872 lines
29 KiB
Python
872 lines
29 KiB
Python
"""
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PChome 24h 爬蟲服務
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爬取 PChome 24h 商品資料，支援：
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- 館別頁面爬取 (如 /region/DDAB)
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- 商品詳細資料取得
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- 批次查詢商品 API
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API 參考:
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- 商品 API: https://ecapi-cdn.pchome.com.tw/cdn/ecshop/prodapi/v2/prod?id=ID1,ID2,...
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- 圖片 URL: https://img.pchome.com.tw/cs{Pic.B}
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"""
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import re
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import time
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import logging
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from typing import List, Dict, Optional, Tuple
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from dataclasses import dataclass, asdict
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from datetime import datetime
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import requests
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logger = logging.getLogger(__name__)
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@dataclass
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class PChomeProduct:
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"""PChome 商品資料結構"""
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product_id: str # 商品 ID (如 DDABSD-1900HIE3P)
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name: str # 商品名稱
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price: int # 售價
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original_price: int # 原價
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discount: Optional[int] # 折扣 (%)
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image_url: str # 圖片 URL
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product_url: str # 商品頁面 URL
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stock: int # 庫存數量
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store: str # 店家代碼
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rating: Optional[float] # 評分
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review_count: int # 評論數
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is_on_sale: bool # 是否特價中
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crawled_at: datetime # 爬取時間
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def to_dict(self) -> dict:
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"""轉換為字典"""
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data = asdict(self)
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data['crawled_at'] = self.crawled_at.isoformat()
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return data
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class PChomeCrawler:
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"""PChome 24h 爬蟲"""
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# 基礎 URL
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BASE_URL = 'https://24h.pchome.com.tw'
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API_URL = 'https://ecapi-cdn.pchome.com.tw/cdn/ecshop/prodapi/v2/prod'
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IMAGE_BASE_URL = 'https://img.pchome.com.tw/cs'
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# 預設 Headers
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DEFAULT_HEADERS = {
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'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36',
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'Accept': 'application/json, text/html,application/xhtml+xml',
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'Accept-Language': 'zh-TW,zh;q=0.9,en;q=0.8',
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'Referer': 'https://24h.pchome.com.tw/',
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}
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# 商品 ID 正則表達式
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PRODUCT_ID_PATTERN = re.compile(r'[A-Z]{4}[A-Z0-9]{2}-?[A-Z0-9]{8,10}')
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def __init__(
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self,
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timeout: int = 30,
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delay: float = 1.0,
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max_retries: int = 2,
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retry_backoff: float = 0.8,
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):
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"""
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初始化爬蟲
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Args:
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timeout: 請求超時時間 (秒)
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delay: 請求間隔延遲 (秒)，避免過度頻繁請求
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max_retries: 暫時性錯誤的重試次數
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retry_backoff: 指數退避基礎秒數
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"""
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self.timeout = timeout
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self.delay = delay
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self.max_retries = max(0, int(max_retries))
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self.retry_backoff = max(0.0, float(retry_backoff))
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self.session = requests.Session()
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self.session.headers.update(self.DEFAULT_HEADERS)
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self._last_request_time = 0
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def _rate_limit(self):
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"""速率限制"""
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elapsed = time.time() - self._last_request_time
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if elapsed < self.delay:
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time.sleep(self.delay - elapsed)
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self._last_request_time = time.time()
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def _get_with_retry(self, url: str, **kwargs) -> requests.Response:
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"""GET with polite rate limiting and bounded retry for transient failures."""
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retryable_statuses = {429, 500, 502, 503, 504}
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last_error = None
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for attempt in range(self.max_retries + 1):
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self._rate_limit()
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try:
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response = self.session.get(url, **kwargs)
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status_code = getattr(response, "status_code", 200)
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if (
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status_code in retryable_statuses
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and attempt < self.max_retries
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):
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last_error = requests.HTTPError(
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f"HTTP {status_code} for {url}",
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response=response,
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)
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else:
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response.raise_for_status()
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return response
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except (requests.Timeout, requests.ConnectionError, requests.HTTPError) as exc:
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last_error = exc
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response = getattr(exc, "response", None)
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status_code = getattr(response, "status_code", None)
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if (
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attempt >= self.max_retries
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or (
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isinstance(exc, requests.HTTPError)
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and status_code not in retryable_statuses
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)
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):
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raise
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sleep_sec = self.retry_backoff * (2 ** attempt)
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if sleep_sec > 0:
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time.sleep(sleep_sec)
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if last_error:
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raise last_error
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raise requests.RequestException(f"GET failed: {url}")
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def _normalize_product_id(self, product_id: str) -> str:
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"""
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正規化商品 ID 格式
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Args:
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product_id: 原始商品 ID
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Returns:
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正規化後的 ID (格式: XXXXXX-XXXXXXXX)
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"""
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# 移除空白
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product_id = product_id.strip()
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# 如果已經有 - 就直接返回
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if '-' in product_id:
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return product_id
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# 在第 6 個字元後加入 -
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if len(product_id) > 6:
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return f"{product_id[:6]}-{product_id[6:]}"
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return product_id
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def _extract_product_ids_from_html(self, html: str) -> List[str]:
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"""
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從 HTML 中提取商品 ID
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Args:
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html: 頁面 HTML 內容
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Returns:
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商品 ID 列表 (已去重)
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"""
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raw_ids = self.PRODUCT_ID_PATTERN.findall(html)
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# 正規化並去重
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normalized_ids = set()
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for pid in raw_ids:
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normalized = self._normalize_product_id(pid)
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normalized_ids.add(normalized)
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return list(normalized_ids)
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def fetch_region_page(self, region_code: str) -> Tuple[bool, str, List[str]]:
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"""
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爬取館別頁面，取得商品 ID 列表
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Args:
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region_code: 館別代碼 (如 DDAB)
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Returns:
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(成功與否, 訊息, 商品 ID 列表)
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"""
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url = f"{self.BASE_URL}/region/{region_code}"
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try:
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response = self._get_with_retry(url, timeout=self.timeout)
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product_ids = self._extract_product_ids_from_html(response.text)
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logger.info(f"從 {url} 取得 {len(product_ids)} 個商品 ID")
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return True, f"成功取得 {len(product_ids)} 個商品", product_ids
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except requests.RequestException as e:
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logger.error(f"爬取 {url} 失敗: {e}")
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return False, f"請求失敗: {str(e)}", []
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def fetch_product_details(self, product_ids: List[str], batch_size: int = 20) -> Tuple[bool, str, List[PChomeProduct]]:
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"""
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批次取得商品詳細資料
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Args:
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product_ids: 商品 ID 列表
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batch_size: 每批次查詢數量 (API 限制約 20-30 個)
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Returns:
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(成功與否, 訊息, 商品資料列表)
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"""
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if not product_ids:
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return False, "沒有提供商品 ID", []
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all_products = []
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failed_count = 0
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# 分批處理
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for i in range(0, len(product_ids), batch_size):
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batch = product_ids[i:i + batch_size]
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try:
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# 呼叫商品 API
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params = {'id': ','.join(batch)}
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response = self._get_with_retry(
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self.API_URL,
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params=params,
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timeout=self.timeout
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)
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data = response.json()
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crawled_at = datetime.now()
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if isinstance(data, dict):
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product_entries = data.items()
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product_count = len(data)
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elif isinstance(data, list):
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product_entries = [
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((item or {}).get('Id') or f'index_{idx}', item)
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for idx, item in enumerate(data)
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if isinstance(item, dict)
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]
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product_count = len(product_entries)
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failed_count += max(0, len(data) - product_count)
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else:
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logger.warning(
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"PChome 商品 API 回傳格式異常 (批次 %s): %s",
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i // batch_size + 1,
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type(data).__name__,
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)
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failed_count += len(batch)
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continue
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# 解析商品資料
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for prod_key, prod_data in product_entries:
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try:
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product = self._parse_product_data(prod_data, crawled_at)
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if product:
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all_products.append(product)
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except Exception as e:
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logger.warning(f"解析商品 {prod_key} 失敗: {e}")
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failed_count += 1
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logger.info(f"批次 {i // batch_size + 1}: 取得 {product_count} 個商品資料")
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except requests.RequestException as e:
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logger.error(f"API 請求失敗 (批次 {i // batch_size + 1}): {e}")
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failed_count += len(batch)
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message = f"成功取得 {len(all_products)} 個商品資料"
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if failed_count > 0:
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message += f"，{failed_count} 個失敗"
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return len(all_products) > 0, message, all_products
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def _parse_product_data(self, data: dict, crawled_at: datetime) -> Optional[PChomeProduct]:
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"""
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解析 API 回傳的商品資料
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Args:
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data: API 回傳的商品資料
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crawled_at: 爬取時間
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Returns:
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PChomeProduct 物件
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"""
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try:
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product_id = data.get('Id', '')
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# 移除尾部的 -000
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if product_id.endswith('-000'):
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product_id = product_id[:-4]
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# 取得價格資訊
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# [2026-04-18 台北] Bug-1 防禦 Layer C：PChome API 若改版導致 'P' 欄位消失，
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# 舊版靜默歸零 → DB 寫入 $0 → 全鏈路幻覺。改為偵測到缺值時 return None，
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# 由上層決定跳過 — Claude Opus 4.7
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price_info = data.get('Price', {})
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if isinstance(price_info, dict):
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price = price_info.get('P')
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if price is None or price == 0:
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logger.warning(
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f"[PChome] Id={data.get('Id', '?')} 價格欄位 Price.P 缺失或為 0，"
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f"疑似 API 格式變更或商品下架，跳過此筆"
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)
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return None
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original_price = price_info.get('M', price)
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else:
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price = price_info
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if not price:
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logger.warning(
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f"[PChome] Id={data.get('Id', '?')} 價格欄位為非 dict 且為空，跳過"
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)
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return None
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original_price = price
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# 計算折扣
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discount = None
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if original_price and original_price > price:
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discount = round((1 - price / original_price) * 100)
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# 取得圖片 URL
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pic_info = data.get('Pic', {})
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if isinstance(pic_info, dict):
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pic_path = pic_info.get('B', '')
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else:
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pic_path = pic_info or ''
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image_url = f"{self.IMAGE_BASE_URL}{pic_path}" if pic_path else ''
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return PChomeProduct(
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product_id=product_id,
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name=data.get('Name', ''),
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price=price,
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original_price=original_price,
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discount=discount,
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image_url=image_url,
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product_url=f"{self.BASE_URL}/prod/{product_id}",
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stock=data.get('Qty', 0),
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store=data.get('Store', ''),
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rating=data.get('RatingValue'),
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review_count=data.get('ReviewCount', 0),
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is_on_sale=data.get('isOnSale', False),
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crawled_at=crawled_at
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)
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except Exception as e:
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logger.error(f"解析商品資料失敗: {e}")
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return None
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def crawl_region(self, region_code: str) -> Tuple[bool, str, List[PChomeProduct]]:
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"""
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完整爬取館別頁面 (取得 ID + 詳細資料)
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Args:
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region_code: 館別代碼
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Returns:
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(成功與否, 訊息, 商品資料列表)
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"""
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# Step 1: 取得商品 ID
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success, message, product_ids = self.fetch_region_page(region_code)
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if not success:
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return False, message, []
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if not product_ids:
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return False, "頁面中沒有找到商品", []
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# Step 2: 取得詳細資料
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success, message, products = self.fetch_product_details(product_ids)
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return success, message, products
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def search_products(
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self,
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keyword: str,
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limit: int = 50,
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max_pages: Optional[int] = None,
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sort: str = "rnk/dc",
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) -> Tuple[bool, str, List[PChomeProduct]]:
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"""
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搜尋商品 (使用搜尋 API)
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Args:
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keyword: 搜尋關鍵字
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limit: 最多回傳數量
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max_pages: 搜尋結果最多掃描頁數；預設依 limit 最多掃到 3 頁
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sort: 搜尋排序；預設 relevance ranking (`rnk/dc`)
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Returns:
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(成功與否, 訊息, 商品資料列表)
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"""
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search_url = f"https://ecshweb.pchome.com.tw/search/v4.3/all/results"
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limit = max(1, int(limit or 1))
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page_cap = max_pages if max_pages is not None else min(3, max(1, (limit // 20) + 1))
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page_cap = max(1, int(page_cap or 1))
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try:
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product_ids = []
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seen_ids = set()
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pages_scanned = 0
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for page in range(1, page_cap + 1):
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params = {
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'q': keyword,
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'page': page,
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'sort': sort,
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'cateid': '24h',
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}
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response = self._get_with_retry(search_url, params=params, timeout=self.timeout)
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pages_scanned += 1
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data = response.json()
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prods = data.get('Prods', [])
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if not prods:
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break
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for item in prods:
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product_id = item.get('Id', '')
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if not product_id or product_id in seen_ids:
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continue
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seen_ids.add(product_id)
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product_ids.append(product_id)
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if len(product_ids) >= limit:
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break
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if len(product_ids) >= limit:
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break
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if not product_ids:
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return False, "沒有找到符合的商品", []
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# 取得詳細資料
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success, message, products = self.fetch_product_details(product_ids[:limit])
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if success:
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message = f"{message}；搜尋頁數 {pages_scanned}；排序 {sort}"
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return success, message, products
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except requests.RequestException as e:
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logger.error(f"搜尋失敗: {e}")
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return False, f"搜尋失敗: {str(e)}", []
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# 預設爬蟲實例
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_crawler_instance = None
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def get_crawler() -> PChomeCrawler:
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"""取得爬蟲實例 (單例模式)"""
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global _crawler_instance
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if _crawler_instance is None:
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_crawler_instance = PChomeCrawler()
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return _crawler_instance
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# 快捷函數
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def crawl_pchome_region(region_code: str) -> Tuple[bool, str, List[dict]]:
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"""
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爬取 PChome 館別頁面
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Args:
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region_code: 館別代碼 (如 DDAB)
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Returns:
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(成功與否, 訊息, 商品資料列表)
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"""
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crawler = get_crawler()
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success, message, products = crawler.crawl_region(region_code)
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return success, message, [p.to_dict() for p in products]
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def search_pchome_products(keyword: str, limit: int = 50) -> Tuple[bool, str, List[dict]]:
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"""
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搜尋 PChome 商品
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Args:
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keyword: 搜尋關鍵字
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limit: 最多回傳數量
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Returns:
|
||
(成功與否, 訊息, 商品資料列表)
|
||
"""
|
||
crawler = get_crawler()
|
||
success, message, products = crawler.search_products(keyword, limit)
|
||
return success, message, [p.to_dict() for p in products]
|
||
|
||
|
||
def get_pchome_bestsellers(category: str, limit: int = 5) -> Tuple[bool, str, List[dict]]:
|
||
"""
|
||
取得 PChome 分類熱銷商品
|
||
|
||
Args:
|
||
category: 分類關鍵字 (如 '面膜', '乳液', '精華液')
|
||
limit: 最多回傳數量
|
||
|
||
Returns:
|
||
(成功與否, 訊息, 商品資料列表)
|
||
"""
|
||
crawler = get_crawler()
|
||
# 使用搜尋 API，按銷量排序
|
||
success, message, products = crawler.search_products(category, limit=limit)
|
||
if success and products:
|
||
# 轉換為精簡格式
|
||
result = []
|
||
for p in products[:limit]:
|
||
result.append({
|
||
'name': p.name,
|
||
'price': p.price,
|
||
'original_price': p.original_price,
|
||
'discount': p.discount,
|
||
'url': p.product_url,
|
||
'image': p.image_url
|
||
})
|
||
return True, f"成功取得 {len(result)} 個熱銷商品", result
|
||
return success, message, []
|
||
|
||
|
||
if __name__ == '__main__':
|
||
# 測試
|
||
logging.basicConfig(level=logging.INFO)
|
||
|
||
print("=== PChome 爬蟲測試 ===\n")
|
||
|
||
# 測試館別爬取
|
||
print("[1] 測試館別爬取 (DDAB - 美妝保養)")
|
||
success, msg, products = crawl_pchome_region('DDAB')
|
||
print(f"結果: {msg}")
|
||
if products:
|
||
print(f"範例商品:")
|
||
for p in products[:3]:
|
||
print(f" - {p['name'][:30]}... ${p['price']} (原價 ${p['original_price']})")
|
||
|
||
print("\n" + "=" * 50 + "\n")
|
||
|
||
# 測試搜尋
|
||
print("[2] 測試搜尋 (關鍵字: iPhone)")
|
||
success, msg, products = search_pchome_products('iPhone', limit=5)
|
||
print(f"結果: {msg}")
|
||
if products:
|
||
print(f"搜尋結果:")
|
||
for p in products[:3]:
|
||
print(f" - {p['name'][:30]}... ${p['price']}")
|
||
|
||
|
||
# =============================================================================
|
||
# 高階競品比較函數（供 openclaw_bot_routes 使用）
|
||
# =============================================================================
|
||
|
||
def search_pchome(keyword: str, limit: int = 10) -> List[dict]:
|
||
"""
|
||
搜尋 PChome 商品（簡化版，直接回傳 list）。
|
||
|
||
Returns:
|
||
[{'name', 'price', 'url', 'in_stock'}, ...]
|
||
"""
|
||
ok, _, products = search_pchome_products(keyword, limit=limit)
|
||
if not ok:
|
||
return []
|
||
result = []
|
||
for p in products:
|
||
result.append({
|
||
'name': p.get('name', ''),
|
||
'price': p.get('price', 0),
|
||
'url': p.get('product_url', ''),
|
||
'in_stock': p.get('stock', 0) > 0,
|
||
})
|
||
return result
|
||
|
||
|
||
def find_best_match(keyword: str, momo_price: float) -> Optional[dict]:
|
||
"""
|
||
在 PChome 搜尋最接近 keyword 的商品並回傳最佳匹配。
|
||
|
||
Returns:
|
||
{'name', 'price', 'url', 'price_diff', 'match_score'} or None
|
||
"""
|
||
results = search_pchome(keyword, limit=5)
|
||
if not results:
|
||
return None
|
||
|
||
try:
|
||
from services.marketplace_product_matcher import score_marketplace_match
|
||
best = None
|
||
best_score = 0.0
|
||
best_diagnostics = None
|
||
for result in results:
|
||
diagnostics = score_marketplace_match(
|
||
keyword,
|
||
result.get('name', ''),
|
||
momo_price=momo_price,
|
||
competitor_price=result.get('price'),
|
||
)
|
||
if diagnostics.score > best_score:
|
||
best = result
|
||
best_score = diagnostics.score
|
||
best_diagnostics = diagnostics
|
||
if not best or best_score < 0.76:
|
||
return None
|
||
best['match_score'] = best_score
|
||
best['match_reasons'] = list(getattr(best_diagnostics, 'reasons', ()) or ())
|
||
except Exception:
|
||
logger.warning("[PChome] identity matcher unavailable, fallback to price distance", exc_info=True)
|
||
best = min(results, key=lambda r: abs(r['price'] - momo_price))
|
||
|
||
best['price_diff'] = best['price'] - momo_price
|
||
return best
|
||
|
||
|
||
def compare_product(
|
||
momo_name: str,
|
||
momo_price: float,
|
||
momo_icode: str = '',
|
||
) -> dict:
|
||
"""
|
||
單一商品 momo vs PChome 比價。
|
||
|
||
Returns:
|
||
{
|
||
'momo_name', 'momo_price', 'momo_icode',
|
||
'found': bool,
|
||
'pc_name', 'pc_price', 'pc_url',
|
||
'price_diff': pc_price - momo_price (正值=PChome貴=momo有優勢),
|
||
'price_diff_pct': %
|
||
}
|
||
"""
|
||
base: dict = {
|
||
'momo_name': momo_name,
|
||
'momo_price': momo_price,
|
||
'momo_icode': momo_icode,
|
||
'found': False,
|
||
'pc_name': '',
|
||
'pc_price': 0,
|
||
'pc_url': '',
|
||
'price_diff': 0,
|
||
'price_diff_pct': 0.0,
|
||
}
|
||
try:
|
||
match = find_best_match(momo_name, momo_price)
|
||
if not match:
|
||
return base
|
||
pc_price = float(match.get('price', 0))
|
||
diff = pc_price - momo_price
|
||
pct = (diff / momo_price * 100) if momo_price else 0
|
||
base.update({
|
||
'found': True,
|
||
'pc_name': match.get('name', ''),
|
||
'pc_price': pc_price,
|
||
'pc_url': match.get('url', ''),
|
||
'price_diff': diff,
|
||
'price_diff_pct': pct,
|
||
'match_score': match.get('match_score', 0),
|
||
})
|
||
except Exception as e:
|
||
logger.warning("[PChome] compare_product error: %s", e)
|
||
return base
|
||
|
||
|
||
def batch_compare_top(
|
||
db,
|
||
top_n: int = 30,
|
||
date_str: str = '',
|
||
) -> List[dict]:
|
||
"""
|
||
批量比較 momo TOP-N 熱銷商品 vs PChome。
|
||
|
||
Args:
|
||
db: SQLAlchemy engine（由 _db() 回傳）
|
||
top_n: 取 momo 前 N 名熱銷商品
|
||
date_str: 日期字串，格式 'YYYY/MM/DD'；空則取最新日期
|
||
|
||
Returns:
|
||
[compare_product() 結果, ...]
|
||
"""
|
||
results: List[dict] = []
|
||
try:
|
||
from sqlalchemy import text as _text
|
||
|
||
date_filter = ''
|
||
params: dict = {'limit': top_n}
|
||
if date_str:
|
||
date_filter = "WHERE DATE(s.date) = DATE(:date_str)"
|
||
params['date_str'] = date_str.replace('/', '-')
|
||
|
||
sql = f"""
|
||
SELECT p.name, p.i_code,
|
||
COALESCE(SUM(s.revenue), 0) AS total_rev,
|
||
(
|
||
SELECT pr.price
|
||
FROM price_records pr
|
||
WHERE pr.product_id = p.id
|
||
ORDER BY pr.timestamp DESC, pr.id DESC
|
||
LIMIT 1
|
||
) AS momo_price
|
||
FROM products p
|
||
JOIN daily_sales s ON p.id = s.product_id
|
||
{date_filter}
|
||
GROUP BY p.id, p.name, p.i_code
|
||
ORDER BY total_rev DESC
|
||
LIMIT :limit
|
||
"""
|
||
with db.connect() as conn:
|
||
rows = conn.execute(_text(sql), params).fetchall()
|
||
|
||
for row in rows:
|
||
name, icode, rev, momo_price = row[0], row[1], float(row[2] or 0), float(row[3] or 0)
|
||
if momo_price <= 0:
|
||
logger.warning("[PChome] skip %s because latest momo price is missing; total_rev=%s", icode, rev)
|
||
continue
|
||
try:
|
||
cmp = compare_product(name, momo_price, icode)
|
||
results.append(cmp)
|
||
time.sleep(0.4) # 限速
|
||
except Exception as e:
|
||
logger.warning("[PChome] batch item error: %s", e)
|
||
except Exception as e:
|
||
logger.error("[PChome] batch_compare_top error: %s", e)
|
||
return results
|
||
|
||
|
||
def save_matches(db, results: List[dict]) -> None:
|
||
"""
|
||
將比價結果寫入 pchome_matches 表（若不存在則建立）。
|
||
"""
|
||
if not results:
|
||
return
|
||
try:
|
||
from sqlalchemy import text as _text
|
||
ensure_tables(db)
|
||
with db.begin() as conn:
|
||
for r in results:
|
||
if not r.get('found'):
|
||
continue
|
||
conn.execute(_text("""
|
||
INSERT INTO pchome_matches
|
||
(momo_icode, momo_name, momo_price,
|
||
pc_name, pc_price, pc_url,
|
||
price_diff, price_diff_pct, matched_at)
|
||
VALUES
|
||
(:icode, :mname, :mprice,
|
||
:pcname, :pcprice, :pcurl,
|
||
:diff, :pct, NOW())
|
||
ON CONFLICT (momo_icode) DO UPDATE SET
|
||
pc_name = EXCLUDED.pc_name,
|
||
pc_price = EXCLUDED.pc_price,
|
||
pc_url = EXCLUDED.pc_url,
|
||
price_diff = EXCLUDED.price_diff,
|
||
price_diff_pct = EXCLUDED.price_diff_pct,
|
||
matched_at = NOW()
|
||
"""), {
|
||
'icode': r.get('momo_icode', ''),
|
||
'mname': r.get('momo_name', ''),
|
||
'mprice': r.get('momo_price', 0),
|
||
'pcname': r.get('pc_name', ''),
|
||
'pcprice': r.get('pc_price', 0),
|
||
'pcurl': r.get('pc_url', ''),
|
||
'diff': r.get('price_diff', 0),
|
||
'pct': r.get('price_diff_pct', 0),
|
||
})
|
||
except Exception as e:
|
||
logger.warning("[PChome] save_matches error: %s", e)
|
||
|
||
|
||
def ensure_tables(db) -> None:
|
||
"""建立 pchome_matches 表（冪等）"""
|
||
try:
|
||
from sqlalchemy import text as _text
|
||
with db.begin() as conn:
|
||
conn.execute(_text("""
|
||
CREATE TABLE IF NOT EXISTS pchome_matches (
|
||
id SERIAL PRIMARY KEY,
|
||
momo_icode VARCHAR(64) UNIQUE,
|
||
momo_name TEXT,
|
||
momo_price NUMERIC(12,2),
|
||
pc_name TEXT,
|
||
pc_price NUMERIC(12,2),
|
||
pc_url TEXT,
|
||
price_diff NUMERIC(12,2),
|
||
price_diff_pct NUMERIC(8,2),
|
||
matched_at TIMESTAMP DEFAULT NOW()
|
||
)
|
||
"""))
|
||
except Exception as e:
|
||
logger.warning("[PChome] ensure_tables error: %s", e)
|
||
|
||
|
||
def fmt_compare_msg(results: List[dict], keyword: str = '') -> str:
|
||
"""
|
||
格式化單品比價訊息（Telegram Markdown）。
|
||
"""
|
||
if not results:
|
||
return f"⚠️ 找不到「{keyword}」的 PChome 比價資料"
|
||
|
||
lines = [f"🔍 *momo vs PChome 比價｜{keyword}*\n"]
|
||
for r in results[:5]:
|
||
found = r.get('found')
|
||
mname = r.get('momo_name', '')[:28]
|
||
mprice = r.get('momo_price', 0)
|
||
|
||
if not found:
|
||
lines.append(f"• {mname}\n momo `NT${mprice:,.0f}` ／ PChome _未找到_\n")
|
||
continue
|
||
|
||
pcprice = r.get('pc_price', 0)
|
||
diff = r.get('price_diff', 0)
|
||
pct = r.get('price_diff_pct', 0)
|
||
pcurl = r.get('pc_url', '')
|
||
|
||
if diff > 10:
|
||
icon = "✅" # PChome 貴 → momo 有優勢
|
||
note = f"momo 便宜 NT${abs(diff):,.0f}（{abs(pct):.1f}%）"
|
||
elif diff < -10:
|
||
icon = "⚠️" # momo 貴
|
||
note = f"PChome 便宜 NT${abs(diff):,.0f}（{abs(pct):.1f}%）"
|
||
else:
|
||
icon = "➖"
|
||
note = "價差 <NT$10，持平"
|
||
|
||
lines.append(
|
||
f"{icon} *{mname}*\n"
|
||
f" momo `NT${mprice:,.0f}` ／ "
|
||
f"[PChome `NT${pcprice:,.0f}`]({pcurl})\n"
|
||
f" {note}\n"
|
||
)
|
||
|
||
return "\n".join(lines)
|
||
|
||
|
||
def fmt_daily_report(results: List[dict], date_str: str = '') -> str:
|
||
"""
|
||
格式化競品日報訊息（Telegram Markdown）。
|
||
"""
|
||
found = [r for r in results if r.get('found')]
|
||
pc_wins = [r for r in found if r.get('price_diff', 0) > 10] # PChome 貴 → momo優
|
||
mo_wins = [r for r in found if r.get('price_diff', 0) < -10] # momo 貴 → PChome優
|
||
avg_pct = (sum(r.get('price_diff_pct', 0) for r in found) / len(found)
|
||
if found else 0)
|
||
|
||
label = date_str or datetime.now().strftime('%Y/%m/%d')
|
||
lines = [
|
||
f"📊 *競品比價日報｜{label}*\n",
|
||
f"🔢 掃描 `{len(results)}` 件 | 比對成功 `{len(found)}` 件",
|
||
f"✅ momo 具優勢 `{len(pc_wins)}` 件 | ⚠️ 需注意 `{len(mo_wins)}` 件",
|
||
f"📈 平均價差 `{avg_pct:+.1f}%`（正=PChome貴=momo有優勢）\n",
|
||
]
|
||
|
||
if pc_wins:
|
||
lines.append("🏆 *momo 優勢商品（TOP5）*")
|
||
for r in pc_wins[:5]:
|
||
lines.append(
|
||
f" ✅ {r['momo_name'][:20]} "
|
||
f"momo `NT${r['momo_price']:,.0f}` vs PC `NT${r['pc_price']:,.0f}`"
|
||
f" 省 NT${abs(r['price_diff']):,.0f}"
|
||
)
|
||
lines.append("")
|
||
|
||
if mo_wins:
|
||
lines.append("⚠️ *需注意商品（PChome 更便宜 TOP5）*")
|
||
for r in mo_wins[:5]:
|
||
lines.append(
|
||
f" ⚠️ {r['momo_name'][:20]} "
|
||
f"momo `NT${r['momo_price']:,.0f}` vs PC `NT${r['pc_price']:,.0f}`"
|
||
f" 差 NT${abs(r['price_diff']):,.0f}"
|
||
)
|
||
lines.append("")
|
||
|
||
lines.append("_資料來源：PChome 24h 即時爬取_")
|
||
return "\n".join(lines)
|