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- import os
- import concurrent.futures
- import schedule
- import time
- import threading
- from common import Material
- from video_rewriting.video_processor import VideoProcessor
- MAX_BPS = 120 * 1024 * 1024 # 120MB/s
- MAX_WORKERS = os.cpu_count() * 2 # 线程池最大工作线程数量
- READ_WRITE_CHUNK_SIZE = 1024 * 1024 # 每次读写的块大小 (1MB)
- SLEEP_INTERVAL = READ_WRITE_CHUNK_SIZE / MAX_BPS # 控制每次读写的延迟时间
- # 全局锁,用于同步读写操作
- lock = threading.Lock()
- def video_task_start(data):
- mark = VideoProcessor.main(data)
- print(f"返回用户名{mark}")
- # data = Material.feishu_list()
- # video_task_start(data[10])
- def controlled_io_operation(data):
- with lock:
- start_time = time.time()
- time.sleep(SLEEP_INTERVAL)
- end_time = time.time()
- elapsed_time = end_time - start_time
- if elapsed_time < SLEEP_INTERVAL:
- time.sleep(SLEEP_INTERVAL - elapsed_time)
- video_task_start(data)
- def video_start():
- print("开始执行生成视频脚本.")
- data = Material.feishu_list()
- data = data[10]
- with concurrent.futures.ThreadPoolExecutor(max_workers=MAX_WORKERS) as executor:
- futures = {executor.submit(controlled_io_operation, data)}
- for future in concurrent.futures.as_completed(futures):
- try:
- future.result()
- print("处理结果: 成功")
- except concurrent.futures.TimeoutError:
- print("任务超时,已取消.")
- except Exception as e:
- print("处理任务时出现异常:", e)
- print("执行生成视频脚本结束.")
- video_start()
- schedule.every(6).hours.do(video_start)
- # schedule.every(20).minutes.do(video_start)
- while True:
- schedule.run_pending()
- time.sleep(1)
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