Files
GarminHealthLab/backend/db.py
ericwyuan c70e7ced80 feat(api): 个人资料/单位/同步偏好 + 运动详情 + 身体年龄
设置 (services/settings.py, routes/settings.py)
- user_settings 表:身高/体重/出生日期/性别/单位/自动同步开关/同步频率/历史范围
- GET|PUT /api/settings,GET /api/settings/options(取值由后端给,前端不臆造)
- GET /api/settings/rating-basis:把每条参考区间的来源公开出来。
  一个把数字标成「偏低」的区间是在下判断,用户有权看到依据。

运动详情 (services/garmin.py)
- GET /api/garmin/activities/<id>/detail:概览/分段/心率区间/天气/装备/采样曲线
- 首次打开回源 Garmin 并落库,之后走缓存;?refresh=1 强制刷新
- 采样点在写入时抽稀到 300,手机图表画不了更多,也免得整行撑大

身体年龄 (services/fitness_age.py)
- 0.2.8 版 garminconnect 没有 fitnessage 接口,改为本地按公开常模推算:
  VO₂max 对应年龄为基准,静息心率与 BMI 做有上限的修正
- 返回每一步的中间值,界面照实展示,不做成一个不可追溯的分数
- 高于参考表最年轻一档时按 20 岁计——那里外推会得到「11 岁」这种结果

调度器改为每 5 分钟 tick,是否该同步按各账号自己的频率判断

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
2026-08-24 00:26:26 +08:00

436 lines
13 KiB
Python

"""
Pluggable data layer for Garmin Health Lab.
Supports both SQLite (stdlib, local dev) and MariaDB (PyMySQL, NAS production)
through a single unified API:
init_db() -> create tables if missing
execute(sql, params) -> INSERT/UPDATE/DELETE, returns {id, changes}
query_one(sql, params) -> one row as dict or None
query_all(sql, params) -> list of row dicts
Both backends accept `?` placeholders; the SQL is translated to `%s` for
MariaDB automatically. Upserts must use backend-specific SQL (see services).
"""
import os
import sqlite3
import threading
import queue
import datetime
from config import (
DB_TYPE,
SQLITE_PATH,
MARIADB_SOCKET,
MARIADB_HOST,
MARIADB_PORT,
MARIADB_USER,
MARIADB_PASSWORD,
MARIADB_DATABASE,
)
SCHEMA = """
CREATE TABLE IF NOT EXISTS users (
id VARCHAR(64) PRIMARY KEY,
email VARCHAR(255) NOT NULL UNIQUE,
garmin_email VARCHAR(255) NOT NULL,
garmin_password_hash TEXT NOT NULL,
jwt_token TEXT,
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
updated_at DATETIME DEFAULT CURRENT_TIMESTAMP
);
CREATE TABLE IF NOT EXISTS health_data (
id VARCHAR(64) PRIMARY KEY,
user_id VARCHAR(64) NOT NULL,
date DATE NOT NULL,
steps INT,
heart_rate INT,
heart_rate_variability DOUBLE,
blood_pressure_systolic INT,
blood_pressure_diastolic INT,
sleep_duration INT,
sleep_quality DOUBLE,
stress INT,
calories_burned DOUBLE,
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
updated_at DATETIME DEFAULT CURRENT_TIMESTAMP,
UNIQUE(user_id, date),
FOREIGN KEY (user_id) REFERENCES users(id)
);
CREATE TABLE IF NOT EXISTS activities (
id VARCHAR(64) PRIMARY KEY,
user_id VARCHAR(64) NOT NULL,
activity_type VARCHAR(255) NOT NULL,
start_time DATETIME NOT NULL,
end_time DATETIME NOT NULL,
duration INT,
distance DOUBLE,
calories DOUBLE,
heart_rate_average INT,
heart_rate_max INT,
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
FOREIGN KEY (user_id) REFERENCES users(id)
);
CREATE TABLE IF NOT EXISTS sync_status (
user_id VARCHAR(64) PRIMARY KEY,
last_sync_time DATETIME,
status VARCHAR(32) DEFAULT 'idle',
last_error TEXT,
records_synced INT DEFAULT 0,
updated_at DATETIME DEFAULT CURRENT_TIMESTAMP,
FOREIGN KEY (user_id) REFERENCES users(id)
);
-- Garmin OAuth tokens, obtained once through an interactive login.
-- Garmin accounts with two-factor auth cannot be logged into unattended: the
-- library asks for an MFA code on stdin, which a gunicorn worker does not
-- have. Storing the resulting tokens lets every later sync skip the login
-- entirely (they stay valid for roughly a year).
CREATE TABLE IF NOT EXISTS garmin_tokens (
user_id VARCHAR(64) PRIMARY KEY,
token TEXT NOT NULL,
garmin_email VARCHAR(255),
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
updated_at DATETIME DEFAULT CURRENT_TIMESTAMP,
FOREIGN KEY (user_id) REFERENCES users(id)
);
-- Badges earned on Garmin Connect ("奖励"). Keyed by Garmin's own badge id so
-- a re-sync updates rather than duplicates.
CREATE TABLE IF NOT EXISTS badges (
id VARCHAR(64) NOT NULL,
user_id VARCHAR(64) NOT NULL,
badge_key VARCHAR(128),
name VARCHAR(255),
category_id INT,
difficulty_id INT,
earned_date DATETIME,
earned_count INT,
points INT,
PRIMARY KEY (user_id, id),
FOREIGN KEY (user_id) REFERENCES users(id)
);
-- Personal records (个人纪录), e.g. fastest 5k, longest run.
CREATE TABLE IF NOT EXISTS personal_records (
id VARCHAR(64) NOT NULL,
user_id VARCHAR(64) NOT NULL,
type_id INT,
activity_id VARCHAR(64),
activity_name VARCHAR(255),
activity_type VARCHAR(64),
value DOUBLE,
achieved_at DATETIME,
PRIMARY KEY (user_id, id),
FOREIGN KEY (user_id) REFERENCES users(id)
);
-- Coordination for work that must happen once per interval regardless of how
-- many gunicorn workers are running. A worker claims a job by writing its
-- row, and the others see a fresh claim and stand down. Without this the
-- hourly sync would fire once per worker.
CREATE TABLE IF NOT EXISTS job_locks (
name VARCHAR(64) PRIMARY KEY,
holder VARCHAR(64),
claimed_at DATETIME,
last_run_at DATETIME
);
-- Rendezvous for the interactive MFA login.
-- garth asks for the code through a *blocking* callback, so the login parks in
-- a background thread while the code arrives in a separate HTTP request that
-- may land on a different gunicorn worker. The handoff therefore goes through
-- the database rather than process memory.
-- Holds no password: that stays in the waiting thread's memory only.
CREATE TABLE IF NOT EXISTS garmin_mfa_sessions (
id VARCHAR(64) PRIMARY KEY,
user_id VARCHAR(64) NOT NULL,
status VARCHAR(32) NOT NULL,
code VARCHAR(16),
error TEXT,
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
updated_at DATETIME DEFAULT CURRENT_TIMESTAMP,
FOREIGN KEY (user_id) REFERENCES users(id)
);
-- Per-user profile and preferences.
-- Height/weight/birth date/sex are here rather than on `users` because they
-- are body measurements the owner edits over time, not identity; and because
-- the rating bands and the fitness-age estimate need them, an account without
-- them still works, just with fewer personalised readings.
CREATE TABLE IF NOT EXISTS user_settings (
user_id VARCHAR(64) PRIMARY KEY,
height_cm DOUBLE,
weight_kg DOUBLE,
birth_date DATE,
sex VARCHAR(16),
units VARCHAR(16),
auto_sync INT,
auto_sync_minutes INT,
history_days INT,
updated_at DATETIME,
FOREIGN KEY (user_id) REFERENCES users(id)
);
-- Full detail for one activity, exactly as Garmin returned it.
-- The list view stores only the summary columns; opening an activity needs
-- laps, heart-rate zones and the sampled series, which are far too large to
-- carry on every list request. Fetched on demand and kept, so the second
-- visit costs nothing and works offline.
CREATE TABLE IF NOT EXISTS activity_details (
activity_id VARCHAR(64) PRIMARY KEY,
user_id VARCHAR(64) NOT NULL,
payload MEDIUMTEXT,
fetched_at DATETIME,
FOREIGN KEY (user_id) REFERENCES users(id)
);
-- One cached LLM answer per user. Generating one takes minutes against a
-- large reasoning model, which is far too slow to sit in a page load, so the
-- result is stored and reused until the underlying data changes.
-- `fingerprint` identifies the health data the advice was derived from.
CREATE TABLE IF NOT EXISTS ai_recommendations (
user_id VARCHAR(64) PRIMARY KEY,
fingerprint VARCHAR(64) NOT NULL,
model VARCHAR(64),
upstream VARCHAR(64),
days INT,
payload TEXT NOT NULL,
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
FOREIGN KEY (user_id) REFERENCES users(id)
);
"""
# --- MariaDB pool (lazy) ----------------------------------------------------
_mariadb_pool = None
_pool_lock = threading.Lock()
def _new_mariadb_conn():
import pymysql
from pymysql.cursors import DictCursor
kwargs = dict(
user=MARIADB_USER,
password=MARIADB_PASSWORD,
database=MARIADB_DATABASE,
charset="utf8mb4",
autocommit=True,
cursorclass=DictCursor,
connect_timeout=10,
)
if MARIADB_SOCKET:
kwargs["unix_socket"] = MARIADB_SOCKET
else:
kwargs["host"] = MARIADB_HOST
kwargs["port"] = MARIADB_PORT
return pymysql.connect(**kwargs)
def _mariadb_acquire():
global _mariadb_pool
if _mariadb_pool is None:
with _pool_lock:
if _mariadb_pool is None:
_mariadb_pool = queue.Queue(maxsize=10)
for _ in range(10):
_mariadb_pool.put(_new_mariadb_conn())
try:
return _mariadb_pool.get(block=False)
except queue.Empty:
return _new_mariadb_conn()
def _mariadb_release(conn):
try:
conn.ping(reconnect=False)
_mariadb_pool.put(conn)
except Exception:
try:
conn.close()
except Exception:
pass
# --- SQLite connection ------------------------------------------------------
def _sqlite_connect():
data_dir = os.path.dirname(SQLITE_PATH)
if data_dir and not os.path.exists(data_dir):
os.makedirs(data_dir, exist_ok=True)
conn = sqlite3.connect(SQLITE_PATH, isolation_level=None)
conn.row_factory = sqlite3.Row
conn.execute("PRAGMA foreign_keys = ON")
return conn
def _connect():
if DB_TYPE == "mariadb":
return _mariadb_acquire()
return _sqlite_connect()
def _disconnect(conn):
if DB_TYPE == "mariadb":
_mariadb_release(conn)
else:
conn.close()
def _adapt_sql(sql):
# pymysql uses %s placeholders; sqlite3 uses ?. Business code writes ?.
return sql.replace("?", "%s") if DB_TYPE == "mariadb" else sql
def _serialize(value):
if value is None:
return None
if isinstance(value, (datetime.datetime, datetime.date)):
return value.isoformat()
return value
def _row_to_dict(row):
if row is None:
return None
if isinstance(row, dict):
return {k: _serialize(v) for k, v in row.items()}
return {k: _serialize(row[k]) for k in row.keys()}
# Columns added after the first release. `CREATE TABLE IF NOT EXISTS` does
# nothing to a table that already exists, so new metrics need an explicit
# additive migration or they silently never appear in production.
MIGRATIONS = {
"sync_status": [
# A full backfill runs for many minutes, so the UI needs to show how
# far along it is rather than an indefinite spinner.
("progress_current", "INT"),
("progress_total", "INT"),
("started_at", "DATETIME"),
],
"health_data": [
# activity / energy
("distance_meters", "DOUBLE"),
("active_calories", "DOUBLE"),
("bmr_calories", "DOUBLE"),
("floors_ascended", "DOUBLE"),
("floors_descended", "DOUBLE"),
("intensity_minutes", "INT"),
("step_goal", "INT"),
("sedentary_seconds", "INT"),
("active_seconds", "INT"),
# heart / stress
("heart_rate_max", "INT"),
("heart_rate_min", "INT"),
("stress_max", "INT"),
# body battery
("body_battery_high", "INT"),
("body_battery_low", "INT"),
("body_battery_charged", "INT"),
("body_battery_drained", "INT"),
# breathing / blood oxygen
("spo2_avg", "DOUBLE"),
("spo2_min", "INT"),
("respiration_avg", "DOUBLE"),
("respiration_min", "DOUBLE"),
("respiration_max", "DOUBLE"),
# sleep detail
("sleep_deep_seconds", "INT"),
("sleep_light_seconds", "INT"),
("sleep_rem_seconds", "INT"),
("sleep_awake_seconds", "INT"),
("sleep_spo2_avg", "DOUBLE"),
("sleep_respiration_avg", "DOUBLE"),
("sleep_stress_avg", "DOUBLE"),
# training
("training_readiness", "INT"),
("vo2max", "DOUBLE"),
("endurance_score", "INT"),
],
}
def _existing_columns(cur, table):
if DB_TYPE == "mariadb":
cur.execute(
"SELECT COLUMN_NAME FROM information_schema.COLUMNS "
"WHERE TABLE_SCHEMA = DATABASE() AND TABLE_NAME = %s",
[table],
)
return {r["COLUMN_NAME"] if isinstance(r, dict) else r[0] for r in cur.fetchall()}
cur.execute(f"PRAGMA table_info({table})")
return {row[1] for row in cur.fetchall()}
def _migrate(cur):
for table, columns in MIGRATIONS.items():
present = _existing_columns(cur, table)
for name, coltype in columns:
if name in present:
continue
# SQLite has no "ADD COLUMN IF NOT EXISTS"; the membership check
# above is what keeps this idempotent on both backends.
cur.execute(f"ALTER TABLE {table} ADD COLUMN {name} {coltype}")
# --- Public API -------------------------------------------------------------
def _statements(schema):
"""Split a schema script into statements.
Comments are stripped first: splitting the raw text on ';' would cut a
comment that happens to contain one in half and hand the remainder to the
database as SQL.
"""
lines = [ln for ln in schema.splitlines() if not ln.strip().startswith("--")]
for stmt in "\n".join(lines).split(";"):
stmt = stmt.strip()
if stmt:
yield stmt
def init_db():
conn = _connect()
try:
cur = conn.cursor()
for stmt in _statements(SCHEMA):
cur.execute(_adapt_sql(stmt))
_migrate(cur)
finally:
_disconnect(conn)
def execute(sql, params=None):
params = params or []
conn = _connect()
try:
cur = conn.cursor()
cur.execute(_adapt_sql(sql), params)
return {"id": cur.lastrowid, "changes": cur.rowcount}
finally:
_disconnect(conn)
def query_one(sql, params=None):
params = params or []
conn = _connect()
try:
cur = conn.cursor()
cur.execute(_adapt_sql(sql), params)
return _row_to_dict(cur.fetchone())
finally:
_disconnect(conn)
def query_all(sql, params=None):
params = params or []
conn = _connect()
try:
cur = conn.cursor()
cur.execute(_adapt_sql(sql), params)
return [_row_to_dict(r) for r in cur.fetchall()]
finally:
_disconnect(conn)