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- 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>
126 lines
4.4 KiB
Python
126 lines
4.4 KiB
Python
# cSpell:ignore momo
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"""
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更新所有監控商品的圖片
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使用 i_code 從商品詳情頁直接獲取圖片 URL
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"""
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import os
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import sys
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import time
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from sqlalchemy import create_engine
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from sqlalchemy.orm import sessionmaker
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# 設定路徑
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BASE_DIR = os.path.dirname(os.path.abspath(__file__))
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sys.path.insert(0, BASE_DIR)
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from database.models import Product
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from utils.image_url_builder import get_product_image_url
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# 資料庫路徑
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DB_PATH = os.path.join(BASE_DIR, 'data', 'momo_database.db')
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def update_all_images(batch_size: int = 100, delay: float = 0.5, start_from: int = 0):
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"""
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更新所有監控商品的圖片
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Args:
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batch_size: 每批處理的商品數量
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delay: 每個請求之間的延遲（秒）
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start_from: 從第幾個商品開始處理（用於斷點續傳）
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"""
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print(f"🔄 開始更新所有監控商品的圖片（從第 {start_from + 1} 個開始）...\n")
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if not os.path.exists(DB_PATH):
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print(f"❌ 資料庫檔案不存在: {DB_PATH}")
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return
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try:
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engine = create_engine(f"sqlite:///{DB_PATH}")
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Session = sessionmaker(bind=engine)
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session = Session()
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# 查詢所有商品的總數
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total_count = session.query(Product).count()
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print(f"📊 資料庫中共有 {total_count} 個監控商品")
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print(f"📦 本次將處理 {min(batch_size, total_count - start_from)} 個商品\n")
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# 查詢指定範圍的商品
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products = session.query(Product).offset(start_from).limit(batch_size).all()
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if not products:
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print("✅ 沒有需要處理的商品！")
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return
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success_count = 0
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fail_count = 0
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skip_count = 0
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for idx, product in enumerate(products, 1):
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global_idx = start_from + idx
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print(f"[{global_idx}/{total_count}] 處理: [{product.i_code}] {product.name[:50]}...")
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try:
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# 從商品詳情頁獲取圖片 URL
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image_url = get_product_image_url(product.i_code)
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if image_url:
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# 檢查圖片是否有變化
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if product.image_url != image_url:
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product.image_url = image_url
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session.commit()
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print(f" ✅ 更新: {image_url}")
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success_count += 1
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else:
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print(f" ⏭️ 相同: 圖片已是最新")
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skip_count += 1
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else:
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print(f" ⚠️ 無法獲取圖片（可能已下架或不存在）")
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fail_count += 1
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# 延遲，避免請求過快
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time.sleep(delay)
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except Exception as e:
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print(f" ❌ 錯誤: {e}")
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fail_count += 1
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session.rollback()
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session.close()
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print("\n" + "=" * 60)
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print("📊 本批更新結果")
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print("=" * 60)
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total = len(products)
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print(f"✅ 成功更新: {success_count}/{total}")
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print(f"⏭️ 跳過（相同）: {skip_count}/{total}")
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print(f"❌ 失敗: {fail_count}/{total}")
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# 顯示進度
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completed = start_from + len(products)
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progress = completed / total_count * 100
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remaining = total_count - completed
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print(f"\n📈 總進度: {completed}/{total_count} ({progress:.1f}%)")
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if remaining > 0:
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print(f"⏳ 剩餘: {remaining} 個商品")
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print(f"\n💡 提示: 繼續執行下一批，使用參數 --start-from {completed}")
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else:
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print(f"\n🎉 所有商品已處理完成！")
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except Exception as e:
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print(f"❌ 批次更新失敗: {e}")
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import traceback
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traceback.print_exc()
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if __name__ == "__main__":
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import argparse
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parser = argparse.ArgumentParser(description='更新所有監控商品的圖片')
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parser.add_argument('--batch-size', type=int, default=100, help='每批處理的商品數量（預設: 100）')
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parser.add_argument('--delay', type=float, default=0.5, help='每個請求之間的延遲秒數（預設: 0.5）')
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parser.add_argument('--start-from', type=int, default=0, help='從第幾個商品開始處理（預設: 0）')
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args = parser.parse_args()
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update_all_images(batch_size=args.batch_size, delay=args.delay, start_from=args.start_from)
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