mitai-jinkendo/backend/data_layer/fitness_viz.py

"""
Layer 2b: Fitness-Hub — ein Bundle für die Aktivitäts-/Fitness-UI (Issue #53).

Single Source: activity_metrics + dieselben Hilfsfunktionen wie Chart-Endpunkte A1/A2.
"""

from __future__ import annotations

from typing import Any, Dict, Optional

from db import get_db, get_cursor
from data_layer.activity_metrics import (
    build_load_monitoring_chart_payload,
    build_quality_sessions_chart_payload,
    build_training_type_distribution_chart_payload,
    build_training_volume_chart_payload,
    calculate_activity_score,
    calculate_training_minutes_week,
    calculate_quality_sessions_pct,
    calculate_vo2max_trend_28d,
    get_activity_summary_data,
    get_training_volume_two_week_delta,
)
from data_layer.fitness_interpretation import (
    build_fitness_dashboard_kpi_tiles,
    build_fitness_progress_insights,
)
from data_layer.scores import get_top_focus_area


def _iso(d: Any) -> Optional[str]:
    if d is None:
        return None
    if hasattr(d, "isoformat"):
        return d.isoformat()[:10]
    return str(d)[:10]


def _has_activity_entries(profile_id: str) -> bool:
    with get_db() as conn:
        cur = get_cursor(conn)
        cur.execute(
            "SELECT 1 FROM activity_log WHERE profile_id=%s LIMIT 1",
            (profile_id,),
        )
        return cur.fetchone() is not None


def _last_activity_date(profile_id: str) -> Optional[str]:
    with get_db() as conn:
        cur = get_cursor(conn)
        cur.execute(
            "SELECT MAX(date) AS d FROM activity_log WHERE profile_id=%s",
            (profile_id,),
        )
        row = cur.fetchone()
        if not row or row["d"] is None:
            return None
        return _iso(row["d"])


def get_activity_last_updated_iso(profile_id: str) -> Optional[str]:
    """
    Leichtgewicht: letztes activity_log.date — identisch zu ``last_updated`` im Fitness-Viz-Bundle.

    Für History-Header o. Ä. ohne vollständige Aktivitätsliste (Phase A, Issue-53-Pfad).
    """
    return _last_activity_date(profile_id)


def get_fitness_dashboard_viz_bundle(profile_id: str, days: int) -> Dict[str, Any]:
    """
    Bundle für Fitness-Übersicht: KPI-Kacheln + eingebettete Chart-Payloads (Chart.js-Format).

    ``days``: Analysefenster für Zusammenfassung; >=9999 = lange Historie (max. 3650 Tage).
    """
    if not _has_activity_entries(profile_id):
        return {
            "confidence": "insufficient",
            "has_activity_entries": False,
            "message": "Noch keine Aktivitätsdaten",
            "kpi_tiles": [],
            "summary": {},
            "progress_insights": [],
            "volume_delta": {},
            "charts": {},
            "meta": {"layer_1": "activity_metrics", "layer_2b": "fitness_viz"},
        }

    all_history = days >= 9999
    eff_days = 3650 if all_history else max(7, min(int(days), 3650))

    summary = get_activity_summary_data(profile_id, eff_days)

    weeks_vol = max(4, min(52, (min(eff_days, 365) + 6) // 7))
    dist_days = min(90, max(7, min(eff_days, 365)))
    load_days = min(90, max(14, min(eff_days, 365)))

    volume_chart = build_training_volume_chart_payload(profile_id, weeks_vol)
    type_chart = build_training_type_distribution_chart_payload(profile_id, dist_days)
    quality_chart = build_quality_sessions_chart_payload(profile_id, dist_days)
    load_chart = build_load_monitoring_chart_payload(profile_id, load_days)

    quality_days = dist_days
    quality_pct = calculate_quality_sessions_pct(profile_id, quality_days)
    minutes_7d = calculate_training_minutes_week(profile_id)
    activity_score = calculate_activity_score(profile_id)
    vo2_trend = calculate_vo2max_trend_28d(profile_id)
    top_focus = get_top_focus_area(profile_id)
    vol_delta = get_training_volume_two_week_delta(profile_id)

    kpi_tiles = build_fitness_dashboard_kpi_tiles(
        summary,
        minutes_7d,
        quality_pct,
        quality_days,
        activity_score,
        vo2_trend,
        top_focus,
        vol_delta,
    )

    load_meta = load_chart.get("metadata") or {}
    if not isinstance(load_meta, dict):
        load_meta = {}
    progress_insights = build_fitness_progress_insights(vol_delta, load_meta, quality_pct)

    conf = summary.get("confidence") or "medium"
    if summary.get("activity_count", 0) == 0:
        conf = "insufficient"

    return {
        "confidence": conf,
        "has_activity_entries": True,
        "days_requested": days,
        "effective_window_days": eff_days,
        "training_volume_weeks_used": weeks_vol,
        "training_type_dist_days_used": dist_days,
        "last_updated": _last_activity_date(profile_id),
        "summary": summary,
        "kpi_tiles": kpi_tiles,
        "interpretation_tiles": [],
        "progress_insights": progress_insights,
        "volume_delta": vol_delta,
        "charts": {
            "training_volume": volume_chart,
            "training_type_distribution": type_chart,
            "quality_sessions": quality_chart,
            "load_monitoring": load_chart,
        },
        "load_chart_days_used": load_days,
        "meta": {
            "layer_1": "activity_metrics",
            "layer_2b": "fitness_viz",
            "issue": "53-layer-2b-fitness",
        },
    }