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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>
66 lines
2.0 KiB
Python
66 lines
2.0 KiB
Python
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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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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DB_PATH = os.path.join(BASE_DIR, 'data', 'momo_database.db')
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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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# 讀取需要修復的商品清單
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with open('incorrect_images.txt', 'r') as f:
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i_codes = [line.strip() for line in f if line.strip()]
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total = len(i_codes)
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print(f"🔧 開始修復 {total} 個商品的圖片 URL\n")
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print("=" * 100)
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success_count = 0
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fail_count = 0
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for i, i_code in enumerate(i_codes, 1):
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product = session.query(Product).filter(Product.i_code == i_code).first()
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if product:
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if i % 50 == 0 or i <= 10:
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print(f"\n[{i}/{total}] 處理: [{i_code}] {product.name[:45]}...")
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if product.image_url:
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print(f" ❌ 舊: {product.image_url[:70]}...")
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# 獲取新的圖片 URL
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new_image_url = get_product_image_url(i_code)
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if new_image_url:
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product.image_url = new_image_url
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session.commit()
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if i % 50 == 0 or i <= 10:
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print(f" ✅ 新: {new_image_url}")
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success_count += 1
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else:
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if i % 50 == 0 or i <= 10:
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print(f" ⚠️ 無法獲取")
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fail_count += 1
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# 每 10 個顯示進度
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if i % 10 == 0:
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progress = i * 100 // total
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print(f" 進度: {i}/{total} ({progress}%) - 成功: {success_count}, 失敗: {fail_count}")
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# 延遲避免請求過快
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time.sleep(0.3)
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else:
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fail_count += 1
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print("\n" + "=" * 100)
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print(f"\n📊 修復結果:")
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print(f" ✅ 成功: {success_count}/{total} ({success_count*100//total}%)")
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print(f" ❌ 失敗: {fail_count}/{total} ({fail_count*100//total}%)")
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session.close()
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