143 lines
6.6 KiB
Python
143 lines
6.6 KiB
Python
import os
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import csv
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import pandas as pd
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from datetime import datetime
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from config import EXCEL_EXPORT_DIR
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from utils.momo_url_utils import build_momo_product_url, normalize_momo_product_url
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class Exporter:
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"""
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報表匯出管理器
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負責將數據轉換為 CSV/Excel 格式並儲存至 exports 目錄
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"""
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def __init__(self):
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self.export_dir = EXCEL_EXPORT_DIR
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if not os.path.exists(self.export_dir):
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try:
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os.makedirs(self.export_dir)
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except OSError:
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pass
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def _write_csv(self, filename, headers, rows):
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"""內部方法：寫入 CSV 檔案 (含 BOM 以支援 Excel 中文顯示)"""
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filepath = os.path.join(self.export_dir, filename)
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try:
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with open(filepath, 'w', newline='', encoding='utf-8-sig') as f:
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writer = csv.writer(f)
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writer.writerow(headers)
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writer.writerows(rows)
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return filepath
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except Exception as e:
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print(f"❌ Export error: {e}")
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return None
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def _safe_product_url(self, product):
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sku = str(getattr(product, 'i_code', '') or '')
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return normalize_momo_product_url(getattr(product, 'url', None), sku) or build_momo_product_url(sku)
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def generate_all_categories_report(self):
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"""匯出所有分類商品快照"""
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# 由於 app.py 呼叫此方法時未傳入數據，需自行查詢資料庫
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from database.manager import DatabaseManager
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from database.models import PriceRecord
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from sqlalchemy import func
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db = DatabaseManager()
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session = db.get_session()
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try:
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# 查詢每個商品最新價格
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subq = session.query(func.max(PriceRecord.id).label('max_id')).group_by(PriceRecord.product_id).subquery()
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records = session.query(PriceRecord).join(subq, PriceRecord.id == subq.c.max_id).all()
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rows = []
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for r in records:
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rows.append([r.product.category, r.product.name, r.price, self._safe_product_url(r.product), r.timestamp.strftime('%Y-%m-%d %H:%M')])
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filename = f"All_Products_{datetime.now().strftime('%Y%m%d_%H%M')}.csv"
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return self._write_csv(filename, ['Category', 'Name', 'Price', 'URL', 'Last Update'], rows)
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finally:
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session.close()
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def generate_price_change_report(self, items):
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"""匯出價格異動商品"""
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rows = []
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for item in items:
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rec = item['record']
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diff = item['yesterday_diff']
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rows.append([rec.product.category, rec.product.name, rec.price, diff, self._safe_product_url(rec.product)])
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filename = f"Price_Changes_{datetime.now().strftime('%Y%m%d_%H%M')}.csv"
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return self._write_csv(filename, ['Category', 'Name', 'Price', 'Change', 'URL'], rows)
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def generate_low_price_report(self):
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return self._write_csv(f"Low_Price_{datetime.now().strftime('%Y%m%d')}.csv", ['Message'], [['Feature not fully implemented']])
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def generate_custom_report(self, items, title):
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rows = []
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for item in items:
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rec = item['record']
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rows.append([rec.product.category, rec.product.name, rec.price, self._safe_product_url(rec.product)])
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filename = f"{title}_{datetime.now().strftime('%Y%m%d_%H%M')}.csv"
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return self._write_csv(filename, ['Category', 'Name', 'Price', 'URL'], rows)
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def generate_delisted_report(self, items, title):
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rows = []
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for item in items:
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p = item['product']
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price = item['last_price']
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rows.append([p.category, p.name, price, self._safe_product_url(p), "DELISTED"])
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filename = f"{title}_{datetime.now().strftime('%Y%m%d_%H%M')}.csv"
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return self._write_csv(filename, ['Category', 'Name', 'Last Price', 'URL', 'Status'], rows)
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def generate_all_products_excel(self, items):
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"""匯出所有商品至 Excel (依分類分頁)"""
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data = []
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for item in items:
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rec = item['record']
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data.append({
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'分類': rec.product.category,
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'商品名稱': rec.product.name,
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'價格': rec.price,
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'連結': self._safe_product_url(rec.product),
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'更新時間': rec.timestamp.strftime('%Y-%m-%d %H:%M')
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})
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filename = f"MOMO_All_{datetime.now().strftime('%Y%m%d_%H%M')}.xlsx"
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filepath = os.path.join(self.export_dir, filename)
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df = pd.DataFrame(data)
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with pd.ExcelWriter(filepath, engine='openpyxl') as writer:
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for cat, group in df.groupby('分類'):
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sheet_name = str(cat)[:30].replace('/', '_').replace(':', '') # 處理 Excel 工作表名稱限制
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group.to_excel(writer, sheet_name=sheet_name, index=False)
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return filepath
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def generate_changes_excel(self, increase, decrease):
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"""匯出漲跌商品至 Excel (兩個分頁)"""
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filename = f"MOMO_Changes_{datetime.now().strftime('%Y%m%d_%H%M')}.xlsx"
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filepath = os.path.join(self.export_dir, filename)
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with pd.ExcelWriter(filepath, engine='openpyxl') as writer:
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# 漲價
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data_inc = [{'分類': i['record'].product.category, '商品名稱': i['record'].product.name, '價格': i['record'].price, '漲幅': i['yesterday_diff'], '連結': self._safe_product_url(i['record'].product)} for i in increase]
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pd.DataFrame(data_inc).to_excel(writer, sheet_name='漲價商品', index=False)
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# 跌價
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data_dec = [{'分類': i['record'].product.category, '商品名稱': i['record'].product.name, '價格': i['record'].price, '跌幅': i['yesterday_diff'], '連結': self._safe_product_url(i['record'].product)} for i in decrease]
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pd.DataFrame(data_dec).to_excel(writer, sheet_name='跌價商品', index=False)
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return filepath
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def generate_delisted_excel(self, delisted_items):
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"""匯出下架商品至 Excel"""
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filename = f"MOMO_Delisted_{datetime.now().strftime('%Y%m%d_%H%M')}.xlsx"
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filepath = os.path.join(self.export_dir, filename)
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data = [{'分類': i['product'].category, '商品名稱': i['product'].name, '最後價格': i['last_price'], '連結': self._safe_product_url(i['product']), '狀態': '下架'} for i in delisted_items]
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with pd.ExcelWriter(filepath, engine='openpyxl') as writer:
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pd.DataFrame(data).to_excel(writer, sheet_name='下架商品', index=False)
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return filepath
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