163 lines
5.4 KiB
Python
163 lines
5.4 KiB
Python
"""
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Script Name:
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Description: 从 https://www.iafd.com 上获取信息。利用cloudscraper绕过cloudflare
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detail_fetch.py 从本地已经保存的列表数据,逐个拉取详情,并输出到文件。
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list_fetch_astro.py 按照星座拉取数据,获得演员的信息列表。数据量适中,各详细字段较全
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list_fetch_birth.py 按照生日拉取数据,获得演员的信息列表。数据量适中,各详细字段较全
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list_fetch_ethnic.py 按照人种拉取数据,获得演员的信息列表。数据量大,但详细字段很多无效的
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list_merge.py 上面三个列表的数据,取交集,得到整体数据。
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iafd_scrape.py 借助 https://github.com/stashapp/CommunityScrapers 实现的脚本,可以输入演员的 iafd链接,获取兼容 stashapp 格式的数据。（作用不大,因为国籍、照片等字段不匹配）
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html_format.py 负责读取已经保存的html目录, 提取信息,格式化输出。
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data_merge.py 负责合并数据,它把从 iafd, javhd, thelordofporn 以及搭建 stashapp, 从上面更新到的演员数据(需导出)进行合并；
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stashdb_merge.py 负责把从stashapp中导出的单个演员的json文件, 批量合并并输出; 通常我们需要把stashapp中导出的批量文件压缩并传输到data/tmp目录,解压后合并
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从而获取到一份完整的数据列表。
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Author: [Your Name]
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Created Date: YYYY-MM-DD
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Last Modified: YYYY-MM-DD
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Version: 1.0
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Modification History:
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- YYYY-MM-DD [Your Name]:
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- YYYY-MM-DD [Your Name]:
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- YYYY-MM-DD [Your Name]:
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"""
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import json
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import os
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import subprocess
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import time
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import logging
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from typing import List
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# 设置日志配置
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logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
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logger = logging.getLogger(__name__)
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# 预定义的 scrapers 目录
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scrapers_dir = "/root/gitlabs/stashapp_CommunityScrapers/scrapers"
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meta_file = "./data/iafd_meta.json"
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cursor_file = "./data/iafd_cursor.txt"
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output_dir = f"{scrapers_dir}/iafd_meta"
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# 重试次数和间隔
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MAX_RETRIES = 10
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RETRY_DELAY = 5 # 5秒重试间隔
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# 创建输出目录
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os.makedirs(output_dir, exist_ok=True)
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def read_processed_hrefs() -> set:
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"""
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读取已经处理过的 href
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"""
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processed_hrefs = set()
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if os.path.exists(cursor_file):
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with open(cursor_file, "r", encoding="utf-8") as f:
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processed_hrefs = {line.strip().split(",")[1] for line in f if "," in line}
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return processed_hrefs
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def execute_scraper_command(href: str, idv: str) -> bool:
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"""
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执行命令抓取数据，成功则返回True，否则返回False。
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包含重试机制。
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"""
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command = f"cd {scrapers_dir}; python3 -m IAFD.IAFD performer {href} > {output_dir}/{idv}.json"
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attempt = 0
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while attempt < MAX_RETRIES:
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try:
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logger.info(f"执行命令: {command}")
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subprocess.run(command, shell=True, check=True)
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return True
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except subprocess.CalledProcessError as e:
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logger.error(f"执行命令失败: {e}. 重试 {attempt + 1}/{MAX_RETRIES}...")
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time.sleep(RETRY_DELAY)
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attempt += 1
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logger.error(f"命令执行失败，已尝试 {MAX_RETRIES} 次: {command}")
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return False
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def validate_json_file(idv: str) -> bool:
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"""
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校验 JSON 文件是否有效
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"""
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output_file = f"{output_dir}/{idv}.json"
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try:
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with open(output_file, "r", encoding="utf-8") as f:
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content = f.read().strip()
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json_data = json.loads(content) # 尝试解析 JSON
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if "name" not in json_data:
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raise ValueError("缺少 'name' 字段")
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return True
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except (json.JSONDecodeError, ValueError) as e:
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logger.error(f"解析失败，删除无效文件: {output_file}. 错误: {e}")
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os.remove(output_file)
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return False
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def process_iafd_meta(data: List[dict], processed_hrefs: set) -> None:
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"""
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处理 iafd_meta.json 中的数据
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"""
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for entry in data:
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person = entry.get("person")
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href = entry.get("href")
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if not person or not href:
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logger.warning(f"跳过无效数据: {entry}")
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continue
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# 解析 href 提取 id
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try:
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idv = href.split("id=")[-1]
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except IndexError:
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logger.error(f"无法解析 ID: {href}")
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continue
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output_file = f"{output_dir}/{idv}.json"
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# 跳过已处理的 href
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if href in processed_hrefs:
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logger.info(f"已处理，跳过: {person}, {href}")
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continue
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# 执行数据抓取
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if not execute_scraper_command(href, idv):
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continue
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# 校验 JSON 文件
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if not validate_json_file(idv):
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continue
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# 记录已处理数据
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with open(cursor_file, "a", encoding="utf-8") as f:
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f.write(f"{person},{href}\n")
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logger.info(f"成功处理: {person} - {href}")
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def main():
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"""
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主程序执行函数
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"""
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# 读取已处理的 href
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processed_hrefs = read_processed_hrefs()
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# 读取 iafd_meta.json 数据
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try:
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with open(meta_file, "r", encoding="utf-8") as f:
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data = json.load(f)
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except json.JSONDecodeError as e:
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logger.error(f"读取 iafd_meta.json 错误: {e}")
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return
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# 处理数据
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process_iafd_meta(data, processed_hrefs)
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if __name__ == "__main__":
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main() |