Fix SDK field names - use camelCase throughout

backend/app/services/fit_parser.py

@@ -1,5 +1,6 @@
 """
 FIT and GPX file parser using the official Garmin FIT Python SDK.
+Field names from the SDK are camelCase as per the SDK documentation.
 """
 import math
 from datetime import datetime, timezone
@@ -59,6 +60,7 @@ def parse_fit_file(filepath: str) -> dict:
         merge_heart_rates=True,
     )
 
+    # SDK returns camelCase keys
     sessions = messages.get("session", [{}])
     session = sessions[0] if sessions else {}
     records = messages.get("record", [])
@@ -73,12 +75,12 @@ def parse_fit_file(filepath: str) -> dict:
     }
     sport_type = sport_map.get(sport, sport)
 
-    start_time = _ensure_utc(session.get("start_time"))
+    start_time = _ensure_utc(session.get("startTime"))
 
     coords = []
     for r in records:
-        lat = r.get("position_lat")
+        lat = r.get("positionLat")
-        lon = r.get("position_long")
+        lon = r.get("positionLong")
         if lat is not None and lon is not None:
             if -90 <= lat <= 90 and -180 <= lon <= 180:
                 coords.append((lat, lon))
@@ -89,8 +91,8 @@ def parse_fit_file(filepath: str) -> dict:
     normalized_points = []
     for r in records:
         ts = _ensure_utc(r.get("timestamp"))
-        lat = r.get("position_lat")
+        lat = r.get("positionLat")
-        lon = r.get("position_long")
+        lon = r.get("positionLong")
 
         if lat is not None and not (-90 <= lat <= 90):
             lat = None
@@ -101,10 +103,10 @@ def parse_fit_file(filepath: str) -> dict:
             "timestamp": ts.isoformat() if ts else None,
             "latitude": _safe_float(lat),
             "longitude": _safe_float(lon),
-            "altitude_m": _safe_float(r.get("altitude") or r.get("enhanced_altitude")),
+            "altitude_m": _safe_float(r.get("altitude") or r.get("enhancedAltitude")),
-            "heart_rate": _safe_float(r.get("heart_rate")),
+            "heart_rate": _safe_float(r.get("heartRate")),
             "cadence": _safe_float(r.get("cadence")),
-            "speed_ms": _safe_float(r.get("speed") or r.get("enhanced_speed")),
+            "speed_ms": _safe_float(r.get("speed") or r.get("enhancedSpeed")),
             "power": _safe_float(r.get("power")),
             "temperature_c": _safe_float(r.get("temperature")),
             "distance_m": _safe_float(r.get("distance")),
@@ -112,16 +114,16 @@ def parse_fit_file(filepath: str) -> dict:
 
     normalized_laps = []
     for i, lap in enumerate(laps):
-        ls = _ensure_utc(lap.get("start_time"))
+        ls = _ensure_utc(lap.get("startTime"))
         normalized_laps.append({
             "lap_number": i + 1,
             "start_time": ls.isoformat() if ls else None,
-            "duration_s": _safe_float(lap.get("total_elapsed_time")),
+            "duration_s": _safe_float(lap.get("totalElapsedTime")),
-            "distance_m": _safe_float(lap.get("total_distance")),
+            "distance_m": _safe_float(lap.get("totalDistance")),
-            "avg_heart_rate": _safe_float(lap.get("avg_heart_rate")),
+            "avg_heart_rate": _safe_float(lap.get("avgHeartRate")),
-            "avg_cadence": _safe_float(lap.get("avg_cadence")),
+            "avg_cadence": _safe_float(lap.get("avgCadence")),
-            "avg_speed_ms": _safe_float(lap.get("avg_speed") or lap.get("enhanced_avg_speed")),
+            "avg_speed_ms": _safe_float(lap.get("avgSpeed") or lap.get("enhancedAvgSpeed")),
-            "avg_power": _safe_float(lap.get("avg_power")),
+            "avg_power": _safe_float(lap.get("avgPower")),
         })
 
     name = sport_type.title()
@@ -132,21 +134,21 @@ def parse_fit_file(filepath: str) -> dict:
         "name": name,
         "sport_type": sport_type,
         "start_time": start_time.isoformat() if start_time else None,
-        "distance_m": _safe_float(session.get("total_distance")),
+        "distance_m": _safe_float(session.get("totalDistance")),
-        "duration_s": _safe_float(session.get("total_elapsed_time")),
+        "duration_s": _safe_float(session.get("totalElapsedTime")),
-        "elevation_gain_m": _safe_float(session.get("total_ascent")),
+        "elevation_gain_m": _safe_float(session.get("totalAscent")),
-        "elevation_loss_m": _safe_float(session.get("total_descent")),
+        "elevation_loss_m": _safe_float(session.get("totalDescent")),
-        "avg_heart_rate": _safe_float(session.get("avg_heart_rate")),
+        "avg_heart_rate": _safe_float(session.get("avgHeartRate")),
-        "max_heart_rate": _safe_float(session.get("max_heart_rate")),
+        "max_heart_rate": _safe_float(session.get("maxHeartRate")),
-        "avg_cadence": _safe_float(session.get("avg_cadence")),
+        "avg_cadence": _safe_float(session.get("avgCadence")),
-        "avg_power": _safe_float(session.get("avg_power")),
+        "avg_power": _safe_float(session.get("avgPower")),
-        "normalized_power": _safe_float(session.get("normalized_power")),
+        "normalized_power": _safe_float(session.get("normalizedPower")),
-        "avg_speed_ms": _safe_float(session.get("avg_speed") or session.get("enhanced_avg_speed")),
+        "avg_speed_ms": _safe_float(session.get("avgSpeed") or session.get("enhancedAvgSpeed")),
-        "max_speed_ms": _safe_float(session.get("max_speed") or session.get("enhanced_max_speed")),
+        "max_speed_ms": _safe_float(session.get("maxSpeed") or session.get("enhancedMaxSpeed")),
-        "avg_temperature_c": _safe_float(session.get("avg_temperature")),
+        "avg_temperature_c": _safe_float(session.get("avgTemperature")),
-        "calories": _safe_float(session.get("total_calories")),
+        "calories": _safe_float(session.get("totalCalories")),
-        "training_stress_score": _safe_float(session.get("training_stress_score")),
+        "training_stress_score": _safe_float(session.get("trainingStressScore")),
-        "vo2max_estimate": _safe_float(session.get("total_training_effect")),
+        "vo2max_estimate": _safe_float(session.get("totalTrainingEffect")),
         "polyline": encoded_polyline,
         "bounding_box": bounding_box,
         "source_type": "fit",

backend/app/services/wellness_parser.py

@@ -1,194 +1,55 @@
 """
-Garmin wellness FIT file parser using the official Garmin FIT Python SDK.
+FIT and GPX file parser using the official Garmin FIT Python SDK.
+Field names from the SDK are camelCase as per the SDK documentation.
 """
-from datetime import datetime, timezone, date
+import math
+from datetime import datetime, timezone
 from typing import Optional
+import gpxpy
+import polyline as polyline_lib
 from garmin_fit_sdk import Decoder, Stream
 
 
-FIT_EPOCH_S = 631065600
+def haversine_distance(lat1, lon1, lat2, lon2) -> float:
+    R = 6371000
+    phi1, phi2 = math.radians(lat1), math.radians(lat2)
+    dphi = math.radians(lat2 - lat1)
+    dlam = math.radians(lon2 - lon1)
+    a = math.sin(dphi/2)**2 + math.cos(phi1)*math.cos(phi2)*math.sin(dlam/2)**2
+    return 2 * R * math.asin(math.sqrt(a))
 
 
-def _fit_ts(raw) -> Optional[datetime]:
+def _safe_float(val) -> Optional[float]:
-    if raw is None:
-        return None
     try:
-        s = int(raw)
+        return float(val) if val is not None else None
-        if s <= 0 or s == 0xFFFFFFFF:
+    except (TypeError, ValueError):
-            return None
-        return datetime.fromtimestamp(s + FIT_EPOCH_S, tz=timezone.utc)
-    except (TypeError, ValueError, OverflowError, OSError):
         return None
 
 
-def _to_date(val) -> Optional[date]:
+def _bounding_box(coords: list) -> Optional[dict]:
-    if val is None:
+    if not coords:
         return None
-    if isinstance(val, datetime):
+    lats = [c[0] for c in coords]
-        if val.tzinfo is None:
+    lons = [c[1] for c in coords]
-            val = val.replace(tzinfo=timezone.utc)
+    return {"min_lat": min(lats), "max_lat": max(lats),
-        return val.date()
+            "min_lon": min(lons), "max_lon": max(lons)}
-    if isinstance(val, (int, float)):
+
-        dt = _fit_ts(val)
+
-        return dt.date() if dt else None
+def _ensure_utc(dt) -> Optional[datetime]:
+    if dt is None:
+        return None
+    if isinstance(dt, datetime):
+        if dt.tzinfo is None:
+            return dt.replace(tzinfo=timezone.utc)
+        return dt
     return None
 
 
-def parse_wellness_fit(file_path: str) -> dict:
+def parse_fit_file(filepath: str) -> dict:
-    """
+    """Parse a Garmin .fit activity file using the official Garmin SDK."""
-    Parse a Garmin wellness/monitoring FIT file.
+    stream = Stream.from_file(filepath)
-    Returns {"days": {date: metrics_dict}, "error": str|None}
-    """
-    daily = {}
-
-    def ensure_day(d: date) -> dict:
-        if d not in daily:
-            daily[d] = {
-                "heart_rates": [],
-                "stress_values": [],
-                "spo2_readings": [],
-                "sleep_levels": [],
-                "steps": None,
-                "floors_climbed": None,
-                "active_calories": None,
-                "total_calories": None,
-                "resting_hr": None,
-                "hrv_nightly_avg": None,
-                "hrv_5min_high": None,
-                "hrv_status": None,
-            }
-        return daily[d]
-
-    def listener(mesg_num: int, msg: dict):
-
-        if mesg_num == 147:
-            d = _to_date(msg.get("timestamp") or msg.get("local_timestamp"))
-            rhr = msg.get("resting_heart_rate")
-            if d and rhr and 20 < rhr < 120:
-                ensure_day(d)["resting_hr"] = int(rhr)
-
-        elif mesg_num == 148:
-            d = _to_date(msg.get("timestamp") or msg.get("local_timestamp"))
-            if not d:
-                return
-            entry = ensure_day(d)
-            hr = msg.get("heart_rate")
-            if hr and 20 < hr < 250:
-                entry["heart_rates"].append(int(hr))
-            steps = msg.get("steps") or msg.get("cycles")
-            if steps and steps > 0:
-                entry["steps"] = max(entry["steps"] or 0, int(steps))
-            stress = msg.get("stress_level_value")
-            if stress is not None and stress >= 0:
-                entry["stress_values"].append(int(stress))
-
-        elif mesg_num == 275:
-            d = _to_date(msg.get("timestamp"))
-            if not d:
-                return
-            entry = ensure_day(d)
-            for key in ("weekly_average", "last_night_avg", "hrv_nightly_avg"):
-                v = msg.get(key)
-                if v and v > 0:
-                    entry["hrv_nightly_avg"] = float(v)
-                    break
-            high = msg.get("last_night_5_min_high")
-            if high:
-                entry["hrv_5min_high"] = float(high)
-            status = msg.get("hrv_status")
-            if status:
-                entry["hrv_status"] = str(status)
-
-        elif mesg_num == 132:
-            d = _to_date(msg.get("stress_level_time") or msg.get("timestamp"))
-            if not d:
-                return
-            stress = msg.get("stress_level_value")
-            if stress is not None and stress >= 0:
-                ensure_day(d)["stress_values"].append(int(stress))
-
-        elif mesg_num == 258:
-            d = _to_date(msg.get("timestamp"))
-            if not d:
-                return
-            spo2 = msg.get("spo2_percent") or msg.get("reading_spo2")
-            if spo2 and 50 < spo2 <= 100:
-                ensure_day(d)["spo2_readings"].append(float(spo2))
-
-        elif mesg_num == 269:
-            d = _to_date(msg.get("timestamp"))
-            if not d:
-                return
-            level = msg.get("sleep_level")
-            if level is not None:
-                if isinstance(level, str):
-                    level_map = {"unmeasurable": 0, "awake": 1, "light": 2, "deep": 3, "rem": 4}
-                    level = level_map.get(level.lower())
-                if level is not None:
-                    ensure_day(d)["sleep_levels"].append(int(level))
-
-        elif mesg_num == 227:
-            ts_raw = msg.get(1) or msg.get("1") or msg.get("unknown_1")
-            hr_raw = msg.get(2) or msg.get("2") or msg.get("unknown_2")
-            stress_raw = msg.get(0) or msg.get("0") or msg.get("unknown_0")
-            d = _to_date(ts_raw)
-            if not d:
-                return
-            entry = ensure_day(d)
-            if hr_raw and isinstance(hr_raw, (int, float)) and 20 < hr_raw < 250:
-                entry["heart_rates"].append(int(hr_raw))
-            if stress_raw is not None and isinstance(stress_raw, (int, float)) and stress_raw >= 0:
-                entry["stress_values"].append(int(stress_raw))
-
-        elif mesg_num == 103:
-            ts_raw = msg.get(253) or msg.get("253") or msg.get("timestamp")
-            d = _to_date(ts_raw)
-            if not d:
-                return
-            entry = ensure_day(d)
-            steps = msg.get(3) or msg.get("3")
-            if steps and isinstance(steps, (int, float)) and steps > 0:
-                entry["steps"] = int(steps)
-            floors = msg.get(4) or msg.get("4")
-            if floors and isinstance(floors, (int, float)) and floors > 0:
-                f = float(floors)
-                entry["floors_climbed"] = round(f / 100 if f > 1000 else f, 1)
-            active_cal = msg.get(5) or msg.get("5")
-            if active_cal and isinstance(active_cal, (int, float)) and active_cal > 0:
-                entry["active_calories"] = float(active_cal)
-            total_cal = msg.get(7) or msg.get("7")
-            if total_cal and isinstance(total_cal, (int, float)) and total_cal > 0:
-                entry["total_calories"] = float(total_cal)
-
-        elif mesg_num == 211:
-            ts_raw = msg.get(253) or msg.get("253") or msg.get("timestamp")
-            d = _to_date(ts_raw)
-            if not d:
-                return
-            entry = ensure_day(d)
-            rhr = msg.get(0) or msg.get("0")
-            if rhr and isinstance(rhr, (int, float)) and 20 < rhr < 120:
-                entry["resting_hr"] = int(rhr)
-            hrv = msg.get(1) or msg.get("1")
-            if hrv and isinstance(hrv, (int, float)) and 5 < hrv < 300:
-                entry["hrv_nightly_avg"] = float(hrv)
-
-        elif mesg_num == 55:
-            ts_raw = msg.get(253) or msg.get("253") or msg.get("timestamp")
-            d = _to_date(ts_raw)
-            if not d:
-                return
-            entry = ensure_day(d)
-            steps = msg.get(2) or msg.get("2")
-            if steps and isinstance(steps, (int, float)) and steps > 0:
-                entry["steps"] = max(entry["steps"] or 0, int(steps))
-            hr = msg.get(19) or msg.get("19")
-            if hr and isinstance(hr, (int, float)) and 20 < hr < 250:
-                entry["heart_rates"].append(int(hr))
-
-    try:
-        stream = Stream.from_file(file_path)
     decoder = Decoder(stream)
+
     messages, errors = decoder.read(
         apply_scale_and_offset=True,
         convert_datetimes_to_dates=True,
@@ -196,51 +57,228 @@ def parse_wellness_fit(file_path: str) -> dict:
         enable_crc_check=False,
         expand_sub_fields=True,
         expand_components=True,
-            merge_heart_rates=False,
+        merge_heart_rates=True,
-            mesg_listener=listener,
     )
-    except Exception as e:
-        return {"error": str(e), "days": {}}
 
-    result = {}
+    # SDK returns camelCase keys
-    for day_date, data in daily.items():
+    sessions = messages.get("session", [{}])
-        hrs = data.pop("heart_rates", [])
+    session = sessions[0] if sessions else {}
-        stresses = data.pop("stress_values", [])
+    records = messages.get("record", [])
-        spo2s = data.pop("spo2_readings", [])
+    laps = messages.get("lap", [])
-        sleep_levels = data.pop("sleep_levels", [])
 
-        avg_hr = round(sum(hrs) / len(hrs), 1) if hrs else None
+    sport = str(session.get("sport", "generic")).lower()
-        max_hr = max(hrs) if hrs else None
+    sport_map = {
-        avg_stress = round(sum(s for s in stresses if s >= 0) / len(stresses), 1) if stresses else None
+        "running": "running", "cycling": "cycling",
-        spo2_avg = round(sum(spo2s) / len(spo2s), 1) if spo2s else None
+        "hiking": "hiking", "walking": "walking",
+        "generic": "other", "trail_running": "running",
+        "e_biking": "cycling", "open_water_swimming": "other",
+    }
+    sport_type = sport_map.get(sport, sport)
 
-        if sleep_levels:
+    start_time = _ensure_utc(session.get("startTime"))
-            sleep_deep_s = sum(30 for l in sleep_levels if l == 3) or None
-            sleep_light_s = sum(30 for l in sleep_levels if l == 2) or None
-            sleep_rem_s = sum(30 for l in sleep_levels if l == 4) or None
-            sleep_awake_s = sum(30 for l in sleep_levels if l == 1) or None
-            sleep_duration_s = (sleep_deep_s or 0) + (sleep_light_s or 0) + (sleep_rem_s or 0) or None
-        else:
-            sleep_deep_s = sleep_light_s = sleep_rem_s = sleep_awake_s = sleep_duration_s = None
 
-        result[day_date] = {
+    coords = []
-            "resting_hr": data.get("resting_hr"),
+    for r in records:
-            "avg_hr_day": avg_hr,
+        lat = r.get("positionLat")
-            "max_hr_day": max_hr,
+        lon = r.get("positionLong")
-            "avg_stress": avg_stress,
+        if lat is not None and lon is not None:
-            "spo2_avg": spo2_avg,
+            if -90 <= lat <= 90 and -180 <= lon <= 180:
-            "hrv_nightly_avg": data.get("hrv_nightly_avg"),
+                coords.append((lat, lon))
-            "hrv_5min_high": data.get("hrv_5min_high"),
+
-            "hrv_status": data.get("hrv_status"),
+    encoded_polyline = polyline_lib.encode(coords) if coords else None
-            "steps": data.get("steps"),
+    bounding_box = _bounding_box(coords)
-            "floors_climbed": data.get("floors_climbed"),
+
-            "active_calories": data.get("active_calories"),
+    normalized_points = []
-            "total_calories": data.get("total_calories"),
+    for r in records:
-            "sleep_duration_s": sleep_duration_s,
+        ts = _ensure_utc(r.get("timestamp"))
-            "sleep_deep_s": sleep_deep_s,
+        lat = r.get("positionLat")
-            "sleep_light_s": sleep_light_s,
+        lon = r.get("positionLong")
-            "sleep_rem_s": sleep_rem_s,
+
-            "sleep_awake_s": sleep_awake_s,
+        if lat is not None and not (-90 <= lat <= 90):
+            lat = None
+        if lon is not None and not (-180 <= lon <= 180):
+            lon = None
+
+        normalized_points.append({
+            "timestamp": ts.isoformat() if ts else None,
+            "latitude": _safe_float(lat),
+            "longitude": _safe_float(lon),
+            "altitude_m": _safe_float(r.get("altitude") or r.get("enhancedAltitude")),
+            "heart_rate": _safe_float(r.get("heartRate")),
+            "cadence": _safe_float(r.get("cadence")),
+            "speed_ms": _safe_float(r.get("speed") or r.get("enhancedSpeed")),
+            "power": _safe_float(r.get("power")),
+            "temperature_c": _safe_float(r.get("temperature")),
+            "distance_m": _safe_float(r.get("distance")),
+        })
+
+    normalized_laps = []
+    for i, lap in enumerate(laps):
+        ls = _ensure_utc(lap.get("startTime"))
+        normalized_laps.append({
+            "lap_number": i + 1,
+            "start_time": ls.isoformat() if ls else None,
+            "duration_s": _safe_float(lap.get("totalElapsedTime")),
+            "distance_m": _safe_float(lap.get("totalDistance")),
+            "avg_heart_rate": _safe_float(lap.get("avgHeartRate")),
+            "avg_cadence": _safe_float(lap.get("avgCadence")),
+            "avg_speed_ms": _safe_float(lap.get("avgSpeed") or lap.get("enhancedAvgSpeed")),
+            "avg_power": _safe_float(lap.get("avgPower")),
+        })
+
+    name = sport_type.title()
+    if start_time:
+        name += " " + start_time.strftime("%Y-%m-%d")
+
+    return {
+        "name": name,
+        "sport_type": sport_type,
+        "start_time": start_time.isoformat() if start_time else None,
+        "distance_m": _safe_float(session.get("totalDistance")),
+        "duration_s": _safe_float(session.get("totalElapsedTime")),
+        "elevation_gain_m": _safe_float(session.get("totalAscent")),
+        "elevation_loss_m": _safe_float(session.get("totalDescent")),
+        "avg_heart_rate": _safe_float(session.get("avgHeartRate")),
+        "max_heart_rate": _safe_float(session.get("maxHeartRate")),
+        "avg_cadence": _safe_float(session.get("avgCadence")),
+        "avg_power": _safe_float(session.get("avgPower")),
+        "normalized_power": _safe_float(session.get("normalizedPower")),
+        "avg_speed_ms": _safe_float(session.get("avgSpeed") or session.get("enhancedAvgSpeed")),
+        "max_speed_ms": _safe_float(session.get("maxSpeed") or session.get("enhancedMaxSpeed")),
+        "avg_temperature_c": _safe_float(session.get("avgTemperature")),
+        "calories": _safe_float(session.get("totalCalories")),
+        "training_stress_score": _safe_float(session.get("trainingStressScore")),
+        "vo2max_estimate": _safe_float(session.get("totalTrainingEffect")),
+        "polyline": encoded_polyline,
+        "bounding_box": bounding_box,
+        "source_type": "fit",
+        "data_points": normalized_points,
+        "laps": normalized_laps,
     }
 
-    return {"days": result, "error": None}
+
+def parse_gpx_file(filepath: str) -> dict:
+    """Parse a GPX file."""
+    with open(filepath) as f:
+        gpx = gpxpy.parse(f)
+
+    data_points = []
+    track = gpx.tracks[0] if gpx.tracks else None
+    if not track:
+        raise ValueError("No tracks found in GPX file")
+
+    for segment in track.segments:
+        for pt in segment.points:
+            ts = pt.time
+            if ts and ts.tzinfo is None:
+                ts = ts.replace(tzinfo=timezone.utc)
+
+            extensions = {}
+            if pt.extensions:
+                for ext in pt.extensions:
+                    for child in ext:
+                        tag = child.tag.split("}")[-1] if "}" in child.tag else child.tag
+                        try:
+                            extensions[tag] = float(child.text)
+                        except (ValueError, TypeError):
+                            pass
+
+            data_points.append({
+                "timestamp": ts.isoformat() if ts else None,
+                "latitude": pt.latitude,
+                "longitude": pt.longitude,
+                "altitude_m": pt.elevation,
+                "heart_rate": extensions.get("hr"),
+                "cadence": extensions.get("cad"),
+                "speed_ms": extensions.get("speed"),
+                "power": extensions.get("power"),
+                "temperature_c": extensions.get("temp") or extensions.get("atemp"),
+                "distance_m": None,
+            })
+
+    coords = [(p["latitude"], p["longitude"]) for p in data_points
+              if p["latitude"] and p["longitude"]]
+    encoded_polyline = polyline_lib.encode(coords) if coords else None
+    bounding_box = _bounding_box(coords)
+
+    total_dist = 0.0
+    prev = None
+    for p in data_points:
+        if p["latitude"] and p["longitude"]:
+            if prev:
+                total_dist += haversine_distance(prev[0], prev[1], p["latitude"], p["longitude"])
+            prev = (p["latitude"], p["longitude"])
+        p["distance_m"] = total_dist
+
+    uphill, downhill = 0.0, 0.0
+    alts = [p["altitude_m"] for p in data_points if p["altitude_m"]]
+    for i in range(1, len(alts)):
+        diff = alts[i] - alts[i-1]
+        if diff > 0:
+            uphill += diff
+        else:
+            downhill += abs(diff)
+
+    hrs = [p["heart_rate"] for p in data_points if p["heart_rate"]]
+    start_time_str = data_points[0]["timestamp"] if data_points else None
+    start_dt = datetime.fromisoformat(start_time_str) if start_time_str else None
+    end_dt = datetime.fromisoformat(data_points[-1]["timestamp"]) if data_points else None
+    duration = (end_dt - start_dt).total_seconds() if (start_dt and end_dt) else None
+
+    sport = "running"
+    if track.type:
+        sport = track.type.lower()
+
+    return {
+        "name": track.name or gpx.name or f"Activity {start_dt.date() if start_dt else ''}",
+        "sport_type": sport,
+        "start_time": start_time_str,
+        "distance_m": total_dist,
+        "duration_s": duration,
+        "elevation_gain_m": uphill,
+        "elevation_loss_m": downhill,
+        "avg_heart_rate": (sum(hrs) / len(hrs)) if hrs else None,
+        "max_heart_rate": max(hrs) if hrs else None,
+        "avg_cadence": None,
+        "avg_power": None,
+        "normalized_power": None,
+        "avg_speed_ms": (total_dist / duration) if (total_dist and duration) else None,
+        "max_speed_ms": None,
+        "avg_temperature_c": None,
+        "calories": None,
+        "training_stress_score": None,
+        "vo2max_estimate": None,
+        "polyline": encoded_polyline,
+        "bounding_box": bounding_box,
+        "source_type": "gpx",
+        "data_points": data_points,
+        "laps": [],
+    }
+
+
+def calculate_hr_zones(data_points: list, user_max_hr: float) -> dict:
+    """Calculate % time in each HR zone using user's configured max HR."""
+    if not user_max_hr or user_max_hr < 100:
+        return {}
+
+    zone_bounds = [0.0, 0.60, 0.70, 0.80, 0.90, 1.01]
+    zone_keys = ["z1", "z2", "z3", "z4", "z5"]
+    zones = {k: 0 for k in zone_keys}
+    total = 0
+
+    for p in data_points:
+        hr = p.get("heart_rate")
+        if not hr or hr < 20:
+            continue
+        pct = hr / user_max_hr
+        total += 1
+        for i, key in enumerate(zone_keys):
+            if zone_bounds[i] <= pct < zone_bounds[i+1]:
+                zones[key] += 1
+                break
+        else:
+            zones["z5"] += 1
+
+    if total:
+        return {k: round(v / total * 100, 1) for k, v in zones.items()}
+    return {}

deploy.sh

@@ -0,0 +1,16 @@
+#!/usr/bin/env bash
+set -e
+
+MESSAGE="${1:-update}"
+
+cd "$(dirname "$0")"
+
+git add -A
+git commit -m "$MESSAGE"
+git push
+
+cd ../milevault_docker
+docker compose down -v
+
+echo ""
+echo "Done. Run 'docker compose pull && docker compose up -d' when the build completes."