审计 57 个接口后,把账号里真有数据却从未入库的部分补上。全部走同步模块, 界面只读本地库。 新增数据 - 体重与身体成分(体脂率/肌肉量/体水分/骨量/内脏脂肪/代谢年龄) - 血压(接口通,账号暂无记录) - 跑步成绩预测(5 公里 / 10 公里 / 半马 / 全马) - 爬坡分、饮水量、出汗量 → health_data 新增七列 - 全天曲线:心率 / 压力 / 身体电量 / 呼吸 / 血氧 - 挑战赛(徽章挑战与好友挑战,与一次性的徽章不同,有周期和进度) - 已配对设备 新增界面 - /body/ 身体成分:体重大数字 + BMI 分级 + 体脂肌肉曲线 + 血压表格 - /race/ 成绩预测:四个距离的预测成绩与配速,以及预测随时间的变化 - /challenges/ 挑战赛:按类型筛选,有目标的显示进度条 - /devices/ 已配对设备 - 每日页新增「全天曲线」,这是存日内采样的主要目的 - 健康页新增「身体成分」分组与「更多」入口,运动页加挑战赛与成绩预测入口 同步开销 - 日内曲线每天五个请求,14 天以内的同步顺带拉,更长的历史交给后台 「补齐详细数据」,否则一年的同步会多出约 1800 个请求 - 原来的「补齐运动详情」扩展为统一的补齐任务,分阶段上报进度 日内采样抽稀到每天 240 点:手机图表分辨不出更多,只会把行撑大。 全量 446 项测试通过。 Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
450 lines
16 KiB
Python
450 lines
16 KiB
Python
"""
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The rest of what Garmin holds.
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The original sync covered daily totals, activities, badges and personal
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records — 16 of the library's 57 endpoints. Everything here is data the
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account actually has that was simply never being stored: body composition,
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hill score, race predictions, hydration, the within-day sample series, and
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challenges and devices.
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All of it lands in the local database during a sync, so no screen ever has to
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reach Garmin to draw itself.
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"""
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import datetime
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import json
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from db import execute, query_one, query_all
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from config import DB_TYPE
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# --- small helpers -----------------------------------------------------------
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def _num(*values):
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for v in values:
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if v is None or v == "":
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continue
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try:
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return float(v)
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except (TypeError, ValueError):
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continue
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return None
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def _int(*values):
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n = _num(*values)
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return int(n) if n is not None else None
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def _safe(fn, default=None):
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try:
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return fn()
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except Exception: # noqa: BLE001 - a missing feature must not fail a sync
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return default
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def _day(value):
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"""Garmin dates arrive as ISO strings, epoch millis, or already-dates."""
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if value is None or value == "":
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return None
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if isinstance(value, datetime.date):
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return value.isoformat()
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text = str(value)
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if text.isdigit():
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seconds = int(text) / (1000 if len(text) > 10 else 1)
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return datetime.datetime.utcfromtimestamp(seconds).date().isoformat()
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return text[:10]
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def _stamp(value):
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if value is None or value == "":
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return None
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text = str(value)
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if text.isdigit():
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seconds = int(text) / (1000 if len(text) > 10 else 1)
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return datetime.datetime.utcfromtimestamp(seconds).isoformat(timespec="seconds")
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return text.replace("T", " ")[:19]
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def _upsert(table, key_cols, cols, values):
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placeholders = ", ".join(["?"] * len(cols))
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updatable = [c for c in cols if c not in key_cols]
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if DB_TYPE == "mariadb":
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updates = ", ".join(f"{c}=VALUES({c})" for c in updatable)
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sql = (f"INSERT INTO {table} ({', '.join(cols)}) VALUES ({placeholders}) "
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f"ON DUPLICATE KEY UPDATE {updates}")
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else:
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conflict = ", ".join(key_cols)
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updates = ", ".join(f"{c}=excluded.{c}" for c in updatable)
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sql = (f"INSERT INTO {table} ({', '.join(cols)}) VALUES ({placeholders}) "
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f"ON CONFLICT({conflict}) DO UPDATE SET {updates}")
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execute(sql, values)
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# --- body composition --------------------------------------------------------
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def sync_body_composition(client, user_id, start, end):
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"""Weight and everything a connected scale reports with it."""
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data = _safe(lambda: client.get_body_composition(start, end), {}) or {}
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rows = data.get("dateWeightList") or []
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stored = 0
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for row in rows:
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date = _day(row.get("calendarDate") or row.get("date"))
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if not date:
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continue
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# Garmin stores weight in grams.
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grams = _num(row.get("weight"))
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_upsert(
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"body_composition", ("user_id", "date"),
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["id", "user_id", "date", "weight_kg", "bmi", "body_fat_pct",
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"body_water_pct", "bone_mass_kg", "muscle_mass_kg",
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"physique_rating", "visceral_fat", "metabolic_age", "source"],
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[f"{user_id}-{date}", user_id, date,
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grams / 1000 if grams else None,
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_num(row.get("bmi")),
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_num(row.get("bodyFat")),
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_num(row.get("bodyWater")),
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(_num(row.get("boneMass")) or 0) / 1000 or None,
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(_num(row.get("muscleMass")) or 0) / 1000 or None,
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_num(row.get("physiqueRating")),
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_num(row.get("visceralFat")),
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_num(row.get("metabolicAge")),
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row.get("sourceType")],
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)
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stored += 1
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return stored
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def get_body_composition(user_id, start=None, end=None):
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sql = "WHERE user_id = ?"
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params = [user_id]
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if start:
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sql += " AND date >= ?"
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params.append(start)
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if end:
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sql += " AND date <= ?"
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params.append(end)
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rows = query_all(
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f"SELECT * FROM body_composition {sql} ORDER BY date ASC", params
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)
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return [{
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"date": str(r["date"])[:10],
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"weightKg": r["weight_kg"],
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"bmi": r["bmi"],
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"bodyFatPct": r["body_fat_pct"],
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"bodyWaterPct": r["body_water_pct"],
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"boneMassKg": r["bone_mass_kg"],
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"muscleMassKg": r["muscle_mass_kg"],
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"physiqueRating": r["physique_rating"],
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"visceralFat": r["visceral_fat"],
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"metabolicAge": r["metabolic_age"],
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} for r in rows]
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# --- blood pressure ----------------------------------------------------------
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def sync_blood_pressure(client, user_id, start, end):
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data = _safe(lambda: client.get_blood_pressure(start, end), {}) or {}
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stored = 0
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for summary in data.get("measurementSummaries") or []:
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for m in summary.get("measurements") or []:
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when = _stamp(m.get("measurementTimestampLocal")
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or m.get("measurementTimestampGMT"))
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if not when:
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continue
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_upsert(
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"blood_pressure", ("user_id", "measured_at"),
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["id", "user_id", "measured_at", "systolic", "diastolic",
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"pulse", "note"],
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[f"{user_id}-{when}", user_id, when,
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_int(m.get("systolic")), _int(m.get("diastolic")),
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_int(m.get("pulse")), m.get("notes")],
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)
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stored += 1
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return stored
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def get_blood_pressure(user_id):
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rows = query_all(
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"SELECT * FROM blood_pressure WHERE user_id = ? ORDER BY measured_at DESC",
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[user_id],
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)
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return [{
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"measuredAt": str(r["measured_at"]),
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"systolic": r["systolic"],
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"diastolic": r["diastolic"],
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"pulse": r["pulse"],
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"note": r["note"],
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} for r in rows]
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# --- race predictions --------------------------------------------------------
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def sync_race_predictions(client, user_id, start=None, end=None):
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data = _safe(lambda: client.get_race_predictions(start, end), None)
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rows = data if isinstance(data, list) else [data] if data else []
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stored = 0
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for row in rows:
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if not isinstance(row, dict):
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continue
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date = _day(row.get("calendarDate") or row.get("fromCalendarDate"))
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if not date:
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continue
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_upsert(
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"race_predictions", ("user_id", "date"),
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["id", "user_id", "date", "time_5k", "time_10k", "time_half",
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"time_marathon"],
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[f"{user_id}-{date}", user_id, date,
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_int(row.get("time5K")), _int(row.get("time10K")),
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_int(row.get("timeHalfMarathon")), _int(row.get("timeMarathon"))],
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)
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stored += 1
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return stored
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def get_race_predictions(user_id, limit=90):
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rows = query_all(
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"SELECT * FROM race_predictions WHERE user_id = ? ORDER BY date DESC",
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[user_id],
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)[:limit]
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return [{
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"date": str(r["date"])[:10],
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"time5k": r["time_5k"],
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"time10k": r["time_10k"],
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"timeHalf": r["time_half"],
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"timeMarathon": r["time_marathon"],
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} for r in reversed(rows)]
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# --- within-day series -------------------------------------------------------
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# Each entry: the API call, and how to pull the [timestamp, value] pairs out of
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# whatever shape that particular endpoint returns. They are all different.
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def _hr_series(data):
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return [[_stamp(t), v] for t, v in (data.get("heartRateValues") or [])
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if v is not None]
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def _stress_series(data):
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return [[_stamp(t), v] for t, v in (data.get("stressValuesArray") or [])
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if v is not None and v >= 0]
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def _battery_series(data):
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out = []
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for entry in data if isinstance(data, list) else [data]:
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for point in (entry or {}).get("bodyBatteryValuesArray") or []:
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# [timestamp, status, level, version]
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if len(point) >= 3 and point[2] is not None:
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out.append([_stamp(point[0]), point[2]])
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return out
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def _respiration_series(data):
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return [[_stamp(t), v] for t, v in (data.get("respirationValuesArray") or [])
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if v is not None and v > 0]
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def _spo2_series(data):
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return [[_stamp(t), v] for t, v in (data.get("spO2HourlyAverages") or [])
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if v is not None]
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SERIES_KINDS = {
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"heartRate": (lambda c, d: c.get_heart_rates(d), _hr_series),
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"stress": (lambda c, d: c.get_all_day_stress(d), _stress_series),
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"bodyBattery": (lambda c, d: c.get_body_battery(d, d), _battery_series),
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"respiration": (lambda c, d: c.get_respiration_data(d), _respiration_series),
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"spo2": (lambda c, d: c.get_spo2_data(d), _spo2_series),
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}
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# A day of heart rate is ~500 samples at 2-minute resolution. More than this
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# cannot be told apart on a phone chart and only inflates the row.
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SERIES_MAX_POINTS = 240
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def _thin(points, limit=SERIES_MAX_POINTS):
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if len(points) <= limit:
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return points
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step = (len(points) - 1) / (limit - 1)
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return [points[int(round(i * step))] for i in range(limit)]
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def sync_daily_series(client, user_id, date, kinds=None):
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"""Store the within-day curves for one day."""
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stored = 0
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now = datetime.datetime.utcnow().isoformat(timespec="seconds")
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for kind, (call, extract) in SERIES_KINDS.items():
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if kinds and kind not in kinds:
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continue
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raw = _safe(lambda: call(client, date))
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if raw is None:
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continue
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points = _safe(lambda: _thin(extract(raw)), []) or []
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if not points:
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continue
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_upsert(
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"daily_series", ("user_id", "date", "kind"),
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["id", "user_id", "date", "kind", "payload", "fetched_at"],
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[f"{user_id}-{date}-{kind}", user_id, date, kind,
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json.dumps(points, default=str), now],
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)
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stored += 1
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return stored
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def get_daily_series(user_id, date):
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rows = query_all(
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"SELECT kind, payload FROM daily_series WHERE user_id = ? AND date = ?",
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[user_id, date],
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)
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out = {}
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for r in rows:
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try:
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out[r["kind"]] = json.loads(r["payload"])
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except (ValueError, TypeError):
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continue
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return out
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# --- challenges --------------------------------------------------------------
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def sync_challenges(client, user_id):
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"""Badge challenges and ad-hoc challenges.
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Distinct from badges: a badge is earned once and sits in a list, while a
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challenge has a period, a target and a standing.
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"""
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execute("DELETE FROM challenges WHERE user_id = ?", [user_id])
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stored = 0
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sources = [
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("badge", lambda: client.get_badge_challenges(1, 100)),
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("adhoc", lambda: client.get_adhoc_challenges(1, 100)),
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("available", lambda: client.get_available_badge_challenges(1, 100)),
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("inprogress", lambda: client.get_inprogress_virtual_challenges(1, 100)),
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]
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for kind, call in sources:
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rows = _safe(call, []) or []
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if isinstance(rows, dict):
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rows = rows.get("challenges") or rows.get("badgeChallenges") or []
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for row in rows:
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if not isinstance(row, dict):
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continue
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uuid = row.get("uuid") or row.get("challengeUuid") or row.get("badgeId")
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name = (row.get("badgeChallengeName") or row.get("adHocChallengeName")
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or row.get("challengeName") or row.get("badgeName"))
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execute(
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"INSERT INTO challenges (id, user_id, challenge_uuid, kind, name, "
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"status, start_date, end_date, payload) VALUES (?,?,?,?,?,?,?,?,?)",
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[f"{user_id}-{kind}-{uuid}-{stored}", user_id, str(uuid or ""),
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kind, name,
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str(row.get("badgeChallengeStatusId")
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or row.get("socialChallengeStatusId") or ""),
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_day(row.get("startDate")), _day(row.get("endDate")),
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json.dumps(row, default=str)],
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)
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stored += 1
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return stored
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def get_challenges(user_id):
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rows = query_all(
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"SELECT * FROM challenges WHERE user_id = ? ORDER BY start_date DESC",
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[user_id],
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)
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out = []
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for r in rows:
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try:
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payload = json.loads(r["payload"]) if r["payload"] else {}
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except (ValueError, TypeError):
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payload = {}
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out.append({
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"uuid": r["challenge_uuid"],
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"kind": r["kind"],
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"name": r["name"],
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"status": r["status"],
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"startDate": str(r["start_date"])[:10] if r["start_date"] else None,
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"endDate": str(r["end_date"])[:10] if r["end_date"] else None,
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"payload": payload,
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})
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return out
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# --- devices -----------------------------------------------------------------
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def sync_devices(client, user_id):
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devices = _safe(lambda: client.get_devices(), []) or []
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if isinstance(devices, dict):
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devices = [devices]
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execute("DELETE FROM devices WHERE user_id = ?", [user_id])
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last_used = _safe(lambda: client.get_device_last_used(), {}) or {}
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stored = 0
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for d in devices:
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if not isinstance(d, dict):
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continue
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device_id = str(d.get("deviceId") or d.get("unitId") or stored)
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execute(
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"INSERT INTO devices (id, user_id, device_id, name, model, serial, "
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"software_version, last_used_at, payload) VALUES (?,?,?,?,?,?,?,?,?)",
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[f"{user_id}-{device_id}", user_id, device_id,
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d.get("displayName") or d.get("productDisplayName"),
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d.get("productDisplayName") or d.get("partNumber"),
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str(d.get("serialNumber") or ""),
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str(d.get("softwareVersion") or ""),
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_stamp(last_used.get("lastUsedDeviceUploadTime"))
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if str(last_used.get("userDeviceId") or "") == device_id else None,
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json.dumps(d, default=str)],
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)
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stored += 1
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return stored
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def get_devices(user_id):
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rows = query_all("SELECT * FROM devices WHERE user_id = ?", [user_id])
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return [{
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"deviceId": r["device_id"],
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"name": r["name"],
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"model": r["model"],
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"serial": r["serial"],
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"softwareVersion": r["software_version"],
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"lastUsedAt": str(r["last_used_at"]) if r["last_used_at"] else None,
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} for r in rows]
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# --- per-day extras folded into health_data ----------------------------------
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def daily_extras(client, date):
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"""Hill score, hydration and weight for one day.
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Returned as columns to merge into the day's health_data row rather than
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stored separately — they are daily scalars like every other metric there.
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"""
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out = {}
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hydration = _safe(lambda: client.get_hydration_data(date), {}) or {}
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out["hydrationMl"] = _int(hydration.get("valueInML"))
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out["hydrationGoalMl"] = _int(hydration.get("goalInML"))
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out["sweatLossMl"] = _int(hydration.get("sweatLossInML"))
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hill = _safe(lambda: client.get_hill_score(date, date), {}) or {}
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scores = hill.get("hillScoreDTOList") or []
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if scores:
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out["hillScore"] = _int(scores[-1].get("overallScore"))
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else:
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out["hillScore"] = _int(hill.get("periodAvgScore"))
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weigh = _safe(lambda: client.get_daily_weigh_ins(date), {}) or {}
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summaries = weigh.get("dateWeightList") or []
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if summaries:
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grams = _num(summaries[-1].get("weight"))
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out["weightKg"] = grams / 1000 if grams else None
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out["bmi"] = _num(summaries[-1].get("bmi"))
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out["bodyFatPct"] = _num(summaries[-1].get("bodyFat"))
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return {k: v for k, v in out.items() if v is not None}
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