""" Script Name: Description: 从 javhd.com 上获取女优列表，并逐个获取女优详细信息。 list_fetch.py 从网站上获取列表, 并以json的形式把结果输出到本地文件, 支持ja,zh,en三种语言可选(一般情况下可以三种全部拉取一遍); list_format.py 则把这些文件读取出来，合并，形成完整的列表, 主要是把三种语言的女优名字拼到一起, 使用处理后的链接地址+图片地址作为判断同一个人的依据; model_fetch.py 则把上一步获取到的列表，读取详情页面，合并进来一些详细信息。 注意: Header部分是从浏览器中抓取的, 时间久了可能要替换。 Author: [Your Name] Created Date: YYYY-MM-DD Last Modified: YYYY-MM-DD Version: 1.0 Modification History: - YYYY-MM-DD [Your Name]: - YYYY-MM-DD [Your Name]: - YYYY-MM-DD [Your Name]: """ import json import csv import requests import time import logging import os import re from bs4 import BeautifulSoup # 配置日志 logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s") # 目标文件路径 INPUT_FILE = "result/models.json" OUTPUT_JSON = "result/models_detail.json" OUTPUT_CSV = "result/models_detail.csv" 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,en;q=0.8,en-GB;q=0.7,en-US;q=0.6", 'cookie': 'adult-warning-popup=disabled; st_d=%7B%7D; feid=c18cd2f2cf5c034d120e5975558acc8c; xfeid=3b040b0aecba9d3df41f21732480d947; _ym_uid=1739069925634817268; _ym_d=1739069925; atas_uid=; _clck=1cd9xpy%7C2%7Cftb%7C0%7C1866; _ym_isad=2; nats=ODY0LjIuMi4yNi4yMzQuMC4wLjAuMA; nats_cookie=https%253A%252F%252Fcn.pornhub.com%252F; nats_unique=ODY0LjIuMi4yNi4yMzQuMC4wLjAuMA; nats_sess=480e7410e649efce6003c3add587a579; nats_landing=No%2BLanding%2BPage%2BURL; JAVSESSID=n42hnvj3ecr0r6tadusladpk3h; user_lang=zh; locale=ja; utm=%7B%22ads_type%22%3A%22%22%7D; sid=3679b28ec523df85ec4e7739e32f2008; _ym_visorc=w; feid_sa=62; sid_sa=2' , 'origin': 'https://javhd.com', 'priority': 'u=1, i', 'referer': 'https://javhd.com/ja/model' , 'sec-ch-ua': '"Not A(Brand";v="8", "Chromium";v="132", "Microsoft Edge";v="132"' , 'sec-ch-ua-mobile': '?0' , 'sec-ch-ua-platform': '"macOS"' , 'sec-fetch-dest': 'empty' , 'sec-fetch-mode': 'cors' , 'sec-fetch-site': 'same-origin' , 'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/132.0.0.0 Safari/537.36 Edg/132.0.0.0' , } # 需要提取的字段 FIELDS = ["Height", "Weight", "Breast size", "Breast factor", "Hair color", "Eye color", "Birth date", "Ethnicity", "Birth place"] def fetch_data(url, retries=3): """从给定 URL 获取数据，带重试机制""" for attempt in range(retries): try: response = requests.get(url, headers=HEADERS, timeout=10) response.raise_for_status() return response except requests.exceptions.RequestException as e: print(f"[错误] 请求失败 {url}: {e}, 重试 {attempt + 1}/{retries}") time.sleep(2) return None def process_paragraph(paragraph): # 获取完整的 HTML 结构，而不是 get_text() paragraph_html = str(paragraph) # 使用 BeautifulSoup 解析移除水印标签后的 HTML 并提取文本 soup = BeautifulSoup(paragraph_html, 'html.parser') cleaned_text = soup.get_text().strip() return cleaned_text # 读取已处理数据 def load_existing_data(): if os.path.exists(OUTPUT_JSON): try: with open(OUTPUT_JSON, "r", encoding="utf-8") as f: detailed_models = json.load(f) existing_names = {model["en_name"] for model in detailed_models} except Exception as e: logging.error(f"无法读取 {OUTPUT_JSON}: {e}") detailed_models = [] existing_names = set() else: detailed_models = [] existing_names = set() return detailed_models, existing_names def process_data(): # 读取原始 JSON 数据 try: with open(INPUT_FILE, "r", encoding="utf-8") as f: models = json.load(f) except Exception as e: logging.error(f"无法读取 {INPUT_FILE}: {e}") return detailed_models, existing_names = load_existing_data() # 遍历 models.json 里的每个对象 for model in models: en_name = model.get("en_name", "") ja_name = model.get('ja_name', '') url = model.get("url", "") if not url or en_name in existing_names: logging.info(f"跳过 {en_name}, 已处理或无有效 URL") continue logging.info(f"正在处理: {en_name} - {ja_name} - {url}") try: response = fetch_data(url, retries=100) if not response: logging.warning(f"请求失败 ({response.text}): {url}") break soup = BeautifulSoup(response.text, "html.parser") info_section = soup.find("div", class_="info__features") if not info_section: logging.warning(f"未找到 info__features 区块: {url}") continue extracted_data = {field: "" for field in FIELDS} for li in info_section.find_all("li", class_="content-desc__list-item"): title_tag = li.find("strong", class_="content-desc__list-title") value_tag = li.find("span", class_="content-desc__list-text") if title_tag and value_tag: title = process_paragraph(title_tag) value = process_paragraph(value_tag) if title in extracted_data: extracted_data[title] = value model.update(extracted_data) detailed_models.append(model) # 追加写入 JSON 文件 with open(OUTPUT_JSON, "w+", encoding="utf-8") as f: json.dump(detailed_models, f, ensure_ascii=False, indent=4) logging.info(f"已保存: {en_name}") time.sleep(3) # 适当延迟，防止请求过快 except Exception as e: logging.error(f"处理 {en_name} 失败: {e}") # 从 JSON 生成 CSV def json_to_csv(): if not os.path.exists(OUTPUT_JSON): print("没有 JSON 文件，跳过 CSV 生成") return with open(OUTPUT_JSON, "r", encoding="utf-8") as jsonfile: data = json.load(jsonfile) fieldnames = data[0].keys() with open(OUTPUT_CSV, "w", newline="", encoding="utf-8") as csvfile: writer = csv.DictWriter(csvfile, fieldnames=fieldnames) writer.writeheader() writer.writerows(data) if __name__ == '__main__': process_data() json_to_csv() print("处理完成！")