video_rewriting/job_pl_dy_1.py

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[5])


# 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[5]
#     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)
# while True:
#     schedule.run_pending()
#     time.sleep(1)