantity_g
        FROM nutrition_items i
        WHERE i.profile_id = %s AND i.date = %s
          AND i.food_id IS NOT NULL AND i.quantity_g IS NOT NULL AND i.quantity_g > 0
        """,
        (profile_id, day),
    )
    acc: dict[int, list[float]] = {}
    for it in cur.fetchall():
        cur.execute(
            """
            SELECT v.attribute_id, v.value_num, v.is_trace, a.data_type
            FROM food_attribute_values v
            JOIN food_attributes a ON a.id = v.attribute_id
            WHERE v.food_id = %s AND a.data_type = 'num_per_100g'
              AND v.value_num IS NOT NULL AND v.is_trace = false
            """,
            (it["food_id"],),
        )
        factor = float(it["quantity_g"]) / 100.0
        for row in cur.fetchall():
            acc.setdefault(row["attribute_id"], []).append(float(row["value_num"]) * factor)
    for attr_id, vals in acc.items():
        cur.execute(
            """
            INSERT INTO nutrition_daily_nutrients
                (profile_id, date, attribute_id, value, contributing_item_count, updated_at)
            VALUES (%s, %s, %s, %s, %s, NOW())
            """,
            (profile_id, day, attr_id, round(sum(vals), 6), len(vals)),
        )


def _item_value_origin(mapping: dict | None) -> str:
    if not mapping:
        return "fddb"
    kind = mapping.get("catalog_kind")
    if kind == "official_bls":
        return "bls"
    if kind in ("manual_admin", "manual_user"):
        return "manual_catalog"
    return "fddb"


def replace_csv_items_for_dates(
    cur,
    profile_id: str,
    rows: list[dict[str, Any]],
    *,
    policy: str,
    policy_override: str | None = None,
) -> dict[str, Any]:
    """
    Replace csv-sourced items for the dates present in rows.
    Returns conflicts when policy is prompt and existing macros differ.
    """
    effective = policy_override if policy_override in POLICIES else policy
    by_date: dict[str, list[dict]] = {}
    for row in rows:
        d = row.get("date")
        if hasattr(d, "isoformat"):
            iso = d.isoformat()
        else:
            iso = str(d)[:10]
        if not iso:
            continue
        by_date.setdefault(iso, []).append(row)

    conflicts = []
    days_written = 0
    items_written = 0
    new_log_days = 0

    for iso, day_rows in by_date.items():
        cur.execute(
            """
            DELETE FROM nutrition_items
            WHERE profile_id = %s AND date = %s AND source = 'csv'
            """,
            (profile_id, iso),
        )
        for raw in day_rows:
            name = (raw.get("food_name") or raw.get("source_name_raw") or "").strip()
            if not name:
                continue
            qty_raw = raw.get("quantity_raw")
            qty_g = parse_quantity_g(qty_raw if qty_raw is not None else name)
            mapping = get_food_mapping_with_cursor(cur, name, profile_id)
            logged_at = raw.get("logged_at")
            cur.execute(
                """
                INSERT INTO nutrition_items (
                    id, profile_id, date, logged_at, source_name_raw, source_name_normalized,
                    source_system, quantity_raw, quantity_g,
                    fddb_kcal, fddb_protein_g, fddb_fat_g, fddb_carbs_g,
                    food_id, mapping_id, value_origin, source
                ) VALUES (
                    %s,%s,%s,%s,%s,%s,'fddb',%s,%s,%s,%s,%s,%s,%s,%s,%s,'csv'
                )
                """,
                (
                    str(uuid.uuid4()),
                    profile_id,
                    iso,
                    logged_at,
                    name,
                    normalize_food_name(name),
                    str(qty_raw) if qty_raw is not None else None,
                    qty_g,
                    _f(raw.get("fddb_kcal") if raw.get("fddb_kcal") is not None else raw.get("kcal")),
                    _f(raw.get("fddb_protein_g") if raw.get("fddb_protein_g") is not None else raw.get("protein_g")),
                    _f(raw.get("fddb_fat_g") if raw.get("fddb_fat_g") is not None else raw.get("fat_g")),
                    _f(raw.get("fddb_carbs_g") if raw.get("fddb_carbs_g") is not None else raw.get("carbs_g")),
                    mapping["food_id"] if mapping else None,
                    mapping["mapping_id"] if mapping else None,
                    _item_value_origin(mapping),
                ),
            )
            items_written += 1
        days_written += 1
        sums = compute_day_macro_sums(cur, profile_id, iso)
        rebuild_daily_nutrients(cur, profile_id, iso)
        if not sums["has_items"]:
            continue
        if not sums["has_log"]:
            apply_nutrition_day_macros(
                cur, profile_id, iso, sums["catalog"],
                macro_origin=sums["catalog_origin"], source="csv",
            )
            new_log_days += 1
            continue
        existing = sums["existing"]
        catalog = sums["catalog"]
        fddb = sums["fddb"]
        differ = macros_differ(existing, catalog) or macros_differ(existing, fddb)
        if effective == "keep_existing":
            _touch_item_counts(cur, profile_id, iso, sums)
            continue
        if effective == "overwrite_catalog":
            apply_nutrition_day_macros(
                cur, profile_id, iso, catalog,
                macro_origin=sums["catalog_origin"], source="csv",
            )
            continue
        if effective == "overwrite_fddb":
            apply_nutrition_day_macros(
                cur, profile_id, iso, fddb, macro_origin="fddb", source="csv",
            )
            continue
        # prompt
        if differ:
            conflicts.append({
                "date": iso,
                "existing": existing,
                "fddb": fddb,
                "catalog": catalog,
                "catalog_origin": sums["catalog_origin"],
                "mapped_item_count": sums["mapped_item_count"],
                "unmapped_item_count": sums["unmapped_item_count"],
            })
        else:
            apply_nutrition_day_macros(
                cur, profile_id, iso, catalog,
                macro_origin=sums["catalog_origin"], source="csv",
            )

    return {
        "days_written": days_written,
        "items_written": items_written,
        "new_log_days": new_log_days,
        "conflicts": conflicts,
        "policy": effective,
    }


def _touch_item_counts(cur, profile_id: str, day: str, sums: dict) -> None:
    cur.execute(
        """
        UPDATE nutrition_log
        SET mapped_item_count=%s, unmapped_item_count=%s, has_items=%s, last_import_at=NOW()
        WHERE profile_id=%s AND date=%s
        """,
        (
            sums["mapped_item_count"],
            sums["unmapped_item_count"],
            sums["has_items"],
            profile_id,
            day,
        ),
    )


def resolve_choice_macros(sums: dict[str, Any], choice: str) -> tuple[dict[str, float], str]:
    if choice == "existing":
        return sums["existing"], "user_confirmed"
    if choice == "fddb":
        return sums["fddb"], "fddb"
    if choice == "catalog":
        return sums["catalog"], sums.get("catalog_origin") or "mixed"
    raise ValueError("Ungültige Wahl (existing|fddb|catalog)")


def resolve_food_attributes(cur, food_id: str) -> list[dict]:
    cur.execute(
        """
        SELECT a.attr_key, a.name_de, a.unit, a.category, a.data_type, a.origin AS attr_origin,
               v.value_num, v.value_bool, v.value_text, v.is_trace, v.origin_code
        FROM food_attributes a
        LEFT JOIN food_attribute_values v
            ON v.attribute_id = a.id AND v.food_id = %s
        WHERE a.is_active = true
        ORDER BY a.sort_order, a.attr_key
        """,
        (food_id,),
    )
    return [dict(r) for r in cur.fetchall()]


def dates_for_normalized_name(cur, profile_id: str, source_name_normalized: str) -> list[str]:
    cur.execute(
        """
        SELECT DISTINCT date::text AS date
        FROM nutrition_items
        WHERE profile_id = %s AND source_name_normalized = %s
        """,
        (profile_id, source_name_normalized),
    )
    return [r["date"] for r in cur.fetchall()]