- 建立 Gitea Actions CD pipeline (.gitea/workflows/cd.yaml) - 部署模式: rsync Python 檔案至 188 → docker restart (volume mount) - Dockerfile/requirements 變動時自動重建 Docker image - 部署通知: Telegram (開始/成功/失敗) - 健康檢查: https://mo.wooo.work/health (最多 5 次重試) - 同步最新 CLAUDE.md / ADR-008 / memory (2026-04-19) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
ogt
198
scripts/tools/database_optimization.py
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198
scripts/tools/database_optimization.py
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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SQLite 資料庫優化腳本
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建議在低流量時段執行（晚上 8 點後）
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功能：
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1. 添加缺失的索引（提升查詢效能）
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2. 執行 VACUUM 清理（回收空間、優化儲存）
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3. 分析資料庫統計（更新查詢規劃器統計資訊）
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"""
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import sqlite3
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import os
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import sys
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import time
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from datetime import datetime
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# 資料庫路徑
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DB_PATH = '/home/ogt/momo_pro_system/data/momo_database.db'
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# 日誌函數
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def log(message, level="INFO"):
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timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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print(f"[{timestamp}] [{level}] {message}")
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# 檢查資料庫大小
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def get_db_size():
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size_bytes = os.path.getsize(DB_PATH)
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size_mb = size_bytes / (1024 * 1024)
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return size_bytes, size_mb
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# 檢查索引是否存在
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def index_exists(cursor, index_name):
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cursor.execute(
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"SELECT name FROM sqlite_master WHERE type='index' AND name=?",
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(index_name,)
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)
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return cursor.fetchone() is not None
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# 添加索引
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def add_indexes(conn):
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log("開始添加索引...")
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cursor = conn.cursor()
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indexes = [
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# products 表索引
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("idx_products_category", "CREATE INDEX IF NOT EXISTS idx_products_category ON products (category)"),
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("idx_products_status", "CREATE INDEX IF NOT EXISTS idx_products_status ON products (status)"),
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("idx_products_updated_at", "CREATE INDEX IF NOT EXISTS idx_products_updated_at ON products (updated_at DESC)"),
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# price_records 表索引
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("idx_price_records_product_id", "CREATE INDEX IF NOT EXISTS idx_price_records_product_id ON price_records (product_id)"),
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("idx_price_records_product_time", "CREATE INDEX IF NOT EXISTS idx_price_records_product_time ON price_records (product_id, timestamp DESC)"),
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# promo_products 表索引
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("idx_promo_crawled_at", "CREATE INDEX IF NOT EXISTS idx_promo_crawled_at ON promo_products (crawled_at DESC)"),
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("idx_promo_batch_id", "CREATE INDEX IF NOT EXISTS idx_promo_batch_id ON promo_products (batch_id)"),
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("idx_promo_status_change", "CREATE INDEX IF NOT EXISTS idx_promo_status_change ON promo_products (status_change)"),
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]
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added_count = 0
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skipped_count = 0
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for index_name, create_sql in indexes:
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try:
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if index_exists(cursor, index_name):
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log(f" 索引已存在，跳過: {index_name}", "INFO")
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skipped_count += 1
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continue
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log(f" 創建索引: {index_name}...", "INFO")
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start_time = time.time()
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cursor.execute(create_sql)
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conn.commit()
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elapsed = time.time() - start_time
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log(f" ✓ 索引創建成功: {index_name} (耗時 {elapsed:.2f} 秒)", "SUCCESS")
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added_count += 1
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except Exception as e:
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log(f" ✗ 索引創建失敗: {index_name} - {e}", "ERROR")
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conn.rollback()
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log(f"索引添加完成：新增 {added_count} 個，跳過 {skipped_count} 個", "INFO")
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return added_count
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# 執行 VACUUM
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def run_vacuum(conn):
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log("開始執行 VACUUM 清理...", "INFO")
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log("⚠️ 注意：此操作會鎖定整個資料庫，期間無法讀寫", "WARNING")
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try:
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start_time = time.time()
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conn.execute("VACUUM")
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elapsed = time.time() - start_time
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log(f"✓ VACUUM 執行成功 (耗時 {elapsed:.2f} 秒)", "SUCCESS")
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return True
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except Exception as e:
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log(f"✗ VACUUM 執行失敗: {e}", "ERROR")
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return False
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# 分析資料庫統計
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def analyze_database(conn):
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log("開始分析資料庫統計...", "INFO")
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try:
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start_time = time.time()
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conn.execute("ANALYZE")
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elapsed = time.time() - start_time
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log(f"✓ 資料庫分析完成 (耗時 {elapsed:.2f} 秒)", "SUCCESS")
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return True
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except Exception as e:
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log(f"✗ 資料庫分析失敗: {e}", "ERROR")
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return False
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# 顯示優化前後對比
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def show_statistics(before_size, after_size):
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log("=" * 60)
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log("資料庫優化統計報告", "INFO")
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log("=" * 60)
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log(f"優化前大小: {before_size:.2f} MB", "INFO")
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log(f"優化後大小: {after_size:.2f} MB", "INFO")
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if before_size > after_size:
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saved = before_size - after_size
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saved_pct = (saved / before_size) * 100
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log(f"節省空間: {saved:.2f} MB ({saved_pct:.1f}%)", "SUCCESS")
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else:
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log("空間無變化（資料庫已經很緊湊）", "INFO")
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log("=" * 60)
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def main():
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log("=" * 60)
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log("SQLite 資料庫優化腳本啟動", "INFO")
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log("=" * 60)
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# 檢查資料庫是否存在
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if not os.path.exists(DB_PATH):
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log(f"錯誤：資料庫不存在 - {DB_PATH}", "ERROR")
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sys.exit(1)
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# 記錄開始時間和大小
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before_bytes, before_mb = get_db_size()
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log(f"當前資料庫大小: {before_mb:.2f} MB", "INFO")
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try:
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# 連接資料庫
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log("連接到資料庫...", "INFO")
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conn = sqlite3.connect(DB_PATH, timeout=30.0)
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# 步驟 1: 添加索引
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log("\n" + "=" * 60)
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log("步驟 1/3: 添加索引", "INFO")
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log("=" * 60)
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added_count = add_indexes(conn)
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# 步驟 2: 執行 VACUUM
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log("\n" + "=" * 60)
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log("步驟 2/3: 執行 VACUUM 清理", "INFO")
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log("=" * 60)
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vacuum_success = run_vacuum(conn)
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# 步驟 3: 分析資料庫
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log("\n" + "=" * 60)
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log("步驟 3/3: 分析資料庫統計", "INFO")
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log("=" * 60)
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analyze_success = analyze_database(conn)
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# 關閉連接
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conn.close()
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log("資料庫連接已關閉", "INFO")
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# 顯示統計
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after_bytes, after_mb = get_db_size()
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log("")
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show_statistics(before_mb, after_mb)
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# 最終結果
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log("")
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log("=" * 60)
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if added_count > 0 or vacuum_success:
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log("✓ 資料庫優化完成！", "SUCCESS")
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else:
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log("資料庫優化執行完畢（無顯著變化）", "INFO")
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log("=" * 60)
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except sqlite3.OperationalError as e:
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log(f"資料庫操作錯誤: {e}", "ERROR")
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log("可能原因：資料庫正在被其他程序使用", "ERROR")
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sys.exit(1)
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except Exception as e:
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log(f"未預期的錯誤: {e}", "ERROR")
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import traceback
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traceback.print_exc()
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sys.exit(1)
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if __name__ == "__main__":
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main()
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