mitai-jinkendo/backend/csv_parser/module_registry.py

"""
Ziel-Module für CSV-Import: Tabellen-Felder, Pflichtfelder, Duplikat-Strategie (Issue #21).

Hinweis: blood_pressure nutzt in der DB measured_at; Logik-Felder measured_date + measured_time
werden im Executor zu measured_at zusammengefügt (Phase Import-Executor).

Activity: date kann aus start_time (ISO-Datetime) abgeleitet werden, wenn nur start_time gesetzt ist.
"""

from __future__ import annotations

from typing import Any, Dict, cast

MODULE_DEFINITIONS: Dict[str, Dict[str, Any]] = {
    "nutrition": {
        "table": "nutrition_log",
        "fields": {
            "date": {"type": "date", "required": True},
            "kcal": {"type": "float", "required": False, "unit": "kcal"},
            "protein_g": {"type": "float", "required": False, "min": 0, "unit": "g"},
            "fat_g": {"type": "float", "required": False, "min": 0, "unit": "g"},
            "carbs_g": {"type": "float", "required": False, "min": 0, "unit": "g"},
        },
        "duplicate_key": ["profile_id", "date"],
        "duplicate_strategy": "update",
        # Legacy-Fallback wenn die Vorlage kein import_row_processing speichert — Vorlagen mittelfristig explizit.
        "import_row_processing_default": {
            "group_by": ["date"],
            "aggregates": {
                "kcal": "sum",
                "protein_g": "sum",
                "fat_g": "sum",
                "carbs_g": "sum",
            },
        },
    },
    "activity": {
        "table": "activity_log",
        "fields": {
            "date": {"type": "date", "required": False, "label_de": "Datum"},
            "start_time": {
                "type": "datetime",
                "required": False,
                "label_de": "Start (Datum/Uhrzeit)",
            },
            "end_time": {"type": "datetime", "required": False, "label_de": "Ende (Datum/Uhrzeit)"},
            "activity_type": {"type": "string", "required": True, "label_de": "Trainingsart / Workout-Typ"},
            "duration_min": {"type": "float", "required": False, "min": 0, "label_de": "Dauer (Minuten)"},
            "kcal_active": {"type": "float", "required": False, "unit": "kcal", "label_de": "Kalorien aktiv"},
            "kcal_resting": {"type": "float", "required": False, "unit": "kcal", "label_de": "Kalorien Ruhe"},
            "distance_km": {"type": "float", "required": False, "unit": "km", "label_de": "Distanz (km)"},
            "hr_avg": {
                "type": "float",
                "required": False,
                "min": 30,
                "max": 220,
                "label_de": "Herzfrequenz Ø (bpm)",
            },
            "hr_max": {
                "type": "float",
                "required": False,
                "min": 30,
                "max": 220,
                "label_de": "Herzfrequenz max (bpm)",
            },
            "hr_min": {"type": "int", "required": False, "label_de": "Herzfrequenz min (bpm)"},
            "rpe": {"type": "int", "required": False, "label_de": "RPE (1–10)"},
            "pace_min_per_km": {"type": "float", "required": False, "label_de": "Tempo (min/km)"},
            "cadence": {"type": "int", "required": False, "label_de": "Kadenz"},
            "avg_power": {"type": "int", "required": False, "label_de": "Leistung Ø (W)"},
            "elevation_gain": {"type": "int", "required": False, "label_de": "Höhenmeter / Aufstieg"},
            "temperature_celsius": {"type": "float", "required": False, "label_de": "Temperatur (°C)"},
            "humidity_percent": {"type": "int", "required": False, "label_de": "Luftfeuchtigkeit (%)"},
            "avg_hr_percent": {"type": "float", "required": False, "label_de": "HF Ø (% von max)"},
            "kcal_per_km": {"type": "float", "required": False, "label_de": "Kalorien pro km"},
            "notes": {"type": "string", "required": False, "label_de": "Notiz"},
        },
        "derive_date_from_datetime_field": "start_time",
        "duplicate_key": ["profile_id", "date", "start_time"],
        "duplicate_strategy": "update",
    },
    "sleep": {
        "table": "sleep_log",
        "fields": {},
        "import_mode": "apple_sleep_aggregate",
    },
    "vitals_baseline": {
        "table": "vitals_baseline",
        "fields": {
            "date": {"type": "date", "required": True},
            "resting_hr": {"type": "int", "required": False},
            "hrv": {"type": "int", "required": False},
            "vo2_max": {"type": "float", "required": False},
            "spo2": {"type": "int", "required": False},
            "respiratory_rate": {"type": "float", "required": False},
        },
        "duplicate_key": ["profile_id", "date"],
        "duplicate_strategy": "update",
        # Legacy-Fallback — Vorlagen mittelfristig explizit setzen.
        "import_row_processing_default": {
            "group_by": ["date"],
            "aggregates": {
                "resting_hr": "mean",
                "hrv": "mean",
                "vo2_max": "mean",
                "spo2": "mean",
                "respiratory_rate": "mean",
            },
        },
    },
    "blood_pressure": {
        "table": "blood_pressure_log",
        "fields": {
            "measured_date": {"type": "date", "required": True},
            "measured_time": {"type": "time", "required": True},
            # Apple Health: eine Spalte „Start“ / „Datum/Uhrzeit“ (Datetime); Executor splittet.
            "start_time": {"type": "datetime", "required": False},
            "systolic": {"type": "int", "required": True},
            "diastolic": {"type": "int", "required": True},
            "pulse": {"type": "int", "required": False},
        },
        "logical_to_db": "blood_pressure_composite_measured_at",
        "duplicate_key": ["profile_id", "measured_at"],
        "duplicate_strategy": "update",
    },
    "weight": {
        "table": "weight_log",
        "fields": {
            "date": {"type": "date", "required": True},
            "weight": {"type": "float", "required": True, "min": 20, "max": 400, "unit": "kg"},
            "note": {"type": "string", "required": False, "max_length": 2000},
        },
        "duplicate_key": ["profile_id", "date"],
        "duplicate_strategy": "update",
        # Legacy-Fallback — Vorlagen mittelfristig explizit setzen.
        "import_row_processing_default": {
            "group_by": ["date"],
            "aggregates": {
                "weight": "last",
                "note": "last",
            },
        },
    },
}


def get_module_definition(module: str) -> Dict[str, Any] | None:
    return MODULE_DEFINITIONS.get(module)


def list_modules() -> list[str]:
    return sorted(MODULE_DEFINITIONS.keys())


def validate_field_mappings(module: str, field_mappings: dict, cur=None) -> None:
    """Wirft ValueError bei unbekanntem Modul oder unbekanntem DB-Feld."""
    mod = get_module_definition(module)
    if not mod:
        raise ValueError(f"Unbekanntes Modul: {module}")
    fields = cast(dict, mod["fields"])
    allowed = set(fields.keys())
    if module == "activity" and cur is not None:
        cur.execute("SELECT key FROM training_parameters WHERE is_active = true")
        allowed.update(str(r["key"]) for r in cur.fetchall())
    if not allowed:
        for _csv_col, db_field in field_mappings.items():
            if db_field not in ("", None, "-", "_skip"):
                raise ValueError(
                    f"Modul '{module}' nutzt einen Aggregat-Import ohne Spalten-Mapping; "
                    f"alle Spalten müssen „ignorieren“ sein."
                )
        return
    for _csv_col, db_field in field_mappings.items():
        if db_field in ("", None, "-", "_skip"):
            continue
        if db_field not in allowed:
            raise ValueError(f"Ungültiges Zielfeld '{db_field}' für Modul '{module}'")


def validate_required_field_targets(module: str, field_mappings: dict) -> None:
    """Stellt sicher, dass jedes als required markierte Zielfeld mindestens einer Spalte zugeordnet ist."""
    mod = get_module_definition(module)
    if not mod:
        raise ValueError(f"Unbekanntes Modul: {module}")
    field_defs = cast(dict, mod["fields"])
    targets = {v for v in field_mappings.values() if v and v not in ("-", "_skip")}
    if module == "blood_pressure" and "start_time" in targets:
        targets = set(targets) | {"measured_date", "measured_time"}
    for fname, finfo in field_defs.items():
        if finfo.get("required") and fname not in targets:
            raise ValueError(f"Pflicht-Zielfeld nicht zugeordnet: {fname}")