原来每天只存 7 个指标,而 get_user_summary 一次就返回 60+ 字段, 另有睡眠分期、训练准备度、耐力分等独立端点从未被调用。 db.py: - health_data 新增 31 列(距离/活动卡路里/基础代谢/爬楼/强度分钟/ 久坐时长/最高最低心率/最大压力/身体电量四项/血氧/呼吸/ 睡眠深浅REM清醒分期/睡眠血氧/睡眠呼吸/睡眠压力/训练准备度/ VO2max/耐力分) - 新增 badges 与 personal_records 两张表,均以 (user_id, garmin_id) 为主键,重复同步更新而非累积 - 新增增量迁移: CREATE TABLE IF NOT EXISTS 对已存在的表不生效, 新列必须显式 ALTER,否则生产库上永远不会出现。按列名比对后 逐个补齐,SQLite 与 MariaDB 都幂等 services/garmin.py: - _extract_daily 改为汇总 user_summary + sleep + hrv + training_readiness + training_status + endurance_score 五个端点 - 每个可选端点用 _safe 包裹:某项设备不记录时留 NULL,不影响当天其余数据 - 新增 sync_badges / sync_personal_records(账号级,每次同步取一次) fix(garmin): 个人纪录整批写入失败 - Garmin 在同一份数据里混用 ISO 字符串和 Unix 毫秒时间戳, prStartTimeGmt 是 1570961412000,写进 DATETIME 列被 MariaDB 以 1292 拒绝,导致 11 项个人纪录一条都没存进去 - 新增 _to_datetime 统一处理 ISO / 毫秒 / 秒三种形状,并优先取 Garmin 自己提供的 *Formatted 字段 services/ai.py: - 送给模型的 CSV 从 7 列扩到 23 列,纳入身体电量、血氧、呼吸、 训练准备度、耐力分和睡眠分期 接口: GET /api/health/badges、/api/health/personal-records tests (+13, 共 292): - 徽章/纪录的往返、重复同步不累积、按用户隔离 - 两个用户可持有同一个 Garmin 徽章 id 而不冲突 - 时间戳三种形状的归一化及无效值不抛异常 NAS 实测: 7 天数据每天 31 项指标、65 个奖励、11 项个人纪录 Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
375 lines
11 KiB
Python
375 lines
11 KiB
Python
"""
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Pluggable data layer for Garmin Health Lab.
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Supports both SQLite (stdlib, local dev) and MariaDB (PyMySQL, NAS production)
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through a single unified API:
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init_db() -> create tables if missing
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execute(sql, params) -> INSERT/UPDATE/DELETE, returns {id, changes}
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query_one(sql, params) -> one row as dict or None
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query_all(sql, params) -> list of row dicts
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Both backends accept `?` placeholders; the SQL is translated to `%s` for
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MariaDB automatically. Upserts must use backend-specific SQL (see services).
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"""
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import os
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import sqlite3
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import threading
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import queue
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import datetime
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from config import (
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DB_TYPE,
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SQLITE_PATH,
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MARIADB_SOCKET,
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MARIADB_HOST,
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MARIADB_PORT,
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MARIADB_USER,
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MARIADB_PASSWORD,
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MARIADB_DATABASE,
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)
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SCHEMA = """
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CREATE TABLE IF NOT EXISTS users (
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id VARCHAR(64) PRIMARY KEY,
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email VARCHAR(255) NOT NULL UNIQUE,
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garmin_email VARCHAR(255) NOT NULL,
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garmin_password_hash TEXT NOT NULL,
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jwt_token TEXT,
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created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
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updated_at DATETIME DEFAULT CURRENT_TIMESTAMP
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);
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CREATE TABLE IF NOT EXISTS health_data (
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id VARCHAR(64) PRIMARY KEY,
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user_id VARCHAR(64) NOT NULL,
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date DATE NOT NULL,
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steps INT,
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heart_rate INT,
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heart_rate_variability DOUBLE,
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blood_pressure_systolic INT,
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blood_pressure_diastolic INT,
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sleep_duration INT,
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sleep_quality DOUBLE,
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stress INT,
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calories_burned DOUBLE,
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created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
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updated_at DATETIME DEFAULT CURRENT_TIMESTAMP,
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UNIQUE(user_id, date),
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FOREIGN KEY (user_id) REFERENCES users(id)
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);
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CREATE TABLE IF NOT EXISTS activities (
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id VARCHAR(64) PRIMARY KEY,
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user_id VARCHAR(64) NOT NULL,
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activity_type VARCHAR(255) NOT NULL,
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start_time DATETIME NOT NULL,
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end_time DATETIME NOT NULL,
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duration INT,
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distance DOUBLE,
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calories DOUBLE,
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heart_rate_average INT,
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heart_rate_max INT,
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created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
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FOREIGN KEY (user_id) REFERENCES users(id)
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);
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CREATE TABLE IF NOT EXISTS sync_status (
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user_id VARCHAR(64) PRIMARY KEY,
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last_sync_time DATETIME,
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status VARCHAR(32) DEFAULT 'idle',
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last_error TEXT,
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records_synced INT DEFAULT 0,
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updated_at DATETIME DEFAULT CURRENT_TIMESTAMP,
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FOREIGN KEY (user_id) REFERENCES users(id)
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);
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-- Garmin OAuth tokens, obtained once through an interactive login.
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-- Garmin accounts with two-factor auth cannot be logged into unattended: the
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-- library asks for an MFA code on stdin, which a gunicorn worker does not
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-- have. Storing the resulting tokens lets every later sync skip the login
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-- entirely (they stay valid for roughly a year).
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CREATE TABLE IF NOT EXISTS garmin_tokens (
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user_id VARCHAR(64) PRIMARY KEY,
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token TEXT NOT NULL,
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garmin_email VARCHAR(255),
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created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
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updated_at DATETIME DEFAULT CURRENT_TIMESTAMP,
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FOREIGN KEY (user_id) REFERENCES users(id)
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);
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-- Badges earned on Garmin Connect ("奖励"). Keyed by Garmin's own badge id so
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-- a re-sync updates rather than duplicates.
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CREATE TABLE IF NOT EXISTS badges (
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id VARCHAR(64) NOT NULL,
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user_id VARCHAR(64) NOT NULL,
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badge_key VARCHAR(128),
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name VARCHAR(255),
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category_id INT,
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difficulty_id INT,
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earned_date DATETIME,
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earned_count INT,
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points INT,
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PRIMARY KEY (user_id, id),
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FOREIGN KEY (user_id) REFERENCES users(id)
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);
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-- Personal records (个人纪录), e.g. fastest 5k, longest run.
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CREATE TABLE IF NOT EXISTS personal_records (
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id VARCHAR(64) NOT NULL,
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user_id VARCHAR(64) NOT NULL,
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type_id INT,
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activity_id VARCHAR(64),
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activity_name VARCHAR(255),
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activity_type VARCHAR(64),
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value DOUBLE,
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achieved_at DATETIME,
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PRIMARY KEY (user_id, id),
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FOREIGN KEY (user_id) REFERENCES users(id)
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);
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-- Rendezvous for the interactive MFA login.
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-- garth asks for the code through a *blocking* callback, so the login parks in
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-- a background thread while the code arrives in a separate HTTP request that
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-- may land on a different gunicorn worker. The handoff therefore goes through
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-- the database rather than process memory.
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-- Holds no password: that stays in the waiting thread's memory only.
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CREATE TABLE IF NOT EXISTS garmin_mfa_sessions (
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id VARCHAR(64) PRIMARY KEY,
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user_id VARCHAR(64) NOT NULL,
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status VARCHAR(32) NOT NULL,
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code VARCHAR(16),
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error TEXT,
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created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
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updated_at DATETIME DEFAULT CURRENT_TIMESTAMP,
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FOREIGN KEY (user_id) REFERENCES users(id)
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);
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-- One cached LLM answer per user. Generating one takes minutes against a
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-- large reasoning model, which is far too slow to sit in a page load, so the
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-- result is stored and reused until the underlying data changes.
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-- `fingerprint` identifies the health data the advice was derived from.
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CREATE TABLE IF NOT EXISTS ai_recommendations (
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user_id VARCHAR(64) PRIMARY KEY,
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fingerprint VARCHAR(64) NOT NULL,
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model VARCHAR(64),
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upstream VARCHAR(64),
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days INT,
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payload TEXT NOT NULL,
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created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
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FOREIGN KEY (user_id) REFERENCES users(id)
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);
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"""
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# --- MariaDB pool (lazy) ----------------------------------------------------
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_mariadb_pool = None
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_pool_lock = threading.Lock()
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def _new_mariadb_conn():
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import pymysql
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from pymysql.cursors import DictCursor
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kwargs = dict(
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user=MARIADB_USER,
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password=MARIADB_PASSWORD,
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database=MARIADB_DATABASE,
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charset="utf8mb4",
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autocommit=True,
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cursorclass=DictCursor,
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connect_timeout=10,
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)
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if MARIADB_SOCKET:
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kwargs["unix_socket"] = MARIADB_SOCKET
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else:
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kwargs["host"] = MARIADB_HOST
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kwargs["port"] = MARIADB_PORT
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return pymysql.connect(**kwargs)
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def _mariadb_acquire():
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global _mariadb_pool
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if _mariadb_pool is None:
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with _pool_lock:
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if _mariadb_pool is None:
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_mariadb_pool = queue.Queue(maxsize=10)
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for _ in range(10):
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_mariadb_pool.put(_new_mariadb_conn())
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try:
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return _mariadb_pool.get(block=False)
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except queue.Empty:
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return _new_mariadb_conn()
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def _mariadb_release(conn):
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try:
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conn.ping(reconnect=False)
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_mariadb_pool.put(conn)
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except Exception:
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try:
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conn.close()
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except Exception:
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pass
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# --- SQLite connection ------------------------------------------------------
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def _sqlite_connect():
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data_dir = os.path.dirname(SQLITE_PATH)
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if data_dir and not os.path.exists(data_dir):
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os.makedirs(data_dir, exist_ok=True)
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conn = sqlite3.connect(SQLITE_PATH, isolation_level=None)
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conn.row_factory = sqlite3.Row
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conn.execute("PRAGMA foreign_keys = ON")
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return conn
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def _connect():
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if DB_TYPE == "mariadb":
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return _mariadb_acquire()
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return _sqlite_connect()
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def _disconnect(conn):
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if DB_TYPE == "mariadb":
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_mariadb_release(conn)
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else:
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conn.close()
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def _adapt_sql(sql):
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# pymysql uses %s placeholders; sqlite3 uses ?. Business code writes ?.
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return sql.replace("?", "%s") if DB_TYPE == "mariadb" else sql
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def _serialize(value):
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if value is None:
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return None
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if isinstance(value, (datetime.datetime, datetime.date)):
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return value.isoformat()
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return value
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def _row_to_dict(row):
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if row is None:
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return None
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if isinstance(row, dict):
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return {k: _serialize(v) for k, v in row.items()}
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return {k: _serialize(row[k]) for k in row.keys()}
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# Columns added after the first release. `CREATE TABLE IF NOT EXISTS` does
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# nothing to a table that already exists, so new metrics need an explicit
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# additive migration or they silently never appear in production.
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MIGRATIONS = {
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"health_data": [
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# activity / energy
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("distance_meters", "DOUBLE"),
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("active_calories", "DOUBLE"),
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("bmr_calories", "DOUBLE"),
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("floors_ascended", "DOUBLE"),
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("floors_descended", "DOUBLE"),
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("intensity_minutes", "INT"),
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("step_goal", "INT"),
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("sedentary_seconds", "INT"),
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("active_seconds", "INT"),
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# heart / stress
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("heart_rate_max", "INT"),
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("heart_rate_min", "INT"),
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("stress_max", "INT"),
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# body battery
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("body_battery_high", "INT"),
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("body_battery_low", "INT"),
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("body_battery_charged", "INT"),
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("body_battery_drained", "INT"),
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# breathing / blood oxygen
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("spo2_avg", "DOUBLE"),
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("spo2_min", "INT"),
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("respiration_avg", "DOUBLE"),
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("respiration_min", "DOUBLE"),
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("respiration_max", "DOUBLE"),
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# sleep detail
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("sleep_deep_seconds", "INT"),
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("sleep_light_seconds", "INT"),
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("sleep_rem_seconds", "INT"),
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("sleep_awake_seconds", "INT"),
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("sleep_spo2_avg", "DOUBLE"),
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("sleep_respiration_avg", "DOUBLE"),
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("sleep_stress_avg", "DOUBLE"),
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# training
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("training_readiness", "INT"),
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("vo2max", "DOUBLE"),
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("endurance_score", "INT"),
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],
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}
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def _existing_columns(cur, table):
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if DB_TYPE == "mariadb":
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cur.execute(
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"SELECT COLUMN_NAME FROM information_schema.COLUMNS "
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"WHERE TABLE_SCHEMA = DATABASE() AND TABLE_NAME = %s",
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[table],
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)
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return {r["COLUMN_NAME"] if isinstance(r, dict) else r[0] for r in cur.fetchall()}
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cur.execute(f"PRAGMA table_info({table})")
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return {row[1] for row in cur.fetchall()}
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def _migrate(cur):
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for table, columns in MIGRATIONS.items():
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present = _existing_columns(cur, table)
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for name, coltype in columns:
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if name in present:
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continue
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# SQLite has no "ADD COLUMN IF NOT EXISTS"; the membership check
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# above is what keeps this idempotent on both backends.
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cur.execute(f"ALTER TABLE {table} ADD COLUMN {name} {coltype}")
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# --- Public API -------------------------------------------------------------
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def init_db():
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conn = _connect()
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try:
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cur = conn.cursor()
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for stmt in SCHEMA.split(";"):
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stmt = stmt.strip()
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if not stmt:
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continue
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cur.execute(_adapt_sql(stmt))
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_migrate(cur)
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finally:
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_disconnect(conn)
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def execute(sql, params=None):
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params = params or []
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conn = _connect()
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try:
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cur = conn.cursor()
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cur.execute(_adapt_sql(sql), params)
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return {"id": cur.lastrowid, "changes": cur.rowcount}
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finally:
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_disconnect(conn)
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def query_one(sql, params=None):
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params = params or []
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conn = _connect()
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try:
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cur = conn.cursor()
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cur.execute(_adapt_sql(sql), params)
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return _row_to_dict(cur.fetchone())
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finally:
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_disconnect(conn)
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def query_all(sql, params=None):
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params = params or []
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conn = _connect()
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try:
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cur = conn.cursor()
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cur.execute(_adapt_sql(sql), params)
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return [_row_to_dict(r) for r in cur.fetchall()]
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finally:
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_disconnect(conn)
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