Remove fitparse entirely - use Garmin SDK only with messages dict approach

backend/app/services/fit_parser.py

@@ -1,24 +1,15 @@
 """
-FIT and GPX file parser using:
+FIT and GPX file parser using the official Garmin FIT Python SDK.
-- Official Garmin FIT Python SDK (garmin-fit-sdk) for .fit files
-- gpxpy for .gpx files
-
-The official SDK correctly handles scale/offset, component expansion,
-semicircle-to-degree conversion, and HR message merging.
 """
 import math
-from pathlib import Path
+from datetime import datetime, timezone
-from datetime import datetime, timezone, timedelta
 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:
-    """Distance in metres between two GPS points."""
     R = 6371000
     phi1, phi2 = math.radians(lat1), math.radians(lat2)
     dphi = math.radians(lat2 - lat1)
@@ -43,26 +34,22 @@ def _bounding_box(coords: list) -> Optional[dict]:
             "min_lon": min(lons), "max_lon": max(lons)}
 
 
+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_fit_file(filepath: str) -> dict:
     """Parse a Garmin .fit activity file using the official Garmin SDK."""
-    from garmin_fit_sdk import Decoder, Stream
-
-    session = {}
-    records = []
-    laps = []
-
-    def listener(mesg_num: int, msg: dict):
-        nonlocal session
-        if mesg_num == 18:   # session
-            session = msg
-        elif mesg_num == 20:  # record
-            records.append(msg)
-        elif mesg_num == 19:  # lap
-            laps.append(msg)
-
     stream = Stream.from_file(filepath)
     decoder = Decoder(stream)
-    decoder.read(
+
+    messages, errors = decoder.read(
         apply_scale_and_offset=True,
         convert_datetimes_to_dates=True,
         convert_types_to_strings=True,
@@ -70,58 +57,62 @@ def parse_fit_file(filepath: str) -> dict:
         expand_sub_fields=True,
         expand_components=True,
         merge_heart_rates=True,
-        mesg_listener=listener,
     )
 
-    # Map sport type
+    sessions = messages.get("session", [{}])
+    session = sessions[0] if sessions else {}
+    records = messages.get("record", [])
+    laps = messages.get("lap", [])
+
     sport = str(session.get("sport", "generic")).lower()
     sport_map = {
-        "running": "running", "cycling": "cycling", "swimming": "swimming",
+        "running": "running", "cycling": "cycling",
-        "hiking": "hiking", "walking": "walking", "generic": "other",
+        "hiking": "hiking", "walking": "walking",
-        "open_water_swimming": "swimming", "trail_running": "running",
+        "generic": "other", "trail_running": "running",
-        "e_biking": "cycling",
+        "e_biking": "cycling", "open_water_swimming": "other",
     }
     sport_type = sport_map.get(sport, sport)
 
-    start_time = session.get("start_time")
+    start_time = _ensure_utc(session.get("start_time"))
-    if isinstance(start_time, datetime) and start_time.tzinfo is None:
+
-        start_time = start_time.replace(tzinfo=timezone.utc)
+    coords = []
+    for r in records:
+        lat = r.get("position_lat")
+        lon = r.get("position_long")
+        if lat is not None and lon is not None:
+            if -90 <= lat <= 90 and -180 <= lon <= 180:
+                coords.append((lat, lon))
 
-    # Build GPS track
-    coords = [
-        (r["position_lat"], r["position_long"])
-        for r in records
-        if r.get("position_lat") is not None and r.get("position_long") is not None
-    ]
     encoded_polyline = polyline_lib.encode(coords) if coords else None
     bounding_box = _bounding_box(coords)
 
-    # Normalize data points
     normalized_points = []
     for r in records:
-        ts = r.get("timestamp")
+        ts = _ensure_utc(r.get("timestamp"))
-        if isinstance(ts, datetime) and ts.tzinfo is None:
+        lat = r.get("position_lat")
-            ts = ts.replace(tzinfo=timezone.utc)
+        lon = r.get("position_long")
+
+        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": r.get("position_lat"),
+            "latitude": _safe_float(lat),
-            "longitude": r.get("position_long"),
+            "longitude": _safe_float(lon),
-            "altitude_m": r.get("altitude") or r.get("enhanced_altitude"),
+            "altitude_m": _safe_float(r.get("altitude") or r.get("enhanced_altitude")),
-            "heart_rate": r.get("heart_rate"),
+            "heart_rate": _safe_float(r.get("heart_rate")),
-            "cadence": r.get("cadence") or r.get("fractional_cadence"),
+            "cadence": _safe_float(r.get("cadence")),
-            "speed_ms": r.get("speed") or r.get("enhanced_speed"),
+            "speed_ms": _safe_float(r.get("speed") or r.get("enhanced_speed")),
-            "power": r.get("power"),
+            "power": _safe_float(r.get("power")),
-            "temperature_c": r.get("temperature"),
+            "temperature_c": _safe_float(r.get("temperature")),
-            "distance_m": r.get("distance"),
+            "distance_m": _safe_float(r.get("distance")),
         })
 
-    # Normalize laps
     normalized_laps = []
     for i, lap in enumerate(laps):
-        ls = lap.get("start_time")
+        ls = _ensure_utc(lap.get("start_time"))
-        if isinstance(ls, datetime) and ls.tzinfo is None:
-            ls = ls.replace(tzinfo=timezone.utc)
         normalized_laps.append({
             "lap_number": i + 1,
             "start_time": ls.isoformat() if ls else None,
@@ -133,8 +124,7 @@ def parse_fit_file(filepath: str) -> dict:
             "avg_power": _safe_float(lap.get("avg_power")),
         })
 
-    # Build activity name
+    name = sport_type.title()
-    name = session.get("sport", "Activity").title()
     if start_time:
         name += " " + start_time.strftime("%Y-%m-%d")
 
@@ -209,7 +199,6 @@ def parse_gpx_file(filepath: str) -> dict:
     encoded_polyline = polyline_lib.encode(coords) if coords else None
     bounding_box = _bounding_box(coords)
 
-    # Add cumulative distance
     total_dist = 0.0
     prev = None
     for p in data_points:
@@ -219,7 +208,6 @@ def parse_gpx_file(filepath: str) -> dict:
             prev = (p["latitude"], p["longitude"])
         p["distance_m"] = total_dist
 
-    # Elevation gain/loss
     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)):
@@ -267,20 +255,7 @@ def parse_gpx_file(filepath: str) -> dict:
 
 
 def calculate_hr_zones(data_points: list, user_max_hr: float) -> dict:
-    """
+    """Calculate % time in each HR zone using user's configured max HR."""
-    Calculate % time in each HR zone using the user's configured max HR.
-
-    Zones follow the standard 5-zone model as % of max HR:
-      Z1 Recovery:  < 60%
-      Z2 Base:      60 - 70%
-      Z3 Tempo:     70 - 80%
-      Z4 Threshold: 80 - 90%
-      Z5 Max:       > 90%
-
-    user_max_hr should be the user's actual physiological max HR, NOT the
-    highest HR recorded in this activity. Using activity max shifts all zones
-    upward and makes easy runs look harder than they are.
-    """
     if not user_max_hr or user_max_hr < 100:
         return {}
 
@@ -300,8 +275,8 @@ def calculate_hr_zones(data_points: list, user_max_hr: float) -> dict:
                 zones[key] += 1
                 break
         else:
-            zones["z5"] += 1  # anything above 90% goes to z5
+            zones["z5"] += 1
 
     if total:
         return {k: round(v / total * 100, 1) for k, v in zones.items()}
-    return {}
+    return {}

backend/app/services/wellness_parser.py

@@ -1,56 +1,45 @@
 """
 Garmin wellness FIT file parser using the official Garmin FIT Python SDK.
-
-The official SDK (garmin-fit-sdk) correctly handles:
-- Standard FIT messages (monitoring, hrv_status_summary, sleep_level etc.)
-- Garmin proprietary messages stored by numeric mesg_num
-- Unknown fields stored by field definition number
-- Scale/offset application, component expansion, HR merging
-
-Fenix 6X proprietary message numbers identified by binary analysis:
-  55  - activity accumulation snapshots (cumulative steps, HR per interval)
-  103 - daily totals summary (total steps, floors, calories)
-  211 - resting HR + HRV summary
-  227 - per-minute stress level + heart rate (most valuable for health dashboard)
 """
-from datetime import datetime, timezone, timedelta, date
+from datetime import datetime, timezone, date
 from typing import Optional
+from garmin_fit_sdk import Decoder, Stream
 
 
-FIT_EPOCH_S = 631065600  # seconds between Unix epoch and FIT epoch (Dec 31 1989)
+FIT_EPOCH_S = 631065600
 
 
-def fit_ts(seconds) -> Optional[datetime]:
+def _fit_ts(raw) -> Optional[datetime]:
-    """Convert FIT timestamp to UTC datetime."""
+    if raw is None:
-    if seconds is None:
         return None
     try:
-        s = int(seconds)
+        s = int(raw)
-        if s == 0 or s == 0xFFFFFFFF:
+        if s <= 0 or s == 0xFFFFFFFF:
             return None
         return datetime.fromtimestamp(s + FIT_EPOCH_S, tz=timezone.utc)
     except (TypeError, ValueError, OverflowError, OSError):
         return None
 
 
-def _is_datetime(v) -> bool:
+def _to_date(val) -> Optional[date]:
-    return isinstance(v, datetime)
+    if val is None:
+        return None
+    if isinstance(val, datetime):
+        if val.tzinfo is None:
+            val = val.replace(tzinfo=timezone.utc)
+        return val.date()
+    if isinstance(val, (int, float)):
+        dt = _fit_ts(val)
+        return dt.date() if dt else None
+    return None
 
 
 def parse_wellness_fit(file_path: str) -> dict:
     """
-    Parse a Garmin wellness/monitoring FIT file using the official Garmin SDK.
+    Parse a Garmin wellness/monitoring FIT file.
-
     Returns {"days": {date: metrics_dict}, "error": str|None}
     """
-    try:
+    daily = {}
-        from garmin_fit_sdk import Decoder, Stream
-    except ImportError:
-        # Fall back to fitparse-based parser if SDK not installed yet
-        from app.services.wellness_parser_fallback import parse_wellness_fit as _fb
-        return _fb(file_path)
-
-    daily = {}  # date -> aggregation dict
 
     def ensure_day(d: date) -> dict:
         if d not in daily:
@@ -70,60 +59,37 @@ def parse_wellness_fit(file_path: str) -> dict:
             }
         return daily[d]
 
-    def get_date(msg: dict, *keys) -> Optional[date]:
-        """Extract a date from a message, trying multiple field names."""
-        for key in keys:
-            v = msg.get(key)
-            if v is None:
-                continue
-            if _is_datetime(v):
-                return v.date()
-            if isinstance(v, (int, float)):
-                dt = fit_ts(v)
-                if dt:
-                    return dt.date()
-        return None
-
     def listener(mesg_num: int, msg: dict):
-        """Called for every message after full decoding."""
 
-        # ── Standard: monitoring (148) ────────────────────────────────────
+        if mesg_num == 147:
-        if mesg_num == 148:
+            d = _to_date(msg.get("timestamp") or msg.get("local_timestamp"))
-            d = get_date(msg, "timestamp", "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))
 
-        # ── Standard: monitoring_info (147) ───────────────────────────────
-        elif mesg_num == 147:
-            d = get_date(msg, "timestamp", "local_timestamp")
-            if not d:
-                return
-            rhr = msg.get("resting_heart_rate")
-            if rhr and 20 < rhr < 120:
-                ensure_day(d)["resting_hr"] = int(rhr)
-
-        # ── Standard: hrv_status_summary (275) ────────────────────────────
         elif mesg_num == 275:
-            d = get_date(msg, "timestamp")
+            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:
+                if v and v > 0:
                     entry["hrv_nightly_avg"] = float(v)
                     break
             high = msg.get("last_night_5_min_high")
@@ -133,120 +99,93 @@ def parse_wellness_fit(file_path: str) -> dict:
             if status:
                 entry["hrv_status"] = str(status)
 
-        # ── Standard: stress_level (132) ──────────────────────────────────
         elif mesg_num == 132:
-            d = get_date(msg, "stress_level_time", "timestamp")
+            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))
 
-        # ── Standard: spo2_data (258) ─────────────────────────────────────
         elif mesg_num == 258:
-            d = get_date(msg, "timestamp")
+            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))
 
-        # ── Standard: sleep_level (269) ───────────────────────────────────
         elif mesg_num == 269:
-            d = get_date(msg, "timestamp")
+            d = _to_date(msg.get("timestamp"))
             if not d:
                 return
             level = msg.get("sleep_level")
             if level is not None:
-                # Convert string level names to numeric codes if SDK decoded them
                 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))
 
-        # ── Proprietary 227: per-minute stress + HR ───────────────────────
-        # field_1 = FIT timestamp, field_2 = heart rate bpm, field_0 = stress
         elif mesg_num == 227:
-            # SDK stores unknown fields as "unknown_N" or by def_num
+            ts_raw = msg.get(1) or msg.get("1") or msg.get("unknown_1")
-            ts_raw = msg.get(1) or msg.get("unknown_1") or msg.get("field_1")
+            hr_raw = msg.get(2) or msg.get("2") or msg.get("unknown_2")
-            hr_raw = msg.get(2) or msg.get("unknown_2") or msg.get("field_2")
+            stress_raw = msg.get(0) or msg.get("0") or msg.get("unknown_0")
-            stress_raw = msg.get(0) or msg.get("unknown_0") or msg.get("field_0")
+            d = _to_date(ts_raw)
-
+            if not d:
-            ts = fit_ts(ts_raw) if isinstance(ts_raw, (int, float)) else (
-                ts_raw if _is_datetime(ts_raw) else None
-            )
-            if not ts:
                 return
-            entry = ensure_day(ts.date())
+            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))
 
-        # ── Proprietary 103: daily totals summary ─────────────────────────
-        # field_253 = timestamp, field_3 = steps, field_4 = floors, field_5/7 = cal
         elif mesg_num == 103:
-            ts_v = msg.get(253) or msg.get("timestamp")
+            ts_raw = msg.get(253) or msg.get("253") or msg.get("timestamp")
-            ts = ts_v if _is_datetime(ts_v) else fit_ts(ts_v)
+            d = _to_date(ts_raw)
-            if not ts:
+            if not d:
                 return
-            entry = ensure_day(ts.date())
+            entry = ensure_day(d)
-
+            steps = msg.get(3) or msg.get("3")
-            steps = 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")
-            floors = msg.get(4)
             if floors and isinstance(floors, (int, float)) and floors > 0:
                 f = float(floors)
-                if f > 1000:
+                entry["floors_climbed"] = round(f / 100 if f > 1000 else f, 1)
-                    f = f / 100
+            active_cal = msg.get(5) or msg.get("5")
-                entry["floors_climbed"] = round(f, 1)
-
-            active_cal = 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")
-            total_cal = msg.get(7)
             if total_cal and isinstance(total_cal, (int, float)) and total_cal > 0:
                 entry["total_calories"] = float(total_cal)
 
-        # ── Proprietary 211: resting HR + HRV summary ─────────────────────
         elif mesg_num == 211:
-            ts_v = msg.get(253) or msg.get("timestamp")
+            ts_raw = msg.get(253) or msg.get("253") or msg.get("timestamp")
-            ts = ts_v if _is_datetime(ts_v) else fit_ts(ts_v)
+            d = _to_date(ts_raw)
-            if not ts:
+            if not d:
                 return
-            entry = ensure_day(ts.date())
+            entry = ensure_day(d)
-
+            rhr = msg.get(0) or msg.get("0")
-            rhr = 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")
-            hrv = msg.get(1)
             if hrv and isinstance(hrv, (int, float)) and 5 < hrv < 300:
                 entry["hrv_nightly_avg"] = float(hrv)
 
-        # ── Proprietary 55: activity accumulation snapshots ───────────────
         elif mesg_num == 55:
-            ts_v = msg.get(253) or msg.get("timestamp")
+            ts_raw = msg.get(253) or msg.get("253") or msg.get("timestamp")
-            ts = ts_v if _is_datetime(ts_v) else fit_ts(ts_v)
+            d = _to_date(ts_raw)
-            if not ts:
+            if not d:
                 return
-            entry = ensure_day(ts.date())
+            entry = ensure_day(d)
-
+            steps = msg.get(2) or msg.get("2")
-            steps = 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")
-            hr = msg.get(19)
             if hr and isinstance(hr, (int, float)) and 20 < hr < 250:
                 entry["heart_rates"].append(int(hr))
 
-    # Decode the file
     try:
         stream = Stream.from_file(file_path)
         decoder = Decoder(stream)
@@ -254,16 +193,15 @@ def parse_wellness_fit(file_path: str) -> dict:
             apply_scale_and_offset=True,
             convert_datetimes_to_dates=True,
             convert_types_to_strings=True,
-            enable_crc_check=False,   # wellness files sometimes have bad CRCs
+            enable_crc_check=False,
             expand_sub_fields=True,
             expand_components=True,
-            merge_heart_rates=True,
+            merge_heart_rates=False,
             mesg_listener=listener,
         )
     except Exception as e:
         return {"error": str(e), "days": {}}
 
-    # Aggregate per-day
     result = {}
     for day_date, data in daily.items():
         hrs = data.pop("heart_rates", [])
@@ -276,7 +214,6 @@ def parse_wellness_fit(file_path: str) -> dict:
         avg_stress = round(sum(s for s in stresses if s >= 0) / len(stresses), 1) if stresses else None
         spo2_avg = round(sum(spo2s) / len(spo2s), 1) if spo2s else None
 
-        # Sleep stage seconds (each level record = 30s epoch)
         if sleep_levels:
             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
@@ -306,4 +243,4 @@ def parse_wellness_fit(file_path: str) -> dict:
             "sleep_awake_s": sleep_awake_s,
         }
 
-    return {"days": result, "error": None}
+    return {"days": result, "error": None}

backend/requirements.txt

@@ -13,7 +13,6 @@ httpx==0.27.0
 redis[hiredis]==5.0.4
 celery[redis]==5.4.0
 garmin-fit-sdk==21.195.0
-fitparse==1.2.0
 gpxpy==1.6.2
 numpy==1.26.4
 scipy==1.13.0
@@ -23,4 +22,4 @@ Pillow==10.3.0
 aiofiles==23.2.1
 python-dateutil==2.9.0
 pytz==2024.1
-psycopg2-binary==2.9.9
+psycopg2-binary==2.9.9