All tweaks added

milevault_export/backend/app/workers/celery_app.py

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+"""
+Celery entry point. Re-exports celery_app from tasks so the worker
+can be started with: celery -A app.workers.celery_app worker
+"""
+from app.workers.tasks import celery_app
+
+__all__ = ["celery_app"]

milevault_export/backend/app/workers/tasks.py

@@ -0,0 +1,451 @@
+"""
+Background tasks: activity ingestion, route matching, PR calculation.
+
+Uses synchronous SQLAlchemy because Celery's prefork model doesn't play
+well with asyncio - each worker process needs its own connection pool,
+and async pools don't survive process forks.
+"""
+from celery import Celery
+from app.core.config import settings
+
+celery_app = Celery(
+    "milevault",
+    broker=settings.redis_url,
+    backend=settings.redis_url,
+)
+
+celery_app.conf.update(
+    task_serializer="json",
+    result_serializer="json",
+    accept_content=["json"],
+    timezone="UTC",
+    enable_utc=True,
+    task_track_started=True,
+    worker_prefetch_multiplier=1,
+)
+
+# Garmin FIT file suffixes that are health/wellness data, not activities
+WELLNESS_SUFFIXES = (
+    "_METRICS.fit",
+    "_WELLNESS.fit",
+    "_SLEEP.fit",
+    "_STRESS.fit",
+    "_SPO2.fit",
+    "_HRV.fit",
+    "_MONITORING.fit",
+    "_MONITORING_B.fit",
+)
+
+
+def is_wellness_file(file_path: str) -> bool:
+    name = file_path.upper()
+    return any(name.endswith(s.upper()) for s in WELLNESS_SUFFIXES)
+
+
+@celery_app.task(bind=True, name="process_activity_file")
+def process_activity_file(self, file_path: str, user_id: int, source_type: str):
+    """Parse a FIT/GPX file. Routes wellness files to health parser."""
+
+    # Route wellness/metrics files to health parser instead
+    if is_wellness_file(file_path):
+        parse_wellness_fit.delay(file_path, user_id)
+        return {"status": "routed_to_wellness", "file": file_path}
+
+    from app.services.fit_parser import parse_fit_file, parse_gpx_file, calculate_hr_zones
+    from app.core.database import SyncSessionLocal
+    from app.models.user import Activity, ActivityDataPoint, ActivityLap
+    from sqlalchemy import select
+    from datetime import datetime
+
+    self.update_state(state="PROGRESS", meta={"step": "parsing"})
+
+    try:
+        if source_type == "fit" or file_path.endswith(".fit"):
+            parsed = parse_fit_file(file_path)
+        else:
+            parsed = parse_gpx_file(file_path)
+    except Exception as e:
+        raise self.retry(exc=e, countdown=10, max_retries=3)
+
+    # Skip files with no usable activity data
+    if not parsed.get("start_time"):
+        return {"status": "skipped", "reason": "no start_time", "file": file_path}
+
+    with SyncSessionLocal() as db:
+        # Check for duplicate by garmin activity ID
+        if parsed.get("garmin_activity_id"):
+            existing = db.execute(
+                select(Activity).where(
+                    Activity.garmin_activity_id == parsed["garmin_activity_id"]
+                )
+            ).scalar_one_or_none()
+            if existing:
+                return {"activity_id": existing.id, "status": "duplicate"}
+
+        # Get user's configured max HR for accurate zone calculation
+        # Falls back to: user-set value → 220-age → activity max → 190
+        from app.models.user import User as UserModel
+        user_obj = db.execute(select(UserModel).where(UserModel.id == user_id)).scalar_one_or_none()
+        user_max_hr = None
+        if user_obj:
+            user_max_hr = user_obj.max_heart_rate
+            if not user_max_hr and user_obj.birth_year:
+                from datetime import date as _date
+                age = _date.today().year - user_obj.birth_year
+                user_max_hr = 220 - age
+        if not user_max_hr:
+            # Last resort: use activity max but warn this may shift zones
+            user_max_hr = parsed.get("max_heart_rate") or 190
+
+        hr_zones = calculate_hr_zones(
+            parsed.get("data_points", []),
+            user_max_hr
+        )
+
+        start_time = datetime.fromisoformat(parsed["start_time"])
+
+        activity = Activity(
+            user_id=user_id,
+            name=parsed["name"],
+            sport_type=parsed["sport_type"],
+            start_time=start_time,
+            distance_m=parsed.get("distance_m"),
+            duration_s=parsed.get("duration_s"),
+            elevation_gain_m=parsed.get("elevation_gain_m"),
+            elevation_loss_m=parsed.get("elevation_loss_m"),
+            avg_heart_rate=parsed.get("avg_heart_rate"),
+            max_heart_rate=parsed.get("max_heart_rate"),
+            avg_cadence=parsed.get("avg_cadence"),
+            avg_power=parsed.get("avg_power"),
+            normalized_power=parsed.get("normalized_power"),
+            avg_speed_ms=parsed.get("avg_speed_ms"),
+            max_speed_ms=parsed.get("max_speed_ms"),
+            avg_temperature_c=parsed.get("avg_temperature_c"),
+            calories=parsed.get("calories"),
+            training_stress_score=parsed.get("training_stress_score"),
+            polyline=parsed.get("polyline"),
+            bounding_box=parsed.get("bounding_box"),
+            source_file=file_path,
+            source_type=parsed.get("source_type"),
+            hr_zones=hr_zones,
+        )
+        db.add(activity)
+        db.flush()
+
+        # Insert data points, deduping on (activity_id, timestamp)
+        seen = set()
+        points = parsed.get("data_points", [])
+        batch = []
+        for p in points:
+            if not p.get("timestamp"):
+                continue
+            ts = datetime.fromisoformat(p["timestamp"]) if isinstance(p["timestamp"], str) else p["timestamp"]
+            key = (activity.id, ts)
+            if key in seen:
+                continue
+            seen.add(key)
+            batch.append(ActivityDataPoint(
+                activity_id=activity.id,
+                timestamp=ts,
+                latitude=p.get("latitude"),
+                longitude=p.get("longitude"),
+                altitude_m=p.get("altitude_m"),
+                heart_rate=p.get("heart_rate"),
+                cadence=p.get("cadence"),
+                speed_ms=p.get("speed_ms"),
+                power=p.get("power"),
+                temperature_c=p.get("temperature_c"),
+                distance_m=p.get("distance_m"),
+            ))
+            if len(batch) >= 500:
+                db.add_all(batch)
+                db.flush()
+                batch = []
+        if batch:
+            db.add_all(batch)
+            db.flush()
+
+        # Laps
+        for lap in parsed.get("laps", []):
+            ls = datetime.fromisoformat(lap["start_time"]) if lap.get("start_time") else None
+            db.add(ActivityLap(
+                activity_id=activity.id,
+                lap_number=lap["lap_number"],
+                start_time=ls,
+                duration_s=lap.get("duration_s"),
+                distance_m=lap.get("distance_m"),
+                avg_heart_rate=lap.get("avg_heart_rate"),
+                avg_cadence=lap.get("avg_cadence"),
+                avg_speed_ms=lap.get("avg_speed_ms"),
+                avg_power=lap.get("avg_power"),
+            ))
+
+        db.commit()
+        activity_id = activity.id
+
+    compute_personal_records.delay(activity_id, user_id, parsed)
+    # Auto route detection for running and cycling
+    if parsed.get("sport_type") in ("running", "cycling", "hiking", "walking"):
+        detect_route.delay(activity_id, user_id)
+    return {"activity_id": activity_id, "status": "ok"}
+
+
+@celery_app.task(name="parse_wellness_fit")
+def parse_wellness_fit(file_path: str, user_id: int):
+    """
+    Parse a Garmin wellness/metrics FIT file and upsert into health_metrics.
+    Uses wellness_parser which handles standard FIT + Garmin proprietary messages.
+    """
+    from app.services.wellness_parser import parse_wellness_fit as _parse
+    from app.core.database import SyncSessionLocal
+    from datetime import datetime, timezone
+    from sqlalchemy import text
+
+    result = _parse(file_path)
+    if result.get("error"):
+        return {"status": "error", "error": result["error"], "file": file_path}
+
+    days = result.get("days", {})
+    if not days:
+        return {"status": "no_data", "file": file_path}
+
+    with SyncSessionLocal() as db:
+        for day_date, data in days.items():
+            date_dt = datetime(day_date.year, day_date.month, day_date.day, tzinfo=timezone.utc)
+            db.execute(text("""
+                INSERT INTO health_metrics (user_id, date, resting_hr, avg_hr_day, max_hr_day,
+                    avg_stress, spo2_avg, hrv_nightly_avg, hrv_5min_high, hrv_status,
+                    steps, floors_climbed, active_calories, total_calories,
+                    sleep_duration_s, sleep_deep_s, sleep_light_s, sleep_rem_s, sleep_awake_s)
+                VALUES (:user_id, :date, :resting_hr, :avg_hr, :max_hr,
+                    :avg_stress, :spo2_avg, :hrv_avg, :hrv_high, :hrv_status,
+                    :steps, :floors, :active_cal, :total_cal,
+                    :sleep_dur, :sleep_deep, :sleep_light, :sleep_rem, :sleep_awake)
+                ON CONFLICT (user_id, date) DO UPDATE SET
+                    resting_hr       = COALESCE(EXCLUDED.resting_hr, health_metrics.resting_hr),
+                    avg_hr_day       = COALESCE(EXCLUDED.avg_hr_day, health_metrics.avg_hr_day),
+                    max_hr_day       = COALESCE(EXCLUDED.max_hr_day, health_metrics.max_hr_day),
+                    avg_stress       = COALESCE(EXCLUDED.avg_stress, health_metrics.avg_stress),
+                    spo2_avg         = COALESCE(EXCLUDED.spo2_avg, health_metrics.spo2_avg),
+                    hrv_nightly_avg  = COALESCE(EXCLUDED.hrv_nightly_avg, health_metrics.hrv_nightly_avg),
+                    hrv_5min_high    = COALESCE(EXCLUDED.hrv_5min_high, health_metrics.hrv_5min_high),
+                    hrv_status       = COALESCE(EXCLUDED.hrv_status, health_metrics.hrv_status),
+                    steps            = COALESCE(EXCLUDED.steps, health_metrics.steps),
+                    floors_climbed   = COALESCE(EXCLUDED.floors_climbed, health_metrics.floors_climbed),
+                    active_calories  = COALESCE(EXCLUDED.active_calories, health_metrics.active_calories),
+                    total_calories   = COALESCE(EXCLUDED.total_calories, health_metrics.total_calories),
+                    sleep_duration_s = COALESCE(EXCLUDED.sleep_duration_s, health_metrics.sleep_duration_s),
+                    sleep_deep_s     = COALESCE(EXCLUDED.sleep_deep_s, health_metrics.sleep_deep_s),
+                    sleep_light_s    = COALESCE(EXCLUDED.sleep_light_s, health_metrics.sleep_light_s),
+                    sleep_rem_s      = COALESCE(EXCLUDED.sleep_rem_s, health_metrics.sleep_rem_s),
+                    sleep_awake_s    = COALESCE(EXCLUDED.sleep_awake_s, health_metrics.sleep_awake_s)
+            """), {
+                "user_id": user_id, "date": date_dt,
+                "resting_hr": data.get("resting_hr"),
+                "avg_hr": data.get("avg_hr_day"),
+                "max_hr": data.get("max_hr_day"),
+                "avg_stress": data.get("avg_stress"),
+                "spo2_avg": data.get("spo2_avg"),
+                "hrv_avg": data.get("hrv_nightly_avg"),
+                "hrv_high": data.get("hrv_5min_high"),
+                "hrv_status": data.get("hrv_status"),
+                "steps": data.get("steps"),
+                "floors": data.get("floors_climbed"),
+                "active_cal": data.get("active_calories"),
+                "total_cal": data.get("total_calories"),
+                "sleep_dur": data.get("sleep_duration_s"),
+                "sleep_deep": data.get("sleep_deep_s"),
+                "sleep_light": data.get("sleep_light_s"),
+                "sleep_rem": data.get("sleep_rem_s"),
+                "sleep_awake": data.get("sleep_awake_s"),
+            })
+        db.commit()
+
+    return {"status": "ok", "days_processed": len(days), "file": file_path}
+
+@celery_app.task(name="detect_route")
+def detect_route(activity_id: int, user_id: int):
+    """
+    After importing an activity, check if it matches any existing named routes.
+    If two+ unassigned activities match each other, auto-create a named route.
+    """
+    from app.services.route_matcher import routes_are_similar
+    from app.core.database import SyncSessionLocal
+    from app.models.user import Activity, NamedRoute
+    from sqlalchemy import select
+
+    with SyncSessionLocal() as db:
+        # Get the new activity
+        new_act = db.execute(
+            select(Activity).where(Activity.id == activity_id)
+        ).scalar_one_or_none()
+        if not new_act or not new_act.polyline:
+            return {"status": "no_polyline"}
+
+        # Already assigned to a route?
+        if new_act.named_route_id:
+            return {"status": "already_assigned"}
+
+        # Check against existing named routes first
+        routes = db.execute(
+            select(NamedRoute).where(
+                NamedRoute.user_id == user_id,
+                NamedRoute.sport_type == new_act.sport_type,
+            )
+        ).scalars().all()
+
+        for route in routes:
+            if route.reference_polyline and routes_are_similar(
+                new_act.polyline, route.reference_polyline,
+                new_act.bounding_box, route.bounding_box,
+            ):
+                new_act.named_route_id = route.id
+                db.commit()
+                return {"status": "matched_existing", "route_id": route.id}
+
+        # No existing route matched - check unassigned activities for a match
+        candidates = db.execute(
+            select(Activity).where(
+                Activity.user_id == user_id,
+                Activity.sport_type == new_act.sport_type,
+                Activity.named_route_id == None,
+                Activity.id != activity_id,
+                Activity.polyline != None,
+                # Within 20% distance
+                Activity.distance_m >= (new_act.distance_m or 0) * 0.8,
+                Activity.distance_m <= (new_act.distance_m or 0) * 1.2,
+            )
+        ).scalars().all()
+
+        for candidate in candidates:
+            if routes_are_similar(
+                new_act.polyline, candidate.polyline,
+                new_act.bounding_box, candidate.bounding_box,
+            ):
+                # Auto-create a route from the older activity
+                older = candidate if candidate.start_time < new_act.start_time else new_act
+                newer = new_act if candidate.start_time < new_act.start_time else candidate
+
+                route_name = f"{older.sport_type.title()} route {older.start_time.strftime('%d %b %Y')}"
+                new_route = NamedRoute(
+                    user_id=user_id,
+                    name=route_name,
+                    sport_type=older.sport_type,
+                    reference_polyline=older.polyline,
+                    bounding_box=older.bounding_box,
+                    distance_m=older.distance_m,
+                    auto_detected=True,
+                )
+                db.add(new_route)
+                db.flush()
+                older.named_route_id = new_route.id
+                newer.named_route_id = new_route.id
+                db.commit()
+                return {"status": "auto_created", "route_id": new_route.id}
+
+    return {"status": "no_match"}
+
+
+@celery_app.task(name="compute_personal_records")
+def compute_personal_records(activity_id: int, user_id: int, parsed: dict):
+    """Calculate personal records for standard distances from this activity."""
+    from app.services.route_matcher import compute_best_splits, STANDARD_DISTANCES
+    from app.core.database import SyncSessionLocal
+    from app.models.user import PersonalRecord
+    from sqlalchemy import select
+    from datetime import datetime, timezone
+
+    data_points = parsed.get("data_points", [])
+    total_dist = parsed.get("distance_m", 0) or 0
+    sport = parsed.get("sport_type", "running")
+    start_time_str = parsed.get("start_time")
+    start_time = datetime.fromisoformat(start_time_str) if start_time_str else datetime.now(timezone.utc)
+
+    best_splits = compute_best_splits(data_points, total_dist)
+
+    with SyncSessionLocal() as db:
+        for label, duration_s in best_splits.items():
+            dist_m = next((d for d, l in STANDARD_DISTANCES if l == label), None)
+            if dist_m is None:
+                continue
+
+            current = db.execute(
+                select(PersonalRecord).where(
+                    PersonalRecord.user_id == user_id,
+                    PersonalRecord.sport_type == sport,
+                    PersonalRecord.distance_m == dist_m,
+                    PersonalRecord.is_current_record == True,
+                )
+            ).scalar_one_or_none()
+
+            if current is None or duration_s < current.duration_s:
+                if current:
+                    current.is_current_record = False
+                db.add(PersonalRecord(
+                    user_id=user_id,
+                    activity_id=activity_id,
+                    sport_type=sport,
+                    distance_m=dist_m,
+                    distance_label=label,
+                    duration_s=duration_s,
+                    achieved_at=start_time,
+                    is_current_record=True,
+                ))
+        db.commit()
+
+
+@celery_app.task(name="process_garmin_health_zip")
+def process_garmin_health_zip(zip_path: str, user_id: int):
+    """Extract wellness data from a Garmin Connect export ZIP."""
+    import zipfile
+    import json
+    from app.core.database import SyncSessionLocal
+    from app.models.user import HealthMetric
+    from datetime import datetime, timezone
+
+    with SyncSessionLocal() as db:
+        with zipfile.ZipFile(zip_path) as zf:
+            for name in zf.namelist():
+                if "DailyMetrics" not in name or not name.endswith(".json"):
+                    continue
+                with zf.open(name) as f:
+                    try:
+                        data = json.load(f)
+                    except Exception:
+                        continue
+
+                    date_str = data.get("calendarDate") or data.get("date")
+                    if not date_str:
+                        continue
+
+                    try:
+                        date_dt = datetime.fromisoformat(date_str).replace(tzinfo=timezone.utc)
+                    except ValueError:
+                        continue
+
+                    from sqlalchemy import text as _text
+                    db.execute(_text("""
+                        INSERT INTO health_metrics (user_id, date, resting_hr, steps,
+                            floors_climbed, active_calories, total_calories, avg_stress, spo2_avg)
+                        VALUES (:user_id, :date, :resting_hr, :steps,
+                            :floors, :active_cal, :total_cal, :stress, :spo2)
+                        ON CONFLICT (user_id, date) DO UPDATE SET
+                            resting_hr     = COALESCE(EXCLUDED.resting_hr, health_metrics.resting_hr),
+                            steps          = COALESCE(EXCLUDED.steps, health_metrics.steps),
+                            floors_climbed = COALESCE(EXCLUDED.floors_climbed, health_metrics.floors_climbed),
+                            active_calories = COALESCE(EXCLUDED.active_calories, health_metrics.active_calories),
+                            total_calories = COALESCE(EXCLUDED.total_calories, health_metrics.total_calories),
+                            avg_stress     = COALESCE(EXCLUDED.avg_stress, health_metrics.avg_stress),
+                            spo2_avg       = COALESCE(EXCLUDED.spo2_avg, health_metrics.spo2_avg)
+                    """), {
+                        "user_id": user_id, "date": date_dt,
+                        "resting_hr": data.get("restingHeartRate"),
+                        "steps": data.get("totalSteps"),
+                        "floors": data.get("floorsAscended"),
+                        "active_cal": data.get("activeKilocalories"),
+                        "total_cal": data.get("totalKilocalories"),
+                        "stress": data.get("averageStressLevel"),
+                        "spo2": data.get("avgSpo2"),
+                    })
+
+        db.commit()