mitai-jinkendo/backend/data_layer/fitness_interpretation.py

"""
KPI-Kacheln für Layer-2b Fitness-Dashboard (Issue #53).

Ausgabe für KpiTilesOverview; ``keys`` = Platzhalter-Registry-Referenzen.
"""

from __future__ import annotations

from typing import Any, Dict, List, Optional


def _verdict(status: str) -> str:
    if status == "good":
        return "Gut"
    if status == "warn":
        return "Hinweis"
    return "Achtung"


def _minutes_status(minutes: Optional[int]) -> str:
    if minutes is None:
        return "warn"
    if 150 <= minutes <= 300:
        return "good"
    if minutes < 150:
        return "warn" if minutes >= 90 else "bad"
    return "warn"


def _quality_status(pct: Optional[int]) -> str:
    if pct is None:
        return "warn"
    if pct >= 60:
        return "good"
    if pct >= 40:
        return "warn"
    return "bad"


def _score_status(score: Optional[int]) -> str:
    if score is None:
        return "warn"
    if score >= 70:
        return "good"
    if score >= 50:
        return "warn"
    return "bad"


def _vo2_status(trend: Optional[float]) -> str:
    if trend is None:
        return "warn"
    if trend > 0.5:
        return "good"
    if trend >= -0.5:
        return "warn"
    return "bad"


def build_fitness_dashboard_kpi_tiles(
    summary: Dict[str, Any],
    minutes_7d: Optional[int],
    quality_pct: Optional[int],
    quality_window_days: int,
    activity_score: Optional[int],
    vo2_trend: Optional[float],
    top_focus: Optional[Dict[str, Any]],
) -> List[Dict[str, Any]]:
    spw = summary.get("sessions_per_week")
    try:
        spw_f = float(spw) if spw is not None else None
    except (TypeError, ValueError):
        spw_f = None
    spw_s = f"{spw_f:.1f}".replace(".", ",") if spw_f is not None else "—"

    m_status = _minutes_status(minutes_7d)
    q_status = _quality_status(quality_pct)
    s_status = _score_status(activity_score)
    v_status = _vo2_status(vo2_trend)

    tiles: List[Dict[str, Any]] = [
        {
            "key": "minutes_week",
            "category": "Minuten (7 Tage)",
            "icon": "⏱",
            "value": f"{minutes_7d} min" if minutes_7d is not None else "—",
            "sublabel": "WHO: 150–300 min/Woche",
            "status": m_status,
            "verdict": _verdict(m_status),
            "hoverTop": "Summe Trainingsminuten (letzte 7 Tage)",
            "hoverBody": "Gleiche Quelle wie Platzhalter training_minutes_week.",
            "keys": ["training_minutes_week", "activity_score"],
        },
        {
            "key": "sessions_per_week",
            "category": "Sessions / Woche",
            "icon": "📅",
            "value": spw_s,
            "sublabel": f"Fenster: {summary.get('days_analyzed', '—')} Tage",
            "status": "good",
            "verdict": "Gut",
            "hoverTop": "Durchschnittliche Sessions pro Woche",
            "hoverBody": "Aus activity_summary (activity_log im gewählten Zeitraum).",
            "keys": ["activity_summary"],
        },
        {
            "key": "quality_pct",
            "category": "Qualitätssessions",
            "icon": "✓",
            "value": f"{quality_pct} %" if quality_pct is not None else "—",
            "sublabel": f"Anteil «gut+» · {quality_window_days} Tage",
            "status": q_status,
            "verdict": _verdict(q_status),
            "hoverTop": "Anteil Sessions mit guter Qualitätslabel-Klassifikation",
            "hoverBody": "Entspricht quality_sessions_pct (Fenster wie gewählt).",
            "keys": ["quality_sessions_pct"],
        },
        {
            "key": "activity_score",
            "category": "Activity-Score",
            "icon": "🎯",
            "value": str(activity_score) if activity_score is not None else "—",
            "sublabel": "Ausrichtung an gewichteten Fokusbereichen",
            "status": s_status,
            "verdict": _verdict(s_status) if activity_score is not None else "Hinweis",
            "hoverTop": "Gewichteter Score (0–100)",
            "hoverBody": "Ohne gewichtete Aktivitäts-Fokusbereiche kein Score.",
            "keys": ["activity_score"],
        },
        {
            "key": "vo2_trend",
            "category": "VO₂max-Trend",
            "icon": "🫁",
            "value": f"{vo2_trend:+.1f}" if vo2_trend is not None else "—",
            "sublabel": "28-Tage-Trend (geschätzt)",
            "status": v_status,
            "verdict": _verdict(v_status) if vo2_trend is not None else "Hinweis",
            "hoverTop": "Trend der VO₂max-Schätzung aus Aktivitätsdaten",
            "hoverBody": "Wie vo2max_trend_28d im Data Layer.",
            "keys": ["vo2max_trend_28d"],
        },
    ]

    if top_focus:
        prog = top_focus.get("progress")
        prog_s = f"{prog} %" if prog is not None else "—"
        w = top_focus.get("weight")
        try:
            w_s = f"{float(w):.0f} %" if w is not None else "—"
        except (TypeError, ValueError):
            w_s = "—"
        tiles.append(
            {
                "key": "top_focus",
                "category": "Schwerpunkt-Fokus",
                "icon": "🔭",
                "value": str(top_focus.get("label") or "—"),
                "sublabel": f"Fortschritt {prog_s} · Gewicht {w_s}",
                "status": "good",
                "verdict": "Gut",
                "hoverTop": "Höchstgewichteter Fokusbereich",
                "hoverBody": "Aus focus_area_definitions + Nutzer-Gewichtungen.",
                "keys": ["top_focus_area_name", "top_focus_area_progress"],
            }
        )

    return tiles