Remove fitparse entirely - use Garmin SDK only with messages dict approach
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This commit is contained in:
2026-06-06 19:17:51 +01:00
parent e9811d8d83
commit f609931ebc
3 changed files with 119 additions and 208 deletions
+63 -126
View File
@@ -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]:
"""Convert FIT timestamp to UTC datetime."""
if seconds is None:
def _fit_ts(raw) -> Optional[datetime]:
if raw is None:
return None
try:
s = int(seconds)
if s == 0 or s == 0xFFFFFFFF:
s = int(raw)
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:
return isinstance(v, datetime)
def _to_date(val) -> Optional[date]:
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:
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
daily = {}
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 == 148:
d = get_date(msg, "timestamp", "local_timestamp")
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))
# ── 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("unknown_1") or msg.get("field_1")
hr_raw = msg.get(2) or msg.get("unknown_2") or msg.get("field_2")
stress_raw = msg.get(0) or msg.get("unknown_0") or msg.get("field_0")
ts = fit_ts(ts_raw) if isinstance(ts_raw, (int, float)) else (
ts_raw if _is_datetime(ts_raw) else None
)
if not ts:
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(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 = ts_v if _is_datetime(ts_v) else fit_ts(ts_v)
if not ts:
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(ts.date())
steps = msg.get(3)
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)
floors = msg.get(4) or msg.get("4")
if floors and isinstance(floors, (int, float)) and floors > 0:
f = float(floors)
if f > 1000:
f = f / 100
entry["floors_climbed"] = round(f, 1)
active_cal = msg.get(5)
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)
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)
# ── Proprietary 211: resting HR + HRV summary ─────────────────────
elif mesg_num == 211:
ts_v = msg.get(253) or msg.get("timestamp")
ts = ts_v if _is_datetime(ts_v) else fit_ts(ts_v)
if not ts:
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(ts.date())
rhr = msg.get(0)
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)
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)
# ── Proprietary 55: activity accumulation snapshots ───────────────
elif mesg_num == 55:
ts_v = msg.get(253) or msg.get("timestamp")
ts = ts_v if _is_datetime(ts_v) else fit_ts(ts_v)
if not ts:
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(ts.date())
steps = msg.get(2)
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)
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))
# 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}