Initial Commit
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"""
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Background tasks: activity ingestion, route matching, PR calculation.
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"""
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import asyncio
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from celery import Celery
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from app.core.config import settings
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celery_app = Celery(
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"fittracker",
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broker=settings.redis_url,
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backend=settings.redis_url,
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)
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celery_app.conf.update(
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task_serializer="json",
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result_serializer="json",
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accept_content=["json"],
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timezone="UTC",
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enable_utc=True,
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task_track_started=True,
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worker_prefetch_multiplier=1,
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)
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def run_async(coro):
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loop = asyncio.new_event_loop()
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try:
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return loop.run_until_complete(coro)
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finally:
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loop.close()
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@celery_app.task(bind=True, name="process_activity_file")
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def process_activity_file(self, file_path: str, user_id: int, source_type: str):
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"""Parse a FIT/GPX file and insert activity + data points into DB."""
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from app.services.fit_parser import parse_fit_file, parse_gpx_file, calculate_hr_zones
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from app.services.route_matcher import compute_best_splits, routes_are_similar
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from app.core.database import AsyncSessionLocal
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from app.models.user import Activity, ActivityDataPoint, ActivityLap, PersonalRecord, HealthMetric
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from sqlalchemy import select
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from datetime import datetime, timezone
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self.update_state(state="PROGRESS", meta={"step": "parsing"})
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try:
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if source_type == "fit" or file_path.endswith(".fit"):
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parsed = parse_fit_file(file_path)
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else:
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parsed = parse_gpx_file(file_path)
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except Exception as e:
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raise self.retry(exc=e, countdown=10, max_retries=3)
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async def _insert():
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async with AsyncSessionLocal() as db:
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# Check for duplicate
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if parsed.get("garmin_activity_id"):
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existing = await db.execute(
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select(Activity).where(
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Activity.garmin_activity_id == parsed["garmin_activity_id"]
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)
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)
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if existing.scalar_one_or_none():
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return None
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# HR zones
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hr_zones = calculate_hr_zones(
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parsed.get("data_points", []),
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parsed.get("max_heart_rate") or 190
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)
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# Create activity
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start_time = datetime.fromisoformat(parsed["start_time"]) if parsed.get("start_time") else None
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activity = Activity(
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user_id=user_id,
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name=parsed["name"],
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sport_type=parsed["sport_type"],
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start_time=start_time,
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distance_m=parsed.get("distance_m"),
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duration_s=parsed.get("duration_s"),
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elevation_gain_m=parsed.get("elevation_gain_m"),
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elevation_loss_m=parsed.get("elevation_loss_m"),
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avg_heart_rate=parsed.get("avg_heart_rate"),
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max_heart_rate=parsed.get("max_heart_rate"),
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avg_cadence=parsed.get("avg_cadence"),
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avg_power=parsed.get("avg_power"),
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normalized_power=parsed.get("normalized_power"),
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avg_speed_ms=parsed.get("avg_speed_ms"),
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max_speed_ms=parsed.get("max_speed_ms"),
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avg_temperature_c=parsed.get("avg_temperature_c"),
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calories=parsed.get("calories"),
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training_stress_score=parsed.get("training_stress_score"),
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polyline=parsed.get("polyline"),
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bounding_box=parsed.get("bounding_box"),
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source_file=file_path,
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source_type=parsed.get("source_type"),
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hr_zones=hr_zones,
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)
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db.add(activity)
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await db.flush()
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# Insert data points in batches
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points = parsed.get("data_points", [])
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batch_size = 500
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for i in range(0, len(points), batch_size):
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batch = points[i:i+batch_size]
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db.add_all([
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ActivityDataPoint(
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activity_id=activity.id,
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timestamp=datetime.fromisoformat(p["timestamp"]) if p.get("timestamp") else None,
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latitude=p.get("latitude"),
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longitude=p.get("longitude"),
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altitude_m=p.get("altitude_m"),
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heart_rate=p.get("heart_rate"),
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cadence=p.get("cadence"),
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speed_ms=p.get("speed_ms"),
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power=p.get("power"),
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temperature_c=p.get("temperature_c"),
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distance_m=p.get("distance_m"),
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)
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for p in batch
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])
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# Insert laps
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for lap in parsed.get("laps", []):
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ls = datetime.fromisoformat(lap["start_time"]) if lap.get("start_time") else None
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db.add(ActivityLap(
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activity_id=activity.id,
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lap_number=lap["lap_number"],
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start_time=ls,
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duration_s=lap.get("duration_s"),
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distance_m=lap.get("distance_m"),
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avg_heart_rate=lap.get("avg_heart_rate"),
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avg_cadence=lap.get("avg_cadence"),
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avg_speed_ms=lap.get("avg_speed_ms"),
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avg_power=lap.get("avg_power"),
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))
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await db.commit()
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return activity.id
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activity_id = run_async(_insert())
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if activity_id:
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# Queue PR calculation
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compute_personal_records.delay(activity_id, user_id, parsed)
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return {"activity_id": activity_id, "status": "ok"}
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@celery_app.task(name="compute_personal_records")
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def compute_personal_records(activity_id: int, user_id: int, parsed: dict):
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"""Calculate personal records for standard distances from this activity."""
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from app.services.route_matcher import compute_best_splits, STANDARD_DISTANCES
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from app.core.database import AsyncSessionLocal
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from app.models.user import PersonalRecord
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from sqlalchemy import select
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from datetime import datetime, timezone
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data_points = parsed.get("data_points", [])
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total_dist = parsed.get("distance_m", 0) or 0
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sport = parsed.get("sport_type", "running")
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start_time_str = parsed.get("start_time")
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start_time = datetime.fromisoformat(start_time_str) if start_time_str else datetime.now(timezone.utc)
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best_splits = compute_best_splits(data_points, total_dist)
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async def _save():
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async with AsyncSessionLocal() as db:
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for label, duration_s in best_splits.items():
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dist_m = next((d for d, l in STANDARD_DISTANCES if l == label), None)
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if dist_m is None:
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continue
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# Check existing record
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existing = await db.execute(
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select(PersonalRecord).where(
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PersonalRecord.user_id == user_id,
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PersonalRecord.sport_type == sport,
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PersonalRecord.distance_m == dist_m,
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PersonalRecord.is_current_record == True,
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)
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)
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current = existing.scalar_one_or_none()
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if current is None or duration_s < current.duration_s:
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if current:
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current.is_current_record = False
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db.add(PersonalRecord(
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user_id=user_id,
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activity_id=activity_id,
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sport_type=sport,
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distance_m=dist_m,
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distance_label=label,
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duration_s=duration_s,
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achieved_at=start_time,
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is_current_record=True,
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))
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await db.commit()
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run_async(_save())
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@celery_app.task(name="process_garmin_health_zip")
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def process_garmin_health_zip(zip_path: str, user_id: int):
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"""
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Process a Garmin Connect data export zip.
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Extracts wellness/sleep/HRV CSV files and inserts health metrics.
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"""
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import zipfile
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import json
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import csv
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from pathlib import Path
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from app.core.database import AsyncSessionLocal
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from app.models.user import HealthMetric
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from sqlalchemy.dialects.postgresql import insert
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from datetime import datetime, timezone
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async def _process():
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async with AsyncSessionLocal() as db:
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with zipfile.ZipFile(zip_path) as zf:
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names = zf.namelist()
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# Parse daily summary JSON files from Garmin export
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for name in names:
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if "DailyMetrics" in name and name.endswith(".json"):
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with zf.open(name) as f:
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try:
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data = json.load(f)
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except Exception:
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continue
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date_str = data.get("calendarDate") or data.get("date")
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if not date_str:
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continue
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try:
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date = datetime.fromisoformat(date_str).replace(tzinfo=timezone.utc)
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except ValueError:
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continue
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metric = HealthMetric(
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user_id=user_id,
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date=date,
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resting_hr=data.get("restingHeartRate"),
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steps=data.get("totalSteps"),
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floors_climbed=data.get("floorsAscended"),
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active_calories=data.get("activeKilocalories"),
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total_calories=data.get("totalKilocalories"),
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avg_stress=data.get("averageStressLevel"),
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spo2_avg=data.get("avgSpo2"),
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)
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db.add(metric)
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await db.commit()
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run_async(_process())
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