import requests from bs4 import BeautifulSoup import json import re import pandas as pd # 构建 URL url = "https://mobile.yangkeduo.com/search_result.html" params = { "search_key": "卡奇尔", "search_type": "goods", "source": "index", "options": 1, "search_met_track": "manual", "refer_page_el_sn": 99885, "refer_page_name": "psnl_verification", "refer_page_id": "10390_1719041565192_kvy50ivy6o", "refer_page_sn": 10390 } payload = {} headers = { 'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7', 'accept-language': 'zh-CN,zh;q=0.9', 'cache-control': 'max-age=0', 'cookie': 'api_uid=CiHdtmZ2bOUdZABVWAe/Ag==; _nano_fp=Xpmalp9qnqgylpdJlT_h~uAFy_JoLAWdkdOx0hVt; webp=1; jrpl=RSwIv0e0mE9DfvQqFqfWBr1n5OMeNIQR; njrpl=RSwIv0e0mE9DfvQqFqfWBr1n5OMeNIQR; dilx=bSyz2efIuySKdkq3pYfqD; PDDAccessToken=7JQFYB6SD5FTLTZHX7ECKGBHS3X64WVSHFDD6WNSBRIG6HYMA7UA121b8be; pdd_user_id=6082723443128; pdd_user_uin=X6Q3CK6ATURUPGYQNQFRRKXTA4_GEXDA; pdd_vds=gaLLNOQonbnLInGENOaiEionoNLiNOIotILGmynNOILtGLPQmNPoNmiOoQNo; pdd_vds=gaLLNOQonbnOGQaEGbiIPyiaEatOiELtGtiELILONnIInGmoNPGtmmnINEiP', 'priority': 'u=0, i', 'sec-ch-ua': '"Google Chrome";v="125", "Chromium";v="125", "Not.A/Brand";v="24"', 'sec-ch-ua-mobile': '?0', 'sec-ch-ua-platform': '"macOS"', 'sec-fetch-dest': 'document', 'sec-fetch-mode': 'navigate', 'sec-fetch-site': 'none', 'sec-fetch-user': '?1', 'upgrade-insecure-requests': '1', 'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36' } # 自定义异常类 class ConversionError(Exception): pass def extract_data_from_html(): response = requests.request("GET", url, headers=headers, params=params) # 使用 BeautifulSoup 解析 HTML 结果 soup = BeautifulSoup(response.content, "html.parser") # 找到 body 标签 body_tag = soup.find("body") # 在 body 标签内部找到第一级的 script 标签 first_level_scripts = body_tag.find_all("script", recursive=False) # 遍历第一级的 script 标签,并将其内容转换为 Python 字典 for script_tag in first_level_scripts: script_content = script_tag.string compressed_string = re.sub(r"\n", "", script_content) if compressed_string: # 使用正则表达式提取 window.rawData 赋值语句 match = re.search(r"window\.rawData\s*=\s*(\{.+?\});", compressed_string) if match: raw_data_value = match.group(1) print(raw_data_value) # 尝试使用 json.loads() 将值转换为 Python 字典对象 try: raw_data = json.loads(raw_data_value) except (ValueError, TypeError) as e: # 如果 JSON 解析失败,则使用 eval() 函数尝试解析 raw_data = eval(raw_data_value) print(f"Error converting value : {e}") raise ConversionError(f"Error converting value : {e}") return raw_data return None def write_data_to_excel(data, columns=None): if data: try: list = data['stores']['store']['data']['ssrListData']['list'] searchKey = data['stores']['store']['data']['ssrListData'][ 'searchKey'] except (KeyError, TypeError) as e: print(f"Error parse value : {e}") list = None if list: df = pd.DataFrame(list) # 如果用户指定了列名,则使用指定的列名 if columns: df = df[columns] # 将 DataFrame 写入 Excel 文件 output_file = f"output_{searchKey}.xlsx" df.to_excel(output_file, index=False, engine='xlsxwriter') else: print("No data found in the JSON file.") else: print("No data to write to Excel.") if __name__ == "__main__": try: raw_data = extract_data_from_html() write_data_to_excel( raw_data, columns=['goodsID', 'goodsName', 'goodsName', 'linkURL']) except ConversionError as e: print(e) except Exception as e: print(f"An error occurred: {e}")