### 编写用于内网环境中的批量查询和下载文件的Python脚本 为了实现这一目标，可以利用`requests`库来处理HTTP请求以及多线程或多进程模块加速并发操作。考虑到Windmill框架支持多种编程语言包括Python，并具备测试保存与回放功能[^1]，虽然该工具主要用于Web应用的功能测试，但从其特性可以看出，在编写涉及网络交互的应用程序时，Python拥有强大的生态系统。 下面是一个简单的例子，展示如何创建一个能够连接到指定服务器并尝试获取多个资源链接所指向的内容的脚本： ```python import os from concurrent.futures import ThreadPoolExecutor, as_completed import requests def download_file(url, save_path): try: response = requests.get(url, stream=True) if response.status_code == 200: with open(save_path, 'wb') as file: for chunk in response.iter_content(1024): file.write(chunk) print(f'Successfully downloaded {url}') else: print(f'Failed to retrieve {url}, status code: {response.status_code}') except Exception as e: print(f'Error occurred while downloading {url}:', str(e)) urls_to_download = [ "http://intranet.example.com/file1.pdf", "http://intranet.example.com/report.docx" ] save_directory = "./downloads" if not os.path.exists(save_directory): os.makedirs(save_directory) max_workers = 5 # 可根据实际情况调整最大工作线程数 with ThreadPoolExecutor(max_workers=max_workers) as executor: future_tasks = { executor.submit(download_file, url=url, save_path=os.path.join(save_directory, os.path.basename(url)) ): url for url in urls_to_download} for future in as_completed(future_tasks): url = future_tasks[future] try: _ = future.result() except Exception as exc: print('%r generated an exception: %s' % (url, exc)) print('All downloads completed.') ``` 此代码片段展示了如何通过定义函数`download_file()`来进行单个文件的下载，并使用`ThreadPoolExecutor`管理一组这样的任务以提高效率。注意这里假设所有URL都是有效的并且可以直接访问；实际部署前可能还需要考虑身份验证等问题。